Altered rPrP substrate structures and their influence on real-time quaking induced conversion reactions
Bibliographic record
Abstract
Background Bacterially-produced recombinant prion protein (rPrP) has traditionally been used for in vitro fibrillation assays and reagent development for prion disease research. In recent years, it has also been used as a substrate for real-time quaking-induced conversion (RT-QuIC), a very sensitive method of detecting the presence of the misfolded, disease-associated isoform of the prion protein (PrP d ). Multi-centre trials have demonstrated that RT-QuIC is a suitably reliable and robust technique for clinical practice; however, in the absence of a commercial supplier of rPrP as a substrate for RT-QuIC, laboratories have been required to independently generate this key component of the assay. No harmonized method for producing the protein has been agreed upon, in part due to the variety of substrates that have been applied in RT-QuIC. Methods This study examines the effects of two different rPrP refolding protocols on the production, QuIC performance, and structure characteristics of two constructs of rPrP commonly used in QuIC: full length hamster and a sheep-hamster chimeric rPrP. Results Under the described conditions, the best performing substrate was the chimeric sheep-hamster rPrP produced by shorter guanidine-HCl exposure and faster gradient elution. Conclusions The observation that different rPrP production protocols influence QuIC performance indicates that caution should be exercised when comparing inter-laboratory QuIC results.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".