**3. Results**

#### *3.1. Polyphenol Composition in the Elderberry Fruit Extract*

HPLC-DAD-ESI-MSn analysis of the EDB extract revealed the presence of 22 polyphenolic compounds, including anthocyanins (peaks 1–5), hydroxybenzoic acid derivative (peak 6), flavan-3-ols (peaks 7–8), polymers, tentatively identified as hydrolysable tannins (peaks 9–10), hydroxycinnamic acids (peaks 11–15), and flavonols (peaks 16–22). HPLC-DAD chromatograms and chromatographic characteristics with mass spectral data of polyphenols identified in the EDB extract are presented in Figure 1 and Table 2, respectively.

**Table 2.** HPLC-MS identification of phenolic compounds in elderberry fruit extract in positive (electrospray ionization (ESI) +) and negative (ESI −) ionization mode.

\* mg/g of lyophilized elderberry powder, values were expressed as mean ± SEM for three independent experiments.

Anthocyanins accounted for 43% of all polyphenolics; cyanidin-based anthocyanin compounds (-3,5- *O*-diglucoside, -3- *O*-sambubiosyl-5- *O*-glucoside, -3- *O*-glucoside, -3- *O*-rutinoside, and -3- *O*-sambubioside) were the main group of anthocyanins, with a significant predominance of cyanidin-3- *O*-sambubioside ([M + H]+ at *m*/*z* 287) constituting 73.2% of all anthocyanins. Peak 1 contained two compounds, identified as cyanidin-3,5- *O*-diglucoside ([M + H]+ at *m*/*z* 611) and cyanidin-3- *O*-sambubiosyl-5- *O*-glucoside ([M + H]+ at *m*/*z* 743). These anthocyanins represented 25.0% of total anthocyanin compounds, quantitatively determined in the EDB extract. In contrast, cyanidin-3- *O*-glucoside ([M + H]+ at *m*/*z* 449) and cyanidin-3- *O*-rutinoside ([M + H]+ at *m*/*z* 595) were only detected in trace amounts in the EDB extract (Table 2). The anthocyanin with a molecular ion of *m*/*z* 433, that yielded on MS2 fragment at *m*/*z* 271, was identified as pelargonidin-3- *O*-glucoside and quantified in small amounts estimated at 2.3% of all anthocyanins.

Other groups of compounds: Flavan-3-ols, hydroxycinnamic acids, and flavonols amounted to 22.1%, 16.0%, and 13.7% of the total content of polyphenols, respectively. Moreover, the presence of 4-hydroxybenzoic acid glucoside (5.2%) was found in the extract. The group of non-anthocyanin compounds with the largest share in the polyphenol pool were flavan-3-ols, among which catechin and epicatechin (36%), and tannins (64%) were identified. A total of five compounds were detected within another group of hydroxycinnamic acid derivatives, including *p*-coumaric acid hexoside (57%), *p*-coumaroylquinic acid (16%), chlorogenic acid, and its isomers: Neochlorogenic and cryptochlorogenic acids (27%). Concerning flavonols, the results of the HPLC-DAD analysis revealed the presence of quercetin, kaempferol, and isorhamnetin derivatives, with quercetin-3- *O*-rutinoside (53%) and kaempferol-3- *O*-rutinoside (32%) quantified as the dominant compounds within this class.

**Figure 1.** *Cont*.

The polyphenolic compounds, described above, have been previously identified in berries of *Sambucus nigra* [7,23,24]. However, the content of individual polyphenols in EDB fruits varies, depending on the EDB genotypes as well as specific growth conditions. The total polyphenol content in the extract analyzed was determined to 31.03 mg/g of EDB lyophilized powder, including 13.34 mg of anthocyanins, 6.85 mg of flavan-3-ols, 4.98 mg of hydroxycinnamic acid derivatives, 4.26 mg of flavonols, and 1.6 mg of hydroxybenzoic acid glucoside (Table 2).

#### *3.2. Digestive Enzyme Activity Inhibition by Elderberry Fruit Extract*

The EDB extract was evaluated for the ability to inhibit digestive enzymes, including α-glucosidase, α-amylase and lipase. The extract showed similar α-glucosidase and α-amylase inhibitions (Figure 2a,b), with the same IC10 value of 1.25 mg/mL and non-significantly different IC50 values of 6.38 mg/mL and 6.70 mg/mL, respectively (Table 3).

**Figure 2.** The effect of elderberry fruit extract (EDBE) on the activity of digestive enzymes: α-glucosidase (**a**), α-amylase (**b**), and lipase (**c**). Enzyme activity is expressed in relation to the negative control (without extract addition). As positive controls, reference enzyme inhibitors, including acarbose (ACRB, 100 μg/mL) and orlistat (ORST, 5 μg/mL) were used in the experiment. The values represent the means (*n* = 3) ± SD. \* *p* < 0.05, \*\*\* *p* < 0.001 vs. control group.

**Table 3.** Inhibitory concentrations IC10 and IC50 (the inhibitor concentration required for 10% and 50% inhibition of enzyme activity) of the elderberry fruit extract (EDBE), acarbose (ACRB), and orlistat (ORST) as reference pharmacological inhibitors.

Lower potency of the extract was observed in inhibiting pancreatic lipase activity. The extract concentrations reducing lipase activity by 10% and 50% were determined at 2.09 mg/mL and 10.98 mg/mL, respectively (Table 3). In inhibiting α-amylase and lipase activity, the drugs acarbose (100 μg/mL) and orlistat (5 μg/mL) were more potent than the EDB extract (Figure 2b,c). However, in α-glucosidase inhibition, the extract at concentrations of 5 mg/mL and 10 mg/mL evoked the stronger effects than acarbose at a dose of 100 μg/mL.

#### *3.3. The E*ff*ect of Elderberry Fruit Extract on Hypertrophied Adipocytes*

To determine whether EDB extract affects the condition of mature adipocytes, we examined its effect on the viability, lipid accumulation, and ROS production, as well as regulation of leptin and adiponectin expression in terminally differentiated 3T3-L1 cells. The obtained results indicated that EDB extract did not exert any significant effect on both adipocyte viability (Figure 3a) and intracellular lipid content (Figure 3b,g–i). Nevertheless, it dose-dependently inhibited the intracellular ROS generation in hypertrophied adipocytes. EDB extract caused 36%, 53%, and 58% decrease in ROS level when applied at 5, 10, and 20 mg/mL, respectively, in comparison to untreated cells (*p* < 0.001) (Figure 3c). Moreover, treatment with EDB extract led to down-regulation of *NADPH oxidase 4* (*NOX-4*) mRNA expression by approximately 49 ± 6%, independently of the extract dose. Treatment with the extract at the maximum concentration (20 mg/mL) resulted in approximately 2-fold increased mRNA expression of *superoxide dismutase* (*SOD*) and *glutathione peroxidase* (*GPx*). In contrast, the extract did not influence the mRNA expression level of *catalase* (*CAT*) (Figure 3d).

