Overview of the protein-protein interaction annotation extraction task of BioCreative II

© 2008 Krallinger et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution Licens

Mucosal immune defence polymorphisms: relevant players in IgA vasculitis?

Congresos y Comunicaciones: Comunicación, Congreso - póster

IgAV and IgAN: a single entity regarding CD40, BLK and BANK1 polymorphisms.

Congresos y conferencias: Comunicación de congreso - oral

Fifth European Dirofilaria and Angiostrongylus Days (FiEDAD) 2016

Peer reviewe

Linking genes to literature: text mining, information extraction, and retrieval applications for biology

Efficient access to information contained in online scientific literature collections is essential for life science research, playing a crucial role from the initial stage of experiment planning to the final interpretation and communication of the results. The biological literature also constitutes the main information source for manual literature curation used by expert-curated databases. Following the increasing popularity of web-based applications for analyzing biological data, new text-mining and information extraction strategies are being implemented. These systems exploit existing regularities in natural language to extract biologically relevant information from electronic texts automatically. The aim of the BioCreative challenge is to promote the development of such tools and to provide insight into their performance. This review presents a general introduction to the main characteristics and applications of currently available text-mining systems for life sciences in terms of the following: the type of biological information demands being addressed; the level of information granularity of both user queries and results; and the features and methods commonly exploited by these applications. The current trend in biomedical text mining points toward an increasing diversification in terms of application types and techniques, together with integration of domain-specific resources such as ontologies. Additional descriptions of some of the systems discussed here are available on the internet

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Allergen immunotherapy for allergic rhinoconjunctivitis : a systematic review and meta-analysis

BACKGROUND: The European Academy of Allergy and Clinical Immunology (EAACI) is in the process of developing Guidelines on Allergen Immunotherapy (AIT) for Allergic Rhinoconjunctivitis. In order to inform the development of clinical recommendations, we undertook a systematic review to assess the effectiveness, cost-effectiveness and safety of AIT in the management of allergic rhinoconjunctivitis METHODS: We searched 15 international biomedical databases for published, in progress and unpublished evidence. Studies were independently screened by two reviewers against pre-defined eligibility criteria and critically appraised using established instruments. Our primary outcomes of interest were symptom, medication and combined symptom and medication scores. Secondary outcomes of interest included cost-effectiveness and safety. Data were descriptively summarized and then quantitatively synthesized using random-effects meta-analyses. RESULTS: We identified 5932 studies of which 160 studies satisfied our eligibility criteria. There was a substantial body of evidence demonstrating significant reductions in standardized mean differences (SMD) of symptom (SMD -0.53, 95%CI -0.63, -0.42), medication (SMD -0.37, 95%CI -0.49, -0.26) and combined symptom and medication (SMD -0.49, 95%CI -0.69, -0.30) scores whilst on treatment that were robust to pre-specified sensitivity analyses. There was in comparison a more modest body of evidence on effectiveness post-discontinuation of AIT, this suggesting a benefit in relation to symptom scores. CONCLUSIONS: AIT is effective in improving symptom, medication and combined symptom and medication scores in patients with allergic rhinoconjunctivitis whilst on treatment, and there is some evidence suggesting that these benefits are maintained in relation to symptom scores after discontinuation of therapy. This article is protected by copyright. All rights reserved

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality