Vascular and Microstructural Markers of Cognitive Pathology
Bibliographic record
Abstract
Abstract Background Arterial stiffness may play a role in the development of dementia, presumably through its effects on white matter integrity and hyperintensities (WMH). However, relationships among arterial stiffness, white matter microstructure, and WMH volumes remain poorly understood. Arterial stiffness increases monotonically with age and its increase is accelerated by cardiometabolic disorders (e.g., hypertension , metabolic syndrome, diabetes). Further exploration of these relationships is key to the development of targeted therapies, early management, and detection. Method Arterial stiffness was measured using carotid‐femoral pulse wave velocity (cfPWV) in ADRC participants with baseline systolic blood pressure (SBP) measurements, detailed cognitive testing, cognitive adjudication, and brain MRI. We examined associations of cfPWV and SBP with cognitive function (Montreal Cognitive Assessment [MoCA], Preclinical Alzheimer’s Cognitive Composite [PACC5], and domain measures of memory and executive function) and brain MRI measures of: macrostructure (volume of gray matter [GM] and WMH from T1‐weighted and FLAIR imaging), white matter microstructure (neurite orientation dispersion and density imaging [NODDI] free water [FW] and diffusion tensor imaging [DTI] fractional anisotropy [FA]), and cerebral blood flow (CBF) in white matter (WM) and GM. Age, race, gender, education, and APOE‐4 status were included as covariates and in interaction terms in linear regression analyses. Result Among 458 participants with a mean age 70±8 years and cognitive adjudication (44 dementia, 157 MCI, 257 normal cognition; Table 1), higher cfPWV was associated with worse cognitive performance (MoCA, PACC5), as was SBP (MoCA, PACC5, executive domain, language domain; Table 2). Higher cfPWV was associated with differences in WM microstructure (higher FW, lower FA) and higher WMH volume. While no overall associations between cfPWV and CBF were detected, cfPWV had stronger associations with FW, FA, and WMH in men. Higher SBP was associated with higher FW, higher WMH volume, and lower WM and GM CBF (Table 3). SBP had stronger associations with WMH in younger participants (<70y) and GM CBF in Black/AA participants and participants with impaired fasting glucose. No other interactions were detected. Conclusions Arterial stiffness is associated with microstructural and macrostructural differences and poorer global and executive cognitive function.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".