**Figure 3.** Changes in cell viability (**a**), intracellular triglyceride content (**b**), reactive oxygen species production (**c**), and mRNA expression of *NOX4*, *SOD2*, *catalase* (*CAT*), and *GPx* enzymes (**d**) as well as leptin (*LEP*) (**e**) and adiponectin (*ADIPOQ*) (**f**) expression upon the treatment of3T3-L1 mature adipocytes with the elderberry fruit extract (EDBE). The photos present 3T3-L1 preadipocytes (**g**), fully differentiated 3T3-L1 adipocytes non-treated (**h**) and treated with EDBE at the concentration of 20 mg/mL (**i**). The cells were photographed at magnification of 100 ×. The results were expressed as the means ± SD (*n* = 3). \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001 vs. control group.

Supplementation of the fully differentiated adipocyte cultures with EDB extract considerably affected the expression of key adipokines in treated adipocytes. The decrease in *leptin* (*LEP*) mRNA levels between 78% and 94% was observed in mature adipocytes exposed to the extract at concentrations ranging from 5 mg/mL to 20 mg/mL (*p* < 0.001) (Figure 3e). In contrast to leptin, the expression of adiponectin was significantly up-regulated. The highest dose of EDB extract elevated *adiponectin* (*ADIPOQ*) mRNA level by 77% compared to the control (*p* < 0.001) (Figure 3f). The exposure of mature adipocytes to EDB extract resulted in a decrease of leptin secretion. The extract at concentrations of 5 mg/mL and 10 mg/mL significantly reduced leptin synthesis (*p* < 0.05). Whereas, the highest inhibitory effect with the reduction of leptin by 86% (*p* < 0.001) was observed in the cells treated with the extract at maximum concentration. In contrast, EDB extract at the highest dose of 20 mg/mL stimulated the adiponectin secretion in treated cells. The level of adiponectin was increased by 36% respect to the control (*p* < 0.05) (Figure 3f).

#### *3.4. The E*ff*ect of Elderberry Fruit Extract on Glucose Uptake in Mature 3T3-L1 Adipocytes*

The effect of EDB extract on the glucose analogue (2-NBDG) uptake in mature 3T3-L1 adipocytes was analyzed to determine whether the extract affects the glucose uptake by adipocytes. As shown in Figure 4a, EDB extract caused a significant increase in 2-NBDG uptake at all assayed concentrations (*p* < 0.001). The extract stimulated 2-NBDG uptake by 40%, 44%, and 62% tested at 5, 10, and 20 mg/mL, respectively, in comparison to the control system. Unexpectedly, the stimulatory effect of the extract on the glucose uptake in insulin-sensitive cells was more effective than that observed with rosiglitazone (Figure 4a). Subsequently, the expression of *glucose transporter type 4* (*GLUT-4*) gene in mature 3T3-L1 cells exposed to EDB extract was investigated. The results indicated no significant effect of EDB extract on *GLUT-4* mRNA level (Figure 4d).

**Figure 4.** Effect of the elderberry fruit extract (EDBE) on the glucose uptake (**a**–**c**) and glucose transporter *GLUT-4* mRNA expression (**d**–**f**) in mature 3T3-L1 adipocytes non-induced (**a**,**d**) and induced by TNF-α (**b–f**) and non-treated (**b**,**e**) and treated (**c**,**f**) with insulin (INS). The cells were exposed to EDBE at concentrations of 5, 10, and 20 mg/mL, and to rosiglitazone (RGZ). Data are mean values ± SD (*n* = 3). The significance of the main effects of EDBE was determined by Tukey post hoc test; the control (INS, RGZ) significance was analyzed by T-student test; \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001.

In the parallel experiment, the influence of EDB extract on 2-NBDG incorporation into insulin resistant adipocytes treated with TNF-α was determined. The cells were incubated with the extract in the absence or presence of insulin at 100 nM. In the insulin-resistant adipocytes cultured without insulin supplementation, the EDB extract at concentrations of 5, 10, and 20 mg/mL enhanced 2-NBDG uptake by 40%, 38%, and 39%, respectively (Figure 4b). In this case, quantitative PCR analysis revealed that treatment with EDB extract at doses from 5 mg/mL to 20 mg/mL significantly up-regulated the mRNA expression of *GLUT-4* with an increase ranging from 63% to 82% (Figure 4e).

In the experiments on insulin resistant adipocytes exposed to insulin, the EDB extract at the highest concentration showed insulin-sensitizing properties, stimulating 2-NBDG incorporation by 34% (*p* < 0.01). Its efficacy was comparable to that of rosiglitazone, which enhanced the 2-NBDG uptake by 36% (*p* < 0.01) (Figure 4c). In this study, the extract at a dose of 20 mg/mL up-regulated the expression of *GLUT-4* by 33% (*p* < 0.01), compared to control adipocytes (Figure 4f).

#### *3.5. Anti-Inflammatory E*ff*ects of Elderberry Fruit Extract*

Anti-inflammatory effects of EDB extract were evaluated in activated RAW 264.7 macrophages, considering proinflammatory cytokines and mediators determined at both molecular and cellular levels, using low non-cytotoxic extract doses of 0.1, 1, and 10 μg/mL. The obtained results demonstrated the ability of EDB extract to alleviate the cellular inflammatory response induced by LPS. The extract at concentrations of 1 and 10 μg/mL suppressed mRNA expression of *IL-6* by 34% (*p* < 0.01) and 69% (*p* < 0.001), respectively, compared to control macrophages. Moreover, a 28% decrease in *TNF-*α mRNA level (*p* < 0.05) was observed following treatment with EDB extract at a dose of 10 μg/mL (Figure 5a). The down-regulation of *IL-6* and *TNF-*α expression was consistent with the inhibited secretion of these cytokines. Namely, EDB extract assayed at 1 μg/mL reduced production of IL-6 and TNF-α by 44% and 26%, respectively (*p* < 0.05). At the extract concentration of 10 μg/mL, the 60% decrease in IL-6 secretion (*p* < 0.01) was observed while synthesis of TNF-α was reduced by 52% (*p* < 0.001) (Figure 5b).

