Development of Functional Human Monoclonal Single-Chain Variable Fragment Antibody Against HIV-1 from Human Cervical B Cells
Bibliographic record
Abstract
A panel of novel recombinant single-chain variable fragment (scFv) antibody against human immunodeficiency virus type-1 (HIV-1) was isolated and characterized. We generated human scFvs using RNA harvested from cervical B lymphocytes of Kenyan prostitutes who are highly exposed to HIV-1, but remain persistently seronegative. The variable regions of the heavy (VH) and light (VL) chain antibody genes were selected as hybrids using guided-selection with the VL and VH, respectively, of a derivative of IgGb(12) using the phagemid vector pComb3X. IgGb(12) is a previously well-characterized HIV-1 neutralizing human monoclonal antibody (MAb). One of the hybrid scFv, IgA6/4L, neutralizes HIV-1 infectivity in in vitro cell culture assay. The cervical VH and VL chain antibody genes were connected by a DNA linker and subcloned in pComb3X. The cervical scFv clones were functional in recognizing HIV-1 gp120 by enzyme-linked immunosorbant assay (ELISA) and on cells in flow cytometry. Whole IgGb(12) does not inhibit binding of clones IgA6/5k nor IgA6/30lambda to gp120, which suggests that they bind different epitopes. Nucleotide sequence analysis of the cervical scFv show the clones are unique and reveal interesting characteristics of human cervical V gene pools. This work demonstrates, for the first time, cloning of a functional scFv MAb to a sexually transmitted disease pathogen from local cervical B-cell pools in exposed humans.
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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) | 0.002 | 0.001 |
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".