G-protein-coupled-receptor activation of the smooth muscle calponin gene
Bibliographic record
Abstract
A hallmark of cultured smooth muscle cells (SMCs) is the rapid down-regulation of several lineage-restricted genes that define their in vivo differentiated phenotype. Identifying factors that maintain an SMC differentiated phenotype has important implications in understanding the molecular underpinnings governing SMC differentiation and their subversion to an altered phenotype in various disease settings. Here, we show that several G-protein coupled receptors [alpha-thrombin, lysophosphatidic acid and angiotensin II (AII)] increase the expression of smooth muscle calponin (SM-Calp) in rat and human SMC. The increase in SM-Calp protein appears to be selective for G-protein-coupled receptors as epidermal growth factor was without effect. Studies using AII showed a 30-fold increase in SM-Calp protein, which was dose- and time-dependent and mediated by the angiotensin receptor-1 (AT1 receptor). The increase in SM-Calp protein with AII was attributable to transcriptional activation of SM-Calp based on increases in steady-state SM-Calp mRNA, increases in SM-Calp promoter activity and complete abrogation of protein induction with actinomycin D. To examine the potential role of extracellular signal-regulated kinase (Erk1/2), protein kinase B, p38 mitogen-activated protein kinase and protein kinase C in AII-induced SM-Calp, inhibitors to each of the signalling pathways were used. None of these signalling molecules appears to be crucial for AII-induced SM-Calp expression, although Erk1/2 may be partially involved. These results identify SM-Calp as a target of AII-mediated signalling, and suggest that the SMC response to AII may incorporate a novel activity of SM-Calp.
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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) | 0.002 | 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".