• Applied Microscopy
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• v.33 no.1
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• pp.1-16
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• 2003

As is well known that N-nitroso-N-methylurethane (NNNMU) causes acute lung injury (ALI) in experimental animals. And ALI caused by NNNMU is very similar to ARDS in human being in its pathology and progress. In its context, we investigated the pathogenetic mechanism of ARDS associated with oxidative stress by neutrophils in Sprague-Dawley rat model of NNNMU-induced ALI. NNNMU had increased lung weight/body weight ratio (L/B ratio), lung myeloperoxidase (MPO) activity, protein content and number of neutrophils in bronchoalveolar fluid (BALF) compared with those of control rat (p<0.001, respectively). In contrast, the amount of pulmonary surfactant in BALF was decreased by NNNMU (p<0.001). Morphologically, light microscopic examination denoted pathological findings such as formation of hyaline membrane, infiltration of neutrophils and perivascular cuffing in the lungs of NNNMU-treated rats. In addition, ultrastructural changes such as the necrosis of endothelial cells, swelling and vacuolization of lamellar bodies of alveolar type II cells, and the degeneration of pulmonary surfactant were identified after treatment of NNNMU. Very interestingly, cerium chloride electron microscopic cytochemistry showed that NNNMU had increased the production of cerrous-peroxide granules in the lung, which signified the increased production of hydrogen peroxide in the lung. Collectively, we conclude that NNNMU causes acute lung leak by the mechanism of neutrophilic oxidative stress of the lung.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.285-291
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• 2015

Exposure to cold sea water can be life-threatening to the drowned individual. Although appropriate life jacket can be usually be provided for the buoyance at the drowning accident, heat loss can make the drowned individual experience the hypothermia. Inflatable life jackets filled with inflatable air pocket can increase the thermal protection as well as the buoyancy force. Because it is important to know how the human body behaves unde the different life jacket, present study compares the thermal insulation capacity of solid type life jacket with that of inflatable life jacket. In order to represent the insulation capacity of life jacket, thermal resistance is estimated based on the assumption of steady-state. Also, a transient three-dimensional thermal distribution of the thigh is analyzed by using finite element method implementing the Pennes bioheat equation. The finite element model is a segmental, multi-layered representation of the body section which considers the heat conduction within tissue, bone, fat and local blood flow rate.

• Nutrition Research and Practice
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• v.16 no.1
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• pp.60-73
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• 2022

BACKGROUND/OBJECTIVES: The extract from Dendropanax morbifera exhibited diverse therapeutic potentials. We aimed to evaluate the efficacy and safety of D. morbifera leaf extract for improving metabolic parameters in human. SUBJECTS/METHODS: A 12-week, double blind, placebo-controlled and randomized trial included a total of 74 adults, and they were assigned to the placebo group (n = 38) or 700 mg/day of D. morbifera group (n = 36). The efficacy endpoints were changes in glycemic, lipid, obesity, and blood pressure (BP) parameters, in addition to the prevalence of metabolic syndrome (MetS) and the numbers of MetS components. Safety was assessed by monitoring adverse events (AEs). RESULTS: After 12 weeks of treatment, the hemoglobin A1c (HbA1c) level significantly decreased in the D. morbifera group compared to that of the placebo group (difference: -0.13 ± 0.20% vs. 0.00 ± 0.28%, P = 0.031; % of change: -2.27 ± 3.63% vs. 0.10 ± 5.10%, P = 0.025). The homeostatic model assessment for insulin resistance level also decreased significantly from its baseline in the D. morbifera group. The systolic BP of D. morbifera group decreased significantly than that of placebo group (difference: -3.9 ± 9.8 mmHg vs. 3.3 ± 11.7 mmHg, P = 0.005; % of change: -2.8 ± 7.7% vs. 3.3 ± 10.2%, P = 0.005). However, the lipid parameters and body composition including body weight did not differ between the groups. The prevalence of MetS (36.8% vs. 13.9%, P = 0.022) and the incidence of MetS (10.5% vs. 13.9%, P = 0.027) at 12 weeks was significantly lower in the D. morbifera group than it was in the placebo group. No serious AEs occurred in either group. CONCLUSIONS: Supplementation with D. morbifera extracts over a 12-week period improved metabolic parameters such as HbA1c and BP and reduced the prevalence of MetS.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.285-292
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• 2023

Recently, the impact of fine dust on health has become a major topic. Fine dust is dangerous because it can penetrate the body and affect the respiratory system, without being filtered out by the mucous membrane in the nose. Since fine dust is directly related to the industry, it is practically impossible to completely remove it. Therefore, if the concentration of fine dust can be predicted in advance, pre-emptive measures can be taken to minimize its impact on the human body. Fine dust can travel over 600km in a day, so it not only affects neighboring areas, but also distant regions. In this paper, wind direction and speed data and a time series prediction model were used to predict the concentration of fine dust in Seoul, and the correlation between the concentration of fine dust in Seoul and the concentration in each region was confirmed. In addition, predictions were made using the concentration of fine dust in each region and in Seoul. The lowest MAE (mean absolute error) in the prediction results was 12.13, which was about 15.17% better than the MAE of 14.3 presented in previous studies.

