In vitro antimicrobial susceptibility of <i>Mycoplasma bovis</i> clinical isolates recovered from bison (<i>Bison bison</i>)
Bibliographic record
Abstract
Mycoplasma bovis is a pathogen globally affecting cattle and bison herds, causing pneumonia, arthritis, mastitis, abortions, and other symptoms, leading to huge economic losses. Many studies have been done regarding the antimicrobial susceptibility of M. bovis isolated from cattle, but no such study is available for isolates recovered from bison. For the first time, in vitro susceptibilities of 40 M. bovis clinical isolates collected from bison herds in Canada are reported here. Minimal inhibitory concentration (MIC) values were determined using Sensititre® plates. The most effective MIC50 and MIC90 were for spectinomycin (1 and >64 μg/mL), tiamulin (1 and >32 μg/mL), and tulathromycin (16 and 64 μg/mL), whereas tetracyclines, fluoroquinolones, and florfenicol failed to inhibit growth of M. bovis bison isolates. Isolates were nonsusceptible to tetracyclines (100%), fluoroquinolones (97.5%), and tilmicosin (100%), whereas the highest susceptibility of bison clinical isolates was seen with spectinomycin (95%) and tulathromycin (67.5%). Two lung isolates (Mb283 and 348) were found resistant to both spectinomycin and tulathromycin. These results show a marked difference in antimicrobial susceptibility of bison isolates as compared with previously reported and laboratory reference cattle isolates, emphasizing the necessity of testing antimicrobial susceptibility of M. bovis bison isolates and to generate better therapeutic regime for improved recovery chances for infected bison herds across North America.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".