The Role of the Blood-Brain Barrier in the Pathogenesis of Senile Plaques in Alzheimer’s Disease
Bibliographic record
Abstract
The accumulation of beta-amyloid [Aβ] within senile plaques [SP] is characteristic of these lesions in Alzheimer's disease. The accumulation of Aβ 42, in particular, in the superior temporal [ST] cortex may result from an inability of the blood brain barrier (BBB) to regulate the trans-endothelial transport and clearance of the amyloid. Lipoprotein receptor-related protein [LRP] and P-glycoprotein [P-gp] facilitate the efflux of Aβ out of the brain, whereas receptor for advanced glycation end products [RAGE] facilitates Aβ influx. Additionally, vascular endothelial growth factor [VEGF] and endothelial nitric oxide synthase [eNOS] may influence the trans-BBB transport of Aβ. In this study we examined ST samples and compared SP burden of all types with the capillary expression of LRP, p-gp, RAGE, VEGF, and e-NOS in samples from 15 control and 15 Alzheimer brains. LRP, P-gp, RAGE, VEGF, and eNOS positive capillaries and Aβ 42 plaques were quantified and statistical analysis of the nonparametric data was performed using the Mann-Whitney and Kruskal-Wallis tests. In the Alzheimer condition P-gp, VEGF, and eNOS positive capillaries were negatively correlated with SP burden, but LRP and RAGE were positively correlated with SP burden. These results indicate altered BBB function in the pathogenesis of SPs in Alzheimer brains.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".