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617
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ShareScore release 0.9.0
Dataset results
617 results for “base population”
Breast Milk Extracellular Vesicle miRNAs from a Population-Based Cohort in the Faroe Islands
GEO Series GSE146880. Homo sapiens. 384 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Epigenomic-based identification of major cell identity regulators within heterogeneous cell populations [RNA-seq]
GEO Series GSE89605. Gallus gallus. 3 samples. Type: Expression profiling by high throughput sequencing.
The ultra-sensitive Nodewalk technique identifies stochastic from virtual, population-based enhancer hubs regulating MYC in 3D: Implications for the fitness of cancer cells [GRO-seq]
GEO Series GSE76043. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Clinical Value of RNA Sequencing–Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network—Br
GEO Series GSE81538. Homo sapiens. 405 samples. Type: Expression profiling by high throughput sequencing.
Fig S1: PCA plot indicating the distance and dissimilarity among 46 Asian populations based on 15 autosomal STR data.
<p>Supplementary file related with submission in Genes.</p> <p><strong>Evaluation of the gene flow from East to West among various populations of Rajasthan, India</strong></p> <p>R. K. Kumawat<sup>1, 2#</sup>,<sup> </sup>Pankaj Shrivastava<sup>3</sup>*<sup>#</sup>, Shivani Dixit<sup>3,</sup> Divya Shrivastava<sup>1</sup>, G.K. Mathur<sup> 2 </sup>and Gyaneshwer Chaubey<sup>4</sup></p> <p><sup>1</sup>School of Life Sciences, Jaipur National University, Jaipur-302017, Rajasthan, India</p> <p><sup>2</sup>DNA Division, State Forensic Science Laboratory, Rajasthan, Jaipur -302016, India</p> <p><sup>3</sup>DNA Fingerprinting Unit, State Forensic Science Laboratory, Department of Home (Police), Govt. of MP, Sagar-470001, India</p> <p><sup>4</sup>Cytogenetics Laboratory, Dept. of Zoology, Banaras Hindu University, Varanasi-221005, India</p> <p><sup>#</sup>author with equal credential</p> <p>*Corresponding Author – <a href="mailto:pankaj.shrivastava@rediffmail.com">pankaj.shrivastava@rediffmail.com</a></p> <p>Contact details: Phone No.- +919424371946</p>
Data from: Ectopic fat obesity presents the greatest risk for incident type 2 diabetes: a population-based longitudinal study
Objectives: Obesity is a risk factor for type 2 diabetes mellitus. Among obesity, visceral fat obesity, and ectopic fat obesity, it has been unclear which has the greatest effect on incident diabetes. Methods: In this historical cohort study of 8430 men and 7034 women, we investigated the effect of obesity phenotypes on incident diabetes. Obesity, visceral fat obesity, and ectopic fat obesity were defined as body mass index ≥25 kg/m2, waist circumference ≥90 cm in men or ≥80 cm in women, and having fatty liver diagnosed by abdominal ultrasonography, respectively. We divided the participants into eight groups according to the presence or absence of the three obesity phenotypes. Results: During the median 5.8 years follow-up for men and 5.1 years follow-up for women, 286 men and 87 women developed diabetes. Compared to the non-obese group, the hazard ratios (HRs) of incident diabetes in the only-obesity, only-visceral fat obesity, only-ectopic fat obesity groups, and with all-three types of obesity group were 1.85 (95%CI 1.06–3.26, p = 0.05) in men and 1.79 (0.24–13.21, p = 0.60) in women, 3.41 (2.51–4.64, p < 0.001) in men and 2.30 (0.87–6.05, p = 0.12) in women, 4.74 (1.91–11.70, p < 0.001) in men and 13.99 (7.23–27.09, p < 0.001) in women and 10.5 (8.02–13.8, p < 0.001) in men and 30.0 (18.0–50.0, p < 0.001) in women. Moreover, the risk of incident diabetes of the groups with ectopic fat obesity were almost higher than that of the four groups without ectopic fat obesity. Conclusion: Ectopic fat obesity presented the greatest risk of incident type 2 diabetes.
Data from: The prevalence of MS in the United States: a population-based estimate using health claims data
Objective: To generate a national multiple sclerosis (MS) prevalence estimate for the United States by applying a validated algorithm to multiple administrative health claims (AHC) datasets. Methods: A validated algorithm was applied to private, military, and public AHC datasets to identify adult cases of MS between 2008 and 2010. In each dataset, we determined the 3-year cumulative prevalence overall and stratified by age, sex, and census region. We applied insurance-specific and stratum-specific estimates to the 2010 US Census data and pooled the findings to calculate the 2010 prevalence of MS in the United States cumulated over 3 years. We also estimated the 2010 prevalence cumulated over 10 years using 2 models and extrapolated our estimate to 2017. Results: The estimated 2010 prevalence of MS in the US adult population cumulated over 10 years was 309.2 per 100,000 (95% confidence interval [CI] 308.1–310.1), representing 727,344 cases. During the same time period, the MS prevalence was 450.1 per 100,000 (95% CI 448.1–451.6) for women and 159.7 (95% CI 158.7–160.6) for men (female:male ratio 2.8). The estimated 2010 prevalence of MS was highest in the 55- to 64-year age group. A US north-south decreasing prevalence gradient was identified. The estimated MS prevalence is also presented for 2017. Conclusion: The estimated US national MS prevalence for 2010 is the highest reported to date and provides evidence that the north-south gradient persists. Our rigorous algorithm-based approach to estimating prevalence is efficient and has the potential to be used for other chronic neurologic conditions.
