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## Meet the editor

Dr. Ahmed Lasfar is a faculty member at Rutgers University and a full member of the Rutgers Cancer Institute of New Jersey, USA. He is an editor and board member of several international journals and books. Dr. Lasfar is a scientific adviser and consultant to the pharmaceutical industry and a member of several medical and scientific societies. He graduated in Medical and Applied Science (BS/MD) and obtained a Ph.D. in Immunology from

Paris Diderot University, France. Dr. Lasfar completed his postdoctoral training in cancer immunology at Robert Wood Johnson Medical School, New Jersey, USA.

### Contents

Preface

The tumor microenvironment (TME) is a crucial aspect of all cancer types. It is well established now that TME plays an important role in both the control and the development of solid tumors. The histology of TME consists of a variety of normal resident and recruited cells, which are involved in concise and dynamic interactions with cancer cells. These interactions, which occur via released factors or cell-to-cell contact, are fundamental in tumor-induced suppression and metastatic dissemination of cancer cells, ultimately leading to morbidity and/or mortality for most cancer patients. Considerable progress has been made in understanding the mechanisms by which the TME contributes to the inhibition or promotion of cancer, enabling the emergence of a range of novel targeted therapies. In addition to stroma-targeted strategies, checkpoint inhibitor-based immunotherapy has emerged as a new treatment of choice for many advanced cancers. However, many cancer patients remain resistant to current therapies, necessitating the development of more innovative therapeutic strategies based on the identification of new targets and combining drugs that could counteract resistance. In this book, *Tumor Microenvironment – New Insights*, the authors highlight this aspect with chapters that describe and discuss innovative and impactful studies.

Prominent efforts and collaborations with leading experts in cancer were crucial in achieving this highly valuable book. We thank all the authors for their tremendous expertise and their exceptional quality in pointing out the crucial role of TME in cancer. Understanding and targeting TME constitutes a new hope for cancer patients,

**Ahmed Lasfar**

NJ, USA

Rutgers University,

Department of Toxicology and Pharmacology,

particularly those with advanced diseases.


**2.3.1 Analysis or decomposition**

180 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology

corresponds to the discrete steps of the scale, while the second, denoted by *n* , corresponds to the discrete steps of translation (time displacement). The scale *a* becomes 0

> 2 , 00 0 () ( ) *m*

2 0 0 0 ( , ) () ( )

0 0

*m n*

*m*

*R W mn a f t a t nb dt*

The parameter *m* which is called level, determines the wavelet frequency, while the

( ) ( ,) ( )

where *k* is a constant that depends on the redundancy of the combination of the lattice with

Along with the time-scale plane discretization, the independent variable (time) can also be discretized. The sequence of discrete points of the discretized signal can be represented by a discrete time wavelet series DTWS. The discrete time wavelet series is defined in relation to a discrete mother wavelet, *h k*( ). The discrete wavelet time series maps a discrete finite energy sequence to a discrete grid of coefficients. The discrete time wavelet series is given

Multiresolution Analysis - MRA, aims to develop a signal *f t*( ) representation in terms of an orthogonal basis which is composed by the scale and wavelets functions. An efficient algorithm for this representation was developed in 1988 by Mallat (Mallat, 1989) considering a scale factor 0*a* 2 and a translation factor 0 *b* 1 . This means that at each decomposition

),( )()( 0 0

*f*

2 0 *nbkahkfanmW m m*

powers of 2 can be easily implemented by decimation (sub-sampling) and over-sampling of a discrete signal by a factor of 2. Sub-sampling by a factor of 2, involves taking a signal sample from every two available ones, resulting in a signal with half the number of samples

scales are a power of 2 and translations are proportional to powers of 2. Scaling by

*f t k W m n a a t nb*

*f*

2

*m*

0 0 0

*m*

(3)

(4)

 *t a a t nb*

*m*

*m*

translation, respectively (Young, 1995). Then the wavelet can be represented by:

*m n*

*f*

where, *mn Z* , , and Z is the set of integer numbers.

The inverse discrete wavelet transform is given by:

*m b nb a* , where 0*a* and 0*b* are the discrete steps of the scale and

(1)

(2)

translation becomes 0 0

The discrete wavelet transform is given by:

parameter *n* indicates its position.

the used mother wavelet (Young, 1995).

by (Young, 1995).

level *m* ,

**2.3 Multiresolution analysis**

*m a a* and

The structure of the multiresolution analysis is shown in Figure 2. The original signal passes through two filters, a low pass filter *g k*( ) , the function scale, and a high pass filter *h k*( ), the mother wavelet. The impulse response of *h k*( ) is related to the impulse response of *g k*( ) by (Mallat, 1989):

$$h(k) = (-1)^{1-k} \, \lg(1-k) \tag{5}$$

Filter *h k*( ) is the mirror of filter *g k*( ) and they are called quadrature mirror filters.

In the structure presented in Figure 2, the input signal is convolved with the impulse response of *h k*( ), and *g k*( ) , obtaining two output signals. The low pass filter output represents the low frequency content of the input signal or an approximation of it. The high pass filter output represents the high frequency content of the input signal or a detail of it. It should be noted in Figure 2 that the output provided by the filters has together twice the number of samples of the original signal.

This drawback is overcome by the process of decimation performed on each signal, thereby obtaining the signal *cD* , the wavelet coefficients that are the new signal representation in the wavelet domain, and the signal *cA* , the approximation coefficients which are used to feed the next stage of the decomposition process in an iterative manner resulting in a multi-level decomposition.

Fig. 2. Structure of the multiresolution analysis

The decomposition process in Figure 2 can be iterated with successive approximations being decomposed, then the signal being divided into several resolution levels. This scheme is called "wavelet decomposition tree" or "pyramidal structure" (Young, 1995 and Misit et al, 2000). Figure 3 shows the schematic representation of a signal being decomposed at multiple levels.

Application of Wavelet Transform and Artificial Neural Network to

**3. Probabilistic neural network**

as simple as desired (Specht, 1990).

