THE PATHOLOGICAL PATHWAY FOR THE PERSISTENCE OF AD SYMPTOMS AFTER THE REMOVAL OF AMYLOID PLAQUES
Bibliographic record
Abstract
Amyloid plaque has been an indicative hallmark for Alzheimer’s diseases (AD), however the removal of which has shown to be inefficient in altering the progression of disease; thus, the study will focus on the mechanism behind the persistence of AD. The study examines the causal relationships among Aβ, neurofibrillary tangles (NFTs), cholinergic depletion, and excitotoxicity. Using secondary data from pre-existing studies, it is evidenced that Aβ causes cholinergic depletion, NFTs, and excitotoxicity through interacting with ChaT & nAChRs, IP3-K & GSK-3β, and NR1 subunit on NMDAR respectively; NFTs causes cholinergic depletion and excitotoxicity through mitochondrial dysfunction, and interaction with vGLUT respectively; while excitotoxicity causes NFTs through interaction with cdk5 and PP2A. It is concluded that the persistence of AD after Aβ removal is due to a positive feedback loop mechanism between NFTs and excitotoxicity, which causes the persistence of NFTs, cholinergic depletion, and excitotoxicity. However, the principle causative agent of AD’s progression remains undecidable.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".