Age-related differences in postsynaptic increases in sweating and skin blood flow postexercise
Bibliographic record
Abstract
The influence of peripheral factors on the control of heat loss responses (i.e., sweating and skin blood flow) in the postexercise period remains unknown in young and older adults. Therefore, in eight young (22 ± 3 years) and eight older (65 ± 3 years) males, we examined dose-dependent responses to the administration of acetylcholine (ACh) and methacholine (MCh) for sweating (ventilated capsule), as well as to ACh and sodium nitroprusside (SNP) for cutaneous vascular conductance (CVC, laser-Doppler flowmetry, % of max). In order to assess if peripheral factors are involved in the modulation of thermoeffector activity postexercise, pharmacological agonists were perfused via intradermal microdialysis on two separate days: (1) at rest ( DOSE: ) and (2) following a 30-min bout of exercise ( EX+: DOSE: ). No differences in sweat rate between the DOSE and Ex+DOSE conditions at either ACh or MCh were observed for the young (ACh: P = 0.992 and MCh: P = 0.710) or older (ACh: P = 0.775 and MCh: P = 0.738) adults. Similarly, CVC was not different between the DOSE and Ex+DOSE conditions for the young (ACh: P = 0.123 and SNP: P = 0.893) or older (ACh: P = 0.113 and SNP: P = 0.068) adults. Older adults had a lower sweating response for both the DOSE (ACh: P = 0.049 and MCh: P = 0.006) and Ex+DOSE (ACh: P = 0.050 and MCh: P = 0.029) conditions compared to their younger counterparts. These findings suggest that peripheral factors do not modulate postexercise sweating and skin blood flow in both young and older adults. Additionally, sweat gland function is impaired in older adults, albeit the impairments were not exacerbated during postexercise recovery.
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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".