The effect of endothelin A and B receptor blockade on cutaneous vascular and sweating responses in young men during and following exercise in the heat
Bibliographic record
Abstract
During exercise, cutaneous vasodilation and sweating responses occur, whereas these responses rapidly decrease during postexercise recovery. We hypothesized that the activation of endothelin A (ETA) receptors, but not endothelin B (ETB) receptors, attenuate cutaneous vasodilation during high-intensity exercise and contribute to the subsequent postexercise suppression of cutaneous vasodilation. We also hypothesized that both receptors increase sweating during and following high-intensity exercise. Eleven men (24 ± 4 yr) performed an intermittent cycling protocol consisting of two 30-min bouts of moderate- (40% V̇o2peak) and high-intensity (75% V̇o2peak) exercise in the heat (35°C), each separated by a 20- and 40-min recovery period, respectively. Cutaneous vascular conductance (CVC) and sweat rate were evaluated at four intradermal microdialysis skin sites: 1) lactated Ringer (control), 2) 500 nM BQ123 (a selective ETA receptor blocker), 3) 300 nM BQ788 (a selective ETB receptor blocker), or 4) a combination of BQ123 + BQ788. There were no between-site differences in CVC during each exercise bout (all P > 0.05); however, CVC following high-intensity exercise was greater at BQ123 (56 ± 9%max) and BQ123 + BQ788 (55 ± 14%max) sites relative to the control site (43 ± 12%max) (all P ≤ 0.05). Sweat rate did not differ between sites throughout the protocol (all P > 0.05). We show that neither ETA nor ETB receptors modulate cutaneous vasodilation and sweating responses during and following moderate- and high-intensity exercise in the heat, with the exception that ETA receptors may partly contribute to the suppression of cutaneous vasodilation following high-intensity exercise.
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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".