Central glucagon-like peptide 1 receptor-induced anorexia requires glucose metabolism-mediated suppression of AMPK and is impaired by central fructose
Bibliographic record
Abstract
Glucagon-like peptide-1 (GLP-1) suppresses food intake via activation of a central (i.e., brain) GLP-1 receptor (GLP-1R). Central AMP-activated protein kinase (AMPK) is a nutrient-sensitive regulator of food intake that is inhibited by anorectic signals. The anorectic effect elicited by hindbrain GLP-1R activation is attenuated by the AMPK stimulator AICAR. This suggests that central GLP-1R activation suppresses food intake via inhibition of central AMPK. The present studies examined the mechanism(s) by which central GLP-1R activation inhibits AMPK. Supporting previous findings, AICAR attenuated the anorectic effect elicited by intracerebroventricular (icv) administration of the GLP-1R agonist exendin-4 (Ex-4). We demonstrate that Ex-4 stimulates glycolysis and suppresses AMPK phosphorylation in a glucose-dependent manner in hypothalamic GT1-7 cells. This suggests that inhibition of AMPK and food intake by Ex-4 requires central glucose metabolism. Supporting this, the glycolytic inhibitor 2-deoxyglucose (2-DG) attenuated the anorectic effect of Ex-4. However, icv glucose did not enhance the suppression of food intake by Ex-4. AICAR had no effect on Ex-4-mediated reduction in locomotor activity. We also tested whether other carbohydrates affect the anorectic response to Ex-4. Intracerebroventricular pretreatment with the sucrose metabolite fructose, an AMPK activator, attenuated the anorectic effect of Ex-4. This potentially explains the increased food intake observed in sucrose-fed mice. In summary, we propose a model whereby activation of the central GLP-1R reduces food intake via glucose metabolism-dependent inhibition of central AMPK. We also suggest that fructose stimulates food intake by impairing central GLP-1R action. This has significant implications given the correlation between sugar consumption and obesity.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".