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Stilbenes and Oligostilbenes from Leaf and Stem of Vitis amurensis and Their Cytotoxic Activity
Do Thi Ha,Quan Cheng Chen,Tran Manh Hung,Tran Minh Ngoc,Phuong Thien Thuong,김홍진,성연희,민병선,배기환,윤의중 대한약학회 2009 Archives of Pharmacal Research Vol.32 No.2
Chromatographic separation of the EtOAc fraction from the leaf and stem of Vitis amurensis led to the isolation of six oligostilbenoids (i.e., r-2-viniferin (1), trans-amurensin B (2), trans-ε -viniferin (3), gnetinH (4), amurensin G (5), (+)-ampelopsin A (8)) and four stilbenoids (i.e., trans-resveratrol (6), (+)- ampelopsin F (7), piceatannol (9), and trans-piceid (10)). The structures have been identified on the basis of spectroscopic evidence and physicochemical properties. The isolates were investigated for cytotoxic activity against three cancer cell lines in vitro using the MTT assay method. Amurensin G (5) and trans-resveratrol (6) showed significant cytotoxic activity against L1210, K562 and HTC116 cancer cell lines with IC50 values ranging from 15.7 ± 2.1 to 30.9 ± 1.8 μM. (+)-Ampelopsin A (8) and trans-piceid (10) exhibited considerable cytotoxic activity against L1210 (IC50 values of 30.6 ± 4.1 and 28.7 ± 2.81μM, respectively) and K562 (IC50 values of 38.6 ± 0.82 and 24.6 ± 0.76 μM, respectively). Gnetin H (4)showed only weak cytotoxic activity against L1210 with an IC50 value of 40.1 ± 4.23 μM. On the other hand, r-2-viniverin (1), trans-amurensin B (2), trans-ε -viniferin (3), (+)-ampelopsin F (7), and piceatannol(9) exhibited no activity on three cancer cell lines.
Chien Minh Tran,Ngoc Thi‑Thanh Nguyen,Minh Hieu Ho,Vinh Khanh Doan,Khanh Loan Ly,Nhi Ngoc‑Thao Dang,Nam Minh‑Phuong Tran,Hoai Thi‑Thu Nguyen,Long Phuoc Truong,Thai Minh Do,Quyen Ngoc Tran,Hien Quoc Ng 한국섬유공학회 2023 Fibers and polymers Vol.24 No.1
In this study, we proposed a straightforward electrospun polycaprolactone (PCL) loaded with silver nanoparticles (SNPs)membrane fabrication process, in which SNPs were directly synthesized from silver nitrate (AgNO3) in PCL–acetone mixtureby gamma irradiation. The insolubility of AgNO3in PCL solution was solved using an auxiliary dimethyl sulfoxide solvent. As a physical approach, gamma rays readily converted silver ions into SNPs without the addition of harmful reductionagents, which reduced the cytotoxicity of the synthesized material. By avoiding some processes such as purification, solventremoval, or redispersion of SNPs, this method was more time-saving compared to other related studies. SNPs formation wasconfirmed by both UV–Visible spectrum (UV–Vis) and X-ray diffraction analysis. Scanning electron microscopy (SEM)revealed that the addition of SNPs significantly reduced the fiber diameter of PCL–Ag membranes compared to that of rawPCL. Uniform spherical-shaped SNPs incorporated in PCL fibers were observed under transmission electron microscopy(TEM). The tensile test showed that the electrospun PCL–Ag membranes exhibited good mechanical characteristics. Moistureeasily penetrated the porous microstructure of PCL–Ag, facilitating wound humidity regulation. Inductively coupledplasma-mass spectroscopy (ICP-MS) was employed to study the release profiles of SNPs at different time intervals. Overall,the PCL–Ag 500 ppm sample exerted excellent antibacterial activity against Pseudomonas aeruginosa and Staphylococcusaureus strains and low in vitro cytotoxicity.
Source apportionment of ambient PM2.5 in Ho Chi Minh City, Vietnam
Ngoc Tran,Yusuke Fujii,Md Firoz Khan,To Thi Hien,Tran Hoang Minh,Hiroshi Okochi,Norimichi Takenaka 한국대기환경학회 2024 Asian Journal of Atmospheric Environment (AJAE) Vol.18 No.1
The emission sources of fine particulate matter ( PM2.5) have not yet been fully identified in Ho Chi Minh City (HCMC), Vietnam, presenting difficulties to authorities in controlling air pollution efficiently. To address this issue, this study explores the source apportionment of PM2.5 by the positive matrix factorization (PMF) model and identifies potential regional sources through the weighted concentration-weighted trajectory (WCWT) model based on the field observation data of PM2.5 in HCMC. 24-h PM2.5 samples were collected in central HCMC for a year (September 2019–August 2020). Herein, inductively coupled plasma mass spectroscopy was used to analyze trace elements, in addition to identifying PM2.5 mass and other chemical species, such as water-soluble ions and carbonaceous species, reported in our former study. The PMF results showed that PM2.5 in HCMC was dominated by anthropogenic-rich sources comprising biomass burning, coal combustion, transportation, and crustal origins (36.4% of PM2.5 mass), followed by secondary ammonium sulfate (18.4%), sea salt (13.7%), road dust (9.6%), and coal and crude oil combustion (9.4%). WCWT results suggested that the geological sources of PM2.5 were mainly from local areas and scattered to the northeast/southwest of HCMC. In addition, the long-range transport of PM2.5 from surrounding countries was revealed during the assembly restriction and lockdown period in 2020.
