Analysis of volatile components in herbal pair (HP) herba schizonepetae-ramulus cinnamomi (HS-RC), single herb HS and RC was carried out by gas chromatography-mass spectrometry (GC-MS) data and chemometric resolution ...Analysis of volatile components in herbal pair (HP) herba schizonepetae-ramulus cinnamomi (HS-RC), single herb HS and RC was carried out by gas chromatography-mass spectrometry (GC-MS) data and chemometric resolution method (CRM). The two-dimensional data obtained from GC-MS instruments were resolved into a pure chromatogram and a mass spectrum of each chemical compound by CRM. In total, 47, 61 and 51 chemical components in volatile oil of HS, RC, and HP HS-RC were respectively determined qualitatively and quantitatively, accounting for 90.52%, 88.37%, and 88.72% total contents of volatile oil of HS, RC, and HP HS-RC, respectively. The number of the volatile components of HP HS-RC is almost the addition of that of two single herbs, but their relative contents are changed.展开更多
Objective:To investigate the action mechanism of Rhizoma Atractylodis (Atractylodes lancea (Thunb.) Dc.) and Rhizoma Atractylodis Macrocephalae (Atractylodes macrocephala Koidz.),a two-herb ancient traditional Chinese...Objective:To investigate the action mechanism of Rhizoma Atractylodis (Atractylodes lancea (Thunb.) Dc.) and Rhizoma Atractylodis Macrocephalae (Atractylodes macrocephala Koidz.),a two-herb ancient traditional Chinese medicine used to treat type 2 diabetes mellitus,using molecular docking.Methods:The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was searched for compounds in the two herbs and oral bioavailability and drug-likeness values were used to select compounds.The target proteins were selected based on a survey of the literature and related databases,and three receptors closely related to type 2 diabetes were chosen:insulin receptor,peroxisome proliferator activated receptor and dipeptidyl peptidase-Ⅳ.Molecular docking was performed using the CDocker module in Discovery Studio software.The interactions between targets and ligands were observed and analyzed,including the mode of action.Results:Nineteen compounds from the herbal pair interacted with the insulin receptor,the peroxisome proliferator activated receptor and dipeptidyl peptidase-Ⅳ.Among them,10 compounds bound successfully with all three targets,one compound bound with two targets,and eight compounds bound with one target.According to CDocker Interaction Energy,most compounds from the herbal pair had good binding activities with receptors and nine compounds had even higher scores than those of the original ligands.These data indicate that these compounds may be active in reducing blood glucose levels for the treatment of type 2 diabetes.Conclusion:Multiple compounds in the Rhizoma Atractylodis-Rhizoma Atractylodis Macrocephalae herbal pair can affect multiple human targets related to type 2 diabetes.展开更多
Gas chromatography-mass spectrometry(GC-MS) and the chemometric resolution method(alternative moving window factor analysis,AMWFA) were used for comparative analysis of volatile constituents in herbal pair(HP) flos lo...Gas chromatography-mass spectrometry(GC-MS) and the chemometric resolution method(alternative moving window factor analysis,AMWFA) were used for comparative analysis of volatile constituents in herbal pair(HP) flos lonicerae-caulis lonicerae(FL-CL) and its single herbs.The temperature-programmed retention index(PTRI) was also employed for the identification of compounds.In total,44,39,and 50 volatile chemical components in volatile oil of FL,CL and HP FL-CL were separately determined qualitatively and quantitatively,accounting for 87.22%,94.54% and 90.08% total contents of volatile oil of FL,CL and HP FL-CL,respectively.The results show that there are 32 common volatile constituents between HP FL-CL and single herb FL,33 common volatile constituents between HP FL-CL and single herb CL,and 10 new constituents in the volatile oil of HP FL-CL.展开更多
分析当归及其药对当归—白芍中阿魏酸的含量。采用HPLC-DAD法测定阿魏酸的含量,色谱柱为C18ODS(250 mm×4.6 mm, 5μm);柱温为(35±1)℃;流动相为乙腈—0.085%磷酸溶液;流速为0.9 mL/min;检测波长为322nm;等度洗脱。实验结果表...分析当归及其药对当归—白芍中阿魏酸的含量。采用HPLC-DAD法测定阿魏酸的含量,色谱柱为C18ODS(250 mm×4.6 mm, 5μm);柱温为(35±1)℃;流动相为乙腈—0.085%磷酸溶液;流速为0.9 mL/min;检测波长为322nm;等度洗脱。实验结果表明,当归及其药对当归—白芍检测液中阿魏酸的平均含量分别为25.015、20.975μg/mL,药对中阿魏酸含量下降了16.15%。该方法简便快速,精密度高,重复性好,其结果准确可靠,适用于当归及其药对资源的质量控制。展开更多
