Protocol-dependence of middle cerebral artery dilation to modest hypercapnia
Bibliographic record
Abstract
Abstract There is a need for improved understanding of how different cerebrovascular reactivity (CVR) protocols affect vascular cross-sectional area (CSA) when measures of vascular CSA are not feasible. In human participants, we delivered ~±4mmHg end-tidal partial pressure of CO 2 (PETCO 2 ) relative to baseline through controlled delivery, and measured changes in middle cerebral artery (MCA) cross-sectional area (CSA; magnetic resonance imaging (7 Tesla MRI)), blood velocity (transcranial Doppler and Phase contrast MRI), and calculated CVR based on steady-state versus a ramp protocol during two protocols: a 3-minute steady-state (+4mmHg PETCO 2 ) and a ramp (delta of −3 to +4mmHg of PETCO 2 ). We observed that 1) the MCA did not dilate during the ramp protocol, but did dilate during steady-state hypercapnia, and 2) MCA blood velocity CVR was similar between ramp and steady-state hypercapnia protocols, although calculated MCA blood flow CVR was greater during steady-state hypercapnia than during ramp, the discrepancy due to MCA CSA changes during steady-state hypercapnia. Due to the ability to achieve similar levels of MCA blood velocity CVR as steady-state hypercapnia, the lack of change in MCA cross-sectional area, and the minimal expected change in blood pressure, we propose that a ramp model, across a delta of ~−3 to +4mmHg PETCO 2 , may provide one alternative approach to collecting CVR measures in young adults with TCD when CSA measures are not feasible.
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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 | 0.003 |
| 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 | 0.001 |
| 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".