• Natural Product Sciences
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• v.19 no.2
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• pp.155-159
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• 2013

Honokiol, a naturally occurring neolignan mainly found in Magnolia species, has exhibited a potential anti-proliferative activity in human cancer cells. However, the growth inhibitory activity against hepatocellular carcinoma cells and the underlying molecular mechanisms has been poorly determined. The present study was designed to examine the anti-proliferative effect of honokiol in SK-HEP-1 human hepatocellular cancer cells. Honokiol exerted anti-proliferative activity with cell-cycle arrest at the G0/G1 phase and sequential induction of apoptotic cell death. The cell-cycle arrest was well correlated with the down-regulation of checkpoint proteins including cyclin D1, cyclin A, cyclin E, CDK4, PCNA, retinoblastoma protein (Rb), and c-Myc. The increase of sub-G1 peak by the higher concentration of honokiol ($75{\mu}M$) was closely related to the induction of apoptosis, which was evidenced by decreased expression of Bcl-2, Bid, and caspase-9. Hohokiol was also found to attenuate the activation of signaling proteins in the Akt/mTOR and ERK pathways. These findings suggest that the anti-proliferative effect of honokiol was associated in part with the induction of cell-cycle arrest, apoptosis, and dow-nregulation of Akt/mTOR signaling pathways in human hepatocellular cancer cells.

• Journal of Microbiology and Biotechnology
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• v.16 no.3
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• pp.349-354
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• 2006

Furaneol, a key aroma compound found in strawberry, pineapple, and processed foodstuffs, has been known to possess various biological activities on animal models. In this study, the antimicrobial effects of furaneol against human pathogenic microorganisms were investigated. The results indicated that furaneol displayed a broad spectrum of antimicrobial activities against Gram-positive and Gram-negative bacteria and fungi without hemolytic activity on human erythrocyte cells. To confirm the antifungal activity of furaneol, we examined the accumulation of intracellular trehalose as a stress response marker on toxic agents and its effect on dimorphic transition of Candida albicans. The results demonstrated that furaneol induced significant accumulation of intracellular trehalose and exerted its antifungal effect by disrupting serum-induced mycelial forms. These results suggest that furaneol could be a therapeutic agent having a broad spectrum of antimicrobial activity on human pathogenic microorganisms.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.10
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• pp.4311-4317
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• 2014

Background: Nano-biotechnology is recognized as offering revolutionary changes in the field of cancer therapy and biologically synthesized gold nanoparticles are known to have a wide range of medical applications. Materials and Methods: Gold nanoparticles (GNPs) were biosynthesized with an aqueous extract of the red alga Corallina officinalis, used as a reducing and stabilizing agent. GNPs were characterized using UV-Vis spectroscopy, transmission electron microscopy (TEM), energy dispersive analysis (EDX) and Fourier transform infra-red (FT-IR) spectroscopy and tested for cytotoxic activity against human breast cancer (MCF-7) cells cultured in Dulbecco's modified Eagle medium supplemented with 10% fetal bovine serum, considering their cytotoxicty and effects on cellular DNA. Results: The biosynthesized GNPs were $14.6{\pm}1nm$ in diameter. FT-IR analysis showed that the hydroxyl functional group from polyphenols and carbonyl group from proteins could assist in formation and stabilization. The GNPs showed potent cytotoxic activity against MCF-7 cells, causing necrosis at high concentrations while lower concentrations were without effect as indicated by DNA fragmentation assay. Conclusions: The antitumor activity of the biosynthesized GNPs from the red alga Corallina officinalis against human breast cancer cells may be due to the cytotoxic effects of the gold nanoparticles and the polyphenolcontent of the algal extract.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1189-1204
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• 2018

Detecting and capturing 3D human structures from the intensity-based image sequences is an inherently arguable problem, which attracted attention of several researchers especially in real-time activity recognition (Real-AR). These Real-AR systems have been significantly enhanced by using depth intensity sensors that gives maximum information, in spite of the fact that conventional Real-AR systems are using RGB video sensors. This study proposed a depth-based routine-logging Real-AR system to identify the daily human activity routines and to make these surroundings an intelligent living space. Our real-time routine-logging Real-AR system is categorized into two categories. The data collection with the use of a depth camera, feature extraction based on joint information and training/recognition of each activity. In-addition, the recognition mechanism locates, and pinpoints the learned activities and induces routine-logs. The evaluation applied on the depth datasets (self-annotated and MSRAction3D datasets) demonstrated that proposed system can achieve better recognition rates and robust as compare to state-of-the-art methods. Our Real-AR should be feasibly accessible and permanently used in behavior monitoring applications, humanoid-robot systems and e-medical therapy systems.

• Korean Journal of Human Ecology
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• v.9 no.3
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• pp.271-281
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• 2000

The purpose of this study was to explore the effect of maternal perception of children's temperament on parenting stress. The subjects of this study were 303 mothers of four to six-year-old. Evaluations of Parent and Teacher temperament questionnaire for Children 3-7 years of age(Tomas, Chess, & Kom, 1977)(korean version) was used to measure children's temperament, and PDH(Parenting Daily Hassles) was used to measure maternal perception of parenting stress. Data were analyzed by descriptive analysis, t-test, ANOVA, Peasons's Correlation and multiple regression analysis and Duncan test for post test by SPSS WIN program. The results of this study were as follows; First, the average level of maternal perception of children's temperament was the highest in the category of adaptability and the lowest in the category of threshold of responsiveness. Second, maternal perception of children's temperament was significantly different according to children's sex. Boys were perceived higher than girls for the category of activity level. Third, the degree of daily hassles was explained by adaptability, the quality of mood, and activity level relatively, while the intensity of parenting stress could be predicted orderly by adaptability, threshold of responsiveness, attention span & persistence, regularity, and activity level. Fourth, mother's daily hassles was explained 22% valiance by children's temperament such as adaptability, the quality of mood, and activity level. Future research should be done to identify the interaction of temperamental factors.

