Chatbots and messaging platforms in the classroom: An analysis from the teacher's perspective.

Messaging platforms are applications, generally mediated by an app, desktop program or the web, mainly used for synchronous communication among users. As such, they have been widely adopted officially by higher education establishments, after little or no study of their impact and perception by the teachers. We think that the introduction of these new tools and the opportunities and challenges they have needs to be studied carefully in order to adopt the model, as well as the tool, that is the most adequate for all parties involved. We already studied the perception of these tools by students, in this paper we examine the teachers' experiences and perceptions through a survey that we validated with peers, and what they think these tools should make or serve so that it enhances students learning and helps them achieve their learning objectives. The survey has been distributed among tertiary education teachers, both in universitary and other kind of tertiary establishments, based in Spain (mainly) and Spanish-speaking countries. We have focused on collecting teachers' preferences and opinions on the introduction of messaging platforms in their day-to-day work, as well as other services attached to them, such as chatbots. What we intend with this survey is to understand their needs and to gather information about the various educational use cases where these tools could be valuable. In addition, an analysis of how and when teachers' opinions towards the use of these tools varies across gender, experience, and their discipline of specialization is presented. The key findings of this study highlight the factors that can contribute to the advancement of the adoption of messaging platforms and chatbots in higher education institutions to achieve the desired learning outcomes.

PDGFD switches on stem cell endothelial commitment.

The critical factors regulating stem cell endothelial commitment and renewal remain not well understood. Here, using loss- and gain-of-function assays together with bioinformatic analysis and multiple model systems, we show that PDGFD is an essential factor that switches on endothelial commitment of embryonic stem cells (ESCs). PDGFD genetic deletion or knockdown inhibits ESC differentiation into EC lineage and increases ESC self-renewal, and PDGFD overexpression activates ESC differentiation towards ECs. RNA sequencing reveals a critical requirement of PDGFD for the expression of vascular-differentiation related genes in ESCs. Importantly, PDGFD genetic deletion or knockdown increases ESC self-renewal and decreases blood vessel densities in both embryonic and neonatal mice and in teratomas. Mechanistically, we reveal that PDGFD fulfills this function via the MAPK/ERK pathway. Our findings provide new insight of PDGFD as a novel regulator of ESC fate determination, and suggest therapeutic implications of modulating PDGFD activity in stem cell therapy.

Gene set analysis methods for the functional interpretation of non-mRNA data-Genomic range and ncRNA data.

Gene set analysis (GSA) is one of the methods of choice for analyzing the results of current omics studies; however, it has been mainly developed to analyze mRNA (microarray, RNA-Seq) data. The following review includes an update regarding general methods and resources for GSA and then emphasizes GSA methods and tools for non-mRNA omics datasets, specifically genomic range data (ChIP-Seq, SNP and methylation) and ncRNA data (miRNAs, lncRNAs and others). In the end, the state of the GSA field for non-mRNA datasets is discussed, and some current challenges and trends are highlighted, especially the use of network approaches to face complexity issues.

Popularity and performance of bioinformatics software: the case of gene set analysis.

BACKGROUND: Gene Set Analysis (GSA) is arguably the method of choice for the functional interpretation of omics results. The following paper explores the popularity and the performance of all the GSA methodologies and software published during the 20 years since its inception. "Popularity" is estimated according to each paper's citation counts, while "performance" is based on a comprehensive evaluation of the validation strategies used by papers in the field, as well as the consolidated results from the existing benchmark studies. RESULTS: Regarding popularity, data is collected into an online open database ("GSARefDB") which allows browsing bibliographic and method-descriptive information from 503 GSA paper references; regarding performance, we introduce a repository of jupyter workflows and shiny apps for automated benchmarking of GSA methods ("GSA-BenchmarKING"). After comparing popularity versus performance, results show discrepancies between the most popular and the best performing GSA methods. CONCLUSIONS: The above-mentioned results call our attention towards the nature of the tool selection procedures followed by researchers and raise doubts regarding the quality of the functional interpretation of biological datasets in current biomedical studies. Suggestions for the future of the functional interpretation field are made, including strategies for education and discussion of GSA tools, better validation and benchmarking practices, reproducibility, and functional re-analysis of previously reported data.

Treatment of Persons with Multiple Myeloma in Underprivileged Circumstances: Real-World Data from a Single Institution.

