Seroprevalence of Hepatitis A and E Viruses Based on the Third Korea National Health and Nutrition Survey in Korea

AbstractObjectivesThe purpose of this study was to investigate the seroprevalence of hepatitis A virus (HAV) and hepatitis E virus (HEV) in Korea during 2005.MethodsStudy subjects were selected from across Korea using a stratified multistage probability sampling design, and HAV and HEV seroprevalence was compared on the basis of sex, age, and residency. A total of 497 rural and urban people aged 10–99 years of age (mean ± SD age = 28.87 ± 17.63 years) were selected by two-stage cluster sampling and tested serologically for anti-HAV and anti-HEV IgG using an enzyme-linked immunosorbent assay.ResultsAmong this population, the overall seroprevalence of HAV was 63.80% (55.21% aged in their 20s and 95.92% in their 30s, p < 0.01) and that of HEV was 9.40% (5.21% aged in their 20s and 7.14% in their 30s, p < 0.01). Seroprevalence also varied according to area of residence. HEV prevalence in rural areas was higher than that of urban regions based on the anti-HEV antibody, odds ratio 3.22 (95% confidence interval: 1.46–7.10, p < 0.01). There were no significant differences between male and female against anti-HAV/HEV antibodies.ConclusionOur study suggested that the seropositive rates of HAV and HEV might be related to age and environmental conditions

Updates on the genetic variations of Norovirus in sporadic gastroenteritis in Chungnam Korea, 2009-2010

Previously, we explored the epidemic pattern and molecular characterization of noroviruses (NoVs) isolated in Chungnam, Korea in 2008, and the present study extended these observations to 2009 and 2010. In Korea, NoVs showed the seasonal prevalence from late fall to spring, and widely detected in preschool children and peoples over 60 years of age. Epidemiological pattern of NoV was similar in 2008 and in 2010, but pattern in 2009 was affected by pandemic influenza A/H1N1 2009 virus. NoV-positive samples were subjected to sequence determination of the capsid gene region, which resolved the isolated NoVs into five GI (2, 6, 7, 9 and 10) and eleven GII genotypes (1, 2, 3, 4, 6, 7, 8, 12, 13, 16 and 17). The most prevalent genotype was GII.4 and occupied 130 out of 211 NoV isolates (61.6%). Comparison of NoV GII.4 of prevalent genotype in these periods with reference strains of the same genotype was conducted to genetic analysis by a phylogenetic tree. The NoV GII.4 strains were segregated into seven distinct genetic groups, which are supported by high bootstrap values and previously reported clusters. All Korean NoV GII.4 strains belonged to either VI cluster or VII cluster. The divergence of nucleotide sequences within VI and VII intra-clusters was > 3.9% and > 3.5%, respectively. The "Chungnam(06-117)/2010" strain which was isolated in June 2010 was a variant that did not belong to cluster VI or VII and showed 5.8-8.2%, 6.2-8.1% nucleotide divergence with cluster VI and VII, respectively

Epidemics of enterovirus infection in Chungnam Korea, 2008 and 2009

Previously, we explored the epidemic pattern and molecular characterization of enteroviruses isolated in Chungnam, Korea from 2005 to 2006. The present study extended these observations to 2008 and 2009. In this study, enteroviruses showed similar seasonal prevalent pattern from summer to fall and age distribution to previous investigation. The most prevalent month was July: 42.9% in 2008 and 31.9% in 2009. The highest rate of enterovirus-positive samples occurred in children < 1-year-old-age. Enterovirus-positive samples were subjected to sequence determination of the VP1 region, which resolved the isolated enteroviruses into 10 types in 2008 (coxsackievirus A4, A16, B1, B3, echovirus 6, 7, 9, 11, 16, and 30) and 8 types in 2009 (coxsackievirus A2, A4, A5, A16, B1, B5, echovirus 11, and enterovirus 71). The most prevalent enterovirus serotype in 2008 and 2009 was echovirus 30 and coxsackievirus B1, respectively, whereas echovirus 18 and echovirus 5 were the most prevalent types in 2005 and 2006, respectively. Comparison of coxsackievirus B1 and B5 of prevalent enterovirus type in Korea in 2009 with reference strains of each same serotype were conducted to genetic analysis by a phylogenetic tree. The sequences of coxsackievirus B1 strains segregated into four distinct clusters (A, B, C, and D) with some temporal and regional sub-clustering. Most of Korean coxsackievirus B1 strains in 2008 and 2009 were in cluster D, while only "Kor08-CVB1-001CN" was cluster C. The coxsackievirus B5 strains segregated in five distinct genetic groups (clusters A-E) were supported by high bootstrap values. The Korean strains isolated in 2001 belonged to cluster D, whereas Korean strains isolated in 2005 and 2009 belonged to cluster E. Comparison of the VP1 amino acid sequences of the Korean coxsackievirus B5 isolates with reference strains revealed amino acid sequence substitutions at nine amino acid sequences (532, 562, 570, 571, 576-578, 582, 583, and 585)

