Characterization of Aldh2 -/- mice as an age-related model of cognitive impairment and Alzheimer’s disease
Bibliographic record
Abstract
BACKGROUND: The study of late-onset/age-related Alzheimer's disease (AD)(sporadic AD, 95% of AD cases) has been hampered by a paucity of animal models. Oxidative stress is considered a causative factor in late onset/age-related AD, and aldehyde dehydrogenase 2 (ALDH2) is important for the catabolism of toxic aldehydes associated with oxidative stress. One such toxic aldehyde, the lipid peroxidation product 4-hydroxynonenal (HNE), accumulates in AD brain and is associated with AD pathology. Given this linkage, we hypothesized that in mice lacking ALDH2, there would be increases in HNE and the appearance of AD-like pathological changes. RESULTS: Changes in relevant AD markers in Aldh2 (-/-) mice and their wildtype littermates were assessed over a 1 year period. Marked increases in HNE adducts arise in hippocampi from Aldh2 (-/-) mice, as well as age-related increases in amyloid-beta, p-tau, and activated caspases. Also observed were age-related decreases in pGSK3β, PSD95, synaptophysin, CREB and pCREB. Age-related memory deficits in the novel object recognition and Y maze tasks begin at 3.5-4 months and are maximal at 6.5-7 months. There was decreased performance in the Morris Water Maze task in 6 month old Aldh2 (-/-) mice. These mice exhibited endothelial dysfunction, increased amyloid-beta in cerebral microvessels, decreases in carbachol-induced pCREB and pERK formation in hippocampal slices, and brain atrophy. These AD-associated pathological changes are rarely observed as a constellation in current AD animal models. CONCLUSIONS: We believe that this new model of age-related cognitive impairment will provide new insight into the pathogenesis and molecular/cellular mechanisms driving neurodegenerative diseases of aging such as AD, and will prove useful for assessing the efficacy of therapeutic agents for improving memory and for slowing, preventing, or reversing AD progression.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".