TRPV4 channel blockade does not modulate skin vasodilation and sweating during hyperthermia or cutaneous postocclusive reactive and thermal hyperemia
Bibliographic record
Abstract
Transient receptor potential vanilloid 4 (TRPV4) channels exist on vascular endothelial cells and eccrine sweat gland secretory cells in human skin. Here, we assessed whether TRPV4 channels contribute to cutaneous vasodilation and sweating during whole body passive heat stress ( protocol 1) and to cutaneous vasodilation during postocclusive reactive hyperemia and local thermal hyperemia ( protocol 2). Intradermal microdialysis was employed to locally deliver pharmacological agents to forearm skin sites, where cutaneous vascular conductance (CVC) and sweat rate were assessed. In protocol 1 (12 young adults), CVC and sweat rate were increased by passive whole body heating, resulting in a body core temperature elevation of 1.2 ± 0.1°C. The elevated CVC and sweat rate assessed at sites treated with TRPV4 channel antagonist (either 200 µM HC-067047 or 125 µM GSK2193874) were not different from the vehicle control site (5% dimethyl sulfoxide). After whole body heating, the TRPV4 channel agonist (100 µM GSK1016790A) was administered to each skin site, eliciting elevations in CVC. Relative to control, this response was partly attenuated by both TRPV4 channel antagonists, confirming drug efficacy. In protocol 2 (10 young adults), CVC was increased following a 5-min arterial occlusion and during local heating from 33 to 42°C. These responses did not differ between the control and the TRPV4 channel antagonist sites (200 µM HC-067047). We show that TRPV4 channels are not required for regulating cutaneous vasodilation or sweating during a whole body passive heat stress. Furthermore, they are not required for regulating cutaneous vasodilation during postocclusive reactive hyperemia and local thermal hyperemia.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".