O1‐06‐06: Regulation of BACE1 expression by GSK3‐beta and its therapeutic effect on Alzheimer's disease
Bibliographic record
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disorder leading to dementia. Deposition of amyloid β protein (Aβ) to form neuritic plaques in the brains is the pathological hallmark of Alzheimer's disease (AD). Aβ is generated from sequential cleavages of the β-amyloid precursor protein (APP) by the β- and γ-secretases. Therefore, inhibition of the pathways that lead to Ab generation will have therapeutic implications for the treatment of AD. Beta-site APP cleaving enzyme 1 (BACE1) is the b-secretase essential for Aβ generation. Increased Aβ levels could facilitate AD pathogenesis and inhibition of Aβ generation may have therapeutic implications for AD treatment. Previous studies have indicated that glycogen synthase kinase 3 (GSK3) may play a role in APP processing by modulating γ-secretase activity, thereby facilitating Aβ production. To study the role of GSK3 signaling in AD pathogenesis and its pharmaceutical potential, we treated cells and AD transgenic mice with GSK3-specific inhibitor. APP processing, Aβ production, and BACE1 expression were examined by Western blot and promoter assays. Furthermore, neurotic plaque formation and memory deficits were analyzed by immunohistochemical staining and Morris Water Maze test, respectively. Specific inhibition of GSK3β, but not GSK3α, reduced BACE1-mediated cleavage of APP and Aβ production by decreasing BACE1 gene transcription and expression. The regulation of BACE1 gene expression by GSK3β is dependent on NFÎB signaling. Specific inhibition of GSK3 signaling markedly reduced Ab deposition and neuritic plaque formation, and rescued memory deficits in the double transgenic AD model mice. Taken together, our data provide evidence for regulation of BACE1 expression and AD pathogenesis by GSK3β and that inhibition of GSK3 signaling can reduce Ab neuropathology and alleviate memory deficits in AD model mice. Our study suggests that interventions that target the β-isoform of GSK3 specifically may be a safe and effective approach for treating AD.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".