Sex-related Differences In Cooling Rates After Exercise-induced Hyperthermia
Bibliographic record
Abstract
Ice-water immersion is the most efficient cooling treatment against exercise-induced hyperthermia (EIH). However, sex differences related to body composition may affect cooling rates in hyperthermic individuals. In normothermic individuals, a negative relationship between % body fat and cooling rates has been shown. However, this relationship might not hold true in hyperthermic individuals as redistribution of blood flow and previous heat storage come into play. PURPOSE: To determine sex related differences in cooling rates during ice-water immersion after exercise-induced hyperthermia. METHODS: Six males (M) and six females (F) subjects matched for Body Surface Area/Mass ratio (272.29 cm2/kg ± 22.95 (F) vs. 252.86 cm2/kg ± 15.77 (M), (P> 0.05)) but with different body fat percentage (23% ± 6 (F) vs. 14% ± 3 (M), (P< 0.05)) and different BSA/Lean Body Mass (LBM) ratio (351.92 cm2/kg of LBM ± 17.01 (F) vs. 296.62 cm2/kg of LBM ± 12,79 (M) (P< 0.05)) participated in this study. Subjects exercised at 65% VO2 peak at an ambient temperature of 40°C until rectal temperature (Tre) increased to 39.56°C ± 0.05. Following exercise, subjects were immersed in a 2.4°C ± 0.6 circulated water bath until Tre returned to 37.50 °C. RESULTS: Significant differences (P< 0.05) were found in the overall cooling rates of Tre (0.29°C/min ± 0.15 (F) vs. 0.12°C/min ± 0.02 (M)) and in the overall immersion times (8.42 min ± 3.02 (F) vs. 18.55 min ± 2.43 (M)). Differences also occurred in heat flux during immersion (953 W/m2 ± 146 (F) vs. 771 W/m2 ± 130 (M)). No differences (P> 0.05) were seen in metabolic heat production between groups. CONCLUSIONS: We conclude that previously hyperthermic females have a higher cooling rate compared to males despite a higher % body fat. We attribute this difference to the BSA/LBM ratio, which takes into account the underlying musculature of previously hyperthermic individuals after EIH. Funding for this research is provided by the Natural Sciences and Engineering Research Council of Canada (NSERC).
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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) | 0.002 | 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".