Flame (v2.0): advanced integration and interpretation of functional enrichment results from multiple sources.

Functional enrichment is the process of identifying implicated functional terms from a given input list of genes or proteins. In this article, we present Flame (v2.0), a web tool which offers a combinatorial approach through merging and visualizing results from widely used functional enrichment applications while also allowing various flexible input options. In this version, Flame utilizes the aGOtool, g: Profiler, WebGestalt, and Enrichr pipelines and presents their outputs separately or in combination following a visual analytics approach. For intuitive representations and easier interpretation, it uses interactive plots such as parameterizable networks, heatmaps, barcharts, and scatter plots. Users can also: (i) handle multiple protein/gene lists and analyse union and intersection sets simultaneously through interactive UpSet plots, (ii) automatically extract genes and proteins from free text through text-mining and Named Entity Recognition (NER) techniques, (iii) upload single nucleotide polymorphisms (SNPs) and extract their relative genes, or (iv) analyse multiple lists of differentially expressed proteins/genes after selecting them interactively from a parameterizable volcano plot. Compared to the previous version of 197 supported organisms, Flame (v2.0) currently allows enrichment for 14 436 organisms. AVAILABILITY AND IMPLEMENTATION: Web Application: http://flame.pavlopouloslab.info. Code: https://github.com/PavlopoulosLab/Flame. Docker: https://hub.docker.com/r/pavlopouloslab/flame.

Antioxidant Activity of Leaf Extracts from Stevia rebaudiana Bertoni Exerts Attenuating Effect on Diseased Experimental Rats: A Systematic Review and Meta-Analysis.

Stevia (Stevia rebaudiana Bertoni) is an aromatic plant known for its high sweetening power ascribed to its glycosides. Stevia also contains several bioactive compounds showing antioxidant, antiproliferative, antimicrobial, and anti-inflammatory activities. Since inflammation and oxidative stress play critical roles in the pathogenesis of many diseases, stevia emerges as a promising natural product that could support human health. In this study we set out to investigate the way stevia affects oxidative stress markers (e.g., SOD, CAT, GPx, GSH, MDA) in diseased rats administered stevia leaf extracts or glycosides. To this end, we performed an inclusive literature search, following PRISMA guidelines, and recruited multivariate meta-analysis and meta-regression to synthesize all available data on experimental animal models encountering (a) healthy, (b) diseased, and (c) stevia-treated diseased rats. From the 184 articles initially retrieved, 24 satisfied the eligibility criteria, containing 104 studies. Our results demonstrate that regardless of the assay employed, stevia leaf extracts restored all oxidative stress markers to a higher extent compared to pure glycosides. Meta-regression analysis revealed that results from SOD, CAT, GSH, and TAC assays are not statistically significantly different (p = 0.184) and can be combined in meta-analysis. Organic extracts from stevia leaves showed more robust antioxidant properties compared to aqueous or hydroalcoholic ones. The restoration of oxidative markers ranged from 65% to 85% and was exhibited in all tested tissues. Rats with diabetes mellitus were found to have the highest restorative response to stevia leaf extract administration. Our results suggest that stevia leaf extract can act protectively against various diseases through its antioxidant properties. However, which of each of the multitude of stevia compounds contribute to this effect, and to what extent, awaits further investigation.

In Silico Identification and Analysis of Proteins Containing the Phox Homology Phosphoinositide-Binding Domain in Kinetoplastea Protists: Evolutionary Conservation and Uniqueness of Phox-Homology-Domain-Containing Protein Architectures.

