Inactivation of infectious prions in the environment: a mini-review
Bibliographic record
Abstract
Infectious prions (PrPTSE) contribute to horizontal transmission of transmissible spongiform encephalopathies. Specified risk material (SRM) wastes and wastewater generated from slaughterhouses and rendering plants represent a potential reservoir of PrPTSE. Approved disposal practices for SRM that ensure destruction of PrPTSE, including thermal or alkaline hydrolysis at 150°C–180°C under 4–12 atmospheres and incineration, gasification or combustion at 1000°C, are expensive and challenging to implement in commercial slaughter facilities. Consequently, a large portion of the SRM in Canada is rendered and buried in landfills, whereas they are incinerated at considerable cost in Europe. Alternatives for the disposal of these wastes have been proposed and include anaerobic digestion and composting. These biodegradative processes offer advantages in that they are less energy intensive, CH4 can be used in cogeneration and the end products used as fertiliser. In addition, advanced ozonation of the liquid fraction of SRM may allow its direct release into wastewater streams. For these practices to be adopted, assessment of the extent of PrPTSE inactivation during these processes is required. Moreover, multi-barrier use of these approaches (e.g., anaerobic digestion + composting or anaerobic digestion + ozone) may act synergistically to achieve an acceptable level of PrPTSE inactivation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".