Inhibitors of hepatic microsomal triacylglycerol hydrolase decrease very low density lipoprotein secretion
Bibliographic record
Abstract
The presence of elevated circulating triacylglycerol (TG)-rich very low density lipoprotein (VLDL) and apolipoprotein B-100 (apoB-100) levels represents an independent risk factor for coronary artery disease. Triacylglycerol hydrolase catalyzes the mobilization of cytoplasmic TG stores. To test the hypothesis that the enzyme plays a role in the provision of core lipids for the assembly of VLDL, we inhibited the lipase activity in primary rat hepatocytes and analyzed lipid and apoB synthesis and secretion. Inhibition of lipolysis resulted in a dramatic decrease in secretion of TGs. In addition, secretion of cholesteryl ester and phosphatidylcholine was substantially decreased. Analysis of secreted apolipoproteins indicated that apoB-100 secretion was much more sensitive to lipase inhibition than was apoB-48 secretion, perhaps because of the ability of apoB-48 to be secreted as a relatively lipid-poor particle. The results agreed with those obtained with hepatoma cells transfected with triacylglycerol hydrolase cDNA, in which preferential lipidation of apoB-100 was observed. Together, our findings provide evidence that inhibition of intracellular TG hydrolysis significantly decreases apoB-100 secretion and suggest that triacylglycerol hydrolase may be a suitable pharmacological target in efforts to lower plasma lipid levels.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".