• Proceedings of the Plant Resources Society of Korea Conference
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• 2022.09a
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• pp.120-120
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• 2022

장내세균의 구성과 각종 질환의 상관관계에 대한 연구가 활발히 수행되고 있다. 대장관련 질환 뿐 아니라, 당뇨, 비만 등 대사성 질환, 심지어 정신질환에까지 장내세균 구성의 영향이 미치는 것으로 밝혀졌다. 이에 다양한 천연 소재를 활용하여 각종 동물질환모델에서 생리활성을 검토할 때, 장내세균의 구성을 분석하여 그 상관관계를 밝힐 필요가 있다. 장내세균의 구성에 따라 질환의 양상이 달라질 수 있으며, 치료에 영향을 줄 수 있다. 동물실험을 수행할 때에도 실험동물 간 장내세균의 구성이 다르면 질환의 유도 또는 천연소재에 의한 치료 패턴이 달라질 수 있음을 가정하여 본 연구를 수행하였다. 본 연구에서는 EtOH와 LPS를 이용하여 간장해 동물모델을 구축하고, 장내세균 구성을 T-RFLP법으로 분석하여 그 상관관계를 검토하였고, tracheloside 등의 천연물을 투여함으로써 성분의 대사 패턴을 확인하였다. 이 결과는 천연소재의 간장해 개선 연구를 수행하기 위한 기초 결과로 활용될 수 있다.

• Journal of the Korea Organic Resources Recycling Association
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• v.9 no.1
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• pp.119-126
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• 2001

This research was carried out to evaluate the effect of recycled wastewater and surfactant above CMC(critical micelle concentration) on the removal rate of PAHs in bench-scale slurry bioreactor. Kinetic parameters based on zero order and first order kinetic models were estimated. The first order model was able to describe the removal of phenanthrene and pyrene with high correlation coefficients. Addition of recycled wastewater could enhance the removal rates of phenanthrene and pyrene. Addition of surfactant above CMC could enhance desorption rate and removal rate of phenanthrene and pyrene.

• Applied Biological Chemistry
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• v.48 no.4
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• pp.394-399
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• 2005

The comparative molecular field analyses (CoMFA) models for the herbicidal activities against barnyardgrass (Echinochloa crus-galli) and rice plant (Orysa sativa L.) by the substituent (R) on the hexahydroisoindol-1-one ring in a series of new 2-(4-chloro-5-(2-chloroallyloxy)-2-fluorophenyl)-3-thioalkoxy-2,3,4,5,6,7-hexahydroisoindol-1-one derivatives were conducted and discussed for selectivity between both plants. The statistical results of the two best models (B2 & R7) showed the best predictability for the herbicidal activities based on the cross-validated value $q_2(r^2cv.=0.529{\sim}0.755)$ and none cross-validated value $({r^2}_{ncv.}=0.937{\sim}0.945)$, respectively. Based on the findings, the predictability and fitness of the model (B2) for barnyard grass was better than that of the model (R7) for rice plant. From the two models and contour maps, it is revealed that the novel selective character for herbicidal activity between the two plants depend on the electrostatic field and steric field for the substituent of ortho-positions on the S-phenyl group as R-substituent in hexahydroisoindol-1-one ring.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.679-686
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• 2019

Characteristics of adsorption equilibrium, kinetic and thermodynamic of aniline blue onto activated carbon from aqueous solution were investigated as function of initial concentration, contact time and temperature. Adsorption isotherm of aniline blue was analyzed by Langmuir, Freundlich, Redlich-Peterson, Temkin and Dubinin-Radushkevich models. Langmuir isotherm model fit better with isothermal data than other isotherm models. Estmated Langmuir separation factors ($R_L=0.036{\sim}0.068$) indicated that adsorption process of aniline blue by activated carbon could be an effective treatment method. Adsorption kinetic data were fitted to pseudo first order model, pseudo second order model and intraparticle diffusion models. The kinetic results showed that the adsorption of aniline blue onto activated carbon well followed pseudo second-order model. Adsorption mechanism was evaluated in two steps, film diffusion and intraparticle diffusion, by intraparticle diffusion model. Thermodynamic parameters such as Gibbs free energy, enthalpy and entropy for adsorption process were estimated. Enthalpy change (48.49 kJ/mol) indicated that this adsorption process was physical adsorption and endothermic. Since Gibbs free energy decreased with increasing temperature, the adsorption reaction became more spontaneously with increasing temperature. The isosteric heat of adsorption indicated that there is interaction between the adsorbent and the adsorbate because the energy heterogeneity of the adsorbent surface.

• Smart Media Journal
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• v.12 no.10
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• pp.93-101
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• 2023

Climate change has emerged as a global problem, with frequent temperature increases, droughts, and floods, and it is predicted that it will have a great impact on the characteristics and productivity of crops. Cnidium officinale is used not only as traditionally used herbal medicines, but also as various industrial raw materials such as health functional foods, natural medicines, and living materials, but productivity is decreasing due to threats such as continuous crop damage and climate change. Therefore, this paper proposes a model that can predict the physiologically active ingredient index according to the climate change scenario of Cnidium officinale, a representative medicinal crop vulnerable to climate change. In this paper, data was first augmented using the CTGAN algorithm to solve the problem of data imbalance in the collection of environment information, physiological reactions, and physiological active ingredient information. Column Shape and Column Pair Trends were used to measure augmented data quality, and overall quality of 88% was achieved on average. In addition, five models RF, SVR, XGBoost, AdaBoost, and LightBGM were used to predict phenol and flavonoid content by dividing them into ground and underground using augmented data. As a result of model evaluation, the XGBoost model showed the best performance in predicting the physiological active ingredients of the sacrum, and it was confirmed to be about twice as accurate as the SVR model.