Objective:Using Chinese patents in force to investigate the frequency and patterns of Chinese herbal extract combinations claiming to treat heart disease.Methods:Patent documents were retrieved from the official websi...Objective:Using Chinese patents in force to investigate the frequency and patterns of Chinese herbal extract combinations claiming to treat heart disease.Methods:Patent documents were retrieved from the official website of the State Intellectual Property Office of the People’s Republic China.Cluster,frequency,and fuzzy cluster analyses were applied.Results:A high number of patents in force included high-frequency herbs such as Salvia miltiorrhiza,Panax ginseng,and Panax notoginseng,as well as high-frequency herbal families such as Araliaceae,Leguminosae,Labiatae,and Umbelliferae.Herb pairs such as P.ginsengþOphiopogon japonicus,S.miltiorrhizaþDalbergia odorifera,and P.ginsengþSchisandra chinensis are also commonly used,as well as herbal family pairs such as AraliaceaeþLiliaceae,LauraceaeþLeguminosae,and AraliaceaeþSchisandraceae.Traditional treatment principles for preventing and treating heart diseases was most-commonly based on simultaneously treating the liver and heart and treating the lung and spleen secondarily for choosing herbal combinations.Conclusion:Most of the high-frequency Chinese herbs in the patents investigated belong to the high-frequency herbal families,and herb pairs were commonly selected to coincide with the commonly-used herbal family pairs.Low-frequency Chinese herbs were also used,but generally belonged to the high-frequency herbal families,and were therefore similar to the highfrequency herbs in terms of traditional categories of taste and channel entered.The results reflect the use of traditional principles of formula composition,and suggest that these principles may indeed be an effective guide for further research and development of Chinese herbal extract combinations to prevent and treat heart diseases.展开更多
Objective To analyze various herbal combinations in Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》),seeking to identify...Objective To analyze various herbal combinations in Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》),seeking to identify fundamental rules dictating the selection of herbal combinations through probability models and big data technology.Methods A total of 252 formulae were collected from Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》)by ZHANG Zhong-Jing.Formulae were then preprocessed with all herb names standardized.The concepts of candidate herb pair and candidate herb pair probability were proposed to analyze the rules of combinations in classical formulae based on probability statistics.MapReduce parallel computing framework of distributed big data technology was adopted to analyze large data samples combined with inverted index algorithm.Results The results showed that the core herbs were Glycyrrhizae Radix Rhizoma(Gan Cao,甘草),Cinnamomi Ramulus(Gui Zhi,桂枝),Zingiberis Rhizoma Recens(Sheng Jiang,生姜),Jujubae Fructus(Da Zao,大枣),Paeoniae Radix Alba(Bai Shao,白芍),etc.43 high-frequency pairs co-occurring 10 times or above were extracted,and 35 of these combinations were recognized as traditional herb pairs,such as Cinnamomi Ramulus(Gui Zhi,桂枝)-Glycyrrhizae Radix Rhizoma(Gan Cao,甘草),Zingiberis Rhizoma Recens(Sheng Jiang,生姜)-Jujubae Fructus(Da Zao,大枣),and Cinnamomi Ramulus(Gui Zhi,桂枝)-Ginseng Radix Et Rhizoma(Ren Shen,人参).The other 8 pairs of combinations,such as Paeoniae Radix Alba(Bai Shao,白芍)-Zingiberis Rhizoma Recens(Sheng Jiang,生姜),Paeoniae Radix Alba(Bai Shao,白芍)-Jujubae Fructus(Da Zao,大枣),and Zingiberis Rhizoma Recens(Sheng Jiang,生姜)-Ginseng Radix Et Rhizoma(Ren Shen,人参),were not defined traditionally,but in connection with commonly used herbs.Classical formulae took the core herbs as principles,focusing on tonifying deficiency,strengthening the spleen and the stomach,strengthening the healthy Qi,and eliminating pathogenic factors.The compatibility pattern of properties involved was mainly acrid and sweet,which reflected the compatibility laws of benefiting Qi and tonifying Yang,replenishing Qi and nourishing blood,etc.Conclusions The research of classical formulae provides common understanding of some basic rules that have been adopted to tackle common illnesses/diseases using herbal medicine.The results help to reinforce theoretical understanding and development of traditional Chinese medicine(TCM),and revealing the hidden rules of combination in TCM data.Analyzing wider data samples of various herbal combinations through computation and big data technology can further optimize the use of TCM.展开更多
