Evidence for Altered LRP/RAGE Expression in Alzheimer Lesion Pathogenesis
Bibliographic record
Abstract
There is significant evidence to suggest that a damaged or dysfunctional blood-brain barrier (BBB) may contribute to the pathogenesis of Alzheimer's disease (AD) lesions. Lipoprotein receptor-related protein (LRP-1) and receptor for advanced glycation end products (RAGE) are known to be important (BBB) capillary transport proteins. Altered expression of either of these capillary endothelial LRP-1 and RAGE receptor proteins could indicate a dysfunction of the BBB and its transport regulation of beta-amyloid (Abeta). Cortical samples from the superior temporal (ST) and calcarine occipital (COC) cortices of ten confirmed AD brains and ten comparison group (CG) brains were examined. The densities of neurofibrillary tangles (NFTs), senile plaques (SPs) and LRP-1 and RAGE positive capillaries were recorded and statistically analyzed. There was a statistically significant difference between AD and CG cases and the densities of LRP-1 and RAGE positive capillaries, the AD cases demonstrating the greater numbers. Further, in AD brains there were significant negative correlations between the Abeta burden of SPs and both LRP-1 and RAGE-positive capillaries [p < .001]. Additionally, there was a strong positive correlation between LRP-1 and RAGE capillaries in AD brains [p < .001]. These results suggest that alterations in the LRP-1 and RAGE mediated transport of Abeta take place in AD brains in lesion prone regions and may therefore contribute to SP lesion pathogenesis.
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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 | 0.001 | 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".