• Proceedings of the PSK Conference
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• 2002.10a
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• pp.267.3-268
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• 2002

Aggregation of the high affinity 1gE receptor on mast cells results in many biochemical. events leading to the release of histamine. serotonin. prostaglandins arachidonic acid metabolites, and cytokines. Previously we have shown that M2 pyruvate kinase interacts with the gamma chain of 1gE receptor on the ITAM (immunoreceptor tyrosine-based activation motif) region. (omitted)

• Kosin Medical Journal
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• v.33 no.2
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• pp.135-140
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• 2018

Endometriosis is an estrogen-dependent chronic inflammatory condition that affects women in their reproductive period and is associated with pelvic pain and infertility. Oxidative stress (OS) occurs when reactive oxygen stress (ROS) and anti-oxidants are in imbalance. OS is a potential factor involved in the pathophysiology of endometriosis. Iron-induced ROS may trigger a chain of events resulting in the development and progression of endometriosis. Endogenous ROS are correlated with increased cellular proliferation and ERK1/2 activation in human endometriotic cells. An oxidative environment leads to stimulation of the ERK and PI3K/AKT/mTOR signaling pathways that facilitate endometriotic lesion progression through adhesion, angiogenesis, and proliferation. OS is also known to be involved in epigenetic mechanisms in endometriosis. We summarize the recent knowledge in our understanding of the role of oxidative stress in the pathogenesis of endometriosis.

• Journal of Life Science
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• v.10 no.5
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• pp.533-541
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• 2000

Compared to mammal including human, many bioreactive genes that regulate various biological events has not been cloned and characterized yet in fishes, especially shark, Scyliorhinus torazame. In orther to isolate genes that regulate physiological processes in cartilaginors fishes, we performed reverse transcription-polymerase chain reaction (RT-PCR) using the RNA of cartilage tissues of Scyliofhinus torazame. The cloned partial genes were 86%, 80%, 73%, 84%, 75%, 79% identical to $\alpha$- actin, 90-kDa heat-shock protein, methyle-neterahydrofolate dehydrogenase-methenyltertrahydrofolate cyclohudrolase-formyltetrahydrofolate synthetase, ubiquitin, glutamine synthetase and connective tissue growth factor genes of human, respectively. They also have similar nucleotide sequence homologues with those of another species. These partial bioreactive genes elucidated in this study may support to studies of phylogenetic analysis based on evolutionary relationships between shark and other species.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1441-1444
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• 2007

It is now widely acknowledged that climate variability modifies the frequency spectrum of hydrological extreme events. Traditional hydrological frequency analysis methodologies are not devised to account for nonstationarity that arises due to variation in exogenous factors of the causal structure. We use Hierarchical Bayesian Analysis to consider the exogenous factors that can influence on the frequency of extreme floods. The sea surface temperatures, predicted GCM precipitation, climate indices and snow pack are considered as potential predictors of flood risk. The parameters of the model are estimated using a Markov Chain Monte Carlo (MCMC) algorithm. The predictors are compared in terms of the resulting posterior distributions of the parameters associated with estimated flood frequency distributions.

• Wind and Structures
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• v.13 no.2
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• pp.207-220
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• 2010

The 'chain reaction' effect of the interaction between wind pressure and windborne debris is likely to be a major cause of damage to residential buildings during severe wind events. The current paper (Part II) concerns the quantification of such pressure-debris interaction in an advanced vulnerability model that integrates the debris risk model developed in Part I and a component-based wind-pressure damage model. This vulnerability model may be applied to predict the cumulative wind damage during the passage of particular hurricanes, to estimate annual hurricane losses, or to conduct system reliability analysis for residential developments, with the effect of windborne debris fully considered.

