Larger reductions in blood pressure during post‐exercise standing, but not middle cerebral artery blood velocity, in resistance‐trained versus untrained individuals
Bibliographic record
Abstract
Abstract Dynamic resistance exercise (RE) produces sinusoidal fluctuations in blood pressure, with hypotension and cerebral hypoperfusion commonly observed immediately following RE. Whether the cerebral vasculature adapts to these regular blood pressure challenges is unclear. This study examined the cerebrovascular response to post‐dynamic RE orthostasis. RE‐trained (n = 15, female = 4) and healthy untrained individuals (n = 15, female = 12) completed five stands: one after seated rest, with each of the subsequent four stands occurring immediately following a set of 10 repetitions of unilateral leg extension exercise at 60% of their one repetition maximum. Beat‐to‐beat blood pressure, mean middle cerebral artery blood velocity (MCAvmean) and end‐tidal carbon dioxide were measured throughout. During standing the mean arterial blood pressure (MAP) and MCAvmean nadirs were identified. There was no difference between groups for age (mean ± SD, 26 ± 7 RE‐trained vs. 25 ± 6 years untrained, P = 0.683) or weight (78 ± 15 vs. 71 ± 15 kg, P = 0.683). At MAP nadir during the post‐exercise stand, a greater reduction in MAP was observed in the RE‐trained group (e.g., set 4, −45 ± 11 vs. −36 ± 6 mmHg, training effect P = 0.026). However, post‐exercise stand MCAvmean at MCAvmean nadir was not different (e.g., set 4, −20 ± 7 vs. −17 ± 6 cm/s, interaction effect P = 0.478). Rate of regulation was higher in the RE‐trained group (set 1, 0.301 ± 0.170 vs. 0.167 ± 0.009, training effect P = 0.023). Despite RE‐trained individuals demonstrating greater absolute reductions in MAP during orthostasis following RE, there were no differences in MCAvmean, suggesting that habitual RE may mitigate post‐exercise cerebral hypoperfusion.
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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".