• Journal of Sasang Constitutional Medicine
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• v.35 no.4
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• pp.10-22
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• 2023

Objectives The aim of this study is to explore the mechanism of action and target diseases of Sasang constitutional prescriptions using a multiscale interactome approach. Methods The compound and target information of Sasang constitutional prescriptions were retrieved from various databases such as the TM-MC, STITCH, and TTD. Key targets for Sasang constitutional prescriptions were identified by selecting the top 100 targets based on the number of simple paths within the constructed network. Diffusion profiles for Sasang constitutional prescriptions and diseases were calculated based on a biased random walk algorithm. Potential diseases and key mechanisms of Sasang constitutional prescriptions were identified by analyzing diffusion profiles. Results We identified 144 Sasang constitutional prescriptions and their targets, finding 80 herbs with effective biological targets. A cluster analysis based on selecting up to 100 key targets for each prescription revealed a more cohesive grouping of prescriptions according to Sasang constitution. We then predicted potential diseases for 62 Sasang constitutional prescriptions using diffusion profiles calculated on a multiscale interactome. Finally, our analysis of diffusion profiles revealed key targets and biological functions of prescriptions in obesity and diabetes. Conclusions This study demonstrates the effectiveness of a multiscale interactome approach in elucidating the complex mechanisms and potential therapeutic applications of prescriptions in Sasang constitutional medicine.

• Korean Journal of Organic Agriculture
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• v.27 no.3
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• pp.247-269
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• 2019

Although food related lifestyle has been widely discussed over the last ten years, the majority of research on food related lifestyle has been only conducted in terms of a variable-centered approach. But, recently there is a growing body of research on food related lifestyle profiles over the last three years from the view of a person-centered approach. This study conducted both a cluster analysis and a latent profile analysis (LPA) to identify the patterns of potential food related lifestyle customer profiles based on the five components on the sample of customer, who bought organic products (n=509). The results of each statistical analysis showed both quantitatively and qualitatively different types of food related lifestyle customer profiles even though there were similar types of profiles identified in common between these two analyses. These various profiles were then compared with customer's level of buying behaviors (e.g., buying attitude and buying intentions). Results showed that food related lifestyle profiles with respect to the high level of interesting in dietary life in terms of health and safety are associated with the higher level of buying behaviors. Based on the results, implications for food related lifestyle literature, practices and future research are discussed.

• BMB Reports
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• v.54 no.12
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• pp.601-607
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• 2021

Odorant receptors (ORs) account for about 60% of all human G protein-coupled receptors (GPCRs). OR expression outside of the nose has functions distinct from odor perception, and may contribute to the pathogenesis of disorders including brain diseases and cancers. Glioma is the most common adult malignant brain tumor and requires novel therapeutic strategies to improve clinical outcomes. Here, we outlined the expression of brain ORs and investigated OR expression levels in glioma. Although most ORs were not ubiquitously expressed in gliomas, a subset of ORs displayed glioma subtype-specific expression. Moreover, through systematic survival analysis on OR genes, OR51E1 (mouse Olfr558) was identified as a potential biomarker of unfavorable overall survival, and OR2C1 (mouse Olfr15) was identified as a potential biomarker of favorable overall survival in isocitrate dehydrogenase (IDH) wild-type glioma. In addition to transcriptomic analysis, mutational profiles revealed that somatic mutations in OR genes were detected in > 60% of glioma samples. OR5D18 (mouse Olfr1155) was the most frequently mutated OR gene, and OR5AR1 (mouse Olfr1019) showed IDH wild-type-specific mutation. Based on this systematic analysis and review of the genomic and transcriptomic profiles of ORs in glioma, we suggest that ORs are potential biomarkers and therapeutic targets for glioma.

• Advances in materials Research
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• v.13 no.4
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• pp.285-297
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• 2024

The theory of nonlinear elastic wave propagation is important in multiple scientific and engineering fields. In this study, we present a comprehensive examination of nonlinear elastic wave profiles through a contemporary approach of successive approximation. This research is related to nonlinear elastic wave models along different types of nonlinearities. Murnaghan potential is used due to the assumption of the hyper-elastic materials. We explore the complication of the governing equations and go through the behaviors of nonlinear waves in one dimension. The comparative aspect of our study is a distinctive feature, as we evaluate and contrast the results obtained using successive approximation along different nonlinearities. Additionally, we present graphical representations of our findings, enhancing the visual comprehension of the wave profiles and their evolution. This study contributes to the nonlinear elastic wave analysis and comparison.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2002.05a
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• pp.86-89
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• 2002

Due to extremely large reduction of area or extrusion ratio in ordinary production of extruded profiles, anisotropy is naturally induced by large severe deformation during the extrusion process. Therefore, the anisotropic properties play a great role in the post processing of extruded profiles, such as in bending. Moreover, undesirable deformation will be involved when the deformation-induced anisotropy is ignored. In order to observe the deformation-induced anisotropy of the thin-walled product, the proposed algorithm is applied to some chosen industrial extrusion processes. In the resent work, the method for prediction of deformation-induced anisotropy employing the Barlats six-component yield potential to the rigid-plastic finite element method is proposed. The proposed algorithm is verified with the comparison to the crystallographic texture analysis, and then applied to the C-section exclusion process using a square die. The predicted anisotropy is then compared with the experimental and computational observations for validating the proposed algorithm.

