29-LB: Investigating the Molecular Basis of the Microbiota-Mediated Regulation of Postprandial Chylomicron Production
Bibliographic record
Abstract
Obesity and insulin resistance have been identified as major global health concerns. They are associated with increased intestinal chylomicron production and subsequent remnant lipoprotein accumulation which lead to postprandial dyslipidemia. Dietary composition influences metabolic output of the gut microbiota by digesting dietary nutrients and producing various metabolites, which affects host metabolism. Understanding the mechanistic roles of the microbiota in regulating host lipid metabolism is therefore critical in addressing the pathogenesis of dyslipidemia. In this study, we aimed to investigate the effects of microbiota on lipid and lipoprotein metabolism in Syrian golden hamsters which is a more relevant animal model to human. Microbiota depletion was induced in male and female hamsters given either standard chow or a low fat/high fructose (HF) diet via antibiotic oral gavage administration. The results showed that feeding a HF diet increased plasma triglyceride (TG) and cholesterol (CH) levels while substantially reduced microbiota in antibiotic-administered groups led to significant reduction in circulating TG and CH in both diets. Then, we intended to look at the role of dysbiosis on postprandial lipid accumulation. Interestingly, in both sexes postprandial and TRL-TG levels were dramatically reduced after antibiotic administration; the effect was associated with significantly decreased ApoB48 protein levels. These changes appear to be due to a modulation of genes involved in farnesoid X receptor (FXR) receptor signaling in the ileum. Additionally, some critical genes implicated in lipid synthesis and absorption were also altered in the jejunum, with the most remarkable discovery being the extremely substantial down regulation of Scavenger Receptor Class B type 1“SR-B1” at both the mRNA and protein levels in all antibiotic-treated groups independent of sex and diet. In summary, our results suggest a novel role for the gut microbiota in regulating lipid and lipoprotein metabolism in the gut, urging further studies to determine the underlying mechanisms. Disclosure N. H. S. Abdalqadir: None. K. Adeli: None. Funding Canadian Institutes of Health Research
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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) | 0.003 | 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".