目的:探讨黄芪甲苷预处理对大鼠肝脏缺血再灌注损伤及自噬的影响。方法:大鼠90只,分别划分成HIRI组、Sham组、干预组,根据再灌注时间分为术后4、8、16 h 3个亚组。HIRI组和干预组均建立肝脏缺血再灌注(I/R)模型。检验谷丙(ALT)及谷草(A...目的:探讨黄芪甲苷预处理对大鼠肝脏缺血再灌注损伤及自噬的影响。方法:大鼠90只,分别划分成HIRI组、Sham组、干预组,根据再灌注时间分为术后4、8、16 h 3个亚组。HIRI组和干预组均建立肝脏缺血再灌注(I/R)模型。检验谷丙(ALT)及谷草(AST)转氨酶的含量;光镜下观察肝细胞及肝小叶等结构的变化;免疫印迹法分析Beclin-1的表达含量;在电镜下寻找肝细胞中自噬小体的数量差异。结果:1)同Sham组比较,HIRI组大鼠血清ALT和AST水平明显升高(P<0.05),于8 h达到顶峰。与HIRI组比较,干预组ALT和AST水平均明显降低(P<0.05);2)病理学结果示HIRI组大鼠肝脏出现了不同程度的损伤,而干预组的肝损伤明显改善;3)Western Blot结果现示,同Sham组比较,HIRI组Beclin-1蛋白灰度比均明显升高(P<0.05),于8 h达到顶峰。与HIRI组比较,干预组Beclin-1蛋白灰度比均明显降低(P<0.05);4)电镜结果示,HIRI组肝细胞中的自噬小体数量较Sham组在术后8 h明显上升(P<0.05);而干预组自噬小体较HIRI组在术后8 h明显减少(P<0.05)。结论:黄芪甲苷预处理可减轻大鼠肝缺血再灌注损伤,其可能的机制之一是通过降低大鼠HIRI时的自噬水平。展开更多
We propose a method to improve positioning accuracy while reducing energy consumption in an indoor Wireless Local Area Network(WLAN) environment.First,we intelligently and jointly select the subset of Access Points(AP...We propose a method to improve positioning accuracy while reducing energy consumption in an indoor Wireless Local Area Network(WLAN) environment.First,we intelligently and jointly select the subset of Access Points(APs) used in positioning via Maximum Mutual Information(MMI) criterion.Second,we propose Orthogonal Locality Preserving Projection(OLPP) to reduce the redundancy among selected APs.OLPP effectively extracts the intrinsic location features in situations where previous linear signal projection techniques failed to do,while maintaining computational efficiency.Third,we show that the combination of AP selection and OLPP simultaneously exploits their complementary advantages while avoiding the drawbacks.Experimental results indicate that,compared with the widely used weighted K-nearest neighbor and maximum likelihood estimation method,the proposed method leads to 21.8%(0.49 m) positioning accuracy improvement,while decreasing the computation cost by 65.4%.展开更多
基金the High-Tech Research and Development Program of China，the National Seience Foundation for Young Scientists of China，the China Postdoctoral Science Foundation funded project
文摘We propose a method to improve positioning accuracy while reducing energy consumption in an indoor Wireless Local Area Network(WLAN) environment.First,we intelligently and jointly select the subset of Access Points(APs) used in positioning via Maximum Mutual Information(MMI) criterion.Second,we propose Orthogonal Locality Preserving Projection(OLPP) to reduce the redundancy among selected APs.OLPP effectively extracts the intrinsic location features in situations where previous linear signal projection techniques failed to do,while maintaining computational efficiency.Third,we show that the combination of AP selection and OLPP simultaneously exploits their complementary advantages while avoiding the drawbacks.Experimental results indicate that,compared with the widely used weighted K-nearest neighbor and maximum likelihood estimation method,the proposed method leads to 21.8%(0.49 m) positioning accuracy improvement,while decreasing the computation cost by 65.4%.
