• Journal of the Korean Society of School Health
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• v.22 no.2
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• pp.103-111
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• 2009

Purpose: By analyzing factors related to suicide ideation of Korean middle and high school students, the purpose of this study was to multi-dimensionally understand suicide ideation of Korean middle and high school students and arrange the plans to prevent suicide. Methods: This study used and analyzed the data on ‘The 3rd (Year2007) Korea Youth Health Risk Behavior Web-based Survey (KYHRBWS)' conducted by the Korea Centers for Disease Control and Prevention. In this study, we analyzed 74,698 respondents in total. SPSS 12.0 Program was used to analyze the survey. Descriptive statistics, Chi-Square Test and multivariate logistic regression were also used as research methods. Results: 23.8% of the Korean middle and high school students had suicide ideation during the last one year. Girls had higher possibility of suicide ideation by 1.51 times compared to boys. Students with poor academic achievement had more suicide ideation. In terms of health characteristics, students who perceived themselves as not healthy, and students with short weekday sleeping hours, more drinking experience and more smoking experience had more suicide ideation than others. Furthermore, students who perceived themselves as overweight or obese had more suicide ideation than other students. In terms of mental characteristics, students with high level of stress, low level of happiness and depression had more suicide ideation. Conclusion: As a result of this study, we found out that the factor that had the biggest influence on suicide ideation of Korean middle and high school students was depression. Consequently, active supports and policies to decrease suicide ideation of Korean middle and high school students are necessary. Therefore, active interviews, education for suicide prevention, and periodical screening inspection should be introduced in schools.

• Korean Journal of Oriental Medicine
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• v.17 no.3
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• pp.77-85
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• 2011

Objectives : The purpose of this study was to develop a simulator which can analyze the anti-inflammatory effects of medical herbs based on e-cell concerning p38 MAPK signal pathway. Methods : We collected data concerning medical herbs with anti-inflammatory effects and the active compounds to provide as a fundamental databse and to validate the newly developed algorithm. At this time, we used the target database as pubmed and gathered the data by data mining tool, pathway studio. Also we have developed the web-based search system for confirming database related to anti-inflammation. We researched the mechanism of actions of proteins in p38 MAPK signal pathway when active compound has been inserted into the network. We reduced total network into TAK-MKK3-p38 and made the two types of mathematical model about active compounds' interaction. Results & Conclusion : We constructed the database which have 69 cases of medical herbs, 71 cases of active compounds, about 8,000 cases of URL(Uniform Resource Locator) related to papers and reports. We designed the ordinary differential equations for response of TAK, MKK3, p38 in e-cell's cytosol and nucleus. We used this formular as measure whether an active compound of medicinal plants which is inputted by an user would have an anti-inflammation effects. We developed the visualization program which could show the change of concentration over time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.195-203
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• 2021

Recently, big data, a major technology in the IT field, has been expanding into various industrial sectors and research on how to utilize it is actively underway. In most Internet industries, user reviews help users make decisions about purchasing products. However, the process of screening positive, negative and helpful reviews from vast product reviews requires a lot of time in determining product purchases. Therefore, this paper designs and implements a system that analyzes and aggregates keywords using LDA, a big data analysis technology, to provide meaningful information to users. For the extraction of document topics, in this study, the domestic book industry is crawling data into domains, and big data analysis is conducted. This helps buyers by providing comprehensive information on products based on user review topics and appraisal words, and furthermore, the product's outlook can be identified through the review status analysis.

• Korean Journal of Agricultural Science
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• v.45 no.3
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• pp.447-454
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• 2018

