Amyloid β accelerates phosphorylation of tau and neurofibrillary tangle formation in an amyloid precursor protein and tau double‐transgenic mouse model
Bibliographic record
Abstract
In Alzheimer's disease, Aβ deposits are considered the initial cardinal events that induce tauopathy secondarily. However, the relationship between Aβ amyloidosis and tauopathy has not been determined in detail. We produced double transgenic mice, 2×TgTau(+/-) APP(+/-) , by mating Tg2576 mice that exhibit Aβ amyloidosis and TgTauP301L mice that show tauopathy, and statistically analyzed the effect of Aβ accumulation on tauopathy. There was no significant difference in theprogression of Aβ accumulation among 2×TgTau(+/-) APP(+/-) and 1×TgTau(-/-) APP(+/-) , and tau accumulation among 2×TgTau(+/-) APP(+/-) and 1×Tg Tau(+/-) APP(-/-) . The appearance rates of phosphorylated tau developing in neurons and processes were significantly accelerated in 2×TgTau(+/-) APP(+/-) mice compared with those in 1×TgTau(+/-) APP(-/-) mice at 23 months of age. Accumulation of phosphorylated and confomationally altered tau and GSK3β in neuronal processes was accelerated in the white matter in 2×TgTau(+/-) APP(+/-) . The level of phosphorylated tau in the sarkosyl-insoluble fraction was increased in 2×TgTau(+/-) APP(+/-) brains compared with that in 1×TgTau(+/-) APP(-/-) brains. Thus, Aβ amyloid partially enhances tauopathy through accumulation of insoluble, phosphorylated, and conformationally changed tau in neuronal cytoplasm and processes in the late stage.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".