• Research in Plant Disease
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• v.22 no.3
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• pp.158-167
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• 2016

A pathogen that causes a new disease on green pumpkin in the nursery and the field was characterized and identified. Symptoms of the disease on green pumpkin were water soaking lesions and spots with strong yellow halo on leaf, brown lesion on flower, and yellow spot on fruit. The bacterial isolates from the leaf spot were pathogenic on the 8 curcubitaceae crop plants, green pumpkin, figleaf gourd, wax gourd, young pumpkin, zucchini, cucumber, melon, and oriental melon, whereas they did not cause the disease on sweet pumpkin and watermelon. They were Gram-negative, rod shape with polar flagella, fluorescent on King's B agar and LOPAT group 1a by LOPAT test. Their Biolog substrate utilization patterns were similar to Pseudomonas syringae pv. syringae's in Biolog database. Phylogenetic trees with 16S rRNA gene sequences and multilocus sequence typing (MLST) with nucleotide sequences of 4 housekeeping genes, gapA, gltA, gyrB, rpoD and those of P. syringae complex strains in the Plant Associated and Environmental Microbes Database (PAMDB) showed that the green pumpkin isolates formed in the same clade with P. syringae pv. syringae strains. The clade in MLST tree was in the genomospecies 1 group. The phenotypic and genotypic characteristics suggested that the isolates from green pumpkin lesion were P. syringae pv. syringae.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.22 no.6
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• pp.527-535
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• 2019

Purpose: There is increasing prevalence of psychiatric disorders among inflammatory bowel Disease (IBD) population. Further, presence of psychiatric disorders has been shown as an independent predictor of quality of life among patients with IBD. We intended to explore the prevalence of various psychiatric disorders among pediatric and young adult population with IBD as a population-based analysis. Methods: We did a retrospective case control analysis using a deidentified cloud-based database including health care data across 26 health care networks comprising of more than 360 hospitals across USA. Data collected across different hospitals were classified and stored according to Systematized Nomenclature of Medicine-Clinical Terms. We preidentified 10 psychiatric disorders and the queried the database for the presence of at least one of the ten psychiatric disorders among IBD patients between 5 and 24 years of age and compared with controls. Results: Total of 11,316,450 patients in the age group between 5 and 24 years and the number of patients with a diagnosis of IBD, Crohn's disease or ulcerative colitis were 58,020. The prevalence of psychiatric disorders was 21.6% among IBD mainly comprising of depression and anxiety disorder. Multiple logistic regression analysis showed, IBD is 5 times more likely associated with psychiatric disorders than controls, p<0.001). We showed a steady increasing trend in the incidence of psychiatric disorders among IBD patients (2% in 2006 to 15% in 2017). Conclusion: Largest population-based analysis demonstrated an increased prevalence of psychiatric disorders among IBD patients. Our study emphasizes the need for psychological and mental health services to be incorporated as a part of the routine IBD clinic.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.805-813
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• 2012

In this paper, we have designed and developed a middleware for an effectively approaching database to the existed brain disease clinical research system. The brain disease clinical research system was consisted of two parts i.e., a register and an analyzer. Since the register collects the registration data the analyzer yields a statistical data which based on the diverse variables. The middleware has designed to database management and a large data query processing of clients. By separating the function of each feature as a module, the module which was weakened connectivity between functionalities has been implemented the re-use module. And image data module used a new compression method from image to text for an effective management and storage in database. We tested the middleware system using 700 actual clinical medical data. As a result, the total data transmission time was improved maximum 115 times faster than the existing one. Through the improved module structures, it is possible to provide a robust and reliable system operation and enhanced security functionality. In the future, these middleware importances should be increased to the large medical database constructions.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1293-1297
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• 2016

