Proteasomal degradation of myocardin is required for its transcriptional activity in vascular smooth muscle cells
Bibliographic record
Abstract
Myocardin is a transcriptional co-activator of serum response factor (SRF) and can be degraded through ubiquitin-proteasome system. Our preliminary studies unexpectedly revealed that accumulation of myocardin in response to proteasome inhibition by MG132 or lactacystin resulted in decrease of transcriptional activity of myocardin as indicated by reduced expression of SMC contractile marker genes (SM α-actin, SM22, and calponin) and muscle-enriched microRNAs (miR-143/145 and miR-1/133a), and reduced contractility of human vascular smooth muscle cells (SMCs) embedded in collagen gel lattices, suggesting that myocardin degradation is required for its transcriptional activity. Further studies using chromatin immunoprecipitation assay revealed that proteasome inhibition, although increased the occupancy of myocardin and SRF on the promoter of SM α-actin gene, abolished myocardin-dependent recruitment of RNA polymerase II. We further examined the degradation of myocardin in epithelioid and spindle-shaped SMCs and revealed that myocardin in more differentiated spindle-shaped SMCs was more quickly degraded and had shorter half-life than in epithelioid SMCs. In neointimal lesions, we found that stabilization of myocardin protein was companied by downregulation of transcripts of ubiquitin and proteasome subunits, further illustrating the mechanism underlying reduction of myocardin transcriptional activity. In summary, our results have suggested that proteasomal degradation of myocardin is required for its transcriptional activity.
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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 | 0.000 |
| 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".