SMC-Derived Hyaluronan Modulates Vascular SMC Phenotype in Murine Atherosclerosis
Bibliographic record
Abstract
Rationale: Plaque instability remains poorly understood and new therapeutic approaches to reduce plaque rupture and subsequent clinical events are of great interest. Recent studies revealed an important role of phenotypic switching of smooth muscle cells (SMC) in controlling plaque stability, including ECM (extracellular matrix) deposition. Objective: The aim of this study was to elucidate the role of hyaluronan derived from SMC–hyaluronan synthase 3 ( Has3 ), in phenotypic switching and plaque stability in an animal model of atherosclerosis. Methods and Results: A mouse line with SMC-specific deletion of Has3 and simultaneous SMC-lineage tracing ( e YFP [enhanced yellow fluorescent protein]) on an Apoe −/− background was used. Lineage tracing of SMC with e YFP revealed that SMC-specific deletion of Has3 significantly increased the number of LGALS3 + (galectin-3) transition state SMC and decreased ACTA2 + (alpha-smooth muscle actin) SMC. Notably, SMC- Has3 deletion led to significantly increased collagen deposition and maturation within the fibrous cap and the whole lesion, as evidenced by picrosirius red staining and LC-PolScope analysis. Single-cell RNA sequencing of brachiocephalic artery lesions demonstrated that the loss of SMC- Has3 enhanced the transition of SMC to a Lgals3 + , ECM-producing phenotype with elevated acute-phase response gene expression. Experiments using cultured murine aortic SMC revealed that blocking CD44 (cluster of differentiation-44), an important hyaluronan binding receptor, recapitulated the enhanced acute-phase response, and synthesis of fibrous ECM. Conclusions: These studies provide evidence that the deletion of SMC- Has3 results in an ECM-producing transition state SMC phenotype (characterized by LGALS3 + expression), likely via reduced CD44 signaling, resulting in increased collagen formation and maturation, an index consistent with increased plaque stability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".