• Journal of Life Science
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• v.31 no.8
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• pp.736-744
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• 2021

Artemisia princeps Pampanini is an herbal medicine widely used to immune function-related diseases, such as anti-oxidative, anti-inflammatory, and antibacterial agents. In this study, we investigated the anti-inflammatory effects of AP extract and underlying mechanisms were evaluated in RAW 264.7 cells. The effects of AP extract were also studied in a complete Freund's adjuvant (CFA)-induced arthritis and lipopolysaccharide (LPS)-induced inflammation mouse model. In RAW 264.7 cells, AP extracts significantly inhibited the LPS-induced nitric oxide (NO) production and inducible NO synthase and cyclooxygenase-2 protein expression. The LPS-induced phosphorylation of mitogen-activated protein kinases and nuclear factor-κB was also significantly blocked by AP extract in RAW 264.7 cells. Oral administration of AP extract suppressed the increase in mouse paw edema and spleen index compared to CFA-treated mice group. Histologically, the infiltration of inflammatory cells was increased in cartilage and synovium in the CFA-treated mouse group, whereas it was suppressed in the AP extract-administered group. Furthermore, AP extract treatment significantly reduced the inflammatory cytokine, tumor necrosis factor-α, levels in CFA and LPS-treated mouse. In conclusion, the anti-inflammatory and anti-arthritis effect of AP extract was confirmed in both in vitro and in vivo models, suggesting that Artemisia princeps Pampanini may be a candidate material for arthritis treatment.

• Economic and Environmental Geology
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• v.53 no.6
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• pp.781-792
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• 2020

Mine tailings, which are inevitably formed by the development of manganese nodules, manganese crusts, and hydrothermal seafloor deposits, have attracted attention because of their quantity and potential toxicity. However, there is a lack of data on the quantity of mine tailings being generated, their physicochemical properties, and their effects as environmental hazards and on marine ecosystems in general. The importance of treating mine tailings in an environmentally friendly manner has been recognized recently and related reduction/treatment methods are being considered. In the case of deep-sea mineral resource development, if mine tailings cannot be treated aboard a ship, the issue becomes one of the cost of transporting them to land and solving the problem of environmental pollution there. Therefore, the Korea Institute of Ocean Science and Technology conducted research on the harmfulness of mine tailings, their effect on marine ecosystem, the diffusion model of contaminated particles, and candidate purification treatment technologies based on five representative controlling factors: 1) effects of pollution /on the environment, 2) effects of environmental/ biological hazards, 3) diffusion of particles, 4) mineral dressings, and 5) reducing/processing mine tailings. The results of this study can provide a basis for minimizing environmental problems by providing scientific evidences of the environmental effects of mine tailings. In addition, it is also expected that these results could be applied to the treatment of pollutants of different origins and at land-based mining waste sites.

• Journal of Gastric Cancer
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• v.21 no.2
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• pp.191-202
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• 2021

Purpose: A near-infrared (NIR) fluorescence imaging is a promising tool for cancer-specific image guided surgery. Human epidermal receptor 2 (HER2) is one of the candidate markers for gastric cancer. In this study, we aimed to synthesize HER2-specific NIR fluorescence probes and evaluate their applicability in cancer-specific image-guided surgeries using an animal model. Materials and Methods: An NIR dye emitting light at 800 nm (IRDye800CW; Li-COR) was conjugated to trastuzumab and an HER2-specific affibody using a click mechanism. HER2 affinity was assessed using surface plasmon resonance. Gastric cancer cell lines (NCI-N87 and SNU-601) were subcutaneously implanted into female BALB/c nu (6-8 weeks old) mice. After intravenous injection of the probes, biodistribution and fluorescence signal intensity were measured using Lumina II (Perkin Elmer) and a laparoscopic NIR camera (InTheSmart). Results: Trastuzumab-IRDye800CW exhibited high affinity for HER2 (K_D=2.093(3) pM). Fluorescence signals in the liver and spleen were the highest at 24 hours post injection, while the signal in HER2-positive tumor cells increased until 72 hours, as assessed using the Lumina II system. The signal corresponding to the tumor was visually identified and clearly differentiated from the liver after 72 hours using a laparoscopic NIR camera. Affibody-IRDye800CW also exhibited high affinity for HER2 (K_D=4.71 nM); however, the signal was not identified in the tumor, probably owing to rapid renal clearance. Conclusions: Trastuzumab-IRDye800CW may be used as a potential NIR probe that can be injected 2-3 days before surgery to obtain high HER2-specific signal and contrast. Affibody-based NIR probes may require modifications to enhance mobilization to the tumor site.

