Invited Review: Molecular mechanisms of phenotypic plasticity in smooth muscle cells
Bibliographic record
Abstract
Morphological, functional, molecular and cell biology studies have revealed a striking multifunctional nature of individual smooth muscle cells (SMC). SMCs manifest phenotypic plasticity in response to changes in environment and functional requirements, acquiring a range of structural and functional properties bounded by two extremes, called "synthetic" and "contractile." Each phenotypic state is characterized by expression of a unique set of structural, contractile, and receptor proteins and isoforms that correlate with differing patterns of gene expression. Recent studies have identified signaling pathways and transcription factors (e.g., RhoA GTPase/ROCK, also known as Rho kinase, and serum response factor) that regulate the transcriptional activities of genes encoding proteins associated with the contractile apparatus. Mechanical plasticity of contractile-state smooth muscle further extends SMC functional diversity. This may also be regulated, in part, by the RhoA GTPase/ROCK pathway, via reorganization of cytoskeletal and contractile proteins. Future studies that define transcriptional and posttranscriptional mechanisms of SMC plasticity are necessary to fully understand the role of SMC in the pathogenesis and morbidity of human diseases of the airways, vasculature, and gastrointestinal tract.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.012 |
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".