The Greatly Under-Represented Role of Smooth Muscle Cells in Atherosclerosis
Bibliographic record
Abstract
PURPOSE OF REVIEW: This article summarizes previous and recent research on the fundamental role of arterial smooth muscle cells (SMCs) as drivers of initial and, along with macrophages, later stages of human atherosclerosis. RECENT FINDINGS: Studies using human tissues and SMC lineage-tracing mice have reinforced earlier observations that SMCs drive initial atherogenesis in humans and contribute a multitude of phenotypes including foam cell formation hitherto attributed primarily to macrophages in atherosclerosis. Arterial smooth muscle cells (SMCs) are the primary cell type in human pre-atherosclerotic intima and are responsible for the retention of lipoproteins that drive the development of atherosclerosis. Despite this, images of atherogenesis still depict the process as initially devoid of SMCs, primarily macrophage driven, and indicate only relatively minor roles such as fibrous cap formation to intimal SMCs. This review summarizes historical and recent observations regarding the importance of SMCs in the formation of a pre-atherosclerotic intima, initial and later foam cell formation, and the phenotypic changes that give rise to multiple different roles for SMCs in human and mouse lesions. Potential SMC-specific therapies in atherosclerosis are presented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".