Quality evaluation of WuweiZhenju tablets based on HPLC fingerprint, content determination and chemical pattern recognition analysis

This study established high-performance liquid chromatography(HPLC) fingerprints of Chinese medicines derived from Apocynum venetum and Poacynum pictum in Xinjiang and explored their composition differences with the combination of content determination, similarity analysis, cluster analysis and principal component analysis. The HPLC conditions included Phenomenex Kinetex C_(18) column(4.6 mm ×100 mm, 2.6 μm), acetonitrile-0.01% trifluoroacetic acid aqueous solution as mobile phase, gradient elution, flow rate of 0.6 mL·min~(-1), detection wavelength of 281 nm and column temperature of 25 ℃. The content of chlorogenic acid, quercetin-3-O-sophoroside, rutin, hyperin, isoquercitrin, trifolin and astragalin was determined in 31 batches of medicinal materials, and fingerprint research and chemometric analysis were performed with Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine(Version 2004 A) and SPSS 21.0. In the Chinese Pharmacopoeia 2020, the quality of Apocyni Veneti Folium is controlled by character identification, microscopic identification, thin layer chromatography identification and quantitative determination of hyperin. There were 21 common peaks of A. venetum and P. pictum in the HPLC fingerprints, 5 of which were identified as chlorogenic acid, hyperin, isoquercitrin, trifolin and astragalin, with their content also determined. Except for 3 batches of medicinal materials, the similarity of other 28 batches was higher than 0.83, indicating good similarity. Two categories were formed in the cluster analysis based on content determination, which showed that some differences existed in similarities between different regions of Xinjiang. The medicinal materials were ranked by quality with principal component analysis, and the results indicated that the top 15 all came from northern Xinjiang. The quality difference of A. venetum and P. pictum had a correlation with the place of origin. This study provides a reference for the analysis and evaluation of A. venetum and P. pictum from different habitats and the selection of introduction and cultivation areas.

This work investigated the spectrum-effect relationships between high performance liquid chromatography (HPLC) fingerprints and the anti-benign prostatic hyperplasia activities of aqueous extracts from Saxifraga stolonifera. The fingerprints of S. stolonifera from various sources were established by HPLC and evaluated by similarity analysis (SA), hierarchical clustering analysis (HCA) and principal component analysis (PCA). Nine samples were obtained from these 24 batches of different origins, according to the results of SA, HCA and the common chromatographic peaks area. A testosterone-induced mouse model of benign prostatic hyperplasia (BPH) was used to establish the anti-benign prostatic hyperplasia activities of these nine S. stolonifera samples. The model was evaluated by analyzing prostatic index (PI), serum acid phosphatase (ACP) activity, concentrations of serum dihydrotestosterone (DHT), prostatic acid phosphatase (PACP) and type II 5α-reductase (SRD5A2). The spectrum-effect relationships between HPLC fingerprints and anti-benign prostatic hyperplasia activities were investigated using Grey Correlation Analysis (GRA) and partial least squares regression (PLSR). The results showed that a close correlation existed between the fingerprints and anti-benign prostatic hyperplasia activities, and peak 14 (chlorogenic acid), peak 17 (quercetin 5-O-β-d-glucopyranoside) and peak 18 (quercetin 3-O-β-l-rhamno-pyranoside) in the HPLC fingerprints might be the main active components against anti-benign prostatic hyperplasia. This work provides a general model for the study of spectrum-effect relationships of S. stolonifera by combing HPLC fingerprints with a testosterone-induced mouse model of BPH, which can be employed to discover the principle components of anti-benign prostatic hyperplasia bioactivity.

Fufang Shenqi Oral Liquid (FFSQOL) is an important Chinese medicine compound preparation with a wide range of clinical applications, which is mainly used to regulate immune function, improve cardiovascular function, and have anti-inflammatory and antibacterial effects. At present, it is of great importance to establish the quality evaluation method of FFSQOL and to investigate its quality markers (Q-markers). The aim of this study is to establish a quality evaluation method for FFSQOL and screen its Q-markers to provide a scientific basis for its quality control. Fourteen batches of FFSQOL were subjected to high-performance liquid chromatography (HPLC) fingerprint and similarity analysis. The components of FFSQOL were identified, and their content was determined. This was combined with cluster analysis (CA) and principal component analysis (PCA) to determine the Q-markers of FFSQOL. In this study, an HPLC fingerprint was established for 14 batches of FFSQOL, identifying 12 common peaks and six major components. Four components were identified as stable and reproducible: gallic acid (504.94 ~ 1219.04 μg/mL), caffeic acid (452.15 ~ 783.01 μg/mL), 7-O-glucoside (1097.72 ~ 2440.41 μg/mL), and formononetin (176.2 ~ 177.51 μg/mL). Quality evaluation of the 14 batches was conducted using chemical pattern recognition analysis. CA results indicated two distinct groups, and PCA revealed that principal components 1 and 2 were the main factors influencing batch differences. A combination of HPLC fingerprint, content determination results, and chemical pattern recognition analysis was employed to identify Q-markers for FFSQOL. The markers identified were gallic acid, caffeic acid, calycosin 7-O-glucoside, and formononetin. In this study, a quality evaluation method for FFSQOL was established through the implementation of fingerprint, content determination, and chemical pattern recognition analysis, resulting in the identification of four Q-Markers of FFSQOL, which laid the foundation for the formulation of FFSQOL quality standards.

