PepServe: a web server for peptide analysis, clustering and visualization

Peptides, either as protein fragments or as naturally occurring entities are characterized by their sequence and function features. Many times the researchers need to massively manage peptide lists concerning protein identification, biomarker discovery, bioactivity, immune response or other functionalities. We present a web server that manages peptide lists in terms of feature analysis as well as interactive clustering and visualization of the given peptides. PepServe is a useful tool in the understanding of the peptide feature distribution among a group of peptides. The PepServe web application is freely available at http://bioserver-1.bioacademy.gr/Bioserver/PepServe/

Technical evaluation of the mEducator 3.0 linked data-based environment for sharing medical educational resources

mEducator 3.0 is a content sharing approach for medical education, based on Linked Data principles. Through standardization, it enables sharing and discovery of medical information. Overall the mEducator project seeks to address the following two different approaches, mEducator 2.0, based on web 2.0 and ad-hoc Application Programmers Interfaces (APIs), and mEducator 3.0, which builds upon a collection of Semantic Web Services that federate existing sources of medical and Technology Enhanced Learning (TEL) data. The semantic mEducator 3.0 approach It has a number of different instantiations, allowing flexibility and choice. At present these comprise of a standalone social web-based instantiation (MetaMorphosis+) and instantiations integrated with Drupal, Moodle and OpenLabyrinth systems. This paper presents the evaluation results of the mEducator 3.0 Linked Data based environment for sharing medical educational resources and focuses on metadata enrichment, conformance to the requirements and technical performance (of the MetaMorphosis+ and Drupal instantiations)

MiRNAs expression pattern and machine learning models elucidate risk for gastric GIST

BACKGROUND: Gatrointestinal stromal tumors (GISTs) are the main mesenchymal tumors found in the gastrointestinal system. GISTs clinical phenotypes differ significantly and their molecular basis is not yet completely known. microRNAs (miRNAs) have been involved in carcinogenesis pathways by regulating gene expression at post-transcriptional level. OBJECTIVE: The aim of the present study was to elucidate the expression profiles of miRNAs relevant to gastric GIST carcinogenesis, and to identify miRNA signatures that can discriminate the GIST from normal cases. METHODS: miRNA expression was tested by miScript™miRNA PCR Array Human Cancer PathwayFinder kit and then we used machine learning in order to find a miRNA profile that can predict the risk for GIST development. RESULTS: A number of miRNAs were found to be differentially expressed in GIST cases compared to healthy controls. Among them the hsa-miR-218-5p was found to be the best predictor for GIST development in our cohort. Additionally, hsa-miR-146a-5p, hsa-miR-222-3p, and hsa-miR-126-3p exhibit significantly lower expression in GIST cases compared to controls and were among the top predictors in all our predictive models. CONCLUSIONS: A machine learning classification approach may be accurate in determining the risk for GIST development in patients. Our findings indicate that a small number of miRNAs, with hsa-miR218-5p as a focus, may strongly affect the prognosis of GISTs. © 2022 - IOS Press. All rights reserved

B-cell activating factor (BAFF) expression is associated with Crohn's disease and can serve as a potential prognostic indicator of disease response to Infliximab treatment

Background: Several studies correlated elevated B-cell activating factor (BAFF) levels and its polymorphisms (SNPs) in patients with autoimmunity. Limited data existed regarding the role of BAFF in Crohn's Disease (CD) susceptibility and/or treatment response to infliximab. Aim: This study aims to evaluate BAFF expression in CD patients, investigate if its expression can predict response to infliximab treatment, and examine the association of BAFF SNPs with CD susceptibility. Methods: One hundred twelve CD patients and 164 healthy controls were recruited. Serum BAFF levels were determined using an enzyme-linked immunosorbent assay. Participants were genotyped for rs9514828, rs1041569 and rs2893321 SNPs. Results: Serum BAFF concentration was elevated in CD patients (472.86 ± 223.60 pg/ml) compared with controls (128.16 ± 70.10 pg/ml) before treatment. Responders to IFX treatment had increased serum BAFF levels at baseline (610.03 ± 167.55 pg/ml) compared to non-responders (267.09 ± 107 pg/ml). In responders, BAFF concentration reduced after IFX administration, while increased in non-responders. The rs1041569, TA and AA genotypes frequencies, and the minor allele A were increased significantly in CD patients, indicating an association of the SNP with CD susceptibility. Conclusions: Our study suggests that BAFF could be a potential biomarker of CD, while SNP rs1041569 was associated with CD susceptibility. © 2020 Editrice Gastroenterologica Italiana S.r.l

