Resistance of adipose tissue lipoprotein lipase to insulin action in rats fed an obesity-promoting diet
Bibliographic record
Abstract
This study aimed to assess whether adipose lipoprotein lipase (LPL) becomes resistant to insulin in a nutritional model of resistance of glucose metabolism to insulin. Sprague-Dawley rats were fed for 4 wk chow or a purified high-sucrose, high-fat (HSHF) diet that induced overt insulin resistance. Rats were fasted for 24 h and then refed chow for 1, 3, or 6 h. The postprandial rise in insulinemia was similar in both dietary cohorts, whereas glycemia was higher in HSHF-fed than in chow-fed animals, indicating glucose intolerance and insulin resistance. In chow-fed rats, adipose LPL activity increased two- to fourfold postprandially, but only minimally (30%) in HSHF-fed rats. Muscle LPL decreased postprandially in HSHF-fed rats, suggesting intact sensitivity to insulin, but it increased in chow-fed animals. Peak postprandial triglyceridemia was higher (+70%) in insulin-resistant than in control rats. The postprandial rate of appearance of triglycerides in the circulation was similar in control and insulin-resistant rats, indicating that hypertriglyceridemia of the latter was the result of impaired clearance. These results demonstrate that adipose LPL becomes resistant to insulin in diet-induced IR and further suggest that, under certain nutritional conditions, modifications in adipose LPL modulation associated with insulin resistance, along with low muscle LPL, heightens postprandial hypertriglyceridemia through attenuated triglyceride clearance.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".