• Journal of Internet Computing and Services
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• v.13 no.4
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• pp.45-52
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• 2012

T cells induce immune responses and thereby eliminate infected micro-organisms when peptides from the microbial proteins are bound to HLAs in the host cell surfaces, It is known that the more stable the binding of peptide to HLA is, the stronger the T cell response gets to remove more effectively the source of infection. Accordingly, if peptides (HLA binder) which can be bound stably to a certain HLA are found, those peptieds are utilized to the development of peptide vaccine to prevent infectious diseases or even to cancer. However, HLA is highly polymorphic so that HLA has a large number of alleles with some frequencies even in one population. Therefore, it is very inefficient to find the peptides stably bound to a number of HLAs by testing random possible peptides for all the various alleles frequent in the population. In order to solve this problem, computational methods have recently been developed to predict peptides which are stably bound to a certain HLA. These methods could markedly decrease the number of candidate peptides to be examined by biological experiments. Accordingly, this paper not only introduces a method of machine learning to predict peptides binding to an HLA, but also suggests a new prediction model so called 'knowledge-based genetic algorithm' that has never been tried for HLA binding peptide prediction. Although based on genetic algorithm (GA). it showed more enhanced performance than GA by incorporating expert knowledge in the process of the algorithm. Furthermore, it could extract rules predicting the binding peptide of the HLA alleles common in Koreans.

• Korean Journal of Food Science and Technology
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• v.34 no.3
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• pp.400-406
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• 2002

In case of doenjang, solution of browning problem might be an important remedy in order to dissolve consumers' dissatisfaction, therefore this study was performed to develop traditional doenjang which has improved in color aspect for consumers' needs. Physicochemical compositions and color values of commercialized traditional doenjang which was processed by history references of our country, were analyzed. doenjang used as samples were processed with traditional meju, which were made with soybean and mixed with various rates after following process such as soaking, steaming, cooling, chopping and grinding. The doenjang processed were storaged at $30^{\circ}C$ for 27 days, and their amino-N, pH, color values and sensory evaluation were analyzed with fermentation period. Furthermore, nitrogen results analyzed were compared with that of commercialized traditional doenjang. In the comparison with control, treated with only traditional meju, and doenjang treatments processed with different mixing rates of traditional meju and steamed soybean, the content of amino-N in control were higher than the others, and the contents of amino-N decreased with increasing contents of steamed soybean. Their pH were changed weak alkalic region into weak acidic region with fermentation period. In the aspect of color, traditional doenjang having the rate of traditional meju and steamed soybean (1:4) was most improved and also, in comparison of result of sensory evaluation with commercial traditional doenjang, its color, taste and falvor were evaluated predominent, therefore it might be thought to have competition on the market.

• Experimental and Molecular Medicine
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• v.51 no.2
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• pp.1.1-1.14
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• 2019

Hypoxia-inducible factor-$1{\alpha}$ ($HIF-1{\alpha}$) mediates tumor cell adaptation to hypoxic conditions and is a potentially important anticancer therapeutic target. We previously developed a method for synthesizing a benzofuran-based natural product, (R)-(-)-moracin-O, and obtained a novel potent analog, MO-460 that suppresses the accumulation of $HIF-1{\alpha}$ in Hep3B cells. However, the molecular target and underlying mechanism of action of MO-460 remained unclear. In the current study, we identified heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) as a molecular target of MO-460. MO-460 inhibits the initiation of $HIF-1{\alpha}$ translation by binding to the C-terminal glycinerich domain of hnRNPA2B1 and inhibiting its subsequent binding to the 3'-untranslated region of $HIF-1{\alpha}$ mRNA. Moreover, MO-460 suppresses $HIF-1{\alpha}$ protein synthesis under hypoxic conditions and induces the accumulation of stress granules. The data provided here suggest that hnRNPA2B1 serves as a crucial molecular target in hypoxiainduced tumor survival and thus offer an avenue for the development of novel anticancer therapies.