• Korean Journal of Metals and Materials
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• v.49 no.8
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• pp.628-634
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• 2011

SA508 Gr.4N Ni-Cr-Mo low alloy steel, in which Ni and Cr contents are higher than in commercial SA508 Gr.3 Mn-Mo-Ni low alloy steels, may be a candidate reactor pressure vessel (RPV) material with higher strength and toughness from its tempered martensitic microstructure. The inner surface of the RPV is weld-cladded with stainless steels to prevent corrosion. The goal of this study is to evaluate the microstructural properties of the clad interface between Ni-Cr-Mo low alloy steel and stainless weldment, and the effects of post weld heat treatment (PWHT) on the properties. The properties of the clad interface were compared with those of commercial Mn-Mo-Ni low alloy steel. Multi-layer welding of model alloys with ER308L and ER309L stainless steel by the SAW method was performed, and then PWHT was conducted at $610^{\circ}C$ for 30 h. The microstructural changes of the clad interface were analyzed using OM, SEM and TEM, and micro-Vickers hardness tests were performed. Before PWHT, the heat affected zone (HAZ) showed higher hardness than base and weld metals due to formation of martensite after welding in both steels. In addition, the hardness of the HAZ in Ni-Cr-Mo low alloy steel was higher than that in Mn-Mo-Ni low alloy steel due to a comparatively high martensite fraction. The hardness of the HAZ decreased after PWHT in both steels, but the dark region was formed near the fusion line in which the hardness was locally high. In the case of Mn-Mo-Ni low alloy steel, formation of fine Cr-carbides in the weld region near the fusion line by diffusion of C from the base metal resulted in locally high hardness in the dark region. However, the precipitates of the region in the Ni-Cr-Mo low alloy steel were similar to that in the base metal, and the hardness in the region was not greatly different from that in the base metal.

• Journal of Food Hygiene and Safety
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• v.36 no.1
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• pp.77-85
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• 2021

Glucosylceramides (GluCer) are known to play an important role in both water retention and epidermal permeability barrier function in the mammalian stratum corneum. In this study, we investigated the effects of pineapple fruit extract containing glucosylceramides (PFEG) on the maintenance and recovery of skin barrier function using atopic dermatitis-induced animal models. Five-week-old male Hos:HR-1 mice were divided into four groups fed on standard diet, unsaturated fatty acids-deficient (HR-AD) diet, and HR-AD diet supplemented with 0.01% or 0.1% pineapple-GluCer. Skin barrier function was evaluated by transepidermal water loss (TEWL), dermal moisture content, moisture content of the stratum corneum and wrinkle formation. The control group (HR-AD administration group) showed increased transepidermal water loss (TEWL), while the epidermal moisture content and the moisture content of the stratum corneum slowly decreased. However, in the PFEG groups (with 0.1% or 0.01% glucosylceramide), the TEWL levels were significantly reduced at 2 weeks. The PFEG also helped maintain skin moisturizing function by significantly suppressing the decrease of the epidermal moisture content and the moisture content of the stratum corneum. These results show that the PFEG is effective for maintaining and improving the function of the skin barrier. Therefore, this study suggests that PFEG is a potential candidate material for skin functional foods.

