Isolation nontuberculous mycobacteria and histopathological changes in lymph nodes collected at the abattoir in cattle reactive-positive to tuberculin dermal test
Bibliographic record
Abstract
Abstract Background: The Mycobacterium tuberculosis complex causes a variety of diseases; in bovine, the common pathogen is M. bovis which is considered zoonotic. A separate group of mycobacteria, much less known, is "non-tuberculous mycobacteria (NTM) which are also infectious for animals and humans. The Mexican Official Norm (NOM-ZOO-031-1995) regulates M. bovis in cattle, but not NTM species, even though this last type of microorganisms has a confounding effect for the diagnosis of bovine tuberculosis. The objective of the study was to isolate and identify the NTM of bovine lymph nodes condemned in the slaughterhouse, to characterize the histological lesions in these tissues and to correlate bacteriological and postmortem findings with the antemortem skin test of the tuberculin. Results: Mycobacteria were isolated from 54/528 (10.2%) of the lymph nodes; 29/54 (53.7%) of these isolates were identified as M. bovis and 25/54 (46.2%) as NTM; 3 bacteriological cultures were discarded due to contamination with fungi and in one case it was not possible to identify the species. Granulomatous and pyogranulomatous inflammation were observed in 6/21 (28.6%) and 7/21 (33.3%) of the NTM-positive lymph nodes, respectively. Necrosis and mineralization were only found in 6/21(28.6%) of the lymph nodes. The species of NTM associated with granulomatous lymphadenitis were M. scrofulaceum, M. triviale, M. terrae and M. szulgai, while those causing pyogranulomatous lesions were M. szulgai, M. kansasii, M. phlei, and M. scrofulaceum. Conclusions: Considering the increase of mycobacterial infections in humans worldwide, the idetification of NTM that inducing Tuberculosis-like lesions in abattoir inspection is the first step to investigate the livestock-human-wildlife-environment interactions with especially focus on transmission dynamics.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".