
基于主成分分析与偏最小二乘法-判别分析评价苗药四季草颗粒质量
宋伟1,龚元1*,徐玉平2,万旨贤1,旷波1,王磊1,韩忠耀1
(1.黔南民族医学高等专科学校,都匀 558000;2.凯里学院,凯里 556011)
摘要:目的:对苗药四季草颗粒开展主成分分析(PCA)和偏最小二乘法-判别分析(PLS-DA)等化学模式识别分析,为四季草颗粒的质量综合评价提供方法参考。方法:基于课题组前期构建的苗药四季草颗粒的HPLC指纹图谱,应用IBM
SPSS Statistics 25.0软件,通过PCA特征值(λ)和方差贡献率筛选苗药四季草颗粒的主成分。采用12.0.0.0版SIMCA-P+软件,对四季草颗粒开展偏最小二乘法-判别分析(PLS-DA),筛选影响四季草颗粒的关键质量差异性标志物。结果:苗药四季草颗粒主成分分析共得到4个主成分,四个主成分的方差贡献率分别为37.831%、27.242%、15.136%、11.524%,四个主成分累计贡献率达到91.733%。经PLS-DA分析,筛选出了4个变量投影重要性值大于1的共有色谱峰,分别为峰2、峰6(鞣花酸)、峰9(槲皮苷)、峰10(槲皮素)。结论:初步筛选出了四季草颗粒中鞣花酸、槲皮苷、槲皮素等4个质量差异性标志物,可用于四季草颗粒的质量控制。
关键词:四季草颗粒;偏最小二乘法-判别分析;主成分分析;化学计量学;苗药;化学模式识别
Quality
Evaluation of Miao Medicine Sijicaoo Granules Based on Principal Component
Analysis and Partial Least Squares-Discriminant Analysis
SONG Wei1, GONG Yuan1*, XU Yu-ping2, WAN Zhi-xian1, KUANG Bo1, WANG Lei1, HAN Zhong-yao1
(1. Qiannan Medical College for Nationalities, Duyun 558000, China; 2.Kaili University, Kaili 556011, China)
Abstract: Objective: Principal
component analysis (PCA) and partial least squares-discriminant analysis
(PLS-DA) were performed on the Miao medicine Sijicao granules to provide
methodological reference for their comprehensive quality evaluation. Methods:
Based on the HPLC fingerprint of Sijicao granules (a Miao medicine)
established in our previous study, PCA eigenvalues (λ) and variance
contribution rates were used to identify principal components of the granules
using IBM SPSS Statistics 25.0. Subsequently, partial least
squares-discriminant analysis (PLS-DA) was performed on the granules using
SIMCA-P+ version 12.0.0.0 to screen key quality-discriminative markers. Results:
The principal component analysis of Miao medicine Sijicao granules yielded
four principal components. The variance contribution rate of the four principal
components was 37.831%,
27.242%, 15.136%, 11.524%, and the cumulative contribution rate of the six
principal components reached 91.733%. After PLS-DA
analysis, four common chromatographic peaks with variable projection importance
values greater than 1 were screened out, which were peak 2, peak 6 (ellagic
acid), peak 9 (quercitrin) and peak 10 (quercetin). Conclusion: Four
quality difference markers such as ellagic acid, quercitrin and quercetin in Sijicaoo
granules were preliminarily screened out, which could be used for quality
control of Sijicaoo granules.
Key words: Sijicaoo
granules; partial least squares-discriminant analysis; principal component
analysis; chemometrics; Miao Medicine; chemical pattern recognition
四季草颗粒为国家部颁标准收载的苗药,由四季红(头花蓼)、车前草两味药材生产加工而成,临床上主治湿热蕴结所致排尿不畅、小便短赤等疾病[1-2]。
据文献报道,采用高效液相色谱技术,通过构建四季草颗粒指纹图谱,可基于复方中药整体性化学成分,提高苗药四季草颗粒质量控制方法[2]。通过壳聚糖吸附澄清工艺,可对四季草颗粒生产工艺进行优化,为该产品生产工艺改进与生产水平提升提供了试验参考[3]。王爱民等通过薄层层洗技术,对构成四季草颗粒两味药材头花蓼与车前草,建立了理化鉴别方法,并同时系统研究了指标性成分槲皮苷的定量分析检测方法[4]。张家祎等针对四季草颗粒市场营销策略进行了战略性分析,为提高四季草颗粒市场占有率提供了新思路[5]。SHEN Y等基于网络药理学,对四季草颗粒进行了深入探究[6],而关于苗药四季草颗粒主成分分析与偏最小二乘法-判别分析质量评价相关研究,尚未见报道。
近年来,在建立指纹图谱基础上[7-8],通过相似度评价,可考察不同中药、民族药各批次、不同生长期及不同药用部位之间的共性化学信息[9],而采用化学模式识别分析,如偏最小二乘法-判别分析等,可通过各化学成分信息的差异化,挖掘影响中药、民族药质量的关键质量差异性标志物,从而为中药、民族药后期质量标准提升、二次开发等奠定基础[10-14]。
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