Plasma and vessel wall lipoprotein lipase have different roles in atherosclerosis
Bibliographic record
Abstract
Lipoprotein lipase (LPL) is a key enzyme in lipoprotein metabolism, and has been hypothesized to exert either pro- or anti-atherogenic effects, depending on its localization. Decreased plasma LPL activity is associated with the high triglyceride (TG);-low HDL phenotype that is often observed in patients with premature vascular disease. In contrast, in the vessel wall, decreased LPL may be associated with less lipoprotein retention due to many potential mechanisms and, therefore, decreased foam cell formation. To directly assess this hypothesis, we have distinguished between the effects of variations in plasma and/or vessel wall LPL on atherosclerosis susceptibility in apoE-deficient mice. Reduced LPL in both plasma and vessel wall (LPL(+/-)E(-/-)) was associated with increased TG and increased total cholesterol (TC) compared with LPL(+/+)E(-/-) sibs. However despite their dyslipidemia, LPL(+/-)E(-/-) mice had significantly reduced lesion areas compared to the LPL(+/+)E(-/-) mice. Thus, decreased vessel wall LPL was associated with decreased lesion formation even in the presence of reduced plasma LPL activity. In contrast, transgenic mice with increased plasma LPL but with no increase in LPL expression in macrophages, and thus the vessel wall, had decreased TG and TC and significantly decreased lesion areas compared with LPL(+/+)E(-/-) mice. This demonstrates that increased plasma LPL activity alone, in the absence of an increase in vessel wall LPL, is associated with reduced susceptibility to atherosclerosis. Taken together, these results provide in vivo evidence that the contribution of LPL to atherogenesis is significantly influenced by the balance between vessel wall protein (pro-atherogenic) and plasma activity (anti-atherogenic).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".