Kinetoplastea are free living and parasitic protists with unique features among Eukaryota. Pathogenic Kinetoplastea parasites (i.e., Trypanosoma and Leishmania spp.) undergo several developmental transitions essential for survival in their hosts. These transitions require membrane and cytoskeleton reorganizations that involve phosphoinositides (PIs). Phospholipids like PIs are key regulators of vital functions in all eukaryotes including signal transduction, protein transport and sorting, membrane trafficking, and cytoskeleton and membrane remodeling. A large repertoire of PI-metabolizing enzymes and PI-binding proteins/effectors carrying distinct PI-binding modules like the PX (phox homology) module could play significant roles in the life and virulence of pathogenic Kinetoplastea. The aim of this study was to retrieve the entire spectrum of Kinetoplastea protein sequences containing the PX module (PX-proteins), predict their structures, and identify in them evolutionary conserved and unique traits. Using a large array of bioinformatics tools, protein IDs from two searches (based on PFam's pHMM for PX domain (PF00787)) were combined, aligned, and utilized for the construction of a new Kinetoplastea_PX pHMM. This three-step search retrieved 170 PX-protein sequences. Structural domain configuration analysis identified PX, Pkinase, Lipocalin_5, and Vps5/BAR3-WASP domains and clustered them into five distinct subfamilies. Phylogenetic tree and domain architecture analysis showed that some domain architectures exist in proteomes of all Kinetoplastea spp., while others are genus-specific. Finally, amino acid conservation logos of the Kinetoplastea spp. and Homo sapiens PX domains revealed high evolutionary conservation in residues forming the critical structural motifs for PtdIns3P recognition. This study highlights the PX-Pkinase domain architecture as unique within Trypanosoma spp. and forms the basis for a targeted functional analysis of Kinetoplastea PX-proteins as putative targets for a rational design of anti-parasitic drugs.

School Health Services and Health Education Curricula in Greece: Scoping Review and Policy Plan.

The new generation's health and wellbeing is of paramount importance: it constitutes United Nations' priority, complies with Children's Rights and responds to the Sustainable Development Goals of the United Nations. In this perspective, school health and health education, as facets of the public health domain targeted at young people, deserve further attention after the unprecedented COVID-19 pandemic crisis in order to revise policies. The key objectives of this article are (a) to review the evidence generated over a span of two decades (2003-2023), identifying the main policy gaps by taking Greece as a case study, and (b) to provide a concrete and integrated policy plan. Following the qualitative research paradigm, a scoping review is used to identify policy gaps in school health services (SHS) and school health education curricula (SHEC). Data are extracted from four databases: Scopus, PubMed, Web of Science and Google Scholar, while the findings are categorized into the following themes following specific inclusion and exclusion criteria: school health services, school health education curricula, school nursing, all with reference to Greece. A corpus of 162 out 282 documents in English and Greek initially accumulated, is finally used. The 162 documents consisted of seven doctoral theses, four legislative texts, 27 conference proceedings, 117 publications in journals and seven syllabuses. Out of the 162 documents, only 17 correspond to the set of research questions. The findings suggest that school health services are not school-based but a function of the primary health care system, whereas health education retains a constantly changing position in school curricula, and several deficiencies in schoolteachers' training, coordination and leadership impede the implementation. Regarding the second objective of this article, a set of policy measures is provided in terms of a problem-solving perspective, towards the reform and integration of school health with health education.

Influenza and Pneumococcal Vaccination and the Risk of COVID-19: A Systematic Review and Meta-Analysis.

A number of studies have investigated the potential on-specific effects of some routinely administered vaccines (e.g., influenza, pneumococcal) on COVID-19 related outcomes, with contrasting results. In order to elucidate this discrepancy, we conducted a systematic review and meta-analysis to assess the association between seasonal influenza vaccination and pneumococcal vaccination with SARS-CoV-2 infection and its clinical outcomes. PubMed and medRxiv databases were searched up to April 2022. A random effects model was used in the meta-analysis to pool odds ratio (OR) and adjusted estimates with 95% confidence intervals (CIs). Heterogeneity was quantitatively assessed using the Cochran's Q and the I2 index. Subgroup analysis, sensitivity analysis and assessment of publication bias were performed for all outcomes. In total, 38 observational studies were included in the meta-analysis and there was substantial heterogeneity. Influenza and pneumococcal vaccination were associated with lower risk of SARS-CoV-2 infection (OR: 0.80, 95% CI: 0.75-0.86 and OR: 0.70, 95% CI: 0.57-0.88, respectively). Regarding influenza vaccination, it seems that the majority of studies did not properly adjust for all potential confounders, so when the analysis was limited to studies that adjusted for age, gender, comorbidities and socioeconomic indices, the association diminished. This is not the case regarding pneumococcal vaccination, for which even after adjustment for such factors the association persisted. Regarding harder endpoints such as ICU admission and death, current data do not support the association. Possible explanations are discussed, including trained immunity, inadequate matching for socioeconomic indices and possible coinfection.

