Use of different RT-QuIC substrates for detecting CWD prions in the brain of Norwegian cervids
Bibliographic record
Abstract
Chronic wasting disease (CWD) is a highly contagious prion disease affecting captive and free-ranging cervid populations. CWD has been detected in United States, Canada, South Korea and, most recently, in Europe (Norway, Finland and Sweden). Animals with CWD release infectious prions in the environment through saliva, urine and feces sustaining disease spreading between cervids but also potentially to other non-cervids ruminants (e.g. sheep, goats and cattle). In the light of these considerations and due to CWD unknown zoonotic potential, it is of utmost importance to follow specific surveillance programs useful to minimize disease spreading and transmission. The European community has already in place specific surveillance measures, but the traditional diagnostic tests performed on nervous or lymphoid tissues lack sensitivity. We have optimized a Real-Time Quaking-Induced Conversion (RT-QuIC) assay for detecting CWD prions with high sensitivity and specificity to try to overcome this problem. In this work, we show that bank vole prion protein (PrP) is an excellent substrate for RT-QuIC reactions, enabling the detection of trace-amounts of CWD prions, regardless of prion strain and cervid species. Beside supporting the traditional diagnostic tests, this technology could be exploited for detecting prions in peripheral tissues from live animals, possibly even at preclinical stages of the disease.
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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 | 0.001 |
| 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".