Molecular Events of the Crossbridge Cycle Reflected in the Force–Velocity Relationship of Activated Muscle
Bibliographic record
Abstract
Muscles convert chemical energy to mechanical work. Mechanical performance of a muscle is often assessed by the muscle's ability to shorten and generate power over a range of loads or forces, characterized by the force-velocity and force-power relationships. The hyperbolic force-velocity relationship of muscle, for a long time, has been regarded as a pure empirical description of the force-velocity data. Connections between mechanical manifestation in terms of force-velocity properties and the kinetics of the crossbridge cycle have only been established recently. In this review, we describe how the model of Huxley's crossbridge kinetics can be transformed to the hyperbolic Hill equation, and link the changes in force-velocity properties to molecular events within the crossbridge cycle driven by ATP hydrolysis. This allows us to reinterpret some findings from previous studies on experimental interventions that altered the force-velocity relationship and gain further insight into the molecular mechanisms of muscle contraction under physiological and pathophysiological conditions.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".