• Research in Community and Public Health Nursing
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• v.30 no.3
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• pp.271-280
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• 2019

Purpose: This study evaluates the efficacy of a Self-Care Reinforcement Program (SCRP) based on the Selection Optimization Compensation (SOC) model, in socially vulnerable elderly women with metabolic syndrome. Methods: This study adopts a pretest-posttest nonequivalent control group design. The participants were 64 socially vulnerable elderly Korean women with metabolic syndrome (experimental group: 31, control group: 33). Participants' body composition analysis, nutrient intake, risk factors of metabolic syndrome, depressive symptoms, and social network were measured. Data were analyzed with an independent t-test; statistical significance levels were set at p<.05. The SCRP, including metabolic syndrome education, nutritional education, exercise, and social network, was performed three times a week for 8 weeks. Results: There were statistically significant differences between the experimental and control groups in terms of systolic blood pressure, diastolic pressure, fasting blood sugar, triglycerides, sodium intake, depressive symptoms, and social networks. Conclusion: The SCRP is effective and can be recommended as a community health nursing intervention for socially vulnerable elderly women with metabolic syndrome.

• Journal of Microbiology and Biotechnology
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• v.16 no.6
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• pp.832-848
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• 2006

Systems biology has recently become an important research paradigm that is anticipated to decipher the metabolic, regulatory, and signaling networks of complex living organisms on the whole organism level. Thus, various research outputs are being generated, along with the development of many tools and resources for systems biology research. Accordingly, this review provides a comprehensive summary of the current resources and tools for systems biology research that will hopefully be helpful to researchers involved in this field. The resources are categorized into the following five groups: genome information and analysis, transcriptome and proteome databases, metabolic profiling and metabolic control analysis, metabolic and regulatory information, and software for computational systems biology. A summary table and some future perspectives are also provided.

• Genomics & Informatics
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• v.9 no.4
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• pp.143-151
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• 2011

In this study, we propose a novel, intuitive method of constructing an expression quantitative trait (eQT) network that is related to the metabolic syndrome using LOD scores and peak loci for selected eQTs, based on the concept of gene-gene interactions. We selected 49 eQTs that were related to insulin resistance. A variance component linkage analysis was performed to explore the expression loci of each of the eQTs. The linkage peak loci were investigated, and the "support zone" was defined within boundaries of an LOD score of 0.5 from the peak. If one gene was located within the "support zone" of the peak loci for the eQT of another gene, the relationship was considered as a potential "directed causal pathway" from the former to the latter gene. SNP markers under the linkage peaks or within the support zone were searched for in the database to identify the genes at the loci. Two groups of gene networks were formed separately around the genes IRS2 and UGCGL2. The findings indicated evidence of networks between genes that were related to the metabolic syndrome. The use of linkage analysis enabled the construction of directed causal networks. This methodology showed that characterizing and locating eQTs can provide an effective means of constructing a genetic network.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.462-469
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• 2005

A top-down approach is known to be a useful and effective technique for the design and analysis of metabolic systems. In this Study, we have constructed a grouped metabolic network for Lactococcus lactis under aerobic conditions using grouped enzyme kinetics. To test the usefulness of grouping work, a non-grouped system and grouped systems were compared quantitatively with each other. Here, grouped Systems were designed as two groups according to the extent of grouping. The overall simulated flux values in grouped and non-grouped models had pretty similar distribution trends, but the details on flux ratio at the pyruvate branch point showed a little difference. This result indicates that our grouping technique can be used as a good model for complicated metabolic networks, however, for detailed analysis of metabolic network, a more robust mechanism Should be considered. In addition to the data for the pyruvate branch point analysis, Some major flux control coefficients were obtained in this research.

• 한국생물공학회:학술대회논문집
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• 2005.04a
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• pp.12-12
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• 2005

• Biomaterials and Biomechanics in Bioengineering
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• v.2 no.3
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• pp.143-157
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• 2015

