Intradermal Tuberculin Test in Water Buffalo (Bubalus bubalis): Experimental use of Mycobacterial Antigens for the Diagnosis of Bovine Tuberculosis
Bibliographic record
Abstract
The study aims to evaluate the potential use of mycobacterial ESAT6 and CFP10 antigens, Early Secretory Proteins (ESP) in the Skin Test used for bovine tuberculosis (TB) diagnosis in Water Buffalo. A pilot study was performed on 21 buffaloes from a TB outbreak and 11 buffaloes from a TB-free herd. Three concentrations of ESAT6-CFP10 (10, 20, and 30 mg) and two of ESP (50 and 100 µg) were inoculated in the Skin Test, along with PPDB, PPDA, and PBS as a negative control. Skin thickness was measured with calipers before the test and every 24 hours for 4 days. Then, to evaluate the specificity of the antigens, a field study was conducted, and 100 buffaloes from a TB-free herd were inoculated using the best antigens concentration derived from the pilot study. In the positive buffaloes, the strongest skin response was to PPDB at 24h, with some subjects becoming inconclusive at 72 and 96 h. A peak response to PPDA at 48 hours was detected, followed by a slight decrease. The response to ESP-100 µg remained high at 24 and 48 h, then decreased, remaining positive at 72 h. In the 100 TB-free buffaloes, the best specificity was observed using ESAT6-CFP10 and ESP. ESP yielded the best results, showing higher reactivity in infected animals and no reactivity in the healthy ones at 72 h. Therefore, ESP could be an excellent candidate for further extensive studies in the buffalo species to improve Skin Test performance.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".