Influence of stretch magnitude on the stretch-shortening cycle in skinned fibres
Bibliographic record
Abstract
The mechanical work attained during shortening is increased by prior stretching. Recently, we suggested that the residual force enhancement (RFE) may contribute to this enhanced work. RFE can be changed reliably by changing the stretch magnitude. Therefore, the purpose of this study was to examine the effect of stretch magnitude, and by association of RFE, on the mechanics of the stretch-shortening cycle in skinned skeletal muscle fibres. Three tests were performed using skinned rabbit soleus fibres (N=18). The first test was a pure shortening contraction in which fibers were activated and then shortened from an average sarcomere length of 3.3 to 3.0 µm. The second test was a SSC in which fibers were activated and stretched from 3.0 µm to 3.3 µm, and then shortened to 3.0 µm. The third test was a SSC in which fibers were activated and stretched from 2.4 to 3.3, and then shortened to 3.0 µm. The mechanical work during shortening and the force maintained 15 s after the end of shortening were determined. The relative increase in mechanical work with respect to the pure shortening condition, was greater for the large than the small stretch condition (p<0.001). Similarly, the relative increase in force 15 s after the end of shortening was greater for the large than the small stretch condition (p=0.043). We conclude that increasing the magnitude of stretch results in an increase in mechanical work and increased force at steady-state following the stretch, likely because of the greater RFE.
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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) | 0.002 | 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".