Successful integration of cementless femoral stems using porous surfaces relies on effective periimplant bone healing to secure the bone-implant interface. The initial stages of the healing process involve protein adsorption, fibrin clot formation and cell osteoconduction onto the implant surface. Modelling this process in vitro, the current work considered the effect of fibrin deposition on the responses of human mesenchymal stromal cells cultured on ferritic fibre networks intended for magneto-mechanical actuation of in-growing bone tissue. The underlying hypothesis for the study was that fibrin deposition would support early stromal cell attachment and physiological functions within the optimal regions for strain transmission to the cells in the fibre networks. Highly porous fibre networks composed of 444 ferritic stainless steel were selected due to their ability to support human osteoblasts and mesenchymal stromal cells without inducing untoward inflammatory responses in vitro. Cell attachment, proliferation, metabolic activity, differentiation and penetration into the ferritic fibre networks were examined for one week. For all fibrin-containing samples, cells were observed on and between the metal fibres, supported by the deposited fibrin, while cells on fibrin-free fibre networks (control surface) attached only onto fibre surfaces and junctions. Initial cell attachment, measured by analysis of deoxyribonucleic acid, increased significantly with increasing fibrinogen concentration within the physiological range. Despite higher cell numbers on fibrin-containing samples, similar metabolic activities to control surfaces were observed, which significantly increased for all samples over the duration of the study. It is concluded that fibrin deposition can support the early attachment of viable mesenchymal stromal cells within the inter-fibre spaces of fibre networks intended for magneto-mechanical strain transduction to in-growing cells.

• Journal of Microbiology and Biotechnology
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• v.15 no.1
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• pp.161-174
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• 2005

Abstract Glycolysis has a main function to provide ATP and precursor metabolites for biomass production. Although glycolysis is one of the most important pathways in cellular metabolism, the details of its regulation mechanism and regulating chemicals are not well known yet. The regulation of the glycolytic pathway is very robust to allow for large fluxes at almost constant metabolite levels in spite of changing environmental conditions and many reaction effectors like inhibitors, activating compounds, cofactors, and related metal ions. These changing environmental conditions and metabolic reaction effectors were focused on to understand their roles in the metabolic networks. In this study, we have investigated for construction of the regulatory map of the glycolytic metabolic network and tried to collect all the effectors as much as possible which might affect the glycolysis metabolic pathway. Using the results of this study, it is expected that a complex metabolic situation can be more precisely analyzed and simulated by using available programs and appropriate kinetic data.

• KSBB Journal
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• v.24 no.3
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• pp.287-290
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• 2009

Metabolic network is composed of more than thousands of metabolic reactions. Therefore, understanding of metabolic behavior of microorganisms is required to engineer metabolism of microorganisms. In this paper, we employed ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks) to quantify relationships among metabolic subpathways. The results showed that ARACNE analysis can give new insight into the study of bacterial metabolism.

• Journal of Microbiology and Biotechnology
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• v.17 no.3
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• pp.496-510
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• 2007

This paper describes the use of a discrete mathematical model to represent the basic mechanisms of regulation of the bacteria E. coli in batch fermentation. The specific phenomena studied were the changes in metabolism and genetic regulation when the bacteria use three different carbon substrates (glucose, glycerol, and acetate). The model correctly predicts the behavior of E. coli vis-a-vis substrate mixtures. In a mixture of glucose, glycerol, and acetate, it prefers glucose, then glycerol, and finally acetate. The model included 67 nodes; 28 were genes, 20 enzymes, and 19 regulators/biochemical compounds. The model represents both the genetic regulation and metabolic networks in an integrated form, which is how they function biologically. This is one of the first attempts to include both of these networks in one model. Previously, discrete mathematical models were used only to describe genetic regulation networks. The study of the network dynamics generated 8 $(2^3)$ fixed points, one for each nutrient configuration (substrate mixture) in the medium. The fixed points of the discrete model reflect the phenotypes described. Gene expression and the patterns of the metabolic fluxes generated are described accurately. The activation of the gene regulation network depends basically on the presence of glucose and glycerol. The model predicts the behavior when mixed carbon sources are utilized as well as when there is no carbon source present. Fictitious jokers (Joker1, Joker2, and Repressor SdhC) had to be created to control 12 genes whose regulation mechanism is unknown, since glycerol and glucose do not act directly on the genes. The approach presented in this paper is particularly useful to investigate potential unknown gene regulation mechanisms; such a novel approach can also be used to describe other gene regulation situations such as the comparison between non-recombinant and recombinant yeast strain, producing recombinant proteins, presently under investigation in our group.

• Korean Chemical Engineering Research
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• v.45 no.6
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• pp.529-535
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• 2007

Recently, an attempt to analyze and modify metabolic networks of living organisms in global level emerged with the benefit of development of high-throughput techniques, and it is generally called systems biology. Various systems biology studies have been carried out for the development of enhanced metabolite production systems. By modification of metabolic characteristics of microorganisms, metabolite productivities and yields obtained with metabolically engineered bacteria increased significantly compare with that obtained with wild type bacteria.