The Hypothalamic Glucagon-Like Peptide 1 Receptor Is Sufficient but Not Necessary for the Regulation of Energy Balance and Glucose Homeostasis in Mice
Bibliographic record
Abstract
Pharmacological activation of the hypothalamic glucagon-like peptide 1 (GLP-1) receptor (GLP-1R) promotes weight loss and improves glucose tolerance. This demonstrates that the hypothalamic GLP-1R is sufficient but does not show whether it is necessary for the effects of exogenous GLP-1R agonists (GLP-1RA) or endogenous GLP-1 on these parameters. To address this, we crossed mice harboring floxed Glp1r alleles to mice expressing Nkx2.1-Cre to knock down Glp1r expression throughout the hypothalamus (GLP-1RKDΔNkx2.1cre). We also generated mice lacking Glp1r expression specifically in two GLP-1RA–responsive hypothalamic feeding nuclei/cell types, the paraventricular nucleus (GLP-1RKDΔSim1cre) and proopiomelanocortin neurons (GLP-1RKDΔPOMCcre). Chow-fed GLP-1RKDΔNkx2.1cre mice exhibited increased food intake and energy expenditure with no net effect on body weight. When fed a high-fat diet, these mice exhibited normal food intake but elevated energy expenditure, yielding reduced weight gain. None of these phenotypes were observed in GLP-1RKDΔSim1cre and GLP-1RKDΔPOMCcre mice. The acute anorectic and glucose tolerance effects of peripherally dosed GLP-1RA exendin-4 and liraglutide were preserved in all mouse lines. Chronic liraglutide treatment reduced body weight in chow-fed GLP-1RKDΔNkx2.1cre mice, but this effect was attenuated with high-fat diet feeding. In sum, classic homeostatic control regions are sufficient but not individually necessary for the effects of GLP-1RA on nutrient homeostasis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".