Clinical Characteristics and Etiology of Travelers' Diarrhea among Korean Travelers Visiting South-East Asia

The morbidity of travelers' diarrhea (TD) is still high. This study examined the incidence of common pathogens and characteristics of TD among Korean travelers who visited South-East Asian countries. We performed a prospective study involving 479 Korean travelers with diarrheal disease from February 2009 to April 2009 and stool samples were examined and questionnaire surveys were done after arrival. Enterotoxigenic Escherichia coli (ETEC) was found in 36.0% of TD cases, as were the following: Enteroaggregative Escherichia coli (EAEC) in 27.0%, Vibrio parahaemolyticus in 13.1%, and Norovirus in 11.5%. The detected rate of classic TD was higher in men (P = 0.007), in patients who had a shorter duration trip (P = 0.023) and in patients who drank more than 1 liter of water per day (P = 0.037). Positive stool culture rates were higher in men (P = 0.005), in hospitalized patients (P = 0.013). and in those who consumed impure water or raw foods (P = 0.033). A higher severity of disease corresponded to a significantly higher culture positivity rate (P = 0.029). We should consider the possibility of other pathogens in addition to ETEC in patients with TD who visit South-East Asia. Travelers need to educate about risk factors associated with TD

Non-Marker based Mobile Augmented Reality and its Applications using Object Recognition

As the augmented reality technology has become more pervasive and applicable, it is easily seen in our daily lives regardless of fields and scopes. Existing camera vision based augmented reality techniques depend on marker based approaches rather than real world information. The augmented reality technology using marker recognition has limitations in its applicability and provision of proper environment to guarantee user's immersiveness to relevant service application programs. This study aims to implement a smart mobile terminal based augmented reality technology by using a camera built in a terminal device and image and video processing technology without any markers so that users can recognize multimedia objects from real world images and build an augmented reality service, where 3D content connected to objects and relevant information are added to the real world image. Object recognition from a real world image is involved in a process of comparison against preregistered reference information, where operation to measure similarity is reduced for faster running of the application, considering the characteristics of smart mobile devices. Furthermore, the design allows users to interact through touch events on the smart device after 3D content is output onto the terminal screen. Afterward, users can browse object related information on the web. The augmented reality technology appropriate for the smart mobile environment is proposed and tested through several experiments and showed reliable performances in the results

Robust Authentication Analysis of Copyright Images through Deep Hashing Models with Self-supervision

The increased usage of the internet and ICT has posed a significant challenge to protect copyrighted content due to advanced image forgery techniques that make image authentication extremely difficult. The aim of this paper is to establish a binary classification method for determining copyright images from copyright-free ones. A deep hashing model is introduced for an image authentication system, which uses deep learning-based perceptual hashing. Hash codes from a deep hashing model trained with a copyright image dataset are used to identify images. The deep learning model is able to learn features that represent the implicit meaning or structural information of an image. The copyright dataset, which lacks class labels, is trained with deep hashing models with self-supervision. The proposed model is based on an autoencoder or variational autoencoder model and is improved by including convolutional filters, residual blocks, and vision transformer blocks. Experimental results show that the proposed model performs a one-to-one mapping with most stored images and can retrieve related images using image features in hash collisions. The model can find the query image among the top 5 images with comparable hash codes. The results indicate that the proposed deep hashing approach is robust and applicable