Immune-based treatment re-challenge in renal cell carcinoma: A systematic review and meta-analysis.

Introduction: The use of immune checkpoint inhibitors (ICIs) as a front-line treatment for metastatic renal cell carcinoma (RCC) has significantly improved patient' outcome. However, little is known about the efficacy or lack thereof of immunotherapy after prior use of anti-PD1/PD-L1 or/and anti-CTLA monoclonal antibodies. Methods: Electronic databases, including PubMed, EMBASE, Medline, Web of Science, and Cochrane Library, were comprehensively searched from inception to July 2022. Objective response rates (ORR), progression-free survival (PFS), and ≥ grade 3 adverse events (AEs) were assessed in the meta-analysis, along with corresponding 95% confidence intervals (CIs) and publication bias. Results: Ten studies which contained a total of 500 patients were included. The pooled ORR was 19% (95% CI: 10, 31), and PFS was 5.6 months (95% CI: 4.1, 7.8). There were ≥ grade 3 AEs noted in 25% of patients (95% CI: 14, 37). Conclusion: This meta-analysis on different second-line ICI-containing therapies in ICI-pretreated mRCC patients supports a modest efficacy and tolerable toxicity.

Predicting the Annual Funding for Public Hospitals with Regression Analysis on Hospital's Operating Costs: Evidence from the Greek Public Sector.

The funding of public hospitals is an issue that has been of great concern to health systems in the past decades. Public hospitals are owned and fully funded by the government, providing in most countries medical care to patients free of charge, covering expenses and wages by government reimbursement. Several studies in different countries have attempted to investigate the potential role and contribution of hospital and clinical data to their overall financial requirements. Many of them have suggested the necessity of implementing DRGs (Diagnosis Related Groups) and activity-based funding, whereas others identify flaws and difficulties with these methods. What was attempted in this study is to find an alternative way of estimating the necessary fundings for public hospitals, regardless the case mix managed by each of them, based on their characteristics (size, specialty, location, intensive care units, number of employees, etc.) and its annual output (patients, days of hospitalization, number of surgeries, laboratory tests, etc.). We used financial and operational data from 121 public hospitals in Greece for a 2-years period (2018-2019) and evaluated with regression analysis the contribution of descriptive and operational data in the total operational cost. Since we had repeated measures from the same hospitals over the years, we used methods suitable for longitudinal data analysis and developed a model for calculating annual operational costs with an R²≈0.95. The main conclusion is that the type of hospital in combination with the number of beds, the existence of an intensive care unit, the number of employees, the total number of inpatients, their days of hospitalization and the total number of laboratory tests are the key factors that determine the hospital's operating costs. The significant implication of this model that emerged from this study is its potential to form the basis for a national system of economic evaluation of public hospitals and allocation of national resources for public health.

Drug genetic associations with COVID-19 manifestations: a data mining and network biology approach.

Available drugs have been used as an urgent attempt through clinical trials to minimize severe cases of hospitalizations with Coronavirus disease (COVID-19), however, there are limited data on common pharmacogenomics affecting concomitant medications response in patients with comorbidities. To identify the genomic determinants that influence COVID-19 susceptibility, we use a computational, statistical, and network biology approach to analyze relationships of ineffective concomitant medication with an adverse effect on patients. We statistically construct a pharmacogenetic/biomarker network with significant drug-gene interactions originating from gene-disease associations. Investigation of the predicted pharmacogenes encompassing the gene-disease-gene pharmacogenomics (PGx) network suggests that these genes could play a significant role in COVID-19 clinical manifestation due to their association with autoimmune, metabolic, neurological, cardiovascular, and degenerative disorders, some of which have been reported to be crucial comorbidities in a COVID-19 patient.

