Evaluation of Diagnostic Applications of Monoclonal Antibodies against Avian Influenza H7 Viruses
Bibliographic record
Abstract
A panel of monoclonal antibodies (MAbs) was generated from mice immunized with binary ethylenimine (BEI)-inactivated H7N1 (A/TK/ON/18-2/00) virus. Using a dot blot assay, six of seven MAbs reacted with viruses of the H7 subtype, but not with any of the other 15 hemagglutinin (HA) subtypes tested. Four of the seven MAbs reacted with 14 different H7 isolates, indicating that the MAbs binding epitopes are conserved among viruses of the H7 subtype. The binding epitopes of all seven MAbs were conformational and reacted with the HA1 fraction of the HA protein in Western blots under nonreducing conditions. Applications of these MAbs in the development of rapid tests for H7 subtype viruses were evaluated. The MAbs demonstrated reactivity with AI virus H7 antigen in immunofluorescence and immunohistochemistry assays. Monoclonal antibody 3 showed a very strong immunostaining in the formalin-fixed and paraffin-embedded tissue from the H7N3 virus-infected chicken. A double-antibody sandwich (DAS) enzyme-linked immunosorbent assay (ELISA) was developed using two of the MAbs. The DAS ELISA specifically detected all H7 strains tested in this study. A competitive ELISA (cELISA) for the detection of H7-specific antibodies was evaluated using one MAb and BEI-inactivated H7N1 virus as the antigen. All infected birds showed positive antibody responses at 7 days postinfection. The sensitivity of this cELISA was comparable with that of an influenza A nucleoprotein-based cELISA. This panel of MAbs is valuable in the development of various immunoassays.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".