Caffeine relaxes smooth muscle through actin depolymerization
Bibliographic record
Abstract
Caffeine is sometimes used in cell physiological studies to release internally stored Ca(2+). We obtained evidence that caffeine may also act through a different mechanism that has not been previously described and sought to examine this in greater detail. We ruled out a role for phosphodiesterase (PDE) inhibition, since the effect was 1) not reversed by inhibiting PKA or adenylate cyclase; 2) not exacerbated by inhibiting PDE4; and 3) not mimicked by submillimolar caffeine nor theophylline, both of which are sufficient to inhibit PDE. Although caffeine is an agonist of bitter taste receptors, which in turn mediate bronchodilation, its relaxant effect was not mimicked by quinine. After permeabilizing the membrane using β-escin and depleting the internal Ca(2+) store using A23187, we found that 10 mM caffeine reversed tone evoked by direct application of Ca(2+), suggesting it functionally antagonizes the contractile apparatus. Using a variety of molecular techniques, we found that caffeine did not affect phosphorylation of myosin light chain (MLC) by MLC kinase, actin-filament motility catalyzed by MLC kinase, phosphorylation of CPI-17 by either protein kinase C or RhoA kinase, nor the activity of MLC-phosphatase. However, we did obtain evidence that caffeine decreased actin filament binding to phosphorylated myosin heads and increased the ratio of globular to filamentous actin in precontracted tissues. We conclude that, in addition to its other non-RyR targets, caffeine also interferes with actin function (decreased binding by myosin, possibly with depolymerization), an effect that should be borne in mind in studies using caffeine to probe excitation-contraction coupling in smooth muscle.
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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 | 0.000 |
| 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".