Genetic Analysis and Status of Brown Bear Sub-Populations in Three National Parks of Greece Functioning as Strongholds for the Species' Conservation.

In order to optimize the appropriate conservation actions for the brown bear (Ursus arctos L.) population in Greece, we estimated the census (Nc) and effective (Ne) population size as well as the genetic status of brown bear sub-populations in three National Parks (NP): Prespa (MBPNP), Pindos (PINDNP), and Rhodopi (RMNP). The Prespa and Pindos sub-populations are located in western Greece and the Rhodopi population is located in eastern Greece. We extracted DNA from 472 hair samples and amplified through PCR 10 microsatellite loci. In total, 257 of 472 samples (54.5%) were genotyped for 6-10 microsatellite loci. Genetic analysis revealed that the Ne was 35, 118, and 61 individuals in MBPNP, PINDNP, and RMNP, respectively, while high levels of inbreeding were found in Prespa and Rhodopi but not in Pindos. Moreover, analysis of genetic structure showed that the Pindos population is genetically distinct, whereas Prespa and Rhodopi show mutual overlaps. Finally, we found a notable gene flow from Prespa to Rhodopi (10.19%) and from Rhodopi to Prespa (14.96%). Therefore, targeted actions for the conservation of the bears that live in the abovementioned areas must be undertaken, in order to ensure the species' viability and to preserve the corridors that allow connectivity between the bear sub-populations in Greece.

Identifying and Predicting Healthcare Waste Management Costs for an Optimal Sustainable Management System: Evidence from the Greek Public Sector.

The healthcare sector is an ever-growing industry which produces a vast amount of waste each year, and it is crucial for healthcare systems to have an effective and sustainable medical waste management system in order to protect public health. Greek public hospitals in 2018 produced 9500 tons of hazardous healthcare wastes, and it is expected to reach 18,200 tons in 2025 and exceed 18,800 tons in 2030. In this paper, we investigated the factors that affect healthcare wastes. We obtained data from all Greek public hospitals and conducted a regression analysis, with the management cost of waste and the kilos of waste as the dependent variables, and a number of variables reflecting the characteristics of each hospital and its output as the independent variables. We applied and compared several models. Our study shows that healthcare wastes are affected by several individual-hospital characteristics, such as the number of beds, the type of the hospital, the services the hospital provides, the number of annual inpatients, the days of stay, the total number of surgeries, the existence of special units, and the total number of employees. Finally, our study presents two prediction models concerning the management costs and quantities of infectious waste for Greece's public hospitals and proposes specific actions to reduce healthcare wastes and the respective costs, as well as to implement and adopt certain tools, in terms of sustainability.

Performance of Antigen Detection Tests for SARS-CoV-2: A Systematic Review and Meta-Analysis.

Coronavirus disease 2019 (COVID-19) initiated global health care challenges such as the necessity for new diagnostic tests. Diagnosis by real-time PCR remains the gold-standard method, yet economical and technical issues prohibit its use in points of care (POC) or for repetitive tests in populations. A lot of effort has been exerted in developing, using, and validating antigen-based tests (ATs). Since individual studies focus on few methodological aspects of ATs, a comparison of different tests is needed. Herein, we perform a systematic review and meta-analysis of data from articles in PubMed, medRxiv and bioRxiv. The bivariate method for meta-analysis of diagnostic tests pooling sensitivities and specificities was used. Most of the AT types for SARS-CoV-2 were lateral flow immunoassays (LFIA), fluorescence immunoassays (FIA), and chemiluminescence enzyme immunoassays (CLEIA). We identified 235 articles containing data from 220,049 individuals. All ATs using nasopharyngeal samples show better performance than those with throat saliva (72% compared to 40%). Moreover, the rapid methods LFIA and FIA show about 10% lower sensitivity compared to the laboratory-based CLEIA method (72% compared to 82%). In addition, rapid ATs show higher sensitivity in symptomatic patients compared to asymptomatic patients, suggesting that viral load is a crucial parameter for ATs performed in POCs. Finally, all methods perform with very high specificity, reaching around 99%. LFIA tests, though with moderate sensitivity, appear as the most attractive method for use in POCs and for performing seroprevalence studies.