**Figure 5.** Effect of the elderberry fruit extract (EDBE) on mRNA expression of *IL-6*, *TNF-*α, *COX-2,* and *iNOS* (**a**) and on the production of IL-6, TNF-α, PGE2 protein, and NO (**b**) in the lipopolysaccharide (LPS)-activated RAW 264.7 macrophages. Data are mean values ± SD (*n* = 3). \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001 when compared with control.

The extract at a dose of 10 μg/mL also a ffected *COX-2* expression, causing a 46% reduction of *COX-2* transcripts level in activated macrophages (*p* < 0.01) (Figure 5a). As a consequence, the decrease in PGE2 production was detected after cell exposure to the extract. Namely, PGE2 level lowered by 33% and 47%, respectively, for a dose of 1 μg/mL and 10 μg/mL (Figure 5b).

Furthermore, the obtained results demonstrated the reduction in NO production as well as down-regulation of *inducible NO synthase* (*iNOS*) expression in LPS-stimulated RAW 264.7 macrophages in response to the EDB extract treatment. The extract reduced the NO synthesis by 35% (*p* < 0.05) when assayed at 1 μg/mL and by 54% (*p* < 0.01) when applied at 10 μg/mL (Figure 5b). A significant inhibitory e ffect of EDB extract on *iNOS* expression was noted only at the highest tested dose, which decreased *iNOS* mRNA level by 30% (*p* < 0.01) (Figure 5a).


*2.6. Bioethics*

The ATTICA study was approved by our institutional ethics committee and conformed to the ethical guidelines of the 1975 declaration of Helsinki. All participants were informed about the study protocol, and they provided written signed consent.

## *2.7. Statistical Analysis*

To define the dietary patterns, factor analysis using the PC was applied [34]. Principal components were retained if their eigenvalues were greater than 1.0, a threshold that is commonly used as a cut-o ff to identify meaningful patterns. The resulting components were interpreted based on the variables with loadings above 0.3. Moreover, the Kaiser-Meyer-Olkin criterion was used as a measure of variables (components) inter-correlation and used as an indicator of internal consistency.

Normally distributed continuous variables are presented as mean values ± SD, and categorical variables as frequencies. Normality was tested using the Shapiro-Wilk criterion; the non-normally distributed variables are presented as median and 1st, 3rd tertile. Associations between categorical variables were tested by the chi-square test, whereas between continuous variables by the Pearson r or Spearman's rho coe fficients for normally distributed and skewed variables, respectively. Continuous variables were tested for normality via P-P plots. For normally distributed variables, comparisons were performed by the student's t-test, after controlling for equality of variances by the Levene's test. For continuous variables without normal distribution, comparisons were performed by the non-parametric Mann-Whitney U-test. Previous literature was used as a guide for the selection of variables used for adjustment between dietary patterns and anxiety [35–37]. Multiple linear regression analyses were performed in order to evaluate the association between anxiety as the dependent outcome and a participant´s adherence to dietary patterns, adjusted for multiple confounders. All *p*-values are based on two-sided tests. Statistical analyses were performed with the Statistical Package for Social Sciences version 22 (SPSS Inc., Chicago, IL, USA).


*Review* **ACO (Asthma–COPD Overlap) Is Independent from COPD, a Case in Favor: A Systematic Review**

**Naoya Fujino \* and Hisatoshi Sugiura**

Department of Respiratory Medicine, Tohoku University Graduate School of Medicine, Sendai 980-8574, Japan<EMAIL_ADDRESS>
**\*** Correspondence<EMAIL_ADDRESS>Tel.: +81-22-717-8539

**Abstract:** Asthma and chronic obstructive pulmonary disease (COPD) are now recognized to be able to co-exist as asthma–COPD overlap (ACO). It is clinically relevant to evaluate whether patients with COPD concurrently have components of asthma in primary care. This is because: (i) ACO is a relatively common condition among asthma (over 40 years of age) or COPD irrespective of its diagnosis criteria; (ii) patients with ACO can have higher frequency of exacerbation and more rapid decline in lung function than those with asthma or COPD; and (iii) asthmatic features such as eosinophilic airway inflammation are promising indicators for prediction of inhaled corticosteroidresponsiveness in COPD. The aim of this review to evaluate diagnostic markers for ACO. We searched PubMed for articles related to ACO published until 2020. Articles associated with diagnostic biomarkers were included. We identified a total of 25 studies, some of which have revealed that a combination of biomarkers such as fractional exhaled nitric oxide and serum immunoglobulin E is useful to discern type 2 inflammation in the airways of COPD. Here, we review the current understanding of the clinical characteristics, biomarkers and molecular pathophysiology of ACO in the context of how ACO can be differentiated from COPD.

**Keywords:** asthma–COPD overlap; asthma; COPD; fractional exhaled nitric oxide; immunoglobulin E

### **Citation:** Fujino, N.; Sugiura, H. ACO (Asthma–COPD Overlap) Is Independent from COPD, a Case in Favor: A Systematic Review. *Diagnostics* **2021**, *11*, 859. https:// doi.org/10.3390/diagnostics11050859

Academic Editor: Koichi Nishimura

Received: 6 May 2021 Accepted: 10 May 2021 Published: 11 May 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

**1. Introduction**

#### *1.1. Background of Asthma and Chronic Obstructive Pulmonary Disesase*

The global burdens of asthma and chronic obstructive pulmonary disease (COPD) are increasing, each of which was estimated to affect respectively approximate 339 million and 251 million people worldwide in 2016 [1]. It has been widely accepted that asthma and COPD are strikingly different airway disorders [2,3]. Although the "Dutch hypothesis" suggested a common genetic background underlying airway obstruction with a spectrum of clinical entities from asthma to COPD, recent genetic research indicated that it was unlikely that genetic factors are shared by asthma and COPD [4].

Asthma is a heterogenous and inflammatory disease affecting large and small respiratory tracts but not the lung parenchyma, and contains clusters of demographical, clinical and pathophysiological characteristics underpinned by different pathophysiological processes [5]. This heterogeneity may be explained by the complexity of dysregulated innate and adaptive inflammatory responses to exogenous allergens and proteases leading to the spectrum of abnormal tissue remodeling, where type 2 cytokines such as interleukin (IL)-4, IL-13 and IL-5 primarily promote airway eosinophil infiltration, mucus hypersecretion, bronchial hyperresponsiveness and mast cell activation [6]. Major subpopulations of asthmatics have molecular signatures of T helper 2 (Th2)—inflammation and airway obstruction that markedly respond to inhaled corticosteroid (ICS) [7]. In line with this translational study, accumulated evidence from randomized control trials have revealed the importance of ICS usage from the early steps of asthma treatment because clinical studies have shown that ICS robustly reduced the risk of symptoms, exacerbations, hospitalization and mortality from asthma [8–10].

