Evaluation of Western blotting methods using samples with or without sodium phosphotungstic acid precipitation for diagnosis of scrapie and chronic wasting disease.
Bibliographic record
Abstract
The purpose of this study was to enhance the sensitivity of the Western blot (WB) test for use as an alternative and confirmatory method for the diagnosis of scrapie and chronic wasting disease (CWD) in Canada by comparing 2 sample preparation procedures: an abnormal prion protein (PrPSc) concentration procedure using sodium phosphotungstic acid (PTA) precipitation and a procedure using crude sample without precipitation. A total of 100 cerebrum samples (52 sheep and 48 elk), including 66 negative (31 sheep, 35 elk) and 34 positive (21 scrapie and 13 CWD positive) samples diagnosed by using immunohistochemistry (IHC) on retropharyngeal lymph node (RPLN) and medulla oblongata at obex, were tested by using WB with the 2 sample preparation procedures. The WB using non-PTA enriched sample (crude extract) detected, on average, only 71.7% (9 of 15, 60.0% for scrapie, 5 of 6, 83.3% for CWD) of the samples that tested positive by using WB with PTA enriched samples. No case was positive by WB using crude extract but negative by WB using PTA enriched sample. No false positive was found. Serial dilution of PTA precipitated samples demonstrated that the technique increases the detection limit approximately 100 fold. Additionally, the comparison of the WB and IHC on cerebrum from all the positive cases demonstrated that WB following PTA precipitation and IHC had 100% agreement by detecting 6 positive for CWD on cerebrum; while IHC detected scrapie in only 14 out of 15 positive cerebrum samples by using WB following PTA precipitation. Phosphotungstic acid precipitation is therefore a useful adjunct to WB analysis of scrapie and CWD and tissues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".