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{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nFecal microbiota transplantation ameliorates stress-induced depression-like behaviors associated with the inhibition of glial and NLRP3 inflammasome in rat brain. Evidence from previous studies has demonstrated that the gut-microbiota-brain axis is vital in regulating of behavior and neuroinflammation in the central nervous system. Considering the putative connection among gut microbiota, neural function, and behavior, the present study investigated the potential signaling of gut microbiota to modulate depression-like behaviors and neuroinflammation. Rats showing depression-like behaviors induced by chronic unpredictable mild stress received fecal microbiota treatment or vehicle for 14 days, and alterations in behavior and neuroinflammation were assessed. ELISA, immunofluorescence staining and Western blot were used to analysis the activation of glial cells and NLRP3 inflammasome. Treatment with fecal microbiota transplantation ameliorated depression-like behaviors. 5-Hydroxytryptamine decreased in the chronic unpredictable mild stress rat model but significantly increased after fecal microbiota transplantation. The treatment with fecal microbiota transplantation decreased the production of IL-1β and TNF-α. Moreover, fecal microbiota transplantation administration suppressed the activation of Iba1 positive microglia cells and GFAP positive astrocytes cells and reduced the expression of NLRP3, ASC, Caspase-1, and IL-1β pathway in the prefrontal cortex and hippocampus. Fecal microbiota transplantation can improve depression-like behaviors induced by chronic unpredictable mild stress. The anti-depression effects of fecal microbiota transplantation were associated with the suppressed activation of glial cells and NLRP3 inflammasome in the brain.",
"role": "user"
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{
"content": "Fecal microbiota transplantation ameliorates <DDF>stress-induced depression-like behaviors</DDF> associated with the inhibition of glial and <chemical>NLRP3 inflammasome</chemical> in <anatomical location>rat brain</anatomical location>. Evidence from previous studies has demonstrated that the gut-microbiota-brain axis is vital in regulating of behavior and <DDF>neuroinflammation</DDF> in the central nervous system. Considering the putative connection among <microbiome>gut microbiota</microbiome>, neural function, and behavior, the present study investigated the potential signaling of <microbiome>gut microbiota</microbiome> to modulate <DDF>depression-like behaviors</DDF> and <DDF>neuroinflammation</DDF>. <animal>Rats</animal> showing <DDF>depression-like behaviors</DDF> induced by <DDF>chronic unpredictable mild stress</DDF> received fecal microbiota treatment or vehicle for 14 days, and alterations in behavior and <DDF>neuroinflammation</DDF> were assessed. <biomedical technique>ELISA</biomedical technique>, <biomedical technique>immunofluorescence staining</biomedical technique> and <biomedical technique>Western blot</biomedical technique> were used to analysis the activation of glial cells and <chemical>NLRP3 inflammasome</chemical>. Treatment with fecal microbiota transplantation ameliorated <DDF>depression-like behaviors</DDF>. <chemical>5-Hydroxytryptamine</chemical> decreased in the chronic unpredictable mild stress rat model but significantly increased after fecal microbiota transplantation. The treatment with fecal microbiota transplantation decreased the production of <chemical>IL-1β</chemical> and <chemical>TNF-α</chemical>. Moreover, fecal microbiota transplantation administration suppressed the activation of Iba1 positive microglia cells and GFAP positive astrocytes cells and reduced the expression of <gene>NLRP3</gene>, <chemical>ASC</chemical>, <chemical>Caspase-1</chemical>, and <chemical>IL-1β</chemical> pathway in the <anatomical location>prefrontal cortex</anatomical location> and <anatomical location>hippocampus</anatomical location>. Fecal microbiota transplantation can improve <DDF>depression-like behaviors</DDF> induced by <DDF>chronic unpredictable mild stress</DDF>. The anti-depression effects of fecal microbiota transplantation were associated with the suppressed activation of glial cells and <chemical>NLRP3 inflammasome</chemical> in the <anatomical location>brain</anatomical location>.",
"role": "assistant"
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33692356
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nMeta-analysis of the Parkinson's disease gut microbiome suggests alterations linked to intestinal inflammation. The gut microbiota is emerging as an important modulator of neurodegenerative diseases, and accumulating evidence has linked gut microbes to Parkinson's disease (PD) symptomatology and pathophysiology. PD is often preceded by gastrointestinal symptoms and alterations of the enteric nervous system accompany the disease. Several studies have analyzed the gut microbiome in PD, but a consensus on the features of the PD-specific microbiota is missing. Here, we conduct a meta-analysis re-analyzing the ten currently available 16S microbiome datasets to investigate whether common alterations in the gut microbiota of PD patients exist across cohorts. We found significant alterations in the PD-associated microbiome, which are robust to study-specific technical heterogeneities, although differences in microbiome structure between PD and controls are small. Enrichment of the genera Lactobacillus, Akkermansia, and Bifidobacterium and depletion of bacteria belonging to the Lachnospiraceae family and the Faecalibacterium genus, both important short-chain fatty acids producers, emerged as the most consistent PD gut microbiome alterations. This dysbiosis might result in a pro-inflammatory status which could be linked to the recurrent gastrointestinal symptoms affecting PD patients.",
"role": "user"
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{
"content": "<statistical technique>Meta-analysis of the Parkinson's disease gut microbiome</statistical technique> suggests alterations linked to <DDF>intestinal inflammation</DDF>. The <microbiome>gut microbiota</microbiome> is emerging as an important modulator of <DDF>neurodegenerative diseases</DDF>, and accumulating evidence has linked <microbiome>gut microbes</microbiome> to <DDF>Parkinson's disease (PD) symptomatology and pathophysiology</DDF>. <DDF>PD</DDF> is often preceded by <DDF>gastrointestinal symptoms</DDF> and <DDF>alterations of the enteric nervous system</DDF> accompany the disease. Several studies have analyzed the <microbiome>gut microbiome</microbiome> in <DDF>PD</DDF>, but a consensus on the features of the <microbiome>PD-specific microbiota</microbiome> is missing. Here, we conduct a meta-analysis re-analyzing the ten currently available 16S microbiome datasets to investigate whether common alterations in the <microbiome>gut microbiota</microbiome> of <human>PD patients</human> exist across cohorts. We found significant alterations in the <microbiome>PD-associated microbiome</microbiome>, which are robust to study-specific technical heterogeneities, although differences in microbiome structure between <human>PD and controls</human> are small. Enrichment of the genera <bacteria>Lactobacillus</bacteria>, <bacteria>Akkermansia</bacteria>, and <bacteria>Bifidobacterium</bacteria> and depletion of bacteria belonging to the <bacteria>Lachnospiraceae</bacteria> family and the <bacteria>Faecalibacterium</bacteria> genus, both important <chemical>short-chain fatty acids</chemical> producers, emerged as the most consistent PD gut microbiome alterations. This <DDF>dysbiosis</DDF> might result in a <DDF>pro-inflammatory status</DDF> which could be linked to the <DDF>recurrent gastrointestinal symptoms</DDF> affecting <human>PD patients</human>.",
"role": "assistant"
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33693453
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nDiet and the Microbiota-Gut-Brain Axis: Sowing the Seeds of Good Mental Health. Over the past decade, the gut microbiota has emerged as a key component in regulating brain processes and behavior. Diet is one of the major factors involved in shaping the gut microbiota composition across the lifespan. However, whether and how diet can affect the brain via its effects on the microbiota is only now beginning to receive attention. Several mechanisms for gut-to-brain communication have been identified, including microbial metabolites, immune, neuronal, and metabolic pathways, some of which could be prone to dietary modulation. Animal studies investigating the potential of nutritional interventions on the microbiota-gut-brain axis have led to advancements in our understanding of the role of diet in this bidirectional communication. In this review, we summarize the current state of the literature triangulating diet, microbiota, and host behavior/brain processes and discuss potential underlying mechanisms. Additionally, determinants of the responsiveness to a dietary intervention and evidence for the microbiota as an underlying modulator of the effect of diet on brain health are outlined. In particular, we emphasize the understudied use of whole-dietary approaches in this endeavor and the need for greater evidence from clinical populations. While promising results are reported, additional data, specifically from clinical cohorts, are required to provide evidence-based recommendations for the development of microbiota-targeted, whole-dietary strategies to improve brain and mental health.",
"role": "user"
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{
"content": "Diet and the Microbiota-Gut-Brain Axis: Sowing the Seeds of Good Mental Health. Over the past decade, the <microbiome>gut microbiota</microbiome> has emerged as a key component in regulating brain processes and behavior. Diet is one of the major factors involved in shaping the gut microbiota composition across the lifespan. However, whether and how diet can affect the <anatomical location>brain</anatomical location> via its effects on the microbiota is only now beginning to receive attention. Several mechanisms for gut-to-brain communication have been identified, including <chemical>microbial metabolites</chemical>, immune, neuronal, and metabolic pathways, some of which could be prone to dietary modulation. Animal studies investigating the potential of nutritional interventions on the microbiota-gut-brain axis have led to advancements in our understanding of the role of diet in this bidirectional communication. In this review, we summarize the current state of the literature triangulating diet, microbiota, and host behavior/brain processes and discuss potential underlying mechanisms. Additionally, determinants of the responsiveness to a dietary intervention and evidence for the microbiota as an underlying modulator of the effect of diet on brain health are outlined. In particular, we emphasize the understudied use of whole-dietary approaches in this endeavor and the need for greater evidence from <human>clinical populations</human>. While promising results are reported, additional data, specifically from <statistical technique>clinical cohorts</statistical technique>, are required to provide evidence-based recommendations for the development of microbiota-targeted, whole-dietary strategies to improve brain and mental health.",
"role": "assistant"
}
] |
33782648
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nPreventing and Treating Neurological Disorders with the Flavonol Fisetin. Neurological disorders, including neurodegenerative diseases, have a significant negative impact on both patients and society at large. Since the prevalence of most of these disorders increases with age, the consequences for our aging population are only going to grow. It is now acknowledged that neurological disorders are multi-factorial involving disruptions in multiple cellular systems. While each disorder has specific initiating mechanisms and pathologies, certain common pathways appear to be involved in most, if not all, neurological disorders. Thus, it is becoming increasingly important to identify compounds that can modulate the multiple pathways that contribute to disease development or progression. One of these compounds is the flavonol fisetin. Fisetin has now been shown in preclinical models to be effective at preventing the development and/or progression of multiple neurological disorders including Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, stroke (both ischemic and hemorrhagic) and traumatic brain injury as well as to reduce age-associated changes in the brain. These beneficial effects stem from its actions on multiple pathways associated with the different neurological disorders. These actions include its well characterized anti-inflammatory and anti-oxidant effects as well as more recently described effects on the regulated cell death oxytosis/ferroptosis pathway, the gut microbiome and its senolytic activity. Therefore, the growing body of pre-clinical data, along with fisetin's ability to modulate a large number of pathways associated with brain dysfunction, strongly suggest that it would be worthwhile to pursue its therapeutic effects in humans.",
"role": "user"
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{
"content": "Preventing and Treating <DDF>Neurological Disorders</DDF> with the <chemical>Flavonol Fisetin</chemical>. <DDF>Neurological disorders</DDF>, including <DDF>neurodegenerative diseases</DDF>, have a significant negative impact on both <human>patients</human> and society at large. Since the prevalence of most of these disorders increases with age, the consequences for our <human>aging population</human> are only going to grow. It is now acknowledged that <DDF>neurological disorders</DDF> are multi-factorial involving <DDF>disruptions in multiple cellular systems</DDF>. While each disorder has specific initiating mechanisms and pathologies, certain common pathways appear to be involved in most, if not all, <DDF>neurological disorders</DDF>. Thus, it is becoming increasingly important to identify compounds that can modulate the multiple pathways that contribute to disease development or progression. One of these compounds is the <chemical>flavonol fisetin</chemical>. <chemical>Fisetin</chemical> has now been shown in preclinical models to be effective at preventing the development and/or progression of multiple <DDF>neurological disorders</DDF> including <DDF>Alzheimer's disease</DDF>, <DDF>Parkinson's disease</DDF>, <DDF>Huntington's disease</DDF>, <DDF>amyotrophic lateral sclerosis</DDF>, <DDF>stroke (both ischemic and hemorrhagic)</DDF> and <DDF>traumatic brain injury</DDF> as well as to reduce age-associated changes in the <anatomical location>brain</anatomical location>. These beneficial effects stem from its actions on multiple pathways associated with the different <DDF>neurological disorders</DDF>. These actions include its well characterized anti-inflammatory and anti-oxidant effects as well as more recently described effects on the regulated cell death oxytosis/ferroptosis pathway, the <microbiome>gut microbiome</microbiome> and its senolytic activity. Therefore, the growing body of pre-clinical data, along with fisetin's ability to modulate a large number of pathways associated with <DDF>brain dysfunction</DDF>, strongly suggest that it would be worthwhile to pursue its therapeutic effects in <human>humans</human>.",
"role": "assistant"
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] |
33807447
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nChanges in Gut Microbiota after a Four-Week Intervention with Vegan vs. Meat-Rich Diets in Healthy Participants: A Randomized Controlled Trial. An essential role of the gut microbiota in health and disease is strongly suggested by recent research. The composition of the gut microbiota is modified by multiple internal and external factors, such as diet. A vegan diet is known to show beneficial health effects, yet the role of the gut microbiota is unclear. Within a 4-week, monocentric, randomized, controlled trial with a parallel group design (vegan (VD) vs. meat-rich (MD)) with 53 healthy, omnivore, normal-weight participants (62% female, mean 31 years of age), fecal samples were collected at the beginning and at the end of the trial and were analyzed using 16S rRNA gene amplicon sequencing (Clinical Trial register: DRKS00011963). Alpha diversity as well as beta diversity did not differ significantly between MD and VD. Plotting of baseline and end samples emphasized a highly intra-individual microbial composition. Overall, the gut microbiota was not remarkably altered between VD and MD after the trial. <i>Coprococcus</i> was found to be increased in VD while being decreased in MD. <i>Roseburia</i> and <i>Faecalibacterium</i> were increased in MD while being decreased in VD. Importantly, changes in genera <i>Coprococcus, Roseburia</i> and <i>Faecalibacterium</i> should be subjected to intense investigation as markers for physical and mental health.",
"role": "user"
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{
"content": "Changes in <microbiome>Gut Microbiota</microbiome> after a Four-Week Intervention with <food>Vegan vs. Meat-Rich Diets</food> in <human>Healthy Participants</human>: A Randomized Controlled Trial. An essential role of the <microbiome>gut microbiota</microbiome> in health and <DDF>disease</DDF> is strongly suggested by recent research. The composition of the <microbiome>gut microbiota</microbiome> is modified by multiple internal and external factors, such as diet. A <food>vegan diet</food> is known to show beneficial health effects, yet the role of the <microbiome>gut microbiota</microbiome> is unclear. Within a 4-week, monocentric, randomized, controlled trial with a parallel group design (<food>vegan (VD)</food> vs. <food>meat-rich (MD)</food>) with 53 <human>healthy, omnivore, normal-weight participants</human> (62% female, mean 31 years of age), fecal samples were collected at the beginning and at the end of the trial and were analyzed using <biomedical technique>16S rRNA gene amplicon sequencing</biomedical technique> (Clinical Trial register: DRKS00011963). Alpha diversity as well as beta diversity did not differ significantly between MD and VD. Plotting of baseline and end samples emphasized a highly intra-individual microbial composition. Overall, the <microbiome>gut microbiota</microbiome> was not remarkably altered between <food>VD</food> and <food>MD</food> after the trial. <i><bacteria>Coprococcus</bacteria></i> was found to be increased in <food>VD</food> while being decreased in <food>MD</food>. <i><bacteria>Roseburia</bacteria></i> and <i><bacteria>Faecalibacterium</bacteria></i> were increased in <food>MD</food> while being decreased in <food>VD</food>. Importantly, changes in genera <i><bacteria>Coprococcus</bacteria>, <bacteria>Roseburia</bacteria></i> and <i><bacteria>Faecalibacterium</bacteria></i> should be subjected to intense investigation as markers for physical and mental health.",
"role": "assistant"
}
] |
33819374
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nTrimethylamine modulates dauer formation, neurodegeneration, and lifespan through tyra-3/daf-11 signaling in Caenorhabditis elegans. In the nematode Caenorhabditis elegans, signals derived from bacteria in the diet, the animal's major nutrient source, can modulate both behavior and healthspan. Here we describe a dual role for trimethylamine (TMA), a human gut flora metabolite, which acts as a nutrient signal and a neurotoxin. TMA and its associated metabolites are produced by the human gut microbiome and have been suggested to serve as risk biomarkers for diabetes and cardiovascular diseases. We demonstrate that the tyramine receptor TYRA-3, a conserved G protein-coupled receptor (GPCR), is required to sense TMA and mediate its responses. TMA activates guanylyl cyclase DAF-11 signaling through TYRA-3 in amphid neurons (ASK) and ciliated neurons (BAG) to mediate food-sensing behavior. Bacterial mutants deficient in TMA production enhance dauer formation, extend lifespan, and are less preferred as a food source. Increased levels of TMA lead to neural damage in models of Parkinson's disease and shorten lifespan. Our results reveal conserved signaling pathways modulated by TMA in C. elegans that are likely to be relevant for its effects in mammalian systems.",
"role": "user"
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{
"content": "<chemical>Trimethylamine</chemical> modulates <DDF>dauer formation</DDF>, <DDF>neurodegeneration</DDF>, and lifespan through <gene>tyra-3/daf-11</gene> signaling in <animal>Caenorhabditis elegans</animal>. In the <animal>nematode Caenorhabditis elegans</animal>, signals derived from bacteria in the diet, the animal's major nutrient source, can modulate both behavior and healthspan. Here we describe a dual role for <chemical>trimethylamine</chemical> (<chemical>TMA</chemical>), a human gut flora metabolite, which acts as a nutrient signal and a neurotoxin. <chemical>TMA</chemical> and its associated metabolites are produced by the <microbiome>human gut microbiome</microbiome> and have been suggested to serve as risk biomarkers for <DDF>diabetes</DDF> and <DDF>cardiovascular diseases</DDF>. We demonstrate that the <gene>tyramine receptor TYRA-3</gene>, a conserved <chemical>G protein-coupled receptor</chemical> (<chemical>GPCR</chemical>), is required to sense <chemical>TMA</chemical> and mediate its responses. <chemical>TMA</chemical> activates <gene>guanylyl cyclase DAF-11</gene> signaling through <gene>TYRA-3</gene> in amphid neurons (ASK) and ciliated neurons (BAG) to mediate food-sensing behavior. <animal>Bacterial mutants</animal> deficient in <chemical>TMA</chemical> production enhance dauer formation, extend lifespan, and are less preferred as a food source. Increased levels of <chemical>TMA</chemical> lead to <DDF>neural damage</DDF> in models of <DDF>Parkinson's disease</DDF> and shorten lifespan. Our results reveal conserved signaling pathways modulated by <chemical>TMA</chemical> in <animal>C. elegans</animal> that are likely to be relevant for its effects in mammalian systems.",
"role": "assistant"
}
] |
33825149
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGut Microbial Metabolites in Parkinson's Disease: Implications of Mitochondrial Dysfunction in the Pathogenesis and Treatment. The search for therapeutic targets for Parkinson's disease (PD) is hindered by the incomplete understanding of the pathophysiology of the disease. Mitochondrial dysfunction is an area with high potential. The neurobiological signaling connections between the gut microbiome and the central nervous system are incompletely understood. Multiple lines of evidence suggest that the gut microbiota participates in the pathogenesis of PD. Gut microbial dysbiosis may contribute to the loss of dopaminergic neurons through mitochondrial dysfunction. The intervention of gut microbial metabolites via the microbiota-gut-brain axis may serve as a promising therapeutic strategy for PD. In this narrative review, we summarize the potential roles of gut microbial dysbiosis in PD, with emphasis on microbial metabolites and mitochondrial function. We then review the possible ways in which microbial metabolites affect the central nervous system, as well as the impact of microbial metabolites on mitochondrial dysfunction. We finally discuss the possibility of gut microbiota as a therapeutic target for PD.",
"role": "user"
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{
"content": "<chemical>Gut Microbial Metabolites</chemical> in <DDF>Parkinson's Disease</DDF>: Implications of <DDF>Mitochondrial Dysfunction</DDF> in the Pathogenesis and Treatment. The search for therapeutic targets for <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>) is hindered by the incomplete understanding of the pathophysiology of the disease. <DDF>Mitochondrial dysfunction</DDF> is an area with high potential. The neurobiological signaling connections between the <microbiome>gut microbiome</microbiome> and the central nervous system are incompletely understood. Multiple lines of evidence suggest that the <microbiome>gut microbiota</microbiome> participates in the pathogenesis of <DDF>PD</DDF>. <DDF>Gut microbial dysbiosis</DDF> may contribute to the loss of dopaminergic neurons through <DDF>mitochondrial dysfunction</DDF>. The intervention of <chemical>gut microbial metabolites</chemical> via the microbiota-gut-brain axis may serve as a promising therapeutic strategy for <DDF>PD</DDF>. In this narrative review, we summarize the potential roles of <DDF>gut microbial dysbiosis</DDF> in <DDF>PD</DDF>, with emphasis on <chemical>microbial metabolites</chemical> and mitochondrial function. We then review the possible ways in which <chemical>microbial metabolites</chemical> affect the central nervous system, as well as the impact of <chemical>microbial metabolites</chemical> on <DDF>mitochondrial dysfunction</DDF>. We finally discuss the possibility of <microbiome>gut microbiota</microbiome> as a therapeutic target for <DDF>PD</DDF>.",
"role": "assistant"
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] |
33860090
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nProbiotics for Parkinson's disease: Current evidence and future directions. The gut-brain axis is a hot topic in Parkinson's disease (PD). It has been postulated that gut pathogens and dysbiosis can contribute to peripheral inflammatory states or trigger downstream metabolic effects that exacerbate the neurodegenerative process in PD. Several preclinical and clinical studies have demonstrated disrupted intestinal permeability, intestinal inflammation, altered gut microbiome, and reduced fecal short-chain fatty acids in PD. In this regard, microbial-directed therapies such as probiotics are emerging as potential therapeutic options. Probiotic supplementation is postulated to confer a variety of health benefits due to the diverse functions of these live microorganisms, including inhibition of pathogen colonization, modulation/\"normalization\" of the microbiome and/or its function, immunomodulatory effects (e.g. reducing inflammation), and improved host epithelial barrier function. Interestingly, several PD animal model studies have demonstrated the potential neuroprotective effects of probiotics in reducing dopaminergic neuronal degeneration. Notably, two randomized placebo-controlled trials have provided class I evidence for probiotics as a treatment for constipation in PD. However, the effects of probiotics on other PD aspects, such as motor disability and cognitive function, and its long-term efficacy (including effects on PD drug absorption in the gut) have not been investigated adequately. Further targeted animal and human studies are also warranted to understand the mechanisms of actions of probiotics in PD and to tailor probiotic therapy based on individual host profiles to improve patient outcomes in this disabling disorder.",
"role": "user"
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{
"content": "<dietary supplement>Probiotics</dietary supplement> for <DDF>Parkinson's disease</DDF>: Current evidence and future directions. The gut-brain axis is a hot topic in <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>). It has been postulated that gut pathogens and <DDF>dysbiosis</DDF> can contribute to <DDF>peripheral inflammatory states</DDF> or trigger downstream metabolic effects that exacerbate the neurodegenerative process in <DDF>PD</DDF>. Several preclinical and clinical studies have demonstrated disrupted intestinal permeability, <DDF>intestinal inflammation</DDF>, altered <microbiome>gut microbiome</microbiome>, and reduced <chemical>fecal short-chain fatty acids</chemical> in <DDF>PD</DDF>. In this regard, microbial-directed therapies such as <dietary supplement>probiotics</dietary supplement> are emerging as potential therapeutic options. <dietary supplement>Probiotic supplementation</dietary supplement> is postulated to confer a variety of health benefits due to the diverse functions of these live microorganisms, including inhibition of pathogen colonization, modulation/\"normalization\" of the microbiome and/or its function, immunomodulatory effects (e.g. reducing <DDF>inflammation</DDF>), and improved host epithelial barrier function. Interestingly, several PD animal model studies have demonstrated the potential neuroprotective effects of <dietary supplement>probiotics</dietary supplement> in reducing <DDF>dopaminergic neuronal degeneration</DDF>. Notably, two randomized placebo-controlled trials have provided class I evidence for <dietary supplement>probiotics</dietary supplement> as a treatment for <DDF>constipation</DDF> in <DDF>PD</DDF>. However, the effects of <dietary supplement>probiotics</dietary supplement> on other PD aspects, such as <DDF>motor disability</DDF> and cognitive function, and its long-term efficacy (including effects on PD drug absorption in the <anatomical location>gut</anatomical location>) have not been investigated adequately. Further targeted animal and human studies are also warranted to understand the mechanisms of actions of <dietary supplement>probiotics</dietary supplement> in <DDF>PD</DDF> and to tailor <dietary supplement>probiotic therapy</dietary supplement> based on individual host profiles to improve patient outcomes in this disabling disorder.",
"role": "assistant"
}
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33895287
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nManipulations of the gut microbiome alter chemotherapy-induced inflammation and behavioral side effects in female mice. Chemotherapy treatment is associated with acute behavioral side effects (fatigue, anorexia) that significantly reduce patient quality of life and are dose-limiting, thereby increasing mortality (Kidwell et al., 2014). Disruptions to gut homeostasis (diarrhea, constipation, microbial dysbiosis) are also observed in patients receiving chemotherapy. In non-oncological patients, facets of mental health (fatigue, anxiety, depression) correlate with alterations in the gut microbiome, suggestive of a contribution of the gut in CNS disease etiology. The potential gut-to-brain pathway is poorly understood in patients receiving chemotherapy. Our prior studies have demonstrated a correlation between chemotherapy treatment, gut changes, peripheral and central inflammation, and behavioral symptoms in mice. Here we aimed to determine the extent to which chemotherapy-associated gut manipulations modulate the behavioral and biological consequences of chemotherapy. We measured sickness behaviors, peripheral and central inflammatory mediators, and anxiety in conventional or germ-free female mice: 1) cohabitating with mice of the opposite treatment group, 2) pre-treated with broad-spectrum antibiotics, or 3) given an intra-gastric gavage of gut content from chemotherapy-treated mice. In cohabitation studies, presumed coprophagia promoted body mass recovery, however strong associations with inflammation and behavior were not observed. Reduction of gut microbial alpha diversity via antibiotics did not prevent chemotherapy-associated side effects, however the relative abundances of the genera Tyzzerella, Romboutsia, and Turicibacter correlated with circulating inflammatory (IL-1β) and behavioral outcomes (lethargy, anxiety-like behavior). A gut microbiota transplant from chemotherapy-treated mice decreased central locomotion in open field testing, increased circulating CXCL1, and increased hippocampal Il6 and Tnfa in germ-free mice compared to germ-free mice that received a transplant from vehicle-treated mice. Taken together, these data provide further evidence that the gut microbiota likely contributes to the development of chemotherapy-associated side effects. This work has significant implications in the future treatment of anxiety in patients, and warrants future studies using microbe-based treatment options.",
"role": "user"
},
{
"content": "Manipulations of the <microbiome>gut microbiome</microbiome> alter <DDF>chemotherapy-induced inflammation</DDF> and <DDF>behavioral side effects</DDF> in <animal>female mice</animal>. Chemotherapy treatment is associated with <DDF>acute behavioral side effects</DDF> (<DDF>fatigue</DDF>, <DDF>anorexia</DDF>) that significantly reduce patient quality of life and are dose-limiting, thereby increasing mortality (Kidwell et al., 2014). Disruptions to gut homeostasis (<DDF>diarrhea</DDF>, <DDF>constipation</DDF>, <DDF>microbial dysbiosis</DDF>) are also observed in <human>patients</human> receiving chemotherapy. In <human>non-oncological patients</human>, facets of mental health (<DDF>fatigue</DDF>, <DDF>anxiety</DDF>, <DDF>depression</DDF>) correlate with alterations in the <microbiome>gut microbiome</microbiome>, suggestive of a contribution of the <anatomical location>gut</anatomical location> in CNS disease etiology. The potential gut-to-brain pathway is poorly understood in <human>patients</human> receiving chemotherapy. Our prior studies have demonstrated a correlation between chemotherapy treatment, gut changes, <DDF>peripheral and central inflammation</DDF>, and behavioral symptoms in <animal>mice</animal>. Here we aimed to determine the extent to which chemotherapy-associated gut manipulations modulate the behavioral and biological consequences of chemotherapy. We measured <DDF>sickness behaviors</DDF>, <DDF>peripheral and central inflammatory mediators</DDF>, and <DDF>anxiety</DDF> in <animal>conventional or germ-free female mice</animal>: 1) cohabitating with <animal>mice</animal> of the opposite treatment group, 2) pre-treated with <drug>broad-spectrum antibiotics</drug>, or 3) given an <biomedical technique>intra-gastric gavage</biomedical technique> of gut content from <animal>chemotherapy-treated mice</animal>. In cohabitation studies, presumed <DDF>coprophagia</DDF> promoted body mass recovery, however strong associations with <DDF>inflammation</DDF> and behavior were not observed. Reduction of gut microbial alpha diversity via <drug>antibiotics</drug> did not prevent chemotherapy-associated side effects, however the relative abundances of the genera <bacteria>Tyzzerella</bacteria>, <bacteria>Romboutsia</bacteria>, and <bacteria>Turicibacter</bacteria> correlated with circulating inflammatory (<chemical>IL-1β</chemical>) and behavioral outcomes (<DDF>lethargy</DDF>, <DDF>anxiety-like behavior</DDF>). A <microbiome>gut microbiota</microbiome> transplant from <animal>chemotherapy-treated mice</animal> decreased central locomotion in <biomedical technique>open field testing</biomedical technique>, increased <chemical>circulating CXCL1</chemical>, and increased <chemical>hippocampal Il6 and Tnfa</chemical> in <animal>germ-free mice</animal> compared to <animal>germ-free mice</animal> that received a transplant from <animal>vehicle-treated mice</animal>. Taken together, these data provide further evidence that the <microbiome>gut microbiota</microbiome> likely contributes to the development of <DDF>chemotherapy-associated side effects</DDF>. This work has significant implications in the future treatment of <DDF>anxiety</DDF> in <human>patients</human>, and warrants future studies using microbe-based treatment options.",
"role": "assistant"
}
] |
33899052
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGut Microbiome Changes with Osteopathic Treatment of Constipation in Parkinson's Disease: A Pilot Study. The gut microbiome appears to be predictive of Parkinson's disease (PD) with constipation. Chronic constipation frequently manifests prior to motor symptoms and impairs quality of life. An osteopathic manipulative medicine (OMM) sequence used physical exam assessment and manual treatment of neuromusculoskeletal dysfunctions pertinent to constipation in PD for this prospective ABA-design study, IRB-NYITBHS1065. The effects of 4 weekly treatments on the gut microbiome among men and women over 40 years old with chronic constipation and PD were investigated. Severity of PD was rated with the Movement Disorders Society-Unified PD rating scale (UPDRS) in six subjects with constipation. Also, the Bristol stool scale and questionnaires validated for constipation were administered for diagnosis, symptom severity, and quality of life during a 4-week control-period (A), 4-weekly OMM-treatments (B), and 2-weeks no-intervention (A). Biweekly stool samples were assessed for normalized microbiota abundance. The mean Bristol rating improved from type 2 (± 1) Pre-OMM to 3 (± 1; p = .167; d = 0.677) Post-OMM. Mean constipation severity significantly decreased (p = .010; d = 1.508) Post-OMM. Mean quality of life significantly improved (p = .041; d = 1.072) Post-OMM. The Pre-OMM mean number of families within the phylum Firmicutes decreased by 3 (p = .043; d = 1.177) Post-OMM. There were significant changes in the normalized abundance of phyla Actinobacteria (p = .040; d = 0.845) and Verrucomicrobia (p = .024; d = 0.675) as well as in genus Roseburia (p = .033; d = 1.109), Intestinimonas (p = .035; d = 0.627) and Anaerotruncus (p = .004) Post-OMM. The gut microbiome shifted among individuals with constipation and PD after four weekly treatments with the OMM-sequence. Changes in the gut microbiome Post-OMM were associated with UPDRS results and constipation measures. Clinical trials and studies to develop the gut microbiome into a validated biomarker for PD are necessary to understand the impact of OMM in patients with PD and constipation.",
"role": "user"
},
{
"content": "Gut Microbiome Changes with Osteopathic Treatment of Constipation in <DDF>Parkinson's Disease</DDF>: A Pilot Study. The <microbiome>gut microbiome</microbiome> appears to be predictive of <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>) with <DDF>constipation</DDF>. <DDF>Chronic constipation</DDF> frequently manifests prior to <DDF>motor symptoms</DDF> and impairs quality of life. An <biomedical technique>osteopathic manipulative medicine (OMM) sequence</biomedical technique> used <biomedical technique>physical exam assessment</biomedical technique> and manual treatment of neuromusculoskeletal dysfunctions pertinent to <DDF>constipation</DDF> in <DDF>PD</DDF> for this prospective ABA-design study, IRB-NYITBHS1065. The effects of 4 weekly treatments on the <microbiome>gut microbiome</microbiome> among <human>men and women over 40 years old</human> with <DDF>chronic constipation</DDF> and <DDF>PD</DDF> were investigated. Severity of <DDF>PD</DDF> was rated with the Movement Disorders Society-Unified PD rating scale (UPDRS) in six <human>subjects</human> with <DDF>constipation</DDF>. Also, the Bristol stool scale and questionnaires validated for <DDF>constipation</DDF> were administered for diagnosis, symptom severity, and quality of life during a 4-week control-period (A), 4-weekly OMM-treatments (B), and 2-weeks no-intervention (A). Biweekly stool samples were assessed for normalized microbiota abundance. The mean Bristol rating improved from type 2 (± 1) Pre-OMM to 3 (± 1; p = .167; d = 0.677) Post-OMM. Mean constipation severity significantly decreased (p = .010; d = 1.508) Post-OMM. Mean quality of life significantly improved (p = .041; d = 1.072) Post-OMM. The Pre-OMM mean number of families within the <bacteria>phylum Firmicutes</bacteria> decreased by 3 (p = .043; d = 1.177) Post-OMM. There were significant changes in the normalized abundance of <bacteria>phyla Actinobacteria</bacteria> (p = .040; d = 0.845) and <bacteria>Verrucomicrobia</bacteria> (p = .024; d = 0.675) as well as in <bacteria>genus Roseburia</bacteria> (p = .033; d = 1.109), <bacteria>Intestinimonas</bacteria> (p = .035; d = 0.627) and <bacteria>Anaerotruncus</bacteria> (p = .004) Post-OMM. The <microbiome>gut microbiome</microbiome> shifted among <human>individuals</human> with <DDF>constipation</DDF> and <DDF>PD</DDF> after four weekly treatments with the <biomedical technique>OMM-sequence</biomedical technique>. Changes in the <microbiome>gut microbiome Post-OMM</microbiome> were associated with UPDRS results and constipation measures. Clinical trials and studies to develop the <microbiome>gut microbiome</microbiome> into a validated biomarker for <DDF>PD</DDF> are necessary to understand the impact of OMM in <human>patients</human> with <DDF>PD</DDF> and <DDF>constipation</DDF>.",
"role": "assistant"
}
] |
33936013
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGABA Production by Human Intestinal <i>Bacteroides</i> spp.: Prevalence, Regulation, and Role in Acid Stress Tolerance. The high neuroactive potential of metabolites produced by gut microbes has gained traction over the last few years, with metagenomic-based studies suggesting an important role of microbiota-derived γ-aminobutyric acid (GABA) in modulating mental health. Emerging evidence has revealed the presence of the glutamate decarboxylase (GAD)-encoding gene, a key enzyme to produce GABA, in the prominent human intestinal genus <i>Bacteroides</i>. Here, we investigated GABA production by <i>Bacteroides</i> in culture and metabolic assays combined with comparative genomics and phylogenetics. A total of 961 <i>Bacteroides</i> genomes were analyzed <i>in silico</i> and 17 metabolically and genetically diverse human intestinal isolates representing 11 species were screened <i>in vitro</i>. Using the model organism <i>Bacteroides thetaiotaomicron</i> DSM 2079, we determined GABA production kinetics, its impact on milieu pH, and we assessed its role in mitigating acid-induced cellular damage. We showed that the GAD-system consists of at least four highly conserved genes encoding a GAD, a glutaminase, a glutamate/GABA antiporter, and a potassium channel. We demonstrated a high prevalence of the GAD-system among <i>Bacteroides</i> with 90% of all <i>Bacteroides</i> genomes (96% in human gut isolates only) harboring all genes of the GAD-system and 16 intestinal <i>Bacteroides</i> strains producing GABA <i>in vitro</i> (ranging from 0.09 to 60.84 mM). We identified glutamate and glutamine as precursors of GABA production, showed that the production is regulated by pH, and that the GAD-system acts as a protective mechanism against acid stress in <i>Bacteroides</i>, mitigating cell death and preserving metabolic activity. Our data also indicate that the GAD-system might represent the only amino acid-dependent acid tolerance system in <i>Bacteroides</i>. Altogether, our results suggest an important contribution of <i>Bacteroides</i> in the regulation of the GABAergic system in the human gut.",
"role": "user"
},
{
"content": "GABA Production by <bacteria>Human Intestinal <i>Bacteroides</i> spp.</bacteria>: Prevalence, Regulation, and Role in <DDF>Acid Stress Tolerance</DDF>. The high neuroactive potential of metabolites produced by gut microbes has gained traction over the last few years, with metagenomic-based studies suggesting an important role of <chemical>microbiota-derived γ-aminobutyric acid</chemical> (<chemical>GABA</chemical>) in modulating mental health. Emerging evidence has revealed the presence of the <gene>glutamate decarboxylase (GAD)-encoding gene</gene>, a key enzyme to produce <chemical>GABA</chemical>, in the prominent <bacteria>human intestinal genus <i>Bacteroides</i></bacteria>. Here, we investigated <chemical>GABA</chemical> production by <i><bacteria>Bacteroides</bacteria></i> in culture and metabolic assays combined with <biomedical technique>comparative genomics</biomedical technique> and <biomedical technique>phylogenetics</biomedical technique>. A total of 961 <i><bacteria>Bacteroides</bacteria></i> genomes were analyzed <i>in silico</i> and 17 metabolically and genetically diverse human intestinal isolates representing 11 species were screened <i>in vitro</i>. Using the model organism <<bacteria>i>Bacteroides thetaiotaomicron</i> DSM 2079</bacteria>, we determined GABA production kinetics, its impact on milieu pH, and we assessed its role in mitigating <DDF>acid-induced cellular damage</DDF>. We showed that the GAD-system consists of at least four highly conserved genes encoding a <chemical>GAD</chemical>, a <chemical>glutaminase</chemical>, a <chemical>glutamate/GABA antiporter</chemical>, and a potassium channel. We demonstrated a high prevalence of the GAD-system among <i><bacteria>Bacteroides</bacteria></i> with 90% of all <i><bacteria>Bacteroides</bacteria></i> genomes (96% in <anatomical location>human gut</anatomical location> isolates only) harboring all genes of the GAD-system and 16 <bacteria>intestinal <i>Bacteroides</i></bacteria> strains producing <chemical>GABA</chemical> <i>in vitro</i> (ranging from 0.09 to 60.84 mM). We identified <chemical>glutamate</chemical> and <chemical>glutamine</chemical> as precursors of GABA production, showed that the production is regulated by pH, and that the GAD-system acts as a protective mechanism against <DDF>acid stress</DDF> in <i><bacteria>Bacteroides</bacteria></i>, mitigating cell death and preserving metabolic activity. Our data also indicate that the GAD-system might represent the only amino acid-dependent acid tolerance system in <i><bacteria>Bacteroides</bacteria></i>. Altogether, our results suggest an important contribution of <i><bacteria>Bacteroides</bacteria></i> in the regulation of the GABAergic system in the <anatomical location>human gut</anatomical location>.",
"role": "assistant"
}
] |
33938181
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nHuman glucose-dependent insulinotropic polypeptide (GIP) is an antimicrobial adjuvant re-sensitising multidrug-resistant Gram-negative bacteria. Increasing antibiotic resistance in Gram-negative bacteria has mandated the development of both novel antibiotics and alternative therapeutic strategies. Evidence of interplay between several gastrointestinal peptides and the gut microbiota led us to investigate potential and broad-spectrum roles for the incretin hormone, human glucose-dependent insulinotropic polypeptide (GIP) against the <i>Enterobacteriaceae</i> bacteria, <i>Escherichia coli</i> and <i>Erwinia amylovora</i>. GIP had a potent disruptive action on drug efflux pumps of the multidrug resistant bacteria <i>E. coli TG1</i> and <i>E. amylovora 1189</i> strains. The effect was comparable to bacterial mutants lacking the inner and outer membrane efflux pump factor proteins AcrB and TolC. While GIP was devoid of direct antimicrobial activity, it has a potent membrane depolarizing effect, and at low concentrations, it significantly potentiated the activity of eight antibiotics and bile salt by reducing MICs by 4-8-fold in <i>E. coli TG1</i> and 4-20-fold in <i>E. amylovora 1189</i>. GIP can thus be regarded as an antimicrobial adjuvant with potential for augmenting the available antibiotic arsenal.",
"role": "user"
},
{
"content": "<chemical>Human glucose-dependent insulinotropic polypeptide</chemical> (<chemical>GIP</chemical>) is an <bacteria>antimicrobial adjuvant re-sensitising multidrug-resistant Gram-negative bacteria</bacteria>. <DDF>Increasing antibiotic resistance</DDF> in <bacteria>Gram-negative bacteria</bacteria> has mandated the development of both <drug>novel antibiotics</drug> and alternative therapeutic strategies. Evidence of interplay between several <chemical>gastrointestinal peptides</chemical> and the <microbiome>gut microbiota</microbiome> led us to investigate potential and broad-spectrum roles for the <chemical>incretin hormone</chemical>, <chemical>human glucose-dependent insulinotropic polypeptide</chemical> (<chemical>GIP</chemical>) against the <bacteria><i>Enterobacteriaceae</i> bacteria</bacteria>, <i><bacteria>Escherichia coli</bacteria></i> and <i><bacteria>Erwinia amylovora</bacteria></i>. <chemical>GIP</chemical> had a potent disruptive action on drug efflux pumps of the <bacteria>multidrug resistant bacteria</bacteria> <i><bacteria>E. coli TG1</bacteria></i> and <i><bacteria>E. amylovora 1189</bacteria></i> strains. The effect was comparable to <bacteria>bacterial mutants</bacteria> lacking the <chemical>inner and outer membrane efflux pump factor proteins</chemical> <chemical>AcrB</chemical> and <chemical>TolC</chemical>. While <chemical>GIP</chemical> was devoid of direct antimicrobial activity, it has a potent membrane depolarizing effect, and at low concentrations, it significantly potentiated the activity of eight <drug>antibiotics</drug> and <chemical>bile salt</chemical> by reducing <gene>MICs</gene> by 4-8-fold in <i><bacteria>E. coli TG1</bacteria></i> and 4-20-fold in <i><bacteria>E. amylovora 1189</bacteria></i>. <chemical>GIP</chemical> can thus be regarded as an antimicrobial adjuvant with potential for augmenting the available antibiotic arsenal.",
"role": "assistant"
}
] |
33963284
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nMolecular mechanisms underlying the antidepressant actions of arketamine: beyond the NMDA receptor. The discovery of robust antidepressant actions exerted by the N-methyl-D-aspartate receptor (NMDAR) antagonist (R,S)-ketamine has been a crucial breakthrough in mood disorder research. (R,S)-ketamine is a racemic mixture of equal amounts of (R)-ketamine (arketamine) and (S)-ketamine (esketamine). In 2019, an esketamine nasal spray from Johnson & Johnson was approved in the United States of America and Europe for treatment-resistant depression. However, an increasing number of preclinical studies show that arketamine has greater potency and longer-lasting antidepressant-like effects than esketamine in rodents, despite the lower binding affinity of arketamine for the NMDAR. In clinical trials, non-ketamine NMDAR-related compounds did not exhibit ketamine-like robust antidepressant actions in patients with depression, despite these compounds showing antidepressant-like effects in rodents. Thus, the rodent data do not necessarily translate to humans due to the complexity of human psychiatric disorders. Collectively, the available studies indicate that it is unlikely that NMDAR plays a major role in the antidepressant action of (R,S)-ketamine and its enantiomers, although the precise molecular mechanisms underlying antidepressant actions of (R,S)-ketamine and its enantiomers remain unclear. In this paper, we review recent findings on the molecular mechanisms underlying the antidepressant actions of (R,S)-ketamine and its potent enantiomer arketamine. Furthermore, we discuss the possible role of the brain-gut-microbiota axis and brain-spleen axis in stress-related psychiatric disorders and in the antidepressant-like action of arketamine. Finally, we discuss the potential of arketamine as a treatment for cognitive impairment in psychiatric disorders, Parkinson's disease, osteoporosis, inflammatory bowel diseases, and stroke.",
"role": "user"
},
{