• Journal of Physiology & Pathology in Korean Medicine
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• v.35 no.3
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• pp.97-103
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• 2021

Perilla frutescens (P. frutescens) is an important herb used for many purposes such as medicinal, aromatic, and functional food in Asian countries and has beneficial effects such as antioxidant activity, anti-inflammation activity, anti-depression activity, and anxiolytic activity. However, there have been no studies on the protective effect of P. frutescens extract (PFE) on amnesia in vivo. The present study aimed to investigate whether PFE protects memory deficit using a scopolamine-induced mice model and elucidate the underlying mechanisms involved. The protective effect of PFE against scopolamine-induced memory deficits was investigated using Y-maze, passive avoidance, and Morris water maze tests. Furthermore, the potential mechanisms of PFE in improving memory capabilities related to the cholinergic system and antioxidant activity were examined. PFE significantly increased spontaneous alternation in the Y-maze test, step-through latency in the passive avoidance test, and swimming time in the target quadrant in the probe test when compared to the scopolamine-treated group. Likewise, PFE significantly decreased escapes latency in the Morris water maze test. PFE could not regulate cholinergic function in acetylcholine level and acetylcholine esterase activity. However, PFE increased DPPH radical scavenging activity dose-dependently and total polyphenol content was 127.7±1.2 ㎍ GAE/mg. The results showed that the PFE could be a preventive and/or therapeutic candidate for memory and cognitive dysfunction in Alzheimer's disease.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.83-106
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• 2021

Interests in clean fuels have been soaring because of environmental problems such as air pollution and global warming. Unlike fossil fuels, hydrogen obtains public attention as a eco-friendly energy source because it releases only water when burned. Various policy efforts have been made to establish a hydrogen based transportation network. The station that supplies hydrogen to hydrogen-powered trucks is essential for building the hydrogen based logistics system. Thus, determining the optimal location of refueling stations is an important topic in the network. Although previous studies have mostly applied optimization based methodologies, this paper adopts machine learning to review spatial attributes of candidate locations in selecting the optimal position of the refueling stations. Machine learning shows outstanding performance in various fields. However, it has not yet applied to an optimal location selection problem of hydrogen refueling stations. Therefore, several machine learning models are applied and compared in performance by setting variables relevant to the location of highway rest areas and random points on a highway. The results show that Random Forest model is superior in terms of F1-score. We believe that this work can be a starting point to utilize machine learning based methods as the preliminary review for the optimal sites of the stations before the optimization applies.

• Wind and Structures
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• v.34 no.1
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• pp.127-136
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• 2022

In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the high-fidelity model.

• Biomolecules & Therapeutics
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• v.31 no.3
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• pp.350-358
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• 2023

Hand-foot-and-mouth disease (HFMD) is a viral infectious disease that occurs in children under 5 years of age. Its main causes are coxsackievirus (CV) and enterovirus (EV). Since there are no efficient therapeutics for HFMD, vaccines are effective in preventing the disease. To develop broad coverage against CV and EV, the development of a bivalent vaccine form is needed. The Mongolian gerbil is an efficient and suitable animal model of EV71 C4a and CVA16 infection used to investigate vaccine efficacy following direct immunization. In this study, Mongolian gerbils were immunized with a bivalent inactivated EV71 C4a and inactivated CVA16 vaccine to test their effectiveness against viral infection. Bivalent vaccine immunization resulted in increased Ag-specific IgG antibody production; specifically, EV71 C4a-specific IgG was increased with medium and high doses and CVA16-specific IgG was increased with all doses of immunization. When gene expression of T cell-biased cytokines was analysed, Th1, Th2, and Th17 responses were found to be highly activated in the high-dose immunization group. Moreover, bivalent vaccine immunization mitigated paralytic signs and increased the survival rate following lethal viral challenges. When the viral RNA content was determined from various organs, all three doses of bivalent vaccine immunization were found to significantly decrease viral amplification. Upon histologic examination, EV71 C4a and CVA16 induced tissue damage to the heart and muscle. However, bivalent vaccine immunization alleviated this in a dose-dependent manner. These results suggest that the bivalent inactivated EV71 C4a/CVA16 vaccine could be a safe and effective candidate HFMD vaccine.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.