BACKGROUND: The treatment of patients with multiple myeloma (MM) has evolved in recent years, and the disease-associated prognosis has improved substantially. This improvement has been driven largely by the approval of novel agents, many of which are expensive and not universally available. Less expensive but effective approaches would be of value globally. PATIENTS AND METHODS: All consecutive MM patients diagnosed in the Centro de Hematología y Medicina Interna de Puebla after 1993 were included in this study. Patients were given oral thalidomide (100 mg/day), oral dexamethasone (36-40 mg/week), and aspirin 100 mg/day. Bor-tezomib (1.75 mg s.c. every week) was administered to those who could afford it. After 4-6 weeks of treatment, patients were offered an outpatient-based hematopoietic cell transplant (HCT). After the recovery of granulocytes following HCT, patients continued indefinitely on thalidomide; those who failed to tolerate thalidomide were switched to lenalidomide (25 mg/day). RESULTS: The median overall survival (OS) for all patients has not been reached and is >157 months. Median follow-up of the patients lasted 14 months (range 1.3-157). The median OS of patients with and without HCT was similar. The response rate (complete remission or very good partial remission) was 72% for those given thalidomide plus dexamethasone versus 88% for those given bortezomib, thalidomide, and dexamethasone before HCT, but OS was not different. As post-HCT maintenance, 37 patients received thalidomide; 26 of those (70%) could be maintained indefinitely on thalidomide, whereas 11 were switched to lenalidomide after a median of 7 months; median OS of patients maintained on thalidomide or lenalidomide after HCT was not different. CONCLUSION: In this series, a regimen incorporating low-cost novel agents and outpatient HCT was associated with excellent long-term survival in the treatment of MM patients. This approach may be a model for MM treatment in underprivileged circumstances.

[Effect of influenza vaccination in Primary Healthcare workers and the general population in Gran Canaria: A cross-sectional study]. / Efecto de la vacunación antigripal en trabajadores de atención primaria y población general de Gran Canaria: estudio transversal.

OBJECTIVE: To estimate the effect of the influenza vaccination in Primary Healthcare workers and the general population vaccinated during the 2015/2016 campaign. DESIGN: Cross-sectional study. SETTING: All the Primary Healthcare centres within the Gran Canaria healthcare region. PARTICIPANTS: A total of 1,868 Primary Healthcare workers (33.5% men; 66.5% women) and 795,605 individuals from the general population (49.4% men; 50.6% women). PRINCIPAL MEASUREMENTS: The outcome variables in Primary Healthcare workers were: influenza cases reported to the Epidemiological Surveillance System, and the sick leave days due to illness. In the general population: reported flu cases and vaccination coverage in connection with the vaccination status of the healthcare professional. The magnitude of association between vaccination and morbidity was estimated applying logistic regression models. RESULTS: Although not statistically significant, healthcare professionals that were not vaccinated had 1.7-fold increase in the risk of having influenza than those vaccinated. In the general population the association was significant in the female population (OR: 1.3; 95%CI: 1.1-1.5). Population coverage was significantly higher when both the doctor and nurse were vaccinated (OR: 1.3; 95%CI: 1.3-1.3), and reported flu cases decreased when the nurse was vaccinated (OR: 0.9; 95%CI: 0.9-0.9). CONCLUSION: A possible protective effect of influenza vaccination was observed in the general population, as well as an influence of Primary Healthcare workers on the patients regarding this. Even so, the low coverages registered point to a need to implement measures that may lead to a more favourable attitude towards influenza vaccination.

In the loop: promoter-enhancer interactions and bioinformatics.

Enhancer-promoter regulation is a fundamental mechanism underlying differential transcriptional regulation. Spatial chromatin organization brings remote enhancers in contact with target promoters in cis to regulate gene expression. There is considerable evidence for promoter-enhancer interactions (PEIs). In the recent years, genome-wide analyses have identified signatures and mapped novel enhancers; however, being able to precisely identify their target gene(s) requires massive biological and bioinformatics efforts. In this review, we give a short overview of the chromatin landscape and transcriptional regulation. We discuss some key concepts and problems related to chromatin interaction detection technologies, and emerging knowledge from genome-wide chromatin interaction data sets. Then, we critically review different types of bioinformatics analysis methods and tools related to representation and visualization of PEI data, raw data processing and PEI prediction. Lastly, we provide specific examples of how PEIs have been used to elucidate a functional role of non-coding single-nucleotide polymorphisms. The topic is at the forefront of epigenetic research, and by highlighting some future bioinformatics challenges in the field, this review provides a comprehensive background for future PEI studies.

