Tissue-specific postprandial clearance is the major determinant of PPARγ-induced triglyceride lowering in the rat
Bibliographic record
Abstract
Peroxisome proliferator-activated receptor-gamma (PPARgamma) agonism potently reduces circulating triglycerides (TG) in rodents and more modestly so in humans. This study aimed to quantify in vivo the relative contribution of hepatic VLDL-TG secretion and tissue-specific TG clearance to such action. Rats were fed an obesogenic diet, treated with the PPARgamma full agonist COOH (30 mg.kg(-1).day(-1)) for 3 wk, and studied in both the fasted and refed (fat-free) states. Hepatic VLDL-TG secretion rate was not affected by chronic COOH in the fasted state and was only modestly decreased (-30%) in refed rats. In contrast, postprandial VLDL-TG clearance was increased 2.6-fold by COOH, which concomitantly stimulated adipose tissue TG-derived lipid uptake and one of its major determinants, lipoprotein lipase (LPL) activity, in a highly depot-specific manner. TG-derived lipid uptake and LPL were indeed strongly increased in subcutaneous inguinal white adipose tissue and in brown adipose tissue, independently of the nutritional state, whereas of the three visceral fat depots examined (epididymal, retroperitoneal, mesenteric) only the latter responded consistently to COOH. Robust correlations (0.5 < r < 0.9) were observed between TG-derived lipid uptake and LPL in adipose tissues. The agonist did not increase LPL in muscle, and its enhancing action on postprandial muscle lipid uptake appeared to be mediated by post-LPL processes involving increased expression of fatty acid binding/transport proteins (aP2, likely in infiltrated adipocytes, FAT/CD36, and FATP-1). The study establishes in a diet-induced obesity model the major contribution of lipid uptake by specific, metabolically safe adipose depots to the postprandial hypotriglyceridemic action of PPARgamma agonism, and suggests a key role for LPL therein.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".