• Journal of Applied Biological Chemistry
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• v.53 no.4
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• pp.225-231
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• 2010

To understand the inhibitory activity with changing hydroxyl substituents ($R_l-R_9$) of polyhydroxy substituted 2-phenyl-l,4-benzopyrone analogues (1-25) against tyrosinase (PDB ID: oxy-form; 1WX2), molecular docking and the three dimensional quantitative structure-activity relationships (3D-QSARs: Comparative molecular field analysis (CoMFA) & Comparative molecular similarity indices analysis (CoMSIA)) were studied quantitatively. The statistically best models were CoMFA 1 and CoMSIA 1 model from the results. The optimized CoMSIA 1 model with the sensitivity of the perturbation and the prediction produced ($dq^2'/dr_{yy'}^2$=1.009 & $q^2$=0.51l) by a progressive scrambling analysis were not dependent on chance correlation. The inhibitory activities with optimized CoMSIA 1 model were dependent upon electrostatic factor (51.4%) of substrate molecules. Contour mapping the 3D-QSAR models to the active site of tyrosinase provides new insight into the interaction between tyrosinase as receptor and 2-phenyl-l,4-benzopyrone analogues as inhibitor. Therefore, the results will he able to apply to the optimization of a new potent tyrosinase inhibitors.

• The Korean Journal of Pesticide Science
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• v.12 no.1
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• pp.18-23
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• 2008

3D-QSAR on the inhibitory activities of 6-bromobenzo-[4,5]imidazo[$1,2{\alpha}$]-pyridin-8,9-diones analogues as substrate molecule were studied quantitatively using CoMFA and CoMSIA methods. The statistical values of CoMFA model was better predictability and fitness than CoMSIA model. The inhibitory activities according to the optimized CoMFA 2 model were dependent on the steric field (90.4%). From the CoMFA contour maps, it is found that the branched side chain as R-group will be directly attached to the carbon atom (ipso carbon) of substituent, the inhibitory activities had expected to increase. The positive charge favor groups were placed in the position between imidazol ring and pyridine ring, the inhibitory activities would increase. And if the groups of liner type will be substituted, hydrophilic favor group would raise inhibitory activities.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.40 no.4
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• pp.383-390
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• 2014

The following conclusion was made from the 2D-QSAR model for the tyrosinase inhibitory activity according to the variation of the substituents R1 and R2 in analogues of compound 2-[(2,6-dioxocyclohexyl)methyl]cyclohexane- 1,3-dione (1-23). The best optimized 2D-QSAR model was $Obs.pI_{50}=-0.295({\pm}0.031)TDM$ $-0.120({\pm}0.014)DMZ+0.135({\pm}0.050)DMX.R_2+6.382({\pm}0.17)$, and the correlation $r^2=0.905$) of which was greater than its predictability ($q^2=0.843$). The magnitude of the effect of tyrosinase inhibitory activities was in order of TDM > $DMX.R_2{\geq}DMZ$, and it tended to increase as the hydrophobicity of substrate molecule (ClogP > 0) as well as the steric favor of substituent $R_1$ increased. The analysis of the model implies that inhibitory activity of substrate molecule will increase as $DMX.R_2$ (Dipole moment X component of $R_2$-substituent) increases, while TDM (Total Dipole Moment) and DMZ(Dipole Moment of Z-Component) decrease. As such, it is deemed feasible to conclude, that in order to increase the inhibitory effect, it would be rather desirable to replace the polar groups within the molecules with non-polar functional groups.

• Applied Biological Chemistry
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• v.51 no.1
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• pp.38-43
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• 2008

3D-QSARs on the fungicidal activity with N-phenylbenzenesulfonamide and N-phenyl-2-thienylsul-fonamide analogues (1-34) against Fusarium wilt (Fusarium oxysporum) were discussed quantitatively using CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) methods, respectively. Generally, the CoMFA models have better predictability and fitness than the CoMSIA models. The fungicidal activities, according to the information of the optimized CoMF A 2 model $(r^2\;_{cv.}=0.523\;&\;r^2\;_{ncv.}=0.956)$, were dependent on the electrostatic field of the N-phenylbenzenesulfonamide analogues. Therefore, from the results of graphical analyses on the contour maps with the optimized CoMFA 2 model, it is expected that the characters of $R_4-substituents$ on the N-phenyl ring as steric and positive charge favor will contribute to the fungicidal activity against Fusarium wilt.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.579-586
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• 2018

With the beginning of the new era of bigdata, information extraction or prediction are an important research area. Here, we present the acquisition of semi-automatically curated large-scale biological database and the prediction of enzyme reaction annotation for analyzing the pharmacological activities of drugs. Because the xenobiotic metabolism of pharmaceutical drugs by cellular enzymes is an important aspect of pharmacology and medicine. In this study, we apply and analyze similarity models to predict bimolecular reactions between human enzymes and their corresponding substrates. Thirteen models select to reflect the characteristics of each cluster in the similarity model. These models compare based on sensitivity and AUC. Among the evaluation models, the Simpson coefficient model showed the best performance in predicting the reactivity between the enzymes. The whole similarity model implement as a web service. The proposed model can respond dynamically to the addition of reaction information, which will contribute to the shortening of new drug development time and cost reduction.