Cholangiocarcinoma (CCA) is a serious problem in Thailand, particularly in the northeastern and northern regions. Database of population at risk are need required for monitoring, surveillance, home health care, and home visit. Therefore, this study aimed to develop a geographic information system (GIS) database and Google map of the population at risk of CCA in Mueang Yang district, Nakhon Ratchasima province, northeastern Thailand during June to October 2015. Populations at risk were screened using the Korat CCA verbal screening test (KCVST). Software included Microsoft Excel, ArcGIS, and Google Maps. The secondary data included the point of villages, sub-district boundaries, district boundaries, point of hospital in Mueang Yang district, used for created the spatial databese. The populations at risk for CCA and opisthorchiasis were used to create an arttribute database. Data were tranfered to WGS84 UTM ZONE 48. After the conversion, all of the data were imported into Google Earth using online web pages www.earthpoint.us. Some 222 from a 4,800 population at risk for CCA constituted a high risk group. Geo-visual display available at following www.google.com/maps/d/u/0/edit?mid=zPxtcHv_iDLo.kvPpxl5mAs90&hl=th. Geo-visual display 5 layers including: layer 1, village location and number of the population at risk for CCA; layer 2, sub-district health promotion hospital in Mueang Yang district and number of opisthorchiasis; layer 3, sub-district district and the number of population at risk for CCA; layer 4, district hospital and the number of population at risk for CCA and number of opisthorchiasis; and layer 5, district and the number of population at risk for CCA and number of opisthorchiasis. This GIS database and Google map production process is suitable for further monitoring, surveillance, and home health care for CCA sufferers.

• Culinary science and hospitality research
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• v.21 no.4
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• pp.251-270
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• 2015

This study was, based on traditional know-how indigenous to Korea, to systemize the knowledge on how to improve health by dining, and to make the best of it statistically. For this purpose, the knowledge in the Sikryo-chanryo(食療纂要), in Korean pronunciation and Siglyochan-yo in Chinese characters, which is an old text referring to diet therapy peculiar to Korea, was compiled into a database and analyzed statistically. Data processing was used as a 'Relational data model'. In addition, we have used nine data table to express diet therapy peculiar to Korea in the Siglyochan-yo. The software used for data construction was Microsoft Access 2014. As a result, the Sikryo-chanryo database, which can provide information on both disease treatment by food, medicines, and gourmet ingredients applicable to every kind of symptom, as well as the names of disease, was set up at in a PC interface. By employing the 'Relational data model', we can replace researching in the conventional method by employing the database.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.447-450
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• 2003

In this research, we propose an automatic knowledge acquisition and composite knowledge expression mechanism based on machine learning and relational database. Most of traditional approaches to develop a knowledge base and inference engine of expert systems were based on IF-THEN rules, AND-OR graph, Semantic networks, and Frame separately. However, there are some limitations such as automatic knowledge acquisition, complicate knowledge expression, expansibility of knowledge base, speed of inference, and hierarchies among rules. To overcome these limitations, many of researchers tried to develop an automatic knowledge acquisition, composite knowledge expression, and fast inference method. As a result, the adaptability of the expert systems was improved rapidly. Nonetheless, they didn't suggest a hybrid and generalized solution to support the entire process of development of expert systems. Our proposed mechanism has five advantages empirically. First, it could extract the specific domain knowledge from incomplete database based on machine learning algorithm. Second, this mechanism could reduce the number of rules efficiently according to the rule extraction mechanism used in machine learning. Third, our proposed mechanism could expand the knowledge base unlimitedly by using relational database. Fourth, the backward inference engine developed in this study, could manipulate the knowledge base stored in relational database rapidly. Therefore, the speed of inference is faster than traditional text -oriented inference mechanism. Fifth, our composite knowledge expression mechanism could reflect the traditional knowledge expression method such as IF-THEN rules, AND-OR graph, and Relationship matrix simultaneously. To validate the inference ability of our system, a real data set was adopted from a clinical diagnosis classifying the dermatology disease.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.65-71
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• 2016

