Mechanical Strain Inhibits Airway Smooth Muscle Gene Transcription via Protein Kinase C Signaling
Bibliographic record
Abstract
Mechanical strain affects airway myocyte phenotype, cytoskeletal architecture, proliferation, and contractile function. We hypothesized that (i) short-term mechanical strain modulates transcription of smooth muscle-specific gene promoters for SM22 and smooth muscle myosin heavy chain (smMHC); and (ii) strain-induced change is mediated by altered actin polymerization in association with activation of protein kinase C (PKC). Primary cultured canine tracheal myocytes were transiently transfected with luciferase reporter plasmids harboring a murine SM22, human smMHC, or artificial serum response factor (SRF)-specific gene promoter and then subjected to cyclic strain for 48 h. This strain protocol significantly reduced transcriptional activity of SM22 and smMHC promoters and an artificial SRF-dependent promoter by 55 +/- 5.9%, 57 +/- 6.4%, and 75 +/- 7.9%, respectively, with concomitant reduction in F/G actin ratio by 31 +/- 8%. PKC inhibitors, GF109203X or Gö6976, significantly attenuated these affects. Similar to strain, strain-independent activation of PKC inhibited SM22, smMHC, and SRF-dependent promoter activity by 61 +/- 4%, 66 +/- 5%, and 28 +/- 15%, respectively, and reduced the F/G actin ratio by 30 +/- 5%. Gel shift assay revealed that PKC activation led to decreased binding of the required transcription factor, SRF, to CArG elements in the SM22 promoter. These data suggest a previously unknown role for PKC isoforms in mechanosensitive signaling in airway myocytes that is associated with coordinated regulation of actin cytoskeletal dynamics and smooth muscle-specific gene transcription.
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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 | 0.000 | 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) | 0.000 | 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".