ArticleAdipocyte2021
The characterization of metabolites alterations in white adipose tissue of diabetic GK Rats after ileal transposition surgery by an untargeted metabolomics approach.
Article in Adipocyte, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Efficacy of Xiaokeqing granules and lifestyle intervention in treating prediabetes mellitus considering metabolomic biomarkers: A randomised controlled trial.World journal of diabetes · 2025Trial
- Effects of aerobic exercise on inflammation and gut microbiota in obese mice: a metagenomic and metabolomic analysis.Journal of translational medicine · 2026Article
- Analysis of common and characteristic actions ofJournal of ginseng research · 2023Review
- Traditional Chinese Medicine Formula Jian Pi Tiao Gan Yin Reduces Obesity in Mice by Modulating the Gut Microbiota and Fecal Metabolism.Evidence-based complementary and alternative medicine : eCAM · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dysfunction of adipose tissue could lead to insulin resistance, obesity and type 2 diabetes. Thus, our present study aimed to investigate metabolites alterations in white adipose tissue (WAT) of diabetic GK rats after IT surgery. Ten-week-old male diabetic GK rats were randomly subjected to IT and Sham-IT surgery. Six weeks later, the untargeted metabolomics in WAT of diabetic GK rats was performed. Differential metabolites were selected according to the coefficient of variation (CV) of quality control (QC) sample <30%, variable importance in the projection (VIP) >1 and P < 0.05. Then, the hierarchical clustering of differential metabolites was conducted and the KEGG database was used for metabolic pathway analysis. A total of 50 (in positive ion mode) and 68 (in negative ion mode) metabolites were identified as differential metabolites in WAT of diabetic GK rats between IT group and Sham-IT group, respectively. These differential metabolites were well clustered, which in descending order of the number of involved differential metabolites is ubiquinone and other terpenoid-quinone biosynthesis, AMPK signalling pathway, pantothenate and CoA biosynthesis, ferroptosis, vitamin digestion and absorption, glycerophospholipid metabolism, phenylalanine metabolism, steroid hormone biosynthesis, neuroactive ligand-receptor interaction, porphyrin and chlorophyll metabolism and bile secretion, and correlated with the parameters of body weight, food intake, WAT mass and glucose metabolism, which were significantly improved after IT surgery. The differential metabolites in WAT of diabetic GK rats were mainly related to the pathway of energy metabolism, and correlated with the improved phenotypes of diabetic GK rats after IT surgery.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.