Filament evanescence of myosin II and smooth muscle function
Bibliographic record
Abstract
Smooth muscle is an integral part of hollow organs. Many of them are constantly subjected to mechanical forces that alter organ shape and modify the properties of smooth muscle. To understand the molecular mechanisms underlying smooth muscle function in its dynamic mechanical environment, a new paradigm has emerged that depicts evanescence of myosin filaments as a key mechanism for the muscle's adaptation to external forces in order to maintain optimal contractility. Unlike the bipolar myosin filaments of striated muscle, the side-polar filaments of smooth muscle appear to be less stable, capable of changing their lengths through polymerization and depolymerization (i.e., evanescence). In this review, we summarize accumulated knowledge on the structure and mechanism of filament formation of myosin II and on the influence of ionic strength, pH, ATP, myosin regulatory light chain phosphorylation, and mechanical perturbation on myosin filament stability. We discuss the scenario of intracellular pools of monomeric and filamentous myosin, length distribution of myosin filaments, and the regulatory mechanisms of filament lability in contraction and relaxation of smooth muscle. Based on recent findings, we suggest that filament evanescence is one of the fundamental mechanisms underlying smooth muscle's ability to adapt to the external environment and maintain optimal function. Finally, we briefly discuss how increased ROCK protein expression in asthma may lead to altered myosin filament stability, which may explain the lack of deep-inspiration-induced bronchodilation and bronchoprotection in asthma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".