Intradermal administration of atrial natriuretic peptide has no effect on sweating and cutaneous vasodilator responses in young male adults*
Bibliographic record
Abstract
Atrial natriuretic peptide (ANP) increases during exercise in the heat wherein heat loss responses of sweating and cutaneous vasodilatation are activated. Hence ANP might be involved in the regulation of sweating and cutaneous vasodilatation. However, whether ANP directly mediates sweating and cutaneous vasodilatation needs to be clarified. Also, muscarinic receptor activation induces sweating and cutaneous vasodilatation, however, it remains to be determined whether ANP modulates these responses. In this study, in 11 young males (25 ± 5 years), cutaneous vascular conductance and sweat rate were assessed at intradermal microdialysis sites that were continuously perfused with either lactated Ringer (Control) or 3 different concentrations of ANP (0.1, 1, 10 µM). All 4 sites were co-administrated with methacholine, a muscarinic receptor agonist, in a dose-dependent fashion (0.0125, 0.25, 5, 100, and 2000 mM, 25 min for each). ANP at all concentrations did not increase sweat rate and cutaneous vascular conductance as compared with pre-ANP infusion values (all P > 0.05). Methacholine increased both sweat rate and cutaneous vascular conductance (all P ≤ 0.05). However, the responses were unaffected by co-administration of ANP relative to methacholine only, even as assessed in context of the methacholine concentration required to elicit 50% of the maximal response (EC50) (all P > 0.05). We show that exogenous ANP administration intradermally does not directly modulate sweating and cutaneous vasodilatation under room temperature conditions in resting young adults. Further, there is no effect of ANP on muscarinic sweating and cutaneous vasodilatation.
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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) | 0.002 | 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".