23

COPD is defined as a common, preventable and treatable disease that is characterized by persistent respiratory symptoms and airflow limitation that is due to airway and/or alveolar abnormalities usually caused by significant exposure to noxious particles or gases and influenced by host factors including abnormal lung development [11]. In addition to cigarette smoking, known as the most common COPD risk factor [12], the susceptibility could be influenced by genetic factors [13,14] and abnormal lung growth [15]. Unlike asthma, CD4<sup>+</sup> T helper 1 (Th1) cells, CD8+ cytotoxic T (Tc) cells, neutrophils and macrophages predominantly affect the small airways and the lung parenchyma leading to mucus hypersecretion, alveolar wall destruction (emphysema) and small airway fibrosis in COPD [2,16]. These pro-inflammatory cell-types are functionally altered by oxidative stress and intracellular signaling pathways including activation of the proinflammatory transcription factor nuclear factor κB (NF-κB) [17], and alveolar macrophages are defective in bacterial phagocytosis, possibly via several phagocytic receptors and mitochondrial molecules related to oxidative stress [18–21]. The small airway narrowing induced by pro-inflammatory cell infiltration, luminal exudates, wall thickening, and the loss of small airways associated with emphysema increases airway obstruction [22,23]. In the wall thickening, hyperplasia of basal cells, known as airway epithelial stem cells, could be formed through several molecules such as Axl receptor tyrosine kinase [24] and Yap-Wnt7b [25]. The airflow limitation progressively leads to gas-trapping in peripheral lungs during expiration on exercise, resulting in dynamic hyperinflation which is postulated to be the main mechanism of exertional dyspnea [26,27]. Thus bronchodilators, long-acting muscarinic antagonists (LAMA) and long acting beta2-agonists (LABA), are commonly used as the pharmacological therapy for COPD and are known to reduce lung hyperinflation, dyspnea and exercise endurance [28,29] leading to improvement of the quality of life and a reduction in the frequency of exacerbations [30]. Accumulated evidence indicates that LAMA significantly reduce the frequency of exacerbations and non-serious adverse events and increase the trough forced expiratory volume in one second (FEV1) compared to LABA in patients with stable COPD [31].

#### *1.2. Safety Issues of ICS for Airway Infection of Patients with COPD*

Several lines of evidence have indicated a higher risk of pulmonary infection in COPD patients. A population-based, case-control study conducted in Spain including 859,033 inhabitants showed a strong relationship between COPD and community-acquired pneumonia, which was independent of other clinical factors (odds ratio (OR) 1.84 (95% confidence interval (CI), 1.32–2.59)) [32]. A prospective case-control study with 175,906 COPD subjects in Canada also demonstrated that current use of ICS further increased the risk of hospitalization for pneumonia (rate ratio (RR) 1.70 (95% CI, 1.63–1.77)) and pneumonia followed by death within 30 days (RR 1.53 (95% CI, 1.30–1.80)) [33]. Particularly, a subset of COPD treated with ICS who had both less than 100 cells/μL of blood eosinophils and chronic bronchial infection by potentially pathogenic microorganisms was at higher risk of pneumonia (OR 3.238 (95% CI, 1.426–7.231)) [34]. Moreover, the current use of ICS in subjects even without oral corticosteroid also increased the risk of tuberculosis (TB) in a lowprevalence country (RR 1.33 (95% CI, 1.04–1.71)) [35] as well as in an intermediate-burden setting (OR 1.20 (95% CI 1.08–1.34)) [36]. In addition, the increased risk of TB infection was significantly associated with higher doses of ICS [35,36]. These studies highlighted the importance of the risk of pulmonary infection among COPD patients who are treated with high dose ICS and provided the clinically relevant question of which subset of COPD subjects would benefit from ICS therapy.

#### *1.3. Needs for Considering Patients with Clinical Features of Both Asthma and COPD*

From the early 2000s onwards, the differential diagnosis of patients with respiratory symptoms who are more than forty years of age has been recognized to be more problematic. This is because COPD becomes more common in older adults and discriminating asthma with persistent airflow obstruction from COPD is often challenging [37,38]. In fact, in

2007, the *Canadian Thoracic Society Recommendations for Management of Chronic Obstructive Pulmonary Disease—2007 Update* described the concept of "combined COPD and asthma" to highlight the finding that early introduction of ICS could be justified if the COPD patients had prominent features of asthma [39]. In 2009, Gibson and Simpson introduced the word of "the overlap syndrome of asthma and COPD" and noted that, since these patients had been largely excluded from pivotal therapeutic trials for both asthma and COPD, its diagnosis and treatment were poorly defined and lacking firm evidence [40]. Despite a growing controversy over clinical and prognostic features of ACO, retrospective studies have provided the plausible premise showing that patients with both asthma and COPD have more respiratory symptoms [41], high frequency of exacerbations [41,42] and accelerated decline in lung function [43]. Thereafter, articles regarding asthma–COPD overlap syndrome (ACOS) have been widely reviewed [44–46]. Following these early reviews, in 2014, the Global Strategy for Asthma Management and Prevention (GINA) and the Global Initiative for Chronic Obstructive Pulmonary Disease (GOLD) jointly issued their consensus-based document on ACOS so that clinicians were able to distinguish asthma from COPD and make a diagnosis of ACOS in patients with chronic airflow limitation [47]. GINA then suggested the descriptive term asthma–COPD overlap (ACO) rather than ACOS, which had been often interpreted as implying a single disease [48].

In 2016, based on the urgent requirement of an operational definition of ACO, a global expert panel from North America, Western Europe and Asia proposed criteria for its diagnosis, which consisted of age, smoking history, the presence of persistent airflow limitation defined by spirometry, history of asthma and allergic rhinitis, bronchodilator response in FEV1 and peripheral blood eosinophil counts [49]. Following this attempt, some guidelines, such as Spanish [50] and Japanese [51] guidelines, published diagnostic algorithms that employed objective evaluations of eosinophilic and allergic airway inflammation by quantifying the levels of fractional exhaled nitric oxide (FeNO) and serum immunoglobulin E (IgE). However, the GOLD 2020 update has stated that it no longer mentions ACO [11]. This was because asthma and COPD were different disorders, although they might share common traits and clinical features. In addition, it further documented that "if a concurrent diagnosis of asthma is suspected, pharmacotherapy should primarily follow asthma guidelines, but pharmacological and non-pharmacological approaches may be needed for their COPD". This has given rise to pro and con arguments for experts in obstructive lung diseases [52,53]. As patients with ACO have been certainly excluded from clinical studies of asthma and COPD [49], molecular mechanisms of the disease and evidence of appropriate therapies are less well understood. Considering the pro-con discussion, we still have a large, unresolved question concerning why we should have a diagnostic term of ACO and how we can distinguish between COPD and ACO. The rationale of this systematic review is to describe how ACO differs in clinical features and pathogenesis from COPD. Thus, we aimed to elaborate clinical features and diagnostic markers that enable to discriminate ACO from COPD.