• BMB Reports
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• v.44 no.3
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• pp.182-186
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• 2011

Exogenous stimuli such as nerve growth factor (NGF) exert their effects on neurite outgrowth via Trk neurotrophin receptors. TrkA receptors are known to be ubiquitinated via proteasome inhibition in the presence of NGF. However, the effect of proteasome inhibition on neurite outgrowth has not been studied extensively. To clarify these issues, we investigated signaling events in PC12 cells treated with NGF and the proteasome inhibitor MG132. We found that MG132 facilitated NGF-induced neurite outgrowth and potentiated the phosphorylation of the extracellular signal-regulated kinase/mitogen-activated protein kinase (ERK/MAPK) and phosphatidylinositol-3-kinase (PI3K)/AKT pathways and TrkA receptors. MG132 stimulated internalization of surface TrkA receptor and stabilized intracellular TrkA receptor, and the $Ub^{K63}$ chain was found to be essential for stability. These results indicate that the ubiquitin-proteasome system potentiated neurite formation by regulating the stability of TrkA receptors.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.581-585
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• 2010

This study introduced a Bayesian based frequency analysis in which the statistical trend seasonal analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel and GEV extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both trend and seasonal analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. In addition, full annual cycle of the design rainfall through seasonal model could be applied to annual control such as dam operation, flood control, irrigation water management, and so on. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.357-367
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• 2021

In general, common cause failures (CCFs) have been modeled with the assumption that components within the same group are symmetric. This assumption reduces the number of parameters required for the CCF probability estimation and allows us to use a parametric model, such as the alpha factor model. Although there are various asymmetric conditions in nuclear power plants (NPPs) to be addressed, the traditional CCF models are limited to symmetric conditions. Therefore, this paper proposes the copulabased CCF model to deal with asymmetric as well as symmetric CCFs. Once a joint distribution between the components is constructed using copulas, the proposed model is able to provide the probability of common cause basic events (CCBEs) by formulating a system of equations without symmetry assumptions. In addition, Bayesian inferences for the parameters of the marginal and copula distributions are introduced and Markov Chain Monte Carlo (MCMC) algorithms are employed to sample from the posterior distribution. Three example cases using simulated data, including asymmetry conditions in total failure probabilities and/or dependencies, are illustrated. Consequently, the copula-based CCF model provides appropriate estimates of CCFs for asymmetric conditions. This paper also discusses the limitations and notes on the proposed method.

• Journal of Plant Biotechnology
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• v.42 no.3
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• pp.196-203
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• 2015

AbstractLiving modified organisms (LMO) are one of the most widespread products of modern biotechnology after DNA discovery. Due to the decline of grain self-sufficiency rate and the increase of reliance on LMO imports in Korea, a series of concerns with regard to safety of living modified(LM) crops has been raised. The aim of this study is to establish the detection methods for unintentional release or growing of LMO plants in environmental conditions. To detect LM crop events, general concepts of specific primer design and PCR conditions were provided by the Joint Research Centre (JRC). The certified reference materials of seven LM events (4 soybean, 2 cotton and 1 corn) were obtained from the Institute for Reference Materials and Measurements (IRMM) and the American Oil Chemists' Society (AOCS). Genomic DNA from seven LM events were purified and PCR amplifications were carried out by using individual event-specific primer sets. LM-specific PCR products of all seven events were efficiently amplified by our methods. The results indicate that the established detection method for LMOs is suitable as a scientific tool to monitor whether the crops found in natural environments are LMOs.

• Journal of Plant Biotechnology
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• v.47 no.4
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• pp.309-315
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• 2020

Advances in biotechnology have led to progress in crop genetic engineering to improve agricultural productivity. The use of genetically modified (GM) crops has increased, as have consumers' and regulators' concerns about the safety of GM crops to human health, and ecological biodiversity. As such, the identification of GM crops is a critical issue for developers and distributors, and their labeling is mandatory. Multiplex polymerase chain reaction (PCR) has been developed and its use validated for the detection and identification of GM crops in quarantine. Herein, we established a simultaneous detection method to identify four GM maize events. Event-specific primers were designed between the junction region of transgene and genome of four GM maize lines, namely 5307, DAS-40278-9, MON87460, and MON87427. To verify the efficiency and accuracy of the multiplex PCR we used specificity analysis, limit of detection evaluation, and mixed certified reference materials identification. The multiplex PCR method was applied to analyze 29 living, modified maize volunteers collected in South Korea in 2018 and 2019. We performed multiplex PCR analysis to identify events and confirmed the result by simplex PCR using each event-specific primer. As a result, rather than detecting each event individually, the simultaneous detection PCR method enabled the rapid analysis of 29 GM maize volunteers. Thus, the novel multiplex PCR method is applicable for living modified organism volunteer identification.