Influence of cardiovascular risk-factors on morphological changes of cerebral arteries in healthy adults across the life span
Bibliographic record
Abstract
Cerebral artery morphological alterations have been associated with several cerebrovascular and neurological diseases, whereas these structures are known to be highly variable among healthy individuals. To date, the knowledge about the influence of cardiovascular risk factors on the morphology of cerebral arteries is rather limited. The aim of this work was to investigate the impact of cardiovascular risk factors on the regional cerebroarterial radius and density. Time-of-Flight magnetic resonance angiography from 1722 healthy adults (21-82 years) were used to extract region-specific measurements describing the main cerebral artery morphology. Multivariate statistical analysis was conducted to quantify the impact of cardiovascular risk factors, including clinical and life behavioural factors, on each region-specific artery measurement. Increased age, blood pressure, and markers of obesity were significantly associated with decreased artery radius and density in most regions, with aging having the greatest impact. Additionally, females showed significantly higher artery density while males showed higher artery radius. Smoking and alcohol consumption did not show any significant association with the artery morphology. The results of this study improve the understanding of the impact of aging, clinical factors, and life behavioural factors on cerebrovascular morphology and can help to identify potential risk factors for cerebrovascular and neurological diseases.
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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".