Real-Time Polymerase Chain Reaction (PCR) Quantitative Detection of <i>Brassica napus</i> Using a Locked Nucleic Acid TaqMan Probe
Bibliographic record
Abstract
Several countries have introduced mandatory labeling requirements on foods derived from genetically modified organisms. Real-time quantitative Polymerase Chain Reaction (PCR) has quickly become the method of choice in support of these regulations and requires the development of separate PCR assays targeting the transgenic sequence as well as a specific endogenous gene sequence. To develop a Brassica napus-specific PCR assay, partial sequences of the acetyl-CoA carboxylase BnACCg8 gene from B. napus and the closely related Brassica rapa were determined and compared, and a region of unique nucleotide sequence was identified. Universal amplification primers were designed to either side of this region, and a locked nucleic acid TaqMan probe was designed to the B. napus-specific sequence. Evaluation of this primer/probe combination indicated a high level of specificity to B. napus: no amplification signal was observed with any other species tested, including five closely related Brassica species. The method was assayed with 14 different B. napus cultivars, and comparable amplification curves were consistently obtained for all. The assay was highly sensitive, with a limit of detection between 1 and 10 haploid copies. Practically, the method was demonstrated to be effective for the detection of processed food samples and for the quantification of Roundup Ready canola content in mixed samples.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".