A novel approach for scrapie-associated prion (PrPSc) detection in blood using the competitive affinity of an aggregate-specific antibody and streptavidin to PrPSc
Why this work is in the frame
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Bibliographic record
Abstract
Scrapie is a fatal neurodegenerative disorder affecting sheep and goats, originating from exposure to disease-associated prions (PrPSc). An ante-mortem screening test that can detect native PrPSc in body fluids remains unavailable due to insufficient sensitivity of current detection methods that involve proteinase or denaturation treatments. We adopted an approach to detect PrPSc in whole blood using a simple proteinase- and denaturation-independent immunoassay, based on the competitive affinity of an aggregate-specific monoclonal antibody and streptavidin to PrPSc. First, we demonstrated the ability of native PrPSc to bind to streptavidin and the inhibition of this interaction by 15B3 antibody (P < 0.05). This led to a new two-step assay that involved capturing native prions from infected blood on a solid-state matrix and detection of PrPSc aggregates by evaluating the conformation-dependent conjugate catalytic activity ratio in samples against a pre-determined threshold. This test showed capacity for detecting scrapie prions in 500 μl of sheep whole blood spiked with scrapie brain homogenate containing approximately 5 ng of total brain protein, and estimated to have 500 fg of PrPSc. The test also discriminated between blood samples from scrapie-negative (6 sheep, 4 goats) and scrapie-infected animals (3 experimentally infected sheep, 7 naturally infected goats). Collectively, with the proposed high-throughput sample-processing platform, these initial studies provide insights into the development of a large-scale screening test for the routine diagnosis of scrapie.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it