• Archives of Pharmacal Research
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• v.20 no.6
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• pp.566-571
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• 1997

To gain further insight into how estrogens modulate cell function, the effects of estrogen on cell proliferation were studied inhuman breast cancer cells. We examined the effects of estrogen on the proliferation of three human breast cancer cell lines that differed in their estrogen receptor contents. Ten nM estradiol markedly stimulated the proliferation of MCF-7 human breast cancer cells that contained high levels of estrogen receptor $1.15{\pm}0.03 pmole/mg protein)$(over that of control. In T47D cells that contained low levels of estrogen receptor $0.23{\pm}0.05 pmole/mg protein)$, Ten nM estrogen slightly stimulated the proliferation over that of control. MDA-MB-231 cells, that contained no detectable levels of estrogen receptors, had their growth unaffected by estrogen. These results showed their sensitivity to growth stimulation by estrogen correlated well with their estrogen receptor content. Also we examined the effect of estrogen on cellular progesterone receptor level as well as plasminogen activator activity in MCF-7 cells. Ten nM estradiol showed maximal stimulation of progesterone receptor level as well as plasminogen activator activity in MCF-7 cells. It is not clear whether these stimulations of progesterone receptor and plasminogen activator activity by estrogen are related to the estrogen stimulation of cell proliferation of MCF-7 cells. Studies with estrogen in human breast cancer cells in culture indicate that sensitivity to growth stimulation by estrogen correlates well with estrogen receptor contents.

• Biomedical Science Letters
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• v.25 no.2
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• pp.196-200
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• 2019

Effect of retinoids, i.e., all-trans retinoic acid and 13-cis retinoic acid, on the activity of nitric oxide synthase (NOS) was evaluated in human malignant keratinocytes to examine the possible correlation of retinoids with NOS activities. All-trans retinoic acid and 13-cis retinoic acid did not alter the nitric oxide (NO) production. However, in the presence of lipopolysaccharide (LPS, $1{\mu}g/mL$), they significantly increased NO release in a dose-dependent manner until 48 h at concentrations of $50{\sim}100{\mu}M$. The degree of upregulation of NO by all-trans retinoic acid and 13-cis retinoic acid increased up to 35% and 37%, respectively, compared to that by the control, which demonstrated the upregulation of LPS-inducible nitric oxide synthase (iNOS)-dependent generation of NO as well as showing a crucial link between retinoids-induced activity and NOS. Findings of this study now suggest that the upregulation of LPS-iNOS activity may be associated with modulation of retinoids-induced control of cellular developmental processes, which may produce new therapeutics of retinoids in the complexity of how NO affects human keratinocytes.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.9-16
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• 2021

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.

• Journal of Microbiology and Biotechnology
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• v.32 no.5
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• pp.594-601
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• 2022

This study evaluated the biological properties of lemongrass (Cymbopogon citratus) extracts. The EtOAc extract of lemongrass had DPPH, TEAC, and nitric oxide-scavenging activity assay results of 58.06, 44.14, and 41.08% at the concentration of 50, 10, and 50 ㎍/ml, respectively. The EtOAc extract had higher elastase and collagenase inhibitory activities than the 80% MeOH, n-hexane, BuOH, and water extracts and comparable whitening activity toward monophenolase or diphenolase. Also, the EtOAc fraction had higher lipase inhibitory and antimicrobial activities against Cutibacterium acnes among extracts which is known to an important contributor to the progression of inflammatory acne vulgaris, and an opportunistic pathogen present in human skin. Total phenolic and flavonoid concentrations in the EtOAc extract were 132.31 mg CAE/g extract and 104.50 mg NE/g extract, respectively. Biologically active compounds in lemongrass extracts were analyzed by LC-MS. This study confirms that lemongrass extracts have potential use as cosmetic skincare ingredients. Thus, lemongrass can be considered a promising natural source of readily available, low-cost extracts rich in antioxidant, skincare, and antimicrobial compounds that might be suitable for replacing synthetic compounds in the cosmeceutical industry.

• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.11-18
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• 2022

Recently, research to classify human activity using imagery has been actively conducted for the purpose of crime prevention and facility safety in public places and facilities. In order to improve the performance of human activity classification, most studies have applied deep learning based-transfer learning. However, despite the increase in the number of backbone network models that are the basis of deep learning as well as the diversification of architectures, research on finding a backbone network model suitable for the purpose of operation is insufficient due to the atmosphere of using a certain model. Thus, this study applies the transfer learning into recently developed deep learning backborn network models to build an intelligent system that classifies human activity using imagery. For this, 12 types of active and high-contact human activities based on sports, not basic human behaviors, were determined and 7,200 images were collected. After 20 epochs of transfer learning were equally applied to five backbone network models, we quantitatively analyzed them to find the best backbone network model for human activity classification in terms of learning process and resultant performance. As a result, XceptionNet model demonstrated 0.99 and 0.91 in training and validation accuracy, 0.96 and 0.91 in Top 2 accuracy and average precision, 1,566 sec in train process time and 260.4MB in model memory size. It was confirmed that the performance of XceptionNet was higher than that of other models.