Influence of Aerobic Fitness on Thermoregulation During Exercise in the Heat
Bibliographic record
Abstract
Dear Editor-in-Chief: We wish to challenge some of the expressed views in the review by Dr. Mora-Rodriguez entitled, “Influence of Aerobic Fitness on Thermoregulation during Exercise in the Heat” (3). Dr. Mora-Rodriguez stated that “contrary to what often is believed, aerobically trained individuals do not withstand higher core temperatures before fatiguing than untrained individuals” (3), supporting this statement with data that revealed no relationship between V˙O2max and final Tre tolerated for 17 active soldiers (4). Dr. Mora-Rodriguez suggested that others have questioned this finding, where reference was made to our efforts to define the impact of fitness and body fatness on tolerance to uncompensable heat stress (5). It needs to be emphasized that this study was specifically designed to test the effect of fitness on tolerance and grouped participants into active and inactive categories because earlier work observed differences in Tre tolerated between endurance-trained and untrained individuals, regardless of their state of heat acclimation or hydration (1). Subsequently, we demonstrated large differences in Tre tolerated between trained and untrained individuals during our efforts to characterize the immunoinflammatory cascade during exertional heat stress (6). It is important to highlight that as our understanding of factors that influenced tolerance to heat stress increased, our ethical ceiling for limits to final Tre slowly increased from 39.3°C (1) to 39.5°C (5) and finally to 40.0°C (6). When all 32 endurance-trained and 30 untrained participant data are analyzed together, the final Tre tolerated for the endurance-trained individuals continued to increase significantly as the ethical ceilings were raised, whereas no significant changes were observed for the untrained individuals (1,5,6). Overall, we believe that there is clear evidence that aerobic fitness enhances thermotolerance. There are pronounced adaptations that accompany aerobic exercise to account for the higher thermotolerance of endurance-trained individuals who were not discussed by Dr. Mora-Rodriguez (3). Their expanded plasma volume confers greater protection from gut endotoxin leakage as thermal strain rises (6). Cellular adaptations related to the expression of heat stress proteins and cytokine profiles reduce the impact of increasing thermal strain and help maintain gastrointestinal barrier integrity (6,7). Also, because a given absolute level of thermal strain represents a lower relative strain, key neuroendocrine markers are reduced (8,9). Dr. Mora-Rodriguez also proposed “that absolute heat production will have a greater influence on core body temperature during exercise of longer duration and/or higher intensities” and that “absolute intensity is a better predictor in an uncompensable heat stress situation” (3). We find this statement strange because this hypothesis is not new and was defined in a review by Cheung et al. (2) based on our studies that revealed differential effects of rehydration, heat acclimation, and vapor pressure on thermotolerance during light versus heavy work. As shown in Mora-Rodriguez’s figure 4, there are clear differences between compensable and uncompensable heat stress that cloud the interpretation of the responses between endurance-trained and untrained individuals (3). However, the greatest effects on thermotolerance are the adaptations obtained during endurance training, which includes key adaptive changes to the physiological, immunological, and neuroendocrine systems. We would welcome an open dialogue with Dr. Mora-Rodriguez to address our concerns. Tom M. McLellan Defence Research and Development Canada Toronto, Ontario, Canada Stephen S. Cheung Glen A. Selkirk Department of Kinesiology Brock University St. Catharines, Ontario, Canada Heather E. Wright Faculty of Health Sciences University of Ottawa Ottawa, Ontario, Canada
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".