Quantifying fecal shedding of Mycobacterium avium ssp. paratuberculosis from calves after experimental infection and exposure
Bibliographic record
Abstract
Johne's disease, a chronic enteritis caused by Mycobacterium avium ssp. paratuberculosis (MAP), causes large economic losses to the dairy industry worldwide. Fecal shedding of MAP contaminates the environment, feed, and water and contributes to new infections on farm, yet there is limited knowledge regarding mechanisms of shedding, extent of intermittent shedding, and numbers of MAP bacteria shed. The objectives were to (1) compare (in an experimental setting) the frequency at which intermittent shedding occurred and the quantity of MAP shed among pen mates that were inoculated or contact-exposed (CE); and (2) determine whether an association existed between inoculation dose and quantity of MAP shed. In the first experiment, 32 newborn Holstein-Friesian bull calves were allocated to pens in groups of 4, whereby 2 calves were inoculated with a moderate dose (MD; 5 × 10 8 cfu) of MAP and 2 calves acted as CE. Calves were group-housed for 3 mo, fecal samples were collected and cultured, and culture-positive samples were quantified. In the second experiment, 6 calves were inoculated with either a low (LD) or high (HD) dose of MAP (1 × 10 8 or 1 × 10 10 cfu, respectively), and fecal samples were collected for 3 mo and cultured for detection of MAP. The amount of MAP was quantified using direct extraction (DE) of DNA from fecal samples and F57-specific quantitative PCR. In experiment 1, the average amount of MAP in all culture-positive samples did not differ between MD and CE calves. In experiment 2, when comparing inoculation doses, LD calves had the lowest proportion of MAP-positive culture samples and HD had the highest, but no difference was detected in the average quantity of MAP shed. This study provided new information in regards to Johne's disease research and control regarding shedding from various inoculation doses and from CE animals; these data should inform future trials and 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".