• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5229-5235
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• 2016

Prostate cancer (PCa) remains one of the most widespread and perplexing of all human malignancies. Assessment of gene expression is thought to have an important impact on cancer diagnosis, prognosis and therapeutic decisions. In this context, we explored combined expression of PCa related target genes AMACR and PCA3 in 126 formalin fixed paraffin embedded prostate tissues (FFPE) from Moroccan patients, using quantitative real time reverse transcription-PCR (RT-qPCR). This quantification required data normalization accomplished using stably expressed reference genes (RGs). A panel of twelve RG was assessed, data being analyzed using GenEx V6 based on geNorm, NormFinder and statistical methods. Accordingly, the hnRNP A1 gene was identified and selected as the most stably expressed RG for reliable and accurate gene expression quantification in prostate tissues. The ratios of both PCA3 and AMACR gene expression relative to that of the hnRNP A1 gene were calculated and the performance of each target gene for PCa diagnosis was evaluated using receiver-operating characteristics. PCA3 and AMACR mRNA quantification based on RT-qPCR may prove useful in PCa diagnosis. Of particular interesting, combining PCA3 and AMACR quantification improved PCa prediction by increasing sensitivity with retention of good specificity.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.49 no.4
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• pp.375-383
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• 2023

Malic acid-catalyzed transformation has been developed to produce ginsenoside Rg3 which is increasingly in demand as a functional ingredient. The optimization of the conversion of red ginseng saponin (RGS) to ginsenoside Rg3 by acid catalyzed transformation was carried out using Box-Behnken design (BBD) based on Response Surface Analysis (RSM). The main independent variables were malic acid concentration, temperature, and reaction time. Conversion of ginsenoside Rg3 was performed according to BBD model and optimization conditions were analyzed. The concentration of the converted ginsenoside Rg3 ranged from 1.548 mg/L to 4.558 mg/L, and the highest production was obtained under the condition of reacting 1% malic acid, 50 ℃ and 9h. Consequently, The independent variables affecting the production of ginsenoside Rg3 were identified in the following order: malic acid concentration, reaction time and temperature. In addition, it was confirmed that the interaction between malic acid concentration and reaction time had a greater influence than the temperature.

• Food Science and Preservation
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• v.22 no.3
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• pp.369-376
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• 2015

This study was performed to develop the maufacturing processes of Makgeolli using red ginseng starch (RGS). After the fermentation of RGS with koji, nuruk, and yeast, the different temperature effects on the number of the yeast cells, the content of organic acid, free sugars, and total acid, and pH were investigated. There were no changes in the composition of the yeast cell number and content of organic acid amd during 20 days at $4^{\circ}C$. The content of free sugars (sucrose, glucose and mannose) and the pH value of red ginseng Makgeolli decreased during storage at $4^{\circ}C$. This meant that the total acid content and pH value increased after organic acid was produced from fermentation. Therefore, red ginseng Makgeolli is highly acidic and sour. Since high acidity helps improve storage conditions, so this developed red ginseng Makgeolli is considered safe for consumption. Furthermore, the total content of ginsenoside was 2.47 mg/mL, which was differentiate Makgeolli using red ginseng starch, with others. Therefore, new red ginseng Makgeolli is rich in organic acid, free sugars, and ginsenoside. As a result, its storage, taste, and flavor improved.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

• Korean Journal of Food Science and Technology
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• v.47 no.3
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• pp.286-292
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• 2015

We developed a rapid isolation method for fractionation of polysaccharides with different characteristics, and optimized it for the polysaccharide mixture from Korean citrus peels. A crude polysaccharide mixture, citrus-peel-enzyme (CPE) fraction was isolated from the citrus peels digested with pectinase and ethanol precipitation. CPE was further fractionated with serially diluted ethanol solution (ethanol:deionized water=8:1, 4:1, 3:1, 2:1, 1.5:1, 1:1, and 0.5:1) to produce seven fractions labeled from CPE8 to CPE0.5. Fraction from CPE8 to CPE1 were mostly composed of 11 different sugars, including rhamnogalacturonan (RG) I and II, and the sugars contained arabino-${\beta}$-3,6-galactan moiety. However, CPE0.5 did not contain RG-II and arabino-${\beta}$-3,6-galactans. Treatment of macrophages with fractions CPE8-CPE1 led to a dose-dependent increase in interleukin-6 production (IL-6), while treatment with CPE1 and CPE0.5 fractions resulted in decreased levels of IL-6. These results indicate that this isolation method may be useful for the rapid fractionation of bioactive RGs from polysaccharide mixtures.

