The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources; and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
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http://dx.doi.org/10.1093/database/baq027 | DOI Listing |
J Antimicrob Chemother
January 2025
Research Laboratory, Botswana Harvard Health Partnership, Gaborone, Botswana.
Objectives: We assessed HIV-1 drug resistance profiles among people living with HIV (PLWH) with detectable viral load (VL) and on dolutegravir-based antiretroviral therapy (ART) in Botswana.
Methods: The study utilised available 100 residual HIV-1 VL samples from unique PLWH in Francistown who had viraemia at-least 6 months after initiating ART in Botswana's national ART program from November 2023 to January 2024. Viraemia was categorized as low-level viraemia (LLV) (VL: 200-999 copies/mL) or virologic failure (VF) (VL ≥1000 copies/mL).
J Proteome Res
January 2025
European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, U.K.
The PRIDE database is the largest public data repository of mass spectrometry-based proteomics data and currently stores more than 40,000 data sets covering a wide range of organisms, experimental techniques, and biological conditions. During the past few years, PRIDE has seen a significant increase in the amount of submitted data-independent acquisition (DIA) proteomics data sets. This provides an excellent opportunity for large-scale data reanalysis and reuse.
View Article and Find Full Text PDFHum Reprod Open
November 2024
Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Study Question: How accurately can artificial intelligence (AI) models predict sperm retrieval in non-obstructive azoospermia (NOA) patients undergoing micro-testicular sperm extraction (m-TESE) surgery?
Summary Answer: AI predictive models hold significant promise in predicting successful sperm retrieval in NOA patients undergoing m-TESE, although limitations regarding variability of study designs, small sample sizes, and a lack of validation studies restrict the overall generalizability of studies in this area.
What Is Known Already: Previous studies have explored various predictors of successful sperm retrieval in m-TESE, including clinical and hormonal factors. However, no consistent predictive model has yet been established.
J Diabetes Metab Disord
June 2025
Department of Physiology, Kampala International University, Western Campus, Ishaka, Uganda.
Purpose: Diabetes mellitus is a global health challenge that leads to severe complications, negatively impacting overall health, life expectancy, and quality of life. Herbal medicines, valued for their accessibility and therapeutic benefits with minimal side effects, have been promoted as potential treatments. Managing conditions like diabetes, characterized by free radical production and cytokine-driven inflammation, is vital due to the active components in plants that exert direct pharmacological effects.
View Article and Find Full Text PDFFront Microbiol
December 2024
College of Biology, Hunan University, Changsha, China.
Introduction: Dengue viruses (DENVs), the causative agents of dengue hemorrhagic fever and dengue shock syndrome, undergo genetic mutations that result in new strains and lead to ongoing global re-infections.
Objectives: To address the growing complexity of identifying and tracking biological samples, this study screened RNA barcode segments for the four DENV serotypes, ensuring high specificity and recall rates for DENV identification using segments.
Results: Through analyzing complete genome sequences of DENVs, we screened eight barcode segments for DENV, DENV-1, DENV-2, DENV-3, and DENV-4 identification.
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