• Korean Journal of Exercise Nutrition
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• v.16 no.2
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• pp.65-71
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• 2012

Oxygen is the final acceptor of electron transport from fat and carbohydrate oxidation, which is the rate-limiting factor for cellular ATP production. Under altitude hypoxia condition, energy reliance on anaerobic glycolysis increases to compensate for the shortfall caused by reduced fatty acid oxidation [1]. Therefore, training at altitude is expected to strongly influence the human metabolic system, and has the potential to be designed as a non-pharmacological or recreational intervention regimen for correcting diabetes or related metabolic problems. However, most people cannot accommodate high altitude exposure above 4500 M due to acute mountain sickness (AMS) and insulin resistance corresponding to a increased levels of the stress hormones cortisol and catecholamine [2]. Thus, less stringent conditions were evaluated to determine whether glucose tolerance and insulin sensitivity could be improved by moderate altitude exposure (below 4000 M). In 2003, we and another group in Austria reported that short-term moderate altitude exposure plus endurance-related physical activity significantly improves glucose tolerance (not fasting glucose) in humans [3,4], which is associated with the improvement in the whole-body insulin sensitivity [5]. With daily hiking at an altitude of approximately 4000 M, glucose tolerance can still be improved but fasting glucose was slightly elevated. Individuals vary widely in their response to altitude challenge. In particular, the improvement in glucose tolerance and insulin sensitivity by prolonged altitude hiking activity is not apparent in those individuals with low baseline DHEA-S concentration [6]. In addition, hematopoietic adaptation against altitude hypoxia can also be impaired in individuals with low DHEA-S. In short-lived mammals like rodents, the DHEA-S level is barely detectable since their adrenal cortex does not appear to produce this steroid [7]. In this model, exercise training recovery under prolonged hypoxia exposure (14-15% oxygen, 8 h per day for 6 weeks) can still improve insulin sensitivity, secondary to an effective suppression of adiposity [8]. Genetically obese rats exhibit hyperinsulinemia (sign of insulin resistance) with up-regulated baseline levels of AMP-activated protein kinase and AS160 phosphorylation in skeletal muscle compared to lean rats. After prolonged hypoxia training, this abnormality can be reversed concomitant with an approximately 50% increase in GLUT4 protein expression. Additionally, prolonged moderate hypoxia training results in decreased diffusion distance of muscle fiber (reduced cross-sectional area) without affecting muscle weight. In humans, moderate hypoxia increases postprandial blood distribution towards skeletal muscle during a training recovery. This physiological response plays a role in the redistribution of fuel storage among important energy storage sites and may explain its potent effect on changing body composition. Conclusion: Prolonged moderate altitude hypoxia (rangingfrom 1700 to 2400 M), but not acute high attitude hypoxia (above 4000 M), can effectively improve insulin sensitivity and glucose tolerance for humans and antagonizes the obese phenotype in animals with a genetic defect. In humans, the magnitude of the improvementvaries widely and correlates with baseline plasma DHEA-S levels. Compared to training at sea-level, training at altitude effectively decreases fat mass in parallel with increased muscle mass. This change may be associated with increased perfusion of insulin and fuel towards skeletal muscle that favors muscle competing postprandial fuel in circulation against adipose tissues.

• The Korean Journal of Food And Nutrition
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• v.25 no.4
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• pp.787-792
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• 2012

The objective of this study was to investigate the proper concentration of D-xylose which is expected to reduce the GI (Glycemic index) value of sucrose in the human body. When subjects took a sucrose mixture containing 5% and 10% D-xylose, the blood glucose levels were lowered by approximately 27.5% and 25.9%, respectively, compared to those of sucrose. The GI values of sucrose mixtures containing 5% and 10% D-xylose were 49.3 and 50.4, respectively. The reduction in GI value was not dependent on the D-xylose concentration, as the GI value of sucrose mixture containing 5% D-xylose (XyloSugar) was similar to that of sucrose mixture containing 10% D-xylose (XyloSugar10). D-xylose is not only more expensive but also less sweet than sucrose. So, low concentration of D-xylose has the advantage in the price and taste. It was determined that the proper concentration of D-xylose expected to reduce GI value of sucrose was 5% (w/w).

