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- 저자 : Chuntao Zhang (검색결과 4 건)
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Chuntao Yang,Jianqiang Feng,Hongzhong Ling,Meifen Zhang,Zhanli Yang,Xiuyu Wang,Fanqin Zeng,Chuhuai Wang 한국분자세포생물학회 2011 Molecules and cells Vol.31 No.6
Hypoxia of skin is an important physiopathological process in many diseases, such as pressure ulcer, diabetic ulcer, and varicose ulcer. Although cellular injury and inflammation have been involved in hypoxia-induced dermatic injury, the underlying mechanisms remain largely unknown. This study was conducted to investigate the effects of cobalt chloride (CoCl_2), a hypoxia-mimicking agent, on human skin keratinocytes (HaCaT cells) and to explore the possible molecular mechanisms. Exposure of HaCaT cells to CoCl_2 reduced cell viability and caused overproduction of reactive oxygen species (ROS) and oversecretion of interleukin-6 (IL-6) and interleukin-8 (IL-8). Importantly, CoCl_2 exposure elicited overexpression of cyclooxygenase-2 (COX-2) and phosphorylation of nuclear factor-kappa B (NF-κB) p65 subunit. Inhibition of COX-2 by NS-398, a selective inhibitor of COX-2, significantly repressed the cytotoxicity, as well as secretion of IL-6 and IL-8 induced by CoCl2. Inhibition of NF-κB by PDTC (a selective inhibitor of NF-κB) or genetic silencing of p65 by RNAi (Si-p65), attenuated not only the cytotoxicity and secretion of IL-6 and IL-8, but also overexpression of COX-2 in CoCl2-treated HaCaT cells. Neutralizing anti-IL-6 or anti-IL-8 antibody statistically alleviated CoCl2-induced cytotoxicity in HaCaT cells. N-acetyl-L-cysteine (NAC), a well characterized ROS scavenger, obviously suppressed CoCl_2-induced cytotoxicity in HaCaT cells, as well as secretion of IL-6 and IL-8. Additionally, NAC also repressed overexpression of COX-2 and phosphorylation of NF-κB p65 subunit induced by CoCl_2 in HaCaT cells. In conclusion, our results demonstrated that oxidative stress mediates chemical hypoxia-induced injur and inflammatory response through activation of NF-κB–COX-2 pathway in HaCaT cells.
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Catalytic hydrogenation of ethyl levulinate into γ-valerolactone over commercial Raney Cu catalyst
Du Yueying,Zhang Chuntao,Li Yang,Zhang Nahui,Ren Dezhang,Huo Zhibao 한국화학공학회 2023 Korean Journal of Chemical Engineering Vol.40 No.8
An eco-friendly green reaction process was developed to achieve efficient hydrogenation of ethyl levulinate (EL) to γ-valerolactone (GVL) over commercial-available Raney Cu catalyst with H2 as the hydrogen source. Raney Cu presented higher catalytic activity among a series of Cu based and Raney type catalysts. The maximum yield of GVL was 98.3% at 160 °C for 3 h. It was found that Raney Cu had great reusability and could be used at least three times without loss of activity. Moreover, the results of XRD, XPS and ICP confirmed the high stability of the catalyst. A possible reaction pathway was also proposed. Ethanol was the main byproduct in this reaction; this study therefore provides a green and efficient method for the conversion of EL to GVL.
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Prediction of Power Generation in China Using Process Neural Network
Jianghua Ge,Jiwei Wen,Chuntao Zhang,Yaping Wang,Gang Ding 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.5
The power generation prediction problem can be seen as a time series prediction problem in nature. The traditional time series prediction methods based on regression analysis do not take account into the time accumulation effect existed in the time series due to their discrete input values. This limitation causes the low prediction accuracy of the time series prediction methods based on regression analysis. To solve this problem, a power generation time series prediction model based on the process neural network is proposed. The inputs of the proposed prediction model can be continuous time-varying functions. The time accumulation effect existed in the power generation time series can be expressed and computed by the integration operator of the process neural network. The proposed prediction model is trained and the efficiency of the proposed prediction model is tested by the month power generation data form January 2001 to April 2012, and the comparison experiment results indicate that the process neural network performs better than the auto regression analysis.
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