Force recovery after activated shortening in whole skeletal muscle: transient and steady-state aspects of force depression
Bibliographic record
Abstract
The depression of isometric force after active shortening is a well-accepted characteristic of skeletal muscle, yet its mechanisms remain unknown. Although traditionally analyzed at steady state, transient phenomena caused, at least in part, by cross-bridge kinetics may provide novel insight into the mechanisms associated with force depression (FD). To identify the transient aspects of FD and its relation to shortening speed, shortening amplitude, and muscle mechanical work, in situ experiments were conducted in soleus muscle-tendon units of anesthetized cats. The period immediately after shortening, in which force recovers toward steady state, was fit by using an exponential recovery function (R2 > 0.99). Statistical analyses revealed that steady-state FD (FD(ss)) increased with shortening amplitude and mechanical work. This FD(ss) increase was always accompanied by a significant decrease in force recovery rate. Furthermore, a significant reduction in stiffness was observed after all activated shortenings, presumably because of a reduced proportion of attached cross bridges. These results were interpreted with respect to the two most prominent proposed mechanisms of force depression: sarcomere length nonuniformity theory (7, 32) and a stress-induced inhibition of cross-bridge binding in the newly formed actin-myosin overlap zone (14, 28). We hypothesized that the latter could describe both steady-state and transient aspects of FD using a single scalar variable, the mechanical work done during shortening. As either excursion (overlap) or force (stress) is increased, mechanical work increases, and cross-bridge attachment would become more inhibited, as supported by this study in which an increase in mechanical work resulted in a slower recovery to a more depressed steady-state force.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".