Chemical conjugation of a novel antibody-interleukin 2 immunoconjugate against c-erbB-2 product.
Bibliographic record
Abstract
OBJECTIVE: To develop a new chemical method to produce a monoclonal antibody (MoAb) 520C9/recombinant human interleukin 2 (rhIL-2) conjugate. METHODS: MoAb 520C9 reactive with the protooncogene c-erbB-2 product P185 was chemically conjugated with rhIL-2 by using a simple two-step method. First, the rhIL-2 was activated by Sulfosuccinimidyl 4-[N-maleimidomethyl] cyclohexane-1-carboxylate, a heterobifunctional linker, and N-succinimidyl s-acetylthioacetate was introduced onto 520C9. Then SATA on the 520C9 was reacted with the maleimide group on the activated rhIL-2 to generate 520C9-rhIL-2 immunoconjugate. RESULTS: The immunoconjugate retained the antigen binding activity compared to the respective native antibody as determined by an indirect live cell binding assay. The immunoconjugate also possessed IL-2 activity as measured by the standard CTLL-2 cells proliferation assay and the stimulation of human peripheral blood mononuclear cells (PBMCs) into lymphokine-activated killer cells. CONCLUSION: Our method of conjugation of rhIL-2 to 520C9 preserves the binding activity of the antibody and the cytokine function of IL-2. This simple and efficient method of conjugation should be applicable to other types of MoAbs and recombinant cytokines.
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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 | 0.001 |
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".