The RNA-binding protein RBPMS inhibits smooth muscle cell–driven vascular remodeling in atherosclerosis and vascular injury
Bibliographic record
Abstract
Atherosclerosis and vessel wall trauma induce vascular smooth muscle cell (VSMC) phenotypic modulation, leading to plaque cap growth and postintervention restenosis. Our systems biology approach identified RNA binding protein, mRNA processing factor ( RBPMS ) as a conserved, VSMC-specific gene associated with VSMC modulation in atherosclerosis. RBPMS gene expression positively correlates with VSMC contractile markers in human and murine atherosclerotic arteries as well as in two vascular injury models during the postinjury intimal hyperplasia phase. RBPMS promotes contractile VSMC differentiation, reduces plaque cap development in high-fat diet-fed apolipoprotein E-null ( ApoE −/− ) murine atherosclerotic arteries, and inhibits intimal hyperplasia. Mechanistically, the RBPMS protein interacts with the myocardin ( MYOCD ) pre-mRNA and enhances MYOCD_v3 / MYOCD_v1 transcript balance through alternative exon 2a splicing. RBPMS promotes the VSMC contractile phenotype and reduces their fibroproliferative activity in a MYOCD_v3a-dependent manner. RBPMS enhances Myocd_v3 / Myocd_v1 transcript balance in both atherosclerotic and injured vessels. RBPMS may inhibit VSMC-driven plaque cap development and intervention-induced restenosis.
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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) | 0.000 | 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".