Valproic Acid Stimulates Hippocampal Neurogenesis via Activating the Wnt/β-Catenin Signaling Pathway in the APP/PS1/Nestin-GFP Triple Transgenic Mouse Model of Alzheimer’s Disease
Bibliographic record
Abstract
Alzheimer's disease (AD) is an age-related neurodegenerative disease characterized by the deposition of amyloid-β (Aβ) peptides and neurofibrillary tangles (NFTs) and massive loss of neuronal cells in the brain. Adult hippocampus continuously generates new neurons throughout life to shape brain function and impaired neurogenesis may contribute to a series of cognitive deterioration associated with AD. Enhancing endogenous neurogenesis represents a promising strategy that may ameliorate AD-associated cognitive defects. However, neurogenesis-enhancing approaches and underlying mechanisms are still not well studied. Here, using a mouse model of AD amyloid precursor protein (APP/PS1/Nestin-GFP triple transgenic mice, 3xTgAD), we examined the effects of 4 weeks of valproic acid (VPA) treatment on hippocampal neurogenesis in 2- and 6-month-old mice. VPA treatment promoted cell proliferation and increased the density of immature neurons in the dentate gyrus (DG) of the hippocampus of 3xTgAD mice. Consistent with enhanced neurogenesis, behavioral and morphological analysis showed that VPA treatment improved the learning and memory ability of 3xTgAD mice. Mechanistically, VPA treatment increased β-catenin levels, accumulated the inactive form of glycogen synthase kinase-3β (GSK-3β), and induced the expression of NeuroD1, a Wnt target gene involved in neurogenesis, suggesting the activation of the Wnt signaling pathway in the hippocampus of 3xTgAD mice. This study indicates that VPA stimulates neurogenesis in the adult hippocampus of AD mice model through the Wnt pathway, highlighting VPA as a potential therapeutic for treating AD and related diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".