Validation of an in-house real-time PCR fecal assay and comparison with two commercial assays for the antemortem detection of <i>Mycobacterium avium</i> subsp. <i>paratuberculosis</i> infection in culled sheep
Bibliographic record
Abstract
Paratuberculosis is a chronic infectious enteritis of ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP). In sheep, the antemortem detection of the infection is challenging given the slow progression of the disease and the lack of sensitive, specific, and cost-effective validated tests. We adapted an in-house real-time PCR (rtPCR) assay targeting the multi-copy IS 900 element of MAP. The sensitivity and specificity of this essay for the detection of MAP infection were estimated in a convenience sample of culled ewes from 7 infected flocks and compared to a commercial fecal rtPCR, a commercial ELISA, and fecal culture. An infected ewe was defined as a ewe with a positive culture of the ileum and/or mesenteric lymph node. A non-infected ewe was defined as a ewe negative in intestinal tissue culture, negative in fecal culture, and with no lesions consistent with paratuberculosis. The in-house rtPCR had a sensitivity estimate of 84% (95% confidence interval [CI]: 59%, 97%) among the 44 infected ewes, which was significantly higher ( p ⩽ 0.05) than the sensitivity of a commercial fecal rtPCR (52%, 95% CI: 27%, 76%; or 63%, 95% CI: 35%, 87% depending on the cutoff used), an ELISA (14%, 95% CI:2.0%, 41%), and fecal culture (21%, 95% CI: 2.7%, 59%). No statistical difference in assay specificities was observed for the 30 non-infected ewes. The in-house rtPCR is a promising tool that could be used advantageously for the antemortem detection of MAP infection in sheep.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".