Efficient generation of respiratory syncytial virus (RSV)-neutralizing human MoAbs via human peripheral blood lymphocyte (hu-PBL)-SCID mice and scFv phage display libraries
Bibliographic record
Abstract
RSV is one of the major causes of pneumonia and bronchiolitis in infants and young children and is associated with high mortality. RSV neutralizing human antibody (hu-Ab) is known to mediate resistance to viral infection as well as to be an effective treatment for severe lower respiratory tract RSV infection. We have previously demonstrated that human primary and secondary immune responses can be established in severe combined immunodeficient mice engrafted with human peripheral blood lymphocytes (hu-PBL-SCID). By combining this animal model with the single-chain Fv antibody (scFv) phage display library technique, we were able to investigate further its clinical potential by generating a panel of human scFvs that exhibit both high F glycoprotein (RSV-F) binding affinities ( approximately 108 M(-1)) and strong neutralizing activities against RSV infection in vitro. Sequencing analysis of the randomly isolated anti-RSV-F scFv clones revealed that they were derived from different VH families with mutations in the complementarity-determining region 1 (CDR1). The results suggest that: (i) RSV-F-specific human immune responses and affinity maturation can be induced in hu-PBL-SCID mice; and (ii) this approach can be applied to generate large numbers of human scFvs with therapeutic potential. Despite the fact that hu-PBL-SCID mouse and human scFv phage display library have individually been established, our approach contributes a simple and significant step toward the generalization of antigen-specific human monoclonal antibody (hu-MoAb) production and their clinical applications.
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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) | 0.001 | 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".