目的筛选脑泰方主要有效成分,预测其活性成分干预脑梗死的靶点及通路,对比脑梗死有效靶点及涉及的通路,探究脑泰方干预脑梗死的作用机制。方法采用检索中药系统药理学技术平台(traditional Chinese medicine systems pharmacology datab...目的筛选脑泰方主要有效成分,预测其活性成分干预脑梗死的靶点及通路,对比脑梗死有效靶点及涉及的通路,探究脑泰方干预脑梗死的作用机制。方法采用检索中药系统药理学技术平台(traditional Chinese medicine systems pharmacology database and analysis platform,TCMSP)、台湾中医药资料数据库以及文献资料筛选出脑泰方的主要有效成分,利用其活性成分基于Pubchem数据库和Swiss Target Prediction数据库预测脑泰方有效成分的作用靶点,利用TTD数据库检索出脑梗死涉及的靶点,通过生物学信息注释数据库(DAVID)预测分析相应靶点涉及的通路;然后对比不同途径获得的靶点及通路。结果脑泰方中有40个活性成分,预测得到靶点254个,预测到相关信号通路46条;疾病涉及的靶点26个,相关信号通路6条;其中药物活性成分预测的通路与疾病涉及的通路重合的有5条。结论通过数据对比分析可知,脑泰方干预脑梗死可能是通过调节补体和凝血级联通路、钙离子信号通路、肌动蛋白细胞骨架通路等多途径发挥作用,为进一步阐明脑泰方干预脑梗死具体的作用机制提供了重要参考。展开更多
目的通过网络药理学与分子对接方法探讨半夏-附子同方配伍拮抗冠心病的分子机制。方法基于TCMSP、DisGeNET和OMIM等多个数据库查询半夏-附子药对活性成分和冠心病相关靶点。采用STRING数据库构建半夏-附子药对活性成分拮抗冠心病相关靶...目的通过网络药理学与分子对接方法探讨半夏-附子同方配伍拮抗冠心病的分子机制。方法基于TCMSP、DisGeNET和OMIM等多个数据库查询半夏-附子药对活性成分和冠心病相关靶点。采用STRING数据库构建半夏-附子药对活性成分拮抗冠心病相关靶点PPI网络,运用Cytoscape3.7.1软件构建“半夏-附子药对活性成分-冠心病-靶点-通络”网络,随后使用R语言脚本进行GO和KEGG通路富集分析,最后进行分子对接验证。结果半夏-附子药对活性成分16个,与半夏-附子同方配伍拮抗冠心病的相关靶点有35个,35个靶点富集在57个GO term上,同时富集在75条KEGG信号转导通路上;KEGG富集P值最显著的信号转导通路为Lipid and atherosclerosis;进一步分析提示了,半夏-附子药对活性成分拮抗冠心病的核心靶点可能为AKT1、FOS、MMP9和PTGS2,其关键有效成分为baicalein、cavidine和deltoin。结论本研究初步揭示了半夏-附子药对活性成分通过调控Lipid and atherosclerosis信号转导通路而拮抗冠心病,为半夏-附子药对抗冠心病的物质基础及分子机制的进一步研究奠定了理论基础。展开更多
In many Chinese cities,motorized vehicles (M-vehicles) move slowly at intersections due to the interference of a large number of non-motorized vehicles (NM-vehicles).The slow movement makes a part of M-vehicles fa...In many Chinese cities,motorized vehicles (M-vehicles) move slowly at intersections due to the interference of a large number of non-motorized vehicles (NM-vehicles).The slow movement makes a part of M-vehicles fail to leave intersections timely after the traffic signal tums red,and thereby conflicts between vehicles from two directions occur.The phenomenon was analyzed graphically by using the cumulative vehicle curve.Delays in three cases were modeled and compared:NM-vehicle priorities and M-vehicle priorities with all-red intervals unable to release all vehicles,and longer all-red intervals ensuring release all vehicles.Marginal delays caused by two illegal behaviors that occasionally happened in mixed traffic intersections were also investigated.It is concluded that increasing the speed of M-vehicles leaving intersections and postponing the entering of NM-vehicles are the keys in mathematics,although they are uneasy in disordered mixed traffic intersections due to a dilemma between efficiency and orders in reality.The results could provide implications for the traffic management in the cities maintaining a large number of M-and NM-vehicles.展开更多