**3.1 The Bayes strategy for pattern classification**

categories in which the state of known nature

*x* . Then the Bayes decision rule is given by:

*Ah* is the a priori probability of category

and ( ) *B d x*

whether

where:

 *A* or

priori probability that

decision ( ) *A d x*

Extract Power Quality Information from Voltage Oscillographic Signals in Electric Power Systems 183

The structure of a Probabilistic Neural Network (PNN) is similar to a feed forward network. The main difference is that the activation function is no longer the sigmoid; it is replaced by a class of functions which includes, in particular, the exponential function. The main advantage of PNN is that it requires only one step for training and that the decision surfaces are close to the contours of the Bayes optimal decision when the number of training samples increases. Furthermore, the shape of the decision surface can be as complex as necessary, or

The main drawback of PNN is that all samples used for the training process must be stored and used in the classification of new patterns. However, considering the use of high-density memories, problems with storage of training samples should not occur. In addition, the PNN processing speed in the classification of new patterns is quite satisfactory, and even several times faster than using back propagation algorithms as reported by (Maloney et al, 1989).

One of the traditionally accepted strategies or decision rules used to patterns classification is that they minimize the "expected risk." Such strategies are called Bayes strategies, and can

To illustrate the Bayes decision rule formalism, it is considered the situation of two

( ) () () ( ) () () *A AA A BB B B AA A BB B*

*dx if h l f x hl f x dx if h l f x hl f x*

, can be

 *A* or

*B* . Then, the boundary between the regions in which the Bayes

(7)

*B* based on a measurements set represented by a *n* dimension vector

*B* . It is desired to decide

*A* and

when

*A* patterns occurrence, and 1 *B A h h* is the a

() () *A B f x Kf x* (8)

*h l* (9)

 *B* ,

*B*

when

be applied to problems containing any number of categories (Specht, 1988).

where ( ) *Af x* and ( ) *Bf x* are the probability density functions for categories

*A* ; *Bl* is the uncertainty function associated with the decision ( ) *A d x*

is given by:

respectively, *Al* is the uncertainty function associated with the decision ( ) *B d x*

*B B A A h l K*

It should be noted that, in general, the decision surfaces of two categories defined by Eq. (8) can be arbitrarily complex, since there are no restrictions on the densities except for those conditions to which all probability density functions must satisfy, namely that they must be always non-negative, and integrable and their integrals over all space be equal to unity.

Fig. 3. Schematic representation of a signal being decomposed at multiple levels.

Since the multiresolution analysis process is iterative, it can theoretically be continued indefinitely. In fact, the decomposition can proceed only up to 1 (one) detail, consisting of a single sample. The maximum number of decomposition levels for a signal having *N* samples is given by 2 log *N* .

#### **2.3.2 Synthesis or reconstruction**

The synthesis process or reconstruction is to obtain the original signal from the wavelet coefficients generated by the analysis or decomposition process. While the analysis process involves filtering and sub-sampling, the synthesis process performs a reverse sequence, over-sampling and filtering. The filters used in the synthesis process are called reconstruction filters, being *g k* ( ) the low pass filter, and *h k* ( ) the high pass filter. Figure 4 shows the reconstruction scheme from a single decomposition stage.

Fig. 4. Reconstruction scheme from a single decomposition stage.

It is observed from Figure 4 that to retrieve the original signal, it is necessary to reconstruct details and approximations. Details could be obtained with over-sampling of the *cD* coefficients, and a subsequent filtering with *h k* ( ). Approximations are obtained with oversampling of the coefficients *cA* , and a subsequent filtering with *g k* ( ) .The original signal is then obtained by:

$$S = A + D \tag{6}$$

The scheme presented in Figure 4 can be extended to a multi-level decomposition.


Contents

### **Preface XI**

Chapter 8 **Passive Immunotherapy in Alzheimer's Disease 129** Philip J. Dolan and Wagner Zago

Preface

treat it effectively.

publication.

social and economic problem for many countries.

gression of the disease and delay its occurrence.

The progress of medicine and technology in the second half of the twentieth century has led to an increase in life expectancy. This phenomenon was accompanied by a higher incidence of diseases typical for old age, including Alzheimer's disease. It is known that the incidence of Alzheimer's disease is largely dependent on the patient's age. Alzheimer's disease is cur‐ rently considered an incurable disease with an incomplete etiology and comprises a serious

Nowadays, Alzheimer's disease is considered to be the most common dementia and leads to severe impairment of the patient, and even the final stage of the disease requires constant care of a mentally retarded older person. This book presents contemporary insights into the pathogenesis of Alzheimer's disease and currently used therapies that lead to slow the pro‐

This publication sums up the knowledge of the genetic, biochemical, and immunological fac‐ tors influenced in this dementive disease. It summarizes the pathophysiology observed both in Alzheimer's disease patients and in experimental studies. The book also contains the latest views on the molecular mechanism of dysfunction in this disease and life-long diagnosis. We hope that this book may help in understanding the complex mechanisms of Alzheimer's disease pathogenesis and may be an inspiration to find factors to prevent this disease and to

This book was created, thanks to the authors who wanted to share their scientific achieve‐

The editors would like to acknowledge the authors from various parts of the world and all other people who helped with the production of this book for their participation in this

**Professor Jolanta Dorszewska, MDs, PhD**

Poznan University of Medical Sciences

**Professor Wojciech Kozubski, MD, PhD**

Poznan University of Medical Sciences

Laboratory of Neurobiology Department of Neurology

Department of Neurology

Poland

Poland

ments in the field of basic and clinical research in dementive diseases.


**3.2. Active learning strategies**

In the teaching-learning process, instructors in higher institutions are required to use different active learning techniques or strategies to empower students in their learning. The selection of the techniques depends on the nature and content of the subject they are teaching. The active learning strategies comprise different activities that share the common elements of involving learners in doing things and thinking about the things they are doing [7]. The use of different active learning strategies can significantly improve the teaching-learning process.

Different authors, Mocinic [11] and Oliveira et al. [12], proposed the following list of active learning methods to be used by instructors in higher learning institutions to make the students creative and proficient in their learning:

Integrating the above-listed active learning methods in the instructional process based on the nature and contents of the course will make the student's learning successful and competent. For example, collaborative learning is one of the best methods of active learning which can facilitate learner's critical thinking. Peer interactions during collaborative learning can be helpful for the learner's development of critical thinking [13]. Therefore, as Eison [14] stated, the above-listed active learning strategies increase students:

• Students are involved to develop their higher order thinking skills.

**4. Psychological theories of active learning**

on student's active role in the teaching-learning process [16].

personal knowledge structure that they construct.

• Students are actively involved in different activities (e.g., writing, discussing, and reading).

