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Table of Contents
ORIGINAL ARTICLE
Year : 2021  |  Volume : 7  |  Issue : 1  |  Page : 54-62

Comprehensive quality evaluation of shuxuening injection employing quantitative high-performance liquid chromatography fingerprint and chemometrics


1 Chinese Medicine Science Center, Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
2 TCM Standardization Technology Research Group, DICP-CMC Innovation Institute of Medicine, Taizhou 225300, China
3 HeiLongJiang ZBD Pharmaceutical Co., Ltd, Heilongjian, 158400, China
4 Chinese Medicine Science Center, Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023; TCM Standardization Technology Research Group, DICP.CMC Innovation Institute of Medicine, Taizhou 225300, China

Date of Submission01-May-2020
Date of Acceptance18-Nov-2020
Date of Web Publication8-Mar-2021

Correspondence Address:
Prof. Yan-Fang Liu
Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116 023; DICP-CMC Innovation Institute of Medicine, Taizhou 225 300
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/wjtcm.wjtcm_8_21

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  Abstract 


Objective: In this study, a comprehensive and effective quality method for evaluating the efficacy of ShuXueNing injection (SXNI) was developed. Materials and Methods: Quantitative high-performance liquid chromatography fingerprint, the quantitative analysis of multicomponents by a single marker (QAMS) method, hierarchical cluster analysis (HCA), and orthogonal partial least squares discrimination analysis (OPLS-DA) were used to distinguish 53 batches of SXNI samples from 7 manufacturers. Results: A total of 53 batches of samples were analyzed to establish antithesis fingerprint of SXNI, and 12 peaks of the common model were collected and used for the similarity analysis. Meanwhile, six index flavonoid components were determined by the QAMS method, using rutin as internal reference substance. The accuracy of the QAMS method was confirmed by investigating the relative deviation between the QAMS method and the traditional external standard method. The results demonstrated that there was no significant difference (RE < 1%), suggesting that QAMS was a reliable and convenient method for the content determination of multiple components. The HCA and OPLS-DA methods drew a similar conclusion. The 53 batches of SXNI samples from 7 manufacturers were categorized into five groups, indicating that chemometrics could reveal the quality differences of SXNI between the manufacturers. Conclusions: The method established herein was efficient and successful in assessing the quality of SXNI, and that it may be potentially employed in the quality control of related products composed of Ginkgo biloba extract.

Keywords: Chemometrics, quantitative analysis of multicomponents by a single marker, quantitative high-performance liquid chromatography fingerprint, ShuXueNing injection


How to cite this article:
Zhang Y, Xu X, Qi HW, Liu YC, Dong JT, Xi GC, Jin HL, Liu YF, Liang XM. Comprehensive quality evaluation of shuxuening injection employing quantitative high-performance liquid chromatography fingerprint and chemometrics. World J Tradit Chin Med 2021;7:54-62

How to cite this URL:
Zhang Y, Xu X, Qi HW, Liu YC, Dong JT, Xi GC, Jin HL, Liu YF, Liang XM. Comprehensive quality evaluation of shuxuening injection employing quantitative high-performance liquid chromatography fingerprint and chemometrics. World J Tradit Chin Med [serial online] 2021 [cited 2021 Apr 21];7:54-62. Available from: https://www.wjtcm.net/text.asp?2021/7/1/54/310930




  Introduction Top


ShuXueNing injection (SXNI), which is one of the most popular herbal medicine injections made of Ginkgo biloba, has been widely used in the treatment of cardiovascular and cerebrovascular diseases.[1],[2] Due to its high medicinal value, SXNI is among the most extensively used natural plant medicines; extensive research is going on the production of SXNI, and it is undergoing clinical trials in China.[3] However, quality problems in injections have occurred frequently in recent years, and sales have dropped sharply. The quality evaluation and control of SXNI have attracted increasing attention.