"content": "Molecular mechanisms underlying the antidepressant actions of <drug>arketamine</drug>: beyond the <chemical>NMDA receptor</chemical>. The discovery of robust antidepressant actions exerted by the <chemical>N-methyl-D-aspartate receptor</chemical> (<chemical>NMDAR</chemical>) antagonist <drug>(R,S)-ketamine</drug> has been a crucial breakthrough in mood disorder research. <drug>(R,S)-ketamine</drug> is a racemic mixture of equal amounts of <drug>(R)-ketamine</drug> (<drug>arketamine</drug>) and <drug>(S)-ketamine</drug> (<drug>esketamine</drug>). In 2019, an <drug>esketamine</drug> nasal spray from Johnson & Johnson was approved in the United States of America and Europe for <DDF>treatment-resistant depression</DDF>. However, an increasing number of preclinical studies show that <drug>arketamine</drug> has greater potency and longer-lasting antidepressant-like effects than <drug>esketamine</drug> in <animal>rodents</animal>, despite the lower binding affinity of <drug>arketamine</drug> for the <chemical>NMDAR</chemical>. In clinical trials, <chemical>non-ketamine NMDAR-related compounds</chemical> did not exhibit ketamine-like robust antidepressant actions in <human>patients</human> with <DDF>depression</DDF>, despite these compounds showing antidepressant-like effects in <animal>rodents</animal>. Thus, the rodent data do not necessarily translate to <human>humans</human> due to the complexity of <DDF>human psychiatric disorders</DDF>. Collectively, the available studies indicate that it is unlikely that <chemical>NMDAR</chemical> plays a major role in the antidepressant action of <drug>(R,S)-ketamine</drug> and its enantiomers, although the precise molecular mechanisms underlying antidepressant actions of <drug>(R,S)-ketamine</drug> and its enantiomers remain unclear. In this paper, we review recent findings on the molecular mechanisms underlying the antidepressant actions of <drug>(R,S)-ketamine</drug> and its potent enantiomer <drug>arketamine</drug>. Furthermore, we discuss the possible role of the brain-gut-microbiota axis and brain-spleen axis in <DDF>stress-related psychiatric disorders</DDF> and in the antidepressant-like action of <drug>arketamine</drug>. Finally, we discuss the potential of <drug>arketamine</drug> as a treatment for <DDF>cognitive impairment</DDF> in <DDF>psychiatric disorders</DDF>, <DDF>Parkinson's disease</DDF>, <DDF>osteoporosis</DDF>, <DDF>inflammatory bowel diseases</DDF>, and <DDF>stroke</DDF>.",
"role": "assistant"
}
] |
33967849
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nEffectiveness of Probiotic, Prebiotic, and Synbiotic Supplementation to Improve Perinatal Mental Health in Mothers: A Systematic Review and Meta-Analysis. <b>Introduction:</b> There is an emerging interest in modulating the gut microbiota to target the gut-brain axis and improve maternal mental health in the perinatal period. This systematic review evaluated the effectiveness of prebiotics, probiotics, and synbiotics supplementation during pregnancy to reduce the risk of maternal mental health problems in the perinatal period. <b>Methods:</b> Electronic biomedical databases and clinical trial registries were searched from database inception through August 2020 to identify randomized controlled clinical trials (RCTs) evaluating the effect of probiotic, prebiotic, or synbiotic supplements administered to women during pregnancy on measures of perinatal depression, anxiety, and other mental health outcomes. Study selection, risk of bias appraisal, and data extraction were independently performed by two reviewers. Pooled mean differences (MD) and odds ratios (pOR) with 95% confidence intervals (CI) were calculated in random-effects meta-analyses for the outcomes of interest in the review. <b>Results:</b> From 3,868 studies identified through the search strategy, three RCTs of low risk of bias involving 713 participants were included, all three testing probiotics. There were no differences between probiotics and control groups in the mean depression scores (MD -0.46; 95% CI -2.16, 1.25) at end of follow-up. Although statistical significance was not achieved, probiotics showed an advantage in the proportion of participants scoring below an established cut-off for depression (pOR 0.68; 95% CI 0.43, 1.07). Compared to placebo, probiotics in pregnancy reduced anxiety symptoms (MD -0.99; 95% CI -1.80, -0.18); however, this advantage was not translated in a reduction in the proportion of participants scoring above an established cut-off for anxiety (pOR 0.65; 95% CI 0.23, 1.85). There were no differences between probiotics and control groups in global mental health scores at end of follow-up (MD 1.09; 95% CI -2.04, 4.22). <b>Conclusion:</b> There is limited but promising evidence about the effectiveness of probiotics during pregnancy to reduce anxiety symptoms and reduce the proportion of women scoring ABOVE a cut-off depression score. There is a lack of RCT evidence supporting prebiotics and synbiotics supplementation for similar purposes in the perinatal period. More research is needed before prebiotics, probiotics, and synbiotics are recommended to support maternal mental health and well-being in the perinatal period. <b>Systematic Review Registration:</b> PROSPERO, CRD42019137158.",
"role": "user"
},
{
"content": "Effectiveness of <dietary supplement>Probiotic</dietary supplement>, <dietary supplement>Prebiotic</dietary supplement>, and <dietary supplement>Synbiotic Supplementation</dietary supplement> to Improve <DDF>Perinatal Mental Health</DDF> in <human>Mothers</human>: A Systematic Review and Meta-Analysis. <b>Introduction:</b> There is an emerging interest in modulating the <microbiome>gut microbiota</microbiome> to target the gut-brain axis and improve maternal mental health in the perinatal period. This systematic review evaluated the effectiveness of <dietary supplement>prebiotics</dietary supplement>, <dietary supplement>probiotics</dietary supplement>, and <dietary supplement>synbiotics supplementation</dietary supplement> during pregnancy to reduce the risk of <DDF>maternal mental health problems</DDF> in the perinatal period. <b>Methods:</b> Electronic biomedical databases and clinical trial registries were searched from database inception through August 2020 to identify randomized controlled clinical trials (RCTs) evaluating the effect of <dietary supplement>probiotic</dietary supplement>, <dietary supplement>prebiotic</dietary supplement>, or <dietary supplement>synbiotic supplements</dietary supplement> administered to <human>women</human> during pregnancy on measures of <DDF>perinatal depression</DDF>, <DDF>anxiety</DDF>, and other mental health outcomes. Study selection, risk of bias appraisal, and data extraction were independently performed by two reviewers. <statistical technique>Pooled mean differences</statistical technique> (<statistical technique>MD</statistical technique>) and <statistical technique>odds ratios</statistical technique> (pOR) with <statistical technique>95% confidence intervals</statistical technique> (CI) were calculated in <statistical technique>random-effects meta-analyses</statistical technique> for the outcomes of interest in the review. <b>Results:</b> From 3,868 studies identified through the search strategy, three RCTs of low risk of bias involving 713 <human>participants</human> were included, all three testing <dietary supplement>probiotics</dietary supplement>. There were no differences between <dietary supplement>probiotics</dietary supplement> and <human>control groups</human> in the mean depression scores (MD -0.46; 95% CI -2.16, 1.25) at end of follow-up. Although statistical significance was not achieved, <dietary supplement>probiotics</dietary supplement> showed an advantage in the proportion of participants scoring below an established cut-off for <DDF>depression</DDF> (pOR 0.68; 95% CI 0.43, 1.07). Compared to <drug>placebo</drug>, <dietary supplement>probiotics</dietary supplement> in pregnancy reduced <DDF>anxiety symptoms</DDF> (MD -0.99; 95% CI -1.80, -0.18); however, this advantage was not translated in a reduction in the proportion of participants scoring above an established cut-off for <DDF>anxiety</DDF> (pOR 0.65; 95% CI 0.23, 1.85). There were no differences between <dietary supplement>probiotics</dietary supplement> and <human>control groups</human> in global mental health scores at end of follow-up (MD 1.09; 95% CI -2.04, 4.22). <b>Conclusion:</b> There is limited but promising evidence about the effectiveness of probiotics during pregnancy to reduce anxiety symptoms and reduce the proportion of women scoring ABOVE a cut-off depression score. There is a lack of RCT evidence supporting prebiotics and synbiotics supplementation for similar purposes in the perinatal period. More research is needed before prebiotics, probiotics, and synbiotics are recommended to support maternal mental health and well-being in the perinatal period. <b>Systematic Review Registration:</b> PROSPERO, CRD42019137158.",
"role": "assistant"
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34002020
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nEndocannabinoid system mediates the association between gut-microbial diversity and anhedonia/amotivation in a general population cohort. Anhedonia and amotivation are debilitating symptoms and represent unmet therapeutic needs in a range of clinical conditions. The gut-microbiome-endocannabinoid axis might represent a potential modifiable target for interventions. Based on results obtained from animal models, we tested the hypothesis that the endocannabinoid system mediates the association between gut-microbiome diversity and anhedonia/amotivation in a general population cohort. We used longitudinal data collected from 786 volunteer twins recruited as part the TwinsUK register. Our hypothesis was tested with a multilevel mediation model using family structure as random intercept. The model was set using alpha diversity (within-individual gut-microbial diversity) as predictor, serum and faecal levels of the endocannabinoid palmitoylethanolamide (PEA) as mediator, and anhedonia/amotivation as outcome. PEA is considered the endogenous equivalent of cannabidiol, with increased serum levels believed to have anti-depressive effects, while increased stool PEA levels, reflecting increased excretion, are believed to have opposite, detrimental, effects on mental health. We therefore expected that either reduced serum PEA or increased stool PEA would mediate the association between microbial diversity and anhedonia amotivation. Analyses were adjusted for obesity, diet, antidepressant use, sociodemographic and technical covariates. Data were imputed using multiple imputation by chained equations. Mean age was 65.2 ± 7.6; 93% of the sample were females. We found a direct, significant, association between alpha diversity and anhedonia/amotivation (β = -0.37; 95%CI: -0.71 to -0.03; P = 0.03). Faecal, but not serum, levels of the endocannabinoid palmitoylethanolamide (PEA) mediated this association: the indirect effect was significant (β = -0.13; 95%CI: -0.24 to -0.01; P = 0.03), as was the total effect (β = -0.38; 95%CI: -0.72 to -0.04; P = 0.03), whereas the direct effect of alpha diversity on anhedonia/amotivation was attenuated fully (β = -0.25; 95%CI: -0.60 to 0.09; P = 0.16). Our results suggest that gut-microbial diversity might contribute to anhedonia/amotivation via the endocannabinoid system. These findings shed light on the biological underpinnings of anhedonia/amotivation and suggest the gut microbiota-endocannabinoid axis as a promising therapeutic target in an area of unmet clinical need.",
"role": "user"
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{
"content": "Endocannabinoid system mediates the association between gut-microbial diversity and <DDF>anhedonia/amotivation</DDF> in a general population cohort. <DDF>Anhedonia</DDF> and <DDF>amotivation</DDF> are debilitating symptoms and represent unmet therapeutic needs in a range of clinical conditions. The gut-microbiome-endocannabinoid axis might represent a potential modifiable target for interventions. Based on results obtained from animal models, we tested the hypothesis that the endocannabinoid system mediates the association between gut-microbiome diversity and <DDF>anhedonia/amotivation</DDF> in a general population cohort. We used longitudinal data collected from 786 <human>volunteer twins</human> recruited as part the TwinsUK register. Our hypothesis was tested with a <statistical technique>multilevel mediation model</statistical technique> using family structure as random intercept. The model was set using alpha diversity (within-individual gut-microbial diversity) as predictor, serum and faecal levels of the <chemical>endocannabinoid palmitoylethanolamide</chemical> (<chemical>PEA</chemical>) as mediator, and <DDF>anhedonia/amotivation</DDF> as outcome. <chemical>PEA</chemical> is considered the endogenous equivalent of <chemical>cannabidiol</chemical>, with increased serum levels believed to have anti-depressive effects, while increased stool PEA levels, reflecting increased excretion, are believed to have opposite, detrimental, effects on mental health. We therefore expected that either reduced serum PEA or increased stool PEA would mediate the association between microbial diversity and <DDF>anhedonia amotivation</DDF>. Analyses were adjusted for <DDF>obesity</DDF>, diet, antidepressant use, sociodemographic and technical covariates. Data were imputed using <statistical technique>multiple imputation by chained equations</statistical technique>. Mean age was 65.2 ± 7.6; 93% of the sample were <human>females</human>. We found a direct, significant, association between alpha diversity and <DDF>anhedonia/amotivation</DDF> (β = -0.37; 95%CI: -0.71 to -0.03; P = 0.03). Faecal, but not serum, levels of the <chemical>endocannabinoid palmitoylethanolamide</chemical> (<chemical>PEA</chemical>) mediated this association: the indirect effect was significant (β = -0.13; 95%CI: -0.24 to -0.01; P = 0.03), as was the total effect (β = -0.38; 95%CI: -0.72 to -0.04; P = 0.03), whereas the direct effect of alpha diversity on <DDF>anhedonia/amotivation</DDF> was attenuated fully (β = -0.25; 95%CI: -0.60 to 0.09; P = 0.16). Our results suggest that gut-microbial diversity might contribute to anhedonia/amotivation via the endocannabinoid system. These findings shed light on the biological underpinnings of anhedonia/amotivation and suggest the gut microbiota-endocannabinoid axis as a promising therapeutic target in an area of unmet clinical need.",
"role": "assistant"
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34004259
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nAbnormalities in the composition of the gut microbiota in mice after repeated administration of DREADD ligands. Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) are known as genetically modified G-protein-coupled receptors (GPCRs), which can be activated by synthetic ligands such as clozapine N-oxide (CNO) and DREADD agonist 21 (compound 21: C21). The brain-gut-microbiota axis has a crucial role in bidirectional interactions between the brain and the gastrointestinal microbiota. In this study, we investigated whether repeated administration of CNO or C21 could influence the gut microbiota and short-chain fatty acids (SCFAs) in feces of adult mice. Repeated administration of CNO or C21 as drinking water did not alter the α- and β-diversity of gut microbiota in mice compared with control mice. However, we found significant changes in relative abundance for several bacteria in the CNO (or C21) group at the taxonomic level compared to the control group. The linear discriminant analysis effect size (LEfSe) algorithm distinguished the family Prevotellaceae, the genus Anaerocolumna, the genus Prevotella, and the genus Frisingicoccus, these four specific microbial markers for the CNO group relative to the control group. In addition, the LEfSe algorithm identified the family Clostridiaceae, the genus Faecalicatena and the genus Marinisporobacter, these three bacteria of different taxonomic as potential microbial markers for the C21 group relative to the control group. In contrast, repeated administration of CNO (or C21) did not alter SCFAs in feces samples of adult mice. The data suggest that repeated administration of CNO or C21 contributes to an unusual organization of the gut microbiota in adult mice. Therefore, abnormalities in the composition of gut microbiota by repeated dosing of DREADD ligands should be taken into consideration for behavioral and biological functions in rodents treated with DREADD ligands.",
"role": "user"
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"content": "Abnormalities in the composition of the <microbiome>gut microbiota</microbiome> in <animal>mice</animal> after repeated administration of <drug>DREADD ligands</drug>. <chemical>Designer Receptors Exclusively Activated by Designer Drugs</chemical> (<chemical>DREADDs</chemical>) are known as genetically modified <chemical>G-protein-coupled receptors</chemical> (<chemical>GPCRs</chemical>), which can be activated by <chemical>synthetic ligands</chemical> such as <chemical>clozapine N-oxide</chemical> (<chemical>CNO</chemical>) and <chemical>DREADD agonist 21</chemical> (<chemical>compound 21: C21</chemical>). The brain-gut-microbiota axis has a crucial role in bidirectional interactions between the <anatomical location>brain</anatomical location> and the <microbiome>gastrointestinal microbiota</microbiome>. In this study, we investigated whether repeated administration of <chemical>CNO</chemical> or <chemical>C21</chemical> could influence the <microbiome>gut microbiota</microbiome> and <chemical>short-chain fatty acids</chemical> (<chemical>SCFAs</chemical>) in feces of <animal>adult mice</animal>. Repeated administration of <chemical>CNO</chemical> or <chemical>C21</chemical> as drinking water did not alter the α- and β-diversity of <microbiome>gut microbiota</microbiome> in <animal>mice</animal> compared with <animal>control mice</animal>. However, we found significant changes in relative abundance for several bacteria in the CNO (or C21) group at the taxonomic level compared to the control group. The <statistical technique>linear discriminant analysis effect size (LEfSe) algorithm</statistical technique> distinguished the family <bacteria>Prevotellaceae</bacteria>, the <bacteria>genus Anaerocolumna</bacteria>, the <bacteria>genus Prevotella</bacteria>, and the <bacteria>genus Frisingicoccus</bacteria>, these four specific microbial markers for the CNO group relative to the control group. In addition, the <statistical technique>LEfSe</statistical technique> algorithm identified the family <bacteria>Clostridiaceae</bacteria>, the <bacteria>genus Faecalicatena</bacteria> and the <bacteria>genus Marinisporobacter</bacteria>, these three bacteria of different taxonomic as potential microbial markers for the C21 group relative to the control group. In contrast, repeated administration of <chemical>CNO</chemical> (or <chemical>C21</chemical>) did not alter <chemical>SCFAs</chemical> in feces samples of <animal>adult mice</animal>. The data suggest that repeated administration of <chemical>CNO</chemical> or <chemical>C21</chemical> contributes to an unusual organization of the <microbiome>gut microbiota</microbiome> in <animal>adult mice</animal>. Therefore, abnormalities in the composition of <microbiome>gut microbiota</microbiome> by repeated dosing of <drug>DREADD ligands</drug> should be taken into consideration for behavioral and biological functions in <animal>rodents</animal> treated with <drug>DREADD ligands</drug>.",
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34014031
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nImpaired blood-brain barrier in the microbiota-gut-brain axis: Potential role of bipolar susceptibility gene TRANK1. Bipolar disorder (BD) is a common psychiatric illness with high prevalence and disease burden. Accumulating susceptibility genes for BD have been identified in recent years. However, the exact functions of these genes remain largely unknown. Despite its high heritability, gene and environment interaction is commonly accepted as the major contributing factor to BD pathogenesis. Intestine microbiota is increasingly recognized as a critical environmental factor for human health and diseases via the microbiota-gut-brain axis. BD individuals showed altered diversity and compositions in the commensal microbiota. In addition to pro-inflammatory factors, such as interleukin-6 and tumour necrosis factor-α, type 1 interferon signalling pathway is also modulated by specific intestinal bacterial strains. Disruption of the microbiota-gut-brain axis contributes to peripheral and central nervous system inflammation, which accounts for the BD aetiology. Administration of type 1 interferon can induce the expression of TRANK1, which is associated with elevated circulating biomarkers of the impaired blood-brain barrier in BD patients. In this review, we focus on the influence of intestine microbiota on the expression of bipolar gene TRANK1 and propose that intestine microbiota-dependent type 1 interferon signalling is sufficient to induce the over-expression of TRANK1, consequently causing the compromise of BBB integrity and facilitating the entrance of inflammatory mediators into the brain. Activated neuroinflammation eventually contributes to the occurrence and development of BD. This review provides a new perspective on how gut microbiota participate in the pathogenesis of BD. Future studies are needed to validate these assumptions and develop new treatment targets for BD.",
"role": "user"
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"content": "Impaired blood-brain barrier in the microbiota-gut-brain axis: Potential role of <gene>bipolar susceptibility gene TRANK1</gene>. <DDF>Bipolar disorder</DDF> (<DDF>BD</DDF>) is a common <DDF>psychiatric illness</DDF> with high prevalence and disease burden. Accumulating susceptibility genes for <DDF>BD</DDF> have been identified in recent years. However, the exact functions of these genes remain largely unknown. Despite its high heritability, gene and environment interaction is commonly accepted as the major contributing factor to <DDF>BD</DDF> pathogenesis. <microbiome>Intestine microbiota</microbiome> is increasingly recognized as a critical environmental factor for human health and diseases via the microbiota-gut-brain axis. <human>BD individuals</human> showed altered diversity and compositions in the <microbiome>commensal microbiota</microbiome>. In addition to pro-inflammatory factors, such as <chemical>interleukin-6</chemical> and <chemical>tumour necrosis factor-α</chemical>, type 1 interferon signalling pathway is also modulated by specific intestinal bacterial strains. Disruption of the microbiota-gut-brain axis contributes to <DDF>peripheral and central nervous system inflammation</DDF>, which accounts for the BD aetiology. Administration of <chemical>type 1 interferon</chemical> can induce the expression of <gene>TRANK1</gene>, which is associated with elevated circulating biomarkers of the impaired blood-brain barrier in <human>BD patients</human>. In this review, we focus on the influence of <microbiome>intestine microbiota</microbiome> on the expression of <gene>bipolar gene TRANK1</gene> and propose that intestine microbiota-dependent type 1 interferon signalling is sufficient to induce the over-expression of <gene>TRANK1</gene>, consequently causing the compromise of BBB integrity and facilitating the entrance of inflammatory mediators into the <anatomical location>brain</anatomical location>. <DDF>Activated neuroinflammation</DDF> eventually contributes to the occurrence and development of <DDF>BD</DDF>. This review provides a new perspective on how <microbiome>gut microbiota</microbiome> participate in the pathogenesis of <DDF>BD</DDF>. Future studies are needed to validate these assumptions and develop new treatment targets for <DDF>BD</DDF>.",
"role": "assistant"
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34032650
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nPsychobiotics: Evolution of Novel Antidepressants. The gut-brain axis is a bidirectional communication system which allows the central nervous system and gastrointestinal tract to interact with and respond to each other rapidly and effectively. It is becoming increasingly clear that major players in this complex system are gut bacteria. The mechanisms of signal transmission from bacteria to the brain are complex and not fully elucidated, but include neural, endocrine, immune, and metabolic pathways. It was initially demonstrated in a rodent model of depression that the gut microbiota was altered. This observation has been replicated in patients with major depression who show decreased microbial diversity. Furthermore, when rodents receive a microbiota transplant from a depressed patient their behaviour alters, as does their tryptophan metabolism and immune status. Several studies of psychobiotics (bacteria with a potential mental health benefit) have been conducted in healthy populations and in patients with depression. While some psychobiotics have shown efficacy in treating depression, other bacteria have yielded negative findings. Larger-scale, well-designed studies are required. EU-funded guidelines recommend that patients with depression or vulnerability to depression should be encouraged to enhance a plant-based diet with a high content of grains/fibres, fermented foods, and fish. A significant impact of such a diet is likely mediated through the gut microbiota.",
"role": "user"
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{
"content": "<bacteria>Psychobiotics</bacteria>: Evolution of Novel <drug>Antidepressants</drug>. The gut-brain axis is a bidirectional communication system which allows the central nervous system and <anatomical location>gastrointestinal tract</anatomical location> to interact with and respond to each other rapidly and effectively. It is becoming increasingly clear that major players in this complex system are <bacteria>gut bacteria</bacteria>. The mechanisms of signal transmission from bacteria to the <anatomical location>brain</anatomical location> are complex and not fully elucidated, but include neural, endocrine, immune, and metabolic pathways. It was initially demonstrated in a rodent model of <DDF>depression</DDF> that the <microbiome>gut microbiota</microbiome> was altered. This observation has been replicated in <human>patients</human> with <DDF>major depression</DDF> who show decreased microbial diversity. Furthermore, when <animal>rodents</animal> receive a microbiota transplant from a <human>depressed patient</human> their behaviour alters, as does their tryptophan metabolism and immune status. Several studies of <bacteria>psychobiotics</bacteria> (bacteria with a potential mental health benefit) have been conducted in <human>healthy populations</human> and in <human>patients</human> with <DDF>depression</DDF>. While some <bacteria>psychobiotics</bacteria> have shown efficacy in treating <DDF>depression</DDF>, other bacteria have yielded negative findings. Larger-scale, well-designed studies are required. EU-funded guidelines recommend that <human>patients</human> with <DDF>depression</DDF> or vulnerability to <DDF>depression</DDF> should be encouraged to enhance a plant-based diet with a high content of <food>grains</food>/<food>fibres</food>, <food>fermented foods</food>, and <food>fish</food>. A significant impact of such a diet is likely mediated through the <microbiome>gut microbiota</microbiome>.",
"role": "assistant"
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34074025
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nMAIT Cells and Microbiota in Multiple Sclerosis and Other Autoimmune Diseases. The functions of mucosal-associated invariant T (MAIT) cells in homeostatic conditions include the interaction with the microbiota and its products, the protection of body barriers, and the mounting of a tissue-repair response to injuries or infections. Dysfunction of MAIT cells and dysbiosis occur in common chronic diseases of inflammatory, metabolic, and tumor nature. This review is aimed at analyzing the changes of MAIT cells, as well as of the microbiota, in multiple sclerosis and other autoimmune disorders. Common features of dysbiosis in these conditions are the reduced richness of microbial species and the unbalance between pro-inflammatory and immune regulatory components of the gut microbiota. The literature concerning MAIT cells in these disorders is rather complex, and sometimes not consistent. In multiple sclerosis and other autoimmune conditions, several studies have been done, or are in progress, to find correlations between intestinal permeability, dysbiosis, MAIT cell responses, and clinical biomarkers in treated and treatment-naïve patients. The final aims are to explain what activates MAIT cells in diseases not primarily infective, which interactions with the microbiota are potentially pathogenic, and their dynamics related to disease course and disease-modifying treatments.",
"role": "user"
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{
"content": "MAIT Cells and Microbiota in <DDF>Multiple Sclerosis</DDF> and Other <DDF>Autoimmune Diseases</DDF>. The functions of mucosal-associated invariant T (MAIT) cells in homeostatic conditions include the interaction with the microbiota and its products, the protection of body barriers, and the mounting of a tissue-repair response to injuries or <DDF>infections</DDF>. <DDF>Dysfunction of MAIT cells</DDF> and <DDF>dysbiosis</DDF> occur in common <DDF>chronic diseases</DDF> of inflammatory, metabolic, and tumor nature. This review is aimed at analyzing the changes of MAIT cells, as well as of the microbiota, in <DDF>multiple sclerosis</DDF> and other <DDF>autoimmune disorders</DDF>. Common features of <DDF>dysbiosis</DDF> in these conditions are the reduced richness of microbial species and the unbalance between pro-inflammatory and immune regulatory components of the <microbiome>gut microbiota</microbiome>. The literature concerning MAIT cells in these disorders is rather complex, and sometimes not consistent. In <DDF>multiple sclerosis</DDF> and other autoimmune conditions, several studies have been done, or are in progress, to find correlations between intestinal permeability, <DDF>dysbiosis</DDF>, MAIT cell responses, and clinical biomarkers in <human>treated and treatment-naïve patients</human>. The final aims are to explain what activates MAIT cells in diseases not primarily infective, which interactions with the microbiota are potentially pathogenic, and their dynamics related to disease course and disease-modifying treatments.",
"role": "assistant"
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34147969
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nIngestion of Faecalibaculum rodentium causes depression-like phenotypes in resilient Ephx2 knock-out mice: A role of brain-gut-microbiota axis via the subdiaphragmatic vagus nerve. The brain-gut-microbiota axis plays a crucial role in the bidirectional interactions between the brain and the gut. Soluble epoxide hydrolase (coded by the Ephx2 gene) plays an important role in inflammation, which has been implicated in stress-related depression. Ephx2 knock-out (KO) mice exposed to chronic social defeat stress (CSDS) did not show depression-like behaviors, indicating stress resilience. Here we examined whether the brain-gut-microbiota axis influences the resilience in Ephx2 KO mice. Effects of fecal microbiota transplantation (FMT) from CSDS-susceptible (or control) mice in wild-type (WT) mice and Ephx2 KO mice treated with an antibiotic cocktail (ABX) were investigated. Behavioral, biochemical tests and 16S ribosome RNA analysis were performed. FMT from CSDS-susceptible mice produced anhedonia-like behavior in ABX-treated WT and Ephx2 KO mice. The 16S ribosome RNA analysis showed that Faecalibaculum rodentium (F. rodentium) may be responsible for the observed anhedonia-like behavior following FMT from CSDS-susceptible mice. Ingestion of F. rodentium for 14 days produced depression- and anhedonia-like behaviors, higher blood levels of interleukin-6, and reduced expression of synaptic proteins in the prefrontal cortex of ABX-treated Ephx2 KO mice. Furthermore, subdiaphragmatic vagotomy blocked the development of these behavioral abnormalities after ingestion of F. rodentium. Detailed mechanisms are unclear. These findings suggest that F. rodentium might contribute to the conversion of resilient Ephx2 KO mice into KO mice with depression-like phenotypes. The brain-gut-microbiota axis via the subdiaphragmatic vagus nerve plays a crucial role in susceptibility and resilience to stress.",
"role": "user"
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{
"content": "Ingestion of <bacteria>Faecalibaculum rodentium</bacteria> causes depression-like phenotypes in <animal>resilient Ephx2 knock-out mice</animal>: A role of brain-gut-microbiota axis via the <anatomical location>subdiaphragmatic vagus nerve</anatomical location>. The brain-gut-microbiota axis plays a crucial role in the bidirectional interactions between the <anatomical location>brain</anatomical location> and the <anatomical location>gut</anatomical location>. <chemical>Soluble epoxide hydrolase</chemical> (coded by the <gene>Ephx2 gene</gene>) plays an important role in <DDF>inflammation</DDF>, which has been implicated in <DDF>stress-related depression</DDF>. <animal>Ephx2 knock-out (KO) mice</animal> exposed to <DDF>chronic social defeat stress</DDF> (<DDF>CSDS</DDF>) did not show depression-like behaviors, indicating stress resilience. Here we examined whether the brain-gut-microbiota axis influences the resilience in <animal>Ephx2 KO mice</animal>. Effects of fecal microbiota transplantation (FMT) from <animal>CSDS-susceptible (or control) mice</animal> in <animal>wild-type (WT) mice</animal> and <animal>Ephx2 KO mice</animal> treated with an <drug>antibiotic cocktail</drug> (<drug>ABX</drug>) were investigated. <biomedical technique>Behavioral, biochemical tests</biomedical technique> and <biomedical technique>16S ribosome RNA analysis</biomedical technique> were performed. FMT from <animal>CSDS-susceptible mice</animal> produced <DDF>anhedonia-like behavior</DDF> in <animal>ABX-treated WT and Ephx2 KO mice</animal>. The <biomedical technique>16S ribosome RNA analysis</biomedical technique> showed that <bacteria>Faecalibaculum rodentium</bacteria> (<bacteria>F. rodentium</bacteria>) may be responsible for the observed <DDF>anhedonia-like behavior</DDF> following FMT from <animal>CSDS-susceptible mice</animal>. Ingestion of <bacteria>F. rodentium</bacteria> for 14 days produced <DDF>depression- and anhedonia-like behaviors</DDF>, higher blood levels of <chemical>interleukin-6</chemical>, and reduced expression of <chemical>synaptic proteins</chemical> in the <anatomical location>prefrontal cortex</anatomical location> of <animal>ABX-treated Ephx2 KO mice</animal>. Furthermore, subdiaphragmatic vagotomy blocked the development of these behavioral abnormalities after ingestion of <bacteria>F. rodentium</bacteria>. Detailed mechanisms are unclear. These findings suggest that <bacteria>F. rodentium</bacteria> might contribute to the conversion of resilient <animal>Ephx2 KO mice</animal> into <animal>KO mice</animal> with <DDF>depression-like phenotypes</DDF>. The brain-gut-microbiota axis via the <anatomical location>subdiaphragmatic vagus nerve</anatomical location> plays a crucial role in susceptibility and resilience to <DDF>stress</DDF>.",
"role": "assistant"
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34204057
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nMediterranean Diet as an Antioxidant: The Impact on Metabolic Health and Overall Wellbeing. It has been established, worldwide, that non-communicable diseases such as obesity, diabetes, metabolic syndrome, and cardiovascular events account for a high percentage of morbidity and mortality in contemporary societies. Several modifiable risk factors, such as sedentary activities, sleep deprivation, smoking, and unhealthy dietary habits have contributed to this increase. Healthy nutrition in terms of adherence to the Mediterranean diet (MD), rich in fruits, legumes, vegetables, olive oil, herbs, spices, and high fiber intake may contribute to the decrease in this pandemic. The beneficial effects of the MD can be mainly attributed to its numerous components rich in anti-inflammatory and antioxidant properties. Moreover, the MD may further contribute to the improvement of reproductive health, modify the risk for neurodegenerative diseases, and protect against depression and psychosocial maladjustment. There is also evidence highlighting the impact of healthy nutrition in female people on the composition of the gut microbiota and future metabolic and overall health of their offspring. It is therefore important to highlight the beneficial effects of the MD on metabolic, reproductive, and mental health, while shaping the overall health of future generations. The beneficial effects of MD can be further enhanced by increased physical activity in the context of a well-balanced healthy lifestyle.",
"role": "user"
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{
"content": "<food>Mediterranean Diet</food> as an Antioxidant: The Impact on Metabolic Health and Overall Wellbeing. It has been established, worldwide, that <DDF>non-communicable diseases</DDF> such as <DDF>obesity</DDF>, <DDF>diabetes</DDF>, <DDF>metabolic syndrome</DDF>, and <DDF>cardiovascular events</DDF> account for a high percentage of morbidity and mortality in contemporary societies. Several modifiable risk factors, such as sedentary activities, <DDF>sleep deprivation</DDF>, smoking, and unhealthy dietary habits have contributed to this increase. Healthy nutrition in terms of adherence to the <food>Mediterranean diet</food> (<food>MD</food>), rich in <food>fruits</food>, <food>legumes</food>, <food>vegetables</food>, <food>olive oil</food>, <food>herbs</food>, <food>spices</food>, and high fiber intake may contribute to the decrease in this pandemic. The beneficial effects of the <food>MD</food> can be mainly attributed to its numerous components rich in anti-inflammatory and antioxidant properties. Moreover, the <food>MD</food> may further contribute to the improvement of reproductive health, modify the risk for <DDF>neurodegenerative diseases</DDF>, and protect against <DDF>depression</DDF> and <DDF>psychosocial maladjustment</DDF>. There is also evidence highlighting the impact of healthy nutrition in <human>female people</human> on the composition of the <microbiome>gut microbiota</microbiome> and future metabolic and overall health of their offspring. It is therefore important to highlight the beneficial effects of the <food>MD</food> on metabolic, reproductive, and mental health, while shaping the overall health of future generations. The beneficial effects of <food>MD</food> can be further enhanced by increased physical activity in the context of a well-balanced healthy lifestyle.",
"role": "assistant"
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34216356
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nThe Relationship Between the Gut Microbiome and Neurodegenerative Diseases. Many recent studies have shown that the gut microbiome plays important roles in human physiology and pathology. Also, microbiome-based therapies have been used to improve health status and treat diseases. In addition, aging and neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease, have become topics of intense interest in biomedical research. Several researchers have explored the links between these topics to study the potential pathogenic or therapeutic effects of intestinal microbiota in disease. But the exact relationship between neurodegenerative diseases and gut microbiota remains unclear. As technology advances, new techniques for studying the microbiome will be developed and refined, and the relationship between diseases and gut microbiota will be revealed. This article summarizes the known interactions between the gut microbiome and neurodegenerative diseases, highlighting assay techniques for the gut microbiome, and we also discuss the potential therapeutic role of microbiome-based therapies in diseases.",
"role": "user"
},
{
"content": "The Relationship Between the <microbiome>Gut Microbiome</microbiome> and <DDF>Neurodegenerative Diseases</DDF>. Many recent studies have shown that the <microbiome>gut microbiome</microbiome> plays important roles in human physiology and pathology. Also, microbiome-based therapies have been used to improve health status and treat diseases. In addition, <DDF>aging and neurodegenerative diseases</DDF>, including <DDF>Alzheimer's disease</DDF> and <DDF>Parkinson's disease</DDF>, have become topics of intense interest in biomedical research. Several researchers have explored the links between these topics to study the potential pathogenic or therapeutic effects of <microbiome>intestinal microbiota</microbiome> in disease. But the exact relationship between <DDF>neurodegenerative diseases</DDF> and <microbiome>gut microbiota</microbiome> remains unclear. As technology advances, new techniques for studying the microbiome will be developed and refined, and the relationship between diseases and <microbiome>gut microbiota</microbiome> will be revealed. This article summarizes the known interactions between the <microbiome>gut microbiome</microbiome> and <DDF>neurodegenerative diseases</DDF>, highlighting <biomedical technique>assay techniques</biomedical technique> for the <microbiome>gut microbiome</microbiome>, and we also discuss the potential therapeutic role of microbiome-based therapies in diseases.",
"role": "assistant"
}
] |
34250955
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nParkinson's Disease and the Gut: Symptoms, Nutrition, and Microbiota. Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide, characterized by symptoms of bradykinesia, rigidity, postural instability, and tremor. Recently, there has been a growing focus on the relationship between the gut and the development of PD. Emerging to the forefront, an interesting concept has developed suggesting that the initial pathophysiological changes occur in the gastrointestinal tract before changes are seen within the brain. This review is aimed at highlighting the relationship between PD and the gastrointestinal tract, along with the supporting evidence for this. Firstly, we will focus on the gastrointestinal conditions and symptoms which commonly affects patients, including both upper and lower gastrointestinal issues. Secondly, the impact of nutrition and diet on neurological health and PD physiology, with particular emphasis on commonly consumed items including macronutrients and micronutrients. Finally, variability of the gut microbiome will also be discussed and its link with both the symptoms and signs of PD. The evidence presented in this review highly suggests that the initial pathogenesis in the gut may proceed the development of prodromal PD subtypes, and therefore building on this further could be imperative and lead to earlier diagnosis with new and improved therapeutics.",
"role": "user"
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{
"content": "<DDF>Parkinson's Disease</DDF> and the <anatomical location>Gut</anatomical location>: Symptoms, Nutrition, and Microbiota. <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>) is the second most common <DDF>neurodegenerative disease</DDF> worldwide, characterized by symptoms of <DDF>bradykinesia</DDF>, <DDF>rigidity</DDF>, <DDF>postural instability</DDF>, and <DDF>tremor</DDF>. Recently, there has been a growing focus on the relationship between the <anatomical location>gut</anatomical location> and the development of <DDF>PD</DDF>. Emerging to the forefront, an interesting concept has developed suggesting that the <DDF>initial pathophysiological changes</DDF> occur in the <anatomical location>gastrointestinal tract</anatomical location> before changes are seen within the <anatomical location>brain</anatomical location>. This review is aimed at highlighting the relationship between <DDF>PD</DDF> and the <anatomical location>gastrointestinal tract</anatomical location>, along with the supporting evidence for this. Firstly, we will focus on the <DDF>gastrointestinal conditions and symptoms</DDF> which commonly affects <human>patients</human>, including both <DDF>upper and lower gastrointestinal issues</DDF>. Secondly, the impact of nutrition and diet on neurological health and PD physiology, with particular emphasis on commonly consumed items including <chemical>macronutrients</chemical> and <chemical>micronutrients</chemical>. Finally, variability of the <microbiome>gut microbiome</microbiome> will also be discussed and its link with both the symptoms and signs of <DDF>PD</DDF>. The evidence presented in this review highly suggests that the initial pathogenesis in the <anatomical location>gut</anatomical location> may proceed the development of <DDF>prodromal PD subtypes</DDF>, and therefore building on this further could be imperative and lead to earlier diagnosis with new and improved therapeutics.",
"role": "assistant"
}
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34277527
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nTowards Tailored Gut Microbiome-Based and Dietary Interventions for Promoting the Development and Maintenance of a Healthy Brain. Mental health is determined by a complex interplay between the Neurological Exposome and the Human Genome. Multiple genetic and non-genetic (exposome) factors interact early in life, modulating the risk of developing the most common complex neurodevelopmental disorders (NDDs), with potential long-term consequences on health. To date, the understating of the precise etiology underpinning these neurological alterations, and their clinical management pose a challenge. The crucial role played by diet and gut microbiota in brain development and functioning would indicate that modulating the gut-brain axis may help protect against the onset and progression of mental-health disorders. Some nutritional deficiencies and gut microbiota alterations have been linked to NDDs, suggesting their potential pathogenic implications. In addition, certain dietary interventions have emerged as promising alternatives or adjuvant strategies for improving the management of particular NDDs, at least in particular subsets of subjects. The gut microbiota can be a key to mediating the effects of other exposome factors such as diet on mental health, and ongoing research in Psychiatry and Neuropediatrics is developing Precision Nutrition Models to classify subjects according to a diet response prediction based on specific individual features, including microbiome signatures. Here, we review current scientific evidence for the impact of early life environmental factors, including diet, on gut microbiota and neuro-development, emphasizing the potential long-term consequences on health; and also summarize the state of the art regarding the mechanisms underlying diet and gut microbiota influence on the brain-gut axis. Furthermore, we describe the evidence supporting the key role played by gut microbiota, diet and nutrition in neurodevelopment, as well as the effectiveness of certain dietary and microbiome-based interventions aimed at preventing or treating NDDs. Finally, we emphasize the need for further research to gain greater insight into the complex interplay between diet, gut microbiome and brain development. Such knowledge would help towards achieving tailored integrative treatments, including personalized nutrition.",
"role": "user"
},
{
"content": "Towards Tailored Gut Microbiome-Based and Dietary Interventions for Promoting the Development and Maintenance of a Healthy <anatomical location>Brain</anatomical location>. Mental health is determined by a complex interplay between the Neurological Exposome and the Human Genome. Multiple genetic and non-genetic (exposome) factors interact early in life, modulating the risk of developing the most common complex <DDF>neurodevelopmental disorders</DDF> (<DDF>NDDs</DDF>), with potential long-term consequences on health. To date, the understating of the precise etiology underpinning these <DDF>neurological alterations</DDF>, and their clinical management pose a challenge. The crucial role played by diet and <microbiome>gut microbiota</microbiome> in brain development and functioning would indicate that modulating the gut-brain axis may help protect against the onset and progression of <DDF>mental-health disorders</DDF>. Some <DDF>nutritional deficiencies</DDF> and <DDF>gut microbiota alterations</DDF> have been linked to <DDF>NDDs</DDF>, suggesting their potential pathogenic implications. In addition, certain dietary interventions have emerged as promising alternatives or adjuvant strategies for improving the management of particular <DDF>NDDs</DDF>, at least in particular subsets of subjects. The <microbiome>gut microbiota</microbiome> can be a key to mediating the effects of other exposome factors such as diet on mental health, and ongoing research in Psychiatry and Neuropediatrics is developing Precision Nutrition Models to classify subjects according to a diet response prediction based on specific individual features, including microbiome signatures. Here, we review current scientific evidence for the impact of early life environmental factors, including diet, on <microbiome>gut microbiota</microbiome> and neuro-development, emphasizing the potential long-term consequences on health; and also summarize the state of the art regarding the mechanisms underlying diet and <microbiome>gut microbiota</microbiome> influence on the brain-gut axis. Furthermore, we describe the evidence supporting the key role played by <microbiome>gut microbiota</microbiome>, diet and nutrition in neurodevelopment, as well as the effectiveness of certain dietary and microbiome-based interventions aimed at preventing or treating <DDF>NDDs</DDF>. Finally, we emphasize the need for further research to gain greater insight into the complex interplay between diet, <microbiome>gut microbiome</microbiome> and brain development. Such knowledge would help towards achieving tailored integrative treatments, including personalized nutrition.",
"role": "assistant"
}
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34311029
