• Journal of Microbiology and Biotechnology
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• v.14 no.5
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• pp.978-984
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• 2004

In the course of screening for a novel inhibitor of CDC2, HY558-1 was isolated from a culture broth of Penicillium minioluteum F558. Moreover, it was found that HY558-1 had an effect on both the cell cycle regulation and apoptosis of human cervical adenocarcinoma HeLa cells. A flow cytometric analysis of HeLa cells revealed appreciable cell cycle arrest at the G1 and G2/M phases following treatment with HY558-1. Furthermore, DNA fragmentation due to apoptosis was observed in HeLa cells treated with HY558-1. To obtain further information on the cell cycle arrest and apoptotic induction induced by HY558-1, the expression of certain cell cycle and apoptosis-associated proteins was examined using a Western blot analysis. The results revealed that HY558-1 inhibited the phosphorylation of pRb and decreased the expression levels of CDK2, CDC2, and cyclin A in the cell cycle progression. It was also shown that the level of $p21^{WAF1/CIP1}$ was increased in HeLa cells treated with 0.52 mM of HY558-1. Accordingly, HY558-1 was found to inhibit the proliferation of HeLa cells through the induction of G1 phase arrest by inhibiting pRb phosphorylation via an upregulation of $p21^{WAF1/CIP1}$, and G2/M phase arrest by directly inhibiting CDC2 and cyclin A. Moreover, HeLa cells treated with 0.52 mM of HY558-1 exhibited apoptotic induction associated with the cleavage of Bid and release of cytochrome c from mitochondria into the cytosol. Subsequent investigation of the activation of caspase-3 and cleavage of poly (ADP-ribose) polymerase (PARP) suggested that the mitochondrial pathway was primarily involved in the HY558-1-induced apoptosis in HeLa cells.

• Journal of Ginseng Research
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• v.44 no.6
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• pp.790-798
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• 2020

Background: Beneficial effects of Korean Red Ginseng (KRG) on polycystic ovarian syndrome (PCOS) remains unclear. Methods: We examined whether pretreatment (daily from 2 hours before PCOS induction) with KRG extract in water (KRGE; 75 and 150 mg/kg/day, p.o.) could exert a favorable effect in a dehydroepian-drosterone (DHEA)-induced PCOS rat model. Results: Pretreatment with KRGE significantly inhibited the elevation of body and ovary weights, the increase in number and size of ovarian cysts, and the elevation of serum testosterone and estradiol levels induced by DHEA. Pretreatment with KRGE also inhibited macrophage infiltration and enhanced mRNA expression levels of chemokines [interleukin (IL)-8, monocyte chemoattractant protein-1), proinflammatory cytokines (IL-1β, IL-6), and inducible nitric oxide synthase in ovaries induced by DHEA. It also prevented the reduction in mRNA expression of growth factors (epidermal growth factor, transforming growth factor-beta (EGF, TGF-β)) related to inhibition of the nuclear factor kappa-light-chain-enhancer of activated B cell pathway and stimulation of the nuclear factor erythroid-derived 2-related factor 2 pathway. Interestingly, KRGE or representative ginsenosides (Rb1, Rg1, and Rg3(s)) inhibited the activity of inflammatory enzymes cyclooxygenase-2 and iNOS, cytosolic p-IκB, and nuclear p-nuclear factor kappa-light-chain-enhancer of activated B in lipopolysaccharide-induced RAW264.7 cells, whereas they increased nuclear factor erythroid-derived 2-related factor 2 nuclear translocation. Conclusion: These results provide that KRGE could prevent DHEA-induced PCOS via antiinflammatory and antioxidant activities. Thus, KRGE may be used in preventive and therapeutic strategies for PCOS-like symptoms.

• Genomics & Informatics
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• v.16 no.2
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• pp.22-29
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• 2018

