From Stroke to Dementia: a Comprehensive Review Exposing Tight Interactions Between Stroke and Amyloid-β Formation
Bibliographic record
Abstract
Stroke and Alzheimer's disease (AD) are cerebral pathologies with high socioeconomic impact that can occur together and mutually interact. Vascular factors predisposing to cerebrovascular disease have also been specifically associated with development of AD, and acute stroke is known to increase the risk to develop dementia.Despite the apparent association, it remains unknown how acute cerebrovascular disease and development of AD are precisely linked and act on each other. It has been suggested that this interaction is strongly related to vascular deposition of amyloid-β (Aβ), i.e., cerebral amyloid angiopathy (CAA). Furthermore, the blood-brain barrier (BBB), perivascular space, and the glymphatic system, the latter proposedly responsible for the drainage of solutes from the brain parenchyma, may represent key pathophysiological pathways linking stroke, Aβ deposition, and dementia.In this review, we propose a hypothetic connection between CAA, stroke, perivascular space integrity, and dementia. Based on relevant pre-clinical research and a few clinical case reports, we speculate that impaired perivascular space integrity, inflammation, hypoxia, and BBB breakdown after stroke can lead to accelerated deposition of Aβ within brain parenchyma and cerebral vessel walls or exacerbation of CAA. The deposition of Aβ in the parenchyma would then be the initiating event leading to synaptic dysfunction, inducing cognitive decline and dementia. Maintaining the clearance of Aβ after stroke could offer a new therapeutic approach to prevent post-stroke cognitive impairment and development into dementia.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".