The chemical constituents of SXNI include flavonoids as index components, as well as terpene trilactones and some hydrophilic compounds.[4] The currently used method for determining the flavonoid content in SXNI involves the calculation of the total flavonol glycoside content based on the aglycone concentration after acid hydrolysis. Quantitation of total flavonoid content in SXNI cannot provide any information regarding the composition of the individual flavonoids, which leads to the possibility of adulteration. Recently, several reports on SXNI fingerprints have been released to achieve quality control of flavonoids.[3],[4],[5] The Chinese Pharmacopoeia Commission published a standard fingerprint of SXNI, which contains 17 flavonoid peaks and can provide an overall view of all the index components in SXNI.[6] Fingerprint analysis is a type of qualitative analysis that can reflect the general characteristics of the contents, but there are still some deficiencies in revealing internal quality. Recently, quantitative analysis of fingerprints has been introduced as a promising method that can better reflect the accuracy. The combination of fingerprint and multicomponent quantification, characterized by integrality and accuracy, has been extensively used for quality control in herbal medicine.[7],[8],[9] As for SXNI, quantitative methods such as quantitative analysis of multicomponents by a single marker (QAMS) are commonly used for quality control.[10] However, there are few reports on the application of both fingerprint and multicomponent quantification in quality assessment of SXNI.

In 2008, our group first proposed a herbal quality control strategy based on quantitative high-performance liquid chromatography (HPLC) fingerprint.[11],[12] This technique is a combination of fingerprint and multi-index component quantitative analysis, which highlights its integrality and accuracy. Thus, quantitative HPLC fingerprint can comprehensively control the quality of herbal medicines.[13],[14] Chemometric is acknowledged as a more effective and objective method for chemical classification and for the evaluation of similarities and differences of herbal medicines.[15],[16] In combination with quantitative HPLC fingerprint, the chemometric analysis method allows us to acquire holistic quality information on herbal medicines and plays an important role in quality evaluation and control of herbal medicines.[17],[18],[19],[20]

In this study, we aimed to develop a potent method to realize the quality evaluation of SXNI from different manufacturers, based on quantitative HPLC fingerprint and chemometric analysis. In addition, considering the problems of lack of references and high costs, the QAMS method was developed. This method was successfully employed to assess the quality of SXNI from different manufacturers, and it may hold promise to be widely applied in the quality control of related products of G. biloba extract.


  Materials and Methods Top


Materials and reagents

Fifty-three batches of SXNI were purchased from seven manufacturers. The detailed information of all tested samples is listed in [Table S1]. Rutin (F1), isorhamnetin-3-O-rutinoside (F3), and kaempferol-3-O-rutinoside (F2) were purchased from the National Institute for the Control of Pharmaceutical and Biological Products (Beijing, China). Clitorin, quercetin-3-O-2″-(6″-p-coumaroyl) glucosylrhamnoside (F5), and kaempferol-3-O-2″-(6″-p-coumaroyl) glucosylrhamnoside (F6) were purchased from Chengdu Manst Biotechnology Co., Ltd. Quercetin-3-O-2'',6''-dirhamnosylglucoside, isorhamnetin-3-O-2'',6''-dirhamnosylglucoside, and kaempferol-3-O-2''-glucorhamnoside (F4) were isolated from Ginkgo leaves in our laboratory. The purities of F1, F2, F3, F4, F5, and F6 were 91.7%, 90.8%, 93.1%, 96.4%, 99.6%, and 99.5%, respectively. Acetonitrile (HPLC grade), formic acid, and phosphoric acid (analytical purity) were purchased from Sigma-Aldrich Co. (St. Louis, MO, USA). Deionized water (18.2 MΩ·cm) was further purified using a Milli-Q system (Millipore, Bedford, MA, USA).



Instrumentation and analytical conditions

Analysis was applied on two different HPLC systems, including (a) Acchrom S6000 series with S6110 Gradient Pump, S6430 Diode Array Detector, S6210 Automatic Sampler, and S6310 Column Constant Temperature System and (b) Waters Alliance e2695 series with 2998 PDA detector and empower workstation.

Chromatographic separation was performed on a Symmetry C18 (4.6 mm × 250 mm, 5 μm, Waters) column. Mobile phase consisted of 0.4% phosphoric acid (A)-acetonitrile (B), gradient elution program was as follows: 0–5 min, 90%→86%A; 5–52 min, 86%→86%A; 52–70 min, 86%→82%A; 70–100 min, 82%→70%A; 100–105 min, 70%→5%A; 105–110 min, 5%A. The flow rate was 0.8 mL/min. The column temperature was set at 40°C and the injection volume at 10 μL. The PDA monitor was at 360 nm.