• Current Optics and Photonics
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• v.1 no.1
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• pp.51-59
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• 2017

In addition to its typical use for skin rejuvenation, fractional laser irradiation of early cancerous lesions may reduce the risk of tumor development as a byproduct of wound healing in the stroma after the controlled injury. While fractional ablative lasers are commonly used for cosmetic/aesthetic purposes (e.g., photorejuvenation, hair removal, and scar reduction), we propose a novel use of such laser treatments as a stromal treatment to delay tumorigenesis and suppress carcinogenesis. In this study, we found that non-ablative fractional laser (NAFL) irradiation may have a possible suppressive effect on early tumor growth in syngeneic mouse tumor models. We included two syngeneic mouse tumor models in irradiation groups and control groups. In the irradiation group, a thulium fiber based NAFL at 1927 nm was used to irradiate the skin area including the tumor injection region with 70 mJ/spot, while no laser irradiation was applied to the control group. Numerical simulation with the same experimental condition showed that thermal damage was confined only to the irradiation spots, sparing the adjacent tissue area. The irradiation groups of both tumor models showed smaller tumor volumes than the control group at an early tumor growth stage. We also detected elevated inflammatory cytokine levels a day after the NAFL irradiation. NAFL treatment of the stromal tissue could potentially be an alternative anticancer therapeutic modality for early tumorigenesis in a minimally invasive manner.

• Journal of Nutrition and Health
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• v.52 no.2
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• pp.139-148
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• 2019

Purpose: Ulcerative colitis is a common inflammatory bowel disease. Prolonged colitis can be a risk factor for the development of colorectal cancer. Mulberry twig (MT, Sangzhi), a dry branch of Morus alba L., which is widely distributed throughout East Asia, has been shown to have anti-inflammatory activities in the cells. However, the effects of MT extracts on colitis in in vivo are limited. Therefore, in this study, we investigated the anti-inflammatory effects of MT extracts in the dextran sulfate sodium (DSS)-induced mouse colitis model. Methods: Six week-old, male ICR mice were divided into 3 groups: Control (n = 5), DSS (n = 7), and DSS+MT (n = 7) groups. Mice in the DSS and DSS+MT groups were administrated 3% DSS in drinking water for 5 days to induce colitis. At the same time, water extracts of MT (5 g/kg body weight/day) were orally administered to mice in the DSS+MT groups for 5 days. Results: The MT extracts significantly reduced the clinical and pathological characteristics of colitis. Disease activity index, mucosal thickness, and colonocyte proliferation were significantly reduced in the DSS+MT group compared with the DSS group. Furthermore, MT administration reduced the levels of plasma $TNF-{\alpha}$, IL-6, and the colonic myeloperoxidase activity as well as mRNA expression of $TNF-{\alpha}$, IL-6, Cox-2, and iNOS. Conclusion: Taken together, these results suggest that MT water extracts have potent anti-colitis activities in the mouse colitis model.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.645-652
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• 2019

Phosphor with phosphorus doped with rare earth ions was investigated by searching Sr and Eu phosphors suitable for substitution of Eu ions with similar ionic radius to polyphosphate host. The $NaSr(PO_3)_3$ phosphor was synthesized by the solid state method and the $NaSr(PO_3)_3:Eu^{2+}$ phosphor was prepared by the carbon thermal reduction method. Both of the phosphors were identified by X - ray diffraction. The excitation and emission spectra of $NaSr(PO_3)_3:Eu^{3+}$ increased fluorescence intensity and intensity quenching with increasing $Eu^{3+}$ concentration. The higher the $Eu^{3+}$ concentration in the emission spectrum, the higher the local symmetry of $Eu^{3+}$ environment. The mechanism of concentration quenching, in which fluorescence decreases due to the energy transfer between $Eu^{2+}$ ions with the closest critical distance between $Eu^{2+}$ ions with increasing $Eu^{2+}$ ion concentration, was confirmed in the emission spectrum of $NaSr(PO_3)_3:Eu^{2+}$ concentration. It is possible to change the fluorescent region through the post-processing of single rare earth ion added phosphors, and it is possible to change the fluorescence by applying the energy transfer and concentration quenching mechanism according to the local symmetry of $Eu^{3+}$ will be used for high phosphor development.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.435-447
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• 2019

