Age-Related Neuronal Deterioration Specifically Within the Dorsal CA1 Region of the Hippocampus in a Mouse Model of Late Onset Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Neuronal damage resulting from increased oxidative stress is important in the development of late onset/age-related Alzheimer's disease (LOAD). We have developed an oxidative stress-related mouse model of LOAD based on gene deletion of aldehyde dehydrogenase 2 (ALDH2), an enzyme important for the detoxification of endogenous aldehydes arising from lipid peroxidation. Compared to wildtype (WT) mice, the knockout (KO) mice exhibit AD-like pathologies and a progressive decline in recognition and spatial memory. This progression presumably has a morphological basis induced by oxidative damage. OBJECTIVE: We performed morphometric analyses in the dorsal hippocampal CA1 region (dCA1) to determine if altered neuronal structure can help account for the progressive cognitive impairment in 3- to 12-month-old KO mice. METHODS: Dendritic morphology was quantitatively analyzed by branched structured analysis and Sholl analysis following Golgi-Cox staining in WT mice (148 neurons) versus KO mice (180 neurons). RESULTS: The morphology and complexity of dCA1 pyramidal neurons were similar at age 3 months in WTs and KOs. However, by 6 months there were significant reductions in apical and basal dendritic length, dendrite complexity, and spine density in KO versus WT mice that were maintained through ages 9 and 12 months. Immunostaining for protein adducts of the lipid peroxidation product 4-hydroxynonenal revealed significant increases in staining in dCA1 (but not ventral CA1) by 3 months, increasing through 12 months. CONCLUSION: This specific and progressive increase in dCA1 oxidative damage preceded detectable synaptic trimming in KO mice, in keeping with studies showing that lesions to dorsal hippocampus primarily impair cognitive memory.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".