Preparation of standard solutions

A mixed stock solution containing six reference standards was prepared by accurately dissolving each weighed reference standard in methanol.

The working solutions were prepared by appropriately diluting the stock solutions with methanol, resulting in a range of 20.06–200.63 μg/mL for rutin, 20.13–201.39 μg/mL for kaempferol-3-O-rutinoside, 12.45–124.56 μg/mL for isorhamnetin-3-O-rutinoside, 18.49–184.97 μg/mL for kaempferol-3-O-2″-glucosylrhamnoside, 17.37–173.73 μg/mL for quercetin-3-O-2″-(6″-p-coumaroyl) glucosylrhamnoside, and 10.67–106.76 μg/mL for kaempferol-3-O-2″-(6″-p-coumaroyl) glucosylrhamnoside. All standard solutions were stored in a refrigerator at 4° before use.

Preparation of sample solution

A total of 10 mL of SXNI was steamed in an evaporating dish. The residue was dissolved with methanol and transferred to a 10 mL volumetric flask, then diluted with methanol to the scale, and shaken well. SXN was filtered through a 0.45 μm nylon membrane filter, and then, 10 μL of each solution was injected into the column.

Validation of high-performance liquid chromatography fingerprints

The relative retention time (RRT) relative standard deviation (RSD) of each characteristic peak was <1%, and the relative peak area RSD of the main characteristic peaks was <2%, indicating that the precision of the instrument was good. The RRT RSD of each characteristic peak was <1%, and the relative peak area RSD of the main characteristic peak was <2%, indicating that the test solution had good stability within 24 h. The RRT RSD of each characteristic peak was <1%, and the relative peak area RSD of the main characteristic peak was <2%, indicating that the method had good repeatability.

Principle of quantitative analysis of multicomponents by a single marker

The principle of QAMS method is the same as that of correction factor method, in a certain linear range, the amount of components is proportional to the response of the detector. When the method is established, the internal standard is selected, and the relative correction factors (RCFs) between the internal standard and the other measured components can be determined using the following equation (1) and the contents of other measured components can be calculated using (2). To locate target chromatographic peaks, the RRT has been used as shown in (3):







Where Ak and Am stand for the peak area of the internal standard reference and the other components to be determined, respectively. Ck and Cm represent the concentration of the internal standard reference and the measured component, respectively. RTk is the retention time of internal standard reference while RTm is the retention time of the measured component.

For the robustness tests of QAMS, in view of some factors that may affect the reproducibility of the relative correction factors, a series of experiments were designed, focusing on the effects of different experimental conditions on the reproducibility of the relative correction factors and RRT. The experiment was carried out in the same laboratory using two Acchrom S6000 series and a Waters Alliance e2695 system. The effects of three different batches of Symmetry C18 (4.6 mm × 250 mm, 5 μm, Waters) columns on the RCF of the index components were investigated by an Acchrom S6000 HPLC system. An Acchrom S6000 HPLC system and a Symmetry C18 (4.6 mm × 250 mm, 5 μm, Waters) column were used to investigate the influence of different flow rates (0.6, 0.7, 0.8, 0.9, and 1.0 mL/min) and different column temperatures (38°C, 39°C, 40°C, 41°C, and 42°C) on RCFs.

Data analysis

The data were analyzed and evaluated by Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (TCM) (Chinese Pharmacopoeia Commission, Beijing, China) (Version 2012) which was recommended by the SFDA of China for evaluating similarities of chromatographic profiles of TCM. The similarity among different chromatograms was determined by calculating the correlative coefficient or cosine value of the vectorial angle. The hierarchical cluster analysis (HCA) was carried out by calculating squared Euclidean distance to distinguish preparation of different batches using SPSS 22.0 software (IBM, Armonk, New York, USA). The orthogonal partial least squares discrimination analysis (OPLS-DA) was performed using the SIMCA-P 14.0 software (Umetrics, Umeå, Sweden). At the same time, the relative deviation between the result measured by external standard method (ESM) and QAMS method was calculated and the significant difference was tested.