Empowering Learners Using Active Learning in Higher Education Institutions

http://dx.doi.org/10.5772/intechopen.80838

35

It is clear that students have different areas of interest and learning styles in the instructional process. However, the traditional way (lecture method) of teaching assumes that all students learn the same, and they cognitively process information the same way at the same rate [1]. This is in fact impossible. Currently, there is a shift in education theory to a more studentcentered approach specifically active learning methodology [8], because this approach has its own contribution for the learners' better understanding of the issue/lesson presented to them. Student-centered teaching method emerged from constructivist learning theory [15]. This theory was frequently described as student-centered teaching method because it emphasized

According to Walsh and Inala [17], this approach seeks to engage students in their own learning and for them to actively take part in the learning process themselves rather than being simply fed information by their instructors. From the different theories, constructivism theory emphasized that the learner is the center of the learning process, while the instructors playing an advising and facilitating role. Here in constructivism theory, the learner is active rather than passive. Constructivist believes that knowledge is experienced-based activities rather than directed by instructors [18] and it is not received from the outside environment; rather, the student interprets and process what is received through the senses to create knowledge. According to Hativa [9], the theory of constructivism entails that students learn well only when they are active in the teaching-learning process rather than passive, when they use what they are taught to alter their prior knowledge, and when they construct their own understanding. In addition, learners develop their own interpretation of the issue presented to create a theory that makes sense to them. They then connect the new knowledge with the

Hativa [9] added that in the constructivist learning theory, "meaningful learning takes place only when students actively process the new information, interpret it, and link it to their present knowledge." This theory has an implication for effective classroom teaching in a way that instructors should encourage students' active involvement in the learning process and

In active learning, learners construct and formulate knowledge based on previously acquired beliefs and experiences. This theory has huge contribution in empowering learners using active learning methodology. The process followed to empower learners using active learning requires a dynamic interaction between the learners and their experience. The theoretical foundation of critical thinking and higher-order thinking skills is the constructivist principle

learners gain valuable information for their creativity and competency.

• Emphasis is placed on the learners' investigation of their attitudes and values.

Hence, to have the above-listed benefits, using different active learning strategies properly inside and outside the classroom is very important specifically for the learners. Eison [14] suggested that instructors have used larger proportion of time in helping students to develop their understanding and skills and a lesser proportion of time in transmitting information when they use active learning strategies appropriately. In this strategy (active learning), instructors provide opportunities for learners to apply and demonstrate what they are learning. In addition, they provide opportunities for learners to receive feedback from peers and/ or the instructors themselves. In general, the active learning strategies have the following characteristics in promoting students' learning in the classroom [7]:


*4.1.2 Dolphins*

• Families Delphinidae (the oceanic dolphins) (**Figure 2**) [2]

*Introductory Chapter: Marine Mammals of the World DOI: http://dx.doi.org/10.5772/intechopen.105110*

**Figure 1.** *Types of whales in the world.*

**Figure 2.** *Types of dolphins in the world.*

	- Bottlenose dolphin
	- Common dolphin
	- La Plata dolphin (disambiguation) dolphin,

40 species of dolphins within the Delphinidae, 6 are commonly called whales, including the killer and also the pilot whales.

Most dolphins are small, measuring 3 meters (10 feet) long, and have spindleshaped bodies, beaklike snouts (rostrums), and easy needlelike teeth. a number of these cetaceans are occasionally called porpoises.


**3. Alzheimer's disease**

It is expected that the number of Alzheimer's disease (AD) cases will rise to 152 million by the year 2050. It is estimated that over 50 million people worldwide are affected by AD [19, 20]. According to projections, approximately one in ten individuals over the age of 65 will be diagnosed with Alzheimer's disease in the coming years [1, 21]. AD is one of the most common types of dementia worldwide, accounting for two-thirds of all dementia cases [21]. Lifestyle and genetic factors play a role in the development of AD, with oxidative stress playing an important role in the pathogenesis of the disease [6]. AD is characterized by cognitive impairment, typically starting with memory loss and progressing to a state where individuals become dependent on caregivers [15, 20]. It is described as a degenerative brain disease characterized by memory decline, language impairment, and cognitive deficits [1, 19]. VC has been reported to have a neuroprotective effect due to its ability to scavenge free radicals, reduce β-amyloid activity, and participate in the chelation of iron, zinc, and copper

[21]. Despite adequate nutrient intake, Alzheimer's patients have low levels of VC, making VC supplementation a therapeutic approach for AD. VC has been reported to be a potent acetylcholinesterase inhibitor [6]. Mitochondrial dysfunction, high oxidative stress, and amyloid plaque formation play significant roles in the pathogenesis of AD. Long-term VC intake has been reported to significantly reduce amyloid plaque formation [3]. VC supplementation as an adjuvant therapy has gained significant interest in individuals with AD and Parkinson's disease (PH) [10]. Alzheimer's patients have reported low plasma levels of VC, which are associated with increased oxidative stress [1]. A study has reported that a VC-rich diet increases amyloid precursor protein levels [22].


**2.14. BCCH experience of lidocaine infusions for chronic pain**

Second infusion:

Third infusion:

toxicity.

infusion/s.

• Location and monitors as for initial infusion

• Infusion increased to 7 mg/kg over 90 min

• Time between infusions: usually a month

• Total dose: 8 mg/kg (loading dose + infusion)

• Infusion increased to 9 mg/kg over 90–120 min • Total dose: 10 mg/kg (loading dose + infusion)

**2.13. Continuous subcutaneous lidocaine therapy**

1. Child/youth is fully integrated into multi-disciplinary care

3. The pain is not amenable to the use of topical lidocaine

4. Child/youth has no contra-indication to the use of systemic lidocaine.

2. Their pain syndrome is lidocaine-responsive.

If IVLT is effective or partially effective, the patient can be started on a 5-day continuous subcutaneous (SC) infusion if pain is hampering for restoration of function/physical activity (**Table 5**). SC infusions use an elastomer pump which delivers a set volume of lidocaine per hour (depending on the pump used), usually 5 ml/h, which approximately equates with 2 mg/kg/h using 2% lidocaine for a patient who is 50 kg. The infusion only runs whilst the patient is awake so that they can self-report any symptoms, which may suggest lidocaine

5. Child/youth capable of verbally communicating analgesic response and symptoms of early local anaesthetic toxicity. 6. The child has previously experienced a lidocaine infusion in a high acuity environment without complication. 7. The child/youth demonstrates some improvement in functional activity following on from previous lidocaine

9. Appropriate homecare support, immediate telephone contact with healthcare team and follow-up are in place.

8. The child/youth and their principal carer demonstrate the ability to follow safety instructions.

**Table 5.** BCCH selection criteria for subcutaneous lidocaine therapy in child/youth.

• Time between infusions: usually a month

• Loading dose: 1 mg/kg bolus

82 Pain Relief - From Analgesics to Alternative Therapies

• Location and monitors as above

• Loading dose: 1 mg/kg bolus

Of 336 new children/youth seen as out-patients by one pain physician in our institution over a 6.5 year time frame, only 45 (13%) were considered appropriate for trial of IVLT; 36/45 (80%) of these patients were females. The diagnoses, IVLT treatments and outcomes for these 45 children/youth are shown in **Tables 6** and **7**.

