Development of Qualitative Real-time PCR Assays for Detecting Genetically Modified Squash Events ZW20 and CZW3
Bibliographic record
Abstract
In March 2023, unapproved genetically modified (GM) squashes were discovered in South Korea. These were thought to be GM squash ZW20 and CZW3, which are approved for use as food only in Canada and the United States. Because the safety of ZW20 and CZW3 has not been evaluated in Japan, they must continue to be monitored to prevent their unintentional import. In this study, we developed and validated real-time PCR-based qualitative detection methods for ZW20 and CZW3. We evaluated these two detection methods on the basis of PCR amplification efficiency, limit of detection, specificity, and reproducibility to determine their utility for distinguishing and identifying ZW20 and CZW3. One method detects the zucchini yellow mosaic virus resistance gene (ZYMV-coat protein: ZYMV-cp) sequence present in both ZW20 and CZW3, whereas the other method detects the cucumber mosaic virus resistance gene (CMV-coat protein: CMV-cp) sequence present only in CZW3. Our results showed that the ZYMV-cp and CMV-cp detection methods are highly specific for GM squash ZW20 and CZW3, and are sufficiently sensitive, capable of detecting transgenes with at least 6.3 and 3.1 copies per reaction, respectively. Based on this study, we developed the official detection method for GM squash in Japan by combining the ZYMV-cp and CMV-cp detection methods to discriminate between ZW20 and CZW3, making it useful for monitoring food safety.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".