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Two new meroterpenoids produced by the endophytic fungus Penicillium sp. SXH-65
Xinhua Sun,Xianglan Kong,Huquan Gao,Tianjiao Zhu,Guangwei Wu,Qianqun Gu,Dehai Li 대한약학회 2014 Archives of Pharmacal Research Vol.37 No.8
Two new meroterpenoids, arisugacins I (1) andJ (2), together with five known meroterpenoids includingarisugacin B (3), arisugacin F (4), arisugacin G (5), territremB (6) and territrem C (7) were isolated from anendophytic fungus Penicillium sp. SXH-65. Their structureswere determined by extensive spectroscopic experimentsand comparison with literature data. Theircytotoxicities were evaluated against Hela, HL-60 andK562 cell lines, and only 3 and 4 exhibited weak cytotoxicitiesagainst Hela, HL-60 and K562 cell lines withIC50 values ranging from 24 to 60 lM.
Overview of Active Disturbance Rejection Control for Permanent Magnet Synchronous Motors
Zhang Xinhua,Chen Yujia,Sun Xiaodong 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.3
The ubiquitous implementation of permanent magnet synchronous motors (PMSMs) in contemporary alternating current propulsion systems is widely acknowledged. As a superior control method that does not rely on a precise system mathematical model and has superior robustness, Active Disturbance Rejection Control (ADRC) is widely used to improve the overall control performance and efciency of the PMSM drive system. Starting from three parts of ADRC, this paper comprehensively expounds on the advantages of the ADRC control strategy and its shortcomings in the application at present. The problems of too many parameters, not easily controlling the nonlinear part, and difculty in adjusting the parameters are summarized. Then the performance improvement schemes of ADRC such as structure optimization, parameter tuning, nonlinear part optimization, and simplifed parameters are summarized. Finally, the future development trend of the control algorithm is forecasted.
Renxin Xu,Huan Yang,Huajun Sun,Jing Zhou,Zhijun Yue,Xinhua Gao 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2019 NANO Vol.14 No.2
Mg0.2Mn0.8YxFe2-xO4 (x = 0.000, 0.025, 0.050 and 0.075) nanocrystalline is synthesized via hydrothermal technique. Single cubic spinel phase is confirmed by XRD and the formation of Mg0.2Mn0.8YxFe2-xO4 is verified by EDS. The average size of the nanoferrites is around 80 nm, which is examined by TEM image. Y3+ substituted Mg-Mn nanoferrites exhibit low saturation magnetization (Ms) and coercivity (Hc). Especially, the nanoferrites with x = 0.075 show the lowest Ms and Hc of 46.96 emu/g and 12.04 Oe, respectively. The ferrite composites present that the resistivity and the magnetic loss are less than 4.5 x 10 7 Ω · cm and 0.7 in the range of 2–18 GHz, respectively. The low coercivity and high resistivity indicate that the addition of Y3+ contributes to the synthesis of the excellent soft magnetic materials.
Xiaoyan Feng,Xin Wen,Ling Li,Zhenchang Sun,Xin Li,Lei Zhang,Jingjing Wu,Xiaorui Fu,Xinhua Wang,Hui Yu,Xinran Ma,Xudong Zhang,Xinli Xie,Xingmin Han,Mingzhi Zhang 대한암학회 2021 Cancer Research and Treatment Vol.53 No.3
Purpose There is no optimal prognostic model for T-cell lymphoblastic lymphoma (T-LBL). Here, we discussed the predictive value of total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) measured on 18F-fluorodeoxyglucose positron emission tomography–computed tomography (PET-CT) in T-LBL.Materials and Methods Thirty-seven treatment naïve T-LBL patients with PET-CT scans were enrolled. TMTV was obtained using the 41% maximum standardized uptake value (SUVmax) threshold method, and TLG was measured as metabolic tumor volume multiplied by the mean SUV. Progression-free survival (PFS) and overall survival (OS) were analyzed by Kaplan-Meier curves and compared by the log-rank test.Results The optimal cutoff values for SUVmax, TMTV, and TLG were 12.7, 302 cm3, and 890, respectively. A high SUVmax, TMTV, and TLG indicated a shorten PFS and OS. On multivariable analysis, TMTV ≥ 302 cm3, and central nervous system (CNS) involvement predicted inferior PFS, while high SUVmax, TLG and CNS involvement were associated with worse OS. Subsequently, we generated a risk model comprising high SUVmax, TMTV or TLG and CNS involvement, which stratified the population into three risk groups, which had significantly different median PFS of not reached, 14 months, and 7 months for low-risk group, mediate-risk group, and high-risk group, respectively (p < 0.001). Median OS were not reached, 27 months, and 13 months, respectively (p < 0.001).Conclusion Baseline SUVmax, TMTV, and TLG measured on PET-CT are strong predictors of worse outcome in T-LBL. A risk model integrating these three parameters with CNS involvement identifies patients at high risk of disease progression.
Amygdalin inhibits HSC-T6 cell proliferation and fibrosis through the regulation of TGF-β/CTGF
Huanhuan Luo,Liang Li,Jianbang Tang,Fengxue Zhang,Fang Zhao,Da Sun,Fengling Zheng,Xinhua Wang,Xinhua Wang 대한독성 유전단백체 학회 2016 Molecular & cellular toxicology Vol.12 No.3
Amygdalin is one of the nitrilosides that was widely used to treat cancer, inhibit liver fibrosis. In the present study, the aim was to determine the antifibrotic potential of amygdalin and examine its mechanisms of action in vitro. Firstly, we found amygdalin significantly inhibited HSC-T6 cells proliferation. Both mRNA and protein of transforming growth factor-β (TGF-β) were decreased in HSC-T6 cells during amygdalin treatment. Secondly, to investigate functional role of TGF-β, both TGF-β over-expression vector and siRNA against TGF-β were transfected into HSC-T6 cells respectively. The results showed that over-expression of TGF-β promoted proliferation of HSC-T6 cells, whereas TGF-β knockdown inhibited cell viability. Moreover, our data even indicated that TGF-β could promote cell proliferation independent of amygdalin treatment. Finally, we found amygdalin could inhibit expression of the classical fibrotic factor αSMA, which suggested an antifibrotic effect of amygdalin. While the TGF-β antagonized anti-fibrotic effect of amygdalin. To assess the mechanisms, we examined expression of CTGF in cultured HSC-T6 cells. Our results showed that CTGF was down-regulated in HSCT6 cell treated by amygdalin, but was up-regulated when exogenous TGF-β introduced. As CTGF was one of the downstream factors in the TGF-β pathway. These might suggest that amygdalin inhibited HSC-T6 cells proliferation and fibrosis via TGF-β/CTGF pathway.