Human tau increases amyloid β plaque size but not amyloid β‐mediated synapse loss in a novel mouse model of Alzheimer's disease
Bibliographic record
Abstract
Alzheimer's disease is characterized by the presence of aggregates of amyloid beta (Aβ) in senile plaques and tau in neurofibrillary tangles, as well as marked neuron and synapse loss. Of these pathological changes, synapse loss correlates most strongly with cognitive decline. Synapse loss occurs prominently around plaques due to accumulations of oligomeric Aβ. Recent evidence suggests that tau may also play a role in synapse loss but the interactions of Aβ and tau in synapse loss remain to be determined. In this study, we generated a novel transgenic mouse line, the APP/PS1/rTg21221 line, by crossing APP/PS1 mice, which develop Aβ-plaques and synapse loss, with rTg21221 mice, which overexpress wild-type human tau. When compared to the APP/PS1 mice without human tau, the cross-sectional area of ThioS+ dense core plaques was increased by ~50%. Along with increased plaque size, we observed an increase in plaque-associated dystrophic neurites containing misfolded tau, but there was no exacerbation of neurite curvature or local neuron loss around plaques. Array tomography analysis similarly revealed no worsening of synapse loss around plaques, and no change in the accumulation of Aβ at synapses. Together, these results indicate that adding human wild-type tau exacerbates plaque pathology and neurite deformation but does not exacerbate plaque-associated synapse loss.
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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) | 0.002 | 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 | 0.000 |
| Research integrity | 0.002 | 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".