#### **2. Methods**

#### *2.1. Search Strategy and Eligibility Criteria*

This systematic review adheres to the PRISMA guidelines [54]. We searched PubMed for publications until 2020 with terms of "asthma–COPD overlap" or either "diagnosis" or "biomarker". Articles were included if they indicated a total population to evaluate diagnostic biomarkers such as FeNO, IgE, humoral factors or radiographical findings to be able to differentiate ACO from COPD. We excluded articles that: (1) were not associated with diagnosis of ACO by the titles and abstracts; (2) were systematic reviews or guidelines; (3) were subset analyses in other studies; (4) did not report any biomarkers except for blood eosinophil counts and pulmonary function tests. We finally added five articles reporting FeNO-driven identification of ICS responders in patients with COPD as citation searching.

#### *2.2. Data Collection and Risk of Bias Assessment*

Two review authors (NF and HS) screened the titles and abstracts of all studies identified. Full text assessments were performed to identify studies that met inclusion criteria. The risk of bias in the eligible studies was evaluated in accordance with the recommendations in the Cochrane Handbook for Systematic Reviews of Interventions 5.1.0.

#### **3. Results**

#### *3.1. Characteristics of Selected Studies and Risk of Bias*

The literature search yielded 226 candidate studies. After excluding studies on the basis of their titles or abstracts or through examining their full texts, 20 were identified. We also included five articles reporting FeNO-driven identification of ICS responders in patients with COPD as citation searching. Thus, 25 studies were included in this review (Figure 1). These studies were summarized in Table 1. Diagnostic markers for ACO included FeNO, combination of FeNO and IgE, blood, urine or induced sputum biomarkers such as inflammatory cytokines and radiographical parameters (Table 1). There were high selection bias and performance bias in the included studies.

#### **Figure 1.** Study selection.

*3.2. Possible Diagnostic Biomarkers for ACO: The Role of Fractional Exhaled Nitric Oxide, FeNO and IgE for the Detection of Asthmatic Features of COPD Patients*

3.2.1. FeNO as a Potential Biomarker for Type 2 Inflammation for Optimal Diagnosis and to Predict the Treatment Response in Asthma.

Nitric oxide (NO) mainly originates from respiratory epithelial cells and is dominantly produced through inducible NO synthase (iNOS). Homeostatic interferon (IFN)-γ and its downstream molecule, signal transducer and activator of transcription (STAT)-1, maintains iNOS expression in the airway epithelium of healthy subjects [55]. Alving et al. firstly reported level that the FeNO of patients with mild atopic asthma was two- to three-fold higher than that of healthy control subjects [56]. A large-scale general population study supported this preliminary data by demonstrating that individuals with both increased FeNO levels and blood eosinophil counts had an increased risk of respiratory symptoms of asthma and ACO [57]. In addition, the FeNO levels were significantly increased in atopic asthma compared to non-atopic asthma [58]. The increase in the FeNO levels was

underpinned by the up-regulation of iNOS mRNA and protein expression in the airway epithelium of asthmatics [59–62]. A clinical study using a selective iNOS inhibitor further confirmed that up-regulation of the FeNO levels dominantly depended on the increased iNOS expression in asthmatic patients [63]. The extent of FeNO was significantly correlated with the eosinophil counts in induced sputum [64], endobronchial biopsies [65] and bronchoalveolar fluid [66] in asthmatics, suggesting that FeNO could be used as a surrogate marker for eosinophilic airway inflammation. Although airway hyperresponsiveness (AHR) of steroid-naïve asthmatics at baseline was not associated with airway inflammation markers such as FeNO and eosinophils in induced sputum, the improvement of AHR and FEV1 by inhaled corticosteroid therapy was significantly correlated with a reduction in the FeNO levels in those patients [67]. Researchers and clinicians in the field of asthma and allergy have given much attention to the molecular mechanisms underlying the upregulation of iNOS in asthmatic airways. Two groups reported that IL-13 induced iNOS mRNA and protein expression, which was significantly correlated with NO gas production in primary bronchial epithelial cells from healthy subjects [68] and mild-moderate asthmatics [69]. The contribution of the IL-4 and IL-13 pathway to the increase in airway NO production was further confirmed by clinical trials demonstrating that the FeNO levels were reduced in asthmatic patients treated with IL-4/IL-13 signaling blockade including nebulized soluble recombinant IL-4 receptor [70], inhaled recombinant IL-4 variant [71] and a monoclonal antibody to the alpha subunit of the IL-4 receptor alpha [72]. Collectively, these basic, translational and clinical studies have shown convincing evidence that FeNO could be a surrogate marker for type 2 inflammation of the airway.

3.2.2. How Can Feno Be Adopted to Discern ICS-Responsive, Asthmatic Phenotypes in COPD?

COPD is a highly complex and heterogenous disease, including several characteristics that could provide a rationale for the development of precision medicine [73]. Because inappropriate treatment with ICS is known to increase the risk of pneumonia for COPD patients, as discussed above, ICS should be ideally used for patients who can be expected to respond to corticosteroid therapy. Brightling et al. performed a randomized, double blind, crossover trial revealing that subjects with COPD who had higher eosinophil counts in their induced sputum exhibited increased post-bronchodilator FEV1 after six-week-treatment with ICS [74]. Based on this research, much effort has been given to ask whether FeNO can be used to identify asthma-associated features related to a favorable ICS response among COPD patients (Table 1). These studies, despite the small numbers of patients included, produced consistent and substantial results demonstrating that the initial FeNO levels were significantly correlated with the improvement of airway obstruction evaluated by FEV1 or ΔN2 after additional ICS therapy [75–79]. Moreover, a recent double-blind randomized placebo-controlled trial including 214 undiagnosed subjects who had cough, wheeze or dyspnea showed that FeNO could be used in clinical practice for patients with non-specific respiratory symptoms in order to predict the ICS response [80]. Although these studies showed promise for the general use of FeNO in the clinical setting of COPD, it is still unclear whether a FeNO cut-off value could be determined to identify an ICS-responsive subset of COPD patients [81]. This question is of particular importance because the GOLD guideline limited the use of ICS to only the following types of patients: (i) Group D patients with greater than 300 cells/μL of blood eosinophils in initial pharmacological treatment or in follow-up pharmacological management post exacerbations and (ii) patients with more than 100 cells/μL of blood eosinophils when experiencing more than 2 moderate exacerbations per year or at least one severe exacerbation requiring hospitalization in the prior year [11]. Recent clinical studies compared FeNO levels between COPD and ACO and confirmed high accuracy of diagnosis to discriminate ACO from COPD [82–86].

