Aggregation of cellular prion protein is initiated by proximity‐induced dimerization
Bibliographic record
Abstract
Prion diseases or transmissible spongiform encephalopathies (TSEs) are infectious and fatal neurodegenerative disorders in humans and animals. Pathological features of TSEs include the conversion of cellular prion protein (PrP(C)) into an altered disease-associated conformation generally designated PrP(Sc), abnormal deposition of PrP(Sc) aggregates, and spongiform degeneration of the brain. The molecular steps leading to PrP(C) aggregation are unknown. Here, we have utilized an inducible oligomerization strategy to test if, in the absence of any infectious prion particles, the encounter between PrP(C) molecules may trigger its aggregation in neuronal cells. A chimeric PrP(C) composed of one (Fv1) or two (Fv2) modified FK506-binding protein (Fv) fused with PrP(C) were created, and transfected in N2a cells. Similar to PrP(C), Fv1-PrP and Fv2-PrP were glycosylated, displayed normal localization, and anti-apoptotic function. When cells were treated with the dimeric Fv ligand AP20187, to induce dimerization (Fv1) or oligomerization (Fv2) of PrP(C), both dimerization and oligomerization of PrP(C) resulted in the de novo production, release and deposition of extracellular PrP aggregates. Aggregates were insoluble in non-ionic detergents and partially resistant to proteinase K. These findings demonstrate that homologous interactions between PrP(C) molecules may constitute a minimal and sufficient molecular event leading to PrP(C) aggregation and extracellular deposition.
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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".