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8
datasets available to search
ShareScore release 0.9.0
Dataset results
8 results for “obesity, microbiota,children”
Impact of Dietary Fiber as Prebiotics on Intestinal Microbiota in Obese Thai Children
ClinicalTrials.gov study NCT03968003. IPD Sharing: YES. Countries: 1. Publications: 7.
Effect of Prebiotic Intake on Adiposity, Satiety and Gut Microbiota in Overweight and Obese Children
ClinicalTrials.gov study NCT02125955. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Motivational Intervention on the Gut Microbiota of Obese Children
ClinicalTrials.gov study NCT03749291. IPD Sharing: NO. Countries: 1. Publications: 1.
The Effect of Probiotics on Low-grade Inflammation, Microbiota and Risk Factors for Metabolic Syndrome in Obese Children
ClinicalTrials.gov study NCT01020617. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Effects of HMOs on the Faecal Microbiota and on Host Metabolism in Obese Children
ClinicalTrials.gov study NCT02786160. IPD Sharing: NO. Countries: 1. Publications: 1.
Influence of Mediterranean Foods on Gut Microbiota Functionality in Obese Children Compared to Lean Children (Supplemental information)
<p>Complete dataset including the antioxidant capacity for all foods tested with 3 antioxidant method.</p>
Composition and Collection Feasibility of Gut Microbiota in Children With and Without Obesity
ClinicalTrials.gov study NCT03149601. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Composition and metabolic activity of the intestinal microbiota in obese children and adolescents
<p>The intestinal microbiota, according to modern data, is a “metabolic organ". Scientists distinguish a bidirectional "gut-brain" axis, the connection between the components of which is carried out thanks to intestinal microbiota and its metabolites (dopamine, short-chain fatty acids, etc.). Currently, scientific data continue to accumulate actively, studying the relationship of intestinal microbiota disorders and the development of obesity [Abenavoli, L., 2019 г. Julita Tokarek, et, 2022]. The problem of the relationship of the composition, metabolic effects of intestinal microbiota in the development of obesity has not been sufficiently studied and requires additional clarification. The study included children aged 6-18 years with obesity or overweight (74 people) (SDS BMI criterion ≥ 1) and 44 conditionally healthy children and adolescents without acute and severe chronic diseases with normal body weight (SDS BMI ≤1.0, WHO criteria). Anamnestic data were analyzed with the identification of risk factors for the development of obesity and metabolic syndrome, objective status data were evaluated, venous blood was taken (general blood analysis, biochemical blood analysis, study of the extended lipid spectrum (total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, atherogenicity index), hormones (insulin, leptin, resistin, irisin, GLP-1 and GLP-2). Instrumental research methods (ultrasound examination of abdominal organs, bioimpedance). Microbiota composition was studied by mass spectrometry (blood and feces) and 16S-RNA sequencing (feces) and microbiota metabolic activity by gas mass spectrometry (feces). The aim of the study was to establish the significance of the composition and metabolic activity of the intestinal microbiota, clinical and hormonal disorders in overweight and obese children and adolescents for early diagnosis of carbohydrate metabolism disorders. Data have been obtained that the taxonomic composition of the intestinal microbiota in obese and overweight children is characterized by the predominance of a stable phylum (type) of <em>Actinobacteriota</em> and a decrease in the phylum of <em>Bacteroidota</em>, which are part of the phylogenetic nucleus. The metabolic activity of the intestinal microbiota in obese and overweight children is characterized by a decrease in the production of all short-chain fatty acids, mainly butyrate, which is accompanied by a decrease in some types of butyrate-producing bacteria, such as <em>Faecalibacterium</em>. The greatest influence on metabolic activity is exerted by bacteria of the genus <em>Bacteroides</em>, the species <em>Bacteroides_eggerthii</em>. A decrease in the production of short-chain fatty acids in obese and overweight children leads to a decrease in the level of incretins, especially GLP-1 and GLP-2 in the blood, contributing to the development of carbohydrate metabolism disorders.</p>
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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.