Application of the Fluorescence Polarization Assay for Detection of Caprine Antibodies to <i>Brucella melitensis</i> in Areas of High Prevalence and Widespread Vaccination
Bibliographic record
Abstract
The screening Rose Bengal test (RBT), the buffered plate agglutination test (BPAT), and the confirmatory complement fixation test (CFT) are currently approved by the World Organization for Animal Health (OIE) for diagnosis of goat brucellosis. However, RBT (at 3% or 8% cell concentration) is known to be affected by vaccinal antibodies. In the present study, Mexican and Canadian OIE tests were compared with the fluorescence polarization assay (FPA), alone or in combination, using indirect and competitive enzyme-linked immunosorbent assays as classification variables for goat sera obtained from an area of high prevalence and widespread vaccination. The relative sensitivities and specificities were, respectively, 99.7% and 32.5% for RBT3, 92.8% and 68.8% for RBT8, 98.4% and 84.8% for Canadian CFT, 83.7% and 65.5% for Mexican CFT, and 78.1% and 89.3% for FPA. The use of FPA as the confirmatory test in combination with other tests significantly increased the final specificities of the screening tests alone; BPAT, RBT3, and RBT8 plus FPA resulted in final specificities of 90%, 91.2%, and 91.3%, respectively, whereas for the combinations RBT3 plus Mexican CFT, RBT8 plus Mexican CFT, and BPAT plus Canadian CFT, specificities were 65.5%, 63.2%, and 91.7%, respectively. We suggest that FPA may be routinely applied as an adaptable screening test for diagnosis of goat brucellosis and as a confirmatory test for screening test series. Some advantages of FPA are that its cutoff can be adjusted to improve its sensitivity or specificity, it is a low-cost and easy-to-perform test of choice when specificity is relevant or when an alternative confirmatory test is not available, and it is not affected by vaccination, thus reducing the number of misdiagnosed and killed goats.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".