Influence of Posture on the Regulation of Cerebral Perfusion
Bibliographic record
Abstract
BACKGROUND: Posture has a major influence on cerebral blood flow (CBF). Unlike head-up tilt (HUT), less is known about how CBF is regulated during head-down tilt (HDT). We hypothesized that CBF would be elevated during HDT and decreased during HUT. METHODS: In 21 healthy young adults, while controlling for end-tidal Pco2, we combined concurrent measurements of middle cerebral artery velocity and posterior cerebral artery velocity (MCAv and PCAv, respectively), blood pressure (BP), and heart rate (HR). Measures were made at rest and, in a randomized order, during -90 degrees HDT and +900 HUT. Dynamic cerebral autoregulation was quantified using transfer function analysis. In a subgroup, volumetric blood flow recordings were obtained in the common carotid artery (CCA; N=11), internal and external carotid arteries (ICA; N=8 and ECA; N=6), and vertebral artery (VA; N=4). RESULTS: End-tidal Pco2, CCA, ICA, VA, MCAv(mean) and PCAv(mean) remained unchanged during -90 degrees HDT and +90 degrees HUT compared to supine. During -90 degrees HDT, mean BP (+22 mmHg) and cerebral vascular resistance (CVR) in both the MCA and PCA were elevated relative to supine, whereas HR remained unchanged. During +900 HUT, when compared to supine, HR increased (+18 bpm), and mean arterial pressure (MAP) total power and low frequency (LF) power in the MCA and PCA increased. In both the very low frequency (VLF) and LF ranges, coherence during +90 degrees HUT increased (P < 0.05 vs. supine) in both the MCA and PCA. In contrast, coherence was reduced during -90 degrees HDT. DISCUSSION: Despite marked changes in perfusion pressure with HUT or HDT, our findings indicate that cerebral perfusion is well maintained during acute severe changes in posture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".