MAGE: An Open-Source Tool for Meta-Analysis of Gene Expression Studies.

MAGE (Meta-Analysis of Gene Expression) is a Python open-source software package designed to perform meta-analysis and functional enrichment analysis of gene expression data. We incorporate standard methods for the meta-analysis of gene expression studies, bootstrap standard errors, corrections for multiple testing, and meta-analysis of multiple outcomes. Importantly, the MAGE toolkit includes additional features for the conversion of probes to gene identifiers, and for conducting functional enrichment analysis, with annotated results, of statistically significant enriched terms in several formats. Along with the tool itself, a web-based infrastructure was also developed to support the features of this package.

Association of ITPA gene polymorphisms with adverse effects of AZA/6-MP administration: a systematic review and meta-analysis.

Azathioprine (AZA) and its metabolite, mercaptopurine (6-MP), are widely used immunosuppressant drugs. Polymorphisms in genes implicated in AZA/6-MP metabolism, reportedly, could account in part for their potential toxicity. In the present study we performed a systematic review and a meta-analysis, comprising 30 studies and 3582 individuals, to investigate the putative genetic association of two inosine triphosphatase (ITPA) polymorphisms with adverse effects in patients treated with AZA/6-MP. We found that rs1127354 is associated with neutropenia in general populations and in children (OR: 2.39, 95%CI: 1.97-2.90, and OR: 2.43, 95%CI: 2.12-2.79, respectively), and with all adverse effects tested herein in adult populations (OR: 2.12, 95%CI: 1.22-3.69). We also found that rs7270101 is associated with neutropenia and leucopenia in all-ages populations (OR: 2.93, 95%CI: 2.36-3.63, and OR: 2.82, 95%CI: 1.76-4.50, respectively) and with all adverse effects tested herein in children (OR: 1.74, 95%CI: 1.06-2.87). Stratification according to background disease, in combination with multiple comparisons corrections, verified neutropenia to be associated with both polymorphisms, in acute lymphoblastic leukemia (ALL) patients. These findings suggest that ITPA polymorphisms could be used as predictive biomarkers for adverse effects of thiopurine drugs to eliminate intolerance in ALL patients and clarify dosing in patients with different ITPA variants.

Hidden neural networks for transmembrane protein topology prediction.

Hidden Markov Models (HMMs) are amongst the most successful methods for predicting protein features in biological sequence analysis. However, there are biological problems where the Markovian assumption is not sufficient since the sequence context can provide useful information for prediction purposes. Several extensions of HMMs have appeared in the literature in order to overcome their limitations. We apply here a hybrid method that combines HMMs and Neural Networks (NNs), termed Hidden Neural Networks (HNNs), for biological sequence analysis in a straightforward manner. In this framework, the traditional HMM probability parameters are replaced by NN outputs. As a case study, we focus on the topology prediction of for alpha-helical and beta-barrel membrane proteins. The HNNs show performance gains compared to standard HMMs and the respective predictors outperform the top-scoring methods in the field. The implementation of HNNs can be found in the package JUCHMME, downloadable from http://www.compgen.org/tools/juchmme, https://github.com/pbagos/juchmme. The updated PRED-TMBB2 and HMM-TM prediction servers can be accessed at www.compgen.org.

VICTOR: A visual analytics web application for comparing cluster sets.

Clustering is the process of grouping different data objects based on similar properties. Clustering has applications in various case studies from several fields such as graph theory, image analysis, pattern recognition, statistics and others. Nowadays, there are numerous algorithms and tools able to generate clustering results. However, different algorithms or parameterizations may produce quite dissimilar cluster sets. In this way, the user is often forced to manually filter and compare these results in order to decide which of them generate the ideal clusters. To automate this process, in this study, we present VICTOR, the first fully interactive and dependency-free visual analytics web application which allows the visual comparison of the results of various clustering algorithms. VICTOR can handle multiple cluster set results simultaneously and compare them using ten different metrics. Clustering results can be filtered and compared to each other with the use of data tables or interactive heatmaps, bar plots, correlation networks, sankey and circos plots. We demonstrate VICTOR's functionality using three examples. In the first case, we compare five different network clustering algorithms on a Yeast protein-protein interaction dataset whereas in the second example, we test four different parameters of the MCL clustering algorithm on the same dataset. Finally, as a third example, we compare four different meta-analyses with hierarchically clustered differentially expressed genes found to be involved in myocardial infarction. VICTOR is available at http://victor.pavlopouloslab.info or http://bib.fleming.gr:3838/VICTOR.

