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응급실 초기에 다량의 글라이포세이트 중독과 관련된 예측인자: QTc 간격 연장
경동수 ( Dong-soo Kyung ),전재천 ( Jae-cheon Jeon ),최우익 ( Woo Ik Choi ),이상훈 ( Sang-hun Lee ) 대한임상독성학회 2020 대한임상독성학회지 Vol.18 No.2
Purpose: Taking large amounts of glyphosate is life-threatening, but the amounts of glyphosate taken by patients for suicide are not known precisely. The purpose of this study was to find the predictors of large amounts of glyphosate ingestion. Methods: This retrospective study analyzed patients presenting to an emergency department with glyphosate intoxication between 2010 and 2019, in a single tertiary hospital. The variables associated with the intake amounts were investigated. The parameters were analyzed by multivariate variate logistic regression analyses and the receiver operating characteristic (ROC) curve. Results: Of the 28 patients with glyphosate intoxication, 15 (53.6%) were in the large amounts group. Univariate analysis showed that metabolic acidosis, lactic acid, and corrected QT (QTc) interval were significant factors. In contrast, multivariate analysis presented the QTc interval as the only independent factor with intoxication from large amounts of glyphosate. (odds ratio, 95% confidence interval: 1.073, 1.011-1.139; p=0.020) The area under the ROC curve of the QTc interval was 0.838. Conclusion: The QTc interval is associated significantly with patients who visit the emergency department after being intoxicated by large amounts of glyphosate. These conclusions will help in the initial triage of patients with glyphosate intoxication.
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TarGo: network based target gene selection system for human disease related mouse models
형대진,Ann-Marie Mallon,경동수,조수영,성제경 한국실험동물학회 2019 Laboratory Animal Research Vol.35 No.4
Genetically engineered mouse models are used in high-throughput phenotyping screens to understand genotype-phenotype associations and their relevance to human diseases. However, not all mutant mouse lines with detectable phenotypes are associated with human diseases. Here, we propose the “Target gene selection system for Genetically engineered mouse models” (TarGo). Using a combination of human disease descriptions, network topology, and genotype-phenotype correlations, novel genes that are potentially related to human diseases are suggested. We constructed a gene interaction network using protein-protein interactions, molecular pathways, and co-expression data. Several repositories for human disease signatures were used to obtain information on human disease-related genes. We calculated disease- or phenotype-specific gene ranks using network topology and disease signatures. In conclusion, TarGo provides many novel features for gene function prediction.
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이한백,육정환,임유주,노한성,경동수,김황필,방두희,김범석,김태민,김미소,김동완,김태유 대한암학회 2024 Cancer Research and Treatment Vol.56 No.3
Purpose There have been needs to improve the sensitivity of liquid biopsy. This report aims to report the analytical and clinical validation of a next-generation sequencing (NGS)–based circulating tumor DNA (ctDNA) assay. Materials and Methods Analytical validation was conducted in vitro by evaluating the limit of detection (LOD), precision, and specificity for various genomic aberrations. The real-world performance in non–small cell lung cancer (NSCLC) was assessed by comparing the results of AlphaLiquid100 to the tissue-based results. Results The LODs with 30 ng input DNA were 0.11%, 0.11%, 0.06%, 0.21%, and 2.13 copies for detecting single nucleotide variants, insertions, deletions, fusions, and copy number alterations (CNA), respectively. Quantitatively, single nucleotide variants/insertions and deletions, fusions, and CNAs showed a good correlation (R2=0.91, 0.40, and 0.65; y=0.95, 1.06, and 1.19) to the manufacturer’s values, and per-base specificities for all types of variants were near 100%. In real-world NSCLC (n=122), key actionable mutations in NSCLC were detected in 60.7% (74/122) with the ctDNA assay. Comparative analysis against the NGS-based tissue results for all key mutations showed positive percent agreement (PPA) of 85.3%. For individual genes, the PPA was as high as 95.7% for epidermal growth factor receptor (EGFR) mutations and 83.3% for ALK translocations. AlphaLiquid100 detected drug-sensitive EGFR mutation at a variant allele frequency as low as 0.02% and also identified an EGFR mutation in a case where tissue sample missed. Blood samples collected post-targeted therapies revealed additional acquired mutations. Conclusion The AlphaLiquid100 ctDNA assay demonstrates robust analytical validity, offering clinically important information for NSCLC patients.
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