Contributions of DNA Damage to Alzheimer’s Disease
Bibliographic record
Abstract
Alzheimer’s disease (AD) is the most common type of neurodegenerative disease. Its typical pathology consists of extracellular amyloid-β (Aβ) plaques and intracellular tau neurofibrillary tangles. Mutations in the APP, PSEN1, and PSEN2 genes increase Aβ production and aggregation, and thus cause early onset or familial AD. Even with this strong genetic evidence, recent studies support AD to result from complex etiological alterations. Among them, aging is the strongest risk factor for the vast majority of AD cases: Sporadic late onset AD (LOAD). Accumulation of DNA damage is a well-established aging factor. In this regard, a large amount of evidence reveals DNA damage as a critical pathological cause of AD. Clinically, DNA damage is accumulated in brains of AD patients. Genetically, defects in DNA damage repair resulted from mutations in the BRAC1 and other DNA damage repair genes occur in AD brain and facilitate the pathogenesis. Abnormalities in DNA damage repair can be used as diagnostic biomarkers for AD. In this review, we discuss the association, the causative potential, and the biomarker values of DNA damage in AD 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".