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nFatty acids and beyond: Age and Alzheimer's disease related changes in lipids reveal the neuro-nutraceutical potential of lipids in cognition. Lipids are essential in maintaining brain function, and lipid profiles have been reported to be altered in aged and Alzheimer's disease (AD) brains as compared to healthy mature brains. Both age and AD share common metabolic hallmarks such as increased oxidative stress and perturbed metabolic function, and age remains the most strongly correlated risk factor for AD, a neurodegenerative disease. A major accompanying pathological symptom of these conditions is cognitive impairment, which is linked with changes in lipid metabolism. Thus, nutraceuticals that affect brain lipid metabolism or lipid levels as a whole have the potential to ameliorate cognitive decline. Lipid analyses and lipidomic studies reveal changes in specific lipid types with aging and AD, which can identify potential lipid-based nutraceuticals to restore the brain to a healthy lipid phenotype. The brain lipid profile can be influenced directly with dietary administration of lipids themselves, although because of synergistic effects of nutrients it may be more useful to consider a multi-component diet rather than single nutrient supplementation. Gut microbiota also serve as a source of beneficial lipids, and the value of treatments that manipulate the composition of gut microbiome should not be ignored. Lastly, instead of direct supplementation, compounds that affect pathways involved with lipid metabolism should also be considered as a way of manipulating lipid levels to improve cognition. In this review, we briefly discuss the role of lipids in the brain, the changing lipid profile in AD, current research on lipid-based nutraceuticals and their therapeutic potential to combat cognitive impairment.",
"role": "user"
},
{
"content": "<chemical>Fatty acids</chemical> and beyond: Age and Alzheimer's disease related changes in <chemical>lipids</chemical> reveal the neuro-nutraceutical potential of <chemical>lipids</chemical> in cognition. <chemical>Lipids</chemical> are essential in maintaining brain function, and lipid profiles have been reported to be altered in <anatomical location>aged and Alzheimer's disease (AD) brains</anatomical location> as compared to <anatomical location>healthy mature brains</anatomical location>. Both age and <DDF>AD</DDF> share common metabolic hallmarks such as <DDF>increased oxidative stress</DDF> and <DDF>perturbed metabolic function</DDF>, and age remains the most strongly correlated risk factor for <DDF>AD</DDF>, a <DDF>neurodegenerative disease</DDF>. A <DDF>major accompanying pathological symptom</DDF> of these conditions is <DDF>cognitive impairment</DDF>, which is linked with <DDF>changes in lipid metabolism</DDF>. Thus, <dietary supplement>nutraceuticals</dietary supplement> that affect brain lipid metabolism or lipid levels as a whole have the potential to ameliorate <DDF>cognitive decline</DDF>. <biomedical technique>Lipid analyses</biomedical technique> and <biomedical technique>lipidomic studies</biomedical technique> reveal changes in specific lipid types with aging and <DDF>AD</DDF>, which can identify potential <dietary supplement>lipid-based nutraceuticals</dietary supplement> to restore the <anatomical location>brain</anatomical location> to a healthy lipid phenotype. The brain lipid profile can be influenced directly with dietary administration of <dietary supplement>lipids</dietary supplement> themselves, although because of synergistic effects of nutrients it may be more useful to consider a <food>multi-component diet</food> rather than <dietary supplement>single nutrient supplementation</dietary supplement>. <microbiome>Gut microbiota</microbiome> also serve as a source of <chemical>beneficial lipids</chemical>, and the value of treatments that manipulate the composition of <microbiome>gut microbiome</microbiome> should not be ignored. Lastly, instead of direct supplementation, compounds that affect pathways involved with lipid metabolism should also be considered as a way of manipulating lipid levels to improve cognition. In this review, we briefly discuss the role of <chemical>lipids</chemical> in the <anatomical location>brain</anatomical location>, the changing lipid profile in <DDF>AD</DDF>, current research on <dietary supplement>lipid-based nutraceuticals</dietary supplement> and their therapeutic potential to combat <DDF>cognitive impairment</DDF>.",
"role": "assistant"
}
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34357134
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nStudy Protocol: The Evaluation Study for Social Cognition Measures in Japan (ESCoM). In schizophrenia, social cognitive impairment is considered one of the greatest obstacles to social participation. Although numerous measures have been developed to assess social cognition, only a limited number of them have become available in Japan. We are therefore planning this evaluation study for social cognition measures in Japan (ESCoM) to confirm their psychometric characteristics and to promote research focused on social cognition. Participants in the cross-sectional observational study will be 140 patients with schizophrenia recruited from three Japanese facilities and 70 healthy individuals. In our primary analysis, we will calculate several psychometric indicators with a focus on whether they can independently predict social functioning. In secondary analyses, we will assess the reliability and validity of the Japanese translations of each measure and conduct an exploratory investigation of patient background, psychiatric symptoms, defeatist performance belief, and gut microbiota as determinants of social cognition. The protocol for this study is registered in UMIN-CTR, unique ID UMIN000043777.",
"role": "user"
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{
"content": "Study Protocol: The Evaluation Study for Social Cognition Measures in Japan (ESCoM). In <DDF>schizophrenia</DDF>, <DDF>social cognitive impairment</DDF> is considered one of the greatest obstacles to social participation. Although numerous measures have been developed to assess social cognition, only a limited number of them have become available in Japan. We are therefore planning this evaluation study for social cognition measures in Japan (ESCoM) to confirm their psychometric characteristics and to promote research focused on social cognition. Participants in the cross-sectional observational study will be 140 <human>patients</human> with <DDF>schizophrenia</DDF> recruited from three Japanese facilities and 70 <human>healthy individuals</human>. In our primary analysis, we will calculate several psychometric indicators with a focus on whether they can independently predict social functioning. In secondary analyses, we will assess the reliability and validity of the Japanese translations of each measure and conduct an exploratory investigation of patient background, psychiatric symptoms, defeatist performance belief, and <microbiome>gut microbiota</microbiome> as determinants of social cognition. The protocol for this study is registered in UMIN-CTR, unique ID UMIN000043777.",
"role": "assistant"
}
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34357554
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nImmune-microbiome interplay and its implications in neurodegenerative disorders. The neurodegeneration and its related CNS pathologies need an urgent toolbox to minimize the global mental health burden. The neuroimmune system critically regulates the brain maturation and survival of neurons across the nervous system. The chronic manipulated immunological drive can accelerate the neuronal pathology hence promoting the burden of neurodegenerative disorders. The gut is home for trillions of microorganisms having a mutual relationship with the host system. The gut-brain axis is a unique biochemical pathway through which the gut residing microbes connects with the brain cells and regulates various physiological and pathological cascades. The gut microbiota and CNS communicate using a common language that synchronizes the tuning of immune cells. The intestinal gut microbial community has a profound role in the maturation of the immune system as well as the development of the nervous system. We have critically summarised the clinical and preclinical reports from the past a decade emphasising that the significant changes in gut microbiota can enhance the host susceptibility towards neurodegenerative disorders. In this review, we have discussed how the gut microbiota-mediated immune response inclines the host physiology towards neurodegeneration and indicated the gut microbiota as a potential future candidate for the management of neurodegenerative disorders.",
"role": "user"
},
{
"content": "Immune-microbiome interplay and its implications in <DDF>neurodegenerative disorders</DDF>. The <DDF>neurodegeneration</DDF> and its related <DDF>CNS pathologies</DDF> need an urgent toolbox to minimize the global mental health burden. The neuroimmune system critically regulates the brain maturation and survival of neurons across the nervous system. The chronic manipulated immunological drive can accelerate the neuronal pathology hence promoting the burden of <DDF>neurodegenerative disorders</DDF>. The <anatomical location>gut</anatomical location> is home for trillions of microorganisms having a mutual relationship with the host system. The gut-brain axis is a unique biochemical pathway through which the gut residing microbes connects with the brain cells and regulates various physiological and pathological cascades. The <microbiome>gut microbiota</microbiome> and CNS communicate using a common language that synchronizes the tuning of immune cells. The <microbiome>intestinal gut microbial community</microbiome> has a profound role in the maturation of the immune system as well as the development of the nervous system. We have critically summarised the clinical and preclinical reports from the past a decade emphasising that the significant changes in <microbiome>gut microbiota</microbiome> can enhance the host susceptibility towards <DDF>neurodegenerative disorders</DDF>. In this review, we have discussed how the gut microbiota-mediated immune response inclines the host physiology towards <DDF>neurodegeneration</DDF> and indicated the <microbiome>gut microbiota</microbiome> as a potential future candidate for the management of <DDF>neurodegenerative disorders</DDF>.",
"role": "assistant"
}
] |
34399524
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nDietary advanced glycation endproducts (AGEs) increase their concentration in plasma and tissues, result in inflammation and modulate gut microbial composition in mice; evidence for reversibility. Dietary advanced glycation endproducts (AGEs) are associated with negative biological effects, possibly due to accumulation in plasma and tissues and through modulation of inflammation and gut microbiota. Whether these biological consequences are reversible by limiting dietary AGE intake is unknown. Young healthy C57BL/6 mice were fed a standard chow (n = 10) or a baked chow high AGE-diet (n = 10) (~1.8-6.9 fold increased protein-bound Nε-(carboxymethyl)lysine (CML), Nε-(1-carboxyethyl)lysine (CEL), and Nδ-(5-hydro-5-methyl-4-imidazolon-2-yl)-ornithine (MG-H1)) for 10 weeks or a switch diet with baked chow for 5 weeks followed by 5 weeks of standard chow (n = 10). We assessed accumulation of AGEs in plasma, kidney, and liver and measured inflammatory markers and gut microbial composition. After 10 weeks of baked chow, a substantial panel of AGEs were increased in plasma, liver, and kidney. These increases were normalized after the switch diet. The inflammatory z-score increased after the baked chow diet. Gut microbial composition differed significantly between groups, with enriched Dubosiella spp. dominating these alterations. A high AGE-diet led to an increase of AGEs in plasma, kidney, and liver and to more inflammation and modification of the gut microbiota. These effects were reversed or discontinued by a diet lower in AGEs.",
"role": "user"
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{
"content": "<chemical>Dietary advanced glycation endproducts</chemical> (<chemical>AGEs</chemical>) increase their concentration in plasma and tissues, result in <DDF>inflammation</DDF> and modulate gut microbial composition in <animal>mice</animal>; evidence for reversibility. <chemical>Dietary advanced glycation endproducts</chemical> (<chemical>AGEs</chemical>) are associated with negative biological effects, possibly due to accumulation in plasma and tissues and through modulation of <DDF>inflammation</DDF> and <microbiome>gut microbiota</microbiome>. Whether these biological consequences are reversible by limiting dietary AGE intake is unknown. <animal>Young healthy C57BL/6 mice</animal> were fed a <food>standard chow (n = 10) or a baked chow high AGE-diet</food> (n = 10) (~1.8-6.9 fold increased <chemical>protein-bound Nε-(carboxymethyl)lysine</chemical> (<chemical>CML</chemical>), <chemical>Nε-(1-carboxyethyl)lysine</chemical> (<chemical>CEL</chemical>), and <chemical>Nδ-(5-hydro-5-methyl-4-imidazolon-2-yl)-ornithine</chemical> (<chemical>MG-H1</chemical>)) for 10 weeks or a switch diet with <food>baked chow</food> for 5 weeks followed by 5 weeks of <food>standard chow</food> (n = 10). We assessed accumulation of <chemical>AGEs</chemical> in plasma, <anatomical location>kidney</anatomical location>, and <anatomical location>liver</anatomical location> and measured inflammatory markers and gut microbial composition. After 10 weeks of <food>baked chow</food>, a substantial panel of <chemical>AGEs</chemical> were increased in plasma, <anatomical location>liver</anatomical location>, and <anatomical location>kidney</anatomical location>. These increases were normalized after the switch diet. The inflammatory z-score increased after the baked chow diet. Gut microbial composition differed significantly between groups, with enriched <bacteria>Dubosiella spp.</bacteria> dominating these alterations. A high <food>AGE-diet</food> led to an increase of <chemical>AGEs</chemical> in plasma, <anatomical location>kidney</anatomical location>, and <anatomical location>liver</anatomical location> and to more <DDF>inflammation</DDF> and modification of the <microbiome>gut microbiota</microbiome>. These effects were reversed or discontinued by a diet lower in <chemical>AGEs</chemical>.",
"role": "assistant"
}
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34408160
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nExploring human-genome gut-microbiome interaction in Parkinson's disease. The causes of complex diseases remain an enigma despite decades of epidemiologic research on environmental risks and genome-wide studies that have uncovered tens or hundreds of susceptibility loci for each disease. We hypothesize that the microbiome is the missing link. Genetic studies have shown that overexpression of alpha-synuclein, a key pathological protein in Parkinson's disease (PD), can cause familial PD and variants at alpha-synuclein locus confer risk of idiopathic PD. Recently, dysbiosis of gut microbiome in PD was identified: altered abundances of three microbial clusters were found, one of which was composed of opportunistic pathogens. Using two large datasets, we found evidence that the overabundance of opportunistic pathogens in PD gut is influenced by the host genotype at the alpha-synuclein locus, and that the variants responsible modulate alpha-synuclein expression. Results put forth testable hypotheses on the role of gut microbiome in the pathogenesis of PD, the incomplete penetrance of PD susceptibility genes, and potential triggers of pathology in the gut.",
"role": "user"
},
{
"content": "Exploring human-genome gut-microbiome interaction in <DDF>Parkinson's disease</DDF>. The causes of <DDF>complex diseases</DDF> remain an enigma despite decades of epidemiologic research on environmental risks and genome-wide studies that have uncovered tens or hundreds of susceptibility loci for each disease. We hypothesize that the microbiome is the missing link. Genetic studies have shown that overexpression of <chemical>alpha-synuclein</chemical>, a key pathological protein in <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>), can cause <DDF>familial PD</DDF> and variants at <gene>alpha-synuclein locus</gene> confer risk of <DDF>idiopathic PD</DDF>. Recently, <DDF>dysbiosis of gut microbiome</DDF> in <DDF>PD</DDF> was identified: altered abundances of three microbial clusters were found, one of which was composed of <bacteria>opportunistic pathogens</bacteria>. Using two large datasets, we found evidence that the overabundance of <bacteria>opportunistic pathogens</bacteria> in <anatomical location>PD gut</anatomical location> is influenced by the host genotype at the <gene>alpha-synuclein locus</gene>, and that the variants responsible modulate alpha-synuclein expression. Results put forth testable hypotheses on the role of <microbiome>gut microbiome</microbiome> in the <DDF>pathogenesis of PD</DDF>, the incomplete penetrance of <gene>PD susceptibility genes</gene>, and potential triggers of pathology in the <anatomical location>gut</anatomical location>.",
"role": "assistant"
}
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34437440
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nAssociation of Polygenic Risk Score and Bacterial Toxins at Screening Colonoscopy with Colorectal Cancer Progression: A Multicenter Case-Control Study. Colorectal cancer (CRC) is a leading cause of cancer death worldwide, and its incidence is correlated with infections, chronic inflammation, diet, and genetic factors. An emerging aspect is that microbial dysbiosis and chronic infections triggered by certain bacteria can be risk factors for tumor progression. Recent data suggest that certain bacterial toxins implicated in DNA attack or in proliferation, replication, and death can be risk factors for insurgence and progression of CRC. In this study, we recruited more than 300 biopsy specimens from people undergoing colonoscopy, and we analyzed to determine whether a correlation exists between the presence of bacterial genes coding for toxins possibly involved in CRC onset and progression and the different stages of CRC. We also analyzed to determine whether CRC-predisposing genetic factors could contribute to bacterial toxins response. Our results showed that CIF toxin is associated with polyps or adenomas, whereas pks+ seems to be a predisposing factor for CRC. Toxins from <i>Escherichia coli</i> as a whole have a higher incidence rate in adenocarcinoma patients compared to controls, whereas <i>Bacteroides fragilis</i> toxin does not seem to be associated with pre-cancerous nor with cancerous lesions. These results have been obtained irrespectively of the presence of CRC-risk loci.",
"role": "user"
},
{
"content": "Association of Polygenic Risk Score and <chemical>Bacterial Toxins</chemical> at <biomedical technique>Screening Colonoscopy</biomedical technique> with <DDF>Colorectal Cancer Progression</DDF>: A Multicenter Case-Control Study. <DDF>Colorectal cancer</DDF> (<DDF>CRC</DDF>) is a leading cause of <DDF>cancer death</DDF> worldwide, and its incidence is correlated with <DDF>infections</DDF>, <DDF>chronic inflammation</DDF>, diet, and genetic factors. An emerging aspect is that <DDF>microbial dysbiosis</DDF> and <DDF>chronic infections</DDF> triggered by certain bacteria can be risk factors for tumor progression. Recent data suggest that certain bacterial toxins implicated in DNA attack or in proliferation, replication, and death can be risk factors for insurgence and progression of <DDF>CRC</DDF>. In this study, we recruited more than 300 biopsy specimens from <human>people</human> undergoing <biomedical technique>colonoscopy</biomedical technique>, and we analyzed to determine whether a correlation exists between the presence of <gene>bacterial genes</gene> coding for <chemical>toxins</chemical> possibly involved in <DDF>CRC onset and progression</DDF> and the different stages of <DDF>CRC</DDF>. We also analyzed to determine whether CRC-predisposing genetic factors could contribute to bacterial toxins response. Our results showed that <chemical>CIF toxin</chemical> is associated with <DDF>polyps</DDF> or <DDF>adenomas</DDF>, whereas pks+ seems to be a predisposing factor for <DDF>CRC</DDF>. <chemical>Toxins</chemical> from <i><bacteria>Escherichia coli</bacteria></i> as a whole have a higher incidence rate in <human>adenocarcinoma patients</human> compared to <human>controls</human>, whereas <chemical><i>Bacteroides fragilis</i> toxin</chemical> does not seem to be associated with pre-cancerous nor with <DDF>cancerous lesions</DDF>. These results have been obtained irrespectively of the presence of CRC-risk loci.",
"role": "assistant"
}
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34448737
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nDepression: A Gut \"Microbiome\" Feeling! Burgeoning body of evidence from neuroscience is pouring in highlighting a potential association between gut microbiota with the pathophysiology of depression and anxiety. Manipulation of gut microbiota may be then useful to decode this role and to provide novel therapeutics for major depressive disorder (MDD), developing microbiota-related biomarkers to stratify patients at risk and to delineate more homogeneous biotypes of MDD.",
"role": "user"
},
{
"content": "<DDF>Depression</DDF>: A Gut \"Microbiome\" Feeling! Burgeoning body of evidence from neuroscience is pouring in highlighting a potential association between <microbiome>gut microbiota</microbiome> with the pathophysiology of <DDF>depression</DDF> and <DDF>anxiety</DDF>. Manipulation of <microbiome>gut microbiota</microbiome> may be then useful to decode this role and to provide novel therapeutics for <DDF>major depressive disorder</DDF> (<DDF>MDD</DDF>), developing <biomedical technique>microbiota-related biomarkers</biomedical technique> to stratify <human>patients</human> at risk and to delineate more homogeneous biotypes of <DDF>MDD</DDF>.",
"role": "assistant"
}
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34520319
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nSleep, circadian rhythm and gut microbiota: alterations in Alzheimer's disease and their potential links in the pathogenesis. ABSTRATCIn recent years, emerging studies have observed gut microbiota (GM) alterations in Alzheimer's disease (AD), even in individuals with mild cognitive impairment (MCI). Further, impaired sleep and circadian patterns are common symptoms of AD, while sleep and circadian rhythm disruption (SCRD) is associated with greater β-amyloid (Aβ) burden and AD risk, sometimes years before the clinical onset of AD. Moreover, reports have demonstrated that GM and its metabolites exhibit diurnal rhythmicity and the role of SCRD in dampening the GM rhythmicity and eubiosis. This review will provide an evaluation of clinical and animal studies describing GM alterations in distinct conditions, including AD, sleep and circadian disruption. It aims to identify the overlapping and distinctive GM alterations in these conditions and their contributions to pathophysiology. Although most studies are observational and use different methodologies, data indicate partial commonalities in GM alterations and unanimity at functional level. Finally, we discuss the possible interactions between SCRD and GM in AD pathogenesis, as well as several methodological improvements that are necessary for future research.",
"role": "user"
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"content": "Sleep, circadian rhythm and <microbiome>gut microbiota</microbiome>: alterations in <DDF>Alzheimer's disease</DDF> and their potential links in the pathogenesis. ABSTRATCIn recent years, emerging studies have observed <microbiome>gut microbiota</microbiome> (<microbiome>GM</microbiome>) alterations in <DDF>Alzheimer's disease</DDF> (<DDF>AD</DDF>), even in <human>individuals</human> with <DDF>mild cognitive impairment</DDF> (<DDF>MCI</DDF>). Further, <DDF>impaired sleep and circadian patterns</DDF> are common symptoms of <DDF>AD</DDF>, while <DDF>sleep and circadian rhythm disruption</DDF> (<DDF>SCRD</DDF>) is associated with greater <chemical>β-amyloid</chemical> (<chemical>Aβ</chemical>) burden and AD risk, sometimes years before the clinical onset of <DDF>AD</DDF>. Moreover, reports have demonstrated that <microbiome>GM</microbiome> and its metabolites exhibit diurnal rhythmicity and the role of <DDF>SCRD</DDF> in dampening the GM rhythmicity and eubiosis. This review will provide an evaluation of clinical and animal studies describing <DDF>GM alterations</DDF> in distinct conditions, including <DDF>AD</DDF>, <DDF>sleep and circadian disruption</DDF>. It aims to identify the overlapping and distinctive <DDF>GM alterations</DDF> in these conditions and their contributions to pathophysiology. Although most studies are observational and use different methodologies, data indicate partial commonalities in <DDF>GM alterations</DDF> and unanimity at functional level. Finally, we discuss the possible interactions between <DDF>SCRD</DDF> and <microbiome>GM</microbiome> in AD pathogenesis, as well as several methodological improvements that are necessary for future research.",
"role": "assistant"
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34576000
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nNuclear and Mitochondrial Genome, Epigenome and Gut Microbiome: Emerging Molecular Biomarkers for Parkinson's Disease. Parkinson's disease (PD) is currently the second most common neurodegenerative disorder, burdening about 10 million elderly individuals worldwide. The multifactorial nature of PD poses a difficult obstacle for understanding the mechanisms involved in its onset and progression. Currently, diagnosis depends on the appearance of clinical signs, some of which are shared among various neurologic disorders, hindering early diagnosis. There are no effective tools to prevent PD onset, detect the disease in early stages or accurately report the risk of disease progression. Hence, there is an increasing demand for biomarkers that may identify disease onset and progression, as treatment-based medicine may not be the best approach for PD. Over the last few decades, the search for molecular markers to predict susceptibility, aid in accurate diagnosis and evaluate the progress of PD have intensified, but strategies aimed to improve individualized patient care have not yet been established. Genomic variation, regulation by epigenomic mechanisms, as well as the influence of the host gut microbiome seem to have a crucial role in the onset and progress of PD, thus are considered potential biomarkers. As such, the human nuclear and mitochondrial genome, epigenome, and the host gut microbiome might be the key elements to the rise of personalized medicine for PD patients.",
"role": "user"
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{
"content": "Nuclear and Mitochondrial Genome, Epigenome and <microbiome>Gut Microbiome</microbiome>: Emerging Molecular Biomarkers for <DDF>Parkinson's Disease</DDF>. <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>) is currently the second most common <DDF>neurodegenerative disorder</DDF>, burdening about 10 million <human>elderly individuals</human> worldwide. The multifactorial nature of <DDF>PD</DDF> poses a difficult obstacle for understanding the mechanisms involved in its onset and progression. Currently, diagnosis depends on the appearance of clinical signs, some of which are shared among various <DDF>neurologic disorders</DDF>, hindering early diagnosis. There are no effective tools to prevent <DDF>PD onset</DDF>, detect the disease in early stages or accurately report the risk of disease progression. Hence, there is an increasing demand for biomarkers that may identify disease onset and progression, as treatment-based medicine may not be the best approach for <DDF>PD</DDF>. Over the last few decades, the search for molecular markers to predict susceptibility, aid in accurate diagnosis and evaluate the progress of <DDF>PD</DDF> have intensified, but strategies aimed to improve individualized patient care have not yet been established. Genomic variation, regulation by epigenomic mechanisms, as well as the influence of the <microbiome>host gut microbiome</microbiome> seem to have a crucial role in the onset and progress of <DDF>PD</DDF>, thus are considered potential biomarkers. As such, the human nuclear and mitochondrial genome, epigenome, and the <microbiome>host gut microbiome</microbiome> might be the key elements to the rise of personalized medicine for <human>PD patients</human>.",
"role": "assistant"
}
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34576833
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nSpecific Changes in the Mammalian Gut Microbiome as a Biomarker for Oxytocin-Induced Behavioral Changes. Prolonged exposure to psychiatric pharmacological agents is often associated with marked gastrointestinal phenomena, including changes in food intake, bowel motility, gastric emptying, and transit time. Those changes are reflected in the gut microbiota composition of the patient and can, therefore, be objectively measured. This is in contrast to the standard psychiatric evaluation of patients, which includes symptoms that are subjectively assessed (i.e., mood, anxiety level, perception, thought disorders, etc.). The association between a drug's effect on the microbiota and psychiatric symptoms may allow for quantifiable surrogate markers of treatment effectiveness. Changes in the levels of specific drug-sensitive bacterial species can, thus, potentially serve as biomarkers for the intake and effectiveness of psychiatric drugs. Here, we show substantial microbiota changes that were associated with oxytocin administration and the decreased anxiety/depression-like behaviors it conferred in a rat model of corticosterone-induced stress. Compared with oxytocin, citalopram produced more minor effects on the rats' microbiota. Alterations in the gut microbiota may, therefore, reflect the consumption and effectiveness of some psychiatric drugs.",
"role": "user"
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"content": "Specific Changes in the <microbiome>Mammalian Gut Microbiome</microbiome> as a Biomarker for <DDF>Oxytocin-Induced Behavioral Changes</DDF>. Prolonged exposure to <drug>psychiatric pharmacological agents</drug> is often associated with marked <DDF>gastrointestinal phenomena</DDF>, including changes in food intake, bowel motility, gastric emptying, and transit time. Those changes are reflected in the gut microbiota composition of the <human>patient</human> and can, therefore, be objectively measured. This is in contrast to the standard psychiatric evaluation of <human>patients</human>, which includes symptoms that are subjectively assessed (i.e., mood, anxiety level, perception, <DDF>thought disorders</DDF>, etc.). The association between a drug's effect on the microbiota and <DDF>psychiatric symptoms</DDF> may allow for quantifiable surrogate markers of treatment effectiveness. Changes in the levels of specific <bacteria>drug-sensitive bacterial species</bacteria> can, thus, potentially serve as biomarkers for the intake and effectiveness of <drug>psychiatric drugs</drug>. Here, we show substantial microbiota changes that were associated with <drug>oxytocin administration</drug> and the decreased <DDF>anxiety/depression-like behaviors</DDF> it conferred in a rat model of <DDF>corticosterone-induced stress</DDF>. Compared with <drug>oxytocin</drug>, <drug>citalopram</drug> produced more minor effects on the rats' microbiota. Alterations in the <microbiome>gut microbiota</microbiome> may, therefore, reflect the consumption and effectiveness of some <drug>psychiatric drugs</drug>.",
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34589800
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nBeyond the neuro-immune interplay in depression: Could gut microbes be the missing link? Accumulating evidence have positioned inflammatory signaling pathways as crucial routes by which microbes inhabiting the gastrointestinal tract (the gut microbiota) communicate with the host brain to influence behavior, with impacts on mental illnesses. In this short review, an overview of inflammatory and gut microbiota status in human depression and in rodent models of the illness are provided. Next, potential inflammatory pathways mediating the communications between the gut and the brain under stressful conditions are described. Finally, dietary interventions targeting the gut microbiota-immune-brain axis in the context of depression are briefly discussed.",
"role": "user"
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{
"content": "Beyond the neuro-immune interplay in <DDF>depression</DDF>: Could <bacteria>gut microbes</bacteria> be the missing link? Accumulating evidence have positioned inflammatory signaling pathways as crucial routes by which microbes inhabiting the <anatomical location>gastrointestinal tract</anatomical location> (the <microbiome>gut microbiota</microbiome>) communicate with the <anatomical location>host brain</anatomical location> to influence behavior, with impacts on <DDF>mental illnesses</DDF>. In this short review, an overview of inflammatory and gut microbiota status in <DDF>human depression</DDF> and in rodent models of the illness are provided. Next, potential inflammatory pathways mediating the communications between the <anatomical location>gut</anatomical location> and the <anatomical location>brain</anatomical location> under stressful conditions are described. Finally, dietary interventions targeting the gut microbiota-immune-brain axis in the context of <DDF>depression</DDF> are briefly discussed.",
"role": "assistant"
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34589852
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nNutritional psychiatry in the treatment of psychotic disorders: Current hypotheses and research challenges. Current treatment for schizophrenia-spectrum disorders focusses primarily on psychotropic medication to treat symptoms, though their efficacy varies between patients and psychotropic medication is often accompanied by severe side effects. Nutritional interventions to prevent and treat mental illness have received considerable attention over recent years. However, evidence for nutritional interventions in schizophrenia-spectrum disorders remains limited in quantity and quality. Pathways currently in focus include: i) nutritional deficits and impairments in glucose metabolism, ii) inflammation and immune dysregulation (also known from the mild encephalitis hypothesis), and iii) altered gut microbiota. All of which appear to be interconnected. Key limiting factors for advancing research in this field are research challenges associated with assessing and interpreting inflammatory profiles, microbiota and subjective nutritional assessments, which is further complicated by illness characteristics. This review describes the state of evidence for key hypotheses, including underlying mechanisms, implicated in schizophrenia-spectrum disorders, the challenges in nutritional psychiatry research and the current state of nutrition interventions in mental healthcare.",
"role": "user"
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{
"content": "Nutritional psychiatry in the treatment of <DDF>psychotic disorders</DDF>: Current hypotheses and research challenges. Current treatment for <DDF>schizophrenia-spectrum disorders</DDF> focusses primarily on <drug>psychotropic medication</drug> to treat symptoms, though their efficacy varies between <human>patients</human> and <drug>psychotropic medication</drug> is often accompanied by severe side effects. Nutritional interventions to prevent and treat <DDF>mental illness</DDF> have received considerable attention over recent years. However, evidence for nutritional interventions in <DDF>schizophrenia-spectrum disorders</DDF> remains limited in quantity and quality. Pathways currently in focus include: i) <DDF>nutritional deficits</DDF> and impairments in glucose metabolism, ii) <DDF>inflammation and immune dysregulation</DDF> (also known from the mild encephalitis hypothesis), and iii) <microbiome>altered gut microbiota</microbiome>. All of which appear to be interconnected. Key limiting factors for advancing research in this field are research challenges associated with assessing and interpreting inflammatory profiles, microbiota and subjective nutritional assessments, which is further complicated by illness characteristics. This review describes the state of evidence for key hypotheses, including underlying mechanisms, implicated in <DDF>schizophrenia-spectrum disorders</DDF>, the challenges in nutritional psychiatry research and the current state of nutrition interventions in mental healthcare.",
"role": "assistant"
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34692176
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nA Review of Inflammatory Bowel Disease: A Model of Microbial, Immune and Neuropsychological Integration. <b>Objective:</b> Inflammatory bowel diseases (IBDs) are complex chronic inflammatory disorders of the gastro-intestinal (GI) tract with uncertain etiology. IBDs comprise two idiopathic disorders: Crohn's disease (CD) and ulcerative colitis (UC). The aetiology, severity and progression of such disorders are still poorly understood but thought to be influenced by multiple factors (including genetic, environmental, immunological, physiological, psychological factors and gut microbiome) and their interactions. The overarching aim of this review is to evaluate the extent and nature of the interrelationship between these factors with the disease course. A broader conceptual and longitudinal framework of possible neuro-visceral integration, core microbiome analysis and immune modulation assessment may be useful in accurately documenting and characterizing the nature and temporal continuity of crosstalk between these factors and the role of their interaction (s) in IBD disease activity. Characterization of these interactions holds the promise of identifying novel diagnostic, interventions, and therapeutic strategies. <b>Material and Methods:</b> A search of published literature was conducted by exploring PubMed, EMBASE, MEDLINE, Medline Plus, CDSR library databases. Following search terms relating to key question were set for the search included: \"Inflammatory bowel diseases,\" \"gut microbiota,\" \"psychological distress and IBD,\" \"autonomic reactivity and IBD,\" \"immune modulation,\" \"chronic inflammation,\" \"gut inflammation,\" \"enteric nervous system,\" \"gut nervous system,\" \"Crohn's disease,\" \"Ulcerative colitis\", \"depression and IBD\", \"anxiety and IBD\", \"quality of life in IBD patients,\" \"relapse in IBDs,\" \"remission in IBDs,\" \"IBD disease activity,\" \"brain-gut-axis,\" \"microbial signature in IBD,\" \"validated questionnaires in IBD,\" \"IBD activity indices,\" \"IBD aetiology,\" \"IBDs and stress,\" \"epidemiology of IBDs\", \"autonomic nervous system and gut inflammation\", \"IBD and environment,\" \"genetics of IBDs,\" \"pathways of immune response in IBDs,\" \"sleep disturbances in IBD,\" \"hypothalamic-pituitary-adrenal axis (HPA),\" \"sympatho-adrenal axis,\" \"CNS and its control of gut function\" \"mucosal immune response,\" \"commensal and pathogenic bacteria in the gut,\" \"innate and adaptive immunity.\" Studies evaluating any possible associations between gut microbiome, psychological state, immune modulation, and autonomic function with IBDs were identified. Commonly cited published literatures with high quality research methodology/results and additional articles from bibliographies of recovered papers were examined and included where relevant. <b>Results:</b> Although there is a substantial literature identifying major contributing factors with IBD, there has been little attempt to integrate some factors over time and assess their interplay and relationship with IBD disease activity. Such contributing factors include genetic and environmental factors, gut microbiota composition and function, physiological factors, psychological state and gut immune response. Interdependences are evident across psychological and biological factors and IBD disease activity. Although from the available evidence, it is implausible that a single explanatory model could elucidate the interplay between such factors and the disease course as well as the sequence of the effect during the pathophysiology of IBD. <b>Conclusion:</b> Longitudinal monitoring of IBD patients and integrating data related to the contributing/risk factors including psychological state, physiological conditions, inflammatory/immune modulations, and microbiome composition/function, could help to explain how major factors associate and interrelate leading to exacerbation of symptoms and disease activity. Identifying the temporal trajectory of biological and psychosocial disturbances may also help to assess their effects and interdependence on individuals' disease status. Moreover, this allows greater insight into understanding the temporal progressions of subclinical events as potential ground for disease severity in IBD. Furthermore, understanding the interaction between these risk factors may help better interventions in controlling the disease, reducing the costs related to disease management, further implications for clinical practice and research approaches in addition to improving patients' mental health and quality of life.",
"role": "user"
},
{
"content": "A Review of <DDF>Inflammatory Bowel Disease</DDF>: A Model of Microbial, Immune and Neuropsychological Integration. <b>Objective:</b> <DDF>Inflammatory bowel diseases</DDF> (<DDF>IBDs</DDF>) are <DDF>complex chronic inflammatory disorders</DDF> of the gastro-intestinal (GI) tract with uncertain etiology. <DDF>IBDs</DDF> comprise two <DDF>idiopathic disorders</DDF>: <DDF>Crohn's disease</DDF> (<DDF>CD</DDF>) and <DDF>ulcerative colitis</DDF> (<DDF>UC</DDF>). The aetiology, severity and progression of such disorders are still poorly understood but thought to be influenced by multiple factors (including genetic, environmental, immunological, physiological, psychological factors and <microbiome>gut microbiome</microbiome>) and their interactions. The overarching aim of this review is to evaluate the extent and nature of the interrelationship between these factors with the disease course. A broader conceptual and longitudinal framework of possible neuro-visceral integration, core microbiome analysis and immune modulation assessment may be useful in accurately documenting and characterizing the nature and temporal continuity of crosstalk between these factors and the role of their interaction (s) in <DDF>IBD disease activity</DDF>. Characterization of these interactions holds the promise of identifying novel diagnostic, interventions, and therapeutic strategies. <b>Material and Methods:</b> A search of published literature was conducted by exploring PubMed, EMBASE, MEDLINE, Medline Plus, CDSR library databases. Following search terms relating to key question were set for the search included: \"<DDF>Inflammatory bowel diseases</DDF>,\" \"<microbiome>gut microbiota</microbiome>,\" \"<DDF>psychological distress</DDF> and <DDF>IBD</DDF>,\" \"autonomic reactivity and <DDF>IBD</DDF>,\" \"immune modulation,\" \"<DDF>chronic inflammation</DDF>,\" \"<DDF>gut inflammation</DDF>,\" \"enteric nervous system,\" \"gut nervous system,\" \"<DDF>Crohn's disease</DDF>,\" \"<DDF>Ulcerative colitis</DDF>\", \"<DDF>depression</DDF> and <DDF>IBD</DDF>\", \"<DDF>anxiety</DDF> and <DDF>IBD</DDF>\", \"quality of life in <human>IBD patients</human>,\" \"relapse in <DDF>IBDs</DDF>,\" \"remission in <DDF>IBDs</DDF>,\" \"<DDF>IBD disease activity</DDF>,\" \"brain-gut-axis,\" \"microbial signature in <DDF>IBD</DDF>,\" \"validated questionnaires in <DDF>IBD</DDF>,\" \"IBD activity indices,\" \"IBD aetiology,\" \"<DDF>IBDs</DDF> and <DDF>stress</DDF>,\" \"epidemiology of <DDF>IBDs</DDF>\", \"autonomic nervous system and <DDF>gut inflammation</DDF>\", \"<DDF>IBD</DDF> and environment,\" \"genetics of <DDF>IBDs</DDF>,\" \"pathways of immune response in <DDF>IBDs</DDF>,\" \"<DDF>sleep disturbances</DDF> in <DDF>IBD</DDF>,\" \"hypothalamic-pituitary-adrenal axis (HPA),\" \"sympatho-adrenal axis,\" \"CNS and its control of gut function\" \"mucosal immune response,\" \"<bacteria>commensal and pathogenic bacteria</bacteria> in the <anatomical location>gut</anatomical location>,\" \"innate and adaptive immunity.\" Studies evaluating any possible associations between <microbiome>gut microbiome</microbiome>, psychological state, immune modulation, and autonomic function with <DDF>IBDs</DDF> were identified. Commonly cited published literatures with high quality research methodology/results and additional articles from bibliographies of recovered papers were examined and included where relevant. <b>Results:</b> Although there is a substantial literature identifying major contributing factors with <DDF>IBD</DDF>, there has been little attempt to integrate some factors over time and assess their interplay and relationship with <DDF>IBD disease activity</DDF>. Such contributing factors include genetic and environmental factors, gut microbiota composition and function, physiological factors, psychological state and gut immune response. Interdependences are evident across psychological and biological factors and <DDF>IBD disease activity</DDF>. Although from the available evidence, it is implausible that a single explanatory model could elucidate the interplay between such factors and the disease course as well as the sequence of the effect during the <DDF>pathophysiology of IBD</DDF>. <b>Conclusion:</b> Longitudinal monitoring of <human>IBD patients</human> and integrating data related to the contributing/risk factors including psychological state, physiological conditions, inflammatory/immune modulations, and microbiome composition/function, could help to explain how major factors associate and interrelate leading to exacerbation of symptoms and disease activity. Identifying the temporal trajectory of biological and psychosocial disturbances may also help to assess their effects and interdependence on individuals' disease status. Moreover, this allows greater insight into understanding the temporal progressions of subclinical events as potential ground for disease severity in <DDF>IBD</DDF>. Furthermore, understanding the interaction between these risk factors may help better interventions in controlling the disease, reducing the costs related to disease management, further implications for clinical practice and research approaches in addition to improving patients' mental health and quality of life.",
"role": "assistant"
}
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34704023
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGut microbiome alpha-diversity is not a marker of Parkinson's disease and multiple sclerosis. The gut-brain axis may play a central role in the pathogenesis of neurological disorders. Dozens of case-control studies have been carried out to identify bacterial markers by the use of targeted metagenomics. Alterations of several taxonomic profiles have been confirmed across several populations, however, no consensus has been made regarding alpha-diversity. A recent publication has described and validated a novel method based on richness and evenness measures of the gut microbiome in order to reduce the complexity and multiplicity of alpha-diversity indices. We used these recently described richness and evenness composite measures to investigate the potential link between gut microbiome alpha-diversity and neurological disorders and to determine to what extent it could be used as a marker to diagnose neurological disorders from stool samples. We performed an exhaustive review of the literature to identify original published clinical studies including 16S rRNA gene sequencing on Parkinson's disease, multiple Sclerosis and Alzheimer's disease. Richness and evenness factors loadings were quantified from sequencing files in addition with the Shannon diversity index. For each disease, we performed a meta-analysis comparing the indices between patients and healthy controls. Seven studies were meta-analysed for Parkinson's disease, corresponding to 1067 subjects (631 Parkinson's Disease/436 healthy controls). Five studies were meta-analysed for multiple sclerosis, corresponding to 303 subjects (164 Multiple Sclerosis/139 healthy controls). For Alzheimer's disease, the meta-analysis was not done as only two studies matched our criteria. Neither richness nor evenness was significantly altered in Parkinson's disease and multiple sclerosis patients in comparison to healthy controls (<i>P</i>-value > 0.05). Shannon index was neither associated with neurological disorders (<i>P</i>-value > 0.05). After adjusting for age and sex, none of the alpha-diversity measures were associated with Parkinson's Disease. This is the first report investigating systematically alpha-diversity and its potential link to neurological disorders. Our study has demonstrated that unlike in other gastro-intestinal, immune and metabolic disorders, loss of bacterial diversity is not associated with Parkinson's disease and multiple sclerosis.",
"role": "user"
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{
