Generation and characterization of a monoclonal antibody against an African swine fever virus protein encoded by the A137R gene
Bibliographic record
Abstract
The ongoing African swine fever (ASF) pandemic continues to have a major impact on global pork production and trade. Since ASF cannot be distinguished from other swine hemorrhagic fevers clinically, ASF-specific laboratory diagnosis is critical. Thus ASF virus (ASFV)-specific monoclonal antibodies (mAbs) are critical for the development of laboratory diagnostics. In this study, we report one ASFV-specific mAb, F88ASF-55, that was generated and characterized. This mAb recognizes the ASFV A137R -encoded protein (pA137R). Epitope mapping results revealed a highly conserved linear epitope recognized by this mAb, corresponding to amino acids 111–125 of pA137R. We explored the potential use of this mAb in diagnostic applications. Using F88ASF-55 as the detection antibody, six ASFV strains were detected in an enzyme-linked immunosorbent assay (ELISA) with low background. In immunohistochemistry (IHC) assays, this mAb specifically recognized ASFV antigens in the submandibular lymph nodes of animals experimentally infected with different ASFV strains. Although not all ASFV genotypes were tested in this study, based on the conserved ASFV epitope targeted by F88ASF-55, it has the potential to detect multiple ASFV genotypes. In conclusion, this newly generated ASFV pA137R-specific mAb has potential value in ASF diagnostic tool development. It can be used in ELISA, IHC, and possibly-immunochromatographic strip assays for ASFV detection. It also suggests that pA137R may be a good target for diagnostic assays to detect ASFV infection.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".