Spontaneous Atherosclerosis in Aged Lipoprotein Lipase–Deficient Mice With Severe Hypertriglyceridemia on a Normal Chow Diet
Bibliographic record
Abstract
Large-scale epidemiological studies have revealed a strong association between hypertriglyceridemia and coronary arteriosclerotic disease. However, there are conflicting reports whether the severe hypertriglyceridemia caused by lipoprotein lipase (LPL) deficiency is pro- or antiatherogenic. To determine the effect of LPL deficiency on atherosclerosis, we pursued long-term observation of the development of atherosclerotic lesions in an LPL gene deficient mouse model. At 4 months of age, homozygous LPL-deficient mice exhibited severe hypertriglyceridemia but no signs of aortic atherosclerotic lesions. At >15 months of age, these mice developed foam cell-rich atherosclerotic lesions at the aortic root, whereas wild-type and heterozygous mice were lesion-free at the same age. Further investigation revealed that plasma malondialdehyde levels in >15-month-old LPL-deficient mice were significantly higher than those of heterozygous and wild-type mice. Electron spin resonance analysis showed a marked increase in oxidative susceptibility of chylomicrons from the aged LPL-deficient mice. Incubation of chylomicrons from >15-month-old LPL-deficient mice with cultured human umbilical vein endothelial cells showed significantly increased upregulation of vascular cell adhesion molecule-1 and monocyte chemoattractant protein-1, markers of enhanced endothelial activation, and enhanced adherence of human THP-1 mononuclear cells. These results clearly demonstrate the occurrence of spontaneous atherosclerosis in aged LPL-deficient mice mediated by the oxidation of chylomicrons and the activation of vascular endothelial cells.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".