"content": "Gut microbiome alpha-diversity is not a marker of <DDF>Parkinson's disease</DDF> and <DDF>multiple sclerosis</DDF>. The gut-brain axis may play a central role in the pathogenesis of <DDF>neurological disorders</DDF>. Dozens of case-control studies have been carried out to identify bacterial markers by the use of targeted metagenomics. Alterations of several taxonomic profiles have been confirmed across several populations, however, no consensus has been made regarding alpha-diversity. A recent publication has described and validated a novel method based on richness and evenness measures of the <microbiome>gut microbiome</microbiome> in order to reduce the complexity and multiplicity of alpha-diversity indices. We used these recently described richness and evenness composite measures to investigate the potential link between <DDF>gut microbiome alpha-diversity</DDF> and <DDF>neurological disorders</DDF> and to determine to what extent it could be used as a marker to diagnose <DDF>neurological disorders</DDF> from stool samples. We performed an exhaustive review of the literature to identify original published clinical studies including <biomedical technique>16S rRNA gene sequencing</biomedical technique> on <DDF>Parkinson's disease</DDF>, <DDF>multiple Sclerosis</DDF> and <DDF>Alzheimer's disease</DDF>. Richness and evenness factors loadings were quantified from sequencing files in addition with the <statistical technique>Shannon diversity index</statistical technique>. For each disease, we performed a <statistical technique>meta-analysis</statistical technique> comparing the indices between <human>patients</human> and <human>healthy controls</human>. Seven studies were meta-analysed for <DDF>Parkinson's disease</DDF>, corresponding to 1067 subjects (631 <DDF>Parkinson's Disease</DDF>/436 <human>healthy controls</human>). Five studies were meta-analysed for <DDF>multiple sclerosis</DDF>, corresponding to 303 subjects (164 <DDF>Multiple Sclerosis</DDF>/139 <human>healthy controls</human>). For <DDF>Alzheimer's disease</DDF>, the <statistical technique>meta-analysis</statistical technique> was not done as only two studies matched our criteria. Neither richness nor evenness was significantly altered in <human>Parkinson's disease and multiple sclerosis patients</human> in comparison to <human>healthy controls</human> (<i>P</i>-value > 0.05). <statistical technique>Shannon index</statistical technique> was neither associated with <DDF>neurological disorders</DDF> (<i>P</i>-value > 0.05). After adjusting for age and sex, none of the alpha-diversity measures were associated with <DDF>Parkinson's Disease</DDF>. This is the first report investigating systematically alpha-diversity and its potential link to <DDF>neurological disorders</DDF>. Our study has demonstrated that unlike in other <DDF>gastro-intestinal, immune and metabolic disorders</DDF>, loss of bacterial diversity is not associated with <DDF>Parkinson's disease</DDF> and <DDF>multiple sclerosis</DDF>.",
"role": "assistant"
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34836918
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nFootprints of a microbial toxin from the gut microbiome to mesencephalic mitochondria. Idiopathic Parkinson's disease (PD) is characterised by alpha-synuclein (aSyn) aggregation and death of dopaminergic neurons in the midbrain. Recent evidence posits that PD may initiate in the gut by microbes or their toxins that promote chronic gut inflammation that will ultimately impact the brain. In this work, we sought to demonstrate that the effects of the microbial toxin β-<i>N</i>-methylamino-L-alanine (BMAA) in the gut may trigger some PD cases, which is especially worrying as this toxin is present in certain foods but not routinely monitored by public health authorities. To test the hypothesis, we treated wild-type mice, primary neuronal cultures, cell lines and isolated mitochondria with BMAA, and analysed its impact on gut microbiota composition, barrier permeability, inflammation and aSyn aggregation as well as in brain inflammation, dopaminergic neuronal loss and motor behaviour. To further examine the key role of mitochondria, we also determined the specific effects of BMAA on mitochondrial function and on inflammasome activation. BMAA induced extensive depletion of segmented filamentous bacteria (SFB) that regulate gut immunity, thus triggering gut dysbiosis, immune cell migration, increased intestinal inflammation, loss of barrier integrity and caudo-rostral progression of aSyn. Additionally, BMAA induced <i>in vitro</i> and <i>in vivo</i> mitochondrial dysfunction with cardiolipin exposure and consequent activation of neuronal innate immunity. These events primed neuroinflammation, dopaminergic neuronal loss and motor deficits. Taken together, our results demonstrate that chronic exposure to dietary BMAA can trigger a chain of events that recapitulate the evolution of the PD pathology from the gut to the brain, which is consistent with 'gut-first' PD.",
"role": "user"
},
{
"content": "Footprints of a <chemical>microbial toxin</chemical> from the <microbiome>gut microbiome</microbiome> to <anatomical location>mesencephalic mitochondria</anatomical location>. <DDF>Idiopathic Parkinson's disease</DDF> (<DDF>PD</DDF>) is characterised by alpha-synuclein (<chemical>aSyn</chemical>) aggregation and death of dopaminergic neurons in the <anatomical location>midbrain</anatomical location>. Recent evidence posits that <DDF>PD</DDF> may initiate in the <anatomical location>gut</anatomical location> by microbes or their toxins that promote <DDF>chronic gut inflammation</DDF> that will ultimately impact the <anatomical location>brain</anatomical location>. In this work, we sought to demonstrate that the effects of the <chemical>microbial toxin β-<i>N</i>-methylamino-L-alanine</chemical> (<chemical>BMAA</chemical>) in the <anatomical location>gut</anatomical location> may trigger some <DDF>PD</DDF> cases, which is especially worrying as this toxin is present in certain foods but not routinely monitored by public health authorities. To test the hypothesis, we treated <animal>wild-type mice</animal>, primary neuronal cultures, cell lines and isolated mitochondria with <chemical>BMAA</chemical>, and analysed its impact on <microbiome>gut microbiota</microbiome> composition, barrier permeability, <DDF>inflammation</DDF> and aSyn aggregation as well as in <DDF>brain inflammation</DDF>, <DDF>dopaminergic neuronal loss</DDF> and motor behaviour. To further examine the key role of mitochondria, we also determined the specific effects of <chemical>BMAA</chemical> on mitochondrial function and on inflammasome activation. <chemical>BMAA</chemical> induced extensive depletion of <bacteria>segmented filamentous bacteria</bacteria> (<bacteria>SFB</bacteria>) that regulate gut immunity, thus triggering <DDF>gut dysbiosis</DDF>, <DDF>immune cell migration</DDF>, increased <DDF>intestinal inflammation</DDF>, <DDF>loss of barrier integrity</DDF> and caudo-rostral progression of aSyn. Additionally, <chemical>BMAA</chemical> induced <i>in vitro</i> and <i>in vivo</i> mitochondrial dysfunction with <chemical>cardiolipin</chemical> exposure and consequent activation of neuronal innate immunity. These events primed <DDF>neuroinflammation</DDF>, <DDF>dopaminergic neuronal loss</DDF> and <DDF>motor deficits</DDF>. Taken together, our results demonstrate that chronic exposure to dietary <chemical>BMAA</chemical> can trigger a chain of events that recapitulate the evolution of the <DDF>PD pathology</DDF> from the <anatomical location>gut</anatomical location> to the <anatomical location>brain</anatomical location>, which is consistent with <DDF>'gut-first' PD</DDF>.",
"role": "assistant"
}
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34884399
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nDifferences in the Composition of Gut Microbiota between Patients with Parkinson's Disease and Healthy Controls: A Cohort Study. Gut microbiome and colonic inflammation can be associated with the predisposition and progression of Parkinson's disease (PD). The presented study aimed to compare gastrointestinal microbiota composition between patients diagnosed with PD and treated only with Levodopa to healthy controls. In this prospective study, patients were recruited in 1 academic hospital from July 2019 to July 2020. The detailed demographic data and medical history were collected using a set of questionnaires. Fecal samples were obtained from all participants. Next-Generation Sequencing was used to assess the microbiota composition. The endpoint was the difference in composition of the gut microbiota. In this study, we enrolled 27 hospitalized PD patients with well-controlled symptoms. The control group included 44 healthy subjects matched for age. Among PD patients, our results presented a higher abundance of <i>Bacteroides</i> phylum, class <i>Corynebacteria</i> among phylum <i>Actinobacteria</i>, class <i>Deltaproteobacteria</i> among phylum <i>Proteobacteria</i>, and genera such as <i>Butyricimonas, Robinsoniella</i>, and <i>Flavonifractor</i>. The species <i>Akkermansia muciniphila</i>, <i>Eubacterium biforme</i>, and <i>Parabacteroides merdae</i> were identified as more common in the gut microbiota of PD patients. In conclusion, the patients diagnosed with PD have significantly different gut microbiota profiles in comparison with healthy controls.",
"role": "user"
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{
"content": "Differences in the Composition of <microbiome>Gut Microbiota</microbiome> between <human>Patients</human> with <DDF>Parkinson's Disease</DDF> and <human>Healthy Controls</human>: A Cohort Study. <microbiome>Gut microbiome</microbiome> and <DDF>colonic inflammation</DDF> can be associated with the predisposition and progression of <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>). The presented study aimed to compare gastrointestinal microbiota composition between <human>patients</human> diagnosed with <DDF>PD</DDF> and treated only with <drug>Levodopa</drug> to <human>healthy controls</human>. In this prospective study, <human>patients</human> were recruited in 1 academic hospital from July 2019 to July 2020. The detailed demographic data and medical history were collected using a set of questionnaires. Fecal samples were obtained from all participants. <biomedical technique>Next-Generation Sequencing</biomedical technique> was used to assess the microbiota composition. The endpoint was the difference in composition of the <microbiome>gut microbiota</microbiome>. In this study, we enrolled 27 <human>hospitalized PD patients</human> with <DDF>well-controlled symptoms</DDF>. The control group included 44 <human>healthy subjects</human> matched for age. Among <human>PD patients</human>, our results presented a higher abundance of <i><bacteria>Bacteroides</i> phylum</bacteria>, class <i><bacteria>Corynebacteria</bacteria></i> among phylum <i><bacteria>Actinobacteria</bacteria></i>, class <i><bacteria>Deltaproteobacteria</bacteria></i> among phylum <i><bacteria>Proteobacteria</bacteria></i>, and genera such as <i><bacteria>Butyricimonas</bacteria>, <bacteria>Robinsoniella</bacteria></i>, and <i><bacteria>Flavonifractor</bacteria></i>. The species <i><bacteria>Akkermansia muciniphila</bacteria></i>, <i><bacteria>Eubacterium biforme</bacteria></i>, and <i><bacteria>Parabacteroides merdae</bacteria></i> were identified as more common in the <microbiome>gut microbiota</microbiome> of <human>PD patients</human>. In conclusion, the <human>patients</human> diagnosed with <DDF>PD</DDF> have significantly different gut microbiota profiles in comparison with <human>healthy controls</human>.",
"role": "assistant"
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34908715
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGut-brain axis: Synergistic approach. Since decades, there is a change in concept of the gut-brain axis. There is differential increase in evidences focusing on the bidirectional communication between the gut microbiome and the brain. It supports existence of far-reaching model of \"gut-brain axis.\" This axis is attaining more adherence to fields investigating biological and physiological footing of psychiatric, neuro-developmental, age-related, and neurodegenerative disorders. Many factors can change microbiota composition in early life as well as with the increasing age. Stress can affect the microbiota-gut-brain axis at every stages of life. Recent advances have involved the gut microbiota in many conditions including severe mental illness, autism, anxiety, obesity, Parkinson's disease, and Alzheimer's disease. The current studies target on elaborating the underlying mechanisms of microbiota-gut-brain axis and attempt to exemplify intervention and therapeutic strategies for neuropsychiatric disorders.",
"role": "user"
},
{
"content": "Gut-brain axis: Synergistic approach. Since decades, there is a change in concept of the gut-brain axis. There is differential increase in evidences focusing on the bidirectional communication between the <microbiome>gut microbiome</microbiome> and the <anatomical location>brain</anatomical location>. It supports existence of far-reaching model of \"gut-brain axis.\" This axis is attaining more adherence to fields investigating biological and physiological footing of <DDF>psychiatric, neuro-developmental, age-related, and neurodegenerative disorders</DDF>. Many factors can change microbiota composition in early life as well as with the increasing age. <DDF>Stress</DDF> can affect the microbiota-gut-brain axis at every stages of life. Recent advances have involved the <microbiome>gut microbiota</microbiome> in many conditions including <DDF>severe mental illness</DDF>, <DDF>autism</DDF>, <DDF>anxiety</DDF>, <DDF>obesity</DDF>, <DDF>Parkinson's disease</DDF>, and <DDF>Alzheimer's disease</DDF>. The current studies target on elaborating the underlying mechanisms of microbiota-gut-brain axis and attempt to exemplify intervention and therapeutic strategies for <DDF>neuropsychiatric disorders</DDF>.",
"role": "assistant"
}
] |
34970638
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nCUMS and dexamethasone induce depression-like phenotypes in mice by differentially altering gut microbiota and triggering macroglia activation. Although the link between gut microbiota and depression has been suggested, changes of gut microbiota vary largely among individuals with depression. Explore the heterogeneity of microbiota-gut-brain axis and new pathogenic characteristics in murine models of depression. Adolescent female mice were randomly divided into control (CON) group (n=10), chronic unexpected mild stress (CUMS) group (n=15) and dexamethasone (DEX) group (n=15). Mice in the DEX group were gavaged twice a day with 0.2 mg/kg of DEX for 5 weeks, whereas CON mice were given the same amount of solvent. Mice in the CUMS group were exposed to stressors. After behavioural evaluations, all mice were sacrificed for harvesting tissues and blood samples. Enzyme-linked immunosorbent assay (ELISA) was conducted for measuring levels of corticosterone (CORT) and interleukin-1β (IL-1β) in sera, whereas levels of protein expression in colon and hippocampal tissues were examined by western blot. Faecal microbial communities were analysed by sequencing 16S rDNAs. Mice in CUMS and DEX groups exhibited severe depression-like behaviours. Compared with CON mice, CUMS-exposed mice showed a significant increase in both α and β diversity. Prevotellaceae and Desulfovibrio were enriched, whereas Bacilli were decreased in the faeces of mice in the CUMS group. DEX-treated mice had a decrease in the abundance of <i>Clostridium XVIII</i>. Levels of occludin in colon tissue of DEX-treated mice were reduced. Relative to mice in the CON and CUMS groups, DEX-treated mice contained higher serum levels of CORT and IL-1β. Compared with CON mice, mice in the DEX and CUMS groups had higher levels of IL-1β in sera and lower levels of glial fibrillary acidic protein (GFAP), Nestin, Synapsin-1 and P2Y12 receptor in the hippocampus. Changes of gut microbiota diversity, intestinal integrity and neuroinflammation in the brain contribute to CUMS-induced depression, whereas pathobionts and excessive immunosuppression with damaged neuronal synapses is a basis of the DEX-induced depression.",
"role": "user"
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{
"content": "<DDF>CUMS</DDF> and <drug>dexamethasone</drug> induce <DDF>depression-like phenotypes</DDF> in <animal>mice</animal> by differentially altering <microbiome>gut microbiota</microbiome> and triggering macroglia activation. Although the link between <microbiome>gut microbiota</microbiome> and <DDF>depression</DDF> has been suggested, changes of <microbiome>gut microbiota</microbiome> vary largely among <human>individuals</human> with <DDF>depression</DDF>. Explore the heterogeneity of microbiota-gut-brain axis and new pathogenic characteristics in murine models of <DDF>depression</DDF>. <animal>Adolescent female mice</animal> were randomly divided into <animal>control (CON) group</animal> (n=10), chronic unexpected <animal>mild stress (CUMS) group</animal> (n=15) and <animal>dexamethasone (DEX) group</animal> (n=15). <animal>Mice</animal> in the <animal>DEX group</animal> were gavaged twice a day with 0.2 mg/kg of <drug>DEX</drug> for 5 weeks, whereas <animal>CON mice</animal> were given the same amount of <chemical>solvent</chemical>. <animal>Mice</animal> in the <animal>CUMS group</animal> were exposed to stressors. After behavioural evaluations, all <animal>mice</animal> were sacrificed for harvesting tissues and blood samples. <biomedical technique>Enzyme-linked immunosorbent assay</biomedical technique> (<biomedical technique>ELISA</biomedical technique>) was conducted for measuring levels of <chemical>corticosterone</chemical> (<chemical>CORT</chemical>) and <chemical>interleukin-1β</chemical> (<chemical>IL-1β</chemical>) in sera, whereas levels of protein expression in colon and hippocampal tissues were examined by <biomedical technique>western blot</biomedical technique>. Faecal microbial communities were analysed by <biomedical technique>sequencing 16S rDNAs</biomedical technique>. <animal>Mice</animal> in <animal>CUMS and DEX groups</animal> exhibited <DDF>severe depression-like behaviours</DDF>. Compared with <animal>CON mice</animal>, <animal>CUMS-exposed mice</animal> showed a significant increase in both α and β diversity. <bacteria>Prevotellaceae</bacteria> and <bacteria>Desulfovibrio</bacteria> were enriched, whereas <bacteria>Bacilli</bacteria> were decreased in the faeces of <animal>mice</animal> in the <animal>CUMS group</animal>. <animal>DEX-treated mice</animal> had a decrease in the abundance of <i><bacteria>Clostridium XVIII</bacteria></i>. Levels of <chemical>occludin</chemical> in colon tissue of <animal>DEX-treated mice</animal> were reduced. Relative to <animal>mice</animal> in the <animal>CON and CUMS groups</animal>, <animal>DEX-treated mice</animal> contained higher serum levels of <chemical>CORT</chemical> and <chemical>IL-1β</chemical>. Compared with <animal>CON mice</animal>, <animal>mice</animal> in the <animal>DEX and CUMS groups</animal> had higher levels of <chemical>IL-1β</chemical> in sera and lower levels of <chemical>glial fibrillary acidic protein</chemical> (<chemical>GFAP</chemical>), <chemical>Nestin</chemical>, <chemical>Synapsin-1</chemical> and <chemical>P2Y12 receptor</chemical> in the <anatomical location>hippocampus</anatomical location>. Changes of gut microbiota diversity, intestinal integrity and <DDF>neuroinflammation</DDF> in the <anatomical location>brain</anatomical location> contribute to <DDF>CUMS-induced depression</DDF>, whereas <microbiome>pathobionts</microbiome> and <DDF>excessive immunosuppression with damaged neuronal synapses</DDF> is a basis of the <DDF>DEX-induced depression</DDF>.",
"role": "assistant"
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34988495
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nCharacterization of the gut microbiota among Veterans with unique military-related exposures and high prevalence of chronic health conditions: A United States-Veteran Microbiome Project (US-VMP) study. The gut microbiome is impacted by environmental exposures and has been implicated in many physical and mental health conditions, including anxiety disorders, affective disorders, and trauma- and stressor-related disorders such as posttraumatic stress disorder (PTSD). United States (US) military Veterans are a unique population in that their military-related exposures can have consequences for both physical and mental health, but the gut microbiome of this population has been understudied. In this publication, we describe exposures, health conditions, and medication use of Veterans in the US Veteran Microbiome Project (US-VMP) and examine the associations between these characteristics and the gut microbiota. This cohort included 331 US Veterans seeking healthcare with the Veterans Health Administration who were 83% male with an average (±SD) age of 47.6 ± 13.4 years. The cohort displayed a high prevalence of PTSD (49.8%) and history of traumatic brain injuries (76.1%), and high current use of prescription medications (74.9%) to treat various acute and chronic conditions. We observed significant associations between the gut microbiota composition and gastroenteritis, peripheral vascular disease (PVD), bipolar disorders, symptoms of severe depression based on the Beck Depression Inventory, stimulant and opioid use disorders, beta-blockers, serotonin and norepinephrine reuptake inhibitor antidepressants, diabetes medications, and proton pump inhibitors. Many of the Veteran characteristics examined were associated with altered relative abundances of specific taxa. We found that PVD and cardiovascular disease were associated with lower microbiota diversity in the gut (i.e., α-diversity), while supplemental vitamin use was associated with higher α-diversity. Our study contributes novel insights as to whether the unique exposures of Veterans in this cohort correlate with gut microbiota characteristics and, in line with previous findings with other population-level studies of the microbiome, confirms associations between numerous health conditions and medications with the gut microbiome.",
"role": "user"
},
{
"content": "Characterization of the <microbiome>gut microbiota</microbiome> among <human>Veterans</human> with unique military-related exposures and high prevalence of <DDF>chronic health conditions</DDF>: A United States-Veteran Microbiome Project (US-VMP) study. The <microbiome>gut microbiome</microbiome> is impacted by environmental exposures and has been implicated in many physical and mental health conditions, including <DDF>anxiety disorders</DDF>, <DDF>affective disorders</DDF>, and <DDF>trauma- and stressor-related disorders</DDF> such as <DDF>posttraumatic stress disorder</DDF> (<DDF>PTSD</DDF>). <human>United States (US) military Veterans</human> are a unique population in that their military-related exposures can have consequences for both physical and mental health, but the <microbiome>gut microbiome</microbiome> of this population has been understudied. In this publication, we describe exposures, health conditions, and medication use of <human>Veterans</human> in the US Veteran Microbiome Project (US-VMP) and examine the associations between these characteristics and the <microbiome>gut microbiota</microbiome>. This cohort included 331 <human>US Veterans</human> seeking healthcare with the Veterans Health Administration who were 83% <human>male</human> with an average (±SD) age of 47.6 ± 13.4 years. The cohort displayed a high prevalence of <DDF>PTSD</DDF> (49.8%) and history of <DDF>traumatic brain injuries</DDF> (76.1%), and high current use of <drug>prescription medications</drug> (74.9%) to treat various acute and chronic conditions. We observed significant associations between the gut microbiota composition and <DDF>gastroenteritis</DDF>, <DDF>peripheral vascular disease</DDF> (<DDF>PVD</DDF>), <DDF>bipolar disorders</DDF>, symptoms of <DDF>severe depression</DDF> based on the Beck Depression Inventory, <DDF>stimulant and opioid use disorders</DDF>, <drug>beta-blockers</drug>, <drug>serotonin and norepinephrine reuptake inhibitor antidepressants</drug>, <drug>diabetes medications</drug>, and <drug>proton pump inhibitors</drug>. Many of the Veteran characteristics examined were associated with altered relative abundances of specific taxa. We found that <DDF>PVD</DDF> and <DDF>cardiovascular disease</DDF> were associated with lower microbiota diversity in the <anatomical location>gut</anatomical location> (i.e., α-diversity), while <dietary supplement>supplemental vitamin use</dietary supplement> was associated with higher α-diversity. Our study contributes novel insights as to whether the unique exposures of <human>Veterans</human> in this cohort correlate with gut microbiota characteristics and, in line with previous findings with other population-level studies of the microbiome, confirms associations between numerous health conditions and medications with the <microbiome>gut microbiome</microbiome>.",
"role": "assistant"
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35069178
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nThe Gut-Brain Axis and Its Relation to Parkinson's Disease: A Review. Parkinson's disease is a chronic neurodegenerative disease characterized by the accumulation of misfolded alpha-synuclein protein (Lewy bodies) in dopaminergic neurons of the <i>substantia nigra</i> and other related circuitry, which contribute to the development of both motor (bradykinesia, tremors, stiffness, abnormal gait) and non-motor symptoms (gastrointestinal issues, urinogenital complications, olfaction dysfunction, cognitive impairment). Despite tremendous progress in the field, the exact pathways and mechanisms responsible for the initiation and progression of this disease remain unclear. However, recent research suggests a potential relationship between the commensal gut bacteria and the brain capable of influencing neurodevelopment, brain function and health. This bidirectional communication is often referred to as the microbiome-gut-brain axis. Accumulating evidence suggests that the onset of non-motor symptoms, such as gastrointestinal manifestations, often precede the onset of motor symptoms and disease diagnosis, lending support to the potential role that the microbiome-gut-brain axis might play in the underlying pathological mechanisms of Parkinson's disease. This review will provide an overview of and critically discuss the current knowledge of the relationship between the gut microbiota and Parkinson's disease. We will discuss the role of α-synuclein in non-motor disease pathology, proposed pathways constituting the connection between the gut microbiome and the brain, existing evidence related to pre- and probiotic interventions. Finally, we will highlight the potential opportunity for the development of novel preventative measures and therapeutic options that could target the microbiome-gut-brain axis in the context of Parkinson's disease.",
"role": "user"
},
{
"content": "The Gut-Brain Axis and Its Relation to <DDF>Parkinson's Disease</DDF>: A Review. <DDF>Parkinson's disease</DDF> is a <DDF>chronic neurodegenerative disease</DDF> characterized by the accumulation of <chemical>misfolded alpha-synuclein protein</chemical> (<chemical>Lewy bodies</chemical>) in dopaminergic neurons of the <i><anatomical location>substantia nigra</anatomical location></i> and other related circuitry, which contribute to the development of both motor (<DDF>bradykinesia</DDF>, <DDF>tremors</DDF>, <DDF>stiffness</DDF>, <DDF>abnormal gait</DDF>) and <DDF>non-motor symptoms</DDF> (<DDF>gastrointestinal issues</DDF>, <DDF>urinogenital complications</DDF>, <DDF>olfaction dysfunction</DDF>, <DDF>cognitive impairment</DDF>). Despite tremendous progress in the field, the exact pathways and mechanisms responsible for the initiation and progression of this disease remain unclear. However, recent research suggests a potential relationship between the <bacteria>commensal gut bacteria</bacteria> and the <anatomical location>brain</anatomical location> capable of influencing neurodevelopment, brain function and health. This bidirectional communication is often referred to as the microbiome-gut-brain axis. Accumulating evidence suggests that the onset of <DDF>non-motor symptoms</DDF>, such as <DDF>gastrointestinal manifestations</DDF>, often precede the onset of <DDF>motor symptoms</DDF> and disease diagnosis, lending support to the potential role that the microbiome-gut-brain axis might play in the underlying pathological mechanisms of <DDF>Parkinson's disease</DDF>. This review will provide an overview of and critically discuss the current knowledge of the relationship between the <microbiome>gut microbiota</microbiome> and <DDF>Parkinson's disease</DDF>. We will discuss the role of <chemical>α-synuclein</chemical> in non-motor disease pathology, proposed pathways constituting the connection between the <microbiome>gut microbiome</microbiome> and the <anatomical location>brain</anatomical location>, existing evidence related to pre- and probiotic interventions. Finally, we will highlight the potential opportunity for the development of novel preventative measures and therapeutic options that could target the microbiome-gut-brain axis in the context of <DDF>Parkinson's disease</DDF>.",
"role": "assistant"
}
] |
35203906
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nParkinson's Disease in Light of the COVID-19 Pandemic. In this review we attempt to collate the existing scientific evidence regarding the possible role of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the pathophysiology of Parkinson's disease (PD), as well as to investigate the impact of PD/parkinsonism on the clinical course of the viral infection itself. Since etiology of PD is not completely understood, various studies suggest different potential links between coronavirus disease 2019 (COVID-19) and PD. Suggested connections include, among others, similar prodromal symptoms, renin-angiotensin-aldosterone system involvement, or gut microbiome dysbiosis participation. Despite the initial assumptions that, as a mainly elderly population suffering from rigidity of respiratory muscles, impairment of cough reflex, and dyspnea, PD patients would be more susceptible to viral infection, and would experience a more aggressive course of COVID-19, the published scientific reports contain mutually exclusive data that require further investigation and meta-analysis.",
"role": "user"
},
{
"content": "<DDF>Parkinson's Disease</DDF> in Light of the COVID-19 Pandemic. In this review we attempt to collate the existing scientific evidence regarding the possible role of severe acute respiratory syndrome coronavirus 2 (<DDF>SARS-CoV-2</DDF>) in the pathophysiology of <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>), as well as to investigate the impact of <DDF>PD/parkinsonism</DDF> on the clinical course of the <DDF>viral infection</DDF> itself. Since etiology of <DDF>PD</DDF> is not completely understood, various studies suggest different potential links between <DDF>coronavirus disease 2019</DDF> (<DDF>COVID-19</DDF>) and <DDF>PD</DDF>. Suggested connections include, among others, similar prodromal symptoms, renin-angiotensin-aldosterone system involvement, or <DDF>gut microbiome dysbiosis</DDF> participation. Despite the initial assumptions that, as a mainly <human>elderly population</human> suffering from <DDF>rigidity of respiratory muscles</DDF>, <DDF>impairment of cough reflex</DDF>, and <DDF>dyspnea</DDF>, <human>PD patients</human> would be more susceptible to <DDF>viral infection</DDF>, and would experience a more aggressive course of <DDF>COVID-19</DDF>, the published scientific reports contain mutually exclusive data that require further investigation and meta-analysis.",
"role": "assistant"
}
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35207632
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGastrointestinal Dysfunction in Parkinson's Disease: Current and Potential Therapeutics. Abnormalities in the gastrointestinal (GI) tract of Parkinson's disease (PD) sufferers were first reported over 200 years ago; however, the extent and role of GI dysfunction in PD disease progression is still unknown. GI dysfunctions, including dysphagia, gastroparesis, and constipation, are amongst the most prevalent non-motor symptoms in PD. These symptoms not only impact patient quality of life, but also complicate disease management. Conventional treatment pathways for GI dysfunctions (i.e., constipation), such as increasing fibre and fluid intake, and the use of over-the-counter laxatives, are generally ineffective in PD patients, and approved compounds such as guanylate cyclase C agonists and selective 5-hyroxytryptamine 4 receptor agonists have demonstrated limited efficacy. Thus, identification of potential targets for novel therapies to alleviate PD-induced GI dysfunctions are essential to improve clinical outcomes and quality of life in people with PD. Unlike the central nervous system (CNS), where PD pathology and the mechanisms involved in CNS damage are relatively well characterised, the effect of PD at the cellular and tissue level in the enteric nervous system (ENS) remains unclear, making it difficult to alleviate or reverse GI symptoms. However, the resurgence of interest in understanding how the GI tract is involved in various disease states, such as PD, has resulted in the identification of novel therapeutic avenues. This review focuses on common PD-related GI symptoms, and summarizes the current treatments available and their limitations. We propose that by targeting the intestinal barrier, ENS, and/or the gut microbiome, may prove successful in alleviating PD-related GI symptoms, and discuss emerging therapies and potential drugs that could be repurposed to target these areas.",
"role": "user"
},
{
"content": "<DDF>Gastrointestinal Dysfunction</DDF> in <DDF>Parkinson's Disease</DDF>: Current and Potential Therapeutics. Abnormalities in the <anatomical location>gastrointestinal (GI) tract</anatomical location> of <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>) sufferers were first reported over 200 years ago; however, the extent and role of <DDF>GI dysfunction</DDF> in <DDF>PD</DDF> disease progression is still unknown. <DDF>GI dysfunctions</DDF>, including <DDF>dysphagia</DDF>, <DDF>gastroparesis</DDF>, and <DDF>constipation</DDF>, are amongst the most prevalent <DDF>non-motor symptoms</DDF> in <DDF>PD</DDF>. These symptoms not only impact patient quality of life, but also complicate disease management. Conventional treatment pathways for <DDF>GI dysfunctions</DDF> (i.e., <DDF>constipation</DDF>), such as increasing fibre and fluid intake, and the use of <drug>over-the-counter laxatives</drug>, are generally ineffective in <human>PD patients</human>, and approved compounds such as <drug>guanylate cyclase C agonists</drug> and <drug>selective 5-hyroxytryptamine 4 receptor agonists</drug> have demonstrated limited efficacy. Thus, identification of potential targets for novel therapies to alleviate <DDF>PD-induced GI dysfunctions</DDF> are essential to improve clinical outcomes and quality of life in <human>people</human> with <DDF>PD</DDF>. Unlike the central nervous system (CNS), where <DDF>PD</DDF> pathology and the mechanisms involved in <DDF>CNS damage</DDF> are relatively well characterised, the effect of <DDF>PD</DDF> at the cellular and tissue level in the <anatomical location>enteric nervous system</anatomical location> (<anatomical location>ENS</anatomical location>) remains unclear, making it difficult to alleviate or reverse <DDF>GI symptoms</DDF>. However, the resurgence of interest in understanding how the <anatomical location>GI tract</anatomical location> is involved in various disease states, such as <DDF>PD</DDF>, has resulted in the identification of novel therapeutic avenues. This review focuses on common <DDF>PD-related GI symptoms</DDF>, and summarizes the current treatments available and their limitations. We propose that by targeting the <anatomical location>intestinal barrier</anatomical location>, <anatomical location>ENS</anatomical location>, and/or the <microbiome>gut microbiome</microbiome>, may prove successful in alleviating <DDF>PD-related GI symptoms</DDF>, and discuss emerging therapies and potential drugs that could be repurposed to target these areas.",
"role": "assistant"
}
] |
35281490
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nMechanistic Insights Into Gut Microbiome Dysbiosis-Mediated Neuroimmune Dysregulation and Protein Misfolding and Clearance in the Pathogenesis of Chronic Neurodegenerative Disorders. The human gut microbiota is a complex, dynamic, and highly diverse community of microorganisms. Beginning as early as <i>in utero</i> fetal development and continuing through birth to late-stage adulthood, the crosstalk between the gut microbiome and brain is essential for modulating various metabolic, neurodevelopmental, and immune-related pathways. Conversely, microbial dysbiosis - defined as alterations in richness and relative abundances - of the gut is implicated in the pathogenesis of several chronic neurological and neurodegenerative disorders. Evidence from large-population cohort studies suggests that individuals with neurodegenerative conditions have an altered gut microbial composition as well as microbial and serum metabolomic profiles distinct from those in the healthy population. Dysbiosis is also linked to psychiatric and gastrointestinal complications - comorbidities often associated with the prodromal phase of Parkinson's disease (PD) and Alzheimer's disease (AD). Studies have identified potential mediators that link gut dysbiosis and neurological disorders. Recent findings have also elucidated the potential mechanisms of disease pathology in the enteric nervous system prior to the onset of neurodegeneration. This review highlights the functional pathways and mechanisms, particularly gut microbe-induced chronic inflammation, protein misfolding, propagation of disease-specific pathology, defective protein clearance, and autoimmune dysregulation, linking gut microbial dysbiosis and neurodegeneration. In addition, we also discuss how pathogenic transformation of microbial composition leads to increased endotoxin production and fewer beneficial metabolites, both of which could trigger immune cell activation and enteric neuronal dysfunction. These can further disrupt intestinal barrier permeability, aggravate the systemic pro-inflammatory state, impair blood-brain barrier permeability and recruit immune mediators leading to neuroinflammation and neurodegeneration. Continued biomedical advances in understanding the microbiota-gut-brain axis will extend the frontier of neurodegenerative disorders and enable the utilization of novel diagnostic and therapeutic strategies to mitigate the pathological burden of these diseases.",
"role": "user"
},
{
"content": "Mechanistic Insights Into <DDF>Gut Microbiome Dysbiosis-Mediated Neuroimmune Dysregulation</DDF> and <DDF>Protein Misfolding and Clearance</DDF> in the Pathogenesis of <DDF>Chronic Neurodegenerative Disorders</DDF>. The <microbiome>human gut microbiota</microbiome> is a complex, dynamic, and highly diverse community of microorganisms. Beginning as early as <i>in utero</i> fetal development and continuing through birth to late-stage adulthood, the crosstalk between the <microbiome>gut microbiome</microbiome> and <anatomical location>brain</anatomical location> is essential for modulating various metabolic, neurodevelopmental, and immune-related pathways. Conversely, <DDF>microbial dysbiosis</DDF> - defined as alterations in richness and relative abundances - of the <anatomical location>gut</anatomical location> is implicated in the pathogenesis of several <DDF>chronic neurological and neurodegenerative disorders</DDF>. Evidence from large-population cohort studies suggests that individuals with <DDF>neurodegenerative conditions</DDF> have an altered gut microbial composition as well as microbial and serum metabolomic profiles distinct from those in the healthy population. <DDF>Dysbiosis</DDF> is also linked to <DDF>psychiatric and gastrointestinal complications</DDF> - comorbidities often associated with the prodromal phase of <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>) and <DDF>Alzheimer's disease</DDF> (<DDF>AD</DDF>). Studies have identified potential mediators that link <DDF>gut dysbiosis</DDF> and <DDF>neurological disorders</DDF>. Recent findings have also elucidated the potential mechanisms of disease pathology in the enteric nervous system prior to the onset of <DDF>neurodegeneration</DDF>. This review highlights the functional pathways and mechanisms, particularly <DDF>gut microbe-induced chronic inflammation</DDF>, <DDF>protein misfolding</DDF>, propagation of <DDF>disease-specific pathology</DDF>, <DDF>defective protein clearance</DDF>, and <DDF>autoimmune dysregulation</DDF>, linking <DDF>gut microbial dysbiosis</DDF> and <DDF>neurodegeneration</DDF>. In addition, we also discuss how pathogenic transformation of microbial composition leads to increased endotoxin production and fewer <chemical>beneficial metabolites</chemical>, both of which could trigger immune cell activation and <DDF>enteric neuronal dysfunction</DDF>. These can further disrupt intestinal barrier permeability, aggravate the <DDF>systemic pro-inflammatory state</DDF>, impair blood-brain barrier permeability and recruit immune mediators leading to <DDF>neuroinflammation</DDF> and <DDF>neurodegeneration</DDF>. Continued biomedical advances in understanding the microbiota-gut-brain axis will extend the frontier of <DDF>neurodegenerative disorders</DDF> and enable the utilization of novel diagnostic and therapeutic strategies to mitigate the pathological burden of these diseases.",
"role": "assistant"
}
] |
35317228
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nAnalysis methods for the gut microbiome in neuropsychiatric and neurodegenerative disorders. For a long time, the central nervous system was believed to be the only regulator of cognitive functions. However, accumulating evidence suggests that the composition of the microbiome is strongly associated with brain functions and diseases. Indeed, the gut microbiome is involved in neuropsychiatric diseases (e.g., depression, autism spectrum disorder, and anxiety) and neurodegenerative diseases (e.g., Parkinson's disease and Alzheimer's disease). In this review, we provide an overview of the link between the gut microbiome and neuropsychiatric or neurodegenerative disorders. We also introduce analytical methods used to assess the connection between the gut microbiome and the brain. The limitations of the methods used at present are also discussed. The accurate translation of the microbiome information to brain disorder could promote better understanding of neuronal diseases and aid in finding alternative and novel therapies.",
"role": "user"
},
{
"content": "Analysis methods for the <microbiome>gut microbiome</microbiome> in <DDF>neuropsychiatric and neurodegenerative disorders</DDF>. For a long time, the central nervous system was believed to be the only regulator of cognitive functions. However, accumulating evidence suggests that the composition of the microbiome is strongly associated with brain functions and diseases. Indeed, the <microbiome>gut microbiome</microbiome> is involved in <DDF>neuropsychiatric diseases</DDF> (e.g., <DDF>depression</DDF>, <DDF>autism spectrum disorder</DDF>, and <DDF>anxiety</DDF>) and <DDF>neurodegenerative diseases</DDF> (e.g., <DDF>Parkinson's disease</DDF> and <DDF>Alzheimer's disease</DDF>). In this review, we provide an overview of the link between the <microbiome>gut microbiome</microbiome> and <DDF>neuropsychiatric or neurodegenerative disorders</DDF>. We also introduce analytical methods used to assess the connection between the <microbiome>gut microbiome</microbiome> and the <anatomical location>brain</anatomical location>. The limitations of the methods used at present are also discussed. The accurate translation of the microbiome information to <DDF>brain disorder</DDF> could promote better understanding of <DDF>neuronal diseases</DDF> and aid in finding alternative and novel therapies.",
"role": "assistant"
}
] |
35327401
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\n<i>Drosophila</i> Model for Studying Gut Microbiota in Behaviors and Neurodegenerative Diseases. Mounting evidence indicates that the gut microbiota is linked to several physiological processes and disease development in mammals; however, the underlying mechanisms remained unexplored mostly due to the complexity of the mammalian gut microbiome. The fruit fly, <i>Drosophila melanogaster</i>, is a valuable animal model for studying host-gut microbiota interactions in translational aspects. The availability of powerful genetic tools and resources in <i>Drosophila</i> allowed the scientists to unravel the mechanisms by which the gut microbes affect fitness, health, and behavior of their hosts. <i>Drosophila</i> models have been extensively used not only to study animal behaviors (i.e., courtship, aggression, sleep, and learning & memory), but also some human related neurodegenerative diseases (i.e., Alzheimer's disease and Parkinson's disease) in the past. This review comprehensively summarizes the current understanding of the gut microbiota of <i>Drosophila</i> and its impact on fly behavior, physiology, and neurodegenerative diseases.",
"role": "user"
},
{
"content": "<i>Drosophila</i> Model for Studying <microbiome>Gut Microbiota</microbiome> in Behaviors and <DDF>Neurodegenerative Diseases</DDF>. Mounting evidence indicates that the <microbiome>gut microbiota</microbiome> is linked to several physiological processes and disease development in <animal>mammals</animal>; however, the underlying mechanisms remained unexplored mostly due to the complexity of the <microbiome>mammalian gut microbiome</microbiome>. The <animal>fruit fly</animal>, <i><animal>Drosophila melanogaster</animal></i>, is a valuable animal model for studying host-gut microbiota interactions in translational aspects. The availability of powerful genetic tools and resources in <i><animal>Drosophila</animal></i> allowed the scientists to unravel the mechanisms by which the gut microbes affect fitness, health, and behavior of their hosts. <i>Drosophila</i> models have been extensively used not only to study animal behaviors (i.e., courtship, aggression, sleep, and learning & memory), but also some <DDF>human related neurodegenerative diseases</DDF> (i.e., <DDF>Alzheimer's disease</DDF> and <DDF>Parkinson's disease</DDF>) in the past. This review comprehensively summarizes the current understanding of the <microbiome>gut microbiota</microbiome> of <i><animal>Drosophila</animal></i> and its impact on fly behavior, physiology, and <DDF>neurodegenerative diseases</DDF>.",
"role": "assistant"
}
] |
35565918
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nThe Therapeutic Role of Ketogenic Diet in Neurological Disorders. The ketogenic diet (KD) is a high-fat, low-carbohydrate and adequate-protein diet that has gained popularity in recent years in the context of neurological diseases (NDs). The complexity of the pathogenesis of these diseases means that effective forms of treatment are still lacking. Conventional therapy is often associated with increasing tolerance and/or drug resistance. Consequently, more effective therapeutic strategies are being sought to increase the effectiveness of available forms of therapy and improve the quality of life of patients. For the moment, it seems that KD can provide therapeutic benefits in patients with neurological problems by effectively controlling the balance between pro- and antioxidant processes and pro-excitatory and inhibitory neurotransmitters, and modulating inflammation or changing the composition of the gut microbiome. In this review we evaluated the potential therapeutic efficacy of KD in epilepsy, depression, migraine, Alzheimer's disease and Parkinson's disease. In our opinion, KD should be considered as an adjuvant therapeutic option for some neurological diseases.",
"role": "user"
},
{
"content": "The Therapeutic Role of Ketogenic Diet in <DDF>Neurological Disorders</DDF>. The ketogenic diet (KD) is a high-fat, low-carbohydrate and adequate-protein diet that has gained popularity in recent years in the context of <DDF>neurological diseases</DDF> (<DDF>NDs</DDF>). The complexity of the pathogenesis of these diseases means that effective forms of treatment are still lacking. Conventional therapy is often associated with increasing tolerance and/or drug resistance. Consequently, more effective therapeutic strategies are being sought to increase the effectiveness of available forms of therapy and improve the quality of life of <human>patients</human>. For the moment, it seems that KD can provide therapeutic benefits in <human>patients</human> with <DDF>neurological problems</DDF> by effectively controlling the balance between pro- and antioxidant processes and <chemical>pro-excitatory and inhibitory neurotransmitters</chemical>, and modulating <DDF>inflammation</DDF> or changing the composition of the <microbiome>gut microbiome</microbiome>. In this review we evaluated the potential therapeutic efficacy of KD in <DDF>epilepsy</DDF>, <DDF>depression</DDF>, <DDF>migraine</DDF>, <DDF>Alzheimer's disease</DDF> and <DDF>Parkinson's disease</DDF>. In our opinion, KD should be considered as an adjuvant therapeutic option for some <DDF>neurological diseases</DDF>.",
"role": "assistant"
}
] |
35571084
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nUsing <i>Caenorhabditis elegans</i> to Model Therapeutic Interventions of Neurodegenerative Diseases Targeting Microbe-Host Interactions. Emerging evidence from both clinical studies and animal models indicates the importance of the interaction between the gut microbiome and the brain in the pathogenesis of neurodegenerative diseases (NDs). Although how microbes modulate neurodegeneration is still mostly unclear, recent studies have started to probe into the mechanisms for the communication between microbes and hosts in NDs. In this review, we highlight the advantages of using <i>Caenorhabditis elegans</i> (C. elegans) to disentangle the microbe-host interaction that regulates neurodegeneration. We summarize the microbial pro- and anti-neurodegenerative factors identified using the <i>C. elegans</i> ND models and the effects of many are confirmed in mouse models. Specifically, we focused on the role of bacterial amyloid proteins, such as curli, in promoting proteotoxicity and neurodegeneration by cross-seeding the aggregation of endogenous ND-related proteins, such as α-synuclein. Targeting bacterial amyloid production may serve as a novel therapeutic strategy for treating NDs, and several compounds, such as epigallocatechin-3-gallate (EGCG), were shown to suppress neurodegeneration at least partly by inhibiting curli production. Because bacterial amyloid fibrils contribute to biofilm formation, inhibition of amyloid production often leads to the disruption of biofilms. Interestingly, from a list of 59 compounds that showed neuroprotective effects in <i>C. elegans</i> and mouse ND models, we found that about half of them are known to inhibit bacterial growth or biofilm formation, suggesting a strong correlation between the neuroprotective and antibiofilm activities. Whether these potential therapeutics indeed protect neurons from proteotoxicity by inhibiting the cross-seeding between bacterial and human amyloid proteins awaits further investigations. Finally, we propose to screen the long list of antibiofilm agents, both FDA-approved drugs and novel compounds, for their neuroprotective effects and develop new pharmaceuticals that target the gut microbiome for the treatment of NDs. To this end, the <i>C. elegans</i> ND models can serve as a platform for fast, high-throughput, and low-cost drug screens that target the microbe-host interaction in NDs.",