To reduce the expenses for development a novel drug, systems biology has been studied actively. Target prediction, a part of systems biology, contributes to finding a new purpose for FDA(Food and Drug Administration) approved drugs and development novel drugs. In this paper, we propose a classification model for predicting novel target genes based on relation between target genes and disease related genes. After collecting known target genes from TTD(Therapeutic Target Database) and disease related genes from OMIM(Online Mendelian Inheritance in Man), we analyzed the effect of target genes on disease related genes based on PPI(Protein-Protein Interactions) network. We focused on the distinguishing characteristics between known target genes and random target genes, and used the characteristics as features for building a classifier. Because our model is constructed using information about only a disease and its known targets, the model can be applied to unusual diseases without similar drugs and diseases, while existing models for finding new drug-disease associations are based on drug-drug similarity and disease-disease similarity. We validated accuracy of the model using LOOCV of ten times and the AUCs were 0.74 on Alzheimer's disease and 0.71 on Breast cancer.

• Genomics & Informatics
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• v.19 no.3
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• pp.26.1-26.3
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• 2021

Previous approaches to create a controlled vocabulary for Japanese have resorted to existing bilingual dictionary and transformation rules to allow such mappings. However, given the possible new terms introduced due to coronavirus disease 2019 (COVID-19) and the emphasis on respiratory and infection-related terms, coverage might not be guaranteed. We propose creating a Japanese bilingual controlled vocabulary based on MeSH terms assigned to COVID-19 related publications in this work. For such, we resorted to manual curation of several bilingual dictionaries and a computational approach based on machine translation of sentences containing such terms and the ranking of possible translations for the individual terms by mutual information. Our results show that we achieved nearly 99% occurrence coverage in LitCovid, while our computational approach presented average accuracy of 63.33% for all terms, and 84.51% for drugs and chemicals.

• Korean Journal of Poultry Science
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• v.32 no.1
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• pp.23-27
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• 2005

The aim of this study was to investigate differentially expressed proteins between normal chicken liver and chicken liver inffeted by Salmonella pullorum. 2-dimensional electrophoresis (2DE) and mass spectrometry (MS) were used to identify the proteins. More than 300 protein spots were detected on silver stained 2DE gels using pH 3$\~$10 gradients. The most outstanding protein spot was further analyzed by MALDI-TOF MS and protein database using the Mascot search engine. The protein was finally identified as APOAI (Apolipoprotein AI). Based on the known function of the APOAI, this gene acts protective action against the accumulation of platelet thrombin at the site of vascular damage for the pullorum disease. Therefore APOAI protein, identified in this study, can be a valuable biomarker in relation to the pullorum disease in chicken.

• Journal of Preventive Medicine and Public Health
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• v.34 no.4
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• pp.372-378
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• 2001

Objectives : This study introduced the healthy life-year(HeaLY), a composite indicator of disease burden, and used it to estimate the burden of major cancers in Korea. Methods : We collected data from the national death certificate database, the national health insurance claims database and the abridged life table. This data was used to create a spreadsheet and estimate the burden of major cancers by sex in terms of HeaLYs. Results : The burden of 10 major cancers for males was 2,248.97 person-year in terms of HeaLYs. Stomach cancer, liver cancer, and lung cancer were responsible for 75.2% of the burden of 10 major cancers. The disease burden of 10 major cancers for females was estimated to be 1,567.58 person-years. About two thirds of HeaLYs lost were from stomach cancer, liver cancer, lung cancer, colorectal cancer, and breast cancer. The rankings among 10 major cancers were somewhat different in terms of both HeaLYs and deaths as the HeaLY method considers both mortality and morbidity. Conclusions : Despite the limitations of the data sources, we conclude that HeaLY can aid in setting policy priorities concerning major cancers by estimating the disease burden of these cancers. Time-series analysis of the disease burden using HeaLY and DALY will elucidate the strengths and weaknesses of both methods.