#### **Table 1.** Characteristics of included studies.

#### **Table 1.** *Cont.*

**Table 1.** *Cont.*

COPD, chronic obstructive pulmonary disease; FEV1, forced expiratory volume in one second; FeNO, fractional exhaled nitric oxide; ICS, inhaled corticosteroid; FVC, forced vital capacity; IgE, immunoglobulin E; GOLD, global initiative for COPD. CI, confidence interval; IL, interleukin; TNF, tumor necrosis factor; MPO, myeloperoxidase; NGAL, neutrophil gelatinase-associated lipocalin; YKL-40, chitinase-like protein; IQR, interquartile range; CT, computed tomography.

#### 3.2.3. Serum IgE Elevation and Atopic Background for COPD and ACO

Atopy refers to a genetic tendency to produce IgE typically for common and environmental allergens including inhaled allergens and food allergens. The presence of IgE specific for inhaled allergens, such as dust mites, cockroach and animal dander, is known to be a risk factor for asthma [102,103]. Serum total IgE levels were significantly correlated in pairs of siblings for bronchial hyperresponsiveness to histamine, which is implicated as a coinherited trait [104]. In addition, symptoms and exacerbations of asthma were significantly associated with an elevation of serum total IgE, which was independent of specific IgE [105]. This intriguing role of total, non-specific IgE in the association with asthma may be explained by the ability of IgE to enhance mast cell survival via Fcε receptor I cross-linking [106]. Serum levels of total IgE, IL-4 and leukotriene B4 were increased in ACO compared to COPD [107]. These observational and translational studies suggest that the mast cell activation pathway is upregulated in ACO as with asthma. This hypothesis was further supported by at least two clinical studies indicating that omalizumab, a humanized monoclonal antibody for IgE, markedly improved asthma control and health-related quality of life in ACO and this observed improvement in ACO was as large as that in asthma [108,109]. Given the evidence regarding IgE biology in atopic asthma overlapping COPD, it may be sensible to evaluate asthma complications in COPD patients with atopy.

#### 3.2.4. Combination of Type 2 Inflammation-Related Biomarkers to Define ACO

In order to maximize the benefits of ICS for COPD patients while preventing them from having pulmonary infectious diseases including pneumonia and TB caused by its inappropriate use, a combination of biomarkers may be promising for precisely defining an ICS-responsive subset. Based on this concept, our group attempted to determine whether the combination of FeNO and serum IgE had the ability to discern asthmatic, ICS-responsive features among patients with COPD. We found that the sensitivity was 1.0 and the specificity was 0.56 for the subjects who had reversibility of airway obstruction by 12-week-inhalation therapy of fluticasone propionate (FP)/Salmeterol (SAL) when FeNO > 35 parts per billion (ppb) and/or a positive result for specific IgE (atopy+) were combined [78]. Especially, all of the patients with both FeNO > 35 ppb and atopy+ responded to the additional FP/SAL therapy [78]. In addition, no patients with both less than 35 ppb of FeNO and a negative result of specific IgE responded to FP/SAL. We further reported that the prevalence of expected high ICS responders (i.e., FeNO > 35 ppb and atopy+) was 7.8 % of Japanese COPD subjects, whereas that of patients who were not likely given the benefits of ICS (i.e., FeNO ≤ 35 ppb and atopy−) was 54.8% [87]. Another Japanese cohort confirmed this result [88]. These clinical proof-of-concept studies may illustrate that a combination of biomarkers related to type 2 inflammation could be useful for a more precise definition of ACO. Given this concept, in 2018 the Japanese Respiratory Society (JRS) issued guidelines for new definitions and diagnostic criteria of ACO (Table 2) [51,110]. It is noteworthy that these two biomarkers (FeNO and IgE) were included in the criteria to identify the features of asthma among COPD subjects.

COPD, chronic obstructive pulmonary disease; FEV1, forced expiratory volume in one second; FeNO, fractional exhaled nitric oxide; FVC, forced vital capacity; IgE, immunoglobulin E; DLCO, diffusing capacity of the lung carbon monoxide; VA, alveolar volume.

> Two recent reports used the criteria to better characterize the clinical features of ACO in the Japanese population. A retrospective study investigating 170 subjects with persistent airflow limitation indicated that the prevalence of ACO among COPD patients was 31.5% [111]. However, one of the limitations in the retrospective study was that the use of ICS was not controlled, and that the characterization of clinical phenotypes could be biased or masked by ICS. More recently, Hirai, et al. investigated the prevalence of ACO among ICS-naïve patients with COPD and compared the baseline characteristics between COPD and ACO [112]. 197 patients with COPD were included in this study and 38 (19.3%) met the ACO diagnostic criteria by the Japanese guidelines. Although they did not find statistical significance in the baseline clinical features (age, gender, pack

years of smoking and pulmonary function) between ACO and COPD, symptoms and dyspnea evaluated by COPD assessment test (CAT) and modified MRC (mMRC) scale were significantly worse in ACO compared to COPD [112]. In addition, the frequency of acute exacerbations during the one year prior to the participation was three times higher in ACO than in COPD [112]. These studies with other literature [82–86] support the concept that the diagnostic criteria using biomarkers such as FeNO and IgE could be a landmark in facilitating a secure identification of ICS-responders among COPD patients. However, further worldwide research will be necessary to uncover how much the ACO diagnostic criteria could improve the clinical practice for COPD and ACO and to what extent the use of ICS could be avoided. Major problems regarding the development of diagnostic biomarkers include how biological parameters are weighed and how the cut-off values are determined. Leading-edge approach using omics and machine learning may solve this problem in an unbiased way [113–115].

