Kai Xin San is a Chinese herbal formula composed of Radix Ginseng, Poria, Radix Polygalae and Acorus Tatarinowii Rhizome. It has been used in China for many years for treating amnesia. Kai Xin San ameliorates amyloid-...Kai Xin San is a Chinese herbal formula composed of Radix Ginseng, Poria, Radix Polygalae and Acorus Tatarinowii Rhizome. It has been used in China for many years for treating amnesia. Kai Xin San ameliorates amyloid-β （Aβ） induced cognitive dysfunction and is neuroprotective in vivo, but its precise mechanism remains unclear. Expression of insulin-degrading enzyme （IDE）, which degrades Aβ, is strongly correlated with cognitive function. Here, we injected rats with exogenous Aβ42 （200 μM, 5 μL） into the hippocampus and subsequently administered Kai Xin San （0.54 or 1.08 g/kg/d） intragastrically for 21 consecutive days. Hematoxylin eosin and Nissl staining revealed that Kai Xin San protected neurons against Aβ-induced damage. Furthermore, enzyme linked immunosorbent assay, western blot and polymerase chain reaction results showed that Kai Xin San decreased Aβ42 protein levels and increased expression of IDE protein, but not mRNA, in the hippocampus. Our findings reveal that Kai Xin San facilitates hippocampal Aβ degradation and increases IDE expression, which leads, at least in part, to the alleviation of hippocampal neuron injury in rats.展开更多
目的利用层次分析法(analytic hierarchy process,AHP)-自组织映射(self-organizing map,SOM)聚类-逼近理想解排序(technique for order preference by similarity to solution,TOPSIS)算法和中医传承辅助平台(V2.5),对中医药治疗围绝...目的利用层次分析法(analytic hierarchy process,AHP)-自组织映射(self-organizing map,SOM)聚类-逼近理想解排序(technique for order preference by similarity to solution,TOPSIS)算法和中医传承辅助平台(V2.5),对中医药治疗围绝经期抑郁症组方进行数据挖掘研究,并结合中医理论,挖掘治疗围绝经期抑郁症的新组方。同时证明AHP-SOM聚类-TOPSIS算法可以用于临床疾病处方规律挖掘。方法收集中国期刊全文数据库(2000—2021年)中中医治疗围绝经期抑郁症的方剂信息,先后使用关联规则算法(Apriori)、AHP、SOM、TOPSIS等关联、决策和聚类机器学习算法,挖掘其中高频原料药味的配方规律,结合传统中医理论得到可能的新组方,并且使用TOPSIS对新方进行综合评价排名。同时,运用中医传承辅助平台(V2.5)进行组方规律分析,得出新方。结果用药频次分析得到前3位高频药味为柴胡、白芍和甘草,关联规则结果显示高频药味之间产生较强的关联性,排名前3位的药物组合分别为柴胡-白芍、柴胡-甘草、柴胡-茯苓。继而对39个高频药味进行AHP分析和加权后,得到加权值排在前5位的药味为柴胡、白芍、甘草、郁金、半夏,这些药味可以考虑在组方时优先选择。SOM聚类显示所有高频药味可分为7类,其中最优选配方药味与AHP分析结果权重排名前列的药味有极高的重叠。依据传统中医理论中疏肝理气、化痰开窍、活血化瘀等治则进行配伍组合,最终设计了10个可能的配方,并进行TOPSIS分析评价,排名第1的配方为柴胡、酸枣仁、白芍、半夏、郁金、甘草。最后使用中医药传承辅助平台,基于无监督熵层次聚类算法得出2个潜在的核心药组:白芍-麦冬-远志、石菖蒲-柴胡-远志,核心药组再次组合成1个新处方:白芍-麦冬-远志-石菖蒲-柴胡。结论在中医药基本理论的指导下结合各类机器学习算法,分析治疗围绝经期抑郁症的组方规律,设计获得可能的新组方,为临床治疗围绝经期抑郁症提供新思路。展开更多
基金the National Natural Science Foundation of China(8197339)Henan Science Fund for Distinguished Young Scholars(20300410249)Henan Science and Technology Research Project(22102310233).