Zearalenone (ZEN), a mycotoxin produced by Fusarium in food and feed, causes serious damage to the health of humans and livestock. Therefore, we compared the metabolomic profiles in the liver, serum, and urine of piglets fed a ZEN-contaminated diet using proton nuclear magnetic resonance ($^1H-NMR$) spectroscopy. The spectra from the three different samples, treated with ZEN concentrations of 0.8 mg/kg for 4 weeks, were aligned and identified using MATLAB. The aligned data were subjected to discriminating analysis using multivariate statistical analysis and a web server for metabolite set enrichment analysis. The ZEN-exposed groups were almost separated in the three different samples. Metabolic analysis showed that 28, 29, and 20 metabolites were profiled in the liver, serum, and urine, respectively. The discriminating analysis showed that the alanine, arginine, choline, and glucose concentrations were increased in the liver. Phenylalanine and tyrosine metabolites showed high concentrations in serum, whereas valine showed a low concentration. In addition, the formate levels were increased in the ZEN-treated urine. For the integrated analysis, glucose, lactate, taurine, glycine, alanine, glutamate, glutamine, and creatine from orthogonal partial least squares discriminant analysis (OPLS-DA) were potential compounds for the discriminating analysis. In conclusion, our findings suggest that potential biomarker compounds can provide a better understanding on how ZEN contaminated feed in swine affects the liver, serum, and urine.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.32 no.4
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• pp.144-153
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• 2021

Objectives: Anxiety disorders are the most common psychiatric disorders in adolescents and seem to occur the earliest among all forms of psychopathology. The aim of this study was to investigate the association of anxiety severity with health risk behaviors and mental health in adolescents. Methods: Data from the 2020 Korean Youth Risk Behavior Web-Based Survey were analyzed. A total of 54948 adolescents responded to the 7-item Generalized Anxiety Disorder Scale (GAD-7) for the assessment of their anxiety severity as well as to the mental health and health risk behavior survey. Logistic regression analysis, t tests, and variance analysis of a complex sample general linear model were used to examine the association of anxiety severity with health behaviors and mental health. Results: After statistical adjustment for sociodemographic characteristics, the subjects in the severe anxiety group were significantly more likely to be current smokers (odds ratio [OR]: 2.08, 95% confidence interval [CI]: 1.72-2.50), current drinkers (OR: 1.91, 95% CI: 1.67-2.19), experience habitual substance use (OR: 10.89, 95% CI: 8.22-14.42), have sexual intercourse (OR: 2.10, 95% CI: 1.76-2.51), and have unprotected intercourse (OR: 2.21, 95% CI: 1.67-2.92) than those in the normal group. Anxiety severity negatively correlated with sleep satisfaction and happiness, but positively correlated with stress perception, loneliness, depressive symptoms, and suicidality. Conclusion: Adolescent anxiety is associated with health risk behaviors and poor mental health. Thus, early screening and intervention for anxiety in adolescents could contribute to the management and coping of youth health risk behaviors in the community.

• Korean Journal of Radiology
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• v.23 no.5
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• pp.505-516
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• 2022

Objective: To evaluate whether artificial intelligence (AI) for detecting breast cancer on mammography can improve the performance and time efficiency of radiologists reading mammograms. Materials and Methods: A commercial deep learning-based software for mammography was validated using external data collected from 200 patients, 100 each with and without breast cancer (40 with benign lesions and 60 without lesions) from one hospital. Ten readers, including five breast specialist radiologists (BSRs) and five general radiologists (GRs), assessed all mammography images using a seven-point scale to rate the likelihood of malignancy in two sessions, with and without the aid of the AI-based software, and the reading time was automatically recorded using a web-based reporting system. Two reading sessions were conducted with a two-month washout period in between. Differences in the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and reading time between reading with and without AI were analyzed, accounting for data clustering by readers when indicated. Results: The AUROC of the AI alone, BSR (average across five readers), and GR (average across five readers) groups was 0.915 (95% confidence interval, 0.876-0.954), 0.813 (0.756-0.870), and 0.684 (0.616-0.752), respectively. With AI assistance, the AUROC significantly increased to 0.884 (0.840-0.928) and 0.833 (0.779-0.887) in the BSR and GR groups, respectively (p = 0.007 and p < 0.001, respectively). Sensitivity was improved by AI assistance in both groups (74.6% vs. 88.6% in BSR, p < 0.001; 52.1% vs. 79.4% in GR, p < 0.001), but the specificity did not differ significantly (66.6% vs. 66.4% in BSR, p = 0.238; 70.8% vs. 70.0% in GR, p = 0.689). The average reading time pooled across readers was significantly decreased by AI assistance for BSRs (82.73 vs. 73.04 seconds, p < 0.001) but increased in GRs (35.44 vs. 42.52 seconds, p < 0.001). Conclusion: AI-based software improved the performance of radiologists regardless of their experience and affected the reading time.