"role": "user"
},
{
"content": "Using <i><animal>Caenorhabditis elegans</animal></i> to Model Therapeutic Interventions of <DDF>Neurodegenerative Diseases</DDF> Targeting Microbe-Host Interactions. Emerging evidence from both clinical studies and animal models indicates the importance of the interaction between the <microbiome>gut microbiome</microbiome> and the <anatomical location>brain</anatomical location> in the pathogenesis of <DDF>neurodegenerative diseases</DDF> (<DDF>NDs</DDF>). Although how microbes modulate <DDF>neurodegeneration</DDF> is still mostly unclear, recent studies have started to probe into the mechanisms for the communication between microbes and hosts in <DDF>NDs</DDF>. In this review, we highlight the advantages of using <i><animal>Caenorhabditis elegans</animal></i> (<animal>C. elegans</animal>) to disentangle the microbe-host interaction that regulates <DDF>neurodegeneration</DDF>. We summarize the microbial pro- and anti-neurodegenerative factors identified using the <i>C. elegans</i> ND models and the effects of many are confirmed in mouse models. Specifically, we focused on the role of <chemical>bacterial amyloid proteins</chemical>, such as <chemical>curli</chemical>, in promoting <DDF>proteotoxicity</DDF> and <DDF>neurodegeneration</DDF> by cross-seeding the aggregation of <chemical>endogenous ND-related proteins</chemical>, such as <chemical>α-synuclein</chemical>. Targeting bacterial amyloid production may serve as a novel therapeutic strategy for treating <DDF>NDs</DDF>, and several compounds, such as <chemical>epigallocatechin-3-gallate</chemical> (<chemical>EGCG</chemical>), were shown to suppress <DDF>neurodegeneration</DDF> at least partly by inhibiting curli production. Because <chemical>bacterial amyloid fibrils</chemical> contribute to <DDF>biofilm formation</DDF>, inhibition of amyloid production often leads to the disruption of biofilms. Interestingly, from a list of 59 compounds that showed neuroprotective effects in <i><animal>C. elegans</animal></i> and mouse ND models, we found that about half of them are known to inhibit <DDF>bacterial</DDF> growth or <DDF>biofilm formation</DDF>, suggesting a strong correlation between the neuroprotective and antibiofilm activities. Whether these potential therapeutics indeed protect <anatomical location>neurons</anatomical location> from <DDF>proteotoxicity</DDF> by inhibiting the cross-seeding between <chemical>bacterial and human amyloid proteins</chemical> awaits further investigations. Finally, we propose to screen the long list of <drug>antibiofilm agents</drug>, both <drug>FDA-approved drugs</drug> and <chemical>novel compounds</chemical>, for their neuroprotective effects and develop new pharmaceuticals that target the <microbiome>gut microbiome</microbiome> for the treatment of <DDF>NDs</DDF>. To this end, the <i>C. elegans</i> ND models can serve as a platform for fast, high-throughput, and low-cost drug <biomedical technique>screens</biomedical technique> that target the microbe-host interaction in <DDF>NDs</DDF>.",
"role": "assistant"
}
] |
35654142
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nMechanistic insights into accelerated α-synuclein aggregation mediated by human microbiome-associated functional amyloids. The gut microbiome has been shown to have key implications in the pathogenesis of Parkinson's disease (PD). The Escherichia coli functional amyloid CsgA is known to accelerate α-synuclein aggregation in vitro and induce PD symptoms in mice. However, the mechanism governing CsgA-mediated acceleration of α-synuclein aggregation is unclear. Here, we show that CsgA can form stable homodimeric species that correlate with faster α-synuclein amyloid aggregation. Furthermore, we identify and characterize new CsgA homologs encoded by bacteria present in the human microbiome. These CsgA homologs display diverse aggregation kinetics, and they differ in their ability to modulate α-synuclein aggregation. Remarkably, we demonstrate that slowing down CsgA aggregation leads to an increased acceleration of α-synuclein aggregation, suggesting that the intrinsic amyloidogenicity of gut bacterial CsgA homologs affects their ability to accelerate α-synuclein aggregation. Finally, we identify a complex between CsgA and α-synuclein that functions as a platform to accelerate α-synuclein aggregation. Taken together, our work reveals complex interplay between bacterial amyloids and α-synuclein that better informs our understanding of PD causation.",
"role": "user"
},
{
"content": "Mechanistic insights into accelerated α-synuclein aggregation mediated by <chemical>human microbiome-associated functional amyloids</chemical>. The <microbiome>gut microbiome</microbiome> has been shown to have key implications in the pathogenesis of <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>). The <gene>Escherichia coli functional amyloid CsgA</gene> is known to accelerate α-synuclein aggregation in vitro and induce <DDF>PD symptoms</DDF> in <animal>mice</animal>. However, the mechanism governing CsgA-mediated acceleration of α-synuclein aggregation is unclear. Here, we show that <gene>CsgA</gene> can form stable homodimeric species that correlate with faster α-synuclein amyloid aggregation. Furthermore, we identify and characterize new <gene>CsgA homologs</gene> encoded by bacteria present in the <microbiome>human microbiome</microbiome>. These <gene>CsgA homologs</gene> display diverse aggregation kinetics, and they differ in their ability to modulate α-synuclein aggregation. Remarkably, we demonstrate that slowing down CsgA aggregation leads to an increased acceleration of α-synuclein aggregation, suggesting that the intrinsic amyloidogenicity of <gene>gut bacterial CsgA homologs</gene> affects their ability to accelerate α-synuclein aggregation. Finally, we identify a complex between <gene>CsgA</gene> and α-synuclein that functions as a platform to accelerate α-synuclein aggregation. Taken together, our work reveals complex interplay between bacterial amyloids and α-synuclein that better informs our understanding of <DDF>PD</DDF> causation.",
"role": "assistant"
}
] |
35722294
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nIntegrated Microbiome and Host Transcriptome Profiles Link Parkinson's Disease to <i>Blautia</i> Genus: Evidence From Feces, Blood, and Brain. A link between the gut microbiome and Parkinson's disease (PD) has been intensively studied, and more than 100 differential genera were identified across the studies. However, the predominant genera contributing to PD remain poorly understood. Inspired by recent advances showing microbiota distribution in the blood and brain, we, here, comprehensively investigated currently available fecal microbiome data (1,914 samples) to identify significantly altered genera, which were further validated by comparison to the results from microbiome analysis of blood (85 samples) and brain (268 samples). Our data showed that the composition of fecal microbiota was different from that of blood and brain. We found that <i>Blautia</i> was the unique genus consistently depleted across feces, blood, and brain samples of PD patients (<i>P</i> < 0.05), despite using rigorous criteria to remove contaminants. Moreover, enrichment analyses revealed that host genes correlated with <i>Blautia</i> genus abundance were mainly involved in mitochondrial function and energy metabolism, and mapped to neurodegenerative diseases (NDDs) and metabolic diseases. A random forest classifier constructed with fecal microbiota data demonstrated that <i>Blautia</i> genus was an important feature contributing to discriminating PD patients from controls [receiver operating characteristic (ROC)-area under curve (AUC) = 0.704, precision-recall curve (PRC)-AUC = 0.787]. Through the integration of microbiome and transcriptome, our study depicted microbial profiles in the feces, blood, and brain of PD patients, and identified <i>Blautia</i> genus as a potential genus linked to PD. Further studies are greatly encouraged to determine the role of <i>Blautia</i> genus in the pathogenesis of PD.",
"role": "user"
},
{
"content": "Integrated Microbiome and Host Transcriptome Profiles Link <DDF>Parkinson's Disease</DDF> to <i><bacteria>Blautia</bacteria></i> Genus: Evidence From Feces, Blood, and <anatomical location>Brain</anatomical location>. A link between the <microbiome>gut microbiome</microbiome> and <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>) has been intensively studied, and more than 100 differential genera were identified across the studies. However, the predominant genera contributing to <DDF>PD</DDF> remain poorly understood. Inspired by recent advances showing microbiota distribution in the blood and <anatomical location>brain</anatomical location>, we, here, comprehensively investigated currently available fecal microbiome data (1,914 samples) to identify significantly altered genera, which were further validated by comparison to the results from microbiome analysis of blood (85 samples) and <anatomical location>brain</anatomical location> (268 samples). Our data showed that the composition of <microbiome>fecal microbiota</microbiome> was different from that of blood and <anatomical location>brain</anatomical location>. We found that <i><bacteria>Blautia</bacteria></i> was the unique genus consistently depleted across feces, blood, and <anatomical location>brain</anatomical location> samples of <human>PD patients</human> (<i>P</i> < 0.05), despite using rigorous criteria to remove contaminants. Moreover, enrichment analyses revealed that <gene>host genes</gene> correlated with <i><bacteria>Blautia</bacteria></i> genus abundance were mainly involved in mitochondrial function and energy metabolism, and mapped to <DDF>neurodegenerative diseases</DDF> (<DDF>NDDs</DDF>) and <DDF>metabolic diseases</DDF>. A <statistical technique>random forest classifier</statistical technique> constructed with fecal microbiota data demonstrated that <i><bacteria>Blautia</bacteria></i> genus was an important feature contributing to discriminating <human>PD patients</human> from <human>controls</human> [<statistical technique>receiver operating characteristic (ROC)-area under curve (AUC)</statistical technique> = 0.704, <statistical technique>precision-recall curve (PRC)-AUC</statistical technique> = 0.787]. Through the integration of microbiome and transcriptome, our study depicted microbial profiles in the feces, blood, and <anatomical location>brain</anatomical location> of <human>PD patients</human>, and identified <i><bacteria>Blautia</bacteria></i> genus as a potential genus linked to <DDF>PD</DDF>. Further studies are greatly encouraged to determine the role of <i><bacteria>Blautia</bacteria></i> genus in the pathogenesis of <DDF>PD</DDF>.",
"role": "assistant"
}
] |
35798742
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nOral and gut dysbiosis leads to functional alterations in Parkinson's disease. Although several studies have identified a distinct gut microbial composition in Parkinson's disease (PD), few studies have investigated the oral microbiome or functional alteration of the microbiome in PD. We aimed to investigate the connection between the oral and gut microbiome and the functional changes in the PD-specific gut microbiome using shotgun metagenomic sequencing. The taxonomic composition of the oral and gut microbiome was significantly different between PD patients and healthy controls (P = 0.003 and 0.001, respectively). Oral Lactobacillus was more abundant in PD patients and was associated with opportunistic pathogens in the gut (FDR-adjusted P < 0.038). Functional analysis revealed that microbial gene markers for glutamate and arginine biosynthesis were downregulated, while antimicrobial resistance gene markers were upregulated in PD patients than healthy controls (all P < 0.001). We identified a connection between the oral and gut microbiota in PD, which might lead to functional alteration of the microbiome in PD.",
"role": "user"
},
{
"content": "<DDF>Oral and gut dysbiosis</DDF> leads to functional alterations in <DDF>Parkinson's disease</DDF>. Although several studies have identified a distinct gut microbial composition in <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>), few studies have investigated the <microbiome>oral microbiome</microbiome> or functional alteration of the microbiome in <DDF>PD</DDF>. We aimed to investigate the connection between the <microbiome>oral and gut microbiome</microbiome> and the functional changes in the <microbiome>PD-specific gut microbiome</microbiome> using <biomedical technique>shotgun metagenomic sequencing</biomedical technique>. The taxonomic composition of the <microbiome>oral and gut microbiome</microbiome> was significantly different between <human>PD patients</human> and <human>healthy controls</human> (P = 0.003 and 0.001, respectively). <bacteria>Oral Lactobacillus</bacteria> was more abundant in <human>PD patients</human> and was associated with opportunistic pathogens in the <anatomical location>gut</anatomical location> (FDR-adjusted P < 0.038). Functional analysis revealed that microbial gene markers for <chemical>glutamate</chemical> and <chemical>arginine</chemical> biosynthesis were downregulated, while antimicrobial resistance gene markers were upregulated in <human>PD patients</human> than <human>healthy controls</human> (all P < 0.001). We identified a connection between the <microbiome>oral and gut microbiota</microbiome> in <DDF>PD</DDF>, which might lead to functional alteration of the microbiome in <DDF>PD</DDF>.",
"role": "assistant"
}
] |
36056574
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nA Pilot Study of the Gut Microbiota Associated With Depressive Symptoms and Sleep Disturbance Among Chinese and Korean Immigrants in the United States. Depression is prevalent among Asian Americans (AsA) during the COVID-19 pandemic, and depression often leads to sleep disturbance in this population. The gut microbiota (GM) plays a critical role in mental health and sleep quality, and the composition of the GM is largely unknown among AsA. Examine associations of the GM with depressive symptoms and sleep disturbance among Chinese and Korean American immigrants. Depressive symptoms (PROMIS Short Form-Depression) and sleep quality (Pittsburgh Sleep Quality Index [PSQI]) were collected via surveys. PROMIS measure T-score > 55 indicates positive depressive symptoms, and a total PSQI score > 5 indicates sleep disturbance. 16S rRNA V3-V4 gene regions were sequenced from fecal specimens to measure GM. Permutational multivariate analysis of variance and linear discriminant analysis effect size were applied to examine associations of the GM with symptoms. Among 20 participants, 55% (<i>n</i> = 11) reported depressive symptoms and 35% (<i>n</i> = 7) reported sleep disturbance. A higher α-diversity was marginally associated with lower depressive symptoms: Chao1 (r = -0.39, <i>p</i> = 0.09) and Shannon index (r = -0.41, <i>p</i> = 0.08); β-diversity distinguished participants between categories of depressive symptoms (weighted UniFrac, <i>p</i>=0.04) or sleep disturbance (Jaccard, <i>p</i>=0.05). Those with depressive symptoms showed a higher abundance of <i>Actinobacteria,</i> while those without depressive symptoms had a higher abundance of <i>Bacteroidetes</i>. No significant taxa were identified for sleep disturbance. Gut microbial diversity showed promising associations with depressive symptoms and sleep disturbance among Chinese and Korean immigrants. Specific taxa were identified as associated with depressive symptoms. Future studies with a larger sample size are warranted to confirm our findings.",
"role": "user"
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{
"content": "A Pilot Study of the <microbiome>Gut Microbiota</microbiome> Associated With <DDF>Depressive Symptoms</DDF> and <DDF>Sleep Disturbance</DDF> Among <human>Chinese and Korean Immigrants</human> in the United States. <DDF>Depression</DDF> is prevalent among <human>Asian Americans</human> (<human>AsA</human>) during the COVID-19 pandemic, and <DDF>depression</DDF> often leads to <DDF>sleep disturbance</DDF> in this <human>population</human>. The <microbiome>gut microbiota</microbiome> (<microbiome>GM</microbiome>) plays a critical role in mental health and sleep quality, and the composition of the <microbiome>GM</microbiome> is largely unknown among <human>AsA</human>. Examine associations of the <microbiome>GM</microbiome> with <DDF>depressive symptoms</DDF> and <DDF>sleep disturbance</DDF> among <human>Chinese and Korean American immigrants</human>. <DDF>Depressive symptoms</DDF> (PROMIS Short Form-Depression) and sleep quality (Pittsburgh Sleep Quality Index [PSQI]) were collected via surveys. PROMIS measure T-score > 55 indicates positive <DDF>depressive symptoms</DDF>, and a total PSQI score > 5 indicates <DDF>sleep disturbance</DDF>. <gene>16S rRNA V3-V4 gene regions</gene> were sequenced from fecal specimens to measure <microbiome>GM</microbiome>. <statistical technique>Permutational multivariate analysis of variance</statistical technique> and <statistical technique>linear discriminant analysis effect size</statistical technique> were applied to examine associations of the <microbiome>GM</microbiome> with symptoms. Among 20 <human>participants</human>, 55% (<i>n</i> = 11) reported <DDF>depressive symptoms</DDF> and 35% (<i>n</i> = 7) reported <DDF>sleep disturbance</DDF>. A higher α-diversity was marginally associated with lower <DDF>depressive symptoms</DDF>: <statistical technique>Chao1</statistical technique> (r = -0.39, <i>p</i> = 0.09) and <statistical technique>Shannon index</statistical technique> (r = -0.41, <i>p</i> = 0.08); β-diversity distinguished <human>participants</human> between categories of <DDF>depressive symptoms</DDF> (<statistical technique>weighted UniFrac</statistical technique>, <i>p</i>=0.04) or <DDF>sleep disturbance</DDF> (<statistical technique>Jaccard</statistical technique>, <i>p</i>=0.05). Those with <DDF>depressive symptoms</DDF> showed a higher abundance of <i><bacteria>Actinobacteria</bacteria>,</i> while those without <DDF>depressive symptoms</DDF> had a higher abundance of <i><bacteria>Bacteroidetes</bacteria></i>. No significant taxa were identified for <DDF>sleep disturbance</DDF>. Gut microbial diversity showed promising associations with <DDF>depressive symptoms</DDF> and <DDF>sleep disturbance</DDF> among <human>Chinese and Korean immigrants</human>. Specific taxa were identified as associated with <DDF>depressive symptoms</DDF>. Future studies with a larger sample size are warranted to confirm our findings.",
"role": "assistant"
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36072564
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nAge-dependent effects of gut microbiota metabolites on brain resident macrophages. In recent years, development of age-related diseases, such as Alzheimer's and Parkinson's disease, as well as other brain disorders, including anxiety, depression, and schizophrenia have been shown to be associated with changes in the gut microbiome. Several factors can induce an alteration in the bacterial composition of the host's gastrointestinal tract. Besides dietary changes and frequent use of antibiotics, the microbiome is also profoundly affected by aging. Levels of microbiota-derived metabolites are elevated in older individuals with age-associated diseases and cognitive defects compared to younger, healthy age groups. The identified metabolites with higher concentration in aged hosts, which include choline and trimethylamine, are known risk factors for age-related diseases. While the underlying mechanisms and pathways remain elusive for the most part, it has been shown, that these metabolites are able to trigger the innate immunity in the central nervous system by influencing development and activation status of brain-resident macrophages. The macrophages residing in the brain comprise parenchymal microglia and non-parenchymal macrophages located in the perivascular spaces, meninges, and the choroid plexus. In this review, we highlight the impact of age on the composition of the microbiome and microbiota-derived metabolites and their influence on age-associated diseases caused by dysfunctional brain-resident macrophages.",
"role": "user"
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{
"content": "Age-dependent effects of <chemical>gut microbiota metabolites</chemical> on brain resident macrophages. In recent years, development of <DDF>age-related diseases</DDF>, such as <DDF>Alzheimer's and Parkinson's disease</DDF>, as well as other <DDF>brain disorders</DDF>, including <DDF>anxiety</DDF>, <DDF>depression</DDF>, and <DDF>schizophrenia</DDF> have been shown to be associated with changes in the <microbiome>gut microbiome</microbiome>. Several factors can induce an alteration in the bacterial composition of the <anatomical location>host's gastrointestinal tract</anatomical location>. Besides dietary changes and frequent use of <drug>antibiotics</drug>, the microbiome is also profoundly affected by <DDF>aging</DDF>. Levels of <chemical>microbiota-derived metabolites</chemical> are elevated in <human>older individuals</human> with <DDF>age-associated diseases</DDF> and <DDF>cognitive defects</DDF> compared to younger, <human>healthy age groups</human>. The identified metabolites with higher concentration in aged hosts, which include <chemical>choline</chemical> and <chemical>trimethylamine</chemical>, are known risk factors for <DDF>age-related diseases</DDF>. While the underlying mechanisms and pathways remain elusive for the most part, it has been shown, that these metabolites are able to trigger the innate immunity in the central nervous system by influencing development and activation status of brain-resident macrophages. The macrophages residing in the <anatomical location>brain</anatomical location> comprise parenchymal microglia and non-parenchymal macrophages located in the <anatomical location>perivascular spaces</anatomical location>, <anatomical location>meninges</anatomical location>, and the <anatomical location>choroid plexus</anatomical location>. In this review, we highlight the impact of age on the composition of the microbiome and <chemical>microbiota-derived metabolites</chemical> and their influence on <DDF>age-associated diseases</DDF> caused by dysfunctional brain-resident macrophages.",
"role": "assistant"
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36072680
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nDietary Modification for the Restoration of Gut Microbiome and Management of Symptoms in Irritable Bowel Syndrome. Irritable bowel syndrome (IBS) is a functional gastrointestinal disorder leading to chronic debilitating issues. A healthy diet plays an integral role in maintaining the gut microbiota equilibrium, thus promoting digestive health. The structure and function of gut microbiota are affected by genetics and environmental factors, such as altered dietary habits, gastroenteritis, stress, increased use of alcohol and drugs, and medication use. Whereas there are various management approaches cited in the literature to manage symptoms of IBS, the purpose of this article is to focus on dietary options that will restore the gut microbiome and help in managing IBS symptoms. Some of the diets that are discussed in this article include a low-FODMAP (fermentable oligosaccharides, disaccharides, monosaccharides, and polyols) diet, gluten-free/wheat-free diet, high-fiber diet, dietary and herbal supplements (psyllium, peppermint oil), and probiotics/prebiotics/synbiotics. The clinical practice guidelines recommended by the American College of Gastroenterology outlines evidence-based dietary recommendations for patients with IBS to manage symptoms. Recent advancements in the dietary management of IBS highlighting the use of a patient-centered, personalized nutrition approach along with lifestyle changes, pharmacological therapies, and psychosocial and behavioral interventions are also reviewed and discussed.",
"role": "user"
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{
"content": "Dietary Modification for the Restoration of <microbiome>Gut Microbiome</microbiome> and Management of Symptoms in <DDF>Irritable Bowel Syndrome</DDF>. <DDF>Irritable bowel syndrome</DDF> (<DDF>IBS</DDF>) is a <DDF>functional gastrointestinal disorder</DDF> leading to <DDF>chronic debilitating issues</DDF>. A healthy diet plays an integral role in maintaining the gut microbiota equilibrium, thus promoting digestive health. The structure and function of <microbiome>gut microbiota</microbiome> are affected by genetics and environmental factors, such as altered dietary habits, <DDF>gastroenteritis</DDF>, <DDF>stress</DDF>, increased use of alcohol and drugs, and medication use. Whereas there are various management approaches cited in the literature to manage symptoms of <DDF>IBS</DDF>, the purpose of this article is to focus on dietary options that will restore the <microbiome>gut microbiome</microbiome> and help in managing <DDF>IBS</DDF> symptoms. Some of the diets that are discussed in this article include a low-FODMAP (<chemical>fermentable oligosaccharides</chemical>, <chemical>disaccharides</chemical>, <chemical>monosaccharides</chemical>, and <chemical>polyols</chemical>) diet, gluten-free/wheat-free diet, high-fiber diet, dietary and herbal supplements (<dietary supplement>psyllium</dietary supplement>, <dietary supplement>peppermint oil</dietary supplement>), and <dietary supplement>probiotics/prebiotics/synbiotics</dietary supplement>. The clinical practice guidelines recommended by the American College of Gastroenterology outlines evidence-based dietary recommendations for <human>patients</human> with <DDF>IBS</DDF> to manage symptoms. Recent advancements in the dietary management of <DDF>IBS</DDF> highlighting the use of a patient-centered, personalized nutrition approach along with lifestyle changes, pharmacological therapies, and psychosocial and behavioral interventions are also reviewed and discussed.",
"role": "assistant"
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36191806
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nA role of gut-microbiota-brain axis via subdiaphragmatic vagus nerve in depression-like phenotypes in Chrna7 knock-out mice. The α7 subtype of the nicotinic acetylcholine receptor (α7 nAChR: coded by Chrna7) is known to regulate the cholinergic ascending anti-inflammatory pathway. We previously reported that Chrna7 knock-out (KO) mice show depression-like behaviors through abnormal composition of gut microbiota and systemic inflammation. Given the role of subdiaphragmatic vagus nerve in gut-microbiota-brain axis, we investigated whether subdiaphragmatic vagotomy (SDV) could affect depression-like behaviors, abnormal composition of gut microbiota, and microbes-derived metabolites in Chrna7 KO mice. SDV blocked depression-like behaviors and reduced expression of synaptic proteins in the medial prefrontal cortex (mPFC) of Chrna7 KO mice. LEfSe (linear discriminant analysis effect size) analysis revealed that the species Lactobacillus sp. BL302, the species Lactobacillus hominis, and the species Lactobacillus reuteri, were identified as potential microbial markers in the KO + SDV group. There were several genus and species altered among the three groups [wild-type (WT) + sham group, KO + sham group, KO + SDV group]. Furthermore, there were several plasma metabolites altered among the three groups. Moreover, there were correlations between relative abundance of several microbiome and behavioral data (or synaptic proteins). Network analysis showed correlations between relative abundance of several microbiome and plasma metabolites (or behavioral data). These data suggest that Chrna7 KO mice produce depression-like behaviors and reduced expression of synaptic proteins in the mPFC through gut-microbiota-brain axis via subdiaphragmatic vagus nerve.",
"role": "user"
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{
"content": "A role of gut-microbiota-brain axis via <anatomical location>subdiaphragmatic vagus nerve</anatomical location> in <DDF>depression-like phenotypes</DDF> in <animal>Chrna7 knock-out mice</animal>. The <chemical>α7 subtype</chemical> of the <chemical>nicotinic acetylcholine receptor</chemical> (<chemical>α7 nAChR</chemical>: coded by <gene>Chrna7</gene>) is known to regulate the cholinergic ascending anti-inflammatory pathway. We previously reported that <animal>Chrna7 knock-out (KO) mice</animal> show <DDF>depression-like behaviors</DDF> through <DDF>abnormal composition of gut microbiota</DDF> and <DDF>systemic inflammation</DDF>. Given the role of <anatomical location>subdiaphragmatic vagus nerve</anatomical location> in gut-microbiota-brain axis, we investigated whether <biomedical technique>subdiaphragmatic vagotomy</biomedical technique> (<biomedical technique>SDV</biomedical technique>) could affect <DDF>depression-like behaviors</DDF>, <DDF>abnormal composition of gut microbiota</DDF>, and <chemical>microbes-derived metabolites</chemical> in <animal>Chrna7 KO mice</animal>. <biomedical technique>SDV</biomedical technique> blocked <DDF>depression-like behaviors</DDF> and reduced expression of <chemical>synaptic proteins</chemical> in the <anatomical location>medial prefrontal cortex</anatomical location> (<anatomical location>mPFC</anatomical location>) of <animal>Chrna7 KO mice</animal>. <statistical technique>LEfSe (linear discriminant analysis effect size) analysis</statistical technique> revealed that the species <bacteria>Lactobacillus sp. BL302</bacteria>, the species <bacteria>Lactobacillus hominis</bacteria>, and the species <bacteria>Lactobacillus reuteri</bacteria>, were identified as potential microbial markers in the <animal>KO + SDV group</animal>. There were several genus and species altered among the <animal>three groups [wild-type (WT) + sham group, KO + sham group, KO + SDV group]</animal>. Furthermore, there were several <chemical>plasma metabolites</chemical> altered among the <animal>three groups</animal>. Moreover, there were correlations between relative abundance of <microbiome>several microbiome</microbiome> and behavioral data (or <chemical>synaptic proteins</chemical>). Network analysis showed correlations between relative abundance of <microbiome>several microbiome</microbiome> and <chemical>plasma metabolites</chemical> (or behavioral data). These data suggest that <animal>Chrna7 KO mice</animal> produce <DDF>depression-like behaviors</DDF> and reduced expression of <chemical>synaptic proteins</chemical> in the <anatomical location>mPFC</anatomical location> through gut-microbiota-brain axis via <anatomical location>subdiaphragmatic vagus nerve</anatomical location>.",
"role": "assistant"
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36216056
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nEffects of urban particulate matter on gut microbiome and partial schizophrenia-like symptoms in mice: Evidence from shotgun metagenomic and metabolomic profiling. Epidemiological evidence reported that particulate matter (PM) was associated with increased schizophrenia (SCZ) risk. Disturbance of gut microbiome was involved in SCZ. However, it remains unclear whether PM induces SCZ-like symptoms and how gut microbiome regulates them. Therefore, a multi-omics animal experiment was conducted to verify how urban PM induces SCZ-like behavior and altered gut microbiota and metabolic pathways. Using a completely random design, mice were divided into three groups: PM group, control group and MK801 group, which received daily tracheal instillation of PM solution, sterile PBS solution and intraperitoneal injection of MK801 (establish SCZ model), respectively. After a 14-day intervention, feces were collected for multi-omics testing (shotgun metagenomic sequencing and untargeted metabolomic profiling), followed by open field test, tail suspension test, and passive avoidance test. Besides, fecal microbiome of PM group and control group were transplanted into \"pseudo-sterile\" mice, then behavioral tests were conducted. Similar to MK801 group, mice in PM group showed SCZ-like symptoms, including increased spontaneous activity, excitability, anxiety and decreased learning and spatial memory. PM exposure significantly increased the relative abundance of Verrucomicrobia and decreased that of Fibrobacteres et al. The metabolism pathways of estrogen signaling (estriol, 16-glucuronide-estriol and 21-desoxycortisol) and choline metabolism (phosphocholine) were significantly altered by PM exposure. Verrucomicrobia was negatively correlated with the level of estriol, which was correlated with decreased learning and spatial memory. Fibrobacteres and Deinococcus-Thermus were positively correlated with the level of phosphocholine, which was correlated with increased spontaneous activity, excitability and anxiety. Fecal microbiome transplantation from PM group mice reproduced excitability and anxiety symptoms. Exposure to PM may affect composition of gut microbiome and alterations of estrogen signaling pathway and choline metabolism pathway, which were associated with partial SCZ-like behaviors. But whether gut microbiome regulates these metabolic pathways and behaviors remains to be determined.",
"role": "user"
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"content": "Effects of <chemical>urban particulate matter</chemical> on <microbiome>gut microbiome</microbiome> and <DDF>partial schizophrenia-like symptoms</DDF> in <animal>mice</animal>: Evidence from <biomedical technique>shotgun metagenomic</biomedical technique> and <biomedical technique>metabolomic profiling</biomedical technique>. Epidemiological evidence reported that <chemical>particulate matter</chemical> (<chemical>PM</chemical>) was associated with increased <DDF>schizophrenia</DDF> (<DDF>SCZ</DDF>) risk. Disturbance of <microbiome>gut microbiome</microbiome> was involved in <DDF>SCZ</DDF>. However, it remains unclear whether <chemical>PM</chemical> induces <DDF>SCZ-like symptoms</DDF> and how <microbiome>gut microbiome</microbiome> regulates them. Therefore, a <biomedical technique>multi-omics animal experiment</biomedical technique> was conducted to verify how <chemical>urban PM</chemical> induces <DDF>SCZ-like behavior</DDF> and altered <microbiome>gut microbiota</microbiome> and metabolic pathways. Using a completely random design, <animal>mice</animal> were divided into three groups: PM group, control group and MK801 group, which received daily tracheal instillation of <chemical>PM solution</chemical>, <chemical>sterile PBS solution</chemical> and intraperitoneal injection of <chemical>MK801</chemical> (establish SCZ model), respectively. After a 14-day intervention, feces were collected for <biomedical technique>multi-omics testing</biomedical technique> (<biomedical technique>shotgun metagenomic sequencing</biomedical technique> and <biomedical technique>untargeted metabolomic profiling</biomedical technique>), followed by <biomedical technique>open field test</biomedical technique>, <biomedical technique>tail suspension test</biomedical technique>, and <biomedical technique>passive avoidance test</biomedical technique>. Besides, <microbiome>fecal microbiome</microbiome> of PM group and control group were transplanted into \"<animal>pseudo-sterile\" mice</animal>, then <biomedical technique>behavioral tests</biomedical technique> were conducted. Similar to MK801 group, <animal>mice</animal> in <animal>PM group</animal> showed SCZ-like symptoms, including increased spontaneous activity, <DDF>excitability</DDF>, <DDF>anxiety</DDF> and decreased learning and spatial memory. <chemical>PM</chemical> exposure significantly increased the relative abundance of <bacteria>Verrucomicrobia</bacteria> and decreased that of <bacteria>Fibrobacteres</bacteria> et al. The metabolism pathways of estrogen signaling (<chemical>estriol</chemical>, <chemical>16-glucuronide-estriol</chemical> and <chemical>21-desoxycortisol</chemical>) and choline metabolism (<chemical>phosphocholine</chemical>) were significantly altered by <chemical>PM</chemical> exposure. <bacteria>Verrucomicrobia</bacteria> was negatively correlated with the level of <chemical>estriol</chemical>, which was correlated with decreased learning and spatial memory. <bacteria>Fibrobacteres</bacteria> and <bacteria>Deinococcus-Thermus</bacteria> were positively correlated with the level of <chemical>phosphocholine</chemical>, which was correlated with increased spontaneous activity, excitability and <DDF>anxiety</DDF>. Fecal microbiome transplantation from <animal>PM group mice</animal> reproduced excitability and <DDF>anxiety</DDF> symptoms. Exposure to <chemical>PM</chemical> may affect composition of <microbiome>gut microbiome</microbiome> and alterations of estrogen signaling pathway and choline metabolism pathway, which were associated with partial <DDF>SCZ-like behaviors</DDF>. But whether <microbiome>gut microbiome</microbiome> regulates these metabolic pathways and behaviors remains to be determined.",
"role": "assistant"
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36332796
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGut microbiome and Parkinson's disease: Perspective on pathogenesis and treatment. Parkinson's disease (PD) is a disease of ⍺-synuclein aggregation-mediated dopaminergic neuronal loss in the substantia nigra pars compacta, which leads to motor and non-motor symptoms. Through the last two decades of research, there has been growing consensus that inflammation-mediated oxidative stress, mitochondrial dysfunction, and cytokine-induced toxicity are mainly involved in neuronal damage and loss associated with PD. However, it remains unclear how these mechanisms relate to sporadic PD, a more common form of PD. Both enteric and central nervous systems have been implicated in the pathogenesis of sporadic PD, thus highlighting the crosstalk between the gut and brain. of Review: In this review, we summarize how alterations in the gut microbiome can affect PD pathogenesis. We highlight various mechanisms increasing/decreasing the risk of PD development. Based on the previous supporting evidence, we suggest how early interventions could protect against PD development and how controlling specific factors, including our diet, could modify our perspective on disease mechanisms and therapeutics. We explain the strong relationship between the gut microbiota and the brain in PD subjects, by delineating the multiple mechanisms involved inneuroinflammation and oxidative stress. We conclude that the neurodetrimental effects of western diet (WD) and the neuroprotective effects of Mediterranean diets should be further exploredin humans through clinical trials. Key Scientific Concepts of Review: Alterations in the gut microbiome and associated metabolites may contribute to pathogenesis in PD. In some studies, probiotics have been shown to exert anti-oxidative effects in PD via improved mitochondrial dynamics and homeostasis, thus reducing PD-related consequences. However, there is a significant unmet need for randomized clinical trials to investigate the effectiveness of microbial products, probiotic-based supplementation, and dietary intervention in reversing gut microbial dysbiosis in PD.",
"role": "user"
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{
"content": "<microbiome>Gut microbiome</microbiome> and <DDF>Parkinson's disease</DDF>: Perspective on pathogenesis and treatment. <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>) is a disease of ⍺-synuclein aggregation-mediated dopaminergic neuronal loss in the substantia nigra pars compacta, which leads to motor and non-motor symptoms. Through the last two decades of research, there has been growing consensus that inflammation-mediated oxidative stress, <DDF>mitochondrial dysfunction</DDF>, and cytokine-induced toxicity are mainly involved in neuronal damage and loss associated with <DDF>PD</DDF>. However, it remains unclear how these mechanisms relate to <DDF>sporadic PD</DDF>, a more common form of <DDF>PD</DDF>. Both enteric and central nervous systems have been implicated in the pathogenesis of <DDF>sporadic PD</DDF>, thus highlighting the crosstalk between the <anatomical location>gut</anatomical location> and <anatomical location>brain</anatomical location>. of Review: In this review, we summarize how alterations in the <microbiome>gut microbiome</microbiome> can affect PD pathogenesis. We highlight various mechanisms increasing/decreasing the risk of PD development. Based on the previous supporting evidence, we suggest how early interventions could protect against PD development and how controlling specific factors, including our diet, could modify our perspective on disease mechanisms and therapeutics. We explain the strong relationship between the <microbiome>gut microbiota</microbiome> and the <anatomical location>brain</anatomical location> in <human>PD subjects</human>, by delineating the multiple mechanisms involved inneuroinflammation and oxidative stress. We conclude that the neurodetrimental effects of western diet (WD) and the neuroprotective effects of Mediterranean diets should be further exploredin humans through clinical trials. Key Scientific Concepts of Review: Alterations in the <microbiome>gut microbiome</microbiome> and associated metabolites may contribute to pathogenesis in <DDF>PD</DDF>. In some studies, <dietary supplement>probiotics</dietary supplement> have been shown to exert anti-oxidative effects in <DDF>PD</DDF> via improved mitochondrial dynamics and homeostasis, thus reducing PD-related consequences. However, there is a significant unmet need for randomized clinical trials to investigate the effectiveness of microbial products, <dietary supplement>probiotic-based supplementation</dietary supplement>, and dietary intervention in reversing <DDF>gut microbial dysbiosis</DDF> in <DDF>PD</DDF>.",
"role": "assistant"
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36411639
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nDeciphering the gut microbiome in neurodegenerative diseases and metagenomic approaches for characterization of gut microbes. The central nervous system has essential role in the regulation of the physiological condition of the human body. Gut microbes cause several types of gastrointestinal diseases like ulcer stomach and intestine and irritable bowel syndrome. Microbes present in the human gut can affect brain function by the release of neuroactive metabolites such as neurotransmitters, hormones, and other compounds. Gut microbial-derived metabolites also have an important role in neurological diseases such as Alzheimer's disease, Parkinson's disease, etc. Vital communication between the gut microbes and the central nervous system is known as the microbiota-gut-brain axis. It provides a communication pathway between the gut and brain which is made up of the vagus nerve, immune system components, and neuroendocrine. Disturbance in gut microbiota composition can alter the central nervous system and enteric nervous system functions. Metagenomics has been employed for the identification, and characterization of gut microbes and microbial-derived metabolites. This review is focused on the gut microbes-brain relationship and the role of gut microbes in neurodegenerative diseases. This study is also focused on major metagenomic approaches and their role in gut microbes characterization.",
"role": "user"
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{
"content": "Deciphering the <microbiome>gut microbiome</microbiome> in <DDF>neurodegenerative diseases</DDF> and <biomedical technique>metagenomic approaches</biomedical technique> for characterization of <microbiome>gut microbes</microbiome>. The central nervous system has essential role in the regulation of the physiological condition of the human body. <bacteria>Gut microbes</bacteria> cause several types of <DDF>gastrointestinal diseases</DDF> like <DDF>ulcer stomach and intestine</DDF> and <DDF>irritable bowel syndrome</DDF>. Microbes present in the <anatomical location>human gut</anatomical location> can affect brain function by the release of <chemical>neuroactive metabolites</chemical> such as <chemical>neurotransmitters</chemical>, <chemical>hormones</chemical>, and other compounds. <chemical>Gut microbial-derived metabolites</chemical> also have an important role in <DDF>neurological diseases</DDF> such as <DDF>Alzheimer's disease</DDF>, <DDF>Parkinson's disease</DDF>, etc. Vital communication between the <bacteria>gut microbes</bacteria> and the central nervous system is known as the microbiota-gut-brain axis. It provides a communication pathway between the <anatomical location>gut</anatomical location> and <anatomical location>brain</anatomical location> which is made up of the <anatomical location>vagus nerve</anatomical location>, immune system components, and neuroendocrine. Disturbance in <microbiome>gut microbiota composition</microbiome> can alter the central nervous system and enteric nervous system functions. <biomedical technique>Metagenomics</biomedical technique> has been employed for the identification, and characterization of <bacteria>gut microbes</bacteria> and <chemical>microbial-derived metabolites</chemical>. This review is focused on the gut microbes-brain relationship and the role of <bacteria>gut microbes</bacteria> in <DDF>neurodegenerative diseases</DDF>. This study is also focused on <biomedical technique>major metagenomic approaches</biomedical technique> and their role in gut microbes characterization.",
"role": "assistant"
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36462169
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nElevated Systemic Levels of Markers Reflecting Intestinal Barrier Dysfunction and Inflammasome Activation Are Correlated in Severe Mental Illness. Gut microbiota alterations have been reported in severe mental illness (SMI) but fewer studies have probed for signs of gut barrier disruption and inflammation. We hypothesized that gut leakage of microbial products due to intestinal inflammation could contribute to systemic inflammasome activation in SMI. We measured plasma levels of the chemokine CCL25 and soluble mucosal vascular addressin cell adhesion molecule-1 (sMAdCAM-1) as markers of T cell homing, adhesion and inflammation in the gut, lipopolysaccharide binding protein (LBP) and intestinal fatty acid binding protein (I-FABP) as markers of bacterial translocation and gut barrier dysfunction, in a large SMI cohort (n = 567) including schizophrenia (SCZ, n = 389) and affective disorder (AFF, n = 178), relative to healthy controls (HC, n = 418). We assessed associations with plasma IL-18 and IL-18BPa and leukocyte mRNA expression of NLRP3 and NLRC4 as markers of inflammasome activation. Our main findings were: (1) higher levels of sMAdCAM-1 (P = .002), I-FABP (P = 7.6E-11), CCL25 (P = 9.6E-05) and LBP (P = 2.6E-04) in SMI compared to HC in age, sex, BMI, CRP and freezer storage time adjusted analysis; (2) the highest levels of sMAdCAM-1 and CCL25 (both P = 2.6E-04) were observed in SCZ and I-FABP (P = 2.5E-10) and LBP (3) in AFF; and (3), I-FABP correlated with IL-18BPa levels and LBP correlated with NLRC4. Our findings support that intestinal barrier inflammation and dysfunction in SMI could contribute to systemic inflammation through inflammasome activation.",
"role": "user"
},
{
"content": "Elevated Systemic Levels of Markers Reflecting <DDF>Intestinal Barrier Dysfunction</DDF> and Inflammasome Activation Are Correlated in <DDF>Severe Mental Illness</DDF>. <DDF>Gut microbiota alterations</DDF> have been reported in <DDF>severe mental illness</DDF> (<DDF>SMI</DDF>) but fewer studies have probed for signs of <DDF>gut barrier disruption</DDF> and <DDF>inflammation</DDF>. We hypothesized that gut leakage of microbial products due to <DDF>intestinal inflammation</DDF> could contribute to systemic inflammasome activation in <DDF>SMI</DDF>. We measured plasma levels of the <chemical>chemokine CCL25</chemical> and <chemical>soluble mucosal vascular addressin cell adhesion molecule-1</chemical> (<chemical>sMAdCAM-1</chemical>) as markers of T cell homing, adhesion and <DDF>inflammation</DDF> in the <anatomical location>gut</anatomical location>, <chemical>lipopolysaccharide binding protein</chemical> (<chemical>LBP</chemical>) and <chemical>intestinal fatty acid binding protein</chemical> (<chemical>I-FABP</chemical>) as markers of bacterial translocation and <DDF>gut barrier dysfunction</DDF>, in a large <DDF>SMI</DDF> cohort (n = 567) including <DDF>schizophrenia</DDF> (<DDF>SCZ</DDF>, n = 389) and <DDF>affective disorder</DDF> (<DDF>AFF</DDF>, n = 178), relative to <human>healthy controls</human> (<human>HC</human>, n = 418). We assessed associations with <chemical>plasma IL-18</chemical> and <chemical>IL-18BPa</chemical> and leukocyte mRNA expression of <gene>NLRP3</gene> and <gene>NLRC4</gene> as markers of inflammasome activation. Our main findings were: (1) higher levels of <chemical>sMAdCAM-1</chemical> (P = .002), <chemical>I-FABP</chemical> (P = 7.6E-11), <chemical>CCL25</chemical> (P = 9.6E-05) and <chemical>LBP</chemical> (P = 2.6E-04) in <DDF>SMI</DDF> compared to <human>HC</human> in age, sex, BMI, CRP and freezer storage time adjusted analysis; (2) the highest levels of <gene>sMAdCAM-1</gene> and <chemical>CCL25</chemical> (both P = 2.6E-04) were observed in <DDF>SCZ</DDF> and <chemical>I-FABP</chemical> (P = 2.5E-10) and <chemical>LBP</chemical> (3) in <DDF>AFF</DDF>; and (3), <chemical>I-FABP</chemical> correlated with <chemical>IL-18BPa</chemical> levels and <chemical>LBP</chemical> correlated with <gene>NLRC4</gene>. Our findings support that <DDF>intestinal barrier inflammation and dysfunction</DDF> in <DDF>SMI</DDF> could contribute to <DDF>systemic inflammation</DDF> through inflammasome activation.",
"role": "assistant"
}
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36651663
