• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.23-30
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• 2019

The purpose of this study is to find out the structure of the substance that affects antidiabetic using the candidate drug information for diabetes treatment. A quantitative structure activity relationship model based on machine learning method was constructed and major molecular descriptors were determined for each experimental data variables from coefficient values using a partial least squares algorithm. The results of the analysis of the molecular access system fingerprint data reflecting the candidate drug structure information were higher than those of the in vitro data analysis in terms of goodness-of-fit, and the major molecular expression factors affecting the antidiabetic effect were also variously derived. If the proposed method is applied to the new drug development environment, it is possible to reduce the cost for conducting candidate screening experiment and to shorten the search time for new drug development.

• The Journal of the Korea Contents Association
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• v.14 no.2
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• pp.506-516
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• 2014

The purpose of this study is to investigate the influence of perceived parental attachment and self-differentiation on the adjustment to college life For this study, we used research data about the adjustment to college life, perceived parental attachment and self-differentiation which were collected from 271 university students live in Busan. We carried out correlation analysis to see the relationship between perceived parental attachment, self-differentiation and the adjustment to college life. Also, we carried out stepwise multiple regression to predict the most influential variable in college life. Results of this study were as follows. First, perceived parental attachment, and self-differentiation have a meaningful positive relationship with college life. Second, attachment anxiety, attachment avoidance, family projection, and cognitive and emotional functioning have more effects on the adjustment to college. Especially attachment avoidance affects college life more than others. These results show the importance of a wide variety of policy research to develope peer support program and counseling for a better school life on schools, classes, counseling centers.

• Journal of Animal Science and Technology
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• v.63 no.2
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• pp.319-331
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• 2021

Heat stress (HS) causes adverse impacts on pig production and health. A potential biomarker of HS is required to predict its occurrence and thereby better manage pigs under HS. Information about the saliva metabolome in heat-stressed pigs is limited. Therefore, this study was aimed to investigate the effects of acute HS on the saliva metabolome and identify metabolites that could be used as potential biomarkers. Growing pigs (n = 6, 3 boars, and 3 gilts) were raised in a thermal neutral (TN; 25℃) environment for a 5-d adaptation period (CON). After adaptation, the pigs were first exposed to HS (30℃; HS30) and then exposed to higher HS (33℃; HS33) for 24 h. Saliva was collected after adaptation, first HS, and second HS, respectively, for metabolomic analysis using 1H-nuclear magnetic resonance spectroscopy. Four metabolites had significantly variable importance in the projection (VIP > 1; p < 0.05) different levels in TN compared to HS groups from all genders (boars and gilts). However, sex-specific characteristics affected metabolites (glutamate and leucine) by showing the opposite results, indicating that HS was less severe in females than in males. A decrease in creatine levels in males and an increase in creatine phosphate levels in females would have contributed to a protective effect from protein degradation by muscle damage. The results showed that HS led to an alteration in metabolites related to energy and protein. Protection from muscle damage may be attributed to the alteration in protein-related metabolites. However, energy-related metabolites showed opposing results according to sex-specific characteristics, such as sex hormone levels and subcutaneous fat layer. This study had shown that saliva samples could be used as a noninvasive method to evaluate heat-stressed pigs. And the results in this study could be contributed to the development of a diagnostic tool as a noninvasive biomarker for managing heat-stressed pigs.

• Korean Chemical Engineering Research
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• v.54 no.5
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• pp.621-629
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• 2016