The effect of high-volume online haemodiafiltration on nutritional status and body composition: the ProtEin Stores prEservaTion (PESET) study.

Background: Compared with conventional haemodialysis (HD), online haemodiafiltration (OL-HDF) achieves a more efficient removal of uraemic toxins and reduces inflammation, which could favourably affect nutritional status. We evaluate the effect of OL-HDF on body composition and nutritional status in prevalent high-flux HD (HF-HD) patients. Methods: In all, 33 adults with chronic kidney disease (CKD) Stage 5 undergoing maintenance HF-HD were assigned to post-dilution OL-HDF (n = 17) or to remain on HF-HD (n = 16, control group) for 12 months. The primary outcome was the change in lean tissue mass (LTM), intracellular water (ICW) and body cell mass (BCM) assessed by multifrequency bioimpedance spectroscopy (BIS) at baseline and 4, 8 and 12 months. The rate of change in these parameters was estimated with linear mixed-effects models. Results: Compared with OL-HDF, patients assigned to HF-HD experienced a gradual reduction in LTM, ICW and BCM. These differences reached statistical significance at Month 12, with a relative difference of 7.31 kg [95% confidence interval (CI) 2.50-12.11; P = 0.003], 2.32 L (95% CI 0.63-4.01; P = 0.008) and 5.20 kg (95% CI 1.74-8.66; P = 0.004) for LTM, ICW and BCM, respectively. The normalized protein appearance increased in the OL-HDF group compared with the HF-HD group [0.26 g/kg/day (95% CI 0.05-0.47); P = 0.002], with a relative reduction in high-sensitive C-reactive protein [-13.31 mg/dL (95% CI -24.63 to -1.98); P = 0.02] at Month 12. Conclusions: OL-HDF for 1 year compared with HF-HD preserved muscle mass, increased protein intake and reduced the inflammatory state related to uraemia and dialysis, supporting the hypothesis that high convection volume can benefit nutritional status and prevent protein-energy wasting in HD patients.

A novel representation of genomic sequences for taxonomic clustering and visualization by means of self-organizing maps.

MOTIVATION: Self-organizing maps (SOMs) are readily available bioinformatics methods for clustering and visualizing high-dimensional data, provided that such biological information is previously transformed to fixed-size, metric-based vectors. To increase the usefulness of SOM-based approaches for the analysis of genomic sequence data, novel representation methods are required that automatically and objectively transform aligned nucleotide sequences into numeric vectors, dealing with both nucleotide ambiguity and gaps derived from sequence alignment. RESULTS: Six different codification variants based on Euclidean space, just like SOM processing, have been tested using two SOM models: the classical Kohonen's SOM and growing cell structures. They have been applied to two different sets of sequences: 32 sequences of small sub-unit ribosomal RNA from organisms belonging to the three domains of life, and 44 sequences of the reverse transcriptase region of the pol gene of human immunodeficiency virus type 1 belonging to different groups and sub-types. Our results show that the most important factor affecting the accuracy of sequence clustering is the assignment of an extra weight to the presence of alignment-derived gaps. Although each of the codification variants shows a different level of taxonomic consistency, the results are in agreement with sequence-based phylogenetic reconstructions and anticipate a broad applicability of this codification method.

[Trauma Injuries Associated with Rope Bullfights in the Azores: A Cross-Sectional Study]. / Trauma Associado às Touradas à Corda nos Açores: Um Estudo Transversal.

INTRODUCTION: The aim of the study was to describe trauma injuries associated with rope bullfights in the Azores, Portugal, regarding the cause of the incident, trauma mechanism, most affected anatomical areas, and injury severity. METHODS: Two-year cross-sectional study in the local hospital with prospective data collection. Patients who were consecutively admitted to the local hospital's emergency department with trauma injuries from the bull's direct impact or from falls either during the bull's escape or when handling the rope, were included. Data on general demographics, lesion characteristics, treatments, need for hospitalization and mortality were collected. RESULTS: Fifty-six incidents and 80 trauma injuries were identified. The main cause of trauma was the bull's direct impact (37; 66.07%) and the mechanism of injury was blunt trauma in all patients (100%; 56). Head and neck injuries (27; 33.75%) were the most common. The median Injury Severity Score at the emergency department admission was 4. Major trauma was noted in five patients (8.92%). Ten patients (17.85%) needed hospitalization with a median hospital stay of seven days. Three of the 10 hospitalized patients (30%) were previously admitted to the intensive care unit. Surgery was performed in six patients (10.71%). CONCLUSION: The main cause of trauma was the bull's direct impact, and the mechanism of injury was blunt trauma. The most affected anatomical areas were the head and neck. These findings are a wake-up call to the impact of these events regarding the economic costs they entail, the costs for the health of the local population, the safety measures currently implemented and the availability of the necessary means to treat these patients.

