The mechanisms underlying the muscle metaboreflex modulation of sweating and cutaneous blood flow in passively heated humans
Bibliographic record
Abstract
Abstract Metaboreceptors can modulate cutaneous blood flow and sweating during heat stress but the mechanisms remain unknown. Fourteen participants (31 ± 13 years) performed 1‐min bout of isometric handgrip ( IHG ) exercise at 60% of their maximal voluntary contraction followed by a 3‐min occlusion ( OCC ), each separated by 10 min, initially under low ( LHS , to activate sweating without changes in core temperature) and high ( HHS , whole‐body heating to a core temperature increase of 1.0°C) heat stress conditions. Cutaneous vascular conductance ( CVC ) and sweat rate were measured continuously at four forearm skin sites perfused with 1) lactated Ringer's solution (Control), 2) 10 mmol L‐ NAME [inhibits nitric oxide synthase ( NOS )], 3) 10 mmol Ketorolac [inhibits cyclooxygenase ( COX )], or 4) 4 mmol theophylline ( THEO ; inhibits adenosine receptors). Relative to pre‐ IHG levels with Control, NOS inhibition attenuated the metaboreceptor‐mediated increase in sweating under LHS and HHS ( P ≤ 0.05), albeit the attenuation was greater under LHS ( P ≤ 0.05). In addition, a reduction from baseline was observed with THEO under LHS during OCC ( P ≤ 0.05), but not HHS (both P > 0.05). In contrast, CVC was lower than Control with L‐ NAME during OCC in HHS ( P ≤ 0.05), but not LHS ( P > 0.05). We show that metaboreceptor activation modulates CVC via the stimulation of NOS and adenosine receptors, whereas NOS , but not COX or adenosine receptors, contributes to sweating at all levels of heating.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".