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nThe gut-microbiota-brain axis in a Spanish population in the aftermath of the COVID-19 pandemic: microbiota composition linked to anxiety, trauma, and depression profiles. The prevalence of anxiety and depression soared following the COVID-19 pandemic. To effectively treat these conditions, a comprehensive understanding of all etiological factors is needed. This study investigated fecal microbial features associated with mental health outcomes (symptoms of anxiety, depression, or posttraumatic stress disorder (PTSD)) in a Spanish cohort in the aftermath of the COVID-19 pandemic. Microbial communities from stool samples were profiled in 198 individuals who completed validated, self-report questionnaires. 16S ribosomal RNA gene V3-4 amplicon sequencing was performed. Microbial diversity and community structure were analyzed, together with relative taxonomic abundance. In our cohort of N=198, 17.17% reported depressive symptoms, 37.37% state anxiety symptoms, 40.90% trait anxiety symptoms, and 8.08% PTSD symptoms, with high levels of comorbidity. Individuals with trait anxiety had lower Simpson's diversity. <i>Fusicatenibacter saccharivorans</i> was reduced in individuals with comorbid PTSD + depression + state and trait anxiety symptoms, whilst an expansion of Proteobacteria and depletion of Synergistetes phyla were noted in individuals with depressive symptoms. The relative abundance of <i>Anaerostipes</i> was positively correlated with childhood trauma, and higher levels of <i>Turicibacter sanguinis</i> and lower levels of Lentisphaerae were found in individuals who experienced life-threatening traumas. COVID-19 infection and vaccination influenced the overall microbial composition and were associated with distinct relative taxonomic abundance profiles. These findings will help lay the foundation for future studies to identify microbial role players in symptoms of anxiety, depression, and PTSD and provide future therapeutic targets to improve mental health outcomes.",
"role": "user"
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{
"content": "The gut-microbiota-brain axis in a <human>Spanish population</human> in the aftermath of the COVID-19 pandemic: microbiota composition linked to <DDF>anxiety</DDF>, <DDF>trauma</DDF>, and <DDF>depression</DDF> profiles. The prevalence of <DDF>anxiety</DDF> and <DDF>depression</DDF> soared following the COVID-19 pandemic. To effectively treat these conditions, a comprehensive understanding of all etiological factors is needed. This study investigated fecal microbial features associated with mental health outcomes (symptoms of <DDF>anxiety</DDF>, <DDF>depression</DDF>, or <DDF>posttraumatic stress disorder</DDF> (<DDF>PTSD</DDF>)) in a <human>Spanish cohort</human> in the aftermath of the COVID-19 pandemic. Microbial communities from stool samples were profiled in 198 <human>individuals</human> who completed validated, self-report questionnaires. <biomedical technique>16S ribosomal RNA gene V3-4 amplicon sequencing</biomedical technique> was performed. Microbial diversity and community structure were analyzed, together with relative taxonomic abundance. In our cohort of N=198, 17.17% reported depressive symptoms, 37.37% state anxiety symptoms, 40.90% trait anxiety symptoms, and 8.08% PTSD symptoms, with high levels of comorbidity. <human>Individuals</human> with <DDF>trait anxiety</DDF> had lower Simpson's diversity. <i><bacteria>Fusicatenibacter saccharivorans</bacteria></i> was reduced in <human>individuals</human> with comorbid PTSD + depression + state and trait anxiety symptoms, whilst an expansion of <bacteria>Proteobacteria</bacteria> and depletion of <bacteria>Synergistetes phyla</bacteria> were noted in <human>individuals</human> with depressive symptoms. The relative abundance of <i><bacteria>Anaerostipes</bacteria></i> was positively correlated with childhood trauma, and higher levels of <i><bacteria>Turicibacter sanguinis</bacteria></i> and lower levels of <bacteria>Lentisphaerae</bacteria> were found in <human>individuals</human> who experienced life-threatening traumas. <DDF>COVID-19 infection</DDF> and vaccination influenced the overall microbial composition and were associated with distinct relative taxonomic abundance profiles. These findings will help lay the foundation for future studies to identify microbial role players in symptoms of <DDF>anxiety</DDF>, <DDF>depression</DDF>, and <DDF>PTSD</DDF> and provide future therapeutic targets to improve mental health outcomes.",
"role": "assistant"
}
] |
36699448
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nThe host genetics affects gut microbiome diversity in Chinese depressed patients. The gut microbiome and host genetics are both associated with major depressive disorder (MDD); however, the molecular mechanisms among the associations are poorly understood, especially in the Asian, Chinese group. Our study applied linear discriminant analysis (LDA) effect size (LEfSe) and genome-wide association analysis in the cohort with both gut sequencing data and genomics data. We reported the different gut microbiota characteristics between MDD and control groups in the Chinese group and further constructed the association between host genetics and the gut microbiome. <i>Actinobacteria</i> and <i>Pseudomonades</i> were found more in the MDD group. We found significant differences in the ACE and Chao indexes of alpha diversity while no discrepancy in beta diversity. We found three associations between host genetics with microbiome features: beta diversity and rs6108 (<i>p</i> = 8.65 × 10<sup>-9</sup>), <i>Actinobacteria</i> and rs77379751 (<i>p</i> = 8.56 × 10<sup>-9</sup>), and PWY-5913 and rs1775633082 (<i>p</i> = 4.54 × 10<sup>-8</sup>). A species of the <i>Romboutsia</i> genus was co-associated with the species of <i>Ruminococcus gnavus</i> in an internetwork through four genes: <i>METTL8</i>, <i>ITGB2</i>, <i>OTULIN</i>, and <i>PROSER3</i>, with a strict threshold (<i>p</i> < 5 × 10<sup>-4</sup>). Furthermore, our findings suggested that the gut microbiome diversity might affect microRNA expression in the brain and influenced <i>SERPINA5</i> and other spatially close genes afterward. These findings suggest new linkages between depression and gut microbiome in Asian, Chinese people, which might be mediated by genes and microRNA regulation in space distance.",
"role": "user"
},
{
"content": "The host genetics affects gut microbiome diversity in <human>Chinese depressed patients</human>. The <microbiome>gut microbiome</microbiome> and host genetics are both associated with <DDF>major depressive disorder</DDF> (<DDF>MDD</DDF>); however, the molecular mechanisms among the associations are poorly understood, especially in the <human>Asian, Chinese group</human>. Our study applied <statistical technique>linear discriminant analysis (LDA) effect size</statistical technique> (<statistical technique>LEfSe</statistical technique>) and <statistical technique>genome-wide association analysis</statistical technique> in the <human>cohort</human> with both gut sequencing data and genomics data. We reported the different gut microbiota characteristics between MDD and control groups in the <human>Chinese group</human> and further constructed the association between host genetics and the <microbiome>gut microbiome</microbiome>. <i><bacteria>Actinobacteria</bacteria></i> and <i><bacteria>Pseudomonades</bacteria></i> were found more in the <human>MDD group</human>. We found significant differences in the ACE and Chao indexes of alpha diversity while no discrepancy in beta diversity. We found three associations between host genetics with microbiome features: beta diversity and rs6108 (<i>p</i> = 8.65 × 10<sup>-9</sup>), <i><bacteria>Actinobacteria</bacteria></i> and rs77379751 (<i>p</i> = 8.56 × 10<sup>-9</sup>), and PWY-5913 and rs1775633082 (<i>p</i> = 4.54 × 10<sup>-8</sup>). A species of the <i><bacteria>Romboutsia</bacteria></i> genus was co-associated with the species of <i><bacteria>Ruminococcus gnavus</bacteria></i> in an internetwork through four genes: <i><gene>METTL8</gene></i>, <i><gene>ITGB2</gene></i>, <i><gene>OTULIN</gene></i>, and <i><gene>PROSER3</gene></i>, with a strict threshold (<i>p</i> < 5 × 10<sup>-4</sup>). Furthermore, our findings suggested that the gut microbiome diversity might affect microRNA expression in the <anatomical location>brain</anatomical location> and influenced <i><gene>SERPINA5</gene></i> and other spatially close genes afterward. These findings suggest new linkages between <DDF>depression</DDF> and <microbiome>gut microbiome</microbiome> in <human>Asian, Chinese people</human>, which might be mediated by genes and microRNA regulation in space distance.",
"role": "assistant"
}
] |
36707651
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nMicrobiota-gut-brain axis mechanisms in the complex network of bipolar disorders: potential clinical implications and translational opportunities. Bipolar disorders (BD) represent a severe leading disabling mental condition worldwide characterized by episodic and often progressive mood fluctuations with manic and depressive stages. The biological mechanisms underlying the pathophysiology of BD remain incompletely understood, but it seems that there is a complex picture of genetic and environmental factors implicated. Nowadays, gut microbiota is in the spotlight of new research related to this kind of psychiatric disorder, as it can be consistently related to several pathophysiological events observed in BD. In the context of the so-called microbiota-gut-brain (MGB) axis, it is shown to have a strong influence on host neuromodulation and endocrine functions (i.e., controlling the synthesis of neurotransmitters like serotonin or mediating the activation of the hypothalamic-pituitary-adrenal axis), as well as in modulation of host immune responses, critically regulating intestinal, systemic and brain inflammation (neuroinflammation). The present review aims to elucidate pathophysiological mechanisms derived from the MGB axis disruption and possible therapeutic approaches mainly focusing on gut microbiota in the complex network of BD. Understanding the mechanisms of gut microbiota and its bidirectional communication with the immune and other systems can shed light on the discovery of new therapies for improving the clinical management of these patients. Besides, the effect of psychiatric drugs on gut microbiota currently used in BD patients, together with new therapeutical approaches targeting this ecosystem (dietary patterns, probiotics, prebiotics, and other novelties) will also be contemplated.",
"role": "user"
},
{
"content": "Microbiota-gut-brain axis mechanisms in the complex network of <DDF>bipolar disorders</DDF>: potential clinical implications and translational opportunities. <DDF>Bipolar disorders</DDF> (<DDF>BD</DDF>) represent a severe leading disabling mental condition worldwide characterized by episodic and often progressive mood fluctuations with manic and depressive stages. The biological mechanisms underlying the pathophysiology of <DDF>BD</DDF> remain incompletely understood, but it seems that there is a complex picture of genetic and environmental factors implicated. Nowadays, <microbiome>gut microbiota</microbiome> is in the spotlight of new research related to this kind of <DDF>psychiatric disorder</DDF>, as it can be consistently related to several pathophysiological events observed in <DDF>BD</DDF>. In the context of the so-called microbiota-gut-brain (MGB) axis, it is shown to have a strong influence on host neuromodulation and endocrine functions (i.e., controlling the synthesis of neurotransmitters like <chemical>serotonin</chemical> or mediating the activation of the hypothalamic-pituitary-adrenal axis), as well as in modulation of host immune responses, critically regulating <DDF>intestinal, systemic and brain inflammation</DDF> (<DDF>neuroinflammation</DDF>). The present review aims to elucidate pathophysiological mechanisms derived from the MGB axis disruption and possible therapeutic approaches mainly focusing on <microbiome>gut microbiota</microbiome> in the complex network of <DDF>BD</DDF>. Understanding the mechanisms of <microbiome>gut microbiota</microbiome> and its bidirectional communication with the immune and other systems can shed light on the discovery of new therapies for improving the clinical management of these <human>patients</human>. Besides, the effect of <drug>psychiatric drugs</drug> on <microbiome>gut microbiota</microbiome> currently used in <human>BD patients</human>, together with new therapeutical approaches targeting this ecosystem (dietary patterns, <dietary supplement>probiotics</dietary supplement>, <dietary supplement>prebiotics</dietary supplement>, and other novelties) will also be contemplated.",
"role": "assistant"
}
] |
36816743
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nThe Role of Gut Microbiota in Various Neurological and Psychiatric Disorders-An Evidence Mapping Based on Quantified Evidence. We searched PubMed, Cochrane Library, and Epistemonikos to identify systematic reviews and meta-analysis (SRs). We searched for neurological diseases and psychiatric disorders, including Alzheimer's disease (AD), attention deficit hyperactivity disorder (ADHD), amyotrophic lateral sclerosis (ALS), autism spectrum disorder (ASD), anorexia nervosa (AN), bipolar disorder (BD), eating disorder (ED), generalized anxiety disorder (GAD), major depressive disorder (MDD), multiple sclerosis (MS), obsessive compulsive disorder (OCD), Parkinson's disease (PD), posttraumatic stress disorder (PTSD), spinal cord injury (SCI), schizophrenia, and stroke. We used A Measurement Tool to Assess Systematic Reviews (AMSTAR-2) to evaluate the quality of included SRs. We also created an evidence map showing the role of gut microbiota in neurological diseases and the certainty of the evidence. In total, 42 studies were included in this evidence mapping. Most findings were obtained from observational studies. According to the AMSTAR-2 assessment, 21 SRs scored \"critically low\" in terms of methodological quality, 16 SR scored \"low,\" and 5 SR scored \"moderate.\" A total of 15 diseases have been investigated for the potential association between gut microbiome alpha diversity and disease, with the Shannon index and Simpson index being the most widely studied. A total of 12 diseases were investigated for potential link between beta diversity and disease. At the phylum level, <i>Firmicutes</i>, <i>Bacteroidetes</i>, <i>Actinobacteria</i>, <i>Proteobacteria</i>, and <i>Verrucomicrobia</i> were more researched. At the genus level, <i>Prevotella</i>, <i>Coprococcus</i>, <i>Parabacteroides</i>, <i>Phascolarctobacterium</i>, <i>Escherichia Shigella</i>, <i>Alistipes</i>, <i>Sutteralla</i>, <i>Veillonella</i>, <i>Odoribacter</i>, <i>Faecalibacterium</i>, <i>Bacteroides</i>, <i>Bifidobacterium</i>, <i>Dialister</i>, and <i>Blautia</i> were more researched. Some diseases have been found to have specific flora changes, and some diseases have been found to have common intestinal microbiological changes. We found varied levels of evidence for the associations between gut microbiota and neurological diseases; some gut microbiota increased the risk of neurological diseases, whereas others showed evidence of benefit that gut microbiota might be promising therapeutic targets for such diseases.",
"role": "user"
},
{
"content": "The Role of <microbiome>Gut Microbiota</microbiome> in <DDF>Various Neurological and Psychiatric Disorders</DDF>-An Evidence Mapping Based on Quantified Evidence. We searched PubMed, Cochrane Library, and Epistemonikos to identify systematic reviews and meta-analysis (SRs). We searched for <DDF>neurological diseases</DDF> and <DDF>psychiatric disorders</DDF>, including <DDF>Alzheimer's disease</DDF> (<DDF>AD</DDF>), <DDF>attention deficit hyperactivity disorder</DDF> (<DDF>ADHD</DDF>), <DDF>amyotrophic lateral sclerosis</DDF> (<DDF>ALS</DDF>), <DDF>autism spectrum disorder</DDF> (<DDF>ASD</DDF>), <DDF>anorexia nervosa</DDF> (<DDF>AN</DDF>), <DDF>bipolar disorder</DDF> (<DDF>BD</DDF>), <DDF>eating disorder</DDF> (<DDF>ED</DDF>), <DDF>generalized anxiety disorder</DDF> (<DDF>GAD</DDF>), <DDF>major depressive disorder</DDF> (<DDF>MDD</DDF>), <DDF>multiple sclerosis</DDF> (<DDF>MS</DDF>), <DDF>obsessive compulsive disorder</DDF> (<DDF>OCD</DDF>), <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>), <DDF>posttraumatic stress disorder</DDF> (<DDF>PTSD</DDF>), <DDF>spinal cord injury</DDF> (<DDF>SCI</DDF>), <DDF>schizophrenia</DDF>, and <DDF>stroke</DDF>. We used A Measurement Tool to Assess Systematic Reviews (AMSTAR-2) to evaluate the quality of included SRs. We also created an evidence map showing the role of <microbiome>gut microbiota</microbiome> in <DDF>neurological diseases</DDF> and the certainty of the evidence. In total, 42 studies were included in this evidence mapping. Most findings were obtained from observational studies. According to the AMSTAR-2 assessment, 21 SRs scored \"critically low\" in terms of methodological quality, 16 SR scored \"low,\" and 5 SR scored \"moderate.\" A total of 15 diseases have been investigated for the potential association between gut microbiome alpha diversity and disease, with the <statistical technique>Shannon index</statistical technique> and <statistical technique>Simpson index</statistical technique> being the most widely studied. A total of 12 diseases were investigated for potential link between beta diversity and disease. At the phylum level, <i><bacteria>Firmicutes</bacteria></i>, <i><bacteria>Bacteroidetes</bacteria></i>, <i><bacteria>Actinobacteria</bacteria></i>, <i><bacteria>Proteobacteria</bacteria></i>, and <i><bacteria>Verrucomicrobia</bacteria></i> were more researched. At the genus level, <i><bacteria>Prevotella</bacteria></i>, <i><bacteria>Coprococcus</bacteria></i>, <i><bacteria>Parabacteroides</bacteria></i>, <i><bacteria>Phascolarctobacterium</bacteria></i>, <i><bacteria>Escherichia Shigella</bacteria></i>, <i><bacteria>Alistipes</bacteria></i>, <i><bacteria>Sutteralla</bacteria></i>, <i><bacteria>Veillonella</bacteria></i>, <i><bacteria>Odoribacter</bacteria></i>, <i><bacteria>Faecalibacterium</bacteria></i>, <i><bacteria>Bacteroides</bacteria></i>, <i><bacteria>Bifidobacterium</bacteria></i>, <i><bacteria>Dialister</bacteria></i>, and <i><bacteria>Blautia</bacteria></i> were more researched. Some diseases have been found to have specific flora changes, and some diseases have been found to have common intestinal microbiological changes. We found varied levels of evidence for the associations between <microbiome>gut microbiota</microbiome> and <DDF>neurological diseases</DDF>; some <microbiome>gut microbiota</microbiome> increased the risk of <DDF>neurological diseases</DDF>, whereas others showed evidence of benefit that <microbiome>gut microbiota</microbiome> might be promising therapeutic targets for such diseases.",
"role": "assistant"
}
] |
36881806
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nBrain, Gut, and Immune Interconnections in Psychiatric Disorders: Implications for Treatment. Recent studies have linked the gut microbiota to psychiatric symptoms and disorders through complex bidirectional networks. The purpose of the current article is to describe the associations between the gut microbiota and brain in psychiatric disorders. Although there are no approved treatments, there are global efforts underway to find more accurate measures to guide treatment and research. In this brief review, we describe current conceptualizations regarding the complex interconnections between psychiatric disorders and the gut microbiota. [<i>Journal of Psychosocial Nursing and Mental Health Services, 61</i>(3), 7-11.].",
"role": "user"
},
{
"content": "<anatomical location>Brain</anatomical location>, <anatomical location>Gut</anatomical location>, and Immune Interconnections in <DDF>Psychiatric Disorders</DDF>: Implications for Treatment. Recent studies have linked the <microbiome>gut microbiota</microbiome> to psychiatric symptoms and disorders through complex bidirectional networks. The purpose of the current article is to describe the associations between the <microbiome>gut microbiota</microbiome> and <anatomical location>brain</anatomical location> in <DDF>psychiatric disorders</DDF>. Although there are no approved treatments, there are global efforts underway to find more accurate measures to guide treatment and research. In this brief review, we describe current conceptualizations regarding the complex interconnections between <DDF>psychiatric disorders</DDF> and the <microbiome>gut microbiota</microbiome>. [<i>Journal of Psychosocial Nursing and Mental Health Services, 61</i>(3), 7-11.].",
"role": "assistant"
}
] |
36931666
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nEffect of date seed (<i>Phoenix dactylifera</i>) supplementation as functional food on cardiometabolic risk factors, metabolic endotoxaemia and mental health in patients with type 2 diabetes mellitus: a blinded randomised controlled trial protocol. Recently, the improvement of chronic hyperglycaemia-related damage of type 2 diabetes mellitus (T2DM) through functional food consumption has attracted the attention of many clinicians. This study aims to determine the effectiveness of date seed powder (DSP) as a functional food (prebiotic) on the cardiometabolic risk factors, oxidative stress, anti-/inflammatory biomarkers, metabolic endotoxaemia (gut microbiota), adipokines, hypothalamic-pituitary-adrenal axis biomarkers, immune system, anthropometric indices and mental health in patients with T2DM. This study protocol will be conducted as randomised, triple-blind, placebo-controlled trial with the inclusion of 48 patients with T2DM. The participants will be randomly assigned into two equal groups of intervention (n=24) and placebo (n=24) and receive 5 g/day of DSP or placebo for 8 weeks, respectively. At baseline and post-intervention, fasting blood samples will be collected to assess the serum levels of lipid profile, glycaemic indices, antioxidant and oxidative stress, anti-/inflammatory biomarkers, lipopolysaccharide, 8-hydroxy-guanine, adipokines, hypothalamic-pituitary-adrenal axis biomarkers, immune system and mental health. Data will be analysed using the SPSS software (V.16.0). To compare the quantitative variables, paired and unpaired Student's t-tests and covariance analyses will be used. In this study, the potential effects of DSP on patients with T2DM will be evaluated for the first time. It is hoped that the results would increase the body of scientific knowledge about DSP supplementation on the cardiometabolic risk factors, oxidative stress, anti-/inflammatory biomarkers, metabolic endotoxaemia, adipokines, hypothalamic-pituitary-adrenal axis biomarkers, immune system, anthropometric indices and mental health in patients with T2DM. The study protocol was approved by the Ethical Committee of the Tabriz University of Medical Sciences, Tabriz, Iran (code: IR.TBZMED.REC.1400.752). Iranian Registry of Clinical Trials (www.irct.ir/IRCT20150205020965N10).",
"role": "user"
},
{
"content": "Effect of date seed (<i><food>Phoenix dactylifera</food></i>) supplementation as functional food on cardiometabolic risk factors, <DDF>metabolic endotoxaemia</DDF> and mental health in <human>patients</human> with <DDF>type 2 diabetes mellitus</DDF>: a blinded randomised controlled trial protocol. Recently, the improvement of <DDF>chronic hyperglycaemia-related damage</DDF> of <DDF>type 2 diabetes mellitus</DDF> (<DDF>T2DM</DDF>) through functional food consumption has attracted the attention of many clinicians. This study aims to determine the effectiveness of <dietary supplement>date seed powder</dietary supplement> (<dietary supplement>DSP</dietary supplement>) as a functional food (<dietary supplement>prebiotic</dietary supplement>) on the cardiometabolic risk factors, oxidative stress, anti-/inflammatory biomarkers, <DDF>metabolic endotoxaemia</DDF> (<microbiome>gut microbiota</microbiome>), <chemical>adipokines</chemical>, hypothalamic-pituitary-adrenal axis biomarkers, immune system, anthropometric indices and mental health in <human>patients</human> with <DDF>T2DM</DDF>. This study protocol will be conducted as <biomedical technique>randomised, triple-blind, placebo-controlled trial</biomedical technique> with the inclusion of 48 <human>patients</human> with <DDF>T2DM</DDF>. The <human>participants</human> will be randomly assigned into two equal groups of intervention (n=24) and placebo (n=24) and receive 5 g/day of <dietary supplement>DSP</dietary supplement> or <drug>placebo</drug> for 8 weeks, respectively. At baseline and post-intervention, fasting blood samples will be collected to assess the serum levels of lipid profile, glycaemic indices, antioxidant and oxidative stress, anti-/inflammatory biomarkers, <chemical>lipopolysaccharide</chemical>, <chemical>8-hydroxy-guanine</chemical>, <chemical>adipokines</chemical>, hypothalamic-pituitary-adrenal axis biomarkers, immune system and mental health. Data will be analysed using the SPSS software (V.16.0). To compare the quantitative variables, <statistical technique>paired and unpaired Student's t-tests</statistical technique> and <statistical technique>covariance analyses</statistical technique> will be used. In this study, the potential effects of <dietary supplement>DSP</dietary supplement> on <human>patients</human> with <DDF>T2DM</DDF> will be evaluated for the first time. It is hoped that the results would increase the body of scientific knowledge about <dietary supplement>DSP supplementation</dietary supplement> on the cardiometabolic risk factors, oxidative stress, anti-/inflammatory biomarkers, <DDF>metabolic endotoxaemia</DDF>, <chemical>adipokines</chemical>, hypothalamic-pituitary-adrenal axis biomarkers, immune system, anthropometric indices and mental health in <human>patients</human> with <DDF>T2DM</DDF>. The study protocol was approved by the Ethical Committee of the Tabriz University of Medical Sciences, Tabriz, Iran (code: IR.TBZMED.REC.1400.752). Iranian Registry of Clinical Trials (www.irct.ir/IRCT20150205020965N10).",
"role": "assistant"
}
] |
36938477
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nEvaluating the effectiveness of probiotics in relieving constipation in Parkinson's disease: A systematic review and meta-analysis. The aim of this study was to evaluate the effects of probiotics on the treatment of constipation in patients with Parkinson's disease (PD) by analyzing data from published randomized clinical trials (RCTs). PD is a neurodegenerative disease characterized by clinical symptoms such as rigidity, bradykinesia, and resting tremor. Constipation is a common complaint reported by PD patients. Probiotics are often used to treat functional constipation. The potential mechanisms behind PD-related constipation include dysfunction of the enteric nervous system due to alpha-synuclein aggregation, dyssynergic contractions of the puborectalis muscle, and alterations of the gut microbiome. To conduct this study, we searched Scopus, PubMed, and Google Scholar for published articles on PD, probiotics, and constipation. We selected RCTs from 944 studies, and ultimately included 3 RCTs in our meta-analysis. The frequency of bowel movements per week was the only index that could be summarized among the records. We extracted and analyzed the results as means and standard deviations. We calculated a standardized mean difference (SMD) of 0.92 (95% CI, 0.65 to 1.19; I-squared = 57.0%; p < 0.001) to determine the treatment effect in terms of frequency of bowel movements per week in the RCTs. Our results show that probiotic intake has beneficial effects on constipation in PD patients. Further research, including multicenter studies, is needed to assess the long-term efficacy and safety of probiotic supplements in neurodegenerative diseases.",
"role": "user"
},
{
"content": "Evaluating the effectiveness of <dietary supplement>probiotics</dietary supplement> in relieving <DDF>constipation</DDF> in <DDF>Parkinson's disease</DDF>: A systematic review and <statistical technique>meta-analysis</statistical technique>. The aim of this study was to evaluate the effects of <dietary supplement>probiotics</dietary supplement> on the treatment of <DDF>constipation</DDF> in <human>patients</human> with <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>) by analyzing data from published randomized clinical trials (RCTs). <DDF>PD</DDF> is a <DDF>neurodegenerative disease</DDF> characterized by clinical symptoms such as <DDF>rigidity</DDF>, <DDF>bradykinesia</DDF>, and <DDF>resting tremor</DDF>. <DDF>Constipation</DDF> is a common complaint reported by <human>PD patients</human>. <dietary supplement>Probiotics</dietary supplement> are often used to treat <DDF>functional constipation</DDF>. The potential mechanisms behind <DDF>PD-related constipation</DDF> include dysfunction of the enteric nervous system due to alpha-synuclein aggregation, <DDF>dyssynergic contractions</DDF> of the <anatomical location>puborectalis muscle</anatomical location>, and alterations of the <microbiome>gut microbiome</microbiome>. To conduct this study, we searched Scopus, PubMed, and Google Scholar for published articles on <DDF>PD</DDF>, <dietary supplement>probiotics</dietary supplement>, and <DDF>constipation</DDF>. We selected RCTs from 944 studies, and ultimately included 3 RCTs in our <statistical technique>meta-analysis</statistical technique>. The frequency of bowel movements per week was the only index that could be summarized among the records. We extracted and analyzed the results as means and <statistical technique>standard deviations</statistical technique>. We calculated a <statistical technique>standardized mean difference</statistical technique> (<statistical technique>SMD</statistical technique>) of 0.92 (95% CI, 0.65 to 1.19; I-squared = 57.0%; p < 0.001) to determine the treatment effect in terms of frequency of bowel movements per week in the RCTs. Our results show that <dietary supplement>probiotic intake</dietary supplement> has beneficial effects on <DDF>constipation</DDF> in <human>PD patients</human>. Further research, including multicenter studies, is needed to assess the long-term efficacy and safety of <dietary supplement>probiotic supplements</dietary supplement> in <DDF>neurodegenerative diseases</DDF>.",
"role": "assistant"
}
] |
36986165
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nThe Role of Diet as a Modulator of the Inflammatory Process in the Neurological Diseases. Neurological diseases are recognized as major causes of disability and mortality worldwide. Due to the dynamic progress of diseases such as Alzheimer's disease (AD), Parkinson's Disease (PD), Schizophrenia, Depression, and Multiple Sclerosis (MD), scientists are mobilized to look for new and more effective methods of interventions. A growing body of evidence suggests that inflammatory processes and an imbalance in the composition and function of the gut microbiome, which play a critical role in the pathogenesis of various neurological diseases and dietary interventions, such as the Mediterranean diet the DASH diet, or the ketogenic diet can have beneficial effects on their course. The aim of this review was to take a closer look at the role of diet and its ingredients in modulating inflammation associated with the development and/or progression of central nervous system diseases. Presented data shows that consuming a diet abundant in fruits, vegetables, nuts, herbs, spices, and legumes that are sources of anti-inflammatory elements such as omega-3 fatty acids, polyphenols, vitamins, essential minerals, and probiotics while avoiding foods that promote inflammation, create a positive brain environment and is associated with a reduced risk of neurological diseases. Personalized nutritional interventions may constitute a non-invasive and effective strategy in combating neurological disorders.",
"role": "user"
},
{
"content": "The Role of Diet as a Modulator of the <DDF>Inflammatory Process</DDF> in the <DDF>Neurological Diseases</DDF>. <DDF>Neurological diseases</DDF> are recognized as major causes of <DDF>disability</DDF> and mortality worldwide. Due to the dynamic progress of diseases such as <DDF>Alzheimer's disease</DDF> (<DDF>AD</DDF>), <DDF>Parkinson's Disease</DDF> (<DDF>PD</DDF>), <DDF>Schizophrenia</DDF>, <DDF>Depression</DDF>, and <DDF>Multiple Sclerosis</DDF> (<DDF>MD</DDF>), scientists are mobilized to look for new and more effective methods of interventions. A growing body of evidence suggests that <DDF>inflammatory processes</DDF> and an imbalance in the composition and function of the <microbiome>gut microbiome</microbiome>, which play a critical role in the pathogenesis of various <DDF>neurological diseases</DDF> and dietary interventions, such as the Mediterranean diet the DASH diet, or the ketogenic diet can have beneficial effects on their course. The aim of this review was to take a closer look at the role of diet and its ingredients in modulating <DDF>inflammation</DDF> associated with the development and/or progression of <DDF>central nervous system diseases</DDF>. Presented data shows that consuming a diet abundant in <food>fruits</food>, <food>vegetables</food>, <food>nuts</food>, <food>herbs</food>, <food>spices</food>, and <food>legumes</food> that are sources of anti-inflammatory elements such as <chemical>omega-3 fatty acids</chemical>, <chemical>polyphenols</chemical>, <chemical>vitamins</chemical>, <chemical>essential minerals</chemical>, and <dietary supplement>probiotics</dietary supplement> while avoiding foods that promote <DDF>inflammation</DDF>, create a positive brain environment and is associated with a reduced risk of <DDF>neurological diseases</DDF>. Personalized nutritional interventions may constitute a non-invasive and effective strategy in combating <DDF>neurological disorders</DDF>.",
"role": "assistant"
}
] |
36989335
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nTreatment response to supplemental nutrients for ADHD is independent of diet quality: the MADDY Study RCT. The 8-week Micronutrients for ADHD in Youth (MADDY) randomized controlled trial (<i>N</i> = 126, age 6-12) of broad-spectrum multinutrients for ADHD with emotional dysregulation found 3 times as many responders with multinutrients (54%) compared to placebo (18%) by Clinical Global Impression-Improvement (CGI-I). Our primary aim for this analysis tests the hypothesis that those with poor overall diet quality at baseline benefit more. The second aim is to explore whether specific components of diet quality moderate treatment response. 124 children (69 multinutrients, 55 placebo) had diet quality assessed using the Healthy Eating Index-2015 (HEI-2015). For each potential moderator, the outcome CGI-I at week 8 (RCT-end), was modeled two ways: (1) as a dichotomous variable: responder/non-responder, with responders defined by a rating of 1 or 2 'very much' or 'much improved,' all else equals non-responder using logistic regression, and (2) as a dimensional improvement outcome from 1 = very much improved to 7 = very much worse, using linear regression. HEI-2015 total score did not moderate treatment response [odds ratio = 1.00 (95% CI: 0.90,1.10), <i>p</i> = 0.984] or improvement [β = -0.01 (95% CI: -0.06,0.04), <i>p</i> = 0.648]. However, total vegetable intake moderated level of improvement in exploratory analysis [β = -0.48 (95% CI: -0.82, -0.13), <i>p</i> = 0.007]: those with higher baseline vegetable intake showed greater benefit from multinutrients compared to placebo. Multinutrients may benefit children with ADHD and irritability regardless of overall diet quality. The finding that higher baseline vegetable intake may improve response to multinutrients deserves further exploration, including dietary effect on gut microbiota and absorption of multinutrients and parental factors.",
"role": "user"
},
{
"content": "Treatment response to <dietary supplement>supplemental nutrients</dietary supplement> for <DDF>ADHD</DDF> is independent of diet quality: the MADDY Study RCT. The 8-week Micronutrients for ADHD in Youth (MADDY) randomized controlled trial (<i>N</i> = 126, age 6-12) of <dietary supplement>broad-spectrum multinutrients</dietary supplement> for <DDF>ADHD</DDF> with <DDF>emotional dysregulation</DDF> found 3 times as many responders with <dietary supplement>multinutrients</dietary supplement> (54%) compared to <drug>placebo</drug> (18%) by Clinical Global Impression-Improvement (CGI-I). Our primary aim for this analysis tests the hypothesis that those with poor overall diet quality at baseline benefit more. The second aim is to explore whether specific components of diet quality moderate treatment response. 124 <human>children</human> (69 <dietary supplement>multinutrients</dietary supplement>, 55 <drug>placebo</drug>) had diet quality assessed using the Healthy Eating Index-2015 (HEI-2015). For each potential moderator, the outcome CGI-I at week 8 (RCT-end), was modeled two ways: (1) as a dichotomous variable: responder/non-responder, with responders defined by a rating of 1 or 2 'very much' or 'much improved,' all else equals non-responder using <statistical technique>logistic regression</statistical technique>, and (2) as a dimensional improvement outcome from 1 = very much improved to 7 = very much worse, using <statistical technique>linear regression</statistical technique>. HEI-2015 total score did not moderate treatment response [odds ratio = 1.00 (95% CI: 0.90,1.10), <i>p</i> = 0.984] or improvement [β = -0.01 (95% CI: -0.06,0.04), <i>p</i> = 0.648]. However, total vegetable intake moderated level of improvement in exploratory analysis [β = -0.48 (95% CI: -0.82, -0.13), <i>p</i> = 0.007]: those with higher baseline vegetable intake showed greater benefit from <dietary supplement>multinutrients</dietary supplement> compared to placebo. <dietary supplement>Multinutrients</dietary supplement> may benefit <human>children</human> with <DDF>ADHD</DDF> and <DDF>irritability</DDF> regardless of overall diet quality. The finding that higher baseline vegetable intake may improve response to <dietary supplement>multinutrients</dietary supplement> deserves further exploration, including dietary effect on gut microbiota and absorption of multinutrients and parental factors.",
"role": "assistant"
}
] |
37023596
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nDifferent roles of microbiota and genetics in the prediction of treatment response in major depressive disorder. The roles of gut microbiota and susceptibility genes in patients with major depression disorder (MDD) are not well understood. Examining the microbiome and host genetics might be helpful for clinical decision-making. Patients with MDD were recruited in this study and subsequently treated for eight weeks. We identified the differences between the population with a response after two weeks and those with a response after eight weeks. The factors that were significantly correlated with efficacy were used to predict the treatment response. The differences in the importance of microbiota and genetics in prediction were analyzed. Our study identified rs58010457 as a potentially key locus affecting the treatment effect. Different microbiota and enriched pathways might play different roles in the response after two and eight weeks. We found that the area under the curve (AUC) value was greater than 0.8 for both random forest models. The contribution of different components to the AUC was evaluated by removing genetic information, microbiota abundance, and pathway data. The gut microbiome was an important predictor of the response after eight weeks, while genetics was an important predictor of the response after two weeks. These results suggested a dynamic effect of interaction among genetics and gut microbes on treatment. Furthermore, these results provide new guidance for clinical decisions: in cases of inadequate treatment effects after two weeks, the composition of the intestinal flora can be improved by diet therapy, which could ultimately affect the efficacy.",
"role": "user"
},
{
"content": "Different roles of <microbiome>microbiota</microbiome> and genetics in the prediction of treatment response in <DDF>major depressive disorder</DDF>. The roles of <microbiome>gut microbiota</microbiome> and susceptibility genes in <human>patients</human> with <DDF>major depression disorder</DDF> (<DDF>MDD</DDF>) are not well understood. Examining the microbiome and host genetics might be helpful for clinical decision-making. <human>Patients</human> with <DDF>MDD</DDF> were recruited in this study and subsequently treated for eight weeks. We identified the differences between the <human>population</human> with a response after two weeks and those with a response after eight weeks. The factors that were significantly correlated with efficacy were used to predict the treatment response. The differences in the importance of microbiota and genetics in prediction were analyzed. Our study identified <gene>rs58010457</gene> as a potentially key locus affecting the treatment effect. Different microbiota and enriched pathways might play different roles in the response after two and eight weeks. We found that the area under the curve (AUC) value was greater than 0.8 for both <statistical technique>random forest models</statistical technique>. The contribution of different components to the AUC was evaluated by removing genetic information, microbiota abundance, and pathway data. The <microbiome>gut microbiome</microbiome> was an important predictor of the response after eight weeks, while genetics was an important predictor of the response after two weeks. These results suggested a dynamic effect of interaction among genetics and gut microbes on treatment. Furthermore, these results provide new guidance for clinical decisions: in cases of inadequate treatment effects after two weeks, the composition of the <microbiome>intestinal flora</microbiome> can be improved by diet therapy, which could ultimately affect the efficacy.",
"role": "assistant"
}
] |
37049591
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nDysbiosis of the Gut Microbiota and Kynurenine (Kyn) Pathway Activity as Potential Biomarkers in Patients with Major Depressive Disorder. With increasing attention paid to the concept of the microbiota-gut-brain axis, mounting evidence reveals that the gut microbiota is involved in a variety of neurological and psychiatric diseases. However, gut microbiota changes in major depressive disorder (MDD) patients and their association with disease mechanisms remain undefined. Fifty MDD patients and sixty healthy controls were recruited from the Shanghai Healthy Mental Center, China. Fecal samples were collected, and the compositional characteristics of the intestinal flora were determined in MDD patients by MiSeq sequencing. Venous blood was collected for the detection of plasma indoleamine-2,3-dioxygenase (Ido), kynurenine (Kyn) and tryptophan (Trp) levels. Stool samples of bacterial 16S sequencing was carried out. A total of 2,705,809 optimized sequences were obtained, with an average of 54,116 per sample. More unique OTUs were observed at the family, genus and species levels in the control group compared with the MDD cases. Further analysis showed significant changes in the α- and β-diversities and relative abundance levels of gut microbial entities in MDD patients, as well as elevated amounts of Ido and Kyn indicating Kyn pathway activation, KEGG bacterial 16S function prediction analysis shows a variety of amino acids and metabolic (including Ido, Trp and Kyn) changes in the body of patients with MDD. These may result in increased neurotoxic metabolites and reduced generation of serotonin in the disease process. These changed factors may potentially be utilized as biomarkers for MDD in the future, playing more important roles in the disease course.",
"role": "user"
},
{
"content": "<DDF>Dysbiosis of the Gut Microbiota</DDF> and Kynurenine (Kyn) Pathway Activity as Potential Biomarkers in <human>Patients</human> with <DDF>Major Depressive Disorder</DDF>. With increasing attention paid to the concept of the microbiota-gut-brain axis, mounting evidence reveals that the <microbiome>gut microbiota</microbiome> is involved in a variety of <DDF>neurological and psychiatric diseases</DDF>. However, <microbiome>gut microbiota</microbiome> changes in <human>major depressive disorder (MDD) patients</human> and their association with disease mechanisms remain undefined. Fifty <human>MDD patients</human> and sixty <human>healthy controls</human> were recruited from the Shanghai Healthy Mental Center, China. Fecal samples were collected, and the compositional characteristics of the <microbiome>intestinal flora</microbiome> were determined in <human>MDD patients</human> by <biomedical technique>MiSeq sequencing</biomedical technique>. <anatomical location>Venous blood</anatomical location> was collected for the detection of <chemical>plasma indoleamine-2,3-dioxygenase</chemical> (<chemical>Ido</chemical>), <chemical>kynurenine</chemical> (<chemical>Kyn</chemical>) and <chemical>tryptophan</chemical> (<chemical>Trp</chemical>) levels. Stool samples of <biomedical technique>bacterial 16S sequencing</biomedical technique> was carried out. A total of 2,705,809 optimized sequences were obtained, with an average of 54,116 per sample. More unique OTUs were observed at the family, genus and species levels in the <human>control group</human> compared with the <human>MDD cases</human>. Further analysis showed significant changes in the α- and β-diversities and relative abundance levels of gut microbial entities in <human>MDD patients</human>, as well as elevated amounts of <chemical>Ido</chemical> and <chemical>Kyn</chemical> indicating Kyn pathway activation, <biomedical technique>KEGG bacterial 16S function prediction analysis</biomedical technique> shows a variety of <chemical>amino acids</chemical> and metabolic (including <chemical>Ido</chemical>, <chemical>Trp</chemical> and <chemical>Kyn</chemical>) changes in the body of <human>patients</human> with <DDF>MDD</DDF>. These may result in increased <chemical>neurotoxic metabolites</chemical> and reduced generation of <chemical>serotonin</chemical> in the disease process. These changed factors may potentially be utilized as biomarkers for <DDF>MDD</DDF> in the future, playing more important roles in the disease course.",
"role": "assistant"
}
] |
37127945
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nA systematic review on gut-brain axis aberrations in bipolar disorder and methods of balancing the gut microbiota. Bipolar disorder (BD) is a mood disorder that affects millions worldwide. Up to half of the diagnosed patients are reported to not receive adequate treatment. This study aims to assess the relationship between the gut-brain axis and BD and to discuss and compare the efficacy of varying methods of balancing gut microbiotas in BD. Using PubMed, Embase, and Google Scholar from November 2021 to February 2022, we found 5310 studies on gut microbiota and its relation to BD. Using our inclusion criteria, 5283 studies were excluded. A total of 27 full-text articles were assessed for eligibility. Also, 12 articles that met our criteria and eligibility criteria reported on 613 BD patients. Most studies analyzed found an overall difference in gut microbiota composition in bipolar patients compared to healthy controls, though the alterations found were not consistent. Differences in Lactobacillus, Faecalibacterium, and Ruminococcus abundance in BD compared to controls were found to be the most consistent across a few of the studies, but their effects on the gut-brain axis conflicted. Probiotic supplementation was found to lower patient rehospitalizations and significantly improve depressive symptoms and cognitive impairments among patients with BD. Multiple studies included in this review point toward a possible link between BD and the gut microbiota. Probiotic supplements and other gut-balancing therapies could serve as effective adjunctive methods for the treatment of BD. Notable limitations of the studies included for analysis were small sample sizes and majority observational study designs. Furthermore, the microbiota aberrations found in patients with BD were not consistent across multiple studies. Despite these limitations, our findings demonstrate the need for further research regarding the relationship between aberrant gut microbiota profiles and BD, as well as the effectiveness of gut balancing methods as adjunctive treatments.",
"role": "user"
},
{
"content": "A systematic review on gut-brain axis aberrations in <DDF>bipolar disorder</DDF> and methods of balancing the <microbiome>gut microbiota</microbiome>. <DDF>Bipolar disorder</DDF> (<DDF>BD</DDF>) is a <DDF>mood disorder</DDF> that affects millions worldwide. Up to half of the <human>diagnosed patients</human> are reported to not receive adequate treatment. This study aims to assess the relationship between the gut-brain axis and <DDF>BD</DDF> and to discuss and compare the efficacy of varying methods of balancing <microbiome>gut microbiotas</microbiome> in <DDF>BD</DDF>. Using PubMed, Embase, and Google Scholar from November 2021 to February 2022, we found 5310 studies on <microbiome>gut microbiota</microbiome> and its relation to <DDF>BD</DDF>. Using our inclusion criteria, 5283 studies were excluded. A total of 27 full-text articles were assessed for eligibility. Also, 12 articles that met our criteria and eligibility criteria reported on 613 <human>BD patients</human>. Most studies analyzed found an overall difference in gut microbiota composition in <human>bipolar patients</human> compared to <human>healthy controls</human>, though the alterations found were not consistent. Differences in <bacteria>Lactobacillus</bacteria>, <bacteria>Faecalibacterium</bacteria>, and <bacteria>Ruminococcus</bacteria> abundance in <DDF>BD</DDF> compared to <human>controls</human> were found to be the most consistent across a few of the studies, but their effects on the gut-brain axis conflicted. <dietary supplement>Probiotic supplementation</dietary supplement> was found to lower patient rehospitalizations and significantly improve <DDF>depressive symptoms</DDF> and <DDF>cognitive impairments</DDF> among <human>patients</human> with <DDF>BD</DDF>. Multiple studies included in this review point toward a possible link between <DDF>BD</DDF> and the <microbiome>gut microbiota</microbiome>. <dietary supplement>Probiotic supplements</dietary supplement> and other gut-balancing therapies could serve as effective adjunctive methods for the treatment of <DDF>BD</DDF>. Notable limitations of the studies included for analysis were small sample sizes and majority observational study designs. Furthermore, the microbiota aberrations found in <human>patients</human> with <DDF>BD</DDF> were not consistent across multiple studies. Despite these limitations, our findings demonstrate the need for further research regarding the relationship between aberrant gut microbiota profiles and <DDF>BD</DDF>, as well as the effectiveness of gut balancing methods as adjunctive treatments.",
"role": "assistant"
}
] |
37156128
