Detection of Nipah and Hendra Viruses Using Recombinant Human Ephrin B2 Capture Virus in Immunoassays
Bibliographic record
Abstract
Nipah virus (NiV) and Hendra virus (HeV) are classified as high-consequence zoonotic viruses characterized by high pathogenicity and high mortality in animals and humans. Rapid diagnosis is essential to containing the outbreak. In this study, the henipavirus receptor ephrin B2 was examined to determine whether it could be used as a universal ligand for henipavirus detection in immunoassays. Enzyme-linked immunosorbent assays (ELISAs) were developed using recombinant ephrin B2 as the capture ligand and two monoclonal antibodies (mAbs) as detection reagents. Using mAb F27NiV-34, which cross-reacts with NiV and HeV, we were able to detect NiV and HeV, while mAb F20NiV-65 was used to detect NiV. Therefore, using these two ELISAs, we were able to differentiate between NiV and HeV. Furthermore, we developed a rapid lateral flow strip test for NiV detection using ephrin B2 as the capture ligand combined with mAb F20NiV-65 as the detector. Taken together, our results show that the combination of ephrin B2 and a specific mAb provides an excellent pairing for NiV and HeV detection.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".