Development of a sensitive monoclonal antibody-based sandwich ELISA to detect Vip3Aa in genetically modified crops
Bibliographic record
Abstract
OBJECTIVES: To develop a sensitive monoclonal antibody-based sandwich enzyme-linked immunosorbent assay (ELISA) to detect Vip3Aa in genetically modified (GM) crops and their products. RESULTS: Vegetative insecticidal proteins (Vips) are secreted by Bacillus thuringiensis (Bt) and are known to be toxic to Lepidoptera species. Vip3Aa family proteins, Vip3Aa19 and Vip3Aa20, were successfully applied in GM crops to confer an effective and persistent insecticidal resistance. A sensitive monoclonal antibody-based sandwich ELISA was developed to detect Vip3Aa in GM crops and their products. Two monoclonal antibodies were raised against the overexpressed and purified His-Vip3Aa20, were purified from mouse ascites and characterized. A sandwich ELISA method was developed using the 2G3-1D7 monoclonal antibody for capture and the biotin-labeled 1F9-1F5 monoclonal antibody for detection of Vip3Aa20. The linear detection range of the method was found to be approximately 31.25-500 pg/ml, with a sensitivity of 10.24 pg/ml. CONCLUSIONS: The established ELISA was effective for detecting Vip3Aa family proteins other than Vip3Aa8, and was successfully applied in the detection of Vip3Aa20 and Vip3Aa19 expressed in transgenic maize and cotton.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".