**Table 6.** Diagnoses and number of IVLT treatments received as part of 3P treatment package.

**Table 7.** Improved outcomes reported by patients following 3P treatment including intravenous lidocaine therapy (IVLT).

It is clear that not all children and youth with chronic pain are candidates for IVLT. Focus should be on pain conditions with a neuropathic or central element. However, when appropriately selected, and integrated in multi-disciplinary care, IVLT can be part of the reason that children and youth experience less pain facilitating healthier sleep, improved physical activities, and return to school. It is also clear that not all children/youth considered appropriate for IVLT respond positively. This needs to be clearly outlined with a plan of management prior to embarking on an IVLT therapy.


*Edited by Farzana Khan Perveen*

This book contains seven chapters divided into two sections. The first section is "Lepidoptera Systematics." It covers introduction classification and external and internal morphology. It also includes the importance and modern approaches of Lepidoptera collection curation and data management. It also describes molecular phylogeny and taxonomy of Lepidoptera for ecological and evolutionary studies. The second section, "Lepidoptera as a Model for Research," describes eyespot color pattern formation mechanism in the peacock pansy, *Junonia almana* (L.). The complete mitochondrial genome of the American potato tuberworm, *Tecia solanivora* (Povolný), is presented to study a mitogenome in insects. Lepidoptera are sensitive to physical and climatic changes. Therefore, their taxocenotic and biocenotic study was conducted in three environments, i.e., the grassland, forest, and ecotone of Rucamanque, a forest remnant.

ISBN 978-953-51-3659-0

Lepidoptera

Photo by sakhorn38 / iStock


**Appendix 1.**

**Table A1.** *Cont.*

Notes: **†** Exact date unknown; **\*, \*\*, \*\*\*, \*\*\*\*** The number of stars at FEI level events signifies degree of difficulty, with \* being the lowest and \*\*\*\* being the highest.

**Table A1.** *Cont.*

*Animals* **2016**, *6*, 13

### **References**

© 2016 by the author; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

*Review*


**Abstract**

This chapter is based on the data from the national survey on tobacco, alcohol, and drugs among primary and secondary school students aged 15–19 implemented in eight regions of Slovakia during Spring 2018. An unexpected shift was observed in the relationship between the age young people were offered alcohol by an adult and the age when they first experienced its effect. In previous surveys, the mean age of the first offer predated the felt effect of alcohol ("tipsiness") by about 1 year on average. Our data revealed that following the initial offer of alcohol by an adult, approximately ¾ of participants felt the effect of alcohol *later* or during the same year (groups 1 and 2); however, in the remaining cases, the effect was felt *before* alcohol was offered by an adult (group 3). Thus, it appears that one-fifth to one-quarter of participants did not go through the usual ritual of initiation by adults. The analysis showed that this group of participants used cannabis more often than the rest of the sample. Furthermore, there were differences observed among the three groups in reported school attendance, legal and illegal drug use, and bullying. Possible implications of these findings are discussed.

**Keywords:** age of the first offer, tipsiness before or after offer of alcohol, cannabis use, adult persons and drinking initiation


**1. Introduction**

Two LysR-type transcriptional regulators (LTTRs) control benzoate degradation by a soil bacterium, *Acinetobacter baylyi* ADP1 [1]. These paralogs, BenM and CatM, have overlapping but distinct functions (Figure 1). BenM controls the initial steps in benzoate consumption by activating transcription of the *benABCDE* operon in response to benzoate and one of its metabolites, *cis,cis*-muconate, hereafter designated muconate [2,3]. CatM, which responds solely to muconate, activates low-level expression from this promoter, PbenA [4]. We sought to create a benzoate-responsive CatM that mimics an unusual characteristic of BenM, namely the ability to activate transcription synergistically in response to two effectors. These studies should improve understanding of the molecular basis of this type of transcriptional activation and, in general, facilitate the engineering of LTTRs to respond to novel effectors when designed for varied biotechnology applications.

BenM and CatM have similar N-terminal DNA-binding domains (DBDs, Figure 2), and they bind to the same regions of PbenA [2,4]. Whereas LTTR-DNA interactions repress basal transcription, conformational changes occur in response to effectors to activate transcription (depicted in Figure S1). Although CatM alone does not activate sufficient transcription for growth on benzoate as the carbon source, mutations can increase CatM-regulated PbenA transcription by augmenting its response to muconate or by enabling transcription without an effector [3,4]. Two amino acid replacements in

the effector-binding domain (EBD) of CatM each enable BenM-independent growth on benzoate, yet neither of these, nor any other known CatM variant, responds to benzoate.

**Figure 1.** BenM and CatM regulate the *ben* and *cat* genes from four promoter regions (diamonds). The *benABCDE* operon is primarily regulated by BenM from PbenA, and the *catBCIJFD* operon is primarily regulated by CatM from PcatB. The encoded enzymes are used for the degradation of benzoate.

**Figure 2.** (**A**) Ribbon representation of BenM-DBD and the adjacent "linker" helix bound to DNA (PDB ID 4IHS). Green side chains show differences between BenM and CatM. Labeled residues are discussed in the text. (**B**) Nine amino acids differences in the DBDs (bold), including those at positions 18 and 38 (highlighted). The Helix (α2)-Turn-Helix (α3) (HTH) motif is involved in DNA recognition.

