Design, expression, and characterization of a multivalent, combination HIV microbicide
Bibliographic record
Abstract
Many promising microbicide candidates are proteins or peptides, including neutralizing monoclonal antibodies (mAbs). Here, the expression of the HIV-neutralizing mAb b12 in transgenic plants is described. The plant-derived mAb b12 was shown to have gp120 binding activity and HIV-neutralizing activity in vitro. However, it is likely that a protein-based microbicide will need to comprise a combination of two or more products, in order to provide long-lasting and cross-clade protection. Building on the expression of mAb b12 and to address the need for a combinational agent, the expression of a fusion protein of mAb b12 with cyanovirin-N, another protein microbicide, has been explored. This fusion protein molecule is predicted to have four binding sites for HIV gp120 with two different specificities. The fusion protein was assembled and expressed in planta, and functionality was confirmed by gp120 binding and HIV neutralization in vitro. Each moiety of the fusion protein retained its binding ability to gp120. In addition, this fusion protein demonstrated increased anti-HIV potency compared to b12 or CV-N alone. This fusion protein addresses the requirement to combine microbicide products, and the production in plants is a step toward resolving the issues of manufacturing scalability and cost for developing countries.
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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) | 0.000 | 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 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".