#### *3.3. Possible Biomarkers Relevant to Eosinophilic and Neutrophilic Inflammation in ACO*

Christenson, et al. revealed transcriptome of airway epithelial cells in steroid-naïve subjects with mild to moderate asthma (n = 62) and control subjects without asthma (n = 43) and defined the asthma-derived gene expression signatures of Th2 inflammation [116]. The Th2-high signatures identified a clinically relevant subgroup of COPD that had a favourable response to ICS [116]. Eosinophils activated by the Th2-related priming agents, such as IL-5, IL-3, IL-33, granulocyte-macrophage colony-stimulating factor (GM-CSF) or Notch ligands acquire cell motility, increase respiratory burst and release granule proteins including eosinophil-derived neurotoxin (EDN) [117]. The serum EDN levels are known to correlate with the persistent airflow limitation with adult asthma and to be significantly decreased post eight-week treatment of omalizumab [118]. Serum EDN was significantly higher in ACO compared to asthma and COPD [119]. In addition, using a putative diagnosis biomarker for COPD, YKL-40 [120,121], combined assessment of serum EDN and YKL-40 revealed that a subset with both high serum EDN and YKL-40 levels was 45% in ACO, 14% in asthma and 30% in COPD (OR 3.85 (95% CI, 2.35–6.36); sensitivity, 45.2%; specificity 82.4%) [119]. Interestingly, this study showed other subsets of ACO based on the levels of EDN and YKL-40 (27% in high EDN and low YKL-40, 16% in low EDN and high YKL-40 and 12% in low EDN and low YKL-40), confirming that ACO was a heterogenous condition including different forms of airway diseases [47]. Since YKL-40 alone might not be reproducible for the diagnosis of ACO [93,94], combinatory evaluation might be useful.

Not only the eosinophil-related protein EDN but also a neutrophil-associated protein may be involved in the pathogenesis of ACO. Neutrophil gelatinase-associated lipocalin (NGAL) is constitutively expressed by neutrophils and has a pivotal role in antimicrobial immunity by binding bacterial siderophores and depriving bacterial iron [122]. The NGAL protein levels were elevated in induced sputum [123] and plasma [124] in patients with COPD. Moreover, the NGAL levels in bronchoalveolar lavage fluid were elevated even in subjects who had emphysematous changes with normal FEV1 [125,126]. Considering a biochemical study demonstrating that NGAL prevented matrix metalloproteinase (MMP)- 9 from being degraded and maintained the MMP-9 enzymatic activity [127], NGAL has been recognized to contribute to the development of pulmonary emphysema. However, the NGAL levels in induced sputum were significantly higher in ACO compared to COPD and asthma [128]. This might be explained by recent data indicating that NGAL is also secreted from epithelial cells of renal, intestinal and respiratory systems and is now considered to be a biomarker for acute kidney injury [122]. These data suggest that neutrophilic inflammation, emphysematous changes and epithelial injuries might contribute to the elevated levels of NGAL in induced sputum from patients with ACO [128]. However, pro-inflammatory cytokines associated with type 1 and type 2 immunity in peripheral blood might not be useful to diagnose ACO from COPD [91,96].

Recent studies using novel technologies have identified candidate molecules for biomarkers of ACO. Cai, et al. reported that several eicosanoids associated with allergic inflammation were upregulated in ACO compared to COPD and demonstrated high sensitivity and specificity to differentiate ACO from COPD [95]. Urine metabolomics approach found that L-histidine levels were significantly higher in ACO compared to COPD and asthma [97]. Computed tomographic analyses have captured characteristics of allergic airway inflammation in the upper and lower airways to predict the presence of asthma-related lesions in ACO [99–101].

#### **4. Discussion**

There are important problems yet to be addressed in clinical practice for ACO and COPD: Why should we have a diagnostic term of ACO? How can we distinguish between COPD and ACO? Since inappropriate use of ICS increases the risk of respiratory infection in COPD patients, we need to maximize the ability to identify the subset of favourable response to ICS. Our systematic review showed that FeNO was useful biomarker to identify asthmatic components in patients with COPD. In addition, a combination of biomarkers such as FeNO and IgE would be useful and provide promising diagnostic criteria for ACO, which could be validated by future studies. To define more precisely the pathophysiology of ACO, it would be essential to uncover the molecular mechanisms underlying inflammation, tissue damage/repair and oxidative/nitrosative stress that can differentiate ACO from COPD. In fact, several attempts have been done to clarify eosinophilic and neutrophilic inflammation using blood, induced sputum and urine.

Because there has been no global consensus on the diagnostic criteria of ACO, its prevalence considerably depends on how it is defined [129]. However, a recent meta-analysis of 27 studies from North America, Europe and Asia reported that the prevalence of ACO was estimated to be 2.0% (95% confidence interval (CI): 1.4–2.6%) in the general population, 26.5% (95% CI: 19.5–33.6%) among patients with asthma and 29.6% (95% CI: 19.3–33.9%) among patients with COPD [130]. In line with this meta-analysis, recent epidemiological studies confirm that ACO is a common disease in primary care [131,132]. These epidemiological data highlight the clinical importance of evaluating whether patients with airflow limitation have the features of both COPD and asthma and if patients with COPD concurrently have components of asthma in primary care. Thus, further studies are required to detect the features of asthma among patients with COPD using novel biomarkers.

One biological aspect which was not described here is genetics. Genome-wide association studies in non-Hispanic whites and African-American populations (n = 3120 in COPD; 450 in ACO) indicated that the most significant single nucleotide polymorphisms (SNPs) were in or near *GPR65* on chromosome 14 [133]. *GPP65* encodes the chief acid-sensing receptor, G protein-coupled receptor 65 (GPR65), which increased the cellular viability of eosinophils in allergic airway inflammatory settings in mice [134]. Interestingly, the GWAS study for ACO and COPD failed to identify known asthma-associated genetic loci such as *ORMDL3*, *IL1RL1* and *IL4R* [135], indicating that ACO was not just an overlapping condition of asthma and COPD but was associated with a specific genetic background independent of asthma or COPD.

Another aspect of ACO is associated with redox imbalance. Our group has recently reported a key role of oxidative and nitrosative stress in the pathogenesis of ACO. We reported that excessive nitrosative stress and lower antioxidant capability were observed in neutrophils and macrophages collected from the airways of patients with ACO [136]. This redox imbalance was associated with increases in IL-8, monocyte chemotactic protein-1 (MCP-1), tumor necrosis factor (TNF)-α in induced sputum and with a prospective clinical course of higher frequency of exacerbation and more rapid decline of FEV1 in ACO subjects compared to asthmatics [136]. These current data on the role of oxidative and nitrosative stress in ACO development may have clinical implications and provide novel insights for therapeutic strategies [137]. Future basic and translational research to define the molecular and cellular phenotypes of ACO differentiating from COPD are needed.

There are several limitations in this review. First, the number of patients included in the selected studies was relatively small. Second, diagnosis of asthma was not unified

over the selected studies. Third, the selected studies were not randomized control trials. Finally, we did not examine publication bias. These suggest that the risk of selection and performance bias is high in this review. This may be due to the limited studies available regarding ACO diagnosis. Future studies are required to reduce bias and to more precisely define ACO pathogenesis.