The manufacturing of sintered bricks from clay and red mud derived from the alumina processing plant
Ngoc Tuyen Tran,Duc Vu Quyen Nguyen,Van Minh Hai Ho,Xuan Tin Dang,Ngoc Quang Tran 한양대학교 청정에너지연구소 2017 Journal of Ceramic Processing Research Vol.18 No.5
In this study, the manufacturing of sintered bricks from clay and red mud was presented. The initial materials and obtainedbricks were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope(TEM), X-ray fluorescence (XRF), and differential scanning calorimetry-thermal gravimetry (DSC-TG). The compressivestrength, water absorption, bulk density and sintering shrinkage of sintered bricks were performed. The effects of componentsof raw materials, sintering temperature and time on physico-mechanical properties of the products was investigated. Theresults showed that the bricks prepared at 1000 oC for 1 hr with raw material containing up to 50% of red mud providedexcellent physico-mechanical properties. The obtained brick met the Vietnam standard VS1451-1998 and was satisfied theconstruction material requirements that were safe to human’s health and friendly with environment in terms of alkalineleaching and radioactivity indexes.
( Minh Hai Pham ),( Quan Anh Tuan Le ),( Hoang Bac Nguyen ),( Quang Hung Vu ),( Thai Ngoc Huy Tran ),( Hang Dang Khoa N Guyen ),( Thi Ngoc Sang Duong ),( Van Toan Tran ) 대한간학회 2020 춘·추계 학술대회 (KASL) Vol.2020 No.1
Aims: Laparoscopic pancreaticoduodenectomy (LPD) is considered as a safe and effective procedure in well - selected patients and appropriate surgical technique. Our aim is to evaluate suitability of using protocol for LPD in treatment of periampullary cancer at a single team. Methods: case series Results: Indication for LPD included 37 cases with resectable tumors which were classified basing on NCCN. All witness evaluation risk of complications with PREPARE score, ASA and evaluation risk of postoperative pancreatic fistula (POPF) with FRS classification. There were 2 open conversions because of vein resections, accounting for 5.4%. Standard lymphadenectomy was performed in all of 37 cases. In term of PREPARE score, major complications (Clavien - Dindo >= III) were 17.8%, 0% and 0% (5/28, 0/5 and 0/2 cases) in low risk, intermediate risk and high risk group, respectively. All of cases had ASA I or II. POPF happened 11.1% (1/9), 4.1% (1/24) and 50% (1/2) in low risk, intermediate risk and high risk group, respectively. Frozen section was needed for R0 margin. Retrieved lymph nodes was 8 - 18 with 12 lymph nodes in average. Conclusions: Indication for LPD with resectable tumors is acceptable. ASA I or II is a safe measure to select patient for LPD. FRS classification shows appropriation to evaluate risk of POPF.
A Cloud QoS-driven Scheduler based on Deep Reinforcement Learning
Minh Ngoc Tran,Young Han Kim 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.6
Task scheduling is one of the most challenging issue in cloud management. Because it is a decision-making problem, Reinforcement Learning has been utilized by several works to build an intelligent and efficient cloud task scheduler. However, while resources utilization was used as the key factor to schedule task in most studies, another crucial requirement for cloud task scheduling which is tasks’ Quality-of-Service (QoS) guarantee has not been approached yet. Therefore, in this paper, we present a Deep Reinforcement Learning-based task scheduler which focus on QoS guarantee.
Asynchronous Deep Reinforcement Learning based QoS Supporting Scheduler for Kubernetes
Minh Ngoc Tran,Young Han Kim 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.11
Due to the nature of task scheduling problem in cloud environment is a decision-making problem, Deep Reinforcement Learning has been utilized to achieve adaptive intelligence cloud scheduler. Most of Deep Reinforcement Learning proposed design for cloud scheduler focus on optimizing resources utilization between cloud clusters and nodes. However, in 5G networks, QoS guarantee for tasks is another important requirement where there are large amounts of critical-delay tasks. In this paper, we use apply Deep Reinforcement Learning to build a QoS-guarantee scheduler but with an asynchronous design to improve training time and accuracy of previous Deep Reinforcement Learning system.