Stretch-dependent growth and differentiation in vascular smooth muscle: role of the actin cytoskeleton
Bibliographic record
Abstract
The smooth muscle cells in the vascular wall are constantly exposed to distending forces from the intraluminal pressure. A rise in blood pressure triggers growth of the vessel wall, which is characterized primarily by hypertrophy of smooth muscle cells with maintained differentiation in a contractile phenotype. Growth factor stimulation of dissociated smooth muscle cells, on the other hand, causes proliferative growth with loss of contractility. This type of response is also found in neointima development following angioplasty and in atherosclerotic lesions. An intact tissue environment is therefore critical for preserved differentiation. Recent advances point to a role of actin polymerization in the expression of smooth muscle differentiation marker genes, in concert with serum response factor (SRF) and cofactors, such as myocardin. Stretch of intact venous smooth muscle activates Rho and inhibits the actin filament severing factor cofilin, resulting in increased actin polymerization. Concomitantly, the rates of synthesis of SRF-regulated differentiation markers, such as SM22alpha, calponin, and alpha-actin, are increased. This increase in differentiation signals is parallel with activation of the mitogen-activated protein (MAP) kinase pathway. Thus stretch-induced growth in a maintained contractile phenotype occurs by dual activation of signal pathways regulating both growth and differentiation. A current challenge is to identify sites of crosstalk between these pathways in intact smooth muscle tissue.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".