Associations between potential risk factors and blood-brain barrier water permeability in middle-aged and older adults
Bibliographic record
Abstract
Background: Blood-brain barrier (BBB) dysfunction is suggested to be a potential mediator between vascular risk factors and cognitive impairment, leading to vascular cognitive impairment. Objective: To investigate the relationships between age, sex, and vascular risk factors and BBB water permeability as well as their relationship with cognition. Methods: To measure BBB permeability, a novel arterial spin labelling MRI technique (ME-ASL) was applied to derive the time of exchange (Tex), arterial time transit (ATT), and cerebral blood flow (CBF). The association of potential risk factors, such as age, sex, body mass index (BMI), blood pressure (BP), and medical history, with these BBB parameters were assessed in 144 community-dwelling adults (median age 59 years, 57% females). The relationship between BBB permeability and cognitive performance measured by the Montreal Cognitive Assessment (MoCA) was also assessed. Results: We found that increased BMI was significantly associated with decreased CBF (β = −0.06). Systolic BP and diastolic BP showed significant associations with all ASL parameters; systolic BP was negatively correlated with Tex (β = −0.02) and CBF (β = −0.01) but positively with ATT (β = 0.02). Diastolic BP was negatively associated with Tex (β = −0.03) and CBF (β = −0.03) but positively with ATT (β = 0.03). MoCA scores had a borderline significant association with Tex (OR = 1.51) and a significant association with CBF (OR = 1.84), which became non-significant after adjusting for confounders. Conclusions: These outcomes underscore the potential of using ME-ASL, warranting further research to strengthen these findings.
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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 | 0.001 | 0.001 |
| 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".