Effect of active shortening and stretching on the rate of force re-development in rabbit psoas muscle fibres
Bibliographic record
Abstract
The steady-state isometric force produced by skeletal muscle after active shortening and stretching is depressed and enhanced, respectively, compared with purely isometric force produced at corresponding final lengths and at the same level of activation. One hypothesis proposed to account for these force depression (FD) and force enhancement (FE) properties is a change in cross-bridge cycling kinetics. The rate of cross-bridge attachment (f) and/or cross-bridge detachment (g) may be altered following active shortening and active stretching, leading to FD and FE, respectively. Experiments elucidating cross-bridge kinetics in actively shortened and stretched muscle preparations and their corresponding purely isometric contractions have yet to be performed. The aim of this study was to investigate cross-bridge cycling kinetics of muscle fibres at steady-state following active shortening and stretching. This was done by determining muscle fibre stiffness and rate of active force redevelopment following a quick release-re-stretch protocol (kTR). Applying these measures to equations previously used in the literature for a two-state cross-bridge cycling model (attached/detached cross-bridges) allowed us to determine apparent f and g, the proportion of attached cross-bridges, and the force produced per cross-bridge. kTR, apparent f and g, the proportion of attached cross-bridges and the force produced per cross-bridge were significantly decreased following active shortening compared with corresponding purely isometric contractions, indicating a change in cross-bridge cycling kinetics. Additionally, we showed no change in cross-bridge cycling kinetics following active stretch compared with corresponding purely isometric contractions. These findings suggest that FD is associated with changes in cross-bridge kinetics, whereas FE is not.
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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 | 0.000 |
| 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".