  Results Top


Chromatograph optimization

Taking into consideration the quantitative and qualitative aspects, the development of quantitative fingerprints method remains a challenge. It is critical to establish a favorable mobile phase system, gradient elution system, and detection wavelength to obtain good separation quality of the numerous target components. To ensure good resolution of the characteristic peaks, flow rate, detection wavelength, column temperature, chromatographic column type, and gradient program were optimized. After optimization, all peaks were dispersed across the chromatogram and separated with satisfactory resolution as well as symmetry factor [Figure 1]. Six flavonoids, including rutin, clitorin, kaempferol-3-O-2''-glucorhamnoside, isorhamnetin-3-O-rutinoside, kaempferol-3-O-rutinoside, quercetin-3-O-2″-(6″-p-coumaroyl) glucosylrhamnoside, and kaempferol-3-O-2″-(6″-p-coumaroyl) glucosylrhamnoside, were selected as the quantitative index compounds, based on our previous purification research and the acquisition of the reference standards.
Figure 1: A chromatogram of SXNI (SI)

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High-performance liquid chromatography fingerprints and similarity analysis

The 53 batches of SXNI samples from 7 different manufacturers were prepared according to Section preparation of sample solution, and 10 μL was injected into the HPLC system according to the chromatographic conditions described under Section preparation of sample solution. Then, the chromatograms were recorded and entered into the Similarity Evaluation System for Chromatographic Fingerprint of TCM (Version 2012).

The similarity of 53 batches of SXNI is shown in [Table 1]. Fingerprint chromatograms of 53 batches of SXNI are shown in [Figure 2], established by extracting the relative times and peak areas (RRTs and RPAs) of 12 characteristic peaks. Reference standards were used to identify the characteristic peaks [Table 2]. As shown in [Table 1], the results of similarity analysis could not clearly reflect the quality differences of SXNI from different manufacturers.
Figure 2: HPLC fingerprints of 53 batches of SXNI

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Table 1: Similarities of 53 batches of ShuXueNing injection

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Table 2: Identification of characteristic peaks

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Furthermore, we specially enlarged the fingerprint of the first 15 min at wavelength of 254 nm [Figure 3] and some organic acid components were determined by mass spectrometry. Interestingly, we found that the difference of chemical composition was significant between manufacturers. In recent years, it has been proposed that acids may also be pharmacodynamic components.[20] This reminded us that for the quality control of SXNI, more attention should be paid to other components besides flavonoids, which was also the focus of our subsequent work.
Figure 3: Comparison of 0-15 minute fingerprints of manufacturers A to G

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Quantitative analysis of multiple components method validation

Linearity

Based on fingerprints, six main index components, including rutin (F1), kaempferol-3-O-rutinoside (F2), isorhamnetin-3-O-rutinoside (F3), kaempferol-3-O-2''-glucorhamnoside (F4), quercetin-3-O-2″-(6″-p-coumaroyl) glucosylrhamnoside (F5), and kaempferol-3-O-2″-(6″-p-coumaroyl) glucosylrhamnoside (F6), were analyzed quantitatively. Six mixed reference solutions with different concentrations were determined by HPLC to construct the reference curve. As shown in [Table 3], good calibration curves of six compounds were obtained, and high correlation coefficient values ( R2 > 0.999) were shown with good linearity at a wide range of concentrations. The limits of detection and the limits of quantification under the present chromatographic conditions were determined based on the response and slope of each regression equation at signal-to-noise ratios (S/N) of 3 and 10, respectively [Table 3].
Table 3: Standard curves, relative correction factors, and relative retention time of six reference components

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Precision, stability, repeatability, and recovery

The same sample solution of 10 μL was injected for six consecutive times to calculate the peak area RSD of six index components. As shown in [Table 4], the RSD values of the six components were <1%, which indicated that the developed method had a good precision.
Table 4: Precision, repeatability, stability, and recovery test results of the high-performance liquid chromatography method

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The stability of the sample solutions was analyzed at 0, 2, 6, 12, 18, and 24 h at room temperature. As shown in [Table 4], the sample solutions were stable for 24 h (RSD ≤1.0%).