Introdução: O objetivo deste estudo foi caracterizar as lesões traumáticas tauromáquicas ocorridas nas touradas à corda nos Açores no que diz respeito à causa do incidente, mecanismo de trauma, área anatómica mais afetada e gravidade das lesões. Métodos: Estudo unicêntrico, transversal, com a colheita prospetiva de dados realizada durante dois anos. Foram incluídos os doentes que consecutivamente recorreram ao serviço de urgência do hospital local por lesões traumáticas ocorridas por trauma direto com o animal ou quedas aquando da fuga ou manuseio da corda. Foram colhidos dados demográficos gerais, características da lesão, tratamentos efetuados, necessidade de internamento hospitalar e mortalidade. Foi realizada uma análise estatística descritiva com recurso ao software estatístico SPSS. Resultados: Registaram-se 56 admissões hospitalares e 80 lesões traumáticas. A principal causa de traumatismo foi o trauma direto com o animal (37; 66,07%) e o mecanismo de lesão foi o trauma fechado (56; 100%). As áreas anatómicas mais afetadas foram a cabeça e pescoço (27; 33,75%). A mediana de Injury Severity Score foi de 4 à admissão hospitalar. Cinco doentes (8,92%) apresentaram trauma major. Dez doentes (17,85%) necessitaram de internamento hospitalar com uma mediana de dias de internamento de sete (IIQ 4,5 dias). Três (30%) dos doentes internados necessitaram de internamento em unidade de cuidados intensivos. Seis doentes (10,71%) foram submetidos a cirurgia. Conclusão: A principal causa de traumatismo foi o trauma direto com o animal e o mecanismo de lesão foi o trauma fechado. As áreas anatómicas mais afetadas foram a cabeça e pescoço. Estes dados constituem um alerta para o impacto destes eventos no que diz respeito aos custos económicos que acarretam, aos custos para a saúde da população local, às medidas de segurança atualmente implementadas e à disponibilidade dos meios necessários para tratar estes doentes.

Community Care Needs of Highly Complex Chronic Patients: An Epidemiological Study in a Healthcare Area.

One of the priorities in family and community care is the epidemiological surveillance of the care needs and dysfunctionality present in populations of highly complex chronic patients (HCCPs) using standardised nursing languages. The aim of this study is to establish the prevalence of care needs and dysfunctionality among HCCPs in a specific health area by municipalities and geographical areas (metropolitan, north, and south) while verifying correlations with sociodemographic, financial, and health characteristics. This is an epidemiological, observational, descriptive, cross-sectional study carried out with a sample of 51,374 HCCPs, whose data were grouped into 31 municipalities. Data were collected on the following variables: sociodemographic, financial, health, functional status (health patterns), and care needs (nursing diagnoses). The mean age of the HCCPs was 73.41 (1.45) years, of which 56.18 (2.86)% were women. The municipalities in the northern area have a significantly higher proportion of older patients, HCCPs, lower incomes, and higher unemployment rates. The southern area had higher proportions of non-Spanish nationals and professionals in the hotel and catering industry, and the metropolitan area had a higher proportion of employed individuals and higher levels of education. Northern municipalities had a higher prevalence of illnesses and anxiolytic and anti-psychotic treatments. Dysfunctionality frequencies did not differ significantly by area. However, a higher prevalence of 13 nursing diagnoses was observed in the north. A high number of correlations were observed between population characteristics, dysfunctionality, and prevalent diagnoses. Finally, the frequencies of dysfunctionality in the population and the most common care needs were mapped by municipality. This research sought to ascertain whether there was an unequal distribution of these two aspects among HCCPs in order to gain a deeper epidemiological understanding of them from a family and community perspective using standardised nursing languages. This study was not registered.

A survey of protein interaction data and multigenic inherited disorders.