基金supported by the National Natural Science Foundation of China,No.81303248,81603321the Natural Science Foundation of Heilongjiang Province of China,No.H2015028+1 种基金a grant from the Nursing Program for Young Scholars of Heilongjiang Province of China,No.UNPYSCT-2016116the Scientific Research Fund for Doctors of Qiqihar Medical University in China,No.QY2016B-09
文摘Kai Xin San is a Chinese herbal formula composed of Radix Ginseng, Poria, Radix Polygalae and Acorus Tatarinowii Rhizome. It has been used in China for many years for treating amnesia. Kai Xin San ameliorates amyloid-β （Aβ） induced cognitive dysfunction and is neuroprotective in vivo, but its precise mechanism remains unclear. Expression of insulin-degrading enzyme （IDE）, which degrades Aβ, is strongly correlated with cognitive function. Here, we injected rats with exogenous Aβ42 （200 μM, 5 μL） into the hippocampus and subsequently administered Kai Xin San （0.54 or 1.08 g/kg/d） intragastrically for 21 consecutive days. Hematoxylin eosin and Nissl staining revealed that Kai Xin San protected neurons against Aβ-induced damage. Furthermore, enzyme linked immunosorbent assay, western blot and polymerase chain reaction results showed that Kai Xin San decreased Aβ42 protein levels and increased expression of IDE protein, but not mRNA, in the hippocampus. Our findings reveal that Kai Xin San facilitates hippocampal Aβ degradation and increases IDE expression, which leads, at least in part, to the alleviation of hippocampal neuron injury in rats.
文摘目的利用层次分析法(analytic hierarchy process,AHP)-自组织映射(self-organizing map,SOM)聚类-逼近理想解排序(technique for order preference by similarity to solution,TOPSIS)算法和中医传承辅助平台(V2.5),对中医药治疗围绝经期抑郁症组方进行数据挖掘研究,并结合中医理论,挖掘治疗围绝经期抑郁症的新组方。同时证明AHP-SOM聚类-TOPSIS算法可以用于临床疾病处方规律挖掘。方法收集中国期刊全文数据库(2000—2021年)中中医治疗围绝经期抑郁症的方剂信息,先后使用关联规则算法(Apriori)、AHP、SOM、TOPSIS等关联、决策和聚类机器学习算法,挖掘其中高频原料药味的配方规律,结合传统中医理论得到可能的新组方,并且使用TOPSIS对新方进行综合评价排名。同时,运用中医传承辅助平台(V2.5)进行组方规律分析,得出新方。结果用药频次分析得到前3位高频药味为柴胡、白芍和甘草,关联规则结果显示高频药味之间产生较强的关联性,排名前3位的药物组合分别为柴胡-白芍、柴胡-甘草、柴胡-茯苓。继而对39个高频药味进行AHP分析和加权后,得到加权值排在前5位的药味为柴胡、白芍、甘草、郁金、半夏,这些药味可以考虑在组方时优先选择。SOM聚类显示所有高频药味可分为7类,其中最优选配方药味与AHP分析结果权重排名前列的药味有极高的重叠。依据传统中医理论中疏肝理气、化痰开窍、活血化瘀等治则进行配伍组合,最终设计了10个可能的配方,并进行TOPSIS分析评价,排名第1的配方为柴胡、酸枣仁、白芍、半夏、郁金、甘草。最后使用中医药传承辅助平台,基于无监督熵层次聚类算法得出2个潜在的核心药组:白芍-麦冬-远志、石菖蒲-柴胡-远志,核心药组再次组合成1个新处方:白芍-麦冬-远志-石菖蒲-柴胡。结论在中医药基本理论的指导下结合各类机器学习算法,分析治疗围绝经期抑郁症的组方规律,设计获得可能的新组方,为临床治疗围绝经期抑郁症提供新思路。
