| Mi Sun Park | 3 Articles |
Objectives
The aim of this study was to investigate the distribution of Shiga toxin (Stx) gene-positive stool samples from dairy farmer and slaughterhouse workers in Gyeonggi-Do province. Methods A total of 621 samples from healthy farmers and 198 samples from slaughterhouse workers were screened by polymerase chain reaction (PCR) for Shiga toxigenic <i>Escherichia coli</i> (STEC) infection on stool samples. Results The PCR product of Stx-encoding genes was detected in 21 (3.4%) of 621 farmers and 15 (7.6%) of 198 slaughterhouse workers’ stool samples. Distribution of the <i>Stx</i> PCR positive workers by age increment revealed an increase in STEC infection with age increment in both workers. Distribution of the <i>Stx</i> PCR positive workers by working years revealed an increase in STEC infection with working years in farmers. Conclusion These results of the study show that slaughterhouse workers are at higher risk of STEC infection than farmers. In addition, slaughterhouse workers have a more potential source of food contamination of STEC and transmission. Citations
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Objectives
Recent genetic association studies have provided convincing evidence that several novel loci and single nucleotide polymorphisms (SNPs) are associated with the risk of developing type 2 diabetes mellitus (T2DM). The aims of this study were: 1) to develop a predictive model of T2DM using genetic and clinical data; and 2) to compare misclassification rates of different models. Methods We selected 212 individuals with newly diagnosed T2DM and 472 controls aged in their 60s from the Korean Genome and Epidemiology Study. A total of 499 known SNPs from 87 T2DM-related genes were genotyped using germline DNA. SNPs were analyzed for significant association with T2DM using various classification algorithms including Quest (Quick, Unbiased, Efficient, Statistical tree), Support Vector Machine, C4.5, logistic regression, and K-nearest neighbor. Results We tested these models using the complete Korean Genome and Epidemiology Study cohort (<i>n</i> = 10,038) and computed the T2DM misclassification rates for each model. Average misclassification rates ranged at 28.2–52.7%. The misclassification rates for the logistic and machine-learning algorithms were lower than the statistical tree algorithms. Using 1-to-1 matched data, the misclassification rate of the statistical tree QUEST algorithm using body mass index and SNP variables was the lowest, but overall the logistic regression performed best. Conclusions The K-nearest neighbor method exhibited more robust results than other algorithms. For clinical and genetic data, our “multistage adjustment” model outperformed other models in yielding lower rates of misclassification. To improve the performance of these models, further studies using warranted, strategies to estimate better classifiers for the quantification of SNPs need to be developed. Citations
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Objectives
<i>Vibrio vunificus</i> is known to cause septicemia and severe wound infections in patients with chronic liver diseases or an immuno-compromised condition. We carried out the molecular characterization of <i>V. vulnificus</i> isolates from human <i>Vibrio</i> septicemia cases based on pulsed-field gel electrophoresis (PFGE) using NotI and SfiI. Methods and Results PFGE was used to characterize a total of 78 strains from clinical cases after NotI or SfiI digestion. The geographical distribution of PFGE patterns for the strains from the southern part of Korea, a high-risk region for <i>Vibrio</i> septicemia, indicated that the isolates from southeastern Korea showed a comparatively higher degree of homology than those from southwestern Korea. Conclusions We report the genetic distribution of <i>V. vulnficus</i> isolated from <i>Vibrio</i> septicemia cases during 2000–2004 in Korea. This method has potential use as a subspecies-typing tool for <i>V. vulnificus</i> strains isolated from distant geographic regions. Citations
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