Simvastatin rescues memory and granule cell maturation through the Wnt/β-catenin signaling pathway in a mouse model of Alzheimer’s disease
Bibliographic record
Abstract
We previously showed that simvastatin (SV) restored memory in a mouse model of Alzheimer disease (AD) concomitantly with normalization in protein levels of memory-related immediate early genes in hippocampal CA1 neurons. Here, we investigated age-related changes in the hippocampal memory pathway, and whether the beneficial effects of SV could be related to enhanced neurogenesis and signaling in the Wnt/β-catenin pathway. APP mice and wild-type (WT) littermate controls showed comparable number of proliferating (Ki67-positive nuclei) and immature (doublecortin (DCX)-positive) granule cells in the dentate gyrus until 3 months of age. At 4 months, Ki67 or DCX positive cells decreased sharply and remained less numerous until the endpoint (6 months) in both SV-treated and untreated APP mice. In 6 month-old APP mice, dendritic extensions of DCX immature neurons in the molecular layer were shorter, a deficit fully normalized by SV. Similarly, whereas mature granule cells (calbindin-immunopositive) were decreased in APP mice and not restored by SV, their dendritic arborizations were normalized to control levels by SV treatment. SV increased Prox1 protein levels (↑67.7%, p < 0.01), a Wnt/β-catenin signaling target, while significantly decreasing (↓61.2%, p < 0.05) the upregulated levels of the β-catenin-dependent Wnt pathway inhibitor DKK1 seen in APP mice. In APP mice, SV benefits were recapitulated by treatment with the Wnt/β-catenin specific agonist WAY-262611, whereas they were fully abolished in mice that received the Wnt/β-catenin pathway inhibitor XAV939 during the last month of SV treatment. Our results indicate that activation of the Wnt-β-catenin pathway through downregulation of DKK1 underlies SV neuronal and cognitive benefits.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".