搭配刚推出的那一大堆笔电,HP同时发表了一大票的配件。这当中最值得一提的,是全球第一只配备NFC能力的鼠标Touch to Pair Mouse。如同名字的说明,只要将鼠标点一下要配对的对象,就能完成蓝牙配对的过程。如果你运气不好,计算机没有NFC...搭配刚推出的那一大堆笔电,HP同时发表了一大票的配件。这当中最值得一提的,是全球第一只配备NFC能力的鼠标Touch to Pair Mouse。如同名字的说明,只要将鼠标点一下要配对的对象,就能完成蓝牙配对的过程。如果你运气不好,计算机没有NFC的话,那它也可以当成一只普通的蓝牙鼠标使用,展开更多
基金Project(20235020) supported by the National Natural Science Foundation of China
文摘Analysis of volatile components in herbal pair (HP) herba schizonepetae-ramulus cinnamomi (HS-RC), single herb HS and RC was carried out by gas chromatography-mass spectrometry (GC-MS) data and chemometric resolution method (CRM). The two-dimensional data obtained from GC-MS instruments were resolved into a pure chromatogram and a mass spectrum of each chemical compound by CRM. In total, 47, 61 and 51 chemical components in volatile oil of HS, RC, and HP HS-RC were respectively determined qualitatively and quantitatively, accounting for 90.52%, 88.37%, and 88.72% total contents of volatile oil of HS, RC, and HP HS-RC, respectively. The number of the volatile components of HP HS-RC is almost the addition of that of two single herbs, but their relative contents are changed.
基金This study was supported by the National Natural Science Foundation of China(81473800).
文摘Objective:To investigate the action mechanism of Rhizoma Atractylodis (Atractylodes lancea (Thunb.) Dc.) and Rhizoma Atractylodis Macrocephalae (Atractylodes macrocephala Koidz.),a two-herb ancient traditional Chinese medicine used to treat type 2 diabetes mellitus,using molecular docking.Methods:The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was searched for compounds in the two herbs and oral bioavailability and drug-likeness values were used to select compounds.The target proteins were selected based on a survey of the literature and related databases,and three receptors closely related to type 2 diabetes were chosen:insulin receptor,peroxisome proliferator activated receptor and dipeptidyl peptidase-Ⅳ.Molecular docking was performed using the CDocker module in Discovery Studio software.The interactions between targets and ligands were observed and analyzed,including the mode of action.Results:Nineteen compounds from the herbal pair interacted with the insulin receptor,the peroxisome proliferator activated receptor and dipeptidyl peptidase-Ⅳ.Among them,10 compounds bound successfully with all three targets,one compound bound with two targets,and eight compounds bound with one target.According to CDocker Interaction Energy,most compounds from the herbal pair had good binding activities with receptors and nine compounds had even higher scores than those of the original ligands.These data indicate that these compounds may be active in reducing blood glucose levels for the treatment of type 2 diabetes.Conclusion:Multiple compounds in the Rhizoma Atractylodis-Rhizoma Atractylodis Macrocephalae herbal pair can affect multiple human targets related to type 2 diabetes.
基金Project(20976017) supported by the National Natural Science Foundation of China
文摘Gas chromatography-mass spectrometry(GC-MS) and the chemometric resolution method(alternative moving window factor analysis,AMWFA) were used for comparative analysis of volatile constituents in herbal pair(HP) flos lonicerae-caulis lonicerae(FL-CL) and its single herbs.The temperature-programmed retention index(PTRI) was also employed for the identification of compounds.In total,44,39,and 50 volatile chemical components in volatile oil of FL,CL and HP FL-CL were separately determined qualitatively and quantitatively,accounting for 87.22%,94.54% and 90.08% total contents of volatile oil of FL,CL and HP FL-CL,respectively.The results show that there are 32 common volatile constituents between HP FL-CL and single herb FL,33 common volatile constituents between HP FL-CL and single herb CL,and 10 new constituents in the volatile oil of HP FL-CL.
