Urolithin A exerts antiobesity effects through enhancing adipose tissue thermogenesis in mice
Bibliographic record
Abstract
Obesity leads to multiple health problems, including diabetes, fatty liver, and even cancer. Here, we report that urolithin A (UA), a gut-microflora-derived metabolite of pomegranate ellagitannins (ETs), prevents diet-induced obesity and metabolic dysfunctions in mice without causing adverse effects. UA treatment increases energy expenditure (EE) by enhancing thermogenesis in brown adipose tissue (BAT) and inducing browning of white adipose tissue (WAT). Mechanistically, UA-mediated increased thermogenesis is caused by an elevation of triiodothyronine (T3) levels in BAT and inguinal fat depots. This is also confirmed in UA-treated white and brown adipocytes. Consistent with this mechanism, UA loses its beneficial effects on activation of BAT, browning of white fat, body weight control, and glucose homeostasis when thyroid hormone (TH) production is blocked by its inhibitor, propylthiouracil (PTU). Conversely, administration of exogenous tetraiodothyronine (T4) to PTU-treated mice restores UA-induced activation of BAT and browning of white fat and its preventive role on high-fat diet (HFD)-induced weight gain. Together, these results suggest that UA is a potent antiobesity agent with potential for human clinical applications.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".