Comparable blood velocity changes in middle and posterior cerebral arteries during and following acute high‐intensity exercise in young fit women
Bibliographic record
Abstract
The cerebral blood flow response to high-intensity interval training (HIIT) remains unclear. HIIT induces surges in mean arterial pressure (MAP), which could be transmitted to the brain, especially early after exercise onset. The aim of this study was to describe regional cerebral blood velocity changes during and following 30 s of high-intensity exercise. Ten women (age: 27 ± 6 years; VO2max: 48.6 ± 3.8 ml·kg·min−1) cycled for 30 s at the workload reached at O2max followed by 3min of passive recovery. Middle (MCAvmean) and posterior cerebral artery mean blood velocities (PCAvmean; transcranial Doppler ultrasound), MAP (finger photoplethysmography), and end-tidal carbon dioxide partial pressure (PETCO2; gaz analyzer) were measured. MCAvmean (+19 ± 10%) and PCAvmean (+21 ± 14%) increased early after exercise onset, returning toward baseline values afterward. MAP increased throughout exercise (p < .0001). PETCO2 initially decreased by 3 ± 2 mmHg (p < .0001) before returning to baseline values at end-exercise. During recovery, MCAvmean (+43 ± 15%), PCAvmean (+42 ± 15%), and PETCO2 (+11 ± 3 mmHg; p < .0001) increased. In young fit women, cerebral blood velocity quickly increases at the onset of a 30-s exercise performed at maximal workload, before returning to baseline values through the end of the exercise. During recovery, cerebral blood velocity augments in both arteries, along with PETCO2.
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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 | 0.001 |
| 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".