Investigating strain diversity of Creutzfeldt-Jakob disease in Canada
Bibliographic record
Abstract
Prions are infectious proteins that cause rare but invariably fatal neurodegenerative diseases in humans and other mammals. Sporadic Creutzfeldt-Jakob disease (sCJD) is the most common form of human prion disease, with an annual prevalence of 1-2 cases per million individuals. Though extremely rare, sCJD is devastating. This disease is rapid, with most patients dying within 5 months from the onset of symptoms and no available treatments. sCJD is heterogeneous, with diverse clinical signs, brain lesion profiles, and disease durations. It is believed this variability is attributed to different prion strains, which are influenced by host genetics and the shape of the misfolded protein. Strain diversity is poorly understood and remains to be explored experimentally. For these reasons, we have developed methodologies to exploit strain-specific properties and applied them in a retrospective analysis of 31 sCJD cases in Canada. We characterized the biochemical properties of the pathogenic prion proteins from these cases using thermal denaturation assays, capillary-electrophoresis immunoassays, and protein seeding kinetic assays. Atypical cases were inoculated into a novel animal model to analyze strain-specific properties such as incubation periods, clinical signs, and brain lesions. Within our cohort of 31 sCJD patients, we identified two atypical sCJD cases and two cases of a rare strain of sCJD called variably-protease sensitive prionopathy. We propose the two atypical sCJD cases represent novel strains of sCJD in Canada. Additionally, we have developed a sCJD strain baseline through which atypical cases could readily be identified in the future. Understanding prion strains has implications for the detection of zoonotic transmission as well as for the development of therapeutics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".