Neurovascular Alterations in Vascular Dementia: Emphasis on Risk Factors
Bibliographic record
Abstract
Vascular dementia (VaD) constitutes the second most prevalent cause of dementia in the world after Alzheimer’s disease (AD). VaD regroups heterogeneous neurological conditions in which the decline of cognitive functions, including executive functions, is associated with structural and functional alterations in the cerebral vasculature. Among these cerebrovascular disorders, major stroke, and cerebral small vessel disease (cSVD) constitute the major risk factors for VaD. These conditions alter neurovascular functions leading to blood-brain barrier (BBB) deregulation, neurovascular coupling dysfunction, and inflammation. Accumulation of neurovascular impairments over time underlies the cognitive function decline associated with VaD. Furthermore, several vascular risk factors, such as hypertension, obesity, and diabetes have been shown to exacerbate neurovascular impairments and thus increase VaD prevalence. Importantly, air pollution constitutes an underestimated risk factor that triggers vascular dysfunction via inflammation and oxidative stress. The review summarizes the current knowledge related to the pathological mechanisms linking neurovascular impairments associated with stroke, cSVD, and vascular risk factors with a particular emphasis on air pollution, to VaD etiology and progression. Furthermore, the review discusses the major challenges to fully elucidate the pathobiology of VaD, as well as research directions to outline new therapeutic interventions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".