Regulation of Rho/ROCK signaling in airway smooth muscle by membrane potential and [Ca<sup>2+</sup>]<sub>i</sub>
Bibliographic record
Abstract
Recently, we have shown that Rho and Rho-activated kinase (ROCK) may become activated by high-millimolar KCl, which had previously been widely assumed to act solely through opening of voltage-dependent Ca(2+) channels. In this study, we explored in more detail the relationship between membrane depolarization, Ca(2+) currents, and activation of Rho/ROCK in bovine tracheal smooth muscle. Ca(2+) currents began to activate at membrane voltages more positive than -40 mV and were maximally activated above 0 mV; at the same time, these underwent time- and voltage-dependent inactivation. Depolarizing intact tissues by KCl challenge evoked contractions that were blocked equally, and in a nonadditive fashion, by nifedipine or by the ROCK inhibitor Y-27632. Other agents that elevate intracellular calcium concentration ([Ca(2+)](i)) by pathways independent of G protein-coupled receptors, namely the SERCA-pump inhibitor cyclopiazonic acid and the Ca(2+) ionophore A-23187, evoked contractions that were also largely reduced by Y-27632. KCl directly increased Rho and ROCK activities in a concentration-dependent fashion that paralleled closely the effect of KCl on tone and [Ca(2+)](i), as well as the voltage-dependent Ca(2+) currents that were measured over the voltage ranges that are evoked by 0-120 mM KCl. Through the use of various pharmacological inhibitors, we ruled out roles for Ca(2+)/calmodulin-dependent CaM kinase II, protein kinase C, and protein kinase A in mediating the KCl-stimulated changes in tone and Rho/ROCK activities. In conclusion, Rho is activated by elevation of [Ca(2+)](i) (although the signal transduction pathway underlying this Ca(2+) dependence is still unclear) and possibly also by membrane depolarization per se.
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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) | 0.001 | 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".