Pharmacological and physiological activation of TGR5 in the NTS lowers food intake by enhancing leptin-STAT3 signaling
Bibliographic record
Abstract
Feeding increases plasma bile acid levels while the nucleus of the solitary tract (NTS) and area postrema (AP) of the brain detect changes in hormones to regulate feeding. However, whether an increase in bile acids activates Takeda G protein-coupled receptor 5 (TGR5) in the NTS and/or AP to lower feeding through a negative feedback pathway is unknown. Here, we discover that infusion of TGR5 agonist CCDC in the NTS of male rats lowered food intake without causing conditional taste avoidance in short-term high fat (HF) fed male rats in association with HF-induced increase in TGR5 expression in the NTS. In contrast, CCDC infusion into the AP failed to lower food intake in HF rats with a reduction in TGR5 expression in the AP. CCDC infusion in the NTS activates TGR5 to reverse HF-induced leptin resistance by enhancing a leptin-leptin receptor-STAT3 signaling axis selectively in the NTS to lower feeding. Finally, metabolomic analysis indicated that HF impaired a refeeding-induced rise of endogenous TGR5 ligand deoxycholic acid in the plasma and subsequently in the NTS in association with hyperphagia, while direct infusion of deoxycholic acid in the NTS of HF rats activated TGR5 to lower feeding and enhanced leptin-STAT3 signaling, thereby altogether demonstrating physiological and pharmacological activation of TGR5 in the NTS regulates food intake. In summary, we discover that an activation of TGR5 in the NTS enhances leptin-STAT3 signaling to lower food intake. Our findings highlight the potential of targeting TGR5 to reverse leptin resistance in the NTS.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".