文摘分析当归及其药对当归—白芍中阿魏酸的含量。采用HPLC-DAD法测定阿魏酸的含量,色谱柱为C18ODS(250 mm×4.6 mm, 5μm);柱温为(35±1)℃;流动相为乙腈—0.085%磷酸溶液;流速为0.9 mL/min;检测波长为322nm;等度洗脱。实验结果表明,当归及其药对当归—白芍检测液中阿魏酸的平均含量分别为25.015、20.975μg/mL,药对中阿魏酸含量下降了16.15%。该方法简便快速,精密度高,重复性好,其结果准确可靠,适用于当归及其药对资源的质量控制。
文摘Objective:Using Chinese patents in force to investigate the frequency and patterns of Chinese herbal extract combinations claiming to treat heart disease.Methods:Patent documents were retrieved from the official website of the State Intellectual Property Office of the People’s Republic China.Cluster,frequency,and fuzzy cluster analyses were applied.Results:A high number of patents in force included high-frequency herbs such as Salvia miltiorrhiza,Panax ginseng,and Panax notoginseng,as well as high-frequency herbal families such as Araliaceae,Leguminosae,Labiatae,and Umbelliferae.Herb pairs such as P.ginsengþOphiopogon japonicus,S.miltiorrhizaþDalbergia odorifera,and P.ginsengþSchisandra chinensis are also commonly used,as well as herbal family pairs such as AraliaceaeþLiliaceae,LauraceaeþLeguminosae,and AraliaceaeþSchisandraceae.Traditional treatment principles for preventing and treating heart diseases was most-commonly based on simultaneously treating the liver and heart and treating the lung and spleen secondarily for choosing herbal combinations.Conclusion:Most of the high-frequency Chinese herbs in the patents investigated belong to the high-frequency herbal families,and herb pairs were commonly selected to coincide with the commonly-used herbal family pairs.Low-frequency Chinese herbs were also used,but generally belonged to the high-frequency herbal families,and were therefore similar to the highfrequency herbs in terms of traditional categories of taste and channel entered.The results reflect the use of traditional principles of formula composition,and suggest that these principles may indeed be an effective guide for further research and development of Chinese herbal extract combinations to prevent and treat heart diseases.
基金funding support from the Key Technology Research and Development Program from Ministry of Science and Technology of the People’s Republic of China (No. 2017YFC1703306)Key Project of Science and Technology of Hunan Province (No. 2017SK2111)+2 种基金Natural Science Foundation of Hunan Province (No. 2018JJ2301)Scientific Research Foundation of Hunan Provincial Education Department (No. 18A227, No. 18C0380 and No. 18K070)Open Fund for Computer Science and Technology of Hunan University of Chinese Medicine (No. 2018JK04)
文摘Objective To analyze various herbal combinations in Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》),seeking to identify fundamental rules dictating the selection of herbal combinations through probability models and big data technology.Methods A total of 252 formulae were collected from Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》)by ZHANG Zhong-Jing.Formulae were then preprocessed with all herb names standardized.The concepts of candidate herb pair and candidate herb pair probability were proposed to analyze the rules of combinations in classical formulae based on probability statistics.MapReduce parallel computing framework of distributed big data technology was adopted to analyze large data samples combined with inverted index algorithm.Results The results showed that the core herbs were Glycyrrhizae Radix Rhizoma(Gan Cao,甘草),Cinnamomi Ramulus(Gui Zhi,桂枝),Zingiberis Rhizoma Recens(Sheng Jiang,生姜),Jujubae Fructus(Da Zao,大枣),Paeoniae Radix Alba(Bai Shao,白芍),etc.43 high-frequency pairs co-occurring 10 times or above were extracted,and 35 of these combinations were recognized as traditional herb pairs,such as Cinnamomi Ramulus(Gui Zhi,桂枝)-Glycyrrhizae Radix Rhizoma(Gan Cao,甘草),Zingiberis Rhizoma Recens(Sheng Jiang,生姜)-Jujubae Fructus(Da Zao,大枣),and Cinnamomi Ramulus(Gui Zhi,桂枝)-Ginseng Radix Et Rhizoma(Ren Shen,人参).The other 8 pairs of combinations,such as Paeoniae Radix Alba(Bai Shao,白芍)-Zingiberis Rhizoma Recens(Sheng Jiang,生姜),Paeoniae Radix Alba(Bai Shao,白芍)-Jujubae Fructus(Da Zao,大枣),and Zingiberis Rhizoma Recens(Sheng Jiang,生姜)-Ginseng Radix Et Rhizoma(Ren Shen,人参),were not defined traditionally,but in connection with commonly used herbs.Classical formulae took the core herbs as principles,focusing on tonifying deficiency,strengthening the spleen and the stomach,strengthening the healthy Qi,and eliminating pathogenic factors.The compatibility pattern of properties involved was mainly acrid and sweet,which reflected the compatibility laws of benefiting Qi and tonifying Yang,replenishing Qi and nourishing blood,etc.Conclusions The research of classical formulae provides common understanding of some basic rules that have been adopted to tackle common illnesses/diseases using herbal medicine.The results help to reinforce theoretical understanding and development of traditional Chinese medicine(TCM),and revealing the hidden rules of combination in TCM data.Analyzing wider data samples of various herbal combinations through computation and big data technology can further optimize the use of TCM.