Metabolic Dysfunction in Alzheimer’s Disease: From Basic Neurobiology to Clinical Approaches
Bibliographic record
Abstract
Clinical trials have extensively failed to find effective treatments for Alzheimer's disease (AD) so far. Even after decades of AD research, there are still limited options for treating dementia. Mounting evidence has indicated that AD patients develop central and peripheral metabolic dysfunction, and the underpinnings of such events have recently begun to emerge. Basic and preclinical studies have unveiled key pathophysiological mechanisms that include aberrant brain stress signaling, inflammation, and impaired insulin sensitivity. These findings are in accordance with clinical and neuropathological data suggesting that AD patients undergo central and peripheral metabolic deregulation. Here, we review recent basic and clinical findings indicating that metabolic defects are central to AD pathophysiology. We further propose a view for future therapeutics that incorporates metabolic defects as a core feature of AD pathogenesis. This approach could improve disease understanding and therapy development through drug repurposing and/or identification of novel metabolic targets.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".