BACKGROUND: Multigenic diseases are often associated with protein complexes or interactions involved in the same pathway. We wanted to estimate to what extent this is true given a consolidated protein interaction data set. The study stresses data integration and data representation issues. RESULTS: We constructed 497 multigenic disease groups from OMIM and tested for overlaps with interaction and pathway data. A total of 159 disease groups had significant overlaps with protein interaction data consolidated by iRefIndex. A further 68 disease overlaps were found only in the KEGG pathway database. No single database contained all significant overlaps thus stressing the importance of data integration. We also found that disease groups overlapped with all three interaction data types: n-ary, spoke-represented complexes and binary data - thus stressing the importance of considering each of these data types separately. CONCLUSIONS: Almost half of our multigenic disease groups could potentially be explained by protein complexes and pathways. However, the fact that no database or data type was able to cover all disease groups suggests that no single database has systematically covered all disease groups for potential related complex and pathway data. This survey provides a basis for further curation efforts to confirm and search for overlaps between diseases and interaction data. The accompanying R script can be used to reproduce the work and track progress in this area as databases change. Disease group overlaps can be further explored using the iRefscape plugin for Cytoscape.

A Comparison of Cell-Cell Interaction Prediction Tools Based on scRNA-seq Data.

Computational prediction of cell-cell interactions (CCIs) is becoming increasingly important for understanding disease development and progression. We present a benchmark study of available CCI prediction tools based on single-cell RNA sequencing (scRNA-seq) data. By comparing prediction outputs with a manually curated gold standard for idiopathic pulmonary fibrosis (IPF), we evaluated prediction performance and processing time of several CCI prediction tools, including CCInx, CellChat, CellPhoneDB, iTALK, NATMI, scMLnet, SingleCellSignalR, and an ensemble of tools. According to our results, CellPhoneDB and NATMI are the best performer CCI prediction tools, among the ones analyzed, when we define a CCI as a source-target-ligand-receptor tetrad. In addition, we recommend specific tools according to different types of research projects and discuss the possible future paths in the field.

PDGF-D-induced immunoproteasome activation and cell-cell interactions.

Platelet-derived growth factor-D (PDGF-D) is abundantly expressed in ocular diseases. Yet, it remains unknown whether and how PDGF-D affects ocular cells or cell-cell interactions in the eye. In this study, using single-cell RNA sequencing (scRNA-seq) and a mouse model of PDGF-D overexpression in retinal pigment epithelial (RPE) cells, we found that PDGF-D overexpression markedly upregulated the key immunoproteasome genes, leading to increased antigen processing/presentation capacity of RPE cells. Also, more than 6.5-fold ligand-receptor pairs were found in the PDGF-D overexpressing RPE-choroid tissues, suggesting markedly increased cell-cell interactions. Moreover, in the PDGF-D-overexpressing tissues, a unique cell population with a transcriptomic profile of both stromal cells and antigen-presenting RPE cells was detected, suggesting PDGF-D-induced epithelial-mesenchymal transition of RPE cells. Importantly, administration of ONX-0914, an immunoproteasome inhibitor, suppressed choroidal neovascularization (CNV) in a mouse CNV model in vivo. Together, we show that overexpression of PDGF-D increased pro-angiogenic immunoproteasome activities, and inhibiting immunoproteasome pathway may have therapeutic value for the treatment of neovascular diseases.

Epidemiological study of vaccination against SARS-CoV-2 and its impact on COVID-19 progression in a cohort of patients in gran Canaria.

Objectives. We analyzed the impact of age, sex, vaccination against COVID-19, immunosuppressive treatment, and comorbidities on patients' risk of requiring hospital admission or of death. Methods. Population-based observational retrospective study conducted on a cohort of 19,850 patients aged 12 years or more, who were diagnosed with COVID-19 between June 1st and December 31st, 2021, in the island of Gran Canaria. Results. Hypertension (18.5%), asthma (12.8%) and diabetes (7.2%) were the most frequent comorbidities; 147 patients died (0.7%). The combination of advanced age, male sex, cancer, coronary heart disease, immunosuppressive treatment, hospital admission, admission to the intensive care unit, mechanical ventilation and lack of complete COVID-19 vaccination or booster dose was strongly predictive of mortality (p < 0.05); 831 patients required hospital admission and it was more frequent in men, older age groups, and patients with cancer, diabetes, arterial hypertension, chronic obstructive pulmonary disease, congestive heart failure or immunosuppressive treatment. The COVID-19 vaccine booster dose was associated with a lower risk of death ([OR] 0.11, 95% CI 0.06-0.21, p < 0.05) or hospital admission ([OR] 0.36, 95% CI 0.29-0.46, p < 0.05). Conclusions. Cancer, coronary heart disease, and immunosuppressive treatment were associated with increased COVID-19 mortality. More complete vaccination was associated with lower risk of hospital admission or death. Three doses of the SARS-CoV-2 vaccine were highly associated with the prevention of death and hospital admission in all age groups. These findings suggest that COVID-19 vaccination can help bring the pandemic under control.

