Hyperthermia modifies muscle metaboreceptor and baroreceptor modulation of heat loss in humans
Bibliographic record
Abstract
The relative influence of muscle metabo- and baroreflex activity on heat loss responses during post-isometric handgrip (IHG) exercise ischemia remains unknown, particularly under heat stress. Therefore, we examined the separate and integrated influences of metabo- and baroreceptor-mediated reflex activity on sweat rate and cutaneous vascular conductance (CVC) under increasing levels of hyperthermia. Twelve men performed 1 min of IHG exercise at 60% of maximal voluntary contraction followed by 2 min of ischemia with simultaneous application of lower body positive pressure (LBPP, +40 mmHg), lower body negative pressure (LBNP, -20 mmHg), or no pressure (control) under no heat stress. On separate days, trials were repeated under heat stress conditions of 0.6°C (moderate heat stress) and 1.4°C (high heat stress) increase in esophageal temperature. For all conditions, mean arterial pressure was greater with LBPP and lower with LBNP than control during ischemia (all P ≤ 0.05). No differences in sweat rate were observed between pressure conditions, regardless of the level of hyperthermia (P > 0.05). Under moderate heat stress, no differences in CVC were observed between pressure conditions. However, under high heat stress, LBNP significantly reduced CVC by 21 ± 4% (P ≤ 0.05) and LBPP significantly elevated CVC by 14 ± 5% (P ≤ 0.05) relative to control. These results show that sweating during post-IHG exercise ischemia is activated by metaboreflex stimulation, and not by baroreflexes. In contrast, our results suggest that baroreflexes can influence the metaboreflex modulation of CVC, but only at greater levels of hyperthermia.
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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 | 0.000 |
| 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".