Inactivation of Template-Directed Misfolding of Infectious Prion Protein by Ozone
Bibliographic record
Abstract
Misfolded prions (PrP(Sc)) are well known for their resistance to conventional decontamination processes. The potential risk of contamination of the water environment, as a result of disposal of specified risk materials (SRM), has raised public concerns. Ozone is commonly utilized in the water industry for inactivation of microbial contaminants and was tested in this study for its ability to inactivate prions (263K hamster scrapie = PrP(Sc)). Treatment variables included initial ozone dose (7.6 to 25.7 mg/liter), contact time (5 s and 5 min), temperature (4°C and 20°C), and pH (pH 4.4, 6.0, and 8.0). Exposure of dilute suspensions of the infected 263K hamster brain homogenates (IBH) (0.01%) to ozone resulted in the in vitro destruction of the templating properties of PrP(Sc), as measured by the protein misfolding cyclic amplification (PMCA) assay. The highest levels of prion inactivation (≥4 log(10)) were observed with ozone doses of 13.0 mg/liter, at pH 4.4 and 20°C, resulting in a CT (the product of residual ozone concentration and contact time) value as low as 0.59 mg · liter(-1) min. A comparison of ozone CT requirements among various pathogens suggests that prions are more susceptible to ozone degradation than some model bacteria and protozoa and that ozone treatment may be an effective solution for inactivating prions in water and wastewater.
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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".