• 제목/요약/키워드: Human Activity

검색결과 7,714건 처리시간 0.036초

Growth Inhibitory Activity of Honokiol through Cell-cycle Arrest, Apoptosis and Suppression of Akt/mTOR Signaling in Human Hepatocellular Carcinoma Cells

  • Hong, Ji-Young;Park, Hyen Joo;Bae, KiHwan;Kang, Sam Sik;Lee, Sang Kook
    • Natural Product Sciences
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    • 제19권2호
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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.

Antimicrobial Effect of Furaneol Against Human Pathogenic Bacteria and Fungi

  • Sung Woo-Sang;Jung Hyun-Jun;Lee In-Seon;Kim Hyun-Soo;Lee Dong-Gun
    • Journal of Microbiology and Biotechnology
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    • 제16권3호
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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.

Cytotoxic Activity of Biosynthesized Gold Nanoparticles with an Extract of the Red Seaweed Corallina officinalis on the MCF-7 Human Breast Cancer Cell Line

  • El-Kassas, Hala Yassin;El-Sheekh, Mostafa M.
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권10호
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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.

Detecting Complex 3D Human Motions with Body Model Low-Rank Representation for Real-Time Smart Activity Monitoring System

  • Jalal, Ahmad;Kamal, Shaharyar;Kim, Dong-Seong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권3호
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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.

어머니가 지각한 유아의 기질과 양육 스트레스 (Maternal Perception of Children's Temperament & Parenting Stress)

  • 조용신;정영숙
    • 한국생활과학회지
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    • 제9권3호
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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.

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Estrogen Modulation of Human Breast Cancer Cell Growth

  • Lee, Hyung-Ok;Sheen, Yhun-Yhong
    • Archives of Pharmacal Research
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    • 제20권6호
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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.

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Upregulation of Nitric Oxide Synthase Activity by All-trans Retinoic Acid and 13-cis Retinoic Acid in Human Malignant Keratinocytes

  • Moon, Ki-Young
    • 대한의생명과학회지
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    • 제25권2호
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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.

Development of a Hybrid Deep-Learning Model for the Human Activity Recognition based on the Wristband Accelerometer Signals

  • Jeong, Seungmin;Oh, Dongik
    • 인터넷정보학회논문지
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    • 제22권3호
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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.

Evaluation of the EtOAc Extract of Lemongrass (Cymbopogon citratus) as a Potential Skincare Cosmetic Material for Acne Vulgaris

  • Kim, Chowon;Park, Jumin;Lee, Hyeyoung;Hwang, Dae-Youn;Park, So Hae;Lee, Heeseob
    • Journal of Microbiology and Biotechnology
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    • 제32권5호
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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.

영상기반 인체행위분류를 위한 전이학습 중추네트워크모델 분석 (Transfer Learning Backbone Network Model Analysis for Human Activity Classification Using Imagery)

  • 김종환;류준열
    • 한국시뮬레이션학회논문지
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    • 제31권1호
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    • pp.11-18
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    • 2022
  • 최근 공공장소 및 시설에서 범죄예방 및 시설 안전을 목적으로 영상정보 기반의 인체의 행위를 분류하는 연구가 활발히 진행되고 있다. 이러한 인체 행위분류의 성능을 향상하기 위해서 대부분의 연구는 전이학습 기반의 딥러닝을 적용하고 있다. 그러나 딥러닝의 기반이 되는 중추 네트워크 모델(Backbone Network Model)의 수가 증가하고 아키텍처가 다양해짐에도 불구하고, 소수의 모델만 사용하는 분위기 때문에 운용목적에 적합한 중추 네트워크 모델을 찾는 연구는 미흡한 실정이다. 본 연구는 영상정보를 기초로 인체 행위를 분류하는 인공지능 모델을 개발하기 위해 최근에 개발된 5가지의 딥러닝 중추 네트워크 모델을 대상으로 전이학습을 적용하고 각 모델의 정확도 및 학습효율 측면에서 비교 및 분석하여 가장 효율이 높은 모델을 제안하였다. 이를 위해, 기본적인 인체 행위가 아닌 운동 종목 기반의 활동적이고 신체접촉이 높은 12가지의 인체 활동을 선정하고 관련된 7,200개의 이미지를 수집하였으며, 5가지의 중추 네트워크 모델에 총 20회의 전이학습을 균등하게 적용하고 학습과정과 결과성능을 통해 인체 행위를 분류하는데 적합한 중추 네트워크 모델을 정량적으로 비교 및 분석하였다. 그 결과 XceptionNet 모델이 학습 및 검증 정확도에서 0.99 및 0.91로, Top 2 및 평균 정밀도에서 0.96 및 0.91로 나타났으며 학습 소요시간은 1,566초, 모델용량의 크기는 260.4MB로 정확도와 학습효율 측면에서 다른 모델보다 높은 성능이 나타남을 확인할 수 있었다. 이러한 결과는 전이학습을 적용하여 인체 행위분류를 진행하는 다양한 연구 분야에 활용되기를 기대한다.