Baseline analysis of Mycoplasma mycoides subsp. mycoides antigens as targets for a DIVA assay for use with a subunit vaccine for contagious bovine pleuropneumonia
Bibliographic record
Abstract
BACKGROUND: Mycoplasma mycoides subsp. mycoides (Mmm) is the causative agent of contagious bovine pleuropneumonia in cattle. A prototype subunit vaccine is being developed, however, there is currently no diagnostic test that can differentiate between infected cattle and those vaccinated with the prototype subunit vaccine. This study characterized Mmm proteins to identify potential antigens for use in differentiating infected from vaccinated animals. RESULTS: Ten Mmm antigens expressed as recombinant proteins were tested in an indirect ELISA using experimental sera from control groups, infected, and vaccinated animals. Data were imported into R software for analysis and drawing of the box and scatter plots while Cohen's Kappa assessed the level of agreement between the Mmm antigens. Two vaccine antigens (MSC_0499 and MSC_0776) were superior in detecting antibodies in sera of animals vaccinated with the subunit vaccines while two non-vaccine antigens (MSC_0636 and LppB) detected antibodies in sera of infected animals showing all clinical stages of the disease. Sensitivity and specificity of above 87.5% were achieved when the MSC_0499 and MSC_0636 antigens were tested on sera from vaccinated and infected animals. CONCLUSIONS: The MSC_0499 and MSC_0776 antigens were the most promising for detecting vaccinated animals, while MSC_0636 and LppB were the best targets to identify infected animals. Further testing of sera from vaccinated and infected animals collected at different time intervals in the field should help establish how useful a diagnostic test based on a cocktail of these proteins would be.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".