Bibliographic record
Abstract
PURPOSE OF REVIEW: Smooth muscle cells (SMCs) form the thickened intimal layer in atherosclerosis-prone arteries in early life, and provide the initial site for retention and uptake of atherogenic lipoproteins. Here we review current knowledge regarding the importance of SMCs in the deposition of cholesterol in atherosclerotic plaque. RECENT FINDINGS: SMCs were found to comprise at least 50% of total foam cells in human coronary artery atherosclerosis, and exhibit a selective loss of expression of the cholesterol efflux promoter ATP-binding cassette transporter A1. Cholesterol loading induced a loss of SMC gene expression and an increase in macrophage and proinflammatory marker expression by cultured mouse and human arterial SMCs, with reversal of these effects upon removal of the excess cholesterol. Mice engineered to track all cells of SMC lineage indicated that, at most, SMCs make up about one-third of total cells in atherosclerotic plaque in these animals. SUMMARY: SMCs appear to be the origin of the majority of foam cells in human atherosclerotic plaque. Recent studies suggest a renaissance of research on the role of SMCs in atherosclerosis is needed to make the next leap forward in the prevention and treatment of this disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 0.030 |
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".