Chimerism of avian <scp>IgY‐scFv</scp> and truncated <scp>IgG‐Fc</scp>: <scp>A</scp> novel strategy in cross‐species antibody generation and enhancement
Bibliographic record
Abstract
Chicken single-chain fragment variable (IgY-scFv) is a functional fragment and an emerging development in genetically engineered antibodies with a wide range of biomedical applications. However, scFvs have considerably shorter serum half-life due to the absence of antibody Fc region compared with the full-length antibody, and usually requires continuous intravenous administration for efficacy. A promising approach to overcome this limitation is to fuse scFv with immunoglobulin G (IgG) Fc region, for better recognition and mediation by the neonatal Fc receptor (FcRn) in the host. In this study, engineered mammalian ΔFc domains (CH2, CH3, and intact Fc region) were fused with anti-canine parvovirus-like particles avian IgY-scFv to produce chimeric antibodies and expressed in the HEK293 cell expression system. The obtained scFv-CH2, scFv-CH3, and scFv-Fc can bind with antigen specifically and dose-dependently. Surface plasmon resonance investigation confirmed that scFv-CH2, scFv-CH3, and scFv-Fc had different degrees of binding to FcRn, with scFv-Fc showing the highest affinity. scFv-Fc had a significantly longer half-life in mice compared with the unfused scFv. The identified ΔFcs are promising for the development of engineered Fc-based therapeutic antibodies and proteins with longer half-lives. The avian IgY-scFv-mammalian IgG Fc region opens up new avenues for antibody engineering, and it is a novel strategy to enhance the rapid development and screening of functional antibodies in veterinary and human 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 | 0.001 |
| 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".