Ageing and amyloidosis underlie the molecular and pathological alterations of tau in a mouse model of familial Alzheimer’s disease
Bibliographic record
Abstract
Abstract Despite compelling evidence that the accumulation of amyloid-beta (Aβ) promotes neocortical MAPT (tau) aggregation in familial and idiopathic Alzheimer’s disease (AD), murine models of cerebral amyloidosis are not considered to develop tau-associated pathology. In the present study, we show that tau can accumulate spontaneously in aged transgenic APP swe / PS1 ΔE9 mice. Tau pathology is abundant around Aβ deposits, and further characterized by accumulation of Gallyas and thioflavin-S-positive inclusions, which were detected in the APP swe / PS1 ΔE9 brain at 18 months of age. Age-dependent increases in argyrophilia correlated positively with binding levels of the paired helical filament (PHF) tracer [ 18 F]Flortaucipir, in all brain areas examined. Sarkosyl-insoluble PHFs were visualized by electron microscopy. Quantitative proteomics identified sequences of hyperphosphorylated and three-repeat tau in transgenic mice, along with signs of RNA missplicing, ribosomal dysregulation and disturbed energy metabolism. Tissue from the frontal gyrus of human subjects was used to validate these findings, revealing primarily quantitative differences between the tau pathology observed in AD patient vs. transgenic mouse tissue. As physiological levels of endogenous, ‘wild-type’ tau aggregate secondarily to Aβ in APP swe / PS1 ΔE9 mice, this study suggests that amyloidosis is both necessary and sufficient to drive tauopathy in experimental models of familial 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".