目的:探讨XMU-MP-1(Xiamen University-inhibitor of mammalian sterile 20-like kinase protein 1)对氧糖剥夺(OGD)损伤后小胶质细胞M1/M2极化平衡的调节作用。方法采用OGD法诱导BV2细胞损伤。实验分为6组:对照组、模型组、MST1/2 siRN...目的:探讨XMU-MP-1(Xiamen University-inhibitor of mammalian sterile 20-like kinase protein 1)对氧糖剥夺(OGD)损伤后小胶质细胞M1/M2极化平衡的调节作用。方法采用OGD法诱导BV2细胞损伤。实验分为6组:对照组、模型组、MST1/2 siRNA组和低、中、高剂量实验组(分别给予1.25、5.0和20.0μg·mL^(-1) XMU-MP-1)。采用MTT法测细胞活力,ELISA测细胞上清液中TNF-α、IL-6和IL-1β表达,qRT-PCR测M1和M2标志物的mRNA表达,流式细胞术测CD206表达,蛋白印迹法测MST1、LATS1和YAP蛋白表达。结果与模型组相比,XMU-MP-1抑制BV2细胞增殖,显著降低TNF-α、IL-6和IL-1β的表达水平,下调MCP-1、IL-6、TNF-α和i NOS mRNA的表达,上调CD206、IL-10、TGF-β、IL-10和YM1 mRNA表达,降低MST1和LAST 1蛋白表达,上调YAP和CD206表达。结论XMU-MP-1通过调控MST1/2的磷酸化,调节OGD损伤后的BV2细胞M1/M2极化平衡,为神经炎症靶点药物研发提供理论基础。展开更多
Path-based clustering algorithms typically generate clusters by optimizing a benchmark function.Most optimiza-tion methods in clustering algorithms often offer solutions close to the general optimal value.This study a...Path-based clustering algorithms typically generate clusters by optimizing a benchmark function.Most optimiza-tion methods in clustering algorithms often offer solutions close to the general optimal value.This study achieves the global optimum value for the criterion function in a shorter time using the minimax distance,Maximum Spanning Tree“MST”,and meta-heuristic algorithms,including Genetic Algorithm“GA”and Particle Swarm Optimization“PSO”.The Fast Path-based Clustering“FPC”algorithm proposed in this paper can find cluster centers correctly in most datasets and quickly perform clustering operations.The FPC does this operation using MST,the minimax distance,and a new hybrid meta-heuristic algorithm in a few rounds of algorithm iterations.This algorithm can achieve the global optimal value,and the main clustering process of the algorithm has a computational complexity of O�k2×n�.However,due to the complexity of the minimum distance algorithm,the total computational complexity is O�n2�.Experimental results of FPC on synthetic datasets with arbitrary shapes demonstrate that the algorithm is resistant to noise and outliers and can correctly identify clusters of varying sizes and numbers.In addition,the FPC requires the number of clusters as the only parameter to perform the clustering process.A comparative analysis of FPC and other clustering algorithms in this domain indicates that FPC exhibits superior speed,stability,and performance.展开更多
文摘目的:探讨XMU-MP-1(Xiamen University-inhibitor of mammalian sterile 20-like kinase protein 1)对氧糖剥夺(OGD)损伤后小胶质细胞M1/M2极化平衡的调节作用。方法采用OGD法诱导BV2细胞损伤。实验分为6组:对照组、模型组、MST1/2 siRNA组和低、中、高剂量实验组(分别给予1.25、5.0和20.0μg·mL^(-1) XMU-MP-1)。采用MTT法测细胞活力,ELISA测细胞上清液中TNF-α、IL-6和IL-1β表达,qRT-PCR测M1和M2标志物的mRNA表达,流式细胞术测CD206表达,蛋白印迹法测MST1、LATS1和YAP蛋白表达。结果与模型组相比,XMU-MP-1抑制BV2细胞增殖,显著降低TNF-α、IL-6和IL-1β的表达水平,下调MCP-1、IL-6、TNF-α和i NOS mRNA的表达,上调CD206、IL-10、TGF-β、IL-10和YM1 mRNA表达,降低MST1和LAST 1蛋白表达,上调YAP和CD206表达。结论XMU-MP-1通过调控MST1/2的磷酸化,调节OGD损伤后的BV2细胞M1/M2极化平衡,为神经炎症靶点药物研发提供理论基础。
文摘Path-based clustering algorithms typically generate clusters by optimizing a benchmark function.Most optimiza-tion methods in clustering algorithms often offer solutions close to the general optimal value.This study achieves the global optimum value for the criterion function in a shorter time using the minimax distance,Maximum Spanning Tree“MST”,and meta-heuristic algorithms,including Genetic Algorithm“GA”and Particle Swarm Optimization“PSO”.The Fast Path-based Clustering“FPC”algorithm proposed in this paper can find cluster centers correctly in most datasets and quickly perform clustering operations.The FPC does this operation using MST,the minimax distance,and a new hybrid meta-heuristic algorithm in a few rounds of algorithm iterations.This algorithm can achieve the global optimal value,and the main clustering process of the algorithm has a computational complexity of O�k2×n�.However,due to the complexity of the minimum distance algorithm,the total computational complexity is O�n2�.Experimental results of FPC on synthetic datasets with arbitrary shapes demonstrate that the algorithm is resistant to noise and outliers and can correctly identify clusters of varying sizes and numbers.In addition,the FPC requires the number of clusters as the only parameter to perform the clustering process.A comparative analysis of FPC and other clustering algorithms in this domain indicates that FPC exhibits superior speed,stability,and performance.
