Assessing Transmissible Spongiform Encephalopathy Species Barriers with an <em>In Vitro</em> Prion Protein Conversion Assay
Bibliographic record
Abstract
Studies to understanding interspecies transmission of transmissible spongiform encephalopathies (TSEs, prion diseases) are challenging in that they typically rely upon lengthy and costly in vivo animal challenge studies. A number of in vitro assays have been developed to aid in measuring prion species barriers, thereby reducing animal use and providing quicker results than animal bioassays. Here, we present the protocol for a rapid in vitro prion conversion assay called the conversion efficiency ratio (CER) assay. In this assay cellular prion protein (PrPC) from an uninfected host brain is denatured at both pH 7.4 and 3.5 to produce two substrates. When the pH 7.4 substrate is incubated with TSE agent, the amount of PrPC that converts to a proteinase K (PK)-resistant state is modulated by the original host's species barrier to the TSE agent. In contrast, PrPC in the pH 3.5 substrate is misfolded by any TSE agent. By comparing the amount of PK-resistant prion protein in the two substrates, an assessment of the host's species barrier can be made. We show that the CER assay correctly predicts known prion species barriers of laboratory mice and, as an example, show some preliminary results suggesting that bobcats (Lynx rufus) may be susceptible to white-tailed deer (Odocoileus virginianus) chronic wasting disease agent.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".