Vascular models of Alzheimer's disease: An overview of recent in vitro models of the blood-brain barrier
Bibliographic record
Abstract
Alzheimer's disease (AD) remains an overwhelming epidemiologic and economic burden on our healthcare systems, affecting an estimate of 11 % of individuals aged 65 years and older. Increasing evidence of the role of the blood-brain barrier (BBB) in AD pathology lends support to the vascular hypothesis of AD, which posits that damage to cerebral vasculature and impairments to cerebral blood flow are major contributors to neurodegeneration in AD. While the question remains whether the dysfunction of the BBB is the cause or consequence of the disease, understanding of the relationship between vascular pathology and AD is growing increasingly complex, warranting the need for better tools to study vasculature in AD. This review provides an overview of AD models in the context of studying vascular impairments and their relevance in pathology. Specifically, we summarize opportunities in in vitro models, cell sources, and phenotypic observations in sporadic and familial forms of AD. Further, we describe recent advances in generating models which recapitulate in vivo characteristics of the BBB in AD through the use of microfluidics, induced pluripotent stem cells (iPSC), and organoid technologies. Finally, we provide a searchable database of reported cell-based models of pathogenic AD gene variants.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".