Objetivos. Analizamos el impacto de la edad, el sexo, la vacunación frente a la COVID-19, el tratamiento inmunosupresor y las comorbilidades en el riesgo de los pacientes de precisar ingreso hospitalario o de fallecer.Métodos. Estudio retrospectivo observacional de base poblacional realizado sobre una cohorte de 19.850 pacientes de 12 años o más, que fueron diagnosticados de COVID-19 entre el 1 de junio y el 31 de diciembre de 2021, en la isla de Gran Canaria.Resultados. La hipertensión arterial (18,5%), el asma (12,8%) y la diabetes (7,2%) fueron las comorbilidades más frecuentes; Fallecieron 147 pacientes (0,7%). La combinación de edad avanzada, sexo masculino, cáncer, cardiopatía coronaria, tratamiento inmunosupresor, ingreso hospitalario, ingreso en unidad de cuidados intensivos, ventilación mecánica y la falta de vacunación completa contra el COVID-19 o dosis de refuerzo fue fuertemente predictiva de mortalidad (p < 0,05); 831 pacientes requirieron ingreso hospitalario y fue más frecuente en hombres, grupos de mayor edad y pacientes con cáncer, diabetes, hipertensión arterial, enfermedad pulmonar obstructiva crónica, insuficiencia cardiaca congestiva o tratamiento inmunosupresor. La dosis de refuerzo contra la vacuna del COVID-19 se asoció con un menor riesgo de muerte ([OR] 0.11, IC 95% 0.06­0.21, p < 0,05) o ingreso hospitalario ([OR] 0.36, IC 95% 0.29­0.46; p < 0,05).Conclusiones. El cáncer, la enfermedad coronaria y el tratamiento inmunosupresor se asociaron con una mayor mortalidad por COVID-19. Una vacunación más completa se asoció con un menor riesgo de hospitalización o muerte. Tres dosis de la vacuna contra el SARS-CoV-2 se asociaron a una mayor prevención de la muerte y el ingreso hospitalario relacionados con la COVID-19 en todos los grupos de edad. Estos hallazgos sugieren que la vacunación contra el COVID-19 puede ayudar a controlar la pandemia.

VEGF-B prevents excessive angiogenesis by inhibiting FGF2/FGFR1 pathway.

Although VEGF-B was discovered as a VEGF-A homolog a long time ago, the angiogenic effect of VEGF-B remains poorly understood with limited and diverse findings from different groups. Notwithstanding, drugs that inhibit VEGF-B together with other VEGF family members are being used to treat patients with various neovascular diseases. It is therefore critical to have a better understanding of the angiogenic effect of VEGF-B and the underlying mechanisms. Using comprehensive in vitro and in vivo methods and models, we reveal here for the first time an unexpected and surprising function of VEGF-B as an endogenous inhibitor of angiogenesis by inhibiting the FGF2/FGFR1 pathway when the latter is abundantly expressed. Mechanistically, we unveil that VEGF-B binds to FGFR1, induces FGFR1/VEGFR1 complex formation, and suppresses FGF2-induced Erk activation, and inhibits FGF2-driven angiogenesis and tumor growth. Our work uncovers a previously unrecognized novel function of VEGF-B in tethering the FGF2/FGFR1 pathway. Given the anti-angiogenic nature of VEGF-B under conditions of high FGF2/FGFR1 levels, caution is warranted when modulating VEGF-B activity to treat neovascular diseases.

Effects of protein interaction data integration, representation and reliability on the use of network properties for drug target prediction.

