Prion-like propagation of β-amyloid aggregates in the absence of APP overexpression
Bibliographic record
Abstract
The amyloid cascade hypothesis posits that the initiating event in Alzheimer’s disease (AD) is the aggregation and deposition of the β-amyloid (Aβ) peptide, which is a proteolytic cleavage product of the amyloid precursor protein (APP). Mounting evidence suggests that the formation and spread of prion-like Aβ aggregates during AD may contribute to disease progression. Inoculation of transgenic mice that overexpress APP with pre-formed Aβ aggregates results in the prion-like induction of cerebral Aβ deposition. To determine whether Aβ deposition can also be induced when physiological APP levels are present in the brain, we inoculated App NL-F mice, a knock-in model of AD that avoids potential artifacts associated with APP overexpression, with Aβ aggregates derived from the brains of AD patients or transgenic mice. In all cases, induced Aβ deposition was apparent in the corpus callosum, olfactory bulb, and meningeal blood vessels of inoculated mice at 130–150 days post-inoculation, whereas uninoculated and buffer-inoculated animals exhibited minimal or no Aβ deposits at these ages. Interestingly, despite being predominantly composed of protease-resistant Aβ42 aggregates, the induced parenchymal Aβ deposits were largely diffuse and were unreactive to an amyloid-binding dye. These results demonstrate that APP overexpression is not a prerequisite for the prion-like induction of cerebral Aβ deposition. Accordingly, spreading of Aβ deposition may contribute to disease progression in AD patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".