Lonicerae Japonicae Flos (LJF) is widely used in food and traditional Chinese medicine. To meet demand, Lonicera japonica Thunb. is widely cultivated in many provinces of China. However, reported studies on the quality evaluation of LJF only used a single or a few active components as indicators, which could not fully reflect the quality of LJF. In the present study, we aimed to develop a methodology for comprehensively evaluating the quality of LJF from different origins based on high-performance liquid chromatography (HPLC) fingerprinting and multicomponent quantitative analysis combined with chemical pattern recognition. The HPLC method was developed for fingerprint analysis and was used to determine the contents of 19 components of LJF. To distinguish between samples and identify differential components, similarity analysis, hierarchical cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis were performed. The HPLC fingerprint was established. Using the developed method, the contents of 19 components recognized in the fingerprint analysis were determined. Samples from different origins could be effectively distinguished. HPLC fingerprinting and multicomponent quantitative analysis combined with chemical pattern recognition is an efficient method for evaluating LJF.

To address medication safety concerns from depleted Notopterygium incisum Ting ex H. T. Chang (NI) resources and inconsistent quality, this study employed the Quality Markers (Q-Marker) concept of Traditional Chinese Medicine to screen potential Q-Markers via multi-step compositional transfer analysis and network pharmacology. This study aimed to screen the Q-Markers of NI for treating cardiovascular diseases. An approach integrating mass transfer analysis, network pharmacology, and High Performance Liquid Chromatography (HPLC) fingerprinting was employed. First, HPLC fingerprints of thirteen batches of NI were established. A representative batch was selected to prepare fresh medicinal materials, processed decoction pieces, and standard decoctions. Additionally, blood-absorbed components were collected, and fingerprints for all sample types were established. The transfer rates of seven index components (chlorogenic acid, nodakenin, ferulic acid, psoralen, bergapten, phenethyl ferulate, and isoimperatorin) were determined via similarity evaluation and least squares discriminant analysis. Network pharmacology and molecular docking were further used to analyze the associations between NI's bioactive components and therapeutic targets for cardiovascular diseases. This study employed an integrated approach of HPLC fingerprinting, mass transfer analysis, network pharmacology, and molecular docking. After establishing HPLC fingerprints for thirteen NI batches, a representative batch was processed from fresh herbs, decoction pieces, standard decoctions, and blood-absorbed components for analysis, after which a determination was made for the transfer rates of seven index components and their associations with cardiovascular disease targets. Chlorogenic acid, nodakenin, ferulic acid, phenethyl ferulate, and isoimperatorin are potential Q-Markers of NI for the treatment of cardiovascular diseases. In this study, mass transfer analysis, network pharmacology, and HPLC fingerprinting were integrated, combined with orthogonal partial least squares-discriminant analysis (OPLS-DA) and molecular docking. Potential Q-Markers of NI for the treatment of cardiovascular diseases were identified.

HPLC combined with chemometrics for quality control of Huamoyan Granules or Capsules

Morphological resemblance among Cymbopogon distans species and their adulterants which are procured from different markets in the form of dried or fresh plant tissues represents a serious problem for quality and safety of medicinal plants, as it supports frauds for substitution. In order to assure the quality control of C. distans species, DNA barcode, microscopic identification and High Performance liquid chromatography (HPLC) fingerprint were synergistically used to discriminate C. distans from its adulterants. In this work, the internal transcribed spacer 2 (ITS2) was chosen for distinguishing C. distans from their usual adulterants from 5 provinces of China. Sequences were obtained after removal of the 5.8S and 28S sections. A multiple sequence alignment was finalized. Results exhibited that ITS2 performed well, with 100% of genera being accurately distinguished. Additionally, finding indicates that the upper epidermis in leaf of C. distans was composed of one layer of wide elongated cells called Bulliform cells whereas in C. distans the upper epidermis consist of one layer cell, thus these feactures are very important for the anatomy identification. The HPLC fingerprint method was also developed, the similarities of 6 batches of C. distans samples were all more than 0.93, indicating that the samples from different geographical origins shared similar HPLC fingerprints. And the similarities between C. distans, C. citratus, C. flexuosus and Imperata cylindrica were all less than 0.93, suggesting that there was significance difference between C. distans and its adulterants. Finally, it was concluded that the DNA barcode, HPLC fingerprint and microscopic methods could effectively authenticate the quality of C. distans from their adulterants and can provide accurate and reliable information to tackle the complex quality issue of C. distans in markets. This is the first report of detailed analysis of the C. distans for effective quality and safety.

