Voluntary muscle activation is impaired by core temperature rather than local muscle temperature
Bibliographic record
Abstract
Fatigue during hyperthermia may be due in part to a failure of the central nervous system to fully activate the working muscles. We investigated the effects of passive hyperthermia on maximal plantar flexor isometric torque (maximal isometric voluntary contraction) and voluntary activation to determine the roles of local skin temperature, core temperature, and peripheral muscle temperature in fatigue. Nine healthy subjects were passively heated from 37.2 to 39.5 degrees C (core temperature) and then cooled back down to 37.9 degrees C using a liquid-conditioning garment, with the right leg kept at a thermoneutral temperature throughout the protocol, whereas the left leg was allowed to heat and cool. Passive heating resulted in significant decreases in torque from [mean (SD)] 172 N x m (SD 39) to 160 N x m (SD 44) and in voluntary activation from 96% (SD 2) to 91% (SD 5) in the heated leg, and maximal isometric voluntary contraction decreased similarly from 178 N xm (SD 37) to 165 N x m (SD 38) and voluntary activation from 97% (SD 2) to 94% (SD 5) in the thermoneutral leg. The initiation of cooling, which produced a rapid decrease in skin temperature and cardiovascular strain [heart rate reserve decreased from 58% (SD 12) to 31% (SD 12)], did not immediately restore either torque or voluntary activation. However, when core temperature was lowered back to normal, torque and voluntary activation were restored to baseline values. It was concluded that an increase in core temperature is a factor responsible for reducing voluntary activation during brief voluntary isometric contractions and that temperature-induced changes in the contractile properties of muscle and local thermal afferent input from the skin do not contribute significantly to the decrement in torque.
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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".