Effect of short-term exercise-heat acclimation on ventilatory and cerebral blood flow responses to passive heating at rest in humans
Bibliographic record
Abstract
Hyperthermia induces hyperventilation and cerebral hypoperfusion in resting humans. We tested the hypothesis that short-term exercise-heat acclimation would alleviate those effects. Twenty healthy male subjects were divided into two groups that performed exercise training in the heat (TR-HEAT, n = 10) or cold (TR-COLD, n = 10). Before and after the training, the subjects in both groups participated in passive-heat tests at rest. Training was performed at 37°C (TR-HEAT) or 10°C (TR-COLD) and entailed four 20-min bouts of cycling at 50% peak oxygen uptake separated by 10-min recoveries daily for 6 consecutive days. After TR-HEAT, esophageal temperature was lowered when measured before and during passive heating, as was the esophageal temperature threshold for cutaneous active vasodilation, whereas plasma volume was increased (all P < 0.05). These traditional indices of successful heat acclimation were not all induced by TR-COLD (all P > 0.05). TR-HEAT had no significant effect on passive heating-induced increases in minute ventilation, even when evaluated as the esophageal temperature threshold for increases in minute ventilation and the slope relating minute ventilation to esophageal temperature (all P > 0.05). By contrast, TR-HEAT attenuated the passive heating-induced reduction in the cerebral vascular conductance index (middle cerebral artery mean blood velocity/mean arterial pressure) (all P < 0.05). TR-COLD did not attenuate the increase in minute ventilation or the decrease in the cerebral vascular conductance index observed during passive heating (all P > 0.05). These data suggest that in resting heated humans, short-term heat acclimation achieved through moderate-intensity exercise training (i.e., 50% peak oxygen uptake) in the heat does not influence hyperthermia-induced hyperventilation, but it does potentially attenuate cerebral hypoperfusion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".