Incorporation of unique barcodes into fission yeast gene deletion collections has enabled the identification of gene functions by growth fitness analysis. For fine tuning, it is important to examine barcode sequences, because mutations arise during strain construction. Out of 8,708 barcodes (4,354 strains) covering 88.5% of all 4,919 open reading frames, 7,734 barcodes (88.8%) were validated as high-fidelity to be inserted at the correct positions by Sanger sequencing. Sequence examination of the 7,734 high-fidelity barcodes revealed that 1,039 barcodes (13.4%) deviated from the original design. In total, 1,284 mutations (mutation rate of 16.6%) exist within the 1,039 mutated barcodes, which is comparable to budding yeast (18%). When the type of mutation was considered, substitutions accounted for 845 mutations (10.9%), deletions accounted for 319 mutations (4.1%), and insertions accounted for 121 mutations (1.6%). Peculiarly, the frequency of substitutions (67.6%) was unexpectedly higher than in budding yeast (~28%) and well above the predicted error of Sanger sequencing (~2%), which might have arisen during the solid-phase oligonucleotide synthesis and PCR amplification of the barcodes during strain construction. When the mutation rate was analyzed by position within 20-mer barcodes using the 1,284 mutations from the 7,734 sequenced barcodes, there was no significant difference between up-tags and down-tags at a given position. The mutation frequency at a given position was similar at most positions, ranging from 0.4% (32/7,734) to 1.1% (82/7,734), except at position 1, which was highest (3.1%), as in budding yeast. Together, well-defined barcode sequences, combined with the next-generation sequencing platform, promise to make the fission yeast gene deletion library a powerful tool for understanding gene function.

• Korean Journal of Environmental Biology
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• v.21 no.2
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• pp.87-100
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• 2003

It is important to understand the potential human health implications of exposure to environmental chemicals that may act as hormonally active agents. It is necessary to have an understanding of how pharmaceutical and personal care products and other chemicals affect the ecosystem of our planet as well as human health. Endocrine disruption is defined as the ability of a chemical contaminating the workplace or the environment to interfere with homeostasis, development, reproduction, and/or behavior in a living organism or it's offspring. Certain classes of environmentally persistent chemicals such as polychlorinated biphenyls (PCBs), dioxins, furans, and some pesticides can adversely effect the endocrine systems of aquatic life and terrestrial wildlife. Research continues to support the theory of endocrine disruption. However, endocrine disruption researches have been applied to proteomics poorly. Proteomics can be defined as the systematic analysis of proteins for their identity, quantity and function. It could increase the predictability of early drug development and identify non-invasive biomarkers of tonicity or efficacy. Proteome analysis is most commonly accomplished by the combination of two-dimensional gel electrophoresis (2D/E) and MALDI-TOF mass spectrometry (MS) sr protein chip array and SELDI-TOF MS. Proteomics have an opportunity to play an important role in resolving the question of what role endocrine disruptors play in initiating human disease. Proteomics can also play an imfortant role in the evaluation of the risk assessment and use of risk management and risk communication tools required to address public health concerns related to notions of endocrine disruptors. Understanding the need for the proteomics and possessing knowledge of the developing biomakers used to abbess endocrine activity potential will he essential components relevant to the topic of endocrine disruptors.

• Genomics & Informatics
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• v.5 no.1
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• pp.10-18
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• 2007

Numerous studies have reported that genes with similar expression patterns are co-regulated. From gene expression data, we have assumed that genes having similar expression pattern would share similar transcription factor binding sites (TFBSs). These function as the binding regions for transcription factors (TFs) and thereby regulate gene expression. In this context, various analysis tools have been developed. However, they have shortcomings in the combined analysis of expression patterns and significant TFBSs and in the functional analysis of target genes of significantly overrepresented putative regulators. In this study, we present a web-based A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms (FCAnalyzer). This system integrates microarray clustering data with similar expression patterns, and TFBS data in each cluster. FCAnalyzer is designed to perform two independent clustering procedures. The first process clusters gene expression profiles using the K-means clustering method, and the second process clusters predicted TFBSs in the upstream region of previously clustered genes using the hierarchical biclustering method for simultaneous grouping of genes and samples. This system offers retrieved information for predicted TFBSs in each cluster using $Match^{TM}$ in the TRANSFAC database. We used gene ontology term analysis for functional annotation of genes in the same cluster. We also provide the user with a combinatorial TFBS analysis of TFBS pairs. The enrichment of TFBS analysis and GO term analysis is statistically by the calculation of P values based on Fisher’s exact test, hypergeometric distribution and Bonferroni correction. FCAnalyzer is a web-based, user-friendly functional clustering analysis system that facilitates the transcriptional regulatory analysis of co-expressed genes. This system presents the analyses of clustered genes, significant TFBSs, significantly enriched TFBS combinations, their target genes and TFBS-TF pairs.