Urine-Based Molecular Diagnostic Tests for Leishmaniasis Infection in Human and Canine Populations: A Meta-Analysis.

Leishmaniasis is a neglected tropical disease affecting humans and domesticated animals with high mortality in endemic countries. The pleiotropy of symptoms and the complicated gold-standard methods make the need for non-invasive, highly sensitive diagnostic tests imperative. Individual studies on molecular-based Leishmania diagnosis in urine show high discrepancy; thus, a data-evidenced comparison of various techniques is necessary. We performed a systematic review and meta-analysis using the bivariate method of diagnostic methods to pool sensitivities and specificities. We investigated the impact of DNA-extraction method, PCR type, amplified locus, host species, leishmaniasis form, and geographical region. The pooled sensitivity was 69.2%. Tests performed with the kit-based DNA extraction method and qPCR outweighed in sensitivity the phenol-chloroform-based and PCR methods, while their combination showed a sensitivity of 79.3%. Amplified locus, human or canine as host and cutaneous or visceral leishmaniasis revealed similar sensitivities. Tests in European and Middle Eastern countries performed better than tests in other regions (sensitivity 81.7% vs. 43.7%). A combination of kit-based DNA extraction and qPCR could be a safer choice for molecular diagnosis for Leishmania infection in urine samples in European-Middle Eastern countries. For the rest of the world, more studies are needed to better characterize the endemic parasite species.

Smoking prevalence among hospitalized COVID-19 patients and its association with disease severity and mortality: an expanded re-analysis of a recent publication.

BACKGROUND: There is a lot of debate about the effects of smoking on COVID-19. A recent fixed-effects meta-analysis found smoking to be associated with disease severity among hospitalized patients, but other studies report an unusually low prevalence of smoking among hospitalized patients. The purpose of this study was to expand the analysis by calculating the prevalence odds ratio (POR) of smoking among hospitalized COVID-19 patients, while the association between smoking and disease severity and mortality was examined by random-effects meta-analyses considering the highly heterogeneous study populations. METHODS: The same studies as examined in the previous meta-analysis were analyzed (N = 22, 20 studies from China and 2 from USA). The POR relative to the expected smoking prevalence was calculated using gender and age-adjusted population smoking rates. Random-effects meta-analyses were used for all other associations. RESULTS: A total of 7162 patients were included, with 482 being smokers. The POR was 0.24 (95%CI 0.19-0.30). Unlike the original study, the association between smoking and disease severity was not statistically significant using random-effects meta-analysis (OR 1.40, 95%CI 0.98-1.98). In agreement with the original study, no statistically significant association was found between smoking and mortality (OR 1.86, 95%CI 0.88-3.94). CONCLUSION: An unusually low prevalence of smoking, approximately 1/4th the expected prevalence, was observed among hospitalized COVID-19 patients. Any association between smoking and COVID-19 severity cannot be generalized but should refer to the seemingly low proportion of smokers who develop severe COVID-19 that requires hospitalization. Smokers should be advised to quit due to long-term health risks, but pharmaceutical nicotine or other nicotinic cholinergic agonists should be explored as potential therapeutic options, based on a recently presented hypothesis.

Staphylococcus aureus Carriage in Hidradenitis Suppurativa: Impact on Response to Adalimumab.