• Transactions of Materials Processing
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• v.11 no.8
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• pp.724-730
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• 2002

Due to extremely large reduction of area or extrusion ratio in ordinary production of extruded profiles, anisotropy is naturally induced by large severe deformation during the extrusion process. Therefore, the anisotropic properties play a great role in the post processing of extruded profiles, such as in bending. Moreover, undesirable deformation will be involved when the deformation-induced anisotropy is ignored. In order to observe the deformation-induced anisotropy of the thin-walled product, the proposed algorithm is applied to some chosen industrial extrusion processes. In the present work, the method for prediction of deformation-induced anisotropy employing the Barlats six-component yield potential to the rigid-plastic finite element method is proposed. The proposed algorithm is verified with the comparison to the crystallographic texture analysis, and then applied to the C-section extrusion process using a square die. The predicted anisotropy is then compared with the experimental and computational observations for validating the proposed algorithm.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2007.11a
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• pp.19-27
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• 2007

An important potential of metabolomics-based approach is the possibility to develop fingerprints of diseases or cellular responses to classes of compounds with known common biological effect. Such fingerprints have the potential to allow classification of disease states or compounds, to provide mechanistic information on cellular perturbations and pathways and to identify biomarkers specific for disease severity and drug efficacy. Metabolic profiles of biological fluids contain a vast array of endogenous metabolites. Changes in those profiles resulting from perturbations of the system can be observed using analytical techniques, such as NMR and MS. $^1H$ NMR was used to generate a molecular fingerprint of serum or urinary sample, and then pattern recognition technique was applied to identity molecular signatures associated with the specific diseases or drug efficiency. Several metabolites that differentiate disease samples from the control were thoroughly characterized by NMR spectroscopy. We investigated the metabolic changes in human normal and clinical samples using $^1H$ NMR. Spectral data were applied to targeted profiling and spectral binning method, and then multivariate statistical data analysis (MVDA) was used to examine in detail the modulation of small molecule candidate biomarkers. We show that targeted profiling produces robust models, generates accurate metabolite concentration data, and provides data that can be used to help understand metabolic differences between healthy and disease population. Such metabolic signatures could provide diagnostic markers for a disease state or biomarkers for drug response phenotypes.

• Journal of Microbiology and Biotechnology
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• v.12 no.1
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• pp.77-83
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• 2002

A bacterial consortium capable of utilizing a variety of polycyclic aromatic hydrocarbons has been isolated from a former manufactured gas plant site. The consortium consisted of four members including Arthrobacter sp., Burkholderia sp., Ochrobacterium sp., and Alcaligenes sp., which were identified and characterized by the patterns of fatty acid methyl esters (FAME analysis) and carbon source utilization (BIOLOG system). With the individual members, the biodegradation characteristics of aromatic hydrocarbons depending on different growth substrates were determined. FAME analyses demonstrated that microbial fatty acid profiles changed to significant extents in response to different carbon sources, and hence, such shift profiles may be informative to characterize the biodegradation potential of a bacterium or microbial community.

• Computers and Concrete
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• v.26 no.5
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• pp.429-438
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• 2020

To shorten the construction times of nuclear facility structures, three high-strength concrete mixtures were developed with specific consideration given to their curing temperatures, their economic efficiency, and the practicality of their quality control. This study was conducted to examine the temperature rise profiles of these three concrete mixtures and the potential for early-age thermal cracking in the primary containment vessel of a nuclear reactor with a wall thickness of 1200 mm. The one-layer placement height of the concrete for the primary containment vessel was increased from the conventional 3 m to 3.5 m. A nonlinear finite element analysis (FEA) was conducted using the thermal properties of concrete determined from the isothermal hydration and adiabatic hydration tests, and tuned through comparisons made with temperature rise profiles obtained for 1200-mm-thick mock-up wall specimens cured at temperatures of 5, 20, and 35℃. The hydration heat performance of the three concrete mixtures and their potential to produce thermal cracking in nuclear facilities indicate that the mixtures have considerable potential for practical application to the primary containment vessel of a nuclear reactor at various curing temperatures, fulfilling the minimum requirements of the ACI 301 and minimizing the likelihood of the occurrence of thermal cracks.

• Journal of the Semiconductor & Display Technology
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• v.2 no.4
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• pp.9-12
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• 2003

This paper describes a newly developed simulation environment for analysis and design of a plasma processing chamber based on first principles including complicated physical and chemical interactions of plasma, fluid dynamics of neutrals, and transport phenomena of particles. Capabilities of our simulator, named VIP-SEPCAD (Virtual Integrated Prototyping Simulation Environment for Plasma Chamber Analysis and Design), are demonstrated through a two dimensional simulation of an oxygen plasma chamber. VIP-SEPCAD can provide plasma properties such as spatiotemporal profiles of plasma density and potential, electron temperature, ion flux and energy, etc. By coupling neutral and particle transport models with a three moment plasma model, VIP-SEPCAD can also predict spatiotemporal profiles of chemically reactive species and particles exist in plasma.