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RISS 인기검색어
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- 저자 : Li Chenfeng (검색결과 3 건)
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Setosphapyrone C and D accelerate macrophages cholesterol effl ux by promoting LXRa/ABCA1 pathway
Ting Li,Jiayu Yin,Yubin Ji,Ping Lin,Yanjie Li,Zixun Yang,Shumei Hu,Jin Wang,Baihui Zhang,Saloni Koshti,Junfeng Wang,Chenfeng Ji,Shoudong Guo 대한약학회 2020 Archives of Pharmacal Research Vol.43 No.8
LXRα agonists have attracted signifi cant attentiondue to their potential biological activities on promotingcholesterol effl ux. This study was designed to investigatewhether setosphapyrone C and D have potential lipid-loweringcapacity and the underlying mechanisms in vitro. Ourdata showed that setosphapyrone C and D had weak cytotoxicitycompared to the liver X receptor α (LXRα) agonistT0901317. In RAW 264.7 macrophages, setosphapyroneC and D signifi cantly enhanced [ 3 H]-cholesterol effl ux by~ 21.3% and 32.4%, respectively; furthermore, setosphapyroneC and D enhanced the protein levels of ATP-bindingcassette transporter (ABC) A1 and LXRα by 58% and 69%,and 60% and 70% (8 μM), respectively; however, they had noeff ect on the protein levels of ABCG1 and scavenger receptorB type 1; additionally, they had minor eff ect on the mRNAexpression of lipogenic genes. Of note, setosphapyrone C and D signifi cantly enhanced LXRα/ABCA1pathway inmice primary macrophages. In BRL cells, setosphapyroneC and D signifi cantly improved the protein levels of ABCA1and ABCG1; setosphapyrone D signifi cantly enhanced theprotein expression of low-density lipoprotein. Collectively,setosphapyrone C and D with weak cytotoxicity exhibitedeff ective lipid-lowering eff ect via enhancing LXRα/ABCpathways. Setosphapyrones possess potential applicationfor the treatment of hyperlipidemic diseases.
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Effect of welding defects on mechanical properties of welded joints subjected to temperature
Min Yan,Zhen Guo,Chenfeng Li,Yi Liu,Xiangren Wang 국제구조공학회 2021 Steel and Composite Structures, An International J Vol.40 No.2
Welding defects negatively affect the safety of steel structures. In fire, the steel connections with welding defects would fracture prematurely that cause the structure lose their fire resistance. However, the knowledge of effects of welding defects on welding connections at elevated temperature are still limit. This paper conducted steady-state tensile tests on butt welded specimens with artificial defects to investigate the effect of defects on the mechanical properties of butt welding at high temperatures. These effects on the evolution law of stress and strain, fracture strengths and extension abilities were discussed. The results show that the stress concentration caused by the defects in the welding zone reduced the yield strengths of the weldments at high-temperature, and the stress concentration induced brittle fracture occurring at the welding zone at high temperature with low levels and produced different failure modes. The extension abilities of the weldments at different temperatures were influenced by the defect levels significantly.
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Wang Qiang,Yu Pengyao,Lv Mingdong,Wu Xiangcheng,Li Chenfeng,Chang Xin,Wu Lihong 대한조선학회 2024 International Journal of Naval Architecture and Oc Vol.16 No.-
Real-time acquisition of wave-induced hull girder loads of a sailing ship will help the captain make reasonable decisions, which is of great significance for improving the safety of the ship’s navigation. This paper investigates the real-time prediction method of hull girder loads based on the Recurrent Neural Network (RNN) model and error correction strategy. Firstly, taking the vertical bending moment, horizontal bending moment, and torsional moment at the mid-ship position of a large container ship as examples, corresponding neural network prediction models are established through parameter influence analysis. Secondly, various sea state conditions are used to verify the feasibility of established network prediction models to predict the hull girder loads in real-time. The VBM prediction model performs better than the TM prediction model and HBM prediction model, and the errors of the TM prediction model and HBM prediction model are slightly larger in some cases. Lastly, an improved prediction model based on an error correction strategy is proposed to improve the prediction accuracy of the neural network prediction model, and the adequate performance of the error correction strategy is discussed.
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