BACKGROUND: Several patients with hidradenitis suppurativa (HS) present flare-ups during treatment with adalimumab (ADA), the cause of which is not clear. ADA is the only FDA-approved biologic for the therapy of moderate-to-severe HS. A previous study of our group has shown that Staphylococcus aureus stimulation of whole blood affects the production of human ß-defensin 2 and modulates HS severity. It is, therefore, hypothesized, that carriage of S. aureus may drive HS flare-ups. OBJECTIVE: To explore the association between carriage of S. aureus and loss of response to ADA. PATIENTS AND METHODS: Among patients with moderate-to-severe HS without carriage of S. aureus at start of treatment with ADA, we investigated for carriage of S. aureus from the nares when flare-ups occurred. Flare-ups were pre-defined as at least 25% increase of inflammatory lesions (sum of inflammatory nodules and abscesses) from baseline. Samplings were also done after completion of 12 weeks of ADA treatment from all patients who did not present flare-ups. Clinical response to ADA was assessed by the HS Clinical Response score (HiSCR). RESULTS: Thirty-nine patients were studied; 24 with Hurley II stage HS and 15 with Hurley III stage HS. Twenty-nine patients achieved HiSCR after 12 weeks of treatment without any flare-ups; 10 patients had flare-ups and failed HiSCR. Three (10.3%) and 5 (50%) patients, respectively, had nasal carriage of S. aureus (odds ratio 8.67; 95% CI 1.54-48.49; p = 0.014). Among 32 patients reaching follow-up week 48, 20 patients achieved HiSCR and 12 had flare-ups leading to ADA failure; 2 (10%) and 5 (41.7%) patients, respectively, had positive culture for S. aureus (odds ratio 6.42; 95% CI 1.00-41.20; p = 0.05). CONCLUSION: Nasal carriage of S. aureus may be associated with loss of response to ADA. Findings need confirmation in larger series of patients.

OMPdb: A Global Hub of Beta-Barrel Outer Membrane Proteins.

OMPdb (www.ompdb.org) was introduced as a database for ß-barrel outer membrane proteins from Gram-negative bacteria in 2011 and then included 69,354 entries classified into 85 families. The database has been updated continuously using a collection of characteristic profile Hidden Markov Models able to discriminate between the different families of prokaryotic transmembrane ß-barrels. The number of families has increased ultimately to a total of 129 families in the current, second major version of OMPdb. New additions have been made in parallel with efforts to update existing families and add novel families. Here, we present the upgrade of OMPdb, which from now on aims to become a global repository for all transmembrane ß-barrel proteins, both eukaryotic and bacterial.

Improved strategies to counter the COVID-19 pandemic: Lockdowns vs. primary and community healthcare.

COVID-19 pandemic mitigation strategies are mainly based on social distancing measures and healthcare system reinforcement. However, many countries in Europe and elsewhere implemented strict, horizontal lockdowns because of extensive viral spread in the community which challenges the capacity of the healthcare systems. However, strict lockdowns have various untintended adverse social, economic and health effects, which have yet to be fully elucidated, and have not been considered in models examining the effects of various mitigation measures. Unlike commonly suggested, the dilemma is not about health vs wealth because the economic devastation of long-lasting lockdowns will definitely have adverse health effects in the population. Furthermore, they cannot provide a lasting solution in pandemic containment, potentially resulting in a vicious cycle of consecutive lockdowns with in-between breaks. Hospital preparedness has been the main strategy used by governments. However, a major characteristic of the COVID-19 pandemic is the rapid viral transmission in populations with no immunity. Thus, even the best hospital system could not cope with the demand. Primary, community and home care are the only viable strategies that could achieve the goal of pandemic mitigation. We present the case example of Greece, a country which followed a strategy focused on hospital preparedness but failed to reinforce primary and community care. This, along with strategic mistakes in epidemiological surveillance, resulted in Greece implementing a second strict, horizontal lockdown and having one of the highest COVID-19 death rates in Europe during the second wave. We provide recommendations for measures that will reinstate primary and community care at the forefront in managing the current public health crisis by protecting hospitals from unnecessary admissions, providing primary and secondary prevention services in relation to COVID-19 and maintaining population health through treatment of non-COVID-19 conditions. This, together with more selective social distancing measures (instead of horizontal lockdowns), represents the only viable and realistic long-term strategy for COVID-19 pandemic mitigation.