The structures of BenM-EBD and CatM-EBD are highly conserved (Figure S2) [5,6]. Although benzoate binds in a hydrophobic pocket of BenM, this compound has not been detected in structures of the corresponding region of CatM [5,6]. This pocket is distinct from an inter-domain cleft in BenM and CatM that binds muconate and serves as the typical effector-binding site in LTTRs [6]. The EBDs of LTTRs usually assume the conformation of a periplasmic-binding protein [7–9]. However, BenM is the only LTTR known to have a secondary effector-binding site that enables synergistic activation of transcription with different metabolites [2]. In an effort to understand this synergism, we engineered amino acid replacements to make CatM more similar to BenM.

Two residues in the hydrophobic binding pocket of BenM are critical for benzoate-activated transcription, R160 and Y293 [5,6]. When these amino acids are replaced with those at the comparable positions of CatM, H160 and F293, BenM fails to activate transcription in response to benzoate as a sole effector or in combination with muconate [5]. Moreover, benzoate inhibits muconate-activated gene expression in these BenM variants [3,5]. As described here, the converse changes in CatM (H160R and F293Y) did not initially generate a benzoate-responsive CatM. However, efforts to alter CatM were expanded to increase understanding of these representative members of the LTTR family, the largest group of homologous transcriptional regulators in bacteria [10]. After multiple attempts, CatM variants were isolated that respond to benzoate and that activate increased transcription in response to both effectors. As discussed below, changes were required in both the DBD and EBD regions of CatM for this new functionality.

#### **2. Materials and Methods**

#### *2.1. Bacterial Strains and Growth Conditions*

*A. baylyi* strains, derived from the wild-type ADP1 [11,12] are listed in Table S1. *Escherichia coli* DH5α (Thermo Fisher Scientific, Waltham, MA, USA) and XL-1 blue (Agilent Technologies, Santa Clara, CA, USA) were used as plasmid hosts. Bacteria were grown on Luria-Bertani (LB) medium at 37 ◦C [13]. In some cases, *A. baylyi* strains were grown in minimal medium [14,15] with succinate (10 mM), pyruvate (20 mM), benzoate (2 mM), muconate, (2.5 mM), or anthranilate (1.5 mM) as the carbon source. Antibiotics were added when needed at the following final concentrations: ampicillin, 150 μg/mL, kanamycin, 25 μg/mL, spectinomycin, 13 μg/mL, and streptomycin, 13 μg/mL. Growth was monitored by turbidity (OD600).

#### *2.2. Site-Directed Mutagenesis and Strain Construction by Allelic Replacement*

Site-directed mutagenesis of plasmid DNA was conducted with mutagenic primers and methods based on the QuickChange II protocol (Agilent Technologies, Santa Clara, CA, USA [5]). The primers, and the mutations they introduce, are listed in Tables S2 and S3. In some cases, plasmids were constructed using splicing by overlap extension PCR (SOEing) [16]. Linearized plasmid-borne alleles were used to replace chromosomal genes in *A. baylyi* recipient strains by homologous recombination [17,18]. Transformants were identified by phenotypic changes in antibiotic resistance, carbon source utilization or loss of the *sacB* marker (in the presence of 10% sucrose and no NaCl in the medium) [5,18]. The genotypes of mutant strains were confirmed by PCR analysis and DNA sequencing (Genewiz laboratories, South Plainfield, NJ, USA) of the chromosomal regions where changes were introduced.

#### *2.3. Selection for BenM-Independent Growth on Benzoate*

Strains that form colonies on plates with benzoate as the sole carbon source were defined as Ben+. Spontaneous Ben+ mutants arising from strains lacking BenM were isolated as described [3,4]. Chromosomal *catM* DNA was recovered from Ben+ strains using the gap-repair method [18,19]. Briefly, cells were grown on benzoate medium to mid-log phase, mixed with linearized pBAC184 (Table S2) and plated on LB medium. Transformants with circularized plasmids, resulting from homologous recombination, were selected in medium with ampicillin. Drug-resistant cells were pooled, and plasmid DNA was extracted and used to transform *E. coli*. Recovered *A. baylyi* DNA was tested for the ability to confer a Ben+ phenotype to recipient strains (without BenM) by allelic replacement. Mutations were identified by DNA sequencing (Genewiz laboratories, South Plainfield, NJ, USA).

#### *2.4.* β*-Galactosidase (LacZ) Assays*

Transcriptional *lacZ* fusions were constructed as described [3,4]. For cultures grown on LB, effectors were added at final concentrations of 500 μM of benzoate or muconate, or when added together, 250 μM of each. Some cultures were grown with pyruvate (20 mM) or muconate (3 mM) as the carbon source. Effectors added to pyruvate-grown cultures were added at the following concentrations: 65 μM benzoate or muconate, or 32.5 μM of each when added together. Growth was measured by optical density (OD600), and assays were done when cultures reached late-exponential phase as

described [4,5]. Directions from the FlourAce β-galactosidase reporter kit (BioRad, Hercules, CA, USA) were followed. The hydrolysis of the substrate, 4 methylumbelliferyl-galactopyranoside (MUG) to the product 4-methyllumbelliferone (4MU) was detected with a TD-360 miniflourometer (Turner Designs, San Jose, CA, USA). A standard curve was used to quantify 4MU.

#### *2.5. Purification of BenM and CatM and Variant Proteins*

Plasmids, pBAC433 and pBAC430, were used to express full-length regulators with C-terminal histidine tags, BenM-His and CatM-His, respectively [2]. Plasmids were made to encode variants, pBAC1027 (BenM-DBDCatM-His), pBAC1045 (CatM(I18F,K38N)-His), and pBAC1086 (Ben-DBDCatM(H160R,F293Y)-His). BenM-His was purified as described [20]. CatM-His and CatM variants were purified similarly but were eluted in a di fferent bu ffer (30 mM Tris, 500 mM NaCl, 30% glycerol (*v*/*v*), 500 mM imidazole, and 10 mM β-mercaptoethanol (pH 7.9)). Fractions with pure CatM were pooled and dialyzed against a bu ffer (20 mM Tris-HCl, 250 imidazole (pH 7.9), 500 NaCl, 10% (*v*/*v*) glycerol) to increase solubility, and then were concentrated to 2–10 mg·mL−1. Protein concentrations were determined by the method of Bradford with bovine serum albumin as the standard [21]. Proteins fractions were frozen with liquid nitrogen and stored at −70 ◦C until use.

