Tauroursodeoxycholic acid functions as a critical effector mediating insulin sensitization of metformin in obese mice
Bibliographic record
Abstract
Metformin is widely used to surmount insulin resistance (IR) and type 2 diabetes. Accumulating evidence suggests that metformin may improve IR through regulating gut microbiota and bile acids. However, the underlying mechanisms remain unclear. Our metabolomic analysis showed that metformin significantly increased the accumulation of tauroursodeoxycholic acid (TUDCA) in intestine and liver from high-fat diet (HFD)-induced IR mice. TUDCA also alleviated IR, and reduced oxidative stress and intestinal inflammation in ob/ob mice. TUDCA blocked KEAP1 to bind with Nrf2, resulting in Nrf2 translocation into nuclear and initiating the transcription of antioxidant genes, which eventually reduced intracellular ROS accumulation and improved insulin signaling. Analysis of gut microbiota further revealed that metformin reduced the relative abundance of Bifidobacterium, which produces bile salt hydrolase (BSH). The reduction in BSH was probably crucial for the accumulation of TUDCA. Metformin also increased the proportion of Akkermanisia muciniphlia in gut microbiota of ob/ob mice via TUDCA. These beneficial effects of metformin in remodeling gut microbiota, reducing oxidative stress and improving insulin sensitivity were partly due to the accumulation of TUDCA, suggesting that TUDCA may be a potential therapy for metabolic syndrome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".