To validate the repeatability of the method, six independent samples solutions prepared from the same batch were injected into the HPLC system. As shown in [Table 4], the RSD values of the peak area were <1.0%. The results indicated that the analytical method was reproducible.

Recovery was performed to evaluate the accuracy of the method. SXNI samples from the same batch were evaluated at three concentration levels (low, middle, and high levels) of target standards. Then, the resultant samples were extracted and analyzed using the proposed method, and three experiments were repeated at each level. The results showed that the recoveries of the six components were in the range of 94.91%-'104.53% and RSD values were <2.14%, suggesting that the method was reliable and effective, as shown in [Table 4].

Quantitative analysis of multicomponents by a single marker

Calculation of relative correction factor

Given that the quantitative analysis of multiple components was limited by the high price, limited availability, and poor stability of some of the necessary standards, a QAMS method was performed. We selected cheap, readily available, and chemically stable rutin as an internal reference standard for the quantitative determination of the other five flavonoids. The RCF and RRT values of the other five analytes were calculated at six different concentration levels of mixed standards solution, which are shown in [Table 3].

Robustness tests of quantitative analysis of multicomponents by a single marker

We investigated the influence of different instruments, different columns, and different chromatographic conditions such as flow rate and column temperature on the RCF values, and results are shown in [Table 5]. Their RSDs were ≤5%, indicating that RCFs had good repeatability on different chromatographic systems and conditions.
Table 5: Effects of columns and instruments on relative correction factors and relative retention time

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We also investigated the influence of different instruments and different columns on the RRT values, and results are shown in [Table 5]. The results showed that their RSDs were ≤5% and no interference with other components, which indicated that the RRT could be applied to locate the peak component of the analytes.

Sample analysis

To validate the difference between ESM and QAMS method using RCFs, 53 batches of samples were analyzed [Table 6]. All the values of relative average deviation (RE < 0.01) revealed that there was no significant difference between ESM and QAMS methods of all SXNI samples. In addition, the quantitative results obtained above laid the foundation for the follow-up chemometric research.
Table 6: Quantitative result of 53 batches of ShuXueNing injection from the external standard method and quantitative analysis of multicomponents by a single marker (μg/ml)

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Chemometric method

Hierarchical cluster analysis

The 6 × 53 matrices were obtained from six peak areas of fingerprints of 53 batches of SXNI. The cluster analysis was performed using SPSS 2.0 software. The Euclidean distance was chosen as the measure of the distance between groups. The results are shown in [Figure 4]. S31-S35, S36-S40, S46-S50, and S51-S53 batches of samples from four manufacturers were exactly divided into four categories, which indicated that there were differences in the content of the components in the samples prepared from these four manufacturers. Moreover, the remaining batches were divided into another classification, which means that there was no significant difference between samples from these three manufacturers. From the change of color block, it can be clearly seen that the content of the index components varied greatly between manufacturers, especially the contents of components F4, F5, and F6.
Figure 4: Clustering analysis graph of 53 SXNI samples

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Quantitative fingerprinting combined with chemometric methods could clearly reflect the differences between manufacturers.

Orthogonal partial least squares discrimination analysis

In this study, content of the six markers in 53 batches of samples composed a data matrix with 53 rows and 6 columns, which were used for the OPLS-DA analysis after normalization. As shown in [Figure 5], 53 batches of samples were divided into five groups. The results of OPLS-DA were the same as the results of HCA, which verified the accuracy of the chemometric methods.
Figure 5: Results of OPLS-DA of the 53 SXNI samples

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  Discussion Top


It is important to obtain good resolution of characteristic peaks in developing the quantitative fingerprints method. In this study, flow rate and column temperature were key factors that need to be optimized. The effect of flow rate (from 0.7 to 1.0 mL/min) was evaluated, and it was found that the separation of peak 3, peak 4, and peak 5 improved with a decrease in the flow rate. Considering the separation effect and analysis time, 0.8 mL/min was chosen as the flow rate. The influence of different column temperatures (40°, 45°, and 50°) on the resolution was investigated. As the column temperature increased, the resolution of peak 4 and peak 5 was better. Considering the separation effect on all components, 40 ° was chosen as the column temperature.