#### *2.6. Electrophoretic Mobility Shift Assays (EMSAs)*

Operator-promoter DNA (PbenA and PcatB) was PCR amplified with 5'-6-carboxyfluorescein (6-FAM) labeled primers (Table S3). PCR products, approximately 150–250 bp, were extracted with a gel DNA recovery kit (Zymo Research, Irvine, CA, USA). For EMSAs, 1 nM DNA was incubated with di fferent concentrations of protein (0, 2.5 nM, 5 nM, 10 nM, 20 nM, 40 nM, 80 nM, 160 nM, 320 nM, 640 nM and 1.28 μM) for 1 h at 37 ◦C with or without muconate, benzoate or both. E ffectors in the reaction were present at a total concentration of 1.6 mM individually or at a concentration of 800 μM each when combined. DNA-protein samples were resolved in 6% polyacrylamide gels. Electrophoresis was performed in bu ffer (40 mM Tris (pH 7.6), 20 mM acetic acid, 1 mM EDTA) for 1 h at 185 volts at 4 ◦C. When indicated, e ffectors were added to this bu ffer at the same concentrations described above. Fluorescently labeled bands were detected using the Amersham Typhoon PhosphorImager system (GE Healthcare Bio-Sciences, Pittsburgh, PA, USA) at 526 nm using the short-pass emission filter. The bound DNA relative to the unbound DNA was quantified by Gel-Pro analyzer (Media Cybernetics, Rockville, MD, USA). Values were fitted into a saturation curve using the equation for one site binding with total accounting for ligand depletion to determine the equilibrium constant (Kd) (Prism 8 software, GraphPad, San Diego, CA, USA) [22].

#### *2.7. Modeling the Transcription Activation Complex at PbenA and PcatB*

An atomic model of PbenA was created by merging the structures of BenM-DBD bound to DNA [23] and a transcription initiation complex of *E. coli* RNA polymerase (RNAP) [24] using the X3DNA suite [25] with the DNA atoms as alignment guides. Since the Site 1 DNA of PcatB has the most sequence identity with *benA* Site 2, the structure of BenM-DBD complexed with PcatB Site 1 (PDB ID 4IHS, chains A, B, E, and F) was used to model atoms locally at *benA* Site 2. The structure of BenM-DBD complexed with PbenA Site 1 (PDB ID 4IHT, chains A, B, E, and F) was used to model *benA* Site 1. The model for RNAP (PDB ID 4YLN) was positioned assuming that the TTGAAC downstream from PbenA Site 2 corresponds to the *E. coli* σ70 binding site with the sequence TTGACA in the 4IHT complex. DNA residues in the three structures were changed and renumbered to match the PbenA sequence with the program *mutate\_bases*. A composite DNA backbone was generated by calculating the helical parameter sets (shear, stretch, stagger, buckle, prop-tw, opening, shift, slide, rise, tilt, roll, and twist) with program *find\_pair* from the three individual DNA double helical segments and then merging the parameters into one file. The two helical parameter sets at the transition regions were averaged. A DNA model was generated from the combined helical parameters using the program *rebuild*. The three atomic structures containing both the DNA and protein residues were aligned on the composite

DNA backbone using *align* command of PyMOL [26]. Similar structures of the PcatB and PbenA5146 transcriptional activation complexes were generated by mutating the *benA* DNA sequences in the composite structure. The EBD domains were not fitted to the model because the close proximity of the two binding sites is not consistent with any full-length structure of an LTTR at this time.


**5. Initiation of ERT**

Initiation of ERT requires a fully confirmed diagnosis of Fabry disease [19]. The patient/patient's family should be included in the decision-making process and should have a good understanding of the impact of the treatment as well as potential adverse reactions. The initiation of lifelong ERT infusion therapy is a major decision with important implications for both the patient, particularly the pediatric patient, and the family [42]. Treatment and follow-up assessments should ideally be led by a physician who is experienced in the management of patients with Fabry disease, with support from a multidisciplinary clinical team including nephrology, cardiology, medical genetics, neurology, psychology, and nursing [19].


3.1.6. Lighting

We use six ARRI L5-c LED directional lights focusing on the individual participant. The lights are set to emit white light only to prevent any discoloring of the participants faces. The backlighting is done with a series of photo beard tungsten fluorescent tubes.

#### 3.1.7. Frame Rate and Storage

We record at the Kinect's maximum capabilities, RGB (1920 × 1080) and Depth (512 × 424) at 30 fps, for speed we save both files in binary format. The images stored are unmodified from the ones received from the Kinect, no lossy compression is implemented. As the data is stored in raw binary format the dataset requires, at the time of writing, over 675 GB of storage for the full dataset.


**6. Conclusions and unanswered questions**

Our study design was a prospective study to evaluate ongoing denervation/reinnervation process. Main aim was to objectively measure the extent of MU loss and the accompanying changes in innervation pattern during the time in ALS patients (Stålberg, 1983; Jabre, 1991), and therefore is often impossible to perform it in a hand muscle in the course of ALS due to the strong wasting of the intrinsic hand muscles; consequently to evaluate distal time disease evolution and its behaviour compared with proximal district we had to use only MUNE.

Area and amplitude of the Macro-MUP reflect number and size of muscle fibers in the motor unit (Schwartz et al., 1976; Stålberg et al., 1976). MUNE instead is the ideal tool for the assessment of disease in which primary defect is MU loss (Strong et al., 1988; Gooch and Shefner, 2004; Daube, 2006; Sartucci et al., 2007).

ALS is featured by repetitive cycles of denervation/reinnervation and the mechanism lead to a variation of fibre density within a given motor unit (Stålberg, 1983; de Carvalho et al., 2005a; de Carvalho et al., 2005b). If this rearrangement is interrupted by new processes of denervation, following further motor neuron loss, this will lead to areas of grouped atrophy and loss of muscle fibers. Reinnervation process are strictly interwoven with lower motor neuron loss; quantization and tracking of MU loss with simultaneously gauging countervailing collateral dynamic innervation may be assessed by combining MUNE and macro-EMG (Gooch and Shefner, 2004; Pouget, 2006). The macro-EMG gives a global view of the MU. First, the physical length of the electrode (15 mm), cover the entire diameter of an average sized MU; the large electrode surface suppresses the contribution of the closest action potentials and favours the relative influence of slow components so including distant fibers (Sanders and Stålberg, 1996).

