Enzymatic Formulation Capable of Degrading Scrapie Prion under Mild Digestion Conditions
Bibliographic record
Abstract
The prion agent is notoriously resistant to common proteases and conventional sterilisation procedures. The current methods known to destroy prion infectivity such as incineration, alkaline and thermal hydrolysis are harsh, destructive, environmentally polluting and potentially hazardous, thus limit their applications for decontamination of delicate medical and laboratory devices, remediation of prion contaminated environment and for processing animal by-products including specified risk materials and carcases. Therefore, an environmentally friendly, non-destructive enzymatic degradation approach is highly desirable. A feather-degrading Bacillus licheniformis N22 keratinase has been isolated which degraded scrapie prion to undetectable level of PrP(Sc) signals as determined by Western Blot analysis. Prion infectivity was verified by ex vivo cell-based assay. An enzymatic formulation combining N22 keratinase and biosurfactant derived from Pseudomonas aeruginosa degraded PrP(Sc) at 65 °C in 10 min to undetectable level -. A time-course degradation analysis carried out at 50 °C over 2 h revealed the progressive attenuation of PrP(Sc) intensity. Test of residual infectivity by standard cell culture assay confirmed that the enzymatic formulation reduced PrP(Sc) infectivity to undetectable levels as compared to cells challenged with untreated standard scrapie sheep prion (SSBP/1) (p-value = 0.008 at 95% confidence interval). This novel enzymatic formulation has significant potential application for prion decontamination in various environmentally friendly systems under mild treatment conditions.
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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) | 0.000 | 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".