Inhibition of macrophage proliferation dominates plaque regression in response to cholesterol lowering
Bibliographic record
Abstract
Statins induce plaque regression characterized by reduced macrophage content in humans, but the underlying mechanisms remain speculative. Studying the translational APOE*3-Leiden.CETP mouse model with a humanized lipoprotein metabolism, we find that systemic cholesterol lowering by oral atorvastatin or dietary restriction inhibits monocyte infiltration, and reverses macrophage accumulation in atherosclerotic plaques. Contrary to current believes, none of (1) reduced monocyte influx (studied by cell fate mapping in thorax-shielded irradiation bone marrow chimeras), (2) enhanced macrophage egress (studied by fluorescent bead labeling and transfer), or (3) atorvastatin accumulation in murine or human plaque (assessed by mass spectrometry) could adequately account for the observed loss in macrophage content in plaques that undergo phenotypic regression. Instead, suppression of local proliferation of macrophages dominates phenotypic plaque regression in response to cholesterol lowering: the lower the levels of serum LDL-cholesterol and lipid contents in murine aortic and human carotid artery plaques, the lower the rates of in situ macrophage proliferation. Our study identifies macrophage proliferation as the predominant turnover determinant and an attractive target for inducing plaque regression.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".