As shown in [Figure 6], a full-wavelength scan of 200–400 nm was performed on the sample of SXNI (batch 1) using a PDA detector. The results showed that the detection wavelength at 360 nm could comprehensively reflect the index peaks in the sample, with a better resolution and a more stable baseline. Besides, flavonoids were mostly measured by the UV detector at 360 nm to avoid the interference of nontarget substances,[21],[22] so 360 nm was finally selected as the quantitative detection wavelength of SXNI samples.
Figure 6: The UV spectra of peak-F1, F2, F3, F4, F5 and F6 acquired in the batch-1 sample

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As a combination of fingerprint and multicomponent quantitative analysis, quantitative HPLC fingerprint is a comprehensive and effective technology for the quality control and evaluation of herbal medicine due to its integrality and accuracy. In this work, quantitative HPLC fingerprint of SXNI was performed. Twelve peaks of the common model were collected from 53 batches of samples and were identified using the reference standards. Rutin was chosen as the internal reference substance. The RCF between rutin and other five flavonoids was calculated and investigated using the QAMS method. Meanwhile, the accuracy of the QAMS method was confirmed by comparing the results of that method with those of an ESM. No significant difference between these two methods was observed. The quantitative HPLC fingerprint established in this work was simple and reliable, which can provide a certain reference for the comprehensive quality control of SXNI.

Chemometric was an objective method for the further evaluation. Hierarchical clustering analysis (HCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) were performed to differentiate and classify the samples based on the contents of six index flavonoid compounds. The results of different chemometric analyses were completely consistent with each other, and 53 batches of SXNI from 7 manufacturers could be divided into 7 categories, indicating that there are significant differences in the quality. The combination of the chemometric and quantitative HPLC fingerprint could be a practical tool to identify the differences and contribute to comprehensive estimation of SXNI quality.


  Conclusions Top


The quantitative HPLC fingerprint developed in this work is an effective and convenient method for assessing the quality of SXNI. The HPLC fingerprint could be used as a practical tool for the verification of SXNI. Moreover, the QAMS method was successful in simultaneously quantifying the six index flavonoid components in SXNI by RCFs. When multicomponent quantitative analysis was combined with chemometrics, the quality of SXNIs from seven manufacturers was clearly distinguished by HCA and OPLS-DA methods. As a result, the method established is a feasible and potent approach for the comprehensive quality control of SNXIs, as well as related products of G. biloba extract.

Financial support and sponsorship

This work was supported financially by the Guangxi Science and Technology Research Project (GuiKeAA18242040) and the National Science and Technology Major Project (2018ZX09735-002).

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Luo YH, Xie YM, Yang W, Wang YY, You L, Zhuang Y, et al. Analysis of clinical use of Shuxuening injection in treatment of cerebral infarction based on real world. Chin J Chin Mater Med 2014;39:3499-503.  Back to cited text no. 1
    
2.
Chen J, Xie YM, Yang W, Wang YY, You L, Zhuang Y, et al. Analysis of clinical effects of Shuxuening injection on renal function based on hospital information system data. Chin J Chin Mater Med 2014;39:3599-605.  Back to cited text no. 2
    
3.
Wang JH, Du XW, Zhang XQ, Fu XT. Study on quality evaluation of Shuxuening injection. Clin Med J 2007;5:0026-0019.  Back to cited text no. 3
    
4.
Yu ST, Li J, Guo L, Di CX, Qin XM, Li ZY. Integrated liquid chromatography-mass spectrometry and nuclear magnetic resonance spectra for the comprehensive characterization of various components in the Shuxuening injection. J Chromatogr A 2019;1599:125-35.  Back to cited text no. 4
    
5.
Huang X, Li PL, Liu H, Peng W, Wu Z, Su WW. Quality re-evaluation of extract from Ginkgo biloba leaves injection. Central South Pharm 2016;14:1153-8.  Back to cited text no. 5
    
6.
Chinese Pharmacopoeia Commission. Pharmacopoeia of the People's Republic of China. Beijing, China: Chemical Industry Press; 2015.  Back to cited text no. 6
    
