Aerobic Influence on Neuromuscular Function and Tolerance during Passive Hyperthermia
Bibliographic record
Abstract
PURPOSE: To determine the role of aerobic fitness on central neuromuscular activation and maximal voluntary contractile force during hyperthermia. METHODS: Thirty-seven healthy males in three distinct groups based on aerobic fitness and training history were passively heated using a liquid conditioning garment in a hot (35 degrees C, 50% RH) environment with the intention of testing neuromuscular function with whole-body hyperthermia. Of these initial participants, 11 of the 13 highly fit (HF; VO2max = 71.2 +/- 5.9 mL x kg(-1) x min(-1), body fat = 5.6 +/- 1.9%), 11 of the 13 moderately fit (MF; 57.2 +/- 4.2 mL x kg(-1) x min(-1), 11 +/- 3.4%), and 4 of the 11 lower-fit (LF; 49.6 +/- 1.1 mL x kg(-1) x min(-1), 19.4 +/- 2.6%) individuals tolerated heating to 39.0 degrees C, with the remainder terminating the experimental protocol early. Maximal force output and voluntary activation were examined during a 10-s maximal isometric knee extension. RESULTS: Passive heating attenuated force production (-61.7 +/- 69.6 N change from initial values) and decreased voluntary activation (8.6 (12.6), 18.1 (12.4), and 6.1 (3.1)% for HF, MF, and LF training groups, respectively). Cardiovascular strain moderately increased to 60 +/- 14% (P < 0.001), whereas HF and MF had significantly higher MAP than LF at the end of heating (98 +/- 15, 99 +/- 7, and 79 +/- 5 mm Hg for HF, MF, and LF, respectively; P < 0.05). However, the ability to tolerate passive heating to 39.0 degrees C (and above) differed between the HF and MF compared with LF, despite no difference in their psychophysical rankings of thermal sensations and/or (dis)comfort. CONCLUSION: Low aerobic fitness and activity level are associated with a decreased tolerance to passive hyperthermia. However, at high body temperatures, maximum force production and voluntary activation were impaired to an equal level regardless of training status.
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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".