• Korean Journal of Food Science and Technology
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• v.35 no.6
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• pp.1204-1208
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• 2003

The purpose of this study was to compare the hematopoietic effects of Angelica gigas, A. sinensis, and A. acutiloba extract (1 g/kg B.W.) on cyclophosphamide-induced (30 mg/kg B.W.) anemic rats. Cyclophosphamide injection group (AG, AS, AA) showed a decrease in weight gain in comparison with the normal group. Compared to the cyclophosphamide-treated control group, oral administration of Angelica gigas extract for 14 days in the normal group significantly prevented body weight loss. The iron level of the A. gigas-administered group was significantly higher than the control groups. The serum vitamin $B_{12}$ level of A. gigas-, A. sinensis-, and A. acutiloba-administered groups was significantly higher than in the control. We suggest that administration of A. gigas, A. sinensis, and A. acutiloba prevents cyclophosphamide-induced anemia by improving hematological value and iron status.

• Journal of Nutrition and Health
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• v.41 no.2
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• pp.119-126
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• 2008

This study was conducted to investigate the effect of soy protein hydrolyzate on lipid metabolism and antioxidant activity in the rat. Thirty-eight male rats of Sprague-Dawley strain were divided into five groups: casein, isolated soy protein (ISP), seoritae protein hydrolyzate (SH), soluble soy protein hydrolyzate (SS), and insoluble soy protein hydrolyzate (IS). The control diet (casein group) contained 20% casein protein and experimental diet contained 10% casein and 10% isolated soy-protein or soy-protein hydrolyzate. Fecal lipid content was increased and lipid apparent absorption rate was decreased significantly by the ISP group at the first week of experimental period. Blood triglyceride, total cholesterol, LDL-cholesterol and atherogenic index (AI) were decreased by soy protein hydrolyzate groups than casein group. Liver total lipid, triglyceride and cholesterol were not different among groups, but showed decreasing tendencies in soyprotein hydrolyzate groups. The lipid lowering effect was prominent in the IS group among soy protein hydrolyzate groups. Total antioxidant activity showed increasing tendency in the seoritae hydrolyzate group. Liver superoxide dismutase (SOD), glutathione peroxidase (GPx) and catalase activities also showed higher tendencies in the seoritae hydrolyzate group than other groups. In conclusion, insoluble soyprotein hydrolyzate was more effective in lowering body lipids and seoritae hydrolyzate had higher antioxidant capacity among soy protein hydrolyzates.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.135-150
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• 2018

The biological resources research data around the world are not only very critical themselves but should be shared and utilized. Up to now, the biological resources have been compiled and managed individually depending on the purpose and characteristics of the study without any clear standard. So, in this study, the data reference model would be suggested which is applicable in the phase ranging from the start of the construction of the information system and which can be commonly used. For this purpose, the data model of the related information system would be expanded based on the domestic and foreign standards and data control policy so that the data reference model which can be commonly applicable to individual information system would be developed and its application procedure would be suggested. In addition, for the purpose of proving the excellence of the suggested data reference model, the quality level would be verified by applying the Korgstie's data model evaluation model and its level of data sharing with the domestic and foreign standards would be compared. The test results of this model showed that this model is better than the conventional data model in classifying the data into 4 levels of resources, target, activities and performances and that it has higher quality and sharing level of data in the data reference model which defines the derivation and relation of entity.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.19-29
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• 2011

Due to the development of web technologies and the increasing use of smart devices such as smart phone, in recent various web services are widely used in many application fields. In this environment, the topic of supporting personalized and intelligent web services have been actively researched, and an analysis technique on a web-click stream generated from web usage logs is one of the essential techniques related to the topic. In this paper, for efficient analyzing a web-click stream of sequences, a sequential pattern mining technique is proposed, which satisfies the basic requirements for data stream processing and finds a refined mining result. For this purpose, a concept of interesting sequential patterns with a time-interval constraint is defined, which uses not on1y the order of items in a sequential pattern but also their generation times. In addition, A mining method to find the interesting sequential patterns efficiently over a data stream such as a web-click stream is proposed. The proposed method can be effectively used to various computing application fields such as E-commerce, bio-informatics, and USN environments, which generate data as a form of data streams.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.59-69
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• 2010

The research on protein for the diseases analysis and the new medicines development is one of the most important themes in biotechnology. Since the analysis on diseases and protein needs to handle a large scale of data, we don't use the way to approach it by the experiments anymore. In recent, we have accelerated the research on diseases and protein analysis by sharing and connecting the various experimental data by combining the biotechnology with the IT technology. However, many biotechnology researchers have difficulty in handling the protein analysis tools based on the IT knowledge. In order to solve such problems, data analysis tools through the cooperation between IT researchers and biologists have been developed. However, the existing data analysis tools still have the problems that it is very hard for biologists to extend their functions and to use them. In this paper, we design and implement an effective analysis system for diseases and protein based on components that alleviates the problems of the existing data analysis systems.