Professional sleep societies have identified a need for strategic research in multiple areas that may benefit from access to and aggregation of large, multidimensional datasets. Technological advances provide opportunities to extract and analyze physiological signals and other biomedical information from datasets of unprecedented size, heterogeneity, and complexity. The National Institutes of Health has implemented a Big Data to Knowledge (BD2K) initiative that aims to develop and disseminate state of the art big data access tools and analytical methods. The National Sleep Research Resource (NSRR) is a new National Heart, Lung, and Blood Institute resource designed to provide big data resources to the sleep research community. The NSRR is a web-based data portal that aggregates, harmonizes, and organizes sleep and clinical data from thousands of individuals studied as part of cohort studies or clinical trials and provides the user a suite of tools to facilitate data exploration and data visualization. Each deidentified study record minimally includes the summary results of an overnight sleep study; annotation files with scored events; the raw physiological signals from the sleep record; and available clinical and physiological data. NSRR is designed to be interoperable with other public data resources such as the Biologic Specimen and Data Repository Information Coordinating Center Demographics (BioLINCC) data and analyzed with methods provided by the Research Resource for Complex Physiological Signals (PhysioNet). This article reviews the key objectives, challenges and operational solutions to addressing big data opportunities for sleep research in the context of the national sleep research agenda. It provides information to facilitate further interactions of the user community with NSRR, a community resource.
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http://dx.doi.org/10.5665/sleep.5774 | DOI Listing |
J Pharm Anal
December 2024
Institute of Translational Medicine, Zhejiang University School of Medicine, 268 Kaixuan Road, Hangzhou, 310020, China.
Diabetes mellitus (DM) is a major metabolic disease endangering global health, with diabetic nephropathy (DN) as a primary complication lacking curative therapy. Sporoderm-broken spores of (GLP), an herbal medicine, has been used for the treatment of metabolic disorders. In this study, DN was induced in Sprague-Dawley rats using streptozotocin (STZ) and a high-fat diet (HFD), and the protective mechanisms of GLP were investigated through transcriptomic, metabolomic, and network pharmacology (NP) analyses.
View Article and Find Full Text PDFTher Adv Musculoskelet Dis
January 2025
Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, 158 Shangtang Road, Hangzhou, Zhejiang 310014, China.
Background: Previous meta-analyses have demonstrated osteoarthritis (OA) is associated with an increased risk of dementia, but these studies were prone to bias based on residual confounding factors and reverse causality.
Objectives: We aimed to investigate associations between OA and cognitive function using data from the National Health and Nutrition Examination Survey (NHANES) and to investigate the causality using Mendelian randomization (MR).
Design: This is a cross-sectional study and MR study.
Front Res Metr Anal
January 2025
Centre for Postgraduate Studies, Cape Peninsula University of Technology, Cape Town, South Africa.
Big Data communication researchers have highlighted the need for qualitative analysis of online science conversations to better understand their meaning. However, a scholarly gap exists in exploring how qualitative methods can be applied to small data regarding micro-bloggers' communications about science articles. While social media attention assists with article dissemination, qualitative research into the associated microblogging practices remains limited.
View Article and Find Full Text PDFFront Big Data
January 2025
School of Computing, Engineering and the Built Environment, Edinburgh Napier University, Edinburgh, United Kingdom.
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