Impact of age on cerebrovascular dilation versus reactivity to hypercapnia
Bibliographic record
Abstract
This study quantified the effect of age on cerebrovascular reactivity and cerebrovascular conductance while accounting for differences in grey matter volume in younger (YA: n = 12; 24 ± 4 years, six females) and older adults (OA: n = 10; 66 ± 7 years; five females). Cerebral blood flow velocity (CBFV; transcranial Doppler) in the middle cerebral artery (MCA), MCA cross-sectional area (CSA), intracranial volumes (magnetic resonance imaging), and mean arterial pressure (MAP; Finometer), were measured under normocapnic and hypercapnic (6% carbon dioxide) conditions. Cerebral blood flow (CBF) was quantified from CBFV and MCA CSA and normalized to grey matter volume. Grey matter volume was 719 ± 98 mL in YA and 622 ± 50 mL in OA ( P = 0.009). Cerebrovascular reactivity (%ΔCBF/ΔP ET CO 2 ) was not different between YA and OA. In contrast, cerebrovascular conductance (CBF/MAP) in response to hypercapnia was reduced in OA ( P = 0.02). Of note, MAP increased more with hypercapnia in OA compared with YA. Therefore, the central hemodynamic response to hypercapnia compensated for a diminished dilatory response downstream from the MCA so that the CBF response to hypercapnia per unit of brain mass was not affected by age. This impairment was not detected by traditional measures of cerebrovascular reactivity.
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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".