Upright LBPP application attenuates elevated postexercise resting thresholds for cutaneous vasodilation and sweating
Bibliographic record
Abstract
We evaluated postexercise venous pooling as a factor leading to previously reported increases in the postexercise esophageal temperature threshold for cutaneous vasodilation (ThVD) and sweating (ThSW). Six subjects were randomly exposed to lower body positive pressure (LBPP) and to no LBPP after an exercise and no-exercise treatment protocol. The exercise treatment consisted of 15 min of upright cycling at 65% of peak oxygen consumption, and the no-exercise treatment consisted of 15 min upright seated rest. Immediately after either treatment, subjects donned a liquid-conditioned suit used to regulate mean skin temperature and then were positioned within an upright LBPP chamber. The suit was first perfused with 20 degrees C water to control and stabilize skin and core temperature before whole body heating. Subsequently the skin was heated ( approximately 4.0 degrees C/h) until cutaneous vasodilation and sweating occurred. Forearm skin blood flow and arterial blood pressure were measured noninvasively and were used to calculate cutaneous vascular conductance during whole body heating. Sweat rate response was estimated from a 5.0-cm2 ventilated capsule placed on the upper back. Postexercise ThVD and ThSW were both significantly elevated (0.27 +/- 0.04 degrees C and 0.25 +/- 0.04 degrees C, respectively) compared with the no-exercise trial without LBPP (P < 0.05). However, the postexercise increases in both ThVD and ThSW were reversed with the application of LBPP. Our results support the hypothesis that the postexercise warm thermal responses of cutaneous vasodilation and sweating are attenuated by baroreceptor modulation via lower body venous pooling.
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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".