Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants h...Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.展开更多
The estimation of oil spill coverage is an important part of monitoring of oil spills at sea.The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills...The estimation of oil spill coverage is an important part of monitoring of oil spills at sea.The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills and the accuracy of estimates of their size.We consider at-sea oil spills with zonal distribution in this paper and improve the traditional independent component analysis algorithm.For each independent component we added two constraint conditions:non-negativity and constant sum.We use priority weighting by higher-order statistics,and then the spectral angle match method to overcome the order nondeterminacy.By these steps,endmembers can be extracted and abundance quantified simultaneously.To examine the coverage of a real oil spill and correct our estimate,a simulation experiment and a real experiment were designed using the algorithm described above.The result indicated that,for the simulation data,the abundance estimation error is 2.52% and minimum root mean square error of the reconstructed image is 0.030 6.We estimated the oil spill rate and area based on eight hyper-spectral remote sensing images collected by an airborne survey of Shandong Changdao in 2011.The total oil spill area was 0.224 km^2,and the oil spill rate was 22.89%.The method we demonstrate in this paper can be used for the automatic monitoring of oil spill coverage rates.It also allows the accurate estimation of the oil spill area.展开更多
Complex systems exist widely,including medicines from natural products,functional foods,and biological samples.The biological activity of complex systems is often the result of the synergistic effect of multiple compo...Complex systems exist widely,including medicines from natural products,functional foods,and biological samples.The biological activity of complex systems is often the result of the synergistic effect of multiple components.In the quality evaluation of complex samples,multicomponent quantitative analysis(MCQA)is usually needed.To overcome the difficulty in obtaining standard products,scholars have proposed achieving MCQA through the“single standard to determine multiple components(SSDMC)”approach.This method has been used in the determination of multicomponent content in natural source drugs and the analysis of impurities in chemical drugs and has been included in the Chinese Pharmacopoeia.Depending on a convenient(ultra)high-performance liquid chromatography method,how can the repeatability and robustness of the MCQA method be improved?How can the chromatography conditions be optimized to improve the number of quantitative components?How can computer software technology be introduced to improve the efficiency of multicomponent analysis(MCA)?These are the key problems that remain to be solved in practical MCQA.First,this review article summarizes the calculation methods of relative correction factors in the SSDMC approach in the past five years,as well as the method robustness and accuracy evaluation.Second,it also summarizes methods to improve peak capacity and quantitative accuracy in MCA,including column selection and twodimensional chromatographic analysis technology.Finally,computer software technologies for predicting chromatographic conditions and analytical parameters are introduced,which provides an idea for intelligent method development in MCA.This paper aims to provide methodological ideas for the improvement of complex system analysis,especially MCQA.展开更多
目的立筋骨草药材超高效液相色谱(UPLC)指纹图谱及5种成分的质量分数测定方法。方法采用UPLC法,采用Agilent Eclipse Plus C_(18)色谱柱(100 mm×2.1 mm,1.8μm),以甲醇和0.1%(φ)磷酸水溶液作为流动相梯度洗脱,流速为0.25 m L/min...目的立筋骨草药材超高效液相色谱(UPLC)指纹图谱及5种成分的质量分数测定方法。方法采用UPLC法,采用Agilent Eclipse Plus C_(18)色谱柱(100 mm×2.1 mm,1.8μm),以甲醇和0.1%(φ)磷酸水溶液作为流动相梯度洗脱,流速为0.25 m L/min,柱温为25℃,检测波长为207 nm。运用相似度评价、聚类分析(hierarchical cluster analy‐sis,HCA)、偏最小二乘法判别分析(orthogonal partial least squares discriminant analysis,OPLS-DA)等化学模式识别方法对指纹图谱进行综合评价。结果建立的筋骨草药材UPLC指纹图谱共标示了10个共有峰,指认了哈巴苷、乙酰哈巴苷、毛蕊花糖苷、木犀草素-7-O-二葡萄糖醛酸苷、木犀草苷5种成分。质量分数测定结果显示,15批筋骨草药材中哈巴苷、乙酰哈巴苷、毛蕊花糖苷、木犀草素-7-O-二葡萄糖醛酸苷、木犀草苷的质量分数范围分别为5.37~18.48、4.64~24.25、0.05~0.35、0.74~2.24、0.68~1.12 mg/g。多批样品指纹图谱相似度均在0.90以上;HCA将样品分为3类,通过OPLS-DA分析结合VIP值(variable importance in the projection,VIP)筛选出影响筋骨草药材质量差异的4种主成分。结论所建立的筋骨草药材指纹图谱及质量分数测定方法重复性高、稳定性好,可用于筋骨草药材的质量控制及评价。展开更多
基金supported by the key project at the central government level:The ability establishment of sustainable use for valuable Chinese medicine resources(Grant number 2060302)the National Natural Science Foundation of China(Grant number 82373982,82173929).