To establish high performance liquid chromatography(HPLC) fingerprints for crude and processed Ligustri Lucidi Fructus,and to evaluate their quality through the similarity calculation and chemical pattern recognition. The separation was performed with Syncronis C_(18) column(4.6 mm × 250 mm, 5 μm), with acetonitrile(A) and 0.1% phosphoric acid solution(B) as the mobile phase for gradient elution, and a detection wavelength of 280 nm. HPLC was used to detect 22 batches of crude and processed Ligustri Lucidi Fructus,and the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine(2012 Edition) was used to evaluate the similarity among 22 batches. The research on pattern recognition was conducted with cluster analysis(CA), principal component analysis(PCA), and partial least squares discriminate analysis(PLS-DA). HPLC fingerprints of crude and processed Ligustri Lucidi Fructus were established, with similarity ranging from 0.9 to 1.0. The crude and processed Ligustri Lucidi Fructus can be obviously distinguished by using CA, PCA and PLS-DA. According to the results of PLS-DA,11 constituents including hydroxytyrosol, tyrosol, specnuezhenide and oleuropein were the main marker components leading to the difference. The established fingerprint method is stable and reliable, and can provide method basis for quality control of crude and processed Ligustri Lucidi Fructus. Chemical pattern recognition is proved to be helpful in comprehensive quality control and evaluation of Ligustri Lucidi Fructus before and after the process.

Centipeda minima (L.) A. Br. et Aschers, known as Ebushicao (EBSC) in Chinese, has long been used in traditional Chinese medicine for dispelling wind, clearing orifices, detoxification, and swelling. Although the traditional use of EBSC involves the whole plant, during harvesting and processing, separation of the stems, leaves, flowers, and roots often occurs. However, there are few studies on its medicinal parts. A strategy combining high-performance liquid chromatography (HPLC) fingerprinting and multivariate classification techniques are here proposed for the comparison of roots, stems, leaves, and flowers of EBSC. The roots, stems, leaves, and flowers of EBSC samples were analyzed and compared based on HPLC fingerprints combined with chemometrics, including hierarchical cluster analysis (HCA), principal component analysis (PCA), partial least-squares discriminant analysis (PLS-DA), and back propagation artificial neural network (BP-ANN). Chemical markers were screened using PLS-DA, and the contents of representative ingredients were determined by an HPLC method. The HCA and PCA provided clear discrimination of roots, stems, leaves, and flowers. Moreover, the PLS-DA model and BP-ANN were established to verify the classification results and showed a greater ability to predict new samples. Four representative chemical markers were screened out, and the content of these markers in flowers and leaves was higher than that in stems and roots, and the difference was significant. Combining HPLC fingerprinting and multicomponent chemical pattern recognition technology can be used to distinguish different parts of EBSC. The results indicated that brevilin A, quercetin, rutin, and chlorogenic acid, the important active components of EBSC, were mainly present in the leaves and flowers. This is of great significance for the differentiation and identification of the different medicinal parts of EBSC, as well as for the effectiveness of drug usage in clinical practice. HP LC was used to quickly obtain chemical for fingerprint analysis. HCA, P CA, P LS-DA were used to visualize the discrimination of roots, stems, leaves and flowers of EBSC. P LS-DA model was established to verify the classification results and obtained the chemical marker. BP-ANN model was used to further improve the discrimination accuracy.

To establish the high performance liquid chromatography (HPLC) fingerprint for Digeda-4 decoction (DGD-4D), determine the contents of aesculetin, geniposide, picroside Ⅰ, picroside Ⅱ and ellagicacid in DGD-4D, and provide the scientific foundation for quality control of DGD-4D. The analysis was performed on Diamonsil(2) C₁₈ (4.6 mm×250 mm,5 μm) column, with methanol-0.1% phosphoric acid aqueous solution as mobile phase for gradient elution. The flow rate was 1.0 mL·min⁻¹; injection size was 10 μL; temperature was maintained at 30 °C, and the detection wavelength was set at 254 nm. The common mode of DGD-4D HPLC fingerprint was established, and the hidden information was analyzed by Chemometrics. Chromatographic peaks for DGD-4D were identified by HPLC and quantitative analysis was conducted for characteristic peaks. There were 17 common peaks in the fingerprints and the similarity of the fingerprints was over 0.9 in all 15 batches. The samples were broadly divided into four kinds by principal component analysis and clustering analysis. Four marker compounds were verified by partial least squares discriminant analysis, and No. 9, 12 and 14 peaks were identified as geniposide, picroside Ⅱ, and picroside Ⅰ respectively. The average recoveries were in the range of 95.91%-97.31%. The HPLC fingerprint method for content determination is reliable, accurate, rapid, simple, and reproducible, and can be used as one of the effective methods to control the quality of DGD-4D.

Based on ITS sequences, the molecular identification of Cordyceps cicadae and Tolypocladium dujiaolongae was carried out, and high-performance liquid chromatography(HPLC) fingerprint combined with chemical pattern recognition method was established to differentiate C. cicadae from its adulterant T. dujiaolongae. The genomic DNA from 10 batches of C. cicadae and five batches of T. dujiaolongae was extracted, and ITS sequences were amplified by PCR and sequenced. The stable differential sites of these two species were compared and the phylogenetic tree was constructed via MEGA 7.0. HPLC was used to establish the fingerprints of