• Journal of Nutrition and Health
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• v.49 no.6
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• pp.411-419
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• 2016

Purpose: Dysregulation of adipokines caused by excess adipose tissue has been implicated in the development of obesity-related metabolic diseases. This study evaluated the effects of mugwort (Artemisia princeps Pampanini) ethanol extract on lipid metabolic changes, insulin resistance, adipokine balance, and body fat reduction in obese rats. Methods: Male Sprague-Dawley rats were fed either a control diet (NC), high-fat diet (HF, 40% kcal from fat), or high-fat diet with 1% mugwort extract (HFM) for 6 weeks. Results: Epididymal and retroperitoneal fat mass increased in the HF group compared with the NC group, and epididymal fat mass was reduced in the HFM group (p < 0.05). No difference was observed in serum levels of total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-C) among the groups. However, triglyceride (TG), TG/HDL-C ratio, and TC/HDL-C ratio increased in the HF group and significantly decreased in the HFM group. TG and TC levels in the liver were significantly higher in the HF group, whereas these levels were significantly reduced in the HFM group. HF rats had lower insulin sensitivity as indicated by increased homeostasis model assessment of the insulin resistance (HOMA-IR) value. HOMA-IR values significantly decreased in the HFM group. Adiponectin levels were higher in NC rats, and their leptin and PAI-1 levels were lower. Relative balance of adipokines was reversed in the HF group, with lower adiponectin levels but higher leptin and PAI-1 levels. In contrast, the HFM group maintained balance of adiponectin/leptin and adiponectin/PAI-1 levels similar to NC by reducing leptin and PAI-1 levels. Conclusion: Overall data indicated that mugwort extract can be effective in alleviating metabolic dislipidemia, insulin resistance, and adipokine dysregulation induced by a high-fat diet.

• Food Science and Preservation
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• v.23 no.1
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• pp.104-109
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• 2016

The purpose of this study was to evaluate the inhibitory effect of commercial Makgeolli on tumor growth in human gastric adenocarcinoma cells (AGS) in a xenograft cancer model, transplanted with AGS cells. Commercial Makgeolli was first dealcoholized by evaporation and used as the test sample. We detected a significant increase in the volume and weight of tumor in nude mice (induction) that were transplanted with AGS cells. Administration of $100mg/kg{\cdot}day$ group (ML), and $500mg/kg{\cdot}day$ group (MH) dealcoholized commercial Makgeolli significantly decreased tumor growth. In this study, 5-FU $18mg/kg{\cdot}day$ was used as a positive control for tumor growth inhibition. Additionally, determination of the body weight of both the groups revealed no side effects after the administration of dealcoholized commercial Makgeolli. Using the cell culture system, we also evaluated the effect of dealcoholized commercial Makgeolli on caspase-3/7 activity in the AGS cells. Treatment with dealcoholized commercial Makgeolli increased the activation of caspase-3/7 and the apoptotic markers in AGS cells in a dose-dependent manner. Therefore, dealcoholized commercial Makgeolli can be used for cancer prevention.

• Korean Chemical Engineering Research
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• v.57 no.4
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• pp.475-483
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• 2019

Special chemical warfare agents are lethal gases that attack the human respiratory system. One of such gases are blood agents that react with the irons present in the electron transfer system of the human body. This reaction stops internal respiration and eventually causes death. The molecular sizes of these agents are smaller than the pores of an activated carbon, making chemical adsorption the only alternative method for removing them. In this study, we carried out a Computational Fluid Dynamics simulation by passing a blood agent: cyanogen chloride gas through an SG-1 gas mask canister developed by SG Safety Corporation. The adsorption bed consisted of a Silver-Zinc-Molybdenum-Triethylenediamine activated carbon impregnated with copper, silver, zinc and molybdenum ions. The kinetic analysis of the chemical adsorption was performed in accordance with the test procedure for the gas mask canister and was validated by the kinetic data obtained from experimental results. We predicted the dynamic behaviors of the main variables such as the pressure drop inside the canister and the amount of gas adsorbed by chemisorption. By using a granular packed bed instead of the Ergun equation that is used to model porous materials in Computational Fluid Dynamics, applicable results of the activated carbon were obtained. Dynamic simulations and flow analyses of the chemical adsorption with varying gas flow rates were also executed.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.