The GMQL system is freely available for non-commercial use as open source project at: http://www.bioinformatics.deib.polimi.it/GMQLsystem/.
ViruSurf, available at http://gmql.eu/virusurf/, is a large public database of viral sequences and integrated and curated metadata from heterogeneous sources (RefSeq, GenBank, COG-UK and NMDC); it also exposes computed nucleotide and amino acid variants, called from original sequences. A GISAID-specific ViruSurf database, available at http://gmql.eu/virusurf_gisaid/, offers a subset of these functionalities. Given the current pandemic outbreak, SARS-CoV-2 data are collected from the four sources; but ViruSurf contains other virus species harmful to humans, including SARS-CoV, MERS-CoV, Ebola and Dengue. The database is centered on sequences, described from their biological, technological and organizational dimensions. In addition, the analytical dimension characterizes the sequence in terms of its annotations and variants. The web interface enables expressing complex search queries in a simple way; arbitrary search queries can freely combine conditions on attributes from the four dimensions, extracting the resulting sequences. Several example queries on the database confirm and possibly improve results from recent research papers; results can be recomputed over time and upon selected populations. Effective search over large and curated sequence data may enable faster responses to future threats that could arise from new viruses.
Many valuable resources developed by world-wide research institutions and consortia describe genomic datasets that are both open and available for secondary research, but their metadata search interfaces are heterogeneous, not interoperable and sometimes with very limited capabilities. We implemented GenoSurf, a multi-ontology semantic search system providing access to a consolidated collection of metadata attributes found in the most relevant genomic datasets; values of 10 attributes are semantically enriched by making use of the most suited available ontologies. The user of GenoSurf provides as input the search terms, sets the desired level of ontological enrichment and obtains as output the identity of matching data files at the various sources. Search is facilitated by drop-down lists of matching values; aggregate counts describing resulting files are updated in real time while the search terms are progressively added. In addition to the consolidated attributes, users can perform keyword-based searches on the original (raw) metadata, which are also imported; GenoSurf supports the interplay of attribute-based and keyword-based search through well-defined interfaces. Currently, GenoSurf integrates about 40 million metadata of several major valuable data sources, including three providers of clinical and experimental data (TCGA, ENCODE and Roadmap Epigenomics) and two sources of annotation data (GENCODE and RefSeq); it can be used as a standalone resource for targeting the genomic datasets at their original sources (identified with their accession IDs and URLs), or as part of an integrated query answering system for performing complex queries over genomic regions and metadata.
The integration of genomic metadata is, at the same time, an important, difficult, and well-recognized challenge. It is important because a wealth of public data repositories is available to drive biological and clinical research; combining information from various heterogeneous and widely dispersed sources is paramount to a number of biological discoveries. It is difficult because the domain is complex and there is no agreement among the various metadata definitions, which refer to different vocabularies and ontologies. It is well-recognized in the bioinformatics community because, in the common practice, repositories are accessed one-by-one, learning their specific metadata definitions as result of long and tedious efforts, and such practice is error-prone. In this paper, we describe META-BASE, an architecture for integrating metadata extracted from a variety of genomic data sources, based upon a structured transformation process. We present a variety of innovative techniques for data extraction, cleaning, normalization and enrichment. The result is a repository that already integrates several important sources, and a general, open and extensible pipeline that can easily incorporate any number of new data sources.
ImportanceData on the association of COVID-19 vaccination with intensive care unit (ICU) admission and outcomes of patients with SARS-CoV-2–related pneumonia are scarce.ObjectiveTo evaluate whether COVID-19 vaccination is associated with preventing ICU admission for COVID-19 pneumonia and to compare baseline characteristics and outcomes of vaccinated and unvaccinated patients admitted to an ICU.Design, Setting, and ParticipantsThis retrospective cohort study on regional data sets reports: (1) daily number of administered vaccines and (2) data of all consecutive patients admitted to an ICU in Lombardy, Italy, from August 1 to December 15, 2021 (Delta variant predominant). Vaccinated patients received either mRNA vaccines (BNT162b2 or mRNA-1273) or adenoviral vector vaccines (ChAdOx1-S or Ad26.COV2). Incident rate ratios (IRRs) were computed from August 1, 2021, to January 31, 2022; ICU and baseline characteristics and outcomes of vaccinated and unvaccinated patients admitted to an ICU were analyzed from August 1 to December 15, 2021.ExposuresCOVID-19 vaccination status (no vaccination, mRNA vaccine, adenoviral vector vaccine).Main Outcomes and MeasuresThe incidence IRR of ICU admission was evaluated, comparing vaccinated people with unvaccinated, adjusted for age and sex. The baseline characteristics at ICU admission of vaccinated and unvaccinated patients were investigated. The association between vaccination status at ICU admission and mortality at ICU and hospital discharge were also studied, adjusting for possible confounders.ResultsAmong the 10 107 674 inhabitants of Lombardy, Italy, at the time of this study, the median [IQR] age was 48 [28-64] years and 5 154 914 (51.0%) were female. Of the 7 863 417 individuals who were vaccinated (median [IQR] age: 53 [33-68] years; 4 010 343 [51.4%] female), 6 251 417 (79.5%) received an mRNA vaccine, 550 439 (7.0%) received an adenoviral vector vaccine, and 1 061 561 (13.5%) received a mix of vaccines and 4 497 875 (57.2%) were boosted. Compared with unvaccinated people, IRR of individuals who received an mRNA vaccine within 120 days from the last dose was 0.03 (95% CI, 0.03-0.04; P < .001), whereas IRR of individuals who received an adenoviral vector vaccine after 120 days was 0.21 (95% CI, 0.19-0.24; P < .001). There were 553 patients admitted to an ICU for COVID-19 pneumonia during the study period: 139 patients (25.1%) were vaccinated and 414 (74.9%) were unvaccinated. Compared with unvaccinated patients, vaccinated patients were older (median [IQR]: 72 [66-76] vs 60 [51-69] years; P < .001), primarily male individuals (110 patients [79.1%] vs 252 patients [60.9%]; P < .001), with more comorbidities (median [IQR]: 2 [1-3] vs 0 [0-1] comorbidities; P < .001) and had higher ratio of arterial partial pressure of oxygen (Pao2) and fraction of inspiratory oxygen (FiO2) at ICU admission (median [IQR]: 138 [100-180] vs 120 [90-158] mm Hg; P = .007). Factors associated with ICU and hospital mortality were higher age, premorbid heart disease, lower Pao2/FiO2 at ICU admission, and female sex (this factor only for ICU mortality). ICU and hospital mortality were similar between vaccinated and unvaccinated patients.Conclusions and RelevanceIn this cohort study, mRNA and adenoviral vector vaccines were associated with significantly lower risk of ICU admission for COVID-19 pneumonia. ICU and hospital mortality were not associated with vaccinated status. These findings suggest a substantial reduction of the risk of developing COVID-19–related severe acute respiratory failure requiring ICU admission among vaccinated people.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.