The association of detection method, season, and lactation stage on identification of fecal shedding in Mycobacterium avium ssp. paratuberculosis infectious dairy cows
Bibliographic record
Abstract
Mycobacterium avium ssp. paratuberculosis (MAP) is the causative organism of Johne's disease. Although fecal culture is considered the standard diagnostic test, the long incubation times, costs, and intermittent shedding of MAP hinder efficient screening programs based on culture results. The primary objectives of this study were to determine the detection ability of solid culture, broth culture, and real-time PCR (qPCR) for MAP in fecal samples and to assess how shedding patterns of MAP in feces vary with lactation stage and season. This knowledge could improve the use of these diagnostic assays in Johne's management programs. For this study, 51 MAP-infectious cows from 7 Atlantic Canadian dairy farms had fecal samples collected monthly over a 12-mo period. Samples were analyzed for MAP bacterial load via solid culture, broth culture, and qPCR. For all fecal samples, 46% [95% confidence interval (CI): 40 to 51%] were positive by solid culture, 55% (95% CI: 50 to 60%) by broth culture, and 78% (95% CI: 73 to 82%) by qPCR. Sensitivity of qPCR was numerically higher in the dry and postpartum lactation periods, and qPCR detection in summer and fall was 85% of that in winter and spring. Furthermore, culture-determined moderate or light shedding categories generally corresponded to qPCR cycle threshold values <35, but heavy shedding categories corresponded to qPCR values <29. Direct fecal qPCR is a MAP detection method that is quick and less costly than culture techniques, and it avoids the use of decontamination steps that could decrease numbers of bacteria in a sample below the detection limit. This study indicates that, for known MAP-positive cows, fecal qPCR had high sensitivity of MAP detection, thereby supporting the use of direct fecal qPCR as part of a Johne's herd control program.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".