GLP-2 Regulation of Dietary Fat Absorption and Intestinal Chylomicron Production via Neuronal Nitric Oxide Synthase (nNOS) Signaling
Bibliographic record
Abstract
Postprandial dyslipidemia is a metabolic condition commonly associated with insulin-resistant states, such as obesity and type 2 diabetes. It is characterized by the overproduction of intestinal chylomicron particles and excess atherogenic chylomicron remnants in circulation. We have previously shown that glucagon-like peptide 2 (GLP-2) augments dietary fat uptake and chylomicron production in insulin-resistant states; however, the underlying mechanisms remain unclear. Previous studies have implicated nitric oxide (NO) in the absorptive actions of GLP-2. In this study, we report a novel role for neuronal NO synthase (nNOS)-mediated NO generation in lipid uptake and chylomicron formation based on studies in C57BL/6J mice, nNOS-/- mice, and Syrian golden hamsters after intraduodenal and oral fat administration. GLP-2 treatment in wild-type (WT) mice significantly increased postprandial lipid accumulation and circulating apolipoprotein B48 protein levels, while these effects were abolished in nNOS-/- mice. nNOS inhibition in Syrian golden hamsters and protein kinase G (PKG) inhibition in WT mice also abrogated the effect of GLP-2 on postprandial lipid accumulation. These studies demonstrate a novel mechanism in which nNOS-generated NO is crucial for GLP-2-mediated lipid absorption and chylomicron production in both mouse and hamster models. Overall, our data implicate an nNOS-PKG-mediated pathway in GLP-2-mediated stimulation of dietary fat absorption and intestinal chylomicron production.
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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) | 0.000 | 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) | 0.001 | 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".