Development and evaluation of swine vesicular disease isotype‐specific antibody ELISAs based on recombinant virus‐like particles
Bibliographic record
Abstract
Swine vesicular disease (SVD) is a contagious viral disease of pigs. The clinical signs of SVD are indistinguishable from other vesicular diseases, such as senecavirus A infection (SVA) and foot-and-mouth disease (FMD). Rapid and accurate diagnostic tests of SVD are considered essential in countries free of vesicular diseases. Competitive ELISA (cELISA) is the serological test used routinely. However, although cELISA is the standard test for SVD antibody testing, this test produces a small number of false-positive results, which caused problems in international trade. The current project developed a SVD isotype antibody ELISA using recombinant SVD virus-like particles (VLP) and an SVD-specific monoclonal antibody (mAb) to reduce the percentage of false positives. The diagnostic specificities of SVD-VLP isotype ELISAs were 98.7% and 99.6% for IgM and IgG. The SVD isotype ELISAs were SVD-specific, without cross-reactivity to other vesicular diseases. A panel of 16 SVD-positive reference sera was evaluated using the SVD-VLP isotype ELISAs. All sera were correctly identified as positive by the two combined SVD-VLP isotype ELISAs. Comparison of the test results showed a high level of correlation between the SVDV antigen isotype ELISAs and SVD-VLP isotype ELISAs. 303 sera from animals lacking clinical signs and history of SVDV exposure were identified positive using SVD cELISA. These samples were examined using SVD-VLP isotype ELISAs. Of the 303 serum samples, five were positive for IgM, and five of 303 were positive for IgG. Comparable to virus neutralization test results, SVD isotype ELISAs significantly reduced the false-positive samples. Based on above test results, the combined use of cELISA and isotype ELISAs can reduce the number of false-positive samples and the use of time-consuming virus neutralization tests, with benefit for international trade in swine and related products.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".