Recently, the researches on quantitative structure activity relationship (QSAR) for describing toxicities or activities of chemicals based on chemical structural characteristics have been widely carried out in order to estimate the toxicity of chemicals in multiuse facilities. Because the toxicity of chemicals are explained by various kinds of molecular descriptors, an important step for QSAR model development is how to select significant molecular descriptors. This research proposes a statistical selection of significant molecular descriptors and a new QSAR model based on partial least square (PLS). The proposed QSAR model is applied to estimate the logarithm of partition coefficients (log P) of 130 polychlorinated biphenyls (PCBs) and lethal concentration ($LC_{50}$) of 14 PCBs, where the prediction accuracies of the proposed QSAR model are compared to a conventional QSAR model provided by OECD QSAR toolbox. For the selection of significant molecular descriptors that have high correlation with molecular descriptors and activity information of the chemicals of interest, correlation coefficient (r) and variable importance of projection (VIP) are applied and then PLS model of the selected molecular descriptors and activity information is used to predict toxicities and activity information of chemicals. In the prediction results of coefficient of regression ($R^2$) and prediction residual error sum of square (PRESS), the proposed QSAR model showed improved prediction performances of log P and $LC_{50}$ by 26% and 91% than the conventional QSAR model, respectively. The proposed QSAR method based on computational toxicology can improve the prediction performance of the toxicities and the activity information of chemicals, which can contribute to the health and environmental risk assessment of toxic chemicals.

• Analytical Science and Technology
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• v.29 no.1
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• pp.1-9
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• 2016

It is believed that traditional Korean medicines can be managed more scientifically through the development of logical criteria to verify their region of cultivation, and that this could contribute to the advancement of the traditional herbal medicine industry. This study attempted to determine such criteria for Sansuyu. The volatile compounds were obtained from 20 samples of domestic Corni fructus (Sansuyu) and 45 samples of Chinese Sansuyu by steam distillation. The metabolites were identified in the NIST Mass Spectral Library via the obtained gas chromatography/mass spectrometer (GC/MS) data of 53 training samples. Data binning at 0.2 min intervals was performed to normalize the number of variables used in the statistical analysis. Multivariate statistical analyses, such as principle component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed using the SIMCA-P software package. Significant variables with a variable importance in the projection (VIP) score higher than 1.0 were obtained from OPLS-DA, and variables that resulted in a p-value of less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Finally, among the 11 variables extracted, 1-ethylbutyl-hydroperoxide (9.089 min), nonadecane (20.170 min), butylated hydroxytoluene (25.319 min), 5β,7βH,10α-eudesm-11-en-1α-ol (25.921 min), 7,9-bis(2-methyl-2-propanyl)-1-oxaspiro[4.5]deca-6,9-diene-2,8-dione (34.257 min), and 2-decyldodecyl-benzene (54.717 min) were selected as markers to indicate the origin of Sansuyu. The statistical model developed was suitable for the determination of the geographical origin of Sansuyu. The cultivation areas of four Korean and eight Chinese Sansuyu samples were predicted via the established OPLS-DA model, and it was confirmed that 11 of the 12 samples were accurately classified.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.3
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• pp.92-106
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• 2017

This paper examines the validity of issuing municipal bonds for land compensation of long-term unexecuted urban parks and greenbelts. Then it suggests that municipal bonds should be issued for compensation priority areas with high rising prices. By conducting correlation analysis and PLS(Partial Least Squares) regression for 32 long-term unexecuted urban parks and greenbelts, the factors were identified that affected 'rising prices of IAPLP(Individually Announced Public Land Price) after seven years'. According to the analysis results, Variable Importance in the Projection in PLS regression was higher in 'IAPLP of base year(1.919)' and 'Accumulated rising Rates of average IAPLP in the borough(1.176).' The implications of this study are as follows. In Seoul, the accumulated rising rates of average IAPLP over the past 12 years is higher than the accumulated interest rates for seven years of urban planning facility bonds, which means that IAPLP have risen more than the interest payments due to the issuance of municipal bonds. In addition, since the actual compensation is three times that of IAPLP, it is judged that the land price is actually much higher than the interest payments. This shows that issuing municipal bonds and preferentially compensating for areas like high rising land prices can increase the economic efficiency of the budget execution. Also, for economic efficiency of budget execution, it is necessary to propose an 'area with high IAPLP' or 'a part in the borough with high rising rate of average IAPLP,' which is expected to have a high rising land price as criteria for compensation priority areas. In the future, when issuing municipal bonds to compensate long-term unexecuted urban parks and greenbelts, variousresearch on financing for municipal bonds repayment should be conducted.