Acetylcholine-induced phosphorylation of CPI-17 in rat bronchial smooth muscle: the roles of Rho-kinase and protein kinase C
Bibliographic record
Abstract
It has been demonstrated that CPI-17 provokes an inhibition of myosin light chain phosphatase to increase myosin light chain phosphorylaton and Ca(2+) sensitivity during contraction of vascular smooth muscle. However, expression and agonist-mediated regulation of CPI-17 in bronchial smooth muscle have not been documented. Thus, expression and phosphorylation of CPI-17 mediated by PKC and ROCK were investigated using rat bronchial preparations. Acetylcholine (ACh)-induced contraction and Ca(2+) sensitization were both attenuated by 10(-6) mol Y-27632 /L, a ROCK inhibitor, 10(-6) mol calphostin C/L, a PKC inhibitor, and their combination. A PKC activator, PDBu, induced a Ca(2+) sensitization in alpha-toxin-permeabilized bronchial smooth muscle. In this case, the Ca(2+) sensitizing effect was significantly inhibited by caphostin C but not by Y-27632. An immunoblot study demonstrated CPI-17 expression in the rat bronchial smooth muscle. Acetylcholine induced a phosphorylation of CPI-17 in a concentration-dependent manner, which was significantly inhibited by Y-27632 and calphostin C. In conclusion, these data suggest that both PKC and ROCK are involved in force development, Ca(2+) sensitization, and CPI-17 phosphorylation induced by ACh stimulation in rat bronchial smooth muscle. As such, RhoA/ROCK, PKC/CPI-17, and RhoA/ROCK/CPI pathways may play important roles in the ACh-induced Ca(2+) sensitization of bronchial smooth muscle contraction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".