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nComparison of gut microbiome profile in patients with schizophrenia and healthy controls - A plausible non-invasive biomarker? The human gut microbiome regulates brain function through the microbiome-gut-brain axis and is implicated in several neuropsychiatric disorders. However, the relationship between the gut microbiome and the pathogenesis of schizophrenia (SCZ) is poorly defined, and very few studies have examined the effect of antipsychotic treatment response. We aim to study the differences in the gut microbiota among drug-naïve (DN SCZ) and risperidone-treated SCZ patients (RISP SCZ), compared to healthy controls (HCs). We recruited a total of 60 participants, from the clinical services of a large neuropsychiatric hospital, which included DN SCZ, RISP SCZ and HCs (n = 20 each). Fecal samples were analyzed using 16s rRNA sequencing in this cross-sectional study. No significant differences were found in taxa richness (alpha diversity) but microbial composition differed between SCZ patients (both DN and RISP) and HCs (PERMANOVA, p = 0.02). Linear Discriminant Analysis Effect Size (LEfSe) and Random Forest model identified the top six genera, which significantly differed in abundance between the study groups. A specific genus-level microbial panel of Ruminococcus, UCG005, Clostridium_sensu_stricto_1 and Bifidobacterium could discriminate SCZ patients from HCs with an area under the curve (AUC) of 0.79, HCs vs DN SCZ (AUC: 0.68), HCs vs RISP SCZ (AUC: 0.93) and DN SCZ vs RISP SCZ (AUC: 0.87). Our study identified distinct microbial signatures that could aid in the differentiation of DN SCZ, RISP SCZ, and HCs. Our findings contribute to a better understanding of the role of the gut microbiome in SCZ pathophysiology and suggest potential targeted interventions.",
"role": "user"
},
{
"content": "Comparison of gut microbiome profile in <human>patients</human> with <DDF>schizophrenia</DDF> and <human>healthy controls</human> - A plausible non-invasive biomarker? The <microbiome>human gut microbiome</microbiome> regulates brain function through the microbiome-gut-brain axis and is implicated in several <DDF>neuropsychiatric disorders</DDF>. However, the relationship between the <microbiome>gut microbiome</microbiome> and the pathogenesis of <DDF>schizophrenia</DDF> (<DDF>SCZ</DDF>) is poorly defined, and very few studies have examined the effect of antipsychotic treatment response. We aim to study the differences in the <microbiome>gut microbiota</microbiome> among <human>drug-naïve (DN SCZ) and risperidone-treated SCZ patients</human> (<human>RISP SCZ</human>), compared to <human>healthy controls</human> (<human>HCs</human>). We recruited a total of 60 <human>participants</human>, from the clinical services of a large neuropsychiatric hospital, which included <human>DN SCZ</human>, <human>RISP SCZ</human> and <human>HCs</human> (n = 20 each). Fecal samples were analyzed using <biomedical technique>16s rRNA sequencing</biomedical technique> in this cross-sectional study. No significant differences were found in taxa richness (alpha diversity) but microbial composition differed between <human>SCZ patients</human> (both <human>DN</human> and <human>RISP</human>) and <human>HCs</human> (<statistical technique>PERMANOVA</statistical technique>, p = 0.02). <statistical technique>Linear Discriminant Analysis Effect Size</statistical technique> (<statistical technique>LEfSe</statistical technique>) and <statistical technique>Random Forest model</statistical technique> identified the top six genera, which significantly differed in abundance between the study groups. A specific genus-level microbial panel of <bacteria>Ruminococcus</bacteria>, <bacteria>UCG005</bacteria>, <bacteria>Clostridium_sensu_stricto_1</bacteria> and <bacteria>Bifidobacterium</bacteria> could discriminate <human>SCZ patients</human> from <human>HCs</human> with an area under the curve (AUC) of 0.79, <human>HCs</human> vs <human>DN SCZ</human> (AUC: 0.68), <human>HCs</human> vs <human>RISP SCZ</human> (AUC: 0.93) and <human>DN SCZ</human> vs <human>RISP SCZ</human> (AUC: 0.87). Our study identified distinct microbial signatures that could aid in the differentiation of <human>DN SCZ</human>, <human>RISP SCZ</human>, and <human>HCs</human>. Our findings contribute to a better understanding of the role of the <microbiome>gut microbiome</microbiome> in SCZ pathophysiology and suggest potential targeted interventions.",
"role": "assistant"
}
] |
37193253
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nAnxiety Disorders and Gut Dysbiosis in Primary Sjögren's Syndrome-Mediated Dry Eye Patients. Primary Sjögren's syndrome (pSS), a disease that is associated with a high prevalence of psychological disorders, has become increasingly important. Interactions between the gut microbiota and ocular conditions have been identified in pSS. As mental intervention is frequently needed, this study aims to investigate the relationship between anxiety disorders and the gut microbiome in patients with pSS-mediated dry eye. Demographics and self-administered questionnaires were obtained. Faecal samples were evaluated using 16S ribosomal RNA gene sequencing. The Hospital Anxiety and Depression Scale (HADS-A) cut-off point of ≥ 8 points showed a sensitivity and specificity of 76.5% and 80.0%, respectively. In all participants, we found that the prevalence of anxiety disorder was 30.4%. Dry eye discomfort could promote an anxious state, and conversely, anxiety could threaten tear film and increase the risk of pSS activity. There was a certain correlation between anxiety disorder and gut dysbiosis. Prevotella was associated with dry eye severity (<i>p</i> <0.001). Bacteroidetes (<i>p</i> =0.046) and Odoribacter (<i>p</i> =0.001) were correlated with pSS activity. There is a bidirectional relationship between anxiety disorder and the gut microbiota in pSS-mediated dry eye. Alterations in certain classes of gut microbiota are associated with pSS activity and dry eye severity. Main gut microbiota alterations that have a facilitating impact on anxiety are emerging in pSS-mediated dry eye. Future studies are needed to explore specific therapeutic targets for improving mental health in pSS-mediated dry eye by microbiota intervention.",
"role": "user"
},
{
"content": "<DDF>Anxiety Disorders</DDF> and <DDF>Gut Dysbiosis</DDF> in <human>Primary Sjögren's Syndrome-Mediated Dry Eye Patients</human>. <DDF>Primary Sjögren's syndrome</DDF> (<DDF>pSS</DDF>), a disease that is associated with a high prevalence of <DDF>psychological disorders</DDF>, has become increasingly important. Interactions between the <microbiome>gut microbiota</microbiome> and <DDF>ocular conditions</DDF> have been identified in <DDF>pSS</DDF>. As mental intervention is frequently needed, this study aims to investigate the relationship between <DDF>anxiety disorders</DDF> and the <microbiome>gut microbiome</microbiome> in <human>patients</human> with <DDF>pSS-mediated dry eye</DDF>. Demographics and self-administered questionnaires were obtained. Faecal samples were evaluated using <biomedical technique>16S ribosomal RNA gene sequencing</biomedical technique>. The Hospital Anxiety and Depression Scale (HADS-A) cut-off point of ≥ 8 points showed a sensitivity and specificity of 76.5% and 80.0%, respectively. In all <human>participants</human>, we found that the prevalence of <DDF>anxiety disorder</DDF> was 30.4%. <DDF>Dry eye discomfort</DDF> could promote an anxious state, and conversely, <DDF>anxiety</DDF> could threaten tear film and increase the risk of pSS activity. There was a certain correlation between <DDF>anxiety disorder</DDF> and <DDF>gut dysbiosis</DDF>. <bacteria>Prevotella</bacteria> was associated with dry eye severity (<i>p</i> <0.001). <bacteria>Bacteroidetes</bacteria> (<i>p</i> =0.046) and <bacteria>Odoribacter</bacteria> (<i>p</i> =0.001) were correlated with pSS activity. There is a bidirectional relationship between <DDF>anxiety disorder</DDF> and the <microbiome>gut microbiota</microbiome> in pSS-mediated dry eye. Alterations in certain classes of <microbiome>gut microbiota</microbiome> are associated with pSS activity and dry eye severity. <DDF>Main gut microbiota alterations</DDF> that have a facilitating impact on <DDF>anxiety</DDF> are emerging in <DDF>pSS-mediated dry eye</DDF>. Future studies are needed to explore specific therapeutic targets for improving mental health in <DDF>pSS-mediated dry eye</DDF> by microbiota intervention.",
"role": "assistant"
}
] |
37291666
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nA comprehensive look at the psychoneuroimmunoendocrinology of spinal cord injury and its progression: mechanisms and clinical opportunities. Spinal cord injury (SCI) is a devastating and disabling medical condition generally caused by a traumatic event (primary injury). This initial trauma is accompanied by a set of biological mechanisms directed to ameliorate neural damage but also exacerbate initial damage (secondary injury). The alterations that occur in the spinal cord have not only local but also systemic consequences and virtually all organs and tissues of the body incur important changes after SCI, explaining the progression and detrimental consequences related to this condition. Psychoneuroimmunoendocrinology (PNIE) is a growing area of research aiming to integrate and explore the interactions among the different systems that compose the human organism, considering the mind and the body as a whole. The initial traumatic event and the consequent neurological disruption trigger immune, endocrine, and multisystem dysfunction, which in turn affect the patient's psyche and well-being. In the present review, we will explore the most important local and systemic consequences of SCI from a PNIE perspective, defining the changes occurring in each system and how all these mechanisms are interconnected. Finally, potential clinical approaches derived from this knowledge will also be collectively presented with the aim to develop integrative therapies to maximize the clinical management of these patients.",
"role": "user"
},
{
"content": "A comprehensive look at the psychoneuroimmunoendocrinology of <DDF>spinal cord injury</DDF> and its progression: mechanisms and clinical opportunities. <DDF>Spinal cord injury</DDF> (<DDF>SCI</DDF>) is a devastating and disabling medical condition generally caused by a traumatic event (primary injury). This initial trauma is accompanied by a set of biological mechanisms directed to ameliorate <DDF>neural damage</DDF> but also exacerbate initial damage (secondary injury). The alterations that occur in the <anatomical location>spinal cord</anatomical location> have not only local but also systemic consequences and virtually all organs and tissues of the body incur important changes after <DDF>SCI</DDF>, explaining the progression and detrimental consequences related to this condition. Psychoneuroimmunoendocrinology (PNIE) is a growing area of research aiming to integrate and explore the interactions among the different systems that compose the human organism, considering the mind and the body as a whole. The initial traumatic event and the consequent <DDF>neurological disruption</DDF> trigger <DDF>immune, endocrine, and multisystem dysfunction</DDF>, which in turn affect the patient's psyche and well-being. In the present review, we will explore the most important local and systemic consequences of <DDF>SCI</DDF> from a PNIE perspective, defining the changes occurring in each system and how all these mechanisms are interconnected. Finally, potential clinical approaches derived from this knowledge will also be collectively presented with the aim to develop integrative therapies to maximize the clinical management of these <human>patients</human>.",
"role": "assistant"
}
] |
37400971
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nMaternal microbiome disturbance induces deficits in the offspring's behaviors: a systematic review and meta-analysis. Recent evidence has suggested that changes in maternal gut microbiota in early life may generate neurobiological consequences associated with psychiatric-related abnormalities. However, the number of studies on humans investigating this problem is limited, and preclinical findings sometimes conflict. Therefore, we run a meta-analysis to examine whether maternal microbiota disturbance (MMD) during neurodevelopment might affect the offspring during adulthood. We found thirteen studies, from a set of 459 records selected by strategy registered on PROSPERO (#289224), to target preclinical studies that evaluated the behavioral outcomes of the rodents generated by dams submitted to perinatal enteric microbiota perturbation. The analysis revealed a significant effect size (SMD = -0.51, 95% CI = -0.79 to -0.22, <i>p</i> < .001, T2 = 0.54, I2 = 79.85%), indicating that MMD might provoke behavioral impairments in the adult offspring. The MMD also induces a significant effect size for the reduction of the sociability behavior (SMD = -0.63, 95% CI = -1.18 to -0.07, <i>p</i> = 0.011, T2 = 0.30, I2 = 76.11%) and obsessive-compulsive-like behavior (SMD = -0.68, 95% CI = -0.01 to -1.36, <i>p</i> = 0.009, T2 = 0.25, I2 = 62.82%) parameters. The effect size was not significant or inconclusive for memory and anxiety-like behavior, or inconclusive for schizophrenia-like and depressive-like behavior. Therefore, experimental perinatal MMD is vertically transmitted to the offspring, negatively impacting behavioral parameters related to psychiatric disorders.",
"role": "user"
},
{
"content": "<DDF>Maternal microbiome disturbance</DDF> induces deficits in the offspring's behaviors: a systematic review and meta-analysis. Recent evidence has suggested that changes in <microbiome>maternal gut microbiota</microbiome> in early life may generate neurobiological consequences associated with <DDF>psychiatric-related abnormalities</DDF>. However, the number of studies on <human>humans</human> investigating this problem is limited, and preclinical findings sometimes conflict. Therefore, we run a meta-analysis to examine whether <DDF>maternal microbiota disturbance</DDF> (<DDF>MMD</DDF>) during neurodevelopment might affect the <animal>offspring</animal> during adulthood. We found thirteen studies, from a set of 459 records selected by strategy registered on PROSPERO (#289224), to target preclinical studies that evaluated the behavioral outcomes of the <animal>rodents</animal> generated by dams submitted to <DDF>perinatal enteric microbiota perturbation</DDF>. The analysis revealed a significant effect size (SMD = -0.51, 95% CI = -0.79 to -0.22, <i>p</i> < .001, T2 = 0.54, I2 = 79.85%), indicating that <DDF>MMD</DDF> might provoke <DDF>behavioral impairments</DDF> in the <animal>adult offspring</animal>. The <DDF>MMD</DDF> also induces a significant effect size for the reduction of the sociability behavior (SMD = -0.63, 95% CI = -1.18 to -0.07, <i>p</i> = 0.011, T2 = 0.30, I2 = 76.11%) and <DDF>obsessive-compulsive-like behavior</DDF> (SMD = -0.68, 95% CI = -0.01 to -1.36, <i>p</i> = 0.009, T2 = 0.25, I2 = 62.82%) parameters. The effect size was not significant or inconclusive for memory and anxiety-like behavior, or inconclusive for <DDF>schizophrenia-like and depressive-like behavior</DDF>. Therefore, <DDF>experimental perinatal MMD</DDF> is vertically transmitted to the <animal>offspring</animal>, negatively impacting behavioral parameters related to <DDF>psychiatric disorders</DDF>.",
"role": "assistant"
}
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37449597
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGut-microbiome-brain axis: the crosstalk between the vagus nerve, alpha-synuclein and the brain in Parkinson's disease. This critical review of the literature shows that there is a close link between the microbiome, the gut, and the brain in Parkinson's disease. The vagus nerve, the main component of the parasympathetic nervous system, is involved in the regulation of immune response, digestion, heart rate, and control of mood. It can detect microbiota metabolites through its afferents, transferring this gut information to the central nervous system. Preclinical and clinical studies have shown the important role played by the gut microbiome and gut-related factors in disease development and progression, as well as treatment responses. These findings suggest that the gut microbiome may be a valuable target for new therapeutic strategies for Parkinson's disease. More studies are needed to better understand the underlying biology and how this axis can be modulated for the patient's benefit.",
"role": "user"
},
{
"content": "Gut-microbiome-brain axis: the crosstalk between the <anatomical location>vagus nerve</anatomical location>, <chemical>alpha-synuclein</chemical> and the <anatomical location>brain</anatomical location> in <DDF>Parkinson's disease</DDF>. This critical review of the literature shows that there is a close link between the microbiome, the <anatomical location>gut</anatomical location>, and the <anatomical location>brain</anatomical location> in <DDF>Parkinson's disease</DDF>. The <anatomical location>vagus nerve</anatomical location>, the main component of the parasympathetic nervous system, is involved in the regulation of immune response, digestion, heart rate, and control of mood. It can detect microbiota metabolites through its afferents, transferring this gut information to the central nervous system. Preclinical and clinical studies have shown the important role played by the <microbiome>gut microbiome</microbiome> and gut-related factors in disease development and progression, as well as treatment responses. These findings suggest that the <microbiome>gut microbiome</microbiome> may be a valuable target for new therapeutic strategies for <DDF>Parkinson's disease</DDF>. More studies are needed to better understand the underlying biology and how this axis can be modulated for the patient's benefit.",
"role": "assistant"
}
] |
37468912
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nAltered gut microbiota-host bile acid metabolism in IBS-D patients with liver depression and spleen deficiency pattern. Dysregulation of gut microbiota-host bile acid (BA) co-metabolism is a critical pathogenic factor of diarrhea-predominant irritable bowel syndrome (IBS-D). Traditional Chinese Medicine (TCM), instructed by pattern differentiation, is effective in treating IBS-D, in which liver depression and spleen deficiency (LDSD) is the most prevalent pattern. Still, it is unclear the linkage between the LDSD pattern and the BA metabolic phenotype. This study aimed to uncover the biological basis of the LDSD pattern from the BA metabolic perspective. Patients with IBS-D completed questionnaires regarding the irritable bowel severity scoring system (IBS-SSS), stool frequency, Stool Bristol scale, and Self-Rating Scales of mental health. Fasting blood and morning feces were collected to analyze the gut metagenome and BA-related indices/metabolites. IBS-D patients with LDSD had a higher incidence of BA overexcretion (41% vs. 23% non-LDSD) with significant elevations in fecal total BAs and serum BA precursor 7α-hydroxy-4-cholesten-3-one levels. Compared to controls or non-LDSD patients, LDSD patients had a featured fecal BA profile, with higher proportions of deoxycholic acid (DCA), 7-ketodeoxycholic acid, and lithocholic acid. It is consistent with the BA-metabolizing genomic changes in the LDSD gut microbiota characterized by overabundances of 7-dehydroxylating bacteria and BA-inducible genes (baiCD/E/H). The score of bowel symptoms (stool frequency and abdominal pain) showing greater severity in the LDSD pattern were positively correlated with bai-expressing bacterial abundances and fecal DCA levels separately. We clarified a differed BA metabolic phenotype in IBS patients with LDSD, which closely correlates with the severity of bowel symptoms. It demonstrates that gut microbiota and host co-metabolism of BAs would provide crucial insight into the biology of the LDSD pattern and its internal relationship with IBS progression.",
"role": "user"
},
{
"content": "<DDF>Altered gut microbiota-host bile acid metabolism</DDF> in <human>IBS-D patients</human> with <DDF>liver depression</DDF> and <DDF>spleen deficiency pattern</DDF>. <DDF>Dysregulation of gut microbiota-host bile acid (BA) co-metabolism</DDF> is a critical pathogenic factor of <DDF>diarrhea-predominant irritable bowel syndrome</DDF> (<DDF>IBS-D</DDF>). Traditional Chinese Medicine (TCM), instructed by pattern differentiation, is effective in treating <DDF>IBS-D</DDF>, in which <DDF>liver depression and spleen deficiency</DDF> (<DDF>LDSD</DDF>) is the most prevalent pattern. Still, it is unclear the linkage between the LDSD pattern and the BA metabolic phenotype. This study aimed to uncover the biological basis of the LDSD pattern from the BA metabolic perspective. <human>Patients</human> with <DDF>IBS-D</DDF> completed questionnaires regarding the irritable bowel severity scoring system (IBS-SSS), stool frequency, Stool Bristol scale, and Self-Rating Scales of mental health. Fasting blood and morning feces were collected to analyze the gut metagenome and BA-related indices/metabolites. <human>IBS-D patients</human> with <DDF>LDSD</DDF> had a higher incidence of BA overexcretion (41% vs. 23% non-LDSD) with significant elevations in fecal total BAs and <chemical>serum BA precursor 7α-hydroxy-4-cholesten-3-one</chemical> levels. Compared to <human>controls</human> or <human>non-LDSD patients</human>, <human>LDSD patients</human> had a featured fecal BA profile, with higher proportions of <chemical>deoxycholic acid</chemical> (<chemical>DCA</chemical>), <chemical>7-ketodeoxycholic acid</chemical>, and <chemical>lithocholic acid</chemical>. It is consistent with the BA-metabolizing genomic changes in the <microbiome>LDSD gut microbiota</microbiome> characterized by overabundances of <bacteria>7-dehydroxylating bacteria</bacteria> and <gene>BA-inducible genes</gene> (<gene>baiCD/E/H</gene>). The score of bowel symptoms (stool frequency and <DDF>abdominal pain</DDF>) showing greater severity in the LDSD pattern were positively correlated with bai-expressing bacterial abundances and fecal DCA levels separately. We clarified a differed BA metabolic phenotype in <human>IBS patients</human> with <DDF>LDSD</DDF>, which closely correlates with the severity of bowel symptoms. It demonstrates that <microbiome>gut microbiota</microbiome> and host co-metabolism of <chemical>BAs</chemical> would provide crucial insight into the biology of the LDSD pattern and its internal relationship with IBS progression.",
"role": "assistant"
}
] |
37485386
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nPrebiotics for depression: how does the gut microbiota play a role? Depression, a mood disorder characterized by persistent feelings of sadness and aversion to activity that can interfere with daily life, is a condition of great concern. Prebiotics, which are non-digestible substances selectively utilized by host microorganisms for health benefits, have gained attention for their potential to improve overall wellness and alleviate various disorders including depression. This study aims to review clinical trials utilizing carbohydrate-type prebiotics such as inulin-type fructans, galactooligosaccharides (GOS), human milk oligosaccharides, resistant starch, prebiotic phytochemicals including epigallocatechin gallate (EGCG), chlorogenic acids, resveratrol, and prebiotic lipids (n-3 polysaturated fatty acids) to determine their effects on depression. Our findings suggest that GOS at a daily dosage of 5 g and eicosapentaenoic acid at or less than 1 g can effectively mitigate depressive symptoms. While EGCG exhibits potential antidepressant properties, a higher dosage of 3 g/d may be necessary to elicit significant effects. The plausible mechanisms underlying the impact of prebiotics on depression include the synthesis of neurotransmitters, production of short-chain fatty acids, and regulation of inflammation.",
"role": "user"
},
{
"content": "<dietary supplement>Prebiotics</dietary supplement> for <DDF>depression</DDF>: how does the <microbiome>gut microbiota</microbiome> play a role? <DDF>Depression</DDF>, a <DDF>mood disorder</DDF> characterized by persistent feelings of sadness and aversion to activity that can interfere with daily life, is a condition of great concern. <dietary supplement>Prebiotics</dietary supplement>, which are non-digestible substances selectively utilized by <bacteria>host microorganisms</bacteria> for health benefits, have gained attention for their potential to improve overall wellness and alleviate various disorders including <DDF>depression</DDF>. This study aims to review clinical trials utilizing <dietary supplement>carbohydrate-type prebiotics</dietary supplement> such as <dietary supplement>inulin-type fructans</dietary supplement>, <dietary supplement>galactooligosaccharides</dietary supplement> (<dietary supplement>GOS</dietary supplement>), <dietary supplement>human milk oligosaccharides</dietary supplement>, <dietary supplement>resistant starch</dietary supplement>, <chemical>prebiotic phytochemicals</chemical> including <chemical>epigallocatechin gallate</chemical> (<chemical>EGCG</chemical>), <chemical>chlorogenic acids</chemical>, <chemical>resveratrol</chemical>, and <chemical>prebiotic lipids</chemical> (<chemical>n-3 polysaturated fatty acids</chemical>) to determine their effects on <DDF>depression</DDF>. Our findings suggest that <dietary supplement>GOS</dietary supplement> at a daily dosage of 5 g and <chemical>eicosapentaenoic acid</chemical> at or less than 1 g can effectively mitigate <DDF>depressive symptoms</DDF>. While <chemical>EGCG</chemical> exhibits potential antidepressant properties, a higher dosage of 3 g/d may be necessary to elicit significant effects. The plausible mechanisms underlying the impact of <dietary supplement>prebiotics</dietary supplement> on <DDF>depression</DDF> include the synthesis of <chemical>neurotransmitters</chemical>, production of <chemical>short-chain fatty acids</chemical>, and regulation of <DDF>inflammation</DDF>.",
"role": "assistant"
}
] |
37502424
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nEffects of human probiotics on memory and psychological and physical measures in community-dwelling older adults with normal and mildly impaired cognition: results of a bi-center, double-blind, randomized, and placebo-controlled clinical trial (CleverAge biota). This study presents results of our randomized clinical trial studying the effect of human probiotics on memory and psychological and physical measures following our study protocol registered at clinicaltrials.gov NCT05051501 and described in detail in our previous paper. Community dwelling participants aged between 55 and 80 years were randomly assigned to receive a single dose of 10<sup>6</sup> colony-forming units of human <i>Streptococcus thermophilus</i> GH, <i>Streptococcus salivarius</i> GH NEXARS, Lactobacilus plantarum GH, and <i>Pediococcus pentosaceus</i> GH or placebo. A cross-over design allowed each group to receive probiotics and placebo for 3 months each in reverse order. A small subset of participants was examined online due to the COVID-19 pandemic. After 6 months a small number of volunteers were additionally assessed after 2 months without any intervention. Primary outcome measures included changes in cognitive functions assessed using brief tests and a neuropsychological battery and changes in mood assessed using validated questionnaires. Secondary outcome measures included changes in self-report and subjective measures using depression and anxiety questionnaires, seven visual analog scales of subjective feelings (memory, digestion, etc.), and physical performance. At baseline, the probiotic-placebo group A (<i>n</i> = 40, age 69 ± 7 years, education 16 ± 3 years, 63% females, body mass index 28.5 ± 6, subjective memory complaint in 43%) did not differ from the placebo-probiotic group B (<i>n</i> = 32) in any of the sociodemographic characteristics and evaluated measures including cognitive status. At follow-up visits after 3, 6, and 8 months, no cross-sectional differences in any of the measures were found between the groups except worse sentence recall of the ALBA test after 3 months of probiotic use. Score changes were not observed for all cognitive tests but one in any group between visits 1 and 3 and between visits 3 and 6. The only change was observed for the TMT B test after the first three months but no change was observed after the second three months. The treatment with human probiotics and prebiotics did not improve cognitive, affective, or physical measures in community-dwelling individuals with normal or mildly impaired cognitive functions. clinicaltrials.gov, identifier NCT05051501.",
"role": "user"
},
{
"content": "Effects of <dietary supplement>human probiotics</dietary supplement> on memory and psychological and physical measures in <human>community-dwelling older adults</human> with normal and <DDF>mildly impaired cognition</DDF>: results of a <biomedical technique>bi-center, double-blind, randomized, and placebo-controlled clinical trial</biomedical technique> (<biomedical technique>CleverAge biota</biomedical technique>). This study presents results of our randomized clinical trial studying the effect of <dietary supplement>human probiotics</dietary supplement> on memory and psychological and physical measures following our study protocol registered at clinicaltrials.gov NCT05051501 and described in detail in our previous paper. <human>Community dwelling participants</human> aged between 55 and 80 years were randomly assigned to receive a single dose of 10<sup>6</sup> colony-forming units of <bacteria>human <i>Streptococcus thermophilus</i> GH</bacteria>, <i><bacteria>Streptococcus salivarius</i> GH NEXARS</bacteria>, <bacteria>Lactobacilus plantarum GH</bacteria>, and <bacteria><i>Pediococcus pentosaceus</i> GH</bacteria> or placebo. A cross-over design allowed each group to receive <dietary supplement>probiotics</dietary supplement> and <drug>placebo</drug> for 3 months each in reverse order. A small subset of <human>participants</human> was examined online due to the COVID-19 pandemic. After 6 months a small number of <human>volunteers</human> were additionally assessed after 2 months without any intervention. Primary outcome measures included changes in cognitive functions assessed using brief tests and a <biomedical technique>neuropsychological battery</biomedical technique> and changes in mood assessed using <biomedical technique>validated questionnaires</biomedical technique>. Secondary outcome measures included changes in self-report and subjective measures using <biomedical technique>depression and anxiety questionnaires</biomedical technique>, seven visual analog scales of subjective feelings (memory, digestion, etc.), and physical performance. At baseline, the <human>probiotic-placebo group A</human> (<i>n</i> = 40, age 69 ± 7 years, education 16 ± 3 years, 63% <human>females</human>, body mass index 28.5 ± 6, <DDF>subjective memory complaint</DDF> in 43%) did not differ from the <human>placebo-probiotic group B</human> (<i>n</i> = 32) in any of the sociodemographic characteristics and evaluated measures including cognitive status. At follow-up visits after 3, 6, and 8 months, no cross-sectional differences in any of the measures were found between the groups except worse sentence recall of the <biomedical technique>ALBA test</biomedical technique> after 3 months of <dietary supplement>probiotic use</dietary supplement>. Score changes were not observed for all cognitive tests but one in any group between visits 1 and 3 and between visits 3 and 6. The only change was observed for the <biomedical technique>TMT B</biomedical technique> test after the first three months but no change was observed after the second three months. The treatment with <dietary supplement>human probiotics and prebiotics</dietary supplement> did not improve cognitive, affective, or physical measures in <human>community-dwelling individuals</human> with normal or <DDF>mildly impaired cognitive functions</DDF>. clinicaltrials.gov, identifier NCT05051501.",
"role": "assistant"
}
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37576972
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nProfiles and diagnostic value of intestinal microbiota in schizophrenia patients with metabolic syndrome. It is widely thought that the intestinal microbiota plays a significant role in the pathogenesis of metabolic disorders. However, the gut microbiota composition and characteristics of schizophrenia patients with metabolic syndrome (MetS) have been largely understudied. Herein, we investigated the association between the metabolic status of mainland Chinese schizophrenia patients with MetS and the intestinal microbiome. Fecal microbiota communities from 115 male schizophrenia patients (57 with MetS and 58 without MetS) were assessed by 16S ribosomal RNA gene sequencing. We assessed the variations of gut microbiome between both groups and explored potential associations between intestinal microbiota and parameters of MetS. In addition, the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) based on the KEGG database was used to predict the function of intestinal microbiota. We also conducted Decision Tree Analysis to develop a diagnostic model for the MetS in patients with schizophrenia based on the composition of intestinal microbiota. The fecal microbial diversity significantly differed between groups with or without MetS (α-diversity (Shannon index and Simpson index): p=0.0155, p=0.0089; β-diversity: p=0.001). Moreover, the microbial composition was significantly different between the two groups, involving five phyla and 38 genera (p<0.05). In addition, a significant correlation was observed between the metabolic-related parameters and abundance of altered microbiota including HDL-c (r2 = 0.203, p=0.0005), GLU (r2 = 0.286, p=0.0005) and WC (r2 = 0.061, p=0.037). Furthermore, KEGG pathway analysis showed that 16 signaling pathways were significantly enriched between the two groups (p<0.05). Importantly, our diagnostic model based on five microorganisms established by decision tree analysis could effectively distinguish between patients with and without MetS (AUC = 0.94). Our study established the compositional and functional characteristics of intestinal microbiota in schizophrenia patients with MetS. These new findings provide novel insights into a better understanding of this disease and provide the theoretical basis for implementing new interventional therapies in clinical practice.",
"role": "user"
},
{
"content": "Profiles and diagnostic value of <microbiome>intestinal microbiota</microbiome> in <human>schizophrenia patients</human> with <DDF>metabolic syndrome</DDF>. It is widely thought that the <microbiome>intestinal microbiota</microbiome> plays a significant role in the pathogenesis of <DDF>metabolic disorders</DDF>. However, the gut microbiota composition and characteristics of <human>schizophrenia patients</human> with <DDF>metabolic syndrome</DDF> (<DDF>MetS</DDF>) have been largely understudied. Herein, we investigated the association between the metabolic status of <human>mainland Chinese schizophrenia patients</human> with <DDF>MetS</DDF> and the <microbiome>intestinal microbiome</microbiome>. <microbiome>Fecal microbiota</microbiome> communities from 115 <human>male schizophrenia patients</human> (57 with <DDF>MetS</DDF> and 58 without <DDF>MetS</DDF>) were assessed by <biomedical technique>16S ribosomal RNA gene sequencing</biomedical technique>. We assessed the variations of <microbiome>gut microbiome</microbiome> between both groups and explored potential associations between <microbiome>intestinal microbiota</microbiome> and parameters of <DDF>MetS</DDF>. In addition, the <biomedical technique>Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt)</biomedical technique> based on the KEGG database was used to predict the function of <microbiome>intestinal microbiota</microbiome>. We also conducted <statistical technique>Decision Tree Analysis</statistical technique> to develop a diagnostic model for the <DDF>MetS</DDF> in <human>patients</human> with <DDF>schizophrenia</DDF> based on the composition of <microbiome>intestinal microbiota</microbiome>. The fecal microbial diversity significantly differed between groups with or without <DDF>MetS</DDF> (α-diversity (<statistical technique>Shannon index</statistical technique> and <statistical technique>Simpson index</statistical technique>): p=0.0155, p=0.0089; β-diversity: p=0.001). Moreover, the microbial composition was significantly different between the two groups, involving five phyla and 38 genera (p<0.05). In addition, a significant correlation was observed between the metabolic-related parameters and abundance of altered microbiota including <chemical>HDL-c</chemical> (r2 = 0.203, p=0.0005), <chemical>GLU</chemical> (r2 = 0.286, p=0.0005) and WC (r2 = 0.061, p=0.037). Furthermore, <biomedical technique>KEGG pathway analysis</biomedical technique> showed that 16 signaling pathways were significantly enriched between the two groups (p<0.05). Importantly, our diagnostic model based on five microorganisms established by <statistical technique>decision tree analysis</statistical technique> could effectively distinguish between <human>patients</human> with and without <DDF>MetS</DDF> (AUC = 0.94). Our study established the compositional and functional characteristics of <microbiome>intestinal microbiota</microbiome> in <human>schizophrenia patients</human> with <DDF>MetS</DDF>. These new findings provide novel insights into a better understanding of this disease and provide the theoretical basis for implementing new interventional therapies in clinical practice.",
"role": "assistant"
}
] |
37607587
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGastrointestinal Dysfunction in Neurological and Neurodegenerative Disorders. Increasing research links the gut microbiome to neurodegenerative disorders. The gut microbiome communicates with the central nervous system via the gut-brain axis and affects behavioral and cognitive phenotypes. Dysbiosis (a dysfunctional microbiome) drives increased intestinal permeability and inflammation that can negatively affect the brain via the gut-brain axis. Healthier metabolic and lipid profiles and cognitive phenotypes are observed in individuals with more distinct microbiomes. In this review, we discuss the role of the gut microbiome and gut-brain axis in neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease and related animal models, in cancer and cancer treatments, and in metabolic syndrome. We also discuss strategies to improve the gut microbiome and ultimately brain function. Because healthier cognitive phenotypes are observed in individuals with more distinct microbiomes, increased efforts are warranted to develop therapeutic strategies for those at increased risk of developing neurological disorders and patients diagnosed with those disorders.",
"role": "user"
},
{
"content": "<DDF>Gastrointestinal Dysfunction</DDF> in <DDF>Neurological and Neurodegenerative Disorders</DDF>. Increasing research links the <microbiome>gut microbiome</microbiome> to <DDF>neurodegenerative disorders</DDF>. The <microbiome>gut microbiome</microbiome> communicates with the central nervous system via the gut-brain axis and affects behavioral and cognitive phenotypes. <DDF>Dysbiosis</DDF> (a <DDF>dysfunctional microbiome</DDF>) drives increased intestinal permeability and <DDF>inflammation</DDF> that can negatively affect the <anatomical location>brain</anatomical location> via the gut-brain axis. Healthier metabolic and lipid profiles and cognitive phenotypes are observed in <human>individuals</human> with more distinct microbiomes. In this review, we discuss the role of the <microbiome>gut microbiome</microbiome> and gut-brain axis in <DDF>neurodegenerative diseases</DDF> such as <DDF>Parkinson's disease</DDF> and <DDF>Alzheimer's disease</DDF> and related animal models, in <DDF>cancer</DDF> and cancer treatments, and in <DDF>metabolic syndrome</DDF>. We also discuss strategies to improve the <microbiome>gut microbiome</microbiome> and ultimately brain function. Because healthier cognitive phenotypes are observed in <human>individuals</human> with more distinct microbiomes, increased efforts are warranted to develop therapeutic strategies for those at increased risk of developing <DDF>neurological disorders</DDF> and <human>patients</human> diagnosed with those disorders.",
"role": "assistant"
}
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37624502
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nThe association between greenery type and gut microbiome in schizophrenia: did all greenspaces play the equivalent role? In recent years, attention has been focused on the benefit of greenspace on mental health, and it is suggested this link may vary with the type of greenspace. More and more studies have emphasized the influence of the gut microbiome on schizophrenia (SCZ). However, the effects of greenspaces on the gut microbiota in SCZ and the effect of different types of greenspaces on the gut microbiota remain unclear. We aim to examine if there were variations in the effects of various greenspace types on the gut microbiome in SCZ. Besides, we sink to explore important taxonomic compositions associated with different greenspace types. We recruited 243 objects with schizophrenia from Anhui Mental Health Center and collected fecal samples for 16Sr RNA gene sequencing. Three types of greenery coverage were calculated with different circular buffers (800, 1500, and 3000 m) corresponding to individual addresses. The association between greenspace and microbiome composition was analyzed with permutational analysis of variance (PERMANOVA). We conducted the linear regression to capture specific gut microbiome taxa associated with greenery coverage. Tree coverage was consistently associated with microbial composition in both 1500 m (R<sup>2</sup> = 0.007, P = 0.030) and 3000 m (R<sup>2</sup> = 0.007, P = 0.039). In contrast, there was no association with grass cover in any of the buffer zones. In the regression analysis, higher tree coverage was significantly correlated with the relative abundance of several taxa. Among them, tree coverage was positively associated with increased Bifidobacterium longum (β = 1.069, P = 0.004), which was the dominant composition in the gut microbiota. The relationship between greenspace and gut microbiome in SCZ differed by the type of greenspace. Besides, \"tree coverage\" may present a dominant effect on the important taxonomic composition. Our findings might provide instructive evidence for the design of urban greenspace to optimize health and well-being in SCZ as well as the whole people.",
"role": "user"
},
{
"content": "The association between greenery type and <microbiome>gut microbiome</microbiome> in <DDF>schizophrenia</DDF>: did all greenspaces play the equivalent role? In recent years, attention has been focused on the benefit of greenspace on mental health, and it is suggested this link may vary with the type of greenspace. More and more studies have emphasized the influence of the <microbiome>gut microbiome</microbiome> on <DDF>schizophrenia</DDF> (<DDF>SCZ</DDF>). However, the effects of greenspaces on the <microbiome>gut microbiota</microbiome> in <DDF>SCZ</DDF> and the effect of different types of greenspaces on the <microbiome>gut microbiota</microbiome> remain unclear. We aim to examine if there were variations in the effects of various greenspace types on the <microbiome>gut microbiome</microbiome> in <DDF>SCZ</DDF>. Besides, we sink to explore important taxonomic compositions associated with different greenspace types. We recruited 243 objects with <DDF>schizophrenia</DDF> from Anhui Mental Health Center and collected fecal samples for <biomedical technique>16Sr RNA gene sequencing</biomedical technique>. Three types of greenery coverage were calculated with different circular buffers (800, 1500, and 3000 m) corresponding to individual addresses. The association between greenspace and microbiome composition was analyzed with <statistical technique>permutational analysis of variance</statistical technique> (<statistical technique>PERMANOVA</statistical technique>). We conducted the <statistical technique>linear regression</statistical technique> to capture specific <microbiome>gut microbiome</microbiome> taxa associated with greenery coverage. Tree coverage was consistently associated with microbial composition in both 1500 m (R<sup>2</sup> = 0.007, P = 0.030) and 3000 m (R<sup>2</sup> = 0.007, P = 0.039). In contrast, there was no association with grass cover in any of the buffer zones. In the <statistical technique>regression analysis</statistical technique>, higher tree coverage was significantly correlated with the relative abundance of several taxa. Among them, tree coverage was positively associated with increased <bacteria>Bifidobacterium longum</bacteria> (β = 1.069, P = 0.004), which was the dominant composition in the <microbiome>gut microbiota</microbiome>. The relationship between greenspace and <microbiome>gut microbiome</microbiome> in <DDF>SCZ</DDF> differed by the type of greenspace. Besides, \"tree coverage\" may present a dominant effect on the important taxonomic composition. Our findings might provide instructive evidence for the design of urban greenspace to optimize health and well-being in <DDF>SCZ</DDF> as well as the whole people.",
"role": "assistant"
}
] |
37655441
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nThe curious case of <i>Prevotella copri</i>. <i>Prevotella copri</i> is an abundant member of the human gastrointestinal microbiome, whose relative abundance has curiously been associated with positive and negative impacts on diseases, such as Parkinson's disease and rheumatoid arthritis. Yet, the verdict is still out on the definitive role of <i>P. copri</i> in human health, and on the effect of different diets on its relative abundance in the gut microbiome. The puzzling discrepancies among <i>P. copri</i> studies have only recently been attributed to the diversity of its strains, which substantially differ in their encoded metabolic patterns from the commonly used reference strain. However, such strain differences cannot be resolved by common 16S rRNA amplicon profiling methods. Here, we scrutinize <i>P. copri</i>, its versatile metabolic potential, and the hypotheses behind the conflicting observations on its association with diet and human health. We also provide suggestions for designing studies and bioinformatics pipelines to better research <i>P. copri</i>.",
"role": "user"
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{
"content": "The curious case of <i><bacteria>Prevotella copri</bacteria></i>. <i><bacteria>Prevotella copri</bacteria></i> is an abundant member of the <microbiome>human gastrointestinal microbiome</microbiome>, whose relative abundance has curiously been associated with positive and negative impacts on diseases, such as <DDF>Parkinson's disease</DDF> and <DDF>rheumatoid arthritis</DDF>. Yet, the verdict is still out on the definitive role of <i><bacteria>P. copri</bacteria></i> in human health, and on the effect of different diets on its relative abundance in the <microbiome>gut microbiome</microbiome>. The puzzling discrepancies among <i><bacteria>P. copri</bacteria></i> studies have only recently been attributed to the diversity of its strains, which substantially differ in their encoded metabolic patterns from the commonly used reference strain. However, such strain differences cannot be resolved by common <biomedical technique>16S rRNA amplicon profiling methods</biomedical technique>. Here, we scrutinize <i><bacteria>P. copri</bacteria></i>, its versatile metabolic potential, and the hypotheses behind the conflicting observations on its association with diet and human health. We also provide suggestions for designing studies and bioinformatics pipelines to better research <i><bacteria>P. copri</bacteria></i>.",
"role": "assistant"
}
] |
37764088
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nAltered Gut Microbiota Composition Is Associated with Difficulty in Explicit Emotion Regulation in Young Children. Executive function (EF) consists of explicit emotion regulation (EER) and cognitive control (CC). Childhood EER in particular predicts mental and physical health in adulthood. Identifying factors affecting EER development has implications for lifelong physical and mental health. Gut microbiota (GM) has attracted attention as a potential biomarker for risk of physical and mental problems in adulthood. Furthermore, GM is related to brain function/structure, which plays a crucial role in emotional processing. However, little is known about how GM compositions are associated with the development of emotion regulation in early childhood. Therefore, in this study, we examined 257 children aged 3-4 to investigate links between GM and risk to EF. EF was measured using the Mother-Reported Behavior Rating Inventory of Executive Function-Preschool version. GM composition (alpha/beta diversity and genus abundance) was evaluated using 16S rRNA gene sequencing and compared between EF-risk and non-risk groups. Our results show that children with EER-risk (an index of inhibitory self-control) had a higher abundance of the genera <i>Actinomyces</i> and <i>Sutterella</i>. Although we have not established a direct link between GM and CC risk, our findings indicate that GM of preschoolers is closely associated with emotional processing and that EERrisk children have more inflammation-related bacteria.",
"role": "user"
},
{
"content": "<DDF>Altered Gut Microbiota Composition</DDF> Is Associated with <DDF>Difficulty in Explicit Emotion Regulation</DDF> in <human>Young Children</human>. Executive function (EF) consists of explicit emotion regulation (EER) and cognitive control (CC). Childhood EER in particular predicts mental and physical health in adulthood. Identifying factors affecting EER development has implications for lifelong physical and mental health. <microbiome>Gut microbiota</microbiome> (<microbiome>GM</microbiome>) has attracted attention as a potential biomarker for risk of <DDF>physical and mental problems</DDF> in adulthood. Furthermore, <microbiome>GM</microbiome> is related to brain function/structure, which plays a crucial role in emotional processing. However, little is known about how GM compositions are associated with the development of emotion regulation in early childhood. Therefore, in this study, we examined 257 <human>children aged 3-4</human> to investigate links between <microbiome>GM</microbiome> and risk to EF. EF was measured using the Mother-Reported Behavior Rating Inventory of Executive Function-Preschool version. GM composition (alpha/beta diversity and genus abundance) was evaluated using <biomedical technique>16S rRNA gene sequencing</biomedical technique> and compared between <human>EF-risk and non-risk groups</human>. Our results show that <human>children with EER-risk</human> (an index of inhibitory self-control) had a higher abundance of the genera <i><bacteria>Actinomyces</bacteria></i> and <i><bacteria>Sutterella</bacteria></i>. Although we have not established a direct link between <microbiome>GM</microbiome> and CC risk, our findings indicate that <microbiome>GM</microbiome> of <human>preschoolers</human> is closely associated with emotional processing and that <human>EERrisk children</human> have more <bacteria>inflammation-related bacteria</bacteria>.",
