Apoptosis Does Not Mediate Macrophage Depletion in Rabbit Atherosclerotic Plaques after Dietary Lipid Lowering
Bibliographic record
Abstract
Unstable atherosclerotic plaques are characterized by a thin fibrous cap that contains few smooth muscle cells (SMCs) and numerous foam cells of macrophage origin. Previously we and others demonstrated that macrophages disappear from atherosclerotic plaques after dietary lipid lowering. However, it remains unclear whether loss of macrophages after lipid lowering occurs via increased apoptosis, decreased macrophage replication and/or recruitment, or via a combination of both. Rabbits were fed a diet supplemented with cholesterol (0.3%) for 24 weeks followed by a normal diet for 4, 12, or 24 weeks. After 24 weeks of cholesterol supplement, plaques showed apoptosis in both macrophages and SMCs, as determined by terminal deoxynucleotidyl transferase dUTP nick-end labeling. Cell replication (Ki-67 immunolabeling) was predominantly present in macrophages. After 24 weeks of cholesterol withdrawal, the thickness and areas of the plaques were unchanged. Nevertheless, plaques showed a considerable loss of macrophages. This event was associated with a reduced immunoreactivity for vascular cell adhesion molecule-1 (VCAM-1) in the endothelial cells starting 4 weeks after cholesterol withdrawal. Apoptosis did not increase after lipid lowering but showed a steady decline. Apart from decreased VCAM-1 expression, a strong decrease in Ki-67 immunolabeling was observed after 12 weeks of cholesterol withdrawal. Our findings suggest that loss of macrophages in atherosclerotic plaques after dietary lipid lowering is not related to induction of macrophage apoptosis but mainly a consequence of impaired monocyte recruitment followed by decreased macrophage replication. This information is essential for understanding the effects of aggressive lipid lowering on plaque stability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 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".