Invited review: Improved control of Johne's disease in dairy cattle through advancements in diagnostics, testing, and management of young stock
Bibliographic record
Abstract
Johne's disease (JD; paratuberculosis) control programs have been regionally implemented across the globe, but few have successfully eradicated the pathogen (Mycobacterium avium ssp. paratuberculosis; MAP) causing this disease. The limited success may partly be attributed to excluding young stock (calves and replacement heifers or bulls) from testing strategies aimed at identifying MAP-infected cattle. Young stock can shed MAP in feces and can have detectable MAP-specific antibodies in blood, as confirmed in experimentally and naturally infected cattle. Furthermore, MAP transmission causes new infections in young stock. Calves and heifers are often included in JD management strategies on dairy farms but excluded from conventional diagnostic tests due to a presumed lag between infection and detection of MAP shedding and MAP-specific serum antibodies. We summarize evidence of MAP shedding early in the course of infection and discuss promising diagnostics, testing and management strategies to support inclusion of young stock in JD control programs. Improvements in fecal PCR, interferon-gamma release assay (IGRA), and ELISA enable earlier detection of MAP and specific early immune responses. Studies on IGRA and ELISA have focused on evaluation of new antigens and optimal age of testing. New diagnostics have been developed, including phage-based tests to detect viable MAP, as well as gene expression patterns and metabolomics to detect MAP-infected young stock. In addition, refinements in testing and management of calves and heifers may enable reductions in MAP prevalence. We provide recommendations for dairy farmers, researchers, veterinarians, and other stakeholders that may improve JD control programs with an objective to control and potentially eradicate JD. Additionally, we have identified the most pressing gaps in knowledge that currently hamper inclusion of young stock in JD prevention and control programs. In summary, transmission among young stock may cause new MAP infections, and appropriate use of new diagnostic tests, testing and management strategies for young stock may improve the efficacy of JD control programs.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.010 |
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".