7.
Hu JT, Liu JH, Chen FQ, Liu T, Jiang L. Discrimination of Pericarpium Citri Reticulatae from different species and habitats based on HPLC and chemometric method. Pharm Today 2019;6:296.  Back to cited text no. 7
    
8.
Chen LH, Wu Y, Guan YM, Jin C, Zhu WF, Yang M. Analysis of the high-performance liquid chromatography fingerprints and quantitative analysis of multicomponents by single marker of products of fermented Cordyceps sinensis. J Anal Methods Chem 2018;2018:5943914.  Back to cited text no. 8
    
9.
Li YH, Zhang YM, Zhang ZJ, Hu YP, Cui XM, Xiong Y. Quality evaluation of Gastrodia elata tubers based on HPLC fingerprint analyses and quantitative analysis of multi-components by single marker. Molecules 2019;24:1521.  Back to cited text no. 9
    
10.
Zhao YY, Chen YG, Guo HZ, Fu XT. Chemical constituents of flavonoid glycosides in extract from Ginkgo biloba leaves used for injection. Chin Tradit Herb Drugs 2013;44:2027-34.  Back to cited text no. 10
    
11.
Feng JT, Jin Y, Wang JC, Xiao YS, Liang XM. Development of full-quantified fingerprint for quality control of traditional Chinese medicines. Chin J Chromatogr 2008;26:180-5.  Back to cited text no. 11
    
12.
Liang XM, Feng JT, Jin Y, Guo Z, Xu Q. Prospects of the development of quality control technologies for traditional Chinese medicine. Chin J Chromatogr 2008;26:130-5.  Back to cited text no. 12
    
13.
Zhang H, Li ZH, Fan XH. UPLC fingerprint combined with quantitative analysis of multi-components by single marker for quality assessment of Danshen Injection. Chin J Chin Mater Med 2019;44:3724-31.  Back to cited text no. 13
    
14.
He B, Liu Y, Li CH, Tian J, Yang SY. Quality control of Lonicerae japonicae Flos by multi-marker components quantitative fingerprint. Chin J Pharm Anal 2015;50:1237-42.  Back to cited text no. 14
    
15.
Liu S, Liang YZ, Liu HT. Chemometrics applied to quality control and metabolomics for traditional Chinese medicines. J Chromatogr B 2016;1015-1016:82-91.  Back to cited text no. 15
    
16.
Cui LL, Zhang YY, Shao W, Gao DM. Analysis of the HPLC fingerprint and QAMS from Pyrrosia species. Ind Crops Prod 2016;85:29-37.  Back to cited text no. 16
    
17.
Cui KK, Cao YT, Shao JF, Lu ZY, Wang LH. Quantitative analysis of multicomponents by a single marker and quality evaluation of Venenum bufonis from different geographical origins. Biomed Chromatogr 2019;33:e4555.  Back to cited text no. 17
    
18.
Chen LY, Tang XM, Yang Q, Cheng XX. Quantitative and chemical fingerprint analysis of Desmodium styracifolium by high-performance liquid chromatography combined with chemometrics. J Chromatogr Sci 2019;58:294-302.  Back to cited text no. 18
    
19.
Yi H, Zhou J, Shang XY, Zhao ZH, Peng Q, Zhu MJ, et al. Multi-component analysis of ilex Kudingcha C. J. tseng by a single marker quantification method and chemometric discrimination of HPLC fingerprints. Molecules 2018;23:854.  Back to cited text no. 19
    
20.
Peng Y, Dong MH, Zou J, Liu ZH. Analysis of the HPLC fingerprint and QAMS for Sanhuang gypsum soup. J Anal Methods Chem 2018;2018:5890973.  Back to cited text no. 20
    
21.
Liu XG, Wu SQ, Li P, Yang H. Advancement in the chemical analysis and quality control of flavonoid in Ginkgo biloba. J Pharm Biomed Anal 2015;113:212-25.  Back to cited text no. 21
    
22.
Shi JY, Zou XB, Zhang JW, Mel H, Wang KL, Wang X, et al. Determination of total flavonoids content in fresh Ginkgo biloba leaf with different colors using near infrared spectroscopy. Spectrochim Acta A Mol Biomol Spectrosc 2012;94:271-6.  Back to cited text no. 22
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]



 

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