BACKGROUND: Previous studies have noted that drug targets appear to be associated with higher-degree or higher-centrality proteins in interaction networks. These studies explicitly or tacitly make choices of different source databases, data integration strategies, representation of proteins and complexes, and data reliability assumptions. Here we examined how the use of different data integration and representation techniques, or different notions of reliability, may affect the efficacy of degree and centrality as features in drug target prediction. RESULTS: Fifty percent of drug targets have a degree of less than nine, and ninety-five percent have a degree of less than ninety. We found that drug targets are over-represented in higher degree bins - this relationship is only seen for the consolidated interactome and it is not dependent on n-ary interaction data or its representation. Degree acts as a weak predictive feature for drug-target status and using more reliable subsets of the data does not increase this performance. However, performance does increase if only cancer-related drug targets are considered. We also note that a protein's membership in pathway records can act as a predictive feature that is better than degree and that high-centrality may be an indicator of a drug that is more likely to be withdrawn. CONCLUSIONS: These results show that protein interaction data integration and cleaning is an important consideration when incorporating network properties as predictive features for drug-target status. The provided scripts and data sets offer a starting point for further studies and cross-comparison of methods.

Chromatin Hubs: A biological and computational outlook.

This review discusses our current understanding of chromatin biology and bioinformatics under the unifying concept of "chromatin hubs." The first part reviews the biology of chromatin hubs, including chromatin-chromatin interaction hubs, chromatin hubs at the nuclear periphery, hubs around macromolecules such as RNA polymerase or lncRNAs, and hubs around nuclear bodies such as the nucleolus or nuclear speckles. The second part reviews existing computational methods, including enhancer-promoter interaction prediction, network analysis, chromatin domain callers, transcription factory predictors, and multi-way interaction analysis. We introduce an integrated model that makes sense of the existing evidence. Understanding chromatin hubs may allow us (i) to explain long-unsolved biological questions such as interaction specificity and redundancy of mechanisms, (ii) to develop more realistic kinetic and functional predictions, and (iii) to explain the etiology of genomic disease.

GSA Central-A web platform to perform, learn, and discuss gene set analysis.

Gene Set Analysis (GSA) is one of the most commonly used strategies to analyze omics data. Hundreds of GSA-related papers have been published, giving birth to a GSA field in Bioinformatics studies. However, as the field grows, it is becoming more difficult to obtain a clear view of all available methods, resources, and their quality. In this paper, we introduce a web platform called "GSA Central" which, as its name indicates, acts as a focal point to centralize GSA information and tools useful to beginners, average users, and experts in the GSA field. "GSA Central" contains five different resources: A Galaxy instance containing GSA tools ("Galaxy-GSA"), a portal to educational material ("GSA Classroom"), a comprehensive database of articles ("GSARefDB"), a set of benchmarking tools ("GSA BenchmarKING"), and a blog ("GSA Blog"). We expect that "GSA Central" will become a useful resource for users looking for introductory learning, state-of-the-art updates, method/tool selection guidelines and insights, tool usage, tool integration under a Galaxy environment, tool design, and tool validation/benchmarking. Moreover, we expect this kind of platform to become an example of a "thematic platform" containing all the resources that people in the field might need, an approach that could be extended to other bioinformatics topics or scientific fields.

Assessment of SARS-CoV-2 Infection According to Previous Metabolic Status and Its Association with Mortality and Post-Acute COVID-19.

Background. SARS-CoV-2 infection was analyzed according to previous metabolic status and its association with mortality and post-acute COVID-19. Methods. A population-based observational retrospective study was conducted on a cohort of 110,726 patients aged 12 years or more who were diagnosed with COVID-19 infection between June 1st, 2021, and 28 February 2022 on the island of Gran Canaria, Spain. Results. In the 347 patients who died, the combination of advanced age, male sex, cancer, immunosuppressive therapy, coronary heart disease, elevated total cholesterol and reduced high-density lipoprotein cholesterol (HDL-C) was strongly predictive of mortality (p < 0.05). In the 555 patients who developed post-acute COVID-19, the persistence of symptoms was most frequent in women, older subjects and patients with obstructive sleep apnea syndrome, asthma, elevated fasting glucose levels or elevated total cholesterol (p < 0.05). A complete vaccination schedule was associated with lower mortality (incidence rate ratio (IRR) 0.5, 95%CI 0.39−0.64; p < 0.05) and post-acute COVID-19 (IRR 0.37, 95%CI 0.31−0.44; p < 0.05). Conclusions. Elevated HDL-C and elevated total cholesterol were significantly associated with COVID-19 mortality. Elevated fasting glucose levels and elevated total cholesterol were risk factors for the development of post-acute COVID-19.