Abstract 684: Nobiletin Corrects Intestinal Lipid Metabolism in <i>Ldlr</i> <sup>-/-</sup> Mice Fed a High-fat Diet
Bibliographic record
Abstract
Supplementation of the citrus flavonoid nobiletin to a high-fat, high-cholesterol (HFHC) diet in Ldlr -/- mice prevents obesity, insulin resistance, hepatic steatosis, dyslipidemia and atherosclerosis, in part, through enhanced hepatic fatty-acid (FA) oxidation. Intriguingly, Ldlr -/- mice fed a HFHC diet, but not chow, retain lipids in the jejunum of the small intestine, even in the fasted state. Addition of nobiletin to the HFHC diet prevents this lipid accumulation, which may contribute to the metabolic and athero-protection. To determine the mechanisms through which nobiletin prevents jejunal lipid accumulation, Ldlr -/- mice were fed HFHC (42% kcal fat, 0.2% cholesterol), or HFHC + nobiletin (0.3%w/w; n=16/group) for 10 weeks. A fasting/2 hr-refeeding protocol revealed that nobiletin increased intestinal FoxO1 phosphorylation and decreased mTOR phosphorylation, indicating improved insulin sensitivity. Jejunal FA-synthesis and triglyceride (TG) synthesis were decreased, whereas jejunal FA-oxidation was unchanged. HFHC increased fasting (6 hr) plasma levels of total TG 2.5-fold (7.45 vs 2.9 mmol/L), chylomicron TG 1.6-fold (0.56 vs 0.36 mmol/L) and apoB48 1.4-fold (3.9 vs 2.8 AU) compared to nobiletin + HFHC. Postprandial experiments employing a poloxamer-407 injection ( i.p .) and a 3 H-TG-containing olive oil gavage showed that nobiletin increased secretion of TG mass and radioactivity into plasma compared to HFHC alone. Additionally, nobiletin increased the secretion of chylomicron-TG 1.3-fold (2.2 vs 1.4 mmol/L/hr), although apoB48 secretion was unchanged, suggesting that nobiletin increases chylomicron TG content. Electron micrographs reveal that nobiletin prevents HFHC-diet induced cytoplasmic lipid droplet formation within jejunal enterocytes 2 hours post-gavage. Nobiletin prevents HFHC-diet induced shortening of the small intestine and increases plasma levels of GLP-1, and likely GLP-2, in both fasting and post-prandial states. We conclude that nobiletin attenuates intestinal lipid accumulation through decreased de novo lipogenesis and increased chylomicron-TG secretion, where the former is achieved through improved intestinal insulin sensitivity and the latter through a possible GLP-2-dependent mechanism.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".