The influence of velocity of stretch–shortening contractions on muscle performance during chronic exposure: age effects
Bibliographic record
Abstract
Aging increases injury susceptibility and impairs the ability to adapt to repetitive exposures of mechanical loading. The objective of this research was to investigate if movement velocity affects muscle response to a chronic administration of stretch-shortening cycles (SSCs) differently in young vs. old rats. Dorsiflexor muscles of old (30 months, n=5) and young rats (12 weeks, n=6) were exposed 3 times/week for 4.5 weeks to a protocol of 80 maximal SSCs per exposure in vivo. Skeletal muscle response was characterized by high- (500 degrees/s) and low- (60 degrees/s) velocity dynamic performance, which was evaluated using peak eccentric force, isometric pre-stretch force, eccentric force enhancement above the isometric pre-stretch force, negative work, and positive work. The performance of the young and old groups was not statistically different at the start of the exposure. By the end of the exposure, however, a statistical difference was noted-performance increased significantly in the young animals and decreased significantly in the old animals. The SSC velocity had a profound effect on muscle response. The young animals' high- and low-velocity performances increased during the chronic exposure period, whereas the old animals' performances declined. High-velocity performance increased more than low-velocity performance in young animals. In contrast, old animals suffered the most loss in high-velocity performance over the chronic exposure period. A chronic exposure of SSCs results in a significant performance increase in young animals, and a significant performance decrease in old animals. These differences are more profound during high-velocity movements. These findings suggest that age may impair the ability of skeletal muscle to adapt to repetitive mechanical loading, particularly during high-velocity movements.
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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 | 0.000 |
| 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".