Abstract 429: Central Glucagon-Like Peptide-1 Reduces Intestinal Chylomicron Production via Melanocortin-4-Receptor Signaling
Bibliographic record
Abstract
Insulin resistance and the metabolic syndrome are associated with intestinal overproduction of chylomicrons, resulting in postprandial dyslipidemia and atherogenic remnants. It is increasingly clear that a reduction in chylomicrons is achieved by the action of glucagon-like peptide-1 (GLP-1) in the periphery. However, this peptide is also generated by central neurons and regulates activity in brain regions that affect sympathetic signaling. Indeed, through sympathetic pathways GLP-1 can modulate peripheral lipogenesis. Therefore, we examined the potential role of peripheral and central GLP-1 in regulating chylomicron production. Healthy hamsters received an oral fat load followed by an intraperitoneal (IP) or intracerebroventricular (ICV) injection of the GLP-1 receptor (GLP-1R) agonist exendin-4. Postprandial triglyceride (TG) and apolipoprotein B48 (apoB48) levels from plasma TG-rich lipoproteins (TRL) were found to be reduced over 6 h. The effects of central exendin-4 were mirrored by ICV MK-0626, an inhibitor of GLP-1 degradation, and reversed by the GLP-1R antagonist exendin9-39. Given a potential link between central GLP-1 and the melanocortin-4-receptor (MC4R) system, hamsters received an MC4R antagonist ICV alongside exendin-4 and this prevented a lowering in TRL-TG levels. To determine whether subsequent communication with the gut was through sympathetic pathways, α- and β-adrenergic receptor blockers were infused intravenously prior to ICV exendin-4 treatment and prevented exendin-4 from reducing TRL-TG. Finally, to examine the interplay between central and peripheral GLP-1R signaling, exendin-4 was given IP while exendin9-39 was given ICV and vice-versa. IP exendin-4 diminished TRL-TG levels during central antagonism, while IP exendin9-39 prevented the action of ICV exendin-4. This suggests that peripheral GLP-1Rs may be potentiated by central stimulation, but can also act independently. Overall, we demonstrate a GLP-1-sensitive brain-gut axis for regulating chylomicron production, involving the MC4R system and sympathetic pathways. Future studies will investigate whether central GLP-1 signals via pro-opiomelanocortin neurons and sympathetic neurotransmitters to affect enterocyte chylomicron output.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".