Fatigue-Induced Reductions of Torque and Shortening Velocity Are Muscle Dependent
Bibliographic record
Abstract
INTRODUCTION: In addition to torque (force) loss during dynamic fatiguing contractions, an important aspect of fatigue is the reduction in shortening velocity. Relatively few reports have studied changes in shortening velocity in response to fatigue, and inconsistencies in the results might depend on the muscle tested. To better understand fatigue-related changes in shortening velocity in different muscles, we compared the fatigue response of two muscles in humans with different physiological properties using the same criterion for task failure. METHODS: During separate sessions for the triceps brachii and soleus, 10 young males performed repetitive shortening contractions with a moderate load (50% of maximum voluntary isometric contraction (MVC) torque) until they achieved a 50% reduction in loaded shortening velocity at task failure. RESULTS: In the unfatigued condition, these muscles expressed different physiological features with similar power output but approximately 1.5 times slower shortening velocity, approximately 1.4 times slower normalized evoked 50-Hz maximum rate of relaxation, and approximately 47% lower postactivation potentiation in the soleus compared with the triceps brachii. During the fatiguing task, significantly less total work was performed in the soleus ( approximately 1986 J) compared with the triceps brachii ( approximately 3940 J), suggesting greater endurance in the triceps brachii. Despite similar relative reductions in shortening velocity in both muscles at task failure, the soleus had a smaller reduction in MVC torque than the triceps brachii at task failure. Furthermore, in both muscles, there was a greater reduction at task failure and a faster restoration of shortening velocity compared with MVC torque. CONCLUSION: Our findings suggest that fatigue-related mechanisms that reduce torque are not the same as those that reduce shortening velocity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".