Utilization of the repeated squat-stand model for studying the directional sensitivity of the cerebral pressure-flow relationship
Bibliographic record
Abstract
Abstract Hysteresis in the cerebral pressure-flow relationship describes the superior ability of the cerebrovasculature to buffer cerebral blood flow changes when mean arterial pressure (MAP) acutely increases compared to when MAP acutely decreases. This phenomenon can be evaluated by comparing the change in middle cerebral artery mean blood velocity (MCAv) per change in MAP during either acute increases or decreases in MAP induced by repeated squat-stands (RSS). However, no real baseline can be employed for this particular protocol as there is no true stable reference point. Herein, we characterized a novel metric using the greatest MAP oscillations induced by RSS without using an independent baseline value and adjusted for time intervals (ΔMCAv T /ΔMAP T ). We also examined whether this metric during each RSS transition were comparable between each other over a 5-min period. ΔMCAv T /ΔMAP T was calculated using the minimum to maximum MCAv and MAP for each RSS performed at 0.05 Hz and 0.10 Hz. We compared averaged ΔMCAv T /ΔMAP T during MAP increases and decreases in 74 healthy subjects [9 women; 32 ± 13 years]. ΔMCAv T /ΔMAP T was lower for MAP increases than MAP decreases at 0.10 Hz RSS only (0.91 ± 0.34 vs. 1.01 ± 0.44 cm·s -1 /mmHg; p = 0.0013). For both frequency and MAP direction, time during RSS had no effect on ΔMCAv T /ΔMAP T . This novel analytical method supports the use of the RSS model to evaluate the directional sensitivity of the pressure-flow relationship. These results contribute to the importance of considering the direction of MAP changes when evaluating dynamic cerebral autoregulation. News & Noteworthy Repeated squat-stand maneuvers are able to examine the directional sensitivity of the cerebral pressure-flow relationship. These maneuvers induce stable physiological cyclic changes where brain blood flow changes with blood pressure increases are buffered more than decreases. These results highlight the importance of considering directional blood pressure changes within cerebral autoregulation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".