Macro-EMG parameters in controls were in agreement with data of others authors (Stålberg and Fawcett, 1982; Stålberg, 1983; Jabre, 1991). Both macro-MUP area, amplitude and FD were beyond upper normal limits, as expected, in ALS (Bauermeister and Jabre, 1992; Gan and Jabre, 1992). Macro-EMG parameters progressively increased, at least in the first eight months compared with baseline as proved by coefficient of correlation at each time displaying a progressive increment of correlation up to 8 months, suggesting the process of MU rearrangement begins to fail after 8 months of disease course. Also when macro EMG area and amplitude were increased, FD was parallely increased.

The time elapsed from disease onset plays a fundamental role, since patients included with a diseases duration between 12 and 24 months showed largest changes in Macro EMG features, suggesting a higher efficiency of compensatory mechanisms at least in early stages of disease. Evidence of some MU loss at baseline compared with controls and its trend over time, together with a broader mean step area, yields novel insights into the pathophysiology of MU loss and its relationship to motor function in patients with ALS (Daube et al., 2000; Sartucci et al., 2007). Fluctuation of MU estimates between separate time could suggest reversible motoneurons dysfunction (Gooch and Shefner, 2004). The coefficient of correlation for MUNE – macro EMG mean area regression line was not significant (= - 0.17) in BB muscle, suggesting that both processes go on in some way independently. In more advanced stages, a decline of the strength of the surviving MUs, especially those with higher thresholds, seems to contribute to the progressive muscle weakness, in addition to both corticospinal degeneration and reduction in motoneurons

Our study design was a prospective study to evaluate ongoing denervation/reinnervation process. Main aim was to objectively measure the extent of MU loss and the accompanying changes in innervation pattern during the time in ALS patients (Stålberg, 1983; Jabre, 1991), and therefore is often impossible to perform it in a hand muscle in the course of ALS due to the strong wasting of the intrinsic hand muscles; consequently to evaluate distal time disease evolution and its behaviour compared with proximal district we had to use only

Area and amplitude of the Macro-MUP reflect number and size of muscle fibers in the motor unit (Schwartz et al., 1976; Stålberg et al., 1976). MUNE instead is the ideal tool for the assessment of disease in which primary defect is MU loss (Strong et al., 1988; Gooch and

ALS is featured by repetitive cycles of denervation/reinnervation and the mechanism lead to a variation of fibre density within a given motor unit (Stålberg, 1983; de Carvalho et al., 2005a; de Carvalho et al., 2005b). If this rearrangement is interrupted by new processes of denervation, following further motor neuron loss, this will lead to areas of grouped atrophy and loss of muscle fibers. Reinnervation process are strictly interwoven with lower motor neuron loss; quantization and tracking of MU loss with simultaneously gauging countervailing collateral dynamic innervation may be assessed by combining MUNE and macro-EMG (Gooch and Shefner, 2004; Pouget, 2006). The macro-EMG gives a global view of the MU. First, the physical length of the electrode (15 mm), cover the entire diameter of an average sized MU; the large electrode surface suppresses the contribution of the closest action potentials and favours the relative influence of slow components so including distant

Macro-EMG parameters in controls were in agreement with data of others authors (Stålberg and Fawcett, 1982; Stålberg, 1983; Jabre, 1991). Both macro-MUP area, amplitude and FD were beyond upper normal limits, as expected, in ALS (Bauermeister and Jabre, 1992; Gan and Jabre, 1992). Macro-EMG parameters progressively increased, at least in the first eight months compared with baseline as proved by coefficient of correlation at each time displaying a progressive increment of correlation up to 8 months, suggesting the process of MU rearrangement begins to fail after 8 months of disease course. Also when macro EMG area and amplitude were increased, FD was

The time elapsed from disease onset plays a fundamental role, since patients included with a diseases duration between 12 and 24 months showed largest changes in Macro EMG features, suggesting a higher efficiency of compensatory mechanisms at least in early stages of disease. Evidence of some MU loss at baseline compared with controls and its trend over time, together with a broader mean step area, yields novel insights into the pathophysiology of MU loss and its relationship to motor function in patients with ALS (Daube et al., 2000; Sartucci et al., 2007). Fluctuation of MU estimates between separate time could suggest reversible motoneurons dysfunction (Gooch and Shefner, 2004). The coefficient of correlation for MUNE – macro EMG mean area regression line was not significant (= - 0.17) in BB muscle, suggesting that both processes go on in some way independently. In more advanced stages, a decline of the strength of the surviving MUs, especially those with higher thresholds, seems to contribute to the progressive muscle weakness, in addition to both corticospinal degeneration and reduction in motoneurons

**6. Conclusions and unanswered questions**

Shefner, 2004; Daube, 2006; Sartucci et al., 2007).

fibers (Sanders and Stålberg, 1996).

parallely increased.

MUNE.

number (Dengler et al., 1990). Our study also showed a significant correlation between MRC scores and EDX measurements throughout the whole course of the disease only for ADM muscle. The absence of a significant correlation between MUNE and MRC values (p > 0.05) for BB could confirm the specificity of EDX investigations to track over time changes in muscle MU features and number. Muscle strength seems to decline more linearly than MUNE values: that could be explained, as recently suggested by Liu et al. (2009) with the persistence of a small proportion of lower motor neurons long-term surviving.

### **6.1 Gender and amyotrophic lateral sclerosis. Lessons from motor unit estimation**

Another interesting result is about gender differences (*Figure 5*); in fact, some studies have reported a significant male predominance until the sixth decade of life and an older average age at onset for females, sometimes explained with a possible protective effect of estrogen. In our experience, MUP amplitude at T0 did not show any significant difference between females and males, even if a bit higher in males: MUP amplitudes were 86.9 ± 21.2 µV and 84.1 ± 17.5 µV for the biceps brachii and abductor digiti minimi muscle, respectively, in females, 90.7 ± 17.3 µV and 88.2 ± 16.8 µV in males (p>0.05). This is only a trend, as gender don't influence motor unit loss neither corresponding decline in MRC values over time. The lack of significant differences between females and males in both spinal and bulbar form, as emerged from our sample, is consistent with results reported by Hegedus (Hegedus et al., 2009): the antioxidant effects of estrogens and their proved role in preventing glutamaterelated toxicity *in vitro* (Kruman et al., 1999; Nakamizo et al., 2000) could not delay both the early retraction of nerve terminals from neuromuscular end-plates and the dying-back of the axons during asymptomatic phase *in vivo*, as well as the denervation/reinnervation process in later stages. However, there is a substantial lack of studies describing the contribution of gender in progression of ALS; that's likely due to the discrepancy between humans patients and animal models, in terms of disease and presymptomatic phase duration, absence of sensitive biological markers and different pathogenesis (sporadic vs. SOD1-related; Zhou et al., 2007).

