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Analysis Of The HPLC Fingerprint And Grey Relational Analysis Of Antilithic Effects Of Pyrrosia Species

Posted on:2018-12-06Degree:MasterType:Thesis
Country:ChinaCandidate:L L CuiFull Text:PDF
GTID:2334330518997118Subject:Pharmacy
Abstract/Summary:PDF Full Text Request
Objective:An effective and comprehensive evaluation method for identifying the origin and assessing the quality of Pyrrosiae Folium has been established,based on analysis of high performance liquid chromatography(HPLC)fingerprint combined with the similarity analysis,hierarchical cluster analysis(HCA),principal component analysis(PCA)and the quantitative analysis multi-components by single marker(QAMS)method.Spectrum-effect relationships has been explored between HPLC fingerprints and parameter ingredients of optimizing extracts of antilithic effects of Pyrrosia petiolosa for efficacy evaluation of Traditional Chinese Medicines(TCMs).Methods and results:Firstly,20 peaks of the common model were collected and used by establishing HPLC fingerprint from 42 Pyrrosia species.The data were analyzed and evaluated by professional software named Similarity Evaluation System for chromatographic fingerprint of TCMs(Version 2004 A)recommended by the SFDA of China for evaluating similarities and SPSS 19.0 statistical analysis software for HCA and PCA.In addition,QAMS method was compared with the external standard method(ESM),to demonstrate the feasibility and stability by the values of relative correction factors(RCFs)from chlorogenic acid(the internal standard)versus mangiferin,rutin and kaempferol.In results,HPLC fingerprint combined with the similarity analysis,HCA,PCA and QAMS method were successfully applied to identification of the herbs origin and evaluation the quality of Pyrrosia materials.When QAMS method was compared with the external standard method(ESM),it was feasible to evaluate the quality of Pyrrosia herbals.Secondly,antilithic effects was researched of Pyrrosia petiolosa using the rat's model of CaOx kidney stone was induced orally by administration of 1 %(v/v)ethylene glycol in drinking water and filling the stomach with 2 %(w/v)ammonium chloride.EDTA complexometric method and potassium chromate oxidating methyl red method are used for detecting the contents of calcium(Ca2+),magnesium(Mg2+)and oxalate from calcium oxalate crystallization,respectively.Extracts of anti-urolithic effects of Pyrrosia petiolosa were optimized using the rats,which provide theoretical and experimental basis for the further development and utilization of Pyrrosia petiolosa in the future.The results showed that it is successful to induce the formation of urinary stones using 1% ethylene glycol and 2% ammonium chloride,and the extracts of water can effectively reduce the concentration of calcium(Ca2+),thus inhibiting the formation of CaOx kidney stone.Additionally,spectrum-effect relationship was established between the HPLC fingerprint and pharmacodynamics,based on optimizing the pharmacodynamics of urinary calculus using extracts of Pyrrosia petiolosa.The grey relational analysis(GRA)model was established by the correlation between the contents of Ca2+,Mg2+ and Ox from the rat's calcium oxalate crystallization and the area values of 74 peaks which were obtained by establishing HPLC fingerprinting of water extracts of 10 Pyrrosia petiolosa.Simultaneously,the mainly ordinary multiple linear regression(OMLR)was used to verify the feasibility of the GRA.The results showed that the component(peak 43)was found to make a significant contribution to the urinary calculi using the GRA and OMLR.Conclusion:A significant scientific basis had been provided with HPLC fingerprint combined with the similarity analysis,HCA,PCA and QAMS method,which were applied to identification and evaluation of the quality of Pyrrosia materials.In addition,that the pharmacodynamics of urinary calculus combined with HPLC fingerprint of Pyrrosia are promising in the widely used “spectrum-effect relationship”.
Keywords/Search Tags:Pyrrosia, HPLC, Chemical pattern recognition, QAMS, Spectrum-effect relationship
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