Alzheimer’s Disease Pathogenesis: Role of Autophagy and Mitophagy Focusing in Microglia
Bibliographic record
Abstract
Alzheimer's disease (AD) is a debilitating neurological disorder, and currently, there is no cure for it. Several pathologic alterations have been described in the brain of AD patients, but the ultimate causative mechanisms of AD are still elusive. The classic hallmarks of AD, including amyloid plaques (Aβ) and tau tangles (tau), are the most studied features of AD. Unfortunately, all the efforts targeting these pathologies have failed to show the desired efficacy in AD patients so far. Neuroinflammation and impaired autophagy are two other main known pathologies in AD. It has been reported that these pathologies exist in AD brain long before the emergence of any clinical manifestation of AD. Microglia are the main inflammatory cells in the brain and are considered by many researchers as the next hope for finding a viable therapeutic target in AD. Interestingly, it appears that the autophagy and mitophagy are also changed in these cells in AD. Inside the cells, autophagy and inflammation interact in a bidirectional manner. In the current review, we briefly discussed an overview on autophagy and mitophagy in AD and then provided a comprehensive discussion on the role of these pathways in microglia and their involvement 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 | 0.000 |
| 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) | 0.002 | 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".