Differential genetic and functional background in inflammatory bowel disease phenotypes of a Greek population: A systems bioinformatics approach

Background: Crohn's disease (CD) and Ulcerative colitis (UC) are the two main entities of inflammatory bowel disease (IBD). Previous works have identified more than 200 risk factors (including loci and signaling pathways) in populations of predominantly European ancestry. Our study was conducted on an extended population-specific cohort of 573 Greek IBD patients (364 CD and 209 UC) and 445 controls. Aims: To highlight the different genetic and functional background of IBD and its phenotypes, utilizing contemporary systems bioinformatics methodologies. Methods: Disease-associated SNPs, obtained via our own 89 loci IBD risk GWAS panel, were detected with the whole genome association analysis toolset PLINK. These SNPs were used as input for 2 novel and different pathway analysis methods to detect functional interactions. Specifically, PathwayConnector was used to create complementary networks of interacting pathways whereas; the online database of protein interactions STRING provided protein-protein association networks and their derived pathways. Network analyses metrics were employed to identify proteins with high significance and subsequently to rank the signaling pathways those participate in. Results: The reported complementary pathway and enriched protein-protein association networks reveal several novel and well-known key players, in the functional background of IBD like Toll-like receptor, TNF, Jak-STAT, PI3K-Akt, T cell receptor, Apoptosis, MAPK and B cell receptor signaling pathways. IBD subphenotypes are found to have distinct genetic and functional profiles which can contribute to their accurate identification and classification. As a secondary result we identify an extended network of diseases with common molecular background to IBD. Conclusions: IBD's burden on the quality of life of patients and intricate functional background presents us constantly with new challenges. Our data and methodology provide researchers with new insights to a specific population, but also, to possible differentiation markers of disease classification and progression. This work, not only provides new insights into the interplay among IBD risk variants and their related signaling pathways, elucidates the mechanisms underlying IBD and its clinical sequelae, but also, introduces a generalized bioinformatics-based methodology which can be applied to studies of different disorders. © 2019 The Author(s)

Semantic Annotation and Linking of Medical Educational Resources

Educational content is often shared among different educators and is enriched, adapted and in general repurposed so that it can be re-used in different contexts. This paper presents the MetaMorphosis+ environment for publishing, sharing and repurposing educational content in medical education. The environment meshes the paradigms of social Web and semantic Web to publish richly annotated educational resources that are further semantically enriched and exposed in the Linked Open Data cloud. The goal is to enable more relevant searching and retrieval of medical educational resources, as well as linking to other related resources in the medical domain, including scientific publications and clinical data

Type i and ii interferon signatures can predict the response to anti-Tnf agents in inflammatory bowel disease patients: Involvement of the microbiota

Background: Anti-TNF agents have been a cornerstone of IBD therapy; however, response to treatment has been variable, and clinically applicable biomarkers are urgently needed. We hypothesized that the type I and type II interferon (IFN) signatures may be a confounding factor for response to antitumor necrosis factor (TNF) treatment via interactions with the host and its gut microbiota. Methods: Peripheral blood from 30 IBD patients and 10 healthy controls was subjected to real-Time quantitative real-Time polymerase chain reaction for type I and type II IFN genes (IFNGs), both at baseline and after treatment with anti-TNF. Correlation between IFN signatures and microbiota composition was also determined for a subgroup of patients and controls. Results: At baseline, type I IFN score was significantly higher in IBD patients (P = 0.04 vs controls). Responders to subsequent anti-TNF treatment had significantly lower baseline scores for both type I and II IFN signatures (P 0.005 vs nonresponders for both comparisons). During treatment with anti-TNF, the expression of type I and II IFNGs was significantly elevated in responders and decreased in nonresponders. In addition, changes in IFN signatures correlated to specific alterations in the abundance of several microbial taxa of the gut microbiome. Conclusions: Baseline expression of type I and II IFN signatures and their kinetics during anti-TNF administration significantly correlate to treatment responses in IBD patients. Peripheral blood IFN signatures may serve as clinically meaningful biomarkers for the identification of subgroups of patients with favorable response to anti-TNF treatment. Additionally, the distinct synergies between different IFN types and microbiota might help drive therapeutic intervention. © 2020 Oxford University Press. All rights reserved