Inhibition of the NFAT Pathway Alleviates Amyloid Beta Neurotoxicity in a Mouse Model of Alzheimer's Disease
Bibliographic record
Abstract
Amyloid β (Aβ) peptides, the main pathological species associated with Alzheimer's disease (AD), disturb intracellular calcium homeostasis, which in turn activates the calcium-dependent phosphatase calcineurin (CaN). CaN activation induced by Aβ leads to pathological morphological changes in neurons, and overexpression of constitutively active calcineurin is sufficient to generate a similar phenotype, even without Aβ. Here, we tested the hypothesis that calcineurin mediates neurodegenerative effects via activation of the nuclear transcription factor of activated T-cells (NFAT). We found that both spine loss and dendritic branching simplification induced by Aβ exposure were mimicked by constitutively active NFAT, and abolished when NFAT activation was blocked using the genetically encoded inhibitor VIVIT. When VIVIT was specifically addressed to the nucleus, identical beneficial effects were observed, thus enforcing the role of NFAT transcriptional activity in Aβ-related neurotoxicity. In vivo, when VIVIT or its nuclear counterpart were overexpressed in a transgenic model of Alzheimer's disease via a gene therapy approach, the spine loss and neuritic abnormalities observed in the vicinity of amyloid plaques were blocked. Overall, these results suggest that NFAT/calcineurin transcriptional cascades contribute to Aβ synaptotoxicity, and may provide a new specific set of pathways for neuroprotective strategies.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".