文摘Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.
基金Supported by the National Scientific Research Fund of China(No.31201133)
文摘The estimation of oil spill coverage is an important part of monitoring of oil spills at sea.The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills and the accuracy of estimates of their size.We consider at-sea oil spills with zonal distribution in this paper and improve the traditional independent component analysis algorithm.For each independent component we added two constraint conditions:non-negativity and constant sum.We use priority weighting by higher-order statistics,and then the spectral angle match method to overcome the order nondeterminacy.By these steps,endmembers can be extracted and abundance quantified simultaneously.To examine the coverage of a real oil spill and correct our estimate,a simulation experiment and a real experiment were designed using the algorithm described above.The result indicated that,for the simulation data,the abundance estimation error is 2.52% and minimum root mean square error of the reconstructed image is 0.030 6.We estimated the oil spill rate and area based on eight hyper-spectral remote sensing images collected by an airborne survey of Shandong Changdao in 2011.The total oil spill area was 0.224 km^2,and the oil spill rate was 22.89%.The method we demonstrate in this paper can be used for the automatic monitoring of oil spill coverage rates.It also allows the accurate estimation of the oil spill area.
基金the National Natural Science Foundation of China(Grant No.:81803734)National S&T Major Special Project for New Innovative Drugs Sponsored(Grant No.:2019ZX09201005).
文摘Complex systems exist widely,including medicines from natural products,functional foods,and biological samples.The biological activity of complex systems is often the result of the synergistic effect of multiple components.In the quality evaluation of complex samples,multicomponent quantitative analysis(MCQA)is usually needed.To overcome the difficulty in obtaining standard products,scholars have proposed achieving MCQA through the“single standard to determine multiple components(SSDMC)”approach.This method has been used in the determination of multicomponent content in natural source drugs and the analysis of impurities in chemical drugs and has been included in the Chinese Pharmacopoeia.Depending on a convenient(ultra)high-performance liquid chromatography method,how can the repeatability and robustness of the MCQA method be improved?How can the chromatography conditions be optimized to improve the number of quantitative components?How can computer software technology be introduced to improve the efficiency of multicomponent analysis(MCA)?These are the key problems that remain to be solved in practical MCQA.First,this review article summarizes the calculation methods of relative correction factors in the SSDMC approach in the past five years,as well as the method robustness and accuracy evaluation.Second,it also summarizes methods to improve peak capacity and quantitative accuracy in MCA,including column selection and twodimensional chromatographic analysis technology.Finally,computer software technologies for predicting chromatographic conditions and analytical parameters are introduced,which provides an idea for intelligent method development in MCA.This paper aims to provide methodological ideas for the improvement of complex system analysis,especially MCQA.
文摘目的立筋骨草药材超高效液相色谱(UPLC)指纹图谱及5种成分的质量分数测定方法。方法采用UPLC法,采用Agilent Eclipse Plus C_(18)色谱柱(100 mm×2.1 mm,1.8μm),以甲醇和0.1%(φ)磷酸水溶液作为流动相梯度洗脱,流速为0.25 m L/min,柱温为25℃,检测波长为207 nm。运用相似度评价、聚类分析(hierarchical cluster analy‐sis,HCA)、偏最小二乘法判别分析(orthogonal partial least squares discriminant analysis,OPLS-DA)等化学模式识别方法对指纹图谱进行综合评价。结果建立的筋骨草药材UPLC指纹图谱共标示了10个共有峰,指认了哈巴苷、乙酰哈巴苷、毛蕊花糖苷、木犀草素-7-O-二葡萄糖醛酸苷、木犀草苷5种成分。质量分数测定结果显示,15批筋骨草药材中哈巴苷、乙酰哈巴苷、毛蕊花糖苷、木犀草素-7-O-二葡萄糖醛酸苷、木犀草苷的质量分数范围分别为5.37~18.48、4.64~24.25、0.05~0.35、0.74~2.24、0.68~1.12 mg/g。多批样品指纹图谱相似度均在0.90以上;HCA将样品分为3类,通过OPLS-DA分析结合VIP值(variable importance in the projection,VIP)筛选出影响筋骨草药材质量差异的4种主成分。结论所建立的筋骨草药材指纹图谱及质量分数测定方法重复性高、稳定性好,可用于筋骨草药材的质量控制及评价。
