Mechanistic Insights and Translational Therapeutics of Neurovascular Unit Dysregulation in Vascular Cognitive Impairment
Bibliographic record
Abstract
Cognitive impairment represents a progressive neurodegenerative condition with severity ranging from mild cognitive impairment (MCI) to dementia and exerts significant burdens on both individuals and healthcare systems. Vascular cognitive impairment (VCI) represents a heterogeneous clinical continuum, spanning a spectrum from subcortical ischemic VCI (featuring small vessel disease, white matter lesions, and lacunar infarcts) to mixed dementia, where vascular and Alzheimer's-type pathologies coexist. While traditionally linked to macro- and microvascular dysfunction, the mechanisms underlying VCI remain complex. However, contemporary research has gone beyond structural vascular damage, highlighting the neurovascular unit (NVU) as a critical mediator. Emerging evidence demonstrates that cerebral endothelial cells within the NVU not only regulate oxygen and nutrient transport but also orchestrate neuroinflammatory signaling and neurovascular coupling (NVC). Crucially, endothelial dysfunction initiates a self-perpetuating cycle of NVU dysregulation characterized by: (1) NVC impairment through diminished nitric oxide bioavailability and calcium signaling defects, (2) blood-brain barrier (BBB) breakdown via tight-junction protein degradation and pericyte detachment, and (3) neuroinflammation driven by endothelial-derived cytokine release and leukocyte infiltration. By integrating recent advances in NVU biology, we have established a framework to inform clinical strategies for early diagnosis and targeted therapies, which we outline in this review. Moreover, proactive management of vascular risk factors (e.g., hypertension, diabetes) in presymptomatic stages may mitigate the progression from vascular injury to irreversible dementia, underscoring its preventive potential. These insights reinforce the idea that preserving NVU integrity represents a pivotal approach to mitigating the global dementia burden.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".