In order to prevent unnecessary re-admission, it is necessary to intensively manage the groups with high probability of re-admission. For this, it is necessary to develop a re-admission prediction model. Two - year discharge summary data of one university hospital were collected from 2016 to 2017 to develop a predictive model of re-admission. In this case, the re-admitted patients were defined as those who were discharged more than once during the study period. We conducted descriptive statistics and crosstab analysis to identify the characteristics of rehospitalized patients. The re-admission prediction model was developed using logistic regression, neural network, and decision tree. AUC (Area Under Curve) was used for model evaluation. The logistic regression model was selected as the final re-admission predictive model because the AUC was the best at 0.81. The main variables affecting the selected rehospitalization in the logistic regression model were Residental regions, Age, CCS, Charlson Index Score, Discharge Dept., Via ER, LOS, Operation, Sex, Total payment, and Insurance. The model developed in this study was limited to generalization because it was two years data of one hospital. It is necessary to develop a model that can collect and generalize long-term data from various hospitals in the future. Furthermore, it is necessary to develop a model that can predict the re-admission that was not planned.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.278-280
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• 2019

Flow cytometer is one of the instrument that can measure various optical properties of a single cell or microparticle. These parameters including size, granularity, and fluorescence intensity are determined by the physical and optical interaction of the cells with excitation light source. However, users have some difficulties such as high cost, size of instrument, and limited fluorescence selectivity. In addition, abundant data is also unintentionally acquired even though user wants to have a single optical parameter. For these reasons, the use of flow cytometer is more challenging for researchers to apply their study. Therefore, the proposed study aims to develop a low-cost portable fluorescence acquisition system using a commercially available light-emitting diode and photodiode. It is designed by a 3D printer, and fluorescence selectivities are increased by changing of the light source / optical filter / detection sensor. Various number sets of fluorescently labeled cells were measured, and its feasibility was evaluated through the proposed system. As a result, acquried fluorescence intensities were proportional to the concentration of the cells and showed high linearity.

• The Korean Journal of Food And Nutrition
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• v.33 no.6
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• pp.655-665
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• 2020

In this study, chemical information on a total of 20 individual compounds was constructed to identify isoflavones from the previous reports related with used parts(seeds, leaves, stems, pods) and products of soybean(Glycine max L.). Through constructed library and UPLC-DAD-QToF/MS analysis, a total of 19 individual isoflavones including aglycones, glucosides, acetylglucosides and malonylglucosides as major compounds was identified and quantified from 14 selected soybean seeds. Among them, genistein 7-O-(2"-O-apiosyl)glucoside and genistein 7-O-(6"-O-apiosyl)glucoside(ambocin) were identified tentatively as novel compounds in soybean seeds. Besides, among malonylglucosides, glycitein 4'-O-(6"-O-malonyl)glucoside was estimated for the first time. Total isoflavone contents were distributed from 240.21 to 445.21(mg/100 g, dry matter) and 7-O-6"-O-malonylglucosides were composed of 77.8% on total isoflavone as well as genistein derivatives were confirmed as major class. It was considered importantly that the development of isoflavone-rich varieties was necessary to strengthen their effects such as anti-inflammation, anti-cancer and menopause mitigation. The qualitative and quantitative data presented precisely in this study could be help to select and breed isoflavone-rich varieties. Furthermore, their basic isoflavone profile is expected to be applied to estimate the change of isoflavone conjugates on bioavailability after soy food supplements.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.25-34
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• 2020

In this paper, we empirically compare the effectiveness of training models to recognize beauty-related skin disease using supervised deep learning algorithms. Recently, deep learning algorithms are being actively applied for various fields such as industry, education, and medical. For instance, in the medical field, the ability to diagnose cutaneous cancer using deep learning based artificial intelligence has improved to the experts level. However, there are still insufficient cases applied to disease related to skin beauty. This study experimentally compares the effectiveness of identifying beauty-related skin disease by applying deep learning algorithms, considering CNN, ResNet, and SE-ResNet. The experimental results using these training models show that the accuracy of CNN is 71.5% on average, ResNet is 90.6% on average, and SE-ResNet is 95.3% on average. In particular, the SE-ResNet-50 model, which is a SE-ResNet algorithm with 50 hierarchical structures, showed the most effective result for identifying beauty-related skin diseases with an average accuracy of 96.2%. The purpose of this paper is to study effective training and methods of deep learning algorithms in consideration of the identification for beauty-related skin disease. Thus, it will be able to contribute to the development of services used to treat and easy the skin disease.