Correlation Analysis of Capillary APOE, VEGF and eNOS Expression in Alzheimer Brains
Bibliographic record
Abstract
Vasoactive regulatory and transport proteins can modify the transendothelial blood-brain barrier (BBB) transport of beta-amyloid. Dysfunction of one or more of these proteins is hypothesized to contribute to the pathogenesis of Alzheimer's disease (AD). In this study we investigated superior temporal and occipital cortical sections from ten AD and ten control group brains (CG). They were examined using immunohistochemical techniques staining for β(42) amyloid, APOE, VEGF and eNOS. The densities of senile plaques (SPs) and APOE, VEGF and eNOS positive capillaries in each region and in each AD and CG condition were compared using nonparametric statistical analysis. In the AD cases, there were significant negative correlations between APOE positive capillaries and β(42) amyloid SPs, and positive correlations between APOE positive capillaries and VEGF and eNOS positive capillaries. These results demonstrate the increased presence of APOE activity in AD brain capillaries, and that there is a positive correlation between the expression of APOE and each of VEGF and eNOS in the capillaries of AD brains. It is possible, therefore, that the down regulation of APOE in AD brains may contribute significantly to the pathogenesis of SP lesion development by modulating brain β-amyloid burden. The specific interrelationship between APOE, VEGF and eNOS activity at the BBB requires further investigation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".