GLP-1 receptor signaling is not required for reduced body weight after RYGB in rodents
Bibliographic record
Abstract
Exaggerated GLP-1 and PYY secretion is thought to be a major mechanism in the reduced food intake and body weight after Roux-en-Y gastric bypass surgery. Here, we use complementary pharmacological and genetic loss-of-function approaches to test the role of increased signaling by these gut hormones in high-fat diet-induced obese rodents. Chronic brain infusion of a supramaximal dose of the selective GLP-1 receptor antagonist exendin-9-39 into the lateral cerebral ventricle significantly increased food intake and body weight in both RYGB and sham-operated rats, suggesting that, while contributing to the physiological control of food intake and body weight, central GLP-1 receptor signaling tone is not the critical mechanism uniquely responsible for the body weight-lowering effects of RYGB. Central infusion of the selective Y2R-antagonist BIIE0246 had no effect in either group, suggesting that it is not critical for the effects of RYGB on body weight under the conditions tested. In a recently established mouse model of RYGB that closely mimics surgery and weight loss dynamics in humans, obese GLP-1R-deficient mice lost the same amount of body weight and fat mass and maintained similarly lower body weight compared with wild-type mice. Together, the results surprisingly provide no support for important individual roles of either gut hormone in the specific mechanisms by which RYGB rats settle at a lower body weight. It is likely that the beneficial effects of bariatric surgeries are expressed through complex mechanisms that require combination approaches for their identification.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".