Mean arterial pressure following prolonged exercise in the heat: <scp>I</scp>nfluence of training status and fluid replacement
Bibliographic record
Abstract
Prolonged exercise in the heat without fluid replacement represents a significant challenge to the regulation of mean arterial pressure (MAP). It is unknown, however, if MAP is equally challenged during the post-exercise period, and whether regular endurance exercise training can provide any benefit to its regulation. We examined MAP (Finometer) in eight trained (T) and eight untrained (UT) individuals prior to, and following, 120 min of cycling at 42 °C with (HYD) and without (DEHY) fluid replacement. Exercise during DEHY induced significant hyperthermia (T: 39.20 ± 0.52 °C vs UT: 38.70 ± 0.36 °C, P = 0.941) and body weight losses (T: 3.4 ± 1.2% vs UT: 2.7 ± 0.9%, P = 0.332), which did not differ between groups. Although MAP was equally reduced 5 min into the post-exercise period of DEHY (T: -20 ± 11 mmHg vs UT: -22 ± 13 mmHg, P = 0.800), its subsequent recovery was significantly different between groups (P = 0.037). While MAP returned to pre-exercise values in UT (-1 ± 3 mmHg), it remained reduced in T (-9 ± 3 mmHg, P = 0.028). No differences in MAP post-exercise were observed between groups during HYD. These data suggest that trained men exhibit a greater level of post-exercise hypotension following prolonged exercise in the heat without fluid replacement. Furthermore, fluid replacement reverses the sustained post-exercise hypotension observed in trained individuals.
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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".