Glucagon-like Peptide-2 Acts Partially Through Central GLP-2R and MC4R in Mobilizing Stored Lipids from the Intestine
Bibliographic record
Abstract
Background: Glucagon-like peptide-2 (GLP-2) is a gut hormone secreted in response to nutrient intake and regulates lipid metabolism in the gut. The present study aims to elucidate the underlying mechanism of GLP-2 in stimulating gut lipid secretion in the fasted state by testing whether GLP-2 signals through the brain’s GLP-2 receptor and melanocortin 4 receptor (MC4R). Methods: Sprague-Dawley rats were implanted with a mesenteric lymph duct cannula for measuring gut lipid secretion and an intracerebroventricular cannula for infusion of a GLP-2R antagonist (GLP-2(11-33)), an MC4R antagonist (SHU9119), or saline as a control. The rat received a lipid infusion into the small intestine and a peritoneal injection of GLP-2 five hours later. Results: Brain administration of a GLP-2R antagonist or an MC4R antagonist attenuated the stimulatory effects of peripheral GLP-2 on lymph triglyceride output. These effects were associated with differential changes in the expression of key genes in jejunal endothelial cells, smooth muscle cells, and neuronal cells. Conclusions: These results support the involvement of central GLP-2R and MC4R in a neural pathway for GLP-2 to mobilize lipids stored in the gut during the post-absorptive state.
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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) | 0.000 | 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) | 0.004 | 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".