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Accurate quantification of genetically modified organisms (GMOs) is essential for regulatory compliance, especially under threshold-based labeling policies. In this study, we developed and validated twelve event-specific duplex chamber- or chip-based digital PCR (cdPCR) methods using microfluidic array plates to quantify GM maize events approved in South Korea. In contrast to conventional real-time PCR, the cdPCR approach allows for absolute quantification without standard curve calibration and incorporates event-specific zygosity ratio correction to improve accuracy of the measurement. The method was evaluated at GMO content levels of 0.9%, 3.0%, and 5.0%. It demonstrated high sensitivity and robustness, with trueness, precision, and reproducibility satisfying the minimum performance criteria recommended by international guidelines. Comparative analysis with real-time quantitative PCR (qPCR) showed comparable accuracy; however, cdPCR provided advantages in cost-efficiency and operational simplicity. These findings support the applicability of duplex cdPCR as a practical and reliable tool for GMO quantification, particularly in national regulatory laboratories and for enforcement of labeling thresholds such as Korea's 3.0% rule.
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http://dx.doi.org/10.1080/21645698.2025.2548053 | DOI Listing |
Small Methods
September 2025
Department of Pathology, College of Medicine, Hanyang University, Seoul, Republic of Korea.
While human epidermal growth factor receptor (HER2) has emerged as a tumor-agnostic biomarker, standard HER2 testing for anti-HER2 therapies using immunohistochemistry (IHC) and in situ hybridization (ISH) assays remains subjective, time-consuming, and often inaccurate. To address these limitations, an ultrafast and precise HER2 testing method is developed using Lab-On-An-Array (LOAA) digital real-time PCR (drPCR), a fully automated digital PCR enabling real-time absolute quantification. A multicenter study involving four independent breast cancer cohorts cross-validates the high diagnostic accuracy of drPCR-based HER2 assessment.
View Article and Find Full Text PDFClin Chim Acta
September 2025
Department of Hematology and Blood Banking, School of Allied Medical Sciences, Iran University of Medical, Tehran, Iran. Electronic address:
Acute myeloid leukemia (AML) represents a genetically heterogeneous malignancy, with mutations in the nucleophosmin-1 (NPM1) gene identified as the most prevalent and clinically significant molecular biomarkers. These mutations play a crucial pivotal role in the realms of diagnosis, prognosis, and therapeutic decision-making. Although an ideal measurable residual disease (MRD) test has yet to be developed, there is increasing acknowledgment of the significance of advanced molecular methodologies for monitoring MRD in NPM1-mutated (NPM1) AML.
View Article and Find Full Text PDFSci Total Environ
September 2025
Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA; Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16801, USA. Electronic address:
Wastewater surveillance is increasingly an effective public health tool for responding to epidemics and preparing for annual cycles of respiratory illnesses. We measured genetic markers from Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), influenza A virus (IAV) and influenza B virus (IBV) in untreated wastewater of a university campus and its local residential community over a four-year period using digital Polymerase Chain Reaction (PCR) methods. These data were then analyzed and compared to clinical case data reported to the state by zip code.
View Article and Find Full Text PDFHistopathology
September 2025
Institute of Pathology and Molecular Pathology, Bundeswehrkrankenhaus Ulm, Ulm, Germany.
Background: Given that pathologists now frequently assess pathologic response following neoadjuvant or perioperative chemoimmunotherapy for NSCLC, we set up a multicentre study to evaluate the current practice of regression grading in Germany (Re-GraDE NSCLC).
Methods: 133 cases of NSCLC resection specimens following chemoimmunotherapy (IO) were collected from 9 high-volume lung cancer centres in Germany. Case characteristics were obtained from pathology reports/electronic medical records.
Deep learning models applied to digital histology can predict gene expression signatures (GES) and offer a low-cost, rapidly available alternative to molecular testing at the time of diagnosis. We optimized transformer-based models to infer GES results and applied this approach to pre-treatment H&E-stained biopsies from 1,940 breast cancer patients treated with neoadjuvant chemotherapy in clinical trial and real-world cohorts. The most predictive histology-derived GES for pathologic complete response (pCR) in the I-SPY2 trial was validated in four external cohorts: CALGB 40601, CALGB 40603, a trial of durvalumab plus CT, and standard-of-care CT-treated patients from the University of Chicago.
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