The effects of length on fatigue and twitch potentiation in human skeletal muscle
Bibliographic record
Abstract
Fatigue is the decrease in active force that happens after repeated muscle stimulation, and post tetanic twitch potentiation (PTP) is the increase in twitch force observed after repeated muscle stimulation. This study investigated the effects of length on the interaction between fatigue and PTP, as these two forms of force regulation are length-dependent and may coexist. A total number of 14 subjects were tested in 3 days, in which fatigue and PTP were induced in the knee extensor muscles in three different knee angles (30 degrees, 60 degrees and 90 degrees; full extension = 0 degree). PTP was evaluated in rested and fatigued muscles with twitch contractions elicited before and after 10 s maximal voluntary contraction (MVC), and fatigue was evaluated with nine 50 Hz electrically elicited contractions (5 s duration, 5 s interval between contractions). Fatigue was length-dependent, with force values that were (mean +/- SEM) 59 +/- 5, 56 +/- 3 and 38 +/- 1% of maximal force at 90 degrees, 60 degrees and 30 degrees, respectively. PTP was also length-dependent. Rested muscles showed PTP of 39 +/- 4, 47 +/- 2 and 68 +/- 5% at 90 degrees, 60 degrees and 30 degrees, respectively. Fatigued muscles showed PTP of 44 +/- 3, 55 +/- 6 and 68 +/- 5%, at 90 degrees, 60 degrees and 30 degrees, respectively. This study shows that fatigue and PTP may represent independent mechanisms, as they regulate force in opposite directions and are both enhanced in short muscle lengths.
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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".