No influence of steady-state postural changes on cerebrovascular compliance in humans
Bibliographic record
Abstract
The aim of this study was to determine the effect of posture changes on vascular compliance in intracranial (brain) versus extracranial vascular beds (forearm). Eighteen young adults (nine females) performed a supine-to-seated-to-standing protocol involving 5 min of rest in each position. Continuous blood pressure, middle cerebral artery (MCA) blood velocity, and brachial artery blood velocity were recorded at each posture. Three to five consecutive steady-state cardiac cycles at each posture were analyzed by a four-element lumped parameter modified Windkessel model to calculate vascular compliance. Mean arterial pressure (MAP) increased from supine to seated (76(9) vs. 81(12) mmHg; P = 0.006) and from supine to standing (76(9) vs. 82(13) mmHg; P = 0.034). Mean blood flow was greater in the MCA relative to the forearm (forearm: 40(5) mL·min−1, MCA: 224(17) mL·min−1; main effect P < 0.001). Conversely, vascular resistance (forearm: 3.25(0.50) mmHg−1·mL·min−1, brain: 0.36(0.04) mmHg−1·mL·min−1; main effect P < 0.001) and compliance (forearm: 0.010(0.001) mL·min−1·mmHg−1, brain: 0.005(0.001) mL·min−1·mmHg−1; main effect P = 0.001) were greater in the forearm compared to the brain. Significant main effects of posture were observed with decreasing values in upright positions for mean blood flow ( P = 0.001) in both vascular beds, but not for resistance ( P = 0.163) or compliance ( P = 0.385). There were no significant interaction effects between vascular bed and posture for mean flow ( P = 0.057), resistance ( P = 0.258), or compliance ( P = 0.329). This study provides evidence that under steady-state conditions, posture does not affect cerebrovascular compliance.
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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".