Aldehyde dehydrogenase 2 null mice as an oxidative stress‐based model of age‐related cognitive impairment with Alzheimer’s disease‐like pathologies (845.3)
Bibliographic record
Abstract
Most current mouse models Alzheimer’s disease (AD) exhibit pathological changes dependent on overexpression of mutant human genes linked to familial AD, and animal models that mirror late‐onset/age‐related AD (95% of AD cases) are lacking. Oxidative stress is considered a causative factor in age‐related AD, and Aldehyde dehydrogenase 2 (ALDH2) is important for the detoxification of endogenous aldehydes, such as 4‐hydroxynonenal (HNE), a lipid peroxidation product formed during periods of oxidative stress that can form protein adducts, altering cell function. HNE adducts accumulate in the brains of AD patients and are associated with AD pathology. Given this linkage, manipulations that increase HNE levels might be expected to result in biochemical and cognitive changes that mirror those found in AD. Accordingly, we followed the age‐related changes of a number of relevant AD markers over a 12 month period in hippocampal homogenates from Aldh2 null mice. Marked increases in HNE adduct formation occurred as early as 3 months, and there were age‐related increases in monomeric amyloid β (Aβ), phospho tau protein, and activated caspases 3 and 6. Also observed were age‐related decreases in PSD95 and synaptophysin (indicating synaptic loss) and of total and phosphorylated cAMP‐response element binding protein (CREB). Aldh2 null mice exhibit a graded, age‐related decrease in performance in recognition and spatial memory tasks beginning at 3 months of age and maximal at 6 months. These mice also exhibit dystrophic neurites and loss of dendritic spines, defects in cholinergic agonist‐induced CREB phosphorylation, endothelial dysfunction, and monomeric and oligomeric Aβ deposition in cerebral microvessels. Aldh2 null mice exhibit a wide spectrum of AD‐like pathological changes that are rarely observed together in current AD animal models, and may prove useful for assessing the efficacy of therapeutic agents for improving memory and for slowing, preventing, or reversing disease progression. Grant Funding Source : Botterell Foundation
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".