Do metaboreceptors alter heat loss responses following dynamic exercise?
Bibliographic record
Abstract
Metaboreceptor activation during passive heating is known to influence cutaneous vascular conductance (CVC) and sweat rate (SR). However, whether metaboreceptors modulate the suppression of heat loss following dynamic exercise remains unclear. On separate days, before and after 15 min of high-intensity treadmill running in the heat (35°C), eight males underwent either 1) no isometric handgrip exercise (IHG) or ischemia (CON), 2) 1 min IHG (60% of maximum, IHG), 3) 1 min IHG followed by 2 min of ischemia (IHG+OCC), 4) 2 min of ischemia (OCC), or 5) 1 min IHG followed by 2 min of ischemia with application of lower body negative pressure (IHG+LBNP). SR (ventilated capsule), cutaneous blood flow (Laser-Doppler), and mean arterial pressure (Finometer) were measured continuously before and after dynamic exercise. Following dynamic exercise, CVC was reduced with IHG exercise (P < 0.05) and remained attenuated with post-IHG ischemia during IHG+OCC relative to CON (39 ± 2 vs. 47 ± 6%, P < 0.05). Furthermore, the reduction in CVC was exacerbated by application of LBNP during post-IHG ischemia (35 ± 3%, P < 0.05) relative to IHG+OCC. SR increased during IHG exercise (P < 0.05) and remained elevated during post-IHG ischemia relative to CON following dynamic exercise (0.94 ± 0.15 vs. 0.53 ± 0.09 mg·min(-1)·cm(-2), P < 0.05). In contrast, application of LBNP during post-IHG ischemia had no effect on SR (0.93 ± 0.09 mg·min(-1)·cm(-2), P > 0.05) relative to post-IHG ischemia during IHG+OCC. We show that CVC is reduced and that SR is increased by metaboreceptor activation following dynamic exercise. In addition, we show that the metaboreflex-induced loading of the baroreceptors can influence the CVC response, but not the sweating response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".