Activation of arcuate nucleus glucagon-like peptide-1 receptor-expressing neurons suppresses food intake
Bibliographic record
Abstract
Abstract Background Central nervous system (CNS) control of metabolism plays a pivotal role in maintaining energy balance. In the brain, Glucagon-like peptide 1 (GLP-1), encoded by the proglucagon ‘Gcg’ gene, produced in a distinct population of neurons in the nucleus tractus solitarius (NTS), has been shown to regulate feeding behavior leading to the suppression of appetite. However, neuronal networks that mediate endogenous GLP-1 action in the CNS on feeding and energy balance are not well understood. Results We analyzed the distribution of GLP-1R-expressing neurons and axonal projections of NTS GLP-1-producing neurons in the mouse brain. GLP-1R neurons were found to be broadly distributed in the brain and specific forebrain regions, particularly the hypothalamus, including the arcuate nucleus of the hypothalamus (ARC), a brain region known to regulate energy homeostasis and feeding behavior, that receives dense NTSGcg neuronal projections. The impact of GLP-1 signaling in the ARC GLP-1R-expressing neurons and the impact of activation of ARC GLP-1R on food intake was examined. Application of GLP-1R specific agonist Exendin-4 (Exn-4) enhanced a proportion of the ARC GLP-1R-expressing neurons and pro-opiomelanocortin (POMC) neuronal action potential firing rates. Chemogenetic activation of the ARC GLP-1R neurons by using Cre-dependent hM3Dq AAV in the GLP-1R-ires-Cre mice, established that acute activation of the ARC GLP-1R neurons significantly suppressed food intake but did not have a strong impact on glucose homeostasis. Conclusions These results highlight the importance of central GLP-1 signaling in the ARC that express GLP-1R that upon activation, regulate feeding behavior.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.751 | 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 teacher head, 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".