Disease-associated Mutations in the Prion Protein Impair Laminin-induced Process Outgrowth and Survival
Bibliographic record
Abstract
Prions, the agents of transmissible spongiform encephalopathies, require the expression of prion protein (PrP(C)) to propagate disease. PrP(C) is converted into an abnormal insoluble form, PrP(Sc), that gains neurotoxic activity. Conversely, clinical manifestations of prion disease may occur either before or in the absence of PrP(Sc) deposits, but the loss of normal PrP(C) function contribution for the etiology of these diseases is still debatable. Prion disease-associated mutations in PrP(C) represent one of the best models to understand the impact of PrP(C) loss-of-function. PrP(C) associates with various molecules and, in particular, the interaction of PrP(C) with laminin (Ln) modulates neuronal plasticity and memory formation. To assess the functional alterations associated with PrP(C) mutations, wild-type and mutated PrP(C) proteins were expressed in a neural cell line derived from a PrP(C)-null mouse. Treatment with the laminin γ1 chain peptide (Ln γ1), which mimics the Ln binding site for PrP(C), increased intracellular calcium in cells expressing wild-type PrP(C), whereas a significantly lower response was observed in cells expressing mutated PrP(C) molecules. The Ln γ1 did not promote process outgrowth or protect against staurosporine-induced cell death in cells expressing mutated PrP(C) molecules in contrast to cells expressing wild-type PrP(C). The co-expression of wild-type PrP(C) with mutated PrP(C) molecules was able to rescue the Ln protective effects, indicating the lack of negative dominance of PrP(C) mutated molecules. These results indicate that PrP(C) mutations impair process outgrowth and survival mediated by Ln γ1 peptide in neural cells, which may contribute to the pathogenesis of genetic prion diseases.
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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".