In Vitro Microbial Degradation of Abnormal Prions in Central Nervous System from Scrapie Affected Sheep
Bibliographic record
Abstract
Abnormal prion protein (PrP Sc ) is highly resistant to inactivation by conventional chemical and physical means.This study was to determine if microbes from the environment could be used to degrade PrP Sc in central nervous system (CNS) tissues from scrapie positive sheep as measured by Western blot.In the first experiment, the number of microbes in CNS tissue suspended in saline was reduced by autoclaving the suspension at 121°C for 5 minutes.Aliquots of this preparation were then inoculated with additional ovine fecal microbes and controls were not inoculated.The results showed that the addition of microbes increased the degradation of PrP Sc in specimens during incubation at room temperature (RT) or at 60°C, but the reduction was greatest at 60°C.In the second experiment, a separate tissue suspension in saline was prepared from CNS tissue from each of 4 scrapie positive sheep and from each of 4 negative sheep.All specimens contained bacteria and after 90 days of incubation at 60°C, PrP Sc in CNS specimens was degraded beyond the detection limit in tissues from 2 scrapie positive sheep and was partially degraded in the other two specimens.The tissues from scrapie negative sheep were consistently negative for PrP Sc .Analysis of microbial 16S ribosomal DNA indicated that during the 90 day incubation period the microbe population shifted from a predominance of mesophiles to thermophiles, based on guanine-cytosine (GC) content of ribosomal RNA genes.The results in this study suggest that microbes commonly found in sheep carcasses or manure could play a role in the degradation of PrP Sc in CNS tissues during incubation at 60°C.
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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".