Conditional Neuronal Simian Virus 40 T Antigen Expression Induces Alzheimer-Like Tau and Amyloid Pathology in Mice
Bibliographic record
Abstract
A large body of evidence has shown the activation of a cohort of cell cycle regulators and the duplication of DNA in degenerating neurons of Alzheimer's disease (AD) brain. Activation of these regulators and duplication of chromosomes precede neurodegeneration and formation of neurofibrillary tangles (NFTs), one of the diagnostic lesions of AD. These findings, in combination with evidence for cell cycle regulation of amyloid precursor protein and tau, has led to the hypothesis that reentry into the cell cycle underlies AD pathogenesis. To test this hypothesis directly, we have created transgenic mice with forced cell cycle activation in postmitotic neurons via conditional expression of the simian virus 40 large T antigen (TAg) oncogene. We show that TAg mice recapitulate the cell cycle changes seen in AD and display a neurodegenerative phenotype accompanied by tau pathology and NFT-like profiles. Moreover, plaque-like amyloid deposits, similar to those seen in AD, are also observed in the brains of TAg mice. These data provide support for an essential role of ectopic cell cycle activation in the generation of the characteristic pathological hallmarks of AD. Furthermore, our TAg mice are the first model to develop NFTs and amyloid pathology simultaneously and in the absence of any human transgenes. These mice will be useful for further defining the nongenetic mechanisms in AD pathogenesis and for the development of cell cycle-based therapies for 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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".