Publications by authors named "Eulsik Oh"

It is well known that the two chemical compounds endothelin-1 (ET-1) and isoproterenol (ISO) can individually induce cardiac hypertrophy through G protein-coupled receptors in cardiomyocytes. However, the cardiac hypertrophy signaling pathway activated by ET-1 and ISO is not well defined. Therefore, we investigated the protein expression profile and signaling transduction in HL-l cardiomyocyte cells treated with ET-1 and ISO.

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An analytical method of CE-MS and CE with an online preconcentration technique induced by a dynamic pH junction, addition of organic solvent and large volume injection was developed for sensitive determination of peptides in biological samples. Leucine enkephalin, methionine enkephalin, dynorphin A, β-endorphin and angiotensin II were used as model peptides. The optimal online preconcentration conditions were obtained at a sample matrix consisting of 100 mM borate buffer (pH 10.

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In a novel attempt to comprehend the complexity of life, systems biology has recently emerged as a state-of-the-art approach for biological research in contrast to the reductionist approaches that have been used in molecular cell biology since the 1950s. Because a massive amount of information is required in many systems biology studies of life processes, we have increasingly come to depend on techniques that provide high-throughput omics data. CE and CE coupled to MS have served as powerful analytical tools for providing qualitative and quantitative omics data.

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Computational modeling of signal transduction is currently attracting much attention as it can promote the understanding of complex signal transduction mechanisms. Although several mathematical models have been used to examine signaling pathways, little attention has been given to crosstalk mechanisms. In this study, an attempt was made to develop a computational model for the pathways involving growth-factor-mediated mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3'-kinase/protein kinase B (PI3K/Akt).

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This review provides an updated overview of recent developments and applications of CE based on previously published reports in the field of omic research. The increased number of published articles on omics shows that the field is growing and attracting the attention of many life science researchers. Due to developments in the omics sciences, many researchers have been studying systems biology, in which biological events in organisms are systematically interpreted through the combination of complex measurements from various methods resulting in high-throughput data.

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While the emergence of a power-law degree distribution in complex networks is intriguing, the degree exponent is not universal. Here we show that the between ness centrality displays a power-law distribution with an exponent eta, which is robust, and use it to classify the scale-free networks. We have observed two universality classes with eta approximately equal 2.

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