Evaluation of PCR assays for the detection of Campylobacter fetus in bovine preputial scrapings and the identification of subspecies in South African field isolates
Bibliographic record
Abstract
As a result of the high lability and slow growth of Campylobacter fetus subspecies, the laboratory diagnosis of bovine genital campylobacteriosis has always been difficult. This is especially true under South African conditions, where farms are far apart, laboratories are only present in major centres and there are high ambient temperatures. In order to overcome the shortcomings associated with traditional diagnostic methods, the implementation of a molecular assay was sought. This work describes how a previously published PCR assay (MG3F/ MG4R primers) was adapted, optimised and applied in the diagnostic laboratory to test preputial samples directly for the presence of Campylobacter fetus. Field evaluation of the assay revealed an analytical sensitivity and specificity of 85.7% and 99%, respectively. Subsequent genotyping and phenotyping of a diverse collection of South African field isolates revealed that South Africa has an unexpected and previously unreported high incidence of Campylobacter fetus subsp. venerealis biovar intermedius strains. These strains were not identified correctly by the subspecies-specific primer set evaluated. Until such time that cost- effective genotyping methods are available to diagnostic laboratories in South Africa, and other countries with these atypical Campylobacter fetus subsp. venerealis strains, the need for bacterial culture will persist. Identification to subspecies level of isolates at present remains dependent upon a single phenotypic criterion, namely tolerance to 1% glycine.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".