Development of an Immunoglobulin M (IgM) Capture Enzyme-Linked Immunosorbent Assay for Detection of Equine and Swine IgM Antibodies to Vesicular Stomatitis Virus
Bibliographic record
Abstract
An immunoglobulin M (IgM) capture enzyme-linked immunosorbent assay (MC-ELISA) was developed for the detection of primary infection of vesicular stomatitis virus (VSV) in equine and swine sera. The test was based on the use of biotinylated sheep antibodies against equine or swine IgM molecules bound to a streptavidin-coated ELISA plate. The captured IgM antibodies were detected by application of antigens prepared from the New Jersey and the Indiana VSV serotypes (VSV-NJ and VSV-IN, respectively) and mouse polyclonal antibodies against VSV-NJ and VSV-IN. The MC-ELISA was compared to a competitive ELISA (C-ELISA) and the standard microtiter serum neutralization (MTSN) assay by testing serum samples from horses and pigs experimentally infected with VSV-NJ or VSV-IN. The MC-ELISA detected specific homologous IgM antibodies from equine and swine sera as early as 5 and 4 days postinfection (DPI), respectively, and as late as 35 DPI. The MTSN test also detected antibodies as early as 5 DPI and as late as 160 DPI. In a similar fashion, the C-ELISA detected antibodies from 6 to 7 DPI and as late as 160 DPI. These results demonstrated that the MC-ELISA is a useful test for serodiagnosis of primary VSV infection in horses and pigs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".