Epac as a novel relaxant factor in airway smooth muscle
Bibliographic record
Abstract
Obstructive airway diseases are characterized by airway narrowing and progressive lung function decline. Elevations of cAMP by β 2 ‐adrenoceptors reverse airway smooth muscle contraction, a process classically assigned to protein kinase A (PKA). Here we report on a novel cAMP mechanism which regulates airway smooth muscle relaxation. Specific activation of Epac (exchange protein directly activated by cAMP) relaxes pre‐contracted guinea pig tracheal open‐rings independent of PKA. Importantly, human airway smooth muscle also expresses Epac and activated Epac relaxes pre‐contracted human airway smooth muscle. Contraction of smooth muscle cells is believed to depend on Rho/Rac balancing. Regulation of cytoskeleton dynamics by Rho increases myosin light chain (MLC) phosphorylation and stress fiber formation, whereas activation of Rac has the opposite effect. Toxin B‐1470‐inhibited Rac1 attenuated in guinea pig tracheal rings Epac‐mediated airway smooth muscle relaxation, suggesting a key role for Rac1 in the relaxing properties of Epac. Indeed, activation of Epac induced GTP‐loading Rac1 and minimized metacholine‐induced stress fiber formation and MCL phosphorylation in airway smooth muscle. We identify Epac as a novel relaxing factor in airway smooth muscle, most likely by shifting the Rho/Rac balance towards Rac1. Therefore, activation of Epac may have therapeutical potential in the treatment of obstructive airway diseases.
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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".