"role": "assistant"
}
] |
37764277
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nTherapeutic Effects of Baicalin on Diseases Related to Gut-Brain Axis Dysfunctions. The gut-brain axis is an active area of research. Several representative diseases, including central nervous system disorders (Alzheimer's disease, Parkinson's disease, and depression), metabolic disorders (obesity-related diseases), and intestinal disorders (inflammatory bowel disease and dysbiosis), are associated with the dysfunctional gut-brain axis. Baicalin, a bioactive flavonoid extracted from <i>Scutellaria baicalensis</i>, is reported to exert various pharmacological effects. This narrative review summarizes the molecular mechanisms and potential targets of baicalin in disorders of the gut-brain axis. Baicalin protects the central nervous system through anti-neuroinflammatory and anti-neuronal apoptotic effects, suppresses obesity through anti-inflammatory and antioxidant effects, and alleviates intestinal disorders through regulatory effects on intestinal microorganisms and short-chain fatty acid production. The bioactivities of baicalin are mediated through the gut-brain axis. This review comprehensively summarizes the regulatory role of baicalin in gut-brain axis disorders, laying a foundation for future research, although further confirmatory basic research is required.",
"role": "user"
},
{
"content": "Therapeutic Effects of <drug>Baicalin</drug> on <DDF>Diseases</DDF> Related to <DDF>Gut-Brain Axis Dysfunctions</DDF>. The gut-brain axis is an active area of research. Several representative diseases, including <DDF>central nervous system disorders</DDF> (<DDF>Alzheimer's disease</DDF>, <DDF>Parkinson's disease</DDF>, and <DDF>depression</DDF>), <DDF>metabolic disorders</DDF> (<DDF>obesity-related diseases</DDF>), and <DDF>intestinal disorders</DDF> (<DDF>inflammatory bowel disease</DDF> and <DDF>dysbiosis</DDF>), are associated with the dysfunctional gut-brain axis. <chemical>Baicalin</chemical>, a <chemical>bioactive flavonoid</chemical> extracted from <i><bacteria>Scutellaria baicalensis</bacteria></i>, is reported to exert various pharmacological effects. This narrative review summarizes the molecular mechanisms and potential targets of <chemical>baicalin</chemical> in disorders of the gut-brain axis. <chemical>Baicalin</chemical> protects the central nervous system through anti-neuroinflammatory and anti-neuronal apoptotic effects, suppresses <DDF>obesity</DDF> through anti-inflammatory and antioxidant effects, and alleviates <DDF>intestinal disorders</DDF> through regulatory effects on <bacteria>intestinal microorganisms</bacteria> and short-chain <chemical>fatty acid</chemical> production. The bioactivities of <chemical>baicalin</chemical> are mediated through the gut-brain axis. This review comprehensively summarizes the regulatory role of <chemical>baicalin</chemical> in <DDF>gut-brain axis disorders</DDF>, laying a foundation for future research, although further confirmatory basic research is required.",
"role": "assistant"
}
] |
37834373
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nImpact of Microbiome-Brain Communication on Neuroinflammation and Neurodegeneration. The gut microbiome plays a pivotal role in maintaining human health, with numerous studies demonstrating that alterations in microbial compositions can significantly affect the development and progression of various immune-mediated diseases affecting both the digestive tract and the central nervous system (CNS). This complex interplay between the microbiota, the gut, and the CNS is referred to as the gut-brain axis. The role of the gut microbiota in the pathogenesis of neurodegenerative diseases has gained increasing attention in recent years, and evidence suggests that gut dysbiosis may contribute to disease development and progression. Clinical studies have shown alterations in the composition of the gut microbiota in multiple sclerosis patients, with a decrease in beneficial bacteria and an increase in pro-inflammatory bacteria. Furthermore, changes within the microbial community have been linked to the pathogenesis of Parkinson's disease and Alzheimer's disease. Microbiota-gut-brain communication can impact neurodegenerative diseases through various mechanisms, including the regulation of immune function, the production of microbial metabolites, as well as modulation of host-derived soluble factors. This review describes the current literature on the gut-brain axis and highlights novel communication systems that allow cross-talk between the gut microbiota and the host that might influence the pathogenesis of neuroinflammation and neurodegeneration.",
"role": "user"
},
{
"content": "Impact of Microbiome-Brain Communication on <DDF>Neuroinflammation</DDF> and <DDF>Neurodegeneration</DDF>. The <microbiome>gut microbiome</microbiome> plays a pivotal role in maintaining human health, with numerous studies demonstrating that alterations in microbial compositions can significantly affect the development and progression of various <DDF>immune-mediated diseases</DDF> affecting both the <anatomical location>digestive tract</anatomical location> and the central nervous system (CNS). This complex interplay between the microbiota, the <anatomical location>gut</anatomical location>, and the CNS is referred to as the gut-brain axis. The role of the <microbiome>gut microbiota</microbiome> in the pathogenesis of <DDF>neurodegenerative diseases</DDF> has gained increasing attention in recent years, and evidence suggests that <DDF>gut dysbiosis</DDF> may contribute to disease development and progression. Clinical studies have shown alterations in the composition of the <microbiome>gut microbiota</microbiome> in <human>multiple sclerosis patients</human>, with a decrease in beneficial bacteria and an increase in <bacteria>pro-inflammatory bacteria</bacteria>. Furthermore, changes within the <microbiome>microbial community</microbiome> have been linked to the pathogenesis of <DDF>Parkinson's disease</DDF> and <DDF>Alzheimer's disease</DDF>. Microbiota-gut-brain communication can impact <DDF>neurodegenerative diseases</DDF> through various mechanisms, including the regulation of immune function, the production of <chemical>microbial metabolites</chemical>, as well as modulation of <chemical>host-derived soluble factors</chemical>. This review describes the current literature on the gut-brain axis and highlights novel communication systems that allow cross-talk between the <microbiome>gut microbiota</microbiome> and the host that might influence the pathogenesis of <DDF>neuroinflammation</DDF> and <DDF>neurodegeneration</DDF>.",
"role": "assistant"
}
] |
37900921
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\n4-Ethylphenol-fluxes, metabolism and excretion of a gut microbiome derived neuromodulator implicated in autism. Gut-microbiome-derived metabolites, such as 4-Ethylphenol [4EP], have been shown to modulate neurological health and function. Although the source of such metabolites is becoming better understood, knowledge gaps remain as to the mechanisms by which they enter host circulation, how they are transported in the body, how they are metabolised and excreted, and the way they exert their effects. High blood concentrations of host-modified 4EP, 4-ethylphenol sulfate [4EPS], are associated with an anxiety phenotype in autistic individuals. We have reviewed the existing literature and discuss mechanisms that are proposed to contribute influx from the gut microbiome, metabolism, and excretion of 4EP. We note that increased intestinal permeability is common in autistic individuals, potentially explaining increased flux of 4EP and/or 4EPS across the gut epithelium and the Blood Brain Barrier [BBB]. Similarly, kidney dysfunction, another complication observed in autistic individuals, impacts clearance of 4EP and its derivatives from circulation. Evidence indicates that accumulation of 4EPS in the brain of mice affects connectivity between subregions, particularly those linked to anxiety. However, we found no data on the presence or quantity of 4EP and/or 4EPS in human brains, irrespective of neurological status, likely due to challenges sampling this organ. We argue that the penetrative ability of 4EP is dependent on its form at the BBB and its physicochemical similarity to endogenous metabolites with dedicated active transport mechanisms across the BBB. We conclude that future research should focus on physical (e.g., ingestion of sorbents) or metabolic mechanisms (e.g., conversion to 4EP-glucuronide) that are capable of being used as interventions to reduce the flux of 4EP from the gut into the body, increase the efflux of 4EP and/or 4EPS from the brain, or increase excretion from the kidneys as a means of addressing the neurological impacts of 4EP.",
"role": "user"
},
{
"content": "4-Ethylphenol-fluxes, metabolism and excretion of a <microbiome>gut microbiome</microbiome> derived <chemical>neuromodulator</chemical> implicated in <DDF>autism</DDF>. <chemical>Gut-microbiome-derived metabolites</chemical>, such as <chemical>4-Ethylphenol</chemical> [<chemical>4EP</chemical>], have been shown to modulate neurological health and function. Although the source of such metabolites is becoming better understood, knowledge gaps remain as to the mechanisms by which they enter host circulation, how they are transported in the body, how they are metabolised and excreted, and the way they exert their effects. High blood concentrations of <chemical>host-modified 4EP</chemical>, <chemical>4-ethylphenol sulfate</chemical> [<chemical>4EPS</chemical>], are associated with an <DDF>anxiety phenotype</DDF> in <human>autistic individuals</human>. We have reviewed the existing literature and discuss mechanisms that are proposed to contribute influx from the <microbiome>gut microbiome</microbiome>, metabolism, and excretion of <chemical>4EP</chemical>. We note that <DDF>increased intestinal permeability</DDF> is common in <human>autistic individuals</human>, potentially explaining increased flux of <chemical>4EP</chemical> and/or <chemical>4EPS</chemical> across the <anatomical location>gut epithelium</anatomical location> and the Blood Brain Barrier [BBB]. Similarly, <DDF>kidney dysfunction</DDF>, another complication observed in <human>autistic individuals</human>, impacts clearance of <chemical>4EP</chemical> and its derivatives from circulation. Evidence indicates that accumulation of <chemical>4EPS</chemical> in the <anatomical location>brain</anatomical location> of <animal>mice</animal> affects connectivity between subregions, particularly those linked to <DDF>anxiety</DDF>. However, we found no data on the presence or quantity of <chemical>4EP</chemical> and/or <chemical>4EPS</chemical> in <anatomical location>human brains</anatomical location>, irrespective of neurological status, likely due to challenges sampling this organ. We argue that the penetrative ability of <chemical>4EP</chemical> is dependent on its form at the BBB and its physicochemical similarity to <chemical>endogenous metabolites</chemical> with dedicated active transport mechanisms across the BBB. We conclude that future research should focus on physical (e.g., ingestion of sorbents) or metabolic mechanisms (e.g., conversion to <chemical>4EP-glucuronide</chemical>) that are capable of being used as interventions to reduce the flux of <chemical>4EP</chemical> from the <anatomical location>gut</anatomical location> into the body, increase the efflux of <chemical>4EP</chemical> and/or <chemical>4EPS</chemical> from the <anatomical location>brain</anatomical location>, or increase excretion from the <anatomical location>kidneys</anatomical location> as a means of addressing the neurological impacts of <chemical>4EP</chemical>.",
"role": "assistant"
}
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37995475
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGuardians of Rest? Investigating the gut microbiota in central hypersomnolence disorders. In recent years, there has been an increased interest in elucidating the influence of the gut microbiota on sleep physiology. The gut microbiota affects the central nervous system by modulating neuronal pathways through the neuroendocrine and immune system, the hypothalamus-pituitary-adrenal axis, and various metabolic pathways. The gut microbiota can also influence circadian rhythms. In this study, we observed the gut microbiota composition of patients suffering from narcolepsy type 1, narcolepsy type 2, and idiopathic hypersomnia. We did not observe any changes in the alpha diversity of the gut microbiota among patient groups and healthy controls. We observed changes in beta diversity in accordance with Jaccard dissimilarities between the control group and groups of patients suffering from narcolepsy type 1 and idiopathic hypersomnia. Our results indicate that both these patient groups differ from controls relative to the presence of rare bacterial taxa. However, after adjustment for various confounding factors such as BMI, age, and gender, there were no statistical differences among the groups. This indicates that the divergence in beta diversity in the narcolepsy type 1 and idiopathic hypersomnia groups did not arise due to sleep disturbances. This study implies that using metabolomics and proteomics approaches to study the role of microbiota in sleep disorders might prove beneficial.",
"role": "user"
},
{
"content": "Guardians of Rest? Investigating the <microbiome>gut microbiota</microbiome> in <DDF>central hypersomnolence disorders</DDF>. In recent years, there has been an increased interest in elucidating the influence of the <microbiome>gut microbiota</microbiome> on sleep physiology. The <microbiome>gut microbiota</microbiome> affects the central nervous system by modulating neuronal pathways through the neuroendocrine and immune system, the hypothalamus-pituitary-adrenal axis, and various metabolic pathways. The <microbiome>gut microbiota</microbiome> can also influence circadian rhythms. In this study, we observed the gut microbiota composition of <human>patients</human> suffering from <DDF>narcolepsy type 1</DDF>, <DDF>narcolepsy type 2</DDF>, and <DDF>idiopathic hypersomnia</DDF>. We did not observe any changes in the alpha diversity of the <microbiome>gut microbiota</microbiome> among <human>patient groups</human> and <human>healthy controls</human>. We observed changes in beta diversity in accordance with Jaccard dissimilarities between the <human>control group</human> and groups of <human>patients</human> suffering from <DDF>narcolepsy type 1</DDF> and <DDF>idiopathic hypersomnia</DDF>. Our results indicate that both these <human>patient groups</human> differ from <human>controls</human> relative to the presence of rare bacterial taxa. However, after adjustment for various confounding factors such as BMI, age, and gender, there were no statistical differences among the groups. This indicates that the divergence in beta diversity in the <human>narcolepsy type 1 and idiopathic hypersomnia groups</human> did not arise due to <DDF>sleep disturbances</DDF>. This study implies that using <biomedical technique>metabolomics</biomedical technique> and <biomedical technique>proteomics</biomedical technique> approaches to study the role of microbiota in <DDF>sleep disorders</DDF> might prove beneficial.",
"role": "assistant"
}
] |
38011787
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nCryptotanshinone regulates gut microbiota and PI3K-AKT pathway in rats to alleviate CUMS induced depressive symptoms. Cryptotanshinone (CPT), a bioactive compound derived from the traditional Chinese herb Salvia miltiorrhiza, exhibits promising antidepressant properties. Employing a rat model subjected to Chronic Unpredictable Mild Stress (CUMS), behavioral analyses (open field experiment, elevated cross maze experiment, sugar water preference experiment, forced swimming experiment) and inflammatory factor assessments were conducted to assess the efficacy of CPT in alleviating depressive symptoms and inflammatory responses induced by CUMS. Moreover, 16 S rDNA analysis revealed alterations in the gut microbiota of rats exposed to both CUMS and CPT administration. Notably, CPT administration was found to mitigate harmful bacterial shifts associated with depression. Preliminary exploration of the molecular mechanism underlying CPT's antidepressant effects via transcriptomics analysis and molecular docking indicated that CPT might exert its influence by regulating the PI3K-AKT pathway. This study sheds light on the potential therapeutic role of CPT in managing depressive disorders, offering a comprehensive understanding of its impact on behavior, inflammation, gut microbiota, and molecular pathways.",
"role": "user"
},
{
"content": "<chemical>Cryptotanshinone</chemical> regulates <microbiome>gut microbiota</microbiome> and PI3K-AKT pathway in <animal>rats</animal> to alleviate <DDF>CUMS induced depressive symptoms</DDF>. <chemical>Cryptotanshinone</chemical> (<chemical>CPT</chemical>), a bioactive compound derived from the traditional Chinese herb Salvia miltiorrhiza, exhibits promising antidepressant properties. Employing a rat model subjected to <DDF>Chronic Unpredictable Mild Stress</DDF> (<DDF>CUMS</DDF>), behavioral analyses (open field experiment, elevated cross maze experiment, sugar water preference experiment, forced swimming experiment) and inflammatory factor assessments were conducted to assess the efficacy of <chemical>CPT</chemical> in alleviating <DDF>depressive symptoms</DDF> and <DDF>inflammatory responses</DDF> induced by <DDF>CUMS</DDF>. Moreover, <biomedical technique>16 S rDNA analysis</biomedical technique> revealed alterations in the <microbiome>gut microbiota</microbiome> of <animal>rats</animal> exposed to both <DDF>CUMS</DDF> and <chemical>CPT</chemical> administration. Notably, <chemical>CPT</chemical> administration was found to mitigate harmful bacterial shifts associated with <DDF>depression</DDF>. Preliminary exploration of the molecular mechanism underlying CPT's antidepressant effects via <biomedical technique>transcriptomics analysis</biomedical technique> and <biomedical technique>molecular docking</biomedical technique> indicated that <chemical>CPT</chemical> might exert its influence by regulating the PI3K-AKT pathway. This study sheds light on the potential therapeutic role of <chemical>CPT</chemical> in managing <DDF>depressive disorders</DDF>, offering a comprehensive understanding of its impact on behavior, <DDF>inflammation</DDF>, <microbiome>gut microbiota</microbiome>, and molecular pathways.",
"role": "assistant"
}
] |
38045924
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nMicrobiota-gut-brain axis and ketogenic diet: how close are we to tackling epilepsy? The microbiota-gut-brain axis refers to the intricate bidirectional communication between commensal microorganisms residing in the digestive tract and the central nervous system, along neuroendocrine, metabolic, immune, and inflammatory pathways. This axis has been suggested to play a role in several neurological disorders, such as Parkinson's disease, Alzheimer's disease, multiple sclerosis, and epilepsy, paving the way for microbiome-based intervention strategies for the mitigation and treatment of symptoms. Epilepsy is a multifaceted neurological condition affecting more than 50 million individuals worldwide, 30% of whom do not respond to conventional pharmacological therapies. Among the first-hand microbiota modulation strategies, nutritional interventions represent an easily applicable option in both clinical and home settings. In this narrative review, we summarize the mechanisms underlying the microbiota-gut-brain axis involvement in epilepsy, discuss the impact of antiepileptic drugs on the gut microbiome, and then the impact of a particular dietary pattern, the ketogenic diet, on the microbiota-gut-brain axis in epileptic patients. The investigation of the microbiota response to non-pharmacological therapies is an ever-expanding field with the potential to allow the design of increasingly accessible and successful intervention strategies.",
"role": "user"
},
{
"content": "Microbiota-gut-brain axis and ketogenic diet: how close are we to tackling <DDF>epilepsy</DDF>? The microbiota-gut-brain axis refers to the intricate bidirectional communication between commensal microorganisms residing in the <anatomical location>digestive tract</anatomical location> and the central nervous system, along neuroendocrine, metabolic, immune, and inflammatory pathways. This axis has been suggested to play a role in several <DDF>neurological disorders</DDF>, such as <DDF>Parkinson's disease</DDF>, <DDF>Alzheimer's disease</DDF>, <DDF>multiple sclerosis</DDF>, and <DDF>epilepsy</DDF>, paving the way for microbiome-based intervention strategies for the mitigation and treatment of symptoms. <DDF>Epilepsy</DDF> is a multifaceted neurological condition affecting more than 50 million individuals worldwide, 30% of whom do not respond to conventional pharmacological therapies. Among the first-hand microbiota modulation strategies, nutritional interventions represent an easily applicable option in both clinical and home settings. In this narrative review, we summarize the mechanisms underlying the microbiota-gut-brain axis involvement in <DDF>epilepsy</DDF>, discuss the impact of <drug>antiepileptic drugs</drug> on the <microbiome>gut microbiome</microbiome>, and then the impact of a particular dietary pattern, the ketogenic diet, on the microbiota-gut-brain axis in <human>epileptic patients</human>. The investigation of the microbiota response to non-pharmacological therapies is an ever-expanding field with the potential to allow the design of increasingly accessible and successful intervention strategies.",
"role": "assistant"
}
] |
38123016
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nThe many faces of microbiota-gut-brain axis in autism spectrum disorder. The gut-brain axis is gaining more attention in neurodevelopmental disorders, especially autism spectrum disorder (ASD). Many factors can influence microbiota in early life, including host genetics and perinatal events (infections, mode of birth/delivery, medications, nutritional supply, and environmental stressors). The gut microbiome can influence blood-brain barrier (BBB) permeability, drug bioavailability, and social behaviors. Developing microbiota-based interventions such as probiotics, gastrointestinal (GI) microbiota transplantation, or metabolite supplementation may offer an exciting approach to treating ASD. This review highlights that RNA sequencing, metabolomics, and transcriptomics data are needed to understand how microbial modulators can influence ASD pathophysiology. Due to the substantial clinical heterogeneity of ASD, medical caretakers may be unlikely to develop a broad and effective general gut microbiota modulator. However, dietary modulation followed by administration of microbiota modulators is a promising option for treating ASD-related behavioral and gastrointestinal symptoms. Future work should focus on the accuracy of biomarker tests and developing specific psychobiotic agents tailored towards the gut microbiota seen in ASD patients, which may include developing individualized treatment options.",
"role": "user"
},
{
"content": "The many faces of microbiota-gut-brain axis in <DDF>autism spectrum disorder</DDF>. The gut-brain axis is gaining more attention in <DDF>neurodevelopmental disorders</DDF>, especially <DDF>autism spectrum disorder</DDF> (<DDF>ASD</DDF>). Many factors can influence microbiota in early life, including host genetics and perinatal events (<DDF>infections</DDF>, mode of birth/delivery, medications, nutritional supply, and environmental stressors). The <microbiome>gut microbiome</microbiome> can influence blood-brain barrier (BBB) permeability, drug bioavailability, and social behaviors. Developing microbiota-based interventions such as <dietary supplement>probiotics</dietary supplement>, gastrointestinal (GI) microbiota transplantation, or <dietary supplement>metabolite supplementation</dietary supplement> may offer an exciting approach to treating <DDF>ASD</DDF>. This review highlights that <biomedical technique>RNA sequencing</biomedical technique>, <biomedical technique>metabolomics</biomedical technique>, and <biomedical technique>transcriptomics data</biomedical technique> are needed to understand how microbial modulators can influence ASD pathophysiology. Due to the substantial clinical heterogeneity of <DDF>ASD</DDF>, medical caretakers may be unlikely to develop a broad and effective general gut microbiota modulator. However, dietary modulation followed by administration of <dietary supplement>microbiota modulators</dietary supplement> is a promising option for treating ASD-related behavioral and gastrointestinal symptoms. Future work should focus on the accuracy of <biomedical technique>biomarker tests</biomedical technique> and developing specific <dietary supplement>psychobiotic agents</dietary supplement> tailored towards the <microbiome>gut microbiota</microbiome> seen in <human>ASD patients</human>, which may include developing individualized treatment options.",
"role": "assistant"
}
] |
38229613
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nDysbiosis of the Beneficial Gut Bacteria in Patients with Parkinson's Disease from India. Recent advancement in understanding neurological disorders has revealed the involvement of dysbiosis of the gut microbiota in the pathophysiology of Parkinson's disease (PD). We sequenced microbial DNA using fecal samples collected from PD cases and healthy controls (HCs) to evaluate the role of gut microbiota. Full-length bacterial 16S rRNA gene sequencing of fecal samples was performed using amplified polymerase chain reaction (PCR) products on the GridION Nanopore sequencer. Sequenced data were analyzed using web-based tools BugSeq and MicrobiomeAnalyst. We found that certain bacterial families like Clostridia UCG 014, Cristensenellaceae, and Oscillospiraceae are higher in abundance, and Lachinospiracea, Coriobacteriaceae and genera associated with short-chain fatty acid production, <i>Faecalibacterium</i>, <i>Fusicatenibacter</i>, <i>Roseburia</i> and <i>Blautia</i>, are lower in abundance among PD cases when compared with the HC. Genus <i>Akkermansia</i>, <i>Dialister</i>, <i>Bacteroides</i>, and <i>Lachnospiraceae NK4A136</i> group positively correlated with constipation in PD. Observations from this study support the other global research on the PD gut microbiome background and provide fresh insight into the gut microbial composition of PD patients from a south Indian population. We report a higher abundance of Clostridia UCG 014 group, previously not linked to PD.",
"role": "user"
},
{
"content": "<DDF>Dysbiosis</DDF> of the <bacteria>Beneficial Gut Bacteria</bacteria> in <human>Patients</human> with <DDF>Parkinson's Disease</DDF> from India. Recent advancement in understanding <DDF>neurological disorders</DDF> has revealed the involvement of <DDF>dysbiosis</DDF> of the <microbiome>gut microbiota</microbiome> in the pathophysiology of <DDF>Parkinson's disease</DDF> (<DDF>PD</DDF>). We sequenced microbial DNA using fecal samples collected from <human>PD cases</human> and <human>healthy controls</human> (<human>HCs</human>) to evaluate the role of <microbiome>gut microbiota</microbiome>. <biomedical technique>Full-length bacterial 16S rRNA gene sequencing</biomedical technique> of fecal samples was performed using amplified polymerase chain reaction (PCR) products on the GridION Nanopore sequencer. Sequenced data were analyzed using web-based tools BugSeq and MicrobiomeAnalyst. We found that certain bacterial families like <bacteria>Clostridia UCG 014</bacteria>, <bacteria>Cristensenellaceae</bacteria>, and <bacteria>Oscillospiraceae</bacteria> are higher in abundance, and <bacteria>Lachinospiracea</bacteria>, <bacteria>Coriobacteriaceae</bacteria> and genera associated with short-chain fatty acid production, <i><bacteria>Faecalibacterium</bacteria></i>, <i><bacteria>Fusicatenibacter</bacteria></i>, <i><bacteria>Roseburia</bacteria></i> and <i><bacteria>Blautia</bacteria></i>, are lower in abundance among <human>PD cases</human> when compared with the <human>HC</human>. Genus <i><bacteria>Akkermansia</bacteria></i>, <i><bacteria>Dialister</bacteria></i>, <i><bacteria>Bacteroides</bacteria></i>, and <i><bacteria>Lachnospiraceae NK4A136</bacteria></i> group positively correlated with <DDF>constipation</DDF> in <DDF>PD</DDF>. Observations from this study support the other global research on the <microbiome>PD gut microbiome</microbiome> background and provide fresh insight into the gut microbial composition of <human>PD patients</human> from a south Indian population. We report a higher abundance of <bacteria>Clostridia UCG 014</bacteria> group, previously not linked to <DDF>PD</DDF>.",
"role": "assistant"
}
] |
38247868
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nPsychiatric Comorbidities of Inflammatory Bowel Disease: It Is a Matter of Microglia's Gut Feeling. Inflammatory bowel disease (IBD), a common term for Crohn's disease and ulcerative colitis, is a chronic, relapse-remitting condition of the gastrointestinal tract that is increasing worldwide. Psychiatric comorbidities, including depression and anxiety, are more prevalent in IBD patients than in healthy individuals. Evidence suggests that varying levels of neuroinflammation might underlie these states in IBD patients. Within this context, microglia are the crucial non-neural cells in the brain responsible for innate immune responses following inflammatory insults. Alterations in microglia's functions, such as secretory profile, phagocytic activity, and synaptic pruning, might play significant roles in mediating psychiatric manifestations of IBD. In this review, we discuss the role played by microglia in IBD-associated comorbidities.",
"role": "user"
},
{
"content": "<DDF>Psychiatric Comorbidities</DDF> of <DDF>Inflammatory Bowel Disease</DDF>: It Is a Matter of Microglia's Gut Feeling. <DDF>Inflammatory bowel disease</DDF> (<DDF>IBD</DDF>), a common term for <DDF>Crohn's disease</DDF> and <DDF>ulcerative colitis</DDF>, is a <DDF>chronic, relapse-remitting condition</DDF> of the <anatomical location>gastrointestinal tract</anatomical location> that is increasing worldwide. <DDF>Psychiatric comorbidities</DDF>, including <DDF>depression</DDF> and <DDF>anxiety</DDF>, are more prevalent in <human>IBD patients</human> than in <human>healthy individuals</human>. Evidence suggests that varying levels of <DDF>neuroinflammation</DDF> might underlie these states in <human>IBD patients</human>. Within this context, microglia are the crucial non-neural cells in the <anatomical location>brain</anatomical location> responsible for innate immune responses following <DDF>inflammatory insults</DDF>. Alterations in microglia's functions, such as secretory profile, phagocytic activity, and synaptic pruning, might play significant roles in mediating <DDF>psychiatric manifestations of IBD</DDF>. In this review, we discuss the role played by microglia in <DDF>IBD-associated comorbidities</DDF>.",
"role": "assistant"
}
] |
38260914
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nRosacea, microbiome and probiotics: the gut-skin axis. Rosacea is an inflammatory skin disease involving diverse symptoms with a variable clinical progress which can severely impact the patient's quality of life as well as their mental health. The pathophysiological model of rosacea involves an unbalanced immune system predisposed to excessive inflammation, in addition to vascular and nervous alterations, being certain cutaneous microorganisms' triggers of the symptoms onset. The gut-skin axis explains a bidirectional interaction between skin and gut microbiota in some inflammatory skin diseases such as atopic dermatitis, psoriasis, or rosacea. The introduction and consolidation of the next-generation sequencing in recent years has provided unprecedented information about the microbiome. However, the characterization of the gut and skin microbiota and the impact of the gut-skin axis in patients with rosacea has been little explored, in contrast to other inflammatory skin diseases such as atopic dermatitis or psoriasis. Furthermore, the clinical evolution of patients with rosacea is not always adequate and it is common for them to present a sustained symptomatology with frequent flare-ups. In this context, probiotic supplementation could improve the clinical evolution of these patients as happens in other pathologies. Through this review we aim to establish and compile the basics and directions of current knowledge to understand the mechanisms by which the microbiome influences the pathogenesis of rosacea, and how modulation of the skin and gut microbiota could benefit these patients.",
"role": "user"
},
{
"content": "<DDF>Rosacea</DDF>, microbiome and <dietary supplement>probiotics</dietary supplement>: the gut-skin axis. <DDF>Rosacea</DDF> is an <DDF>inflammatory skin disease</DDF> involving diverse symptoms with a variable clinical progress which can severely impact the patient's quality of life as well as their mental health. The pathophysiological model of <DDF>rosacea</DDF> involves an unbalanced immune system predisposed to excessive <DDF>inflammation</DDF>, in addition to <DDF>vascular and nervous alterations</DDF>, being certain cutaneous microorganisms' triggers of the symptoms onset. The gut-skin axis explains a bidirectional interaction between <microbiome>skin and gut microbiota</microbiome> in some <DDF>inflammatory skin diseases</DDF> such as <DDF>atopic dermatitis</DDF>, <DDF>psoriasis</DDF>, or <DDF>rosacea</DDF>. The introduction and consolidation of the <biomedical technique>next-generation sequencing</biomedical technique> in recent years has provided unprecedented information about the microbiome. However, the characterization of the <microbiome>gut and skin microbiota</microbiome> and the impact of the gut-skin axis in <human>patients</human> with <DDF>rosacea</DDF> has been little explored, in contrast to other <DDF>inflammatory skin diseases</DDF> such as <DDF>atopic dermatitis</DDF> or <DDF>psoriasis</DDF>. Furthermore, the clinical evolution of <human>patients</human> with <DDF>rosacea</DDF> is not always adequate and it is common for them to present a sustained <DDF>symptomatology</DDF> with frequent <DDF>flare-ups</DDF>. In this context, <dietary supplement>probiotic supplementation</dietary supplement> could improve the clinical evolution of these <human>patients</human> as happens in other pathologies. Through this review we aim to establish and compile the basics and directions of current knowledge to understand the mechanisms by which the microbiome influences the pathogenesis of <DDF>rosacea</DDF>, and how modulation of the <microbiome>skin and gut microbiota</microbiome> could benefit these <human>patients</human>.",
"role": "assistant"
}
] |
38278499
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nAlcohol use-associated alterations in the circulating metabolite profile in the general population and in individuals with major depressive disorder. Our aim was to evaluate whether alcohol use is associated with changes in the circulating metabolite profile similar to those present in persons with depression. If so, these findings could partially explain the link between alcohol use and depression. We applied a targeted liquid chromatography mass spectrometry method to evaluate correlates between concentrations of 86 circulating metabolites and self-reported alcohol use in a cohort of the non-depressed general population (GP) (n = 247) and a cohort of individuals with major depressive disorder (MDD) (n = 99). Alcohol use was associated with alterations in circulating concentrations of metabolites in both cohorts. Our main finding was that self-reported alcohol use was negatively correlated with serum concentrations of hippuric acid in the GP cohort. In the GP cohort, consumption of six or more doses per week was associated with low hippuric acid concentrations, similar to those observed in the MDD cohort, but in these individuals it was regardless of their level of alcohol use. Reduced serum concentrations of hippuric acid suggest that already-moderate alcohol use is associated with depression-like changes in the serum levels of metabolites associated with gut microbiota and liver function; this may be one possible molecular level link between alcohol use and depression.",
"role": "user"
},
{
"content": "<DDF>Alcohol use-associated alterations</DDF> in the circulating metabolite profile in the <human>general population</human> and in <human>individuals</human> with <DDF>major depressive disorder</DDF>. Our aim was to evaluate whether alcohol use is associated with changes in the circulating metabolite profile similar to those present in <human>persons</human> with <DDF>depression</DDF>. If so, these findings could partially explain the link between alcohol use and <DDF>depression</DDF>. We applied a <biomedical technique>targeted liquid chromatography mass spectrometry method</biomedical technique> to evaluate correlates between concentrations of 86 circulating metabolites and self-reported alcohol use in a cohort of the <human>non-depressed general population</human> (<human>GP</human>) (n = 247) and a cohort of <human>individuals</human> with <DDF>major depressive disorder</DDF> (<DDF>MDD</DDF>) (n = 99). Alcohol use was associated with alterations in circulating concentrations of metabolites in both cohorts. Our main finding was that self-reported alcohol use was negatively correlated with serum concentrations of <chemical>hippuric acid</chemical> in the <human>GP cohort</human>. In the <human>GP cohort</human>, consumption of six or more doses per week was associated with low hippuric acid concentrations, similar to those observed in the <human>MDD cohort</human>, but in these <human>individuals</human> it was regardless of their level of alcohol use. Reduced serum concentrations of <chemical>hippuric acid</chemical> suggest that already-moderate alcohol use is associated with depression-like changes in the serum levels of metabolites associated with gut microbiota and liver function; this may be one possible molecular level link between alcohol use and <DDF>depression</DDF>.",
"role": "assistant"
}
] |
38283894
|
[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nA comparison between children and adolescents with autism spectrum disorders and healthy controls in biomedical factors, trace elements, and microbiota biomarkers: a meta-analysis. Autism spectrum disorder (ASD) is a multifaceted developmental condition that commonly appears during early childhood. The etiology of ASD remains multifactorial and not yet fully understood. The identification of biomarkers may provide insights into the underlying mechanisms and pathophysiology of the disorder. The present study aimed to explore the causes of ASD by investigating the key biomedical markers, trace elements, and microbiota factors between children with autism spectrum disorder (ASD) and control subjects. Medline, PubMed, ProQuest, EMBASE, Cochrane Library, PsycINFO, Web of Science, and EMBSCO databases have been searched for publications from 2012 to 2023 with no language restrictions using the population, intervention, control, and outcome (PICO) approach. Keywords including \"autism spectrum disorder,\" \"oxytocin,\" \"GABA,\" \"Serotonin,\" \"CRP,\" \"IL-6,\" \"Fe,\" \"Zn,\" \"Cu,\" and \"gut microbiota\" were used for the search. The Joanna Briggs Institute (JBI) critical appraisal checklist was used to assess the article quality, and a random model was used to assess the mean difference and standardized difference between ASD and the control group in all biomedical markers, trace elements, and microbiota factors. From 76,217 records, 43 studies met the inclusion and exclusion criteria and were included in this meta-analysis. The pooled analyses showed that children with ASD had significantly lower levels of oxytocin (mean differences, MD = -45.691, 95% confidence interval, CI: -61.667, -29.717), iron (MD = -3.203, 95% CI: -4.891, -1.514), and zinc (MD = -6.707, 95% CI: -12.691, -0.722), lower relative abundance of <i>Bifidobacterium</i> (MD = -1.321, 95% CI: -2.403, -0.238) and <i>Parabacteroides</i> (MD = -0.081, 95% CI: -0.148, -0.013), higher levels of c-reactive protein, CRP (MD = 0.401, 95% CI: 0.036, 0.772), and GABA (MD = 0.115, 95% CI: 0.045, 0.186), and higher relative abundance of <i>Bacteroides</i> (MD = 1.386, 95% CI: 0.717, 2.055) and <i>Clostridium</i> (MD = 0.281, 95% CI: 0.035, 0.526) when compared with controls. The results of the overall analyses were stable after performing the sensitivity analyses. Additionally, no substantial publication bias was observed among the studies. Children with ASD have significantly higher levels of CRP and GABA, lower levels of oxytocin, iron, and zinc, lower relative abundance of <i>Bifidobacterium</i> and <i>Parabacteroides</i>, and higher relative abundance of <i>Faecalibacterium</i>, <i>Bacteroides,</i> and <i>Clostridium</i> when compared with controls. These results suggest that these indicators may be a potential biomarker panel for the diagnosis or determining therapeutic targets of ASD. Furthermore, large, sample-based, and randomized controlled trials are needed to confirm these results.",
"role": "user"
},
{
"content": "A comparison between <human>children</human> and <human>adolescents</human> with <DDF>autism spectrum disorders</DDF> and <human>healthy controls</human> in biomedical factors, <chemical>trace elements</chemical>, and microbiota biomarkers: a <statistical technique>meta-analysis</statistical technique>. <DDF>Autism spectrum disorder</DDF> (<DDF>ASD</DDF>) is a multifaceted developmental condition that commonly appears during early childhood. The etiology of <DDF>ASD</DDF> remains multifactorial and not yet fully understood. The identification of biomarkers may provide insights into the underlying mechanisms and pathophysiology of the disorder. The present study aimed to explore the causes of <DDF>ASD</DDF> by investigating the key biomedical markers, <chemical>trace elements</chemical>, and microbiota factors between <human>children</human> with <DDF>autism spectrum disorder</DDF> (<DDF>ASD</DDF>) and <human>control subjects</human>. Medline, PubMed, ProQuest, EMBASE, Cochrane Library, PsycINFO, Web of Science, and EMBSCO databases have been searched for publications from 2012 to 2023 with no language restrictions using the <statistical technique>population, intervention, control, and outcome (PICO) approach</statistical technique>. Keywords including \"<DDF>autism spectrum disorder</DDF>,\" \"<chemical>oxytocin</chemical>,\" \"<chemical>GABA</chemical>,\" \"<chemical>Serotonin</chemical>,\" \"<chemical>CRP</chemical>,\" \"<chemical>IL-6</chemical>,\" \"<chemical>Fe</chemical>,\" \"<chemical>Zn</chemical>,\" \"<chemical>Cu</chemical>,\" and \"<microbiome>gut microbiota</microbiome>\" were used for the search. The <statistical technique>Joanna Briggs Institute (JBI) critical appraisal checklist</statistical technique> was used to assess the article quality, and a <statistical technique>random model</statistical technique> was used to assess the mean difference and standardized difference between <DDF>ASD</DDF> and the <human>control group</human> in all biomedical markers, <chemical>trace elements</chemical>, and microbiota factors. From 76,217 records, 43 studies met the inclusion and exclusion criteria and were included in this <statistical technique>meta-analysis</statistical technique>. The pooled analyses showed that <human>children</human> with <DDF>ASD</DDF> had significantly lower levels of <chemical>oxytocin</chemical> (mean differences, MD = -45.691, 95% confidence interval, CI: -61.667, -29.717), <chemical>iron</chemical> (MD = -3.203, 95% CI: -4.891, -1.514), and <chemical>zinc</chemical> (MD = -6.707, 95% CI: -12.691, -0.722), lower relative abundance of <i><bacteria>Bifidobacterium</bacteria></i> (MD = -1.321, 95% CI: -2.403, -0.238) and <i><bacteria>Parabacteroides</bacteria></i> (MD = -0.081, 95% CI: -0.148, -0.013), higher levels of <chemical>c-reactive protein</chemical>, <chemical>CRP</chemical> (MD = 0.401, 95% CI: 0.036, 0.772), and <chemical>GABA</chemical> (MD = 0.115, 95% CI: 0.045, 0.186), and higher relative abundance of <i><bacteria>Bacteroides</bacteria></i> (MD = 1.386, 95% CI: 0.717, 2.055) and <i><bacteria>Clostridium</bacteria></i> (MD = 0.281, 95% CI: 0.035, 0.526) when compared with controls. The results of the overall analyses were stable after performing the <statistical technique>sensitivity analyses</statistical technique>. Additionally, no substantial publication bias was observed among the studies. <human>Children</human> with <DDF>ASD</DDF> have significantly higher levels of <chemical>CRP</chemical> and <chemical>GABA</chemical>, lower levels of <chemical>oxytocin</chemical>, <chemical>iron</chemical>, and <chemical>zinc</chemical>, lower relative abundance of <i><bacteria>Bifidobacterium</bacteria></i> and <i><bacteria>Parabacteroides</bacteria></i>, and higher relative abundance of <i><bacteria>Faecalibacterium</bacteria></i>, <i><bacteria>Bacteroides</bacteria>,</i> and <i><bacteria>Clostridium</bacteria></i> when compared with <human>controls</human>. These results suggest that these indicators may be a potential biomarker panel for the diagnosis or determining therapeutic targets of <DDF>ASD</DDF>. Furthermore, <statistical technique>large, sample-based, and randomized controlled trials</statistical technique> are needed to confirm these results.",
"role": "assistant"
}
] |
38292207
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[
{
"content": "You are an expert biomedical NER annotator.\nIdentify every mention of these entity types:\n chemical, microbiome, DDF, gene, animal, dietary supplement,\n human, statistical technique, anatomical location, bacteria,\n biomedical technique, food, drug\n\nFocus on tagging each entire noun or noun phrase that denotes one coherent biological entity.\nDo not split, nest, or overlap tags. Preserve all punctuation and spacing; only insert tags.\n\nTEXT:\nGut-Brain Axis Impact on Canine Anxiety Disorders: New Challenges for Behavioral Veterinary Medicine. Anxiety disorders in dogs are ever-growing and represent an important concern in the veterinary behavior field. These disorders are often disregarded in veterinary clinical practice, negatively impacting the animal's and owner's quality of life. Moreover, these anxiety disorders can potentially result in the abandonment or euthanasia of dogs. Growing evidence shows that the gut microbiota is a central player in the gut-brain axis. A variety of microorganisms inhabit the intestines of dogs, which are essential in maintaining intestinal homeostasis. These microbes can impact mental health through several mechanisms, including metabolic, neural, endocrine, and immune-mediated pathways. The disruption of a balanced composition of resident commensal communities, or dysbiosis, is implicated in several pathological conditions, including mental disorders such as anxiety. Studies carried out in rodent models and humans demonstrate that the intestinal microbiota can influence mental health through these mechanisms, including anxiety disorders. Furthermore, novel therapeutic strategies using prebiotics and probiotics have been shown to ameliorate anxiety-related symptoms. However, regarding the canine veterinary behavior field, there is still a lack of insightful research on this topic. In this review, we explore the few but relevant studies performed on canine anxiety disorders. We agree that innovative bacterial therapeutical approaches for canine anxiety disorders will become a promising field of investigation and certainly pave the way for new approaches to these behavioral conditions.",
"role": "user"
},
{
"content": "Gut-Brain Axis Impact on <DDF>Canine Anxiety Disorders</DDF>: New Challenges for Behavioral Veterinary Medicine. <DDF>Anxiety disorders</DDF> in <animal>dogs</animal> are ever-growing and represent an important concern in the veterinary behavior field. These disorders are often disregarded in veterinary clinical practice, negatively impacting the animal's and owner's quality of life. Moreover, these <DDF>anxiety disorders</DDF> can potentially result in the abandonment or euthanasia of <animal>dogs</animal>. Growing evidence shows that the <microbiome>gut microbiota</microbiome> is a central player in the gut-brain axis. A variety of microorganisms inhabit the <anatomical location>intestines</anatomical location> of <animal>dogs</animal>, which are essential in maintaining intestinal homeostasis. These microbes can impact mental health through several mechanisms, including metabolic, neural, endocrine, and immune-mediated pathways. The disruption of a balanced composition of resident commensal communities, or <DDF>dysbiosis</DDF>, is implicated in several pathological conditions, including <DDF>mental disorders</DDF> such as <DDF>anxiety</DDF>. Studies carried out in rodent models and <human>humans</human> demonstrate that the <microbiome>intestinal microbiota</microbiome> can influence mental health through these mechanisms, including <DDF>anxiety disorders</DDF>. Furthermore, novel therapeutic strategies using <dietary supplement>prebiotics</dietary supplement> and <dietary supplement>probiotics</dietary supplement> have been shown to ameliorate anxiety-related symptoms. However, regarding the canine veterinary behavior field, there is still a lack of insightful research on this topic. In this review, we explore the few but relevant studies performed on <DDF>canine anxiety disorders</DDF>. We agree that innovative bacterial therapeutical approaches for <DDF>canine anxiety disorders</DDF> will become a promising field of investigation and certainly pave the way for new approaches to these behavioral conditions.",
"role": "assistant"
}
] |
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