• Korean Journal of Food Science and Technology
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• v.49 no.4
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• pp.349-354
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• 2017

The geographical origins of raw ginseng (RG) were discriminated using an electronic tongue. Taste screening, DFA (discriminant function analysis), and CDA (canonical discriminant analysis) were used to statistically analyze the data. The taste profile patterns of umami, bitterness, and sweetness of the Korean RG was different from those of the Chinese RG. The Korean RG was stronger than the Chinese RG regarding the taste of umami. DFA discriminated the geographical origins of 154 samples, with a few overlapping samples, between the Korean and Chinese RG. CDA showed that the accuracy of origin discrimination for the Korean and Chinese RGs were 87.01 and 94.81%, respectively. The final accuracy of origin discrimination was 90.91%. The distance between the centroids of each group was 2.7463. Thus, the electronic tongue analysis can be used to efficiently differentiate the geographical origins of RG.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.3
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• pp.12-21
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• 2011

We investigated the location and surveillance system of fortress using inter-visibility analysis between fortress and the capital of the Silla Dynasty. The digital terrain model(DTM) was generated with $10{\times}10m$ grid in Arcview 3.2. Then three fortresses lines(Myeonghwal-sanseong, Namsan-shinseong, Seohyeong-sanseong) were superimposed on the DTM. 4 results of this study were drew out from the cumulative visibility analysis. First, the most of fortress lines which showed the high visible frequency from the Sila-Capital(538 viewpoints) have a good aspect toward the capital. It means that 3 fortresses secured the visibility to the capital. Second, the cumulative visibility analysis from 3 fortresses generated evenly distributed visible frequency across the inside of fortress. It shows that the inner area of fortress is more advantageous to command during the war. On the contrary, a number of invisible(vulnerable) regions which is scattered on the outside were supplemented by adjacent fortress. Third, the north area of the Sila-captial showed the highest visible frequency generated by sum up the visibility from 3 fortresses. The northern captial is placed within 4km distance easy to support at the Myeonghwal and Seohyeong-sanseong. We proved that the Sila-capital had organized a solid surveillance system by 3 fortresses. Fourth, we could infer the practical process of fortress layout from comparing a cumulative visibility map. For the secure of visibility and defense systems, the fortress line would form a rising shape to the peak. This practical location theory can replace the vague common location theory that the fortress would constructed on two thirds of mountain height. It will be an empirical method in the ancient remains research.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.1
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• pp.52-60
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• 2016

The biological activity of polysaccharide is greatly influenced by polysaccharide structure and molecular distribution. Here, we developed a rapid and convenient isolation method for fractionating polysaccharides with different characteristics and optimized it using a polysaccharide mixture from Korean persimmon leaves. A crude polysaccharide mixture, persimmon leaves-enzyme (PLE) fraction, was isolated from persimmon leaves digested with pectinase and ethanol precipitation. The PLE fraction was further fractionated with a serially diluted ethanol solution (ethanol : deionized water=4:1, 2:1, 1.5:1, 1:1, and 0.5:1) to produce 10 subfractions (five precipitate fractions labeled from PLE-4 to PLE-0.5 and five supernatant fractions labeled from PLE-4S to PLE-0.5S). HPLC analysis indicated that PLE-4 and -2 consisted of diverse polysaccharides, whereas PLE-1.5, -1, and -0.5 contained high molecular weight (MW) polysaccharides. The fractions from PLE-4 to PLE-1 were mostly composed of 13 different characteristic sugars in rhamnogalacturonan (RG) I and II, and the sugars contained an arabino-${\beta}$-3,6-galactan moiety. However, PLE-0.5 did not contain RG-II or ${\beta}$-arabino-3,6-galactan. Treatment of macrophages with fractions PLE-1.5S and PLE-1S led to a $10{\mu}g/mL$ increase in interleukin (IL)-6 production, whereas treatment with PLE-4S and PLE-2S fractions composed of low MW polysaccharides resulted in reduced levels of IL-6. These results indicate that this isolation method may be useful for the rapid and convenient fractionation of bioactive RGs from polysaccharide mixtures with various properties.