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319 results for “Intestinal microbiota”

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geo20/100

Gut microbiota dysbiosis affects intestinal sensitivity through epithelium-to-neuron signaling: novel insights from colon organoid-based model to improve visceral pain therapy

GEO Series GSE294757. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenSep 2025View details →
geo20/100

Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences

GEO Series GSE58087. Mus musculus. 37 samples. Type: Expression profiling by array.

openGEO-OpenSep 2014View details →
geo16/100

Ecdysone-mediated intestinal growth contributes to microbiota-driven developmental plasticity under malnutrition

GEO Series GSE310159. Drosophila melanogaster. 20 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJan 2026View details →
geo16/100

Effects of microbiota on intestinal macrophages

GEO Series GSE115202. Mus musculus. 30 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJun 2018View details →
geo16/100

Effect of supplementation of a minimal culture medium with Raffinose compared with a glucose condition, on the gene expression of a set of bacteria of the intestinal microbiota

GEO Series GSE296323. Subdoligranulum variabile; Bacteroides uniformis; Bifidobacterium catenulatum; Bacteroides xylanisolvens; Bacteroides thetaiotaomicron; Agathobacter rectalis; Bifidobacterium adolescentis; Roseburia intestinalis. 48 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJul 2025View details →
geo16/100

Microbiota-driven arginase 1 expression impedes the resolution of intestinal inflammation

GEO Series GSE151931. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJun 2020View details →
geo16/100

Effect of supplementation of a minimal culture medium with inulin, corn fiber and pectin, compared with a glucose condition, on the gene expression of a set of bacteria of the intestinal microbiota

GEO Series GSE237111. Subdoligranulum variabile; Bacteroides xylanisolvens; Bacteroides thetaiotaomicron; Roseburia intestinalis. 36 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenDec 2023View details →
geo16/100

Swine intestinal microbiota perturbation by antibiotic treatment is linked to a reduced number of necrotic epithelial cells and up-regulation of immune-associated pathways using an in vitro Salmonella

GEO Series GSE134130. Sus scrofa. 40 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenApr 2020View details →
geo16/100

Huang Lian Jiedu Decoction ameliorates lipid metabolic disorders in obese mice by modulating gastric inhibitory polypeptide release via intestinal microbiota regulation

GEO Series GSE285884. Mus musculus. 11 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJan 2026View details →
geo16/100

Five Substances Powder with Poria ameliorates lipid metabolic disorders in obese mice by modulating gastric inhibitory polypeptide release via intestinal microbiota regulation

GEO Series GSE286337. Mus musculus. 11 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJan 2026View details →
geo16/100

Homeostatic pockets of interferon lambda-stimulated gene production in the intestine are associated with localized exposure to bacterial microbiota

GEO Series GSE269701. Mus musculus. 10 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJun 2025View details →
geo12/100

Phospholipid Metabolites of the Gut Microbiota Promote Hypoxia-induced Intestinal Injury via CD1d-dependent gd T Cells

GEO Series GSE199645. Mus musculus. 12 samples. Type: Other.

openGEO-OpenApr 2022View details →
geo12/100

Gut Microbiota Metabolite Indole-3-Acetic Acid Maintains Intestinal Epithelial Homeostasis Through Mucin Sulfation

GEO Series GSE249996. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenMay 2024View details →
geo12/100

Expression data from Escherichia coli O157:H7, strain EDL933, cultivated in caecal content of rats associated with the human intestinal microbiota

GEO Series GSE37095. Escherichia coli; Escherichia coli O157:H7 str. EDL933. 6 samples. Type: Expression profiling by array.

openGEO-OpenSep 2013View details →
geo12/100

The protective role of TLR4 in intestinal epithelial cells through the regulation of the gut microbiota in DSS-induced colitis in mice

GEO Series GSE227565. feces metagenome. 12 samples. Type: Other.

openGEO-OpenNov 2023View details →
geo12/100

Polysaccharides from Sargassum fusiforme protect mice against Citrobacter rodentium infection through intestinal microbiota-drived microRNA-92a-3p

GEO Series GSE260446. Mus musculus. 15 samples. Type: Non-coding RNA profiling by high throughput sequencing.

openGEO-OpenMar 2024View details →
zenodo12/100

Composition and metabolic activity of the intestinal microbiota in obese children and adolescents

<p>The intestinal microbiota, according to modern data, is a &ldquo;metabolic organ&quot;. Scientists distinguish a bidirectional &quot;gut-brain&quot; 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 &ge; 1) and 44 conditionally healthy children and adolescents without acute and severe chronic diseases with normal body weight (SDS BMI &le;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>

restrictedFeb 2023View details →
geo12/100

Gene expression accompanying the promotion of hepatocellular carcinoma by intestinal microbiota and Tlr4 in mice.

GEO Series GSE30485. Mus musculus. 15 samples. Type: Expression profiling by array.

openGEO-OpenJul 2014View details →
geo12/100

Gut Microbiota Metabolite Indole-3-Acetic Acid Maintains Intestinal Epithelial Homeostasis via the transcription factor AHR

GEO Series GSE255130. Mus musculus. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenDec 2025View details →

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Allen Brain Atlas

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Last verified 2026-04-30Open record

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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.

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electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

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behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

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openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record