Abstract 445: Niacin Beneficially Alters the Secretion of Intestinal-derived TRL and HDL in a Rat Model of Insulin Resistance
Bibliographic record
Abstract
Introduction The intestine secretes discrete fractions of triglyceride (TG) rich apoB-chylomicrons (CM) and HDL particles into mesenteric lymph. Insulin resistance (IR) is associated with overproduction of intestinal CM however, the effect of IR on intestinal HDL secretion remains unknown. Niacin has been shown to reduce plasma TG while increasing HDL-C, however it is unknown if niacin modulates intestinal lymphatic CM and HDL secretion. Objective To determine the effect of niacin on the secretion and composition of intestinal lymphatic CM and HDL in a model of IR (JCR:LA- cp rat). Methods IR rats were fed control chow or chow supplemented with niacin (0.5% or 1% w/w) for 6 weeks. The mesenteric lymph duct was cannulated and lymph sampled following an intra-gastric intralipid ( fed ) infusion for 6hrs. The lymphatic CM (<1.006g/ml) and HDL (1.063-1.21g/ml) fractions were separated by density ultracentrifugation. Results IR rats over-secreted (2-fold) lymph apoB-CMs, while simultaneously reducing lymphatic apoA1-HDL (-47%) secretion compared to non-IR rats. In addition, CM and HDL particles from IR rats were found to be enriched in TG (64 and 86% respectively). Interestingly, niacin stimulated the secretion of lymph HDL (>60%), as well as attenuated lymph CM (-53%) secretion compared to control. Niacin treatment was also found to normalize the TG content of both lymph-CM and lymph-HDL particles. Conclusion IR appears to stimulate the intestine to over-secrete apoB-CM as well as reduce apoAI-HDL secretion into lymph, potentially contributing to particle dysfunction. Niacin may contribute to improving CVD risk by reducing the over-secretion of intestinal pro-atherogenic apoB-particles, whilst restoring the number and TG enrichment of intestinal anti-atherogenic apoAI-particles.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".