### **6.2 MUNE and Macro-EMG in evaluating response to treatment**

Our investigation was aimed to evaluate also the EDX effects of one of the most common drug employed in the ALS, riluzole (Leigh et al., 2003), on the fundamentals process of ALS: the primary process of motorneurons loss and denervation, and the secondary process of reinnervation. Riluzole is a benzothiazole derivative with a wide range of effects on glutamate pathways including inhibition of presynaptic glutamate release; it is relatively safe and well tolerated. Prescription of riluzole is restricted to patients with probable or definite ALS. At the moment, there is no convincing evidence that treatment at 100 mg daily is associated with a significant increase in survival (Miller et al., 2007); its effects on quality of life and survival are weak especially in older patients (over 75 years), in those with bulbar onset and at more advanced stages (Miller et al., 2003). We did not detect any significant electrophysiological difference between patient intaking the drug and those who didn't (see *Figure 6*), but considering the high attrition rate it's quite difficult to draw any conclusion about the effect of pharmacological treatments on neurophysiological parameters. Future studies are then required to solve this dilemma.

How to Assess Disease's Severity and Monitor Patients with

**7. References**

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Fig. 6. Effects of Riluzole on the macro EMG and MUNE parameters with the time, in patients intaking (filled circle) or not (empty circle) the drug (modified from Sartucci et al., 2011).


**10. Complications**

### **10.1 Airway problems**

Treatment of cleft patients with class III malocclusion that results out of the combination of maxillary hypoplasia and intermaxillary disorder is usually achieved by maxillary advancement, mandibular setback, and clockwise rotation of the maxillomandibular complex. While maxillary advancement is associated with increased upper airway cavity, in contrast, mandibular setback is associated with reduction of airways with outcomes such as postoperative airway blockage, snoring, hypopnea (slow respiration), and obstructive sleep apnoea [65, 66]. Additionally, a pharyngeal flap may contribute to the airway-related difficulties that are encountered during operation or in the postoperative period. When the three-dimensional (3D) pharyngeal airway cavity of cleft patients in their pre- or post-pubertal periods were compared to a control group, Karia et al. [66] found significantly smaller airway sizes in the cleft group. The total airway volume increased from the pre-pubertal to the post-pubertal periods in both groups, but the reason for this outcome in the cleft group was not anteroposterior growth as in the case of the control group, but in contrast, associated with vertical airway growth. Especially in bilateral cleft patients, significantly reduced pharyngeal airway cavity in comparison to individuals without clefts was also confirmed in a CBCT study [67].

A prospective study by Chang et al. [68] examined the airway changes in cleft patients who received maxillary advancement and mandibular setback treatments by not only CBCT but also polysomnographic examination. Regarding the airway changes after orthognathic surgery, it was found that there was no significant difference in sleep-related respiratory functions, but the snoring index was improved.


**8. Conclusions**

One important conclusion should be drawn from the research results presented above, namely, that lactic acid bacteria may cause a different hypocholesterolemic effect in the human digestive system. They may exhibit a clear capacity for permanent binding and removal of cholesterol or to not bind it at all. It is also possible that they may cause such change of the intestinal microflora. Hosono et al. [14] formed a hypothesis that lactic acid bacteria may influence the amount of cholesterol eliminated from the organism despite the fact that they do not have the capacity to transform it into coprostanol. This is an effect of the influence of lactic acid bacteria on other microorganisms present in the intestinal microflora, including microorganisms capable of transforming cholesterol into coprostanol. This is particularly possible in the case of probiotic strains of lactic acid bacteria and bifidobacteria, which are distinguished due to their capacity to produce low-molecular antimicrobial

**89**

*Cholesterol Uptake and Survival of* Lactococcus lactis *Strains in Fluids Simulating the Human…*

substances. Based on the results of experiments conducted by Ziarno [4], it can be stated that the phenomenon of cholesterol binding depends on such a wide array of factors influencing the cell wall and cytoplasmic membrane of bacteria that it may not be impossible to predict the hypocholesterolemic effect unambiguously.

It can be concluded that lactic acid bacteria are capable of binding cholesterol molecules present in their environment. Cholesterol can be subject to adhesion by the cell wall or assimilation via the cytoplasmic membrane or cell wall of lactic acid bacteria, including *Lactococcus*. However, the degree and force of this bond depend on numerous environmental factors. A change of even one of these parameters results in the hypocholesterolemic effect which is no longer reproducible in the experiments. It is likely that this is the manner in which the results and the discrepancies found between in vitro and perhaps also in vivo tests on human volunteers

This work was supported by a grant from Warsaw University of Life Sciences

The author has declared that she does not have any conflict of interest for

Division of Milk Biotechnology, Department of Biotechnology, Microbiology and Food Evaluation, Faculty of Food Sciences, Warsaw University of Life Sciences—

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

and experimental animals should be interpreted and explained.

*DOI: http://dx.doi.org/10.5772/intechopen.88462*

**Acknowledgements**

**Conflict of interest**

publishing this research.

(WULS-SGGW).

**Author details**

Małgorzata Ziarno

SGGW (WULS-SGGW), Warsaw, Poland

provided the original work is properly cited.

\*Address all correspondence to<EMAIL_ADDRESS>
*Cholesterol Uptake and Survival of* Lactococcus lactis *Strains in Fluids Simulating the Human… DOI: http://dx.doi.org/10.5772/intechopen.88462*

substances. Based on the results of experiments conducted by Ziarno [4], it can be stated that the phenomenon of cholesterol binding depends on such a wide array of factors influencing the cell wall and cytoplasmic membrane of bacteria that it may not be impossible to predict the hypocholesterolemic effect unambiguously.

It can be concluded that lactic acid bacteria are capable of binding cholesterol molecules present in their environment. Cholesterol can be subject to adhesion by the cell wall or assimilation via the cytoplasmic membrane or cell wall of lactic acid bacteria, including *Lactococcus*. However, the degree and force of this bond depend on numerous environmental factors. A change of even one of these parameters results in the hypocholesterolemic effect which is no longer reproducible in the experiments. It is likely that this is the manner in which the results and the discrepancies found between in vitro and perhaps also in vivo tests on human volunteers and experimental animals should be interpreted and explained.