文摘目的筛选脑泰方主要有效成分,预测其活性成分干预脑梗死的靶点及通路,对比脑梗死有效靶点及涉及的通路,探究脑泰方干预脑梗死的作用机制。方法采用检索中药系统药理学技术平台(traditional Chinese medicine systems pharmacology database and analysis platform,TCMSP)、台湾中医药资料数据库以及文献资料筛选出脑泰方的主要有效成分,利用其活性成分基于Pubchem数据库和Swiss Target Prediction数据库预测脑泰方有效成分的作用靶点,利用TTD数据库检索出脑梗死涉及的靶点,通过生物学信息注释数据库(DAVID)预测分析相应靶点涉及的通路;然后对比不同途径获得的靶点及通路。结果脑泰方中有40个活性成分,预测得到靶点254个,预测到相关信号通路46条;疾病涉及的靶点26个,相关信号通路6条;其中药物活性成分预测的通路与疾病涉及的通路重合的有5条。结论通过数据对比分析可知,脑泰方干预脑梗死可能是通过调节补体和凝血级联通路、钙离子信号通路、肌动蛋白细胞骨架通路等多途径发挥作用,为进一步阐明脑泰方干预脑梗死具体的作用机制提供了重要参考。
文摘目的通过网络药理学与分子对接方法探讨半夏-附子同方配伍拮抗冠心病的分子机制。方法基于TCMSP、DisGeNET和OMIM等多个数据库查询半夏-附子药对活性成分和冠心病相关靶点。采用STRING数据库构建半夏-附子药对活性成分拮抗冠心病相关靶点PPI网络,运用Cytoscape3.7.1软件构建“半夏-附子药对活性成分-冠心病-靶点-通络”网络,随后使用R语言脚本进行GO和KEGG通路富集分析,最后进行分子对接验证。结果半夏-附子药对活性成分16个,与半夏-附子同方配伍拮抗冠心病的相关靶点有35个,35个靶点富集在57个GO term上,同时富集在75条KEGG信号转导通路上;KEGG富集P值最显著的信号转导通路为Lipid and atherosclerosis;进一步分析提示了,半夏-附子药对活性成分拮抗冠心病的核心靶点可能为AKT1、FOS、MMP9和PTGS2,其关键有效成分为baicalein、cavidine和deltoin。结论本研究初步揭示了半夏-附子药对活性成分通过调控Lipid and atherosclerosis信号转导通路而拮抗冠心病,为半夏-附子药对抗冠心病的物质基础及分子机制的进一步研究奠定了理论基础。
基金Project(2012CB725403)supported by the National Key Research Program of ChinaProject(71131001)supported by the National Natural Science Foundation of ChinaProject(2012JBM064)supported by the Fundamental Research Funds for the Central Universities of China
文摘In many Chinese cities,motorized vehicles (M-vehicles) move slowly at intersections due to the interference of a large number of non-motorized vehicles (NM-vehicles).The slow movement makes a part of M-vehicles fail to leave intersections timely after the traffic signal tums red,and thereby conflicts between vehicles from two directions occur.The phenomenon was analyzed graphically by using the cumulative vehicle curve.Delays in three cases were modeled and compared:NM-vehicle priorities and M-vehicle priorities with all-red intervals unable to release all vehicles,and longer all-red intervals ensuring release all vehicles.Marginal delays caused by two illegal behaviors that occasionally happened in mixed traffic intersections were also investigated.It is concluded that increasing the speed of M-vehicles leaving intersections and postponing the entering of NM-vehicles are the keys in mathematics,although they are uneasy in disordered mixed traffic intersections due to a dilemma between efficiency and orders in reality.The results could provide implications for the traffic management in the cities maintaining a large number of M-and NM-vehicles.