#### **5. Conclusions**

This review demonstrates the current clinical features and diagnostic markers that enable the differentiation of ACO from COPD and discusses possible future directions that should be addressed. In conclusion, a combination of biomarkers such as FeNO and IgE is useful for ACO diagnosis to reduce airway infections in patients with COPD.

**Author Contributions:** Conceptualization, N.F. and H.S.; writing—original draft preparation, N.F.; writing—review and editing, N.F. and H.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by MSD Life Science Foundation, Public Interest Incorporated Foundation.

**Acknowledgments:** We very much appreciate Brent K Bell for reading of the manuscript.

**Conflicts of Interest:** N.F. reports personal fees for lectures from AstraZeneca, outside the submitted work. HS reports grants from MSD and Novartis, personal fees for lectures from Astellas, KYORIN, Novartis and Sanofi, and personal fees for lectures and consulting from AstraZeneca, Boehringer Ingelheim and GlaxoSmithKline, outside the submitted work.

### **References**


It is possible to calculate the quantity of Na metal produced throughout the year by the selfcontained sodium (Na) metal production plant sited in the different geographic locations given in Table 2, based on the hours of daylight and the prevailing air mass conditions. It is not necessary to specify a detailed design for the NaOH electrolytic cell to generate an accurate daily estimate of Na metal production yield throughout the year, if it is assumed that maximum electric power available from the solar tower PV device panel array can always be supplied to the electrolytic cells by appropriately controlling the electrical resistance of the NaOH electrolytic cells together with the set point reference voltage VSET of the PWM DC-DC converter. It is assumed that electrolysis of NaOH, and thereby Na metal production can only occur if the available current supplied by the solar tower PV device panel array has a minimum threshold value of IST ¼ 3,000 A. In Figure 10, the production yield of Na metal is calculated for each day of the hypothetical year 2015, for electrolysis of pure NaOH according to Eq. (2), for the four geographic locations listed in Table 2, using the solar position algorithm (SPA) described in Solar position algorithm for solar radiation applications written by Reda & Andreas in 2004, that is a refined algorithm based on the book, The Astronomical Algorithms written by Meeus in 1998, and is presently regarded as the most accurate [73, 74]. The SPA allows the solar zenith θsz, and azimuth γs, angles to be calculated with uncertainties of �0.0003� in the range between -2000 to 6000 years.

Figure 10. Calculated sodium (Na) metal daily production yields throughout the hypothetical year 2015, for El Paso, Texas (thick solid), Alice Springs, Australia (thin solid), Bangkok, Thailand (thick dash) and Mbandaka, DRC (thin dash).

The calculation in Figure 10 provides the expected daily sodium (Na) metal production yield under the assumption that the energy conversion efficiency ηPV ¼ 90% for the solar tower PV device panel array and furthermore, current is only transmitted to the electrolytic cells when the solar tower PV device panel array receives sufficient solar irradiance to produce the minimum threshold value of current IST ¼ 3,000 A. The calculation in Figure 10, uses the SPA algorithm to determine the solar zenith angle θsz, throughout the day from sunrise to sunset for each day of the hypothetical year 2015, and calculates the air mass (AM) using Eq. (18). The direct normal total (spectrally integrated) solar irradiance incident onto the solar tower PV device panel array is calculated in turn, using Eq. (19) in a real time manner, as the solar position and air mass change throughout the day for each day of the year. The results from Figure 10, show that consistent quantities of Na metal are produced throughout the year when the self-contained sodium (Na) metal production plant is located as near as possible to the equator where the length of the day is the most uniform. Further away from the equator, the variability in the length of the day increases however, even at a latitude ϕ ¼ þ31.8�, in El Paso, Texas, the variability in the length of the day is not so significant as to render Na metal production uneconomical during the winter months when the daylight interval becomes reduced. The mean daily sodium (Na) metal production yields for the hypothetical year 2015 are calculated as 41,998 kg/day for El Paso, 41,884 kg/day for Alice Springs, 40,281 kg/day for Bangkok and 40,947 kg/day for Mbandaka, assuming a mean annual aerosol optical thickness value ka ¼ 0.1 reflecting clear days and uninterrupted Na production for all 365 days of the year. Notwithstanding the variability in daily Na metal production throughout the year, El Paso, Texas has the highest elevation above mean sea level when compared with Alice Springs, Bangkok and Mbandaka as shown in Table 2, resulting in an increased solar irradiance incident onto the PV device panel array and thus, the highest mean daily Na metal production. A conservative estimate for the true mean daily sodium (Na) metal production yield for the year might be mNa ¼ 30,000 kg/day of Na metal, as a consequence of nonproductive days due to inclement weather and required plant maintenance. The results in Figure 10, clearly demonstrate that the scalable, self-contained solar powered electrolytic sodium (Na) metal production plant can be constructed almost anywhere on earth and especially in the southwestern region of the U.S.A., to achieve a hydrogen (H2(g)) fuel, sustainable, closed clean energy cycle.


**6. Organizational interventions**

Organizational interventions focus primarily on making systematic changes to the work environment, including demands and resources, duty schedules, and interactions with leaders and colleagues.

a.**Work environment intervention**: High demands on HCWs is a primary contributing factor to increased burnout. The 24/7 nature of professional duties affecting personal and family life, the complexity of patients' medical and social needs, increased medical documentation requirements, financial constraints, and lack of administrative support for clerical tasks are adding to the daily demand. Burnout has also been linked to the number of working hours, the number of night duty, longer duration shifts, and consecutive working days.

Interventions like adding medical assistants, offloading clerical tasks, reducing patient–nurse ratios, and improving workload by streamlining workflow or adding clinical support are the most common strategies for burnout reduction, particularly for physicians [32]. Studies have shown improvement in burnout by reducing resident duty hours, physician hours in intensive care units, and teaching rotations [19, 31]. These approaches resonate with the excessive workload as a contributor to burnout. HCW burnout is not simply because of the increased workload. It also occurs when high demands are not in concurrence with resources and organizational support. Leaders can use this knowledge to reduce burnout by balancing new needs with allocated resources.

profession altogether [35–37]. Organization support can lead to significantly less emotional exhaustion and better safety culture among these HCWs [37].

d.**Interactions with colleagues**: Improving teamwork can profoundly affect HCW interactions with colleagues and their overall work environment. A study among almost 8000 HCWs demonstrated that HCWs routinely exposed to rudeness in their workplace had significantly higher levels of exhaustion emotionally and depression than those not exposed [38].


*Copyright © 2016 Solevåg, Haemmerle, van Os, Bach, Cheung and Schmölzer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*