• The Korean Journal of Malacology
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• v.22 no.2
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• pp.109-113
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• 2006

Subcellular localization of a protein containing nuclear localization signals (NLS) has been well studied in many organisms ranging from invertebrates to vertebrates. However, no systematic analysis of NLS-containing proteins available from Mollusks has been reported. Here, we describe in silico screening of NLS-containing proteins using the mollusks database that contains 22,138 amino acids. To screen putative proteins with NLS-motif, we used both predict NLS and perl script. As a result, we have found 266 proteins containing NLS sequences which are about 1.2% out of the entire proteins. On the basis of KOG (The eukaryotic orthologous groups) analysis, we can't predict the precise functions of the NLS-containing proteins. However, we found out that these proteins belong to several types of proteins such as chromatin structure and dynamics, translation, ribosomal structure, biogenesis, and signal transduction mechanism. In addition, we have analysed these sequences based on the classes of mollusks. We could not find many from the species that are the main subjects of phylogenetic studies. In contrast, we noticed that cephalopods has the highest number of NLS-containing proteins. Thus, we have constructed mollusks NLS database and added these information and data to the mollusks database by constructing web interface. Taken together, these information will be very useful for those who are or will be studying NLS-containing proteins from mollusks.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.30-30
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• 2022

Philippines is the second world supplier of coconut by-products. As its first major genomics project, the Philippine Genome Center program for Agriculture (PGC-Agriculture) took the challenge to sequence and assemble the whole coconut genome. The project aims to provide advance genetics tools for our collaborating coconut researchers while taking the opportunity to initiate local capacity. Combination of different NGS platforms was explored and the Philippine 'Catigan Green Dwarf' (CATD) variety was selected with the breeders to be the crop's reference genome. A high quality genome assembly of CATD was generated and used to characterize important genes of coconut towards the development of resilient and outstanding varieties especially for added high-value traits. The talk will present the significant results of the project as published in various papers including the first report of whole genome sequence of a dwarf coconut variety. Updates will include the challenges hurdled and specific applications such as gene mining for host insect resistance and screening for least damaged coconuts (thus potentially insect resistant varieties). Genome-wide DNA markers as published and genes related to coconut oil qualitative/quantitative traits will also be presented, including initial molecular/biochemical studies that support nutritional and medicinal claims. A web-based genome database is currently built for ease access and wider utility of these genomics tools. Indeed, a major milestone accomplished by the coconut genomics research team, which was facilitated with the all-out government support and strong collaboration among multidisciplinary experts and partnership with advance research institutes.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.1
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• pp.16-21
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• 2022

Objectives : The purpose of this study is to investigate depression and suicide ideation according to socioeconomic changes after COVID-19 among Korean adolescent. Methods : Data on the study population were obtained from the 16th Korea Youth Risk Behavior Web-based Survey (KYRBS). The KYRBS is a nationally representative sample of Korean adolescents (aged 12-18 years) that originally included over 103 questions in 15 domains of health-risk behaviors. In the 16th KYRBS, a total 54,948 students from 793 schools responded to the survey. Chi-square test and logistic regression analysis were conducted regarding depression and suicide ideation. Results : This study suggests that changes in the family household before and after COVID-19 pandemic are also affecting the mental health of the adolescents. The study shows that worse change of family household is significant associations with suicidal ideation and depression. Adolescents reporting worse (AOR 1.38; 95% CI 1.38-1.57) and much worse (AOR 2.07; 95% CI 1.87-2.29) were significantly more likely to report depression. Adolescents reporting worse (AOR 1.34; 95% CI 1.34-1.60) and much worse (AOR 2.01; 95% CI 1.76-2.29) were significantly more likely to report suicide ideation. Conclusions : In this study, it was confirmed that young people from socially disadvantaged backgrounds are at high risk of suicide ideation and more depression. The results of this study suggest that we should consider improving the screening and prevention of mental health problems for adolescents with poor socioeconomic changes of COVID-19.