Development of a duplex Fluorescent Microsphere Immunoassay (FMIA) for the detection of antibody responses to influenza A and newcastle disease viruses
Bibliographic record
Abstract
Highly pathogenic avian influenza virus (HPAI) and virulent forms of avian paramyxovirus-1 (APMV-1) cause serious illnesses in domestic poultry, both of which are reportable to the World Organization of Animal Health (OIE). The clinical presentation of avian influenza (AI) and APMV-1 infections are difficult to differentiate, emphasizing the importance of rapid and sensitive serologic assays that are able to distinguish them. Currently, a variety of serological assays are used for the serologic diagnosis of both diseases, but these assays are not used in multiplex formats. In this study, development of a duplex fluorescent microsphere immunoassay (FMIA) based on Luminex xMAP Technology is described. The assay employs MagPlex magnetic microspheres that are covalently coated with recombinant avian influenza virus nucleoprotein and APMV-1 nucleocapsid antigens produced in a baculovirus insect cell expression system. The assay is able to detect AIV antibodies against all existing hemagglutinin (H1-H16) subtypes and simultaneously detect antibodies against APMV-1. In the process of this assay development different bead coupling conditions were compared. The assay has the capability of detecting serum antibodies from chickens and turkeys and optimization was accomplished by using 2462 chicken and 446 turkey field and experimental sera and had a comparable detection capability with currently used assays in the laboratory. Assay threshold values were calculated with Receiver Operating Characteristic Analysis (ROC) in non-parametric analysis due to a highly skewed data distribution; this analysis resulted in AIV nucleoprotein relative diagnostic sensitivity and specificity of 99.7%, and 97.3% respectively. The APMV-1 nucleocapsid relative diagnostic sensitivity and specificity were 95.4%, and 98.5% respectively.
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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 | 0.004 | 0.016 |
| 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".