Comparison of culture versus quantitative real-time polymerase chain reaction for the detection of Taylorella equigenitalis in field samples from naturally infected horses in Canada and Germany.
Bibliographic record
Abstract
A quantitative real-time polymerase chain reaction method (qPCR) was developed and tested for the detection of Taylorella equigenitalis. It was shown to have an analytical sensitivity of 5 colony-forming units (CFU) of T. equigenitalis when applied to the testing of culture swabs that mimicked field samples, and a high analytical specificity in not reacting to 8 other commensal bacterial species associated with horses. As designed, it could also differentiate specifically between T. equigenitalis and T. asinigenitalis. The qPCR was compared to standard culture in a study that included 45 swab samples from 6 horses (1 stallion, 5 mares) naturally infected with T. equigenitalis in Canada, 39 swab samples from 5 naturally infected stallions in Germany, and 311 swab samples from 87 culture negative horses in Canada. When the comparison was conducted on an individual sample swab basis, the qPCR had a statistical sensitivity and specificity of 100% and 96.4%, respectively, and 100% and 99.1% when the comparison was conducted on a sample set basis. A comparison was also made on 203 sample swabs from the 5 German stallions taken over a span of 4 to 9 mo following antibiotic treatment. The qPCR was found to be highly sensitive and at least as good as culture in detecting the presence of T. equigenitalis in post-treatment samples. The work demonstrates that the qPCR assay described here can potentially be used to detect the presence of T. equigenitalis directly from submitted sample swabs taken from infected horses and also for determining T. equigenitalis freedom following treatment.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".