Canine Parvovirus is diagnosed and neutralized by chicken IgY-scFv generated against the virus capsid protein
Bibliographic record
Abstract
Abstract Canine parvovirus (CPV) can cause acute and highly contagious bloody enteritis in dog. To obtain antibodies against CPV, hens were immunized with virus-like particles (VLP) of CPV-VP2. The IgY single chain fragment variables (scFv) were generated by T7 phage display system and expressed in E. coli system. The titer of the primary scFv library reached to 1.5 × 106 pfu/mL, and 95% of the phages contained the target fragments. The CPV-VLP and CPV-VP2 protein showed similar reaction values to the purified scFv in the ELISA test, and the results of ELISA analysis using IgY-scFv toward CPV clinical samples were consistent with commercial immunochromatographic assay (ICA) and PCR detection, the scFv did not show cross reactivity with canine distemper virus (CDV) and canine coronavirus (CCV). IgY-scFv was successfully expressed in CRFK cells, and in the virus suppression assay, 55% of CPV infections were eliminated within 24 h. Docking results demonstrated that the number of amino acids of the binding sides between scFv and VP2 were AA37 and AA40, respectively. This study revealed the feasibility of a novel functional antibody fragment development strategy by generating diversified avian IgY-scFv libraries towards the pathogenic target of interest for both detection and therapeutic purposes in veterinary medicine.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".