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Record W7117249788 · doi:10.3358/shokueishi.66.125

Development of Qualitative Real-time PCR Assays for Detecting Genetically Modified Squash Events ZW20 and CZW3

2025· article· en· W7117249788 on OpenAlexaboutno aff
Miyu Sugino, Jumpei Narushima, Chie Taguchi, Keisuke Soga, Satoko Yoshiba, Norihito Shibata

Bibliographic record

VenueFood Hygiene and Safety Science (Shokuhin Eiseigaku Zasshi) · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
Fundersnot available
KeywordsSquashGenetically modified organismGenePotyvirusGenetically modified cropsGene sequenceZucchini yellow mosaic virusTransgene

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.321
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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