Population-based Seroprevalence Survey of COVID-19 Virus Infection in Malaysia
<p>Results of population-based age stratified seroepidemiological investigation in Malaysia</p>
A Multi-Centric Novel Coronavirus (COVID-19) Population-Based Age-Stratified Sero-Epidemiological Study (In Urban, Rural and Tribal Communities at Selected Centers in India: A Prospective Study)
<p>Results of population-based age stratified seroepidemiological investigation in India</p>
Large-Population based Deep Learning Models in Classifying Primary Bone Tumors and Bone Infections based on Radiographs: a Retrospective and Multi-reader Multi-center Study
<p>This retrospective multicenter study collected patients via consecutive sampling between 2013 and 2022 from two cohorts: training cohort (from the Second Xiangya Hospital of Central South University) and testing cohort (from Xiangya Hospital of Central South University and Hunan Children's Hospital of Central South University). These lesions were identified to have bone involvement through pre-operative radiographs and were histologically diagnosed following biopsy or surgery. <br>(i) For the inclusion criteria, lesions were confirmed and diagnosed as PBTs according to the 2020 World Health Organization (WHO) system for the classification for tumors of bone 1 while bone infections were confirmed and proven by histology and (or) bacterial culture. The other vital inclusion criteria are evident as well as available clinical information and pre-operative radiographs. <br>(ii) The screening criteria: (a) radiographs were from patients diagnosed between 2013 and 2022 (b) in selected three hospitals; (c) radiographs with robust quality for reliable assessments of the bone lesions and (d) all of these radiographs were pre-operative. <br>Clinical characteristics like age, gender, and the location of the lesion of interest and so on were obtained from the patients' electronic medical records after data desensitization and standardization.<br>Radiographs were kept and downloaded as Digital Imaging and Communications in Medicine (DICOM) files from the picture archiving and communication system (PACS) at their original sizes and resolutions. All of these radiograph images have undergone desensitization processing of disengaging patient protected health information from DICOM data to meet the relevant legal criteria and requirements of US (HIPAA) as well as European (GDPR). Delineating the region of interest (ROI) was performed by two proficient radiologists. ROIs were meticulously outlined via Click 2 Crop (version 5.2.2) (https://click-2-crop.en.softonic.com/) to closely segment pertinent entities present in each PBT or bone infection. The smallest rectangular box that can completely cover the ROI was manually annotated as the boundary box by senior seniority radiologist to ensure accuracy. Afterwards, the annotated ROIs were used as ground truth for the model development process.</p>
Data and code for Resolving the Taxonomic Status of the Marbled Toad (Bufonidae: Incilius marmoreus): 2RAD-based Phylogeography Including an Isolated Population in Veracruz, Mexico
<p>Data and code for a study of the phylogeography of the Marbled Toad (<em>Incilius marmoreus</em>).</p>
The Acute Effect of a Theacrine-based Supplement on Mobilization of Various Stem Cell Populations.
ClinicalTrials.gov study NCT06219161. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Village-Based Management of Chronic Cardiovascular Disease in Qu Jiang Elderly Population Registry: The BOUQUET Cohort Study
ClinicalTrials.gov study NCT07149688. IPD Sharing: NO. Countries: 1. Publications: 0.
Bile Duct Injuries During Laparoscopic Cholecystectomies: An 11-year Population-based Study
ClinicalTrials.gov study NCT05479227. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Digital Technology Combined With Blood Marker Screening and Diagnosis for Community Populations Based on Classification Theory: an Integrated Study
ClinicalTrials.gov study NCT07286812. IPD Sharing: YES. Countries: 1. Publications: 0.
Establishment of Online Registration Platform for Unruptured Intracranial Aneurysms Based on Regional Medical Centers in China and Population Follow-up Study (Phase Ⅱ)
ClinicalTrials.gov study NCT05608122. IPD Sharing: YES. Countries: 1. Publications: 0.
Quantification of Upper Trapezius Muscle Stiffness Using Supersonic Shear Wave Imaging: Efficacy of Workplace-based Exercise Programme to Reduce Neck and Shoulder Disorders in Working Population
ClinicalTrials.gov study NCT04144764. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Population-based, Multicenter Cohort Study of Combined Screening for Gastrointestinal Tumors
ClinicalTrials.gov study NCT05996458. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
A Population-based Study of Macular Choroidal Neovascularization in a Chinese Population
ClinicalTrials.gov study NCT01666821. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Prevalence and Incidence of Multiple Revisions Following Knee Arthroplasty in Denmark 1998-2021: A Nationwide Population-based Study
ClinicalTrials.gov study NCT06064318. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.