Heterogeneous patterns of vasoreactivity in the middle cerebral and internal carotid arteries
Bibliographic record
Abstract
This study compared changes in cross-sectional area (CSA) and flow (Q) between the middle cerebral artery (MCA) and the internal carotid artery (ICA) at baseline and during 5 min of hypercapnia (HC; 6% CO2) and hypocapnia (HO; hyperventilation) and quantified how these changes contribute to estimates of cerebrovascular reactivity (CVR). Measures of MCA CSA were made using 3T magnetic resonance imaging. On a separate day, MCA flow velocity was measured with transcranial Doppler ultrasound and ICA diameters and flow velocity were measured with duplex ultrasound. Fourteen subjects (23 ± 3 yr, 7 females) participated, providing data for 11 subjects during HC and 9 subjects during HO. An increase in MCA CSA (P < 0.05) was observed within the first minute of HC. During HO, the decrease in MCA CSA (P < 0.05) was delayed until minute 4. No changes were observed in ICA CSA during HC or HO. The relative changes in QICA and QMCA were similar during HC and HO. Therefore, the MCA, but not ICA, dilates and constricts during 5 min of HC and HO, respectively. The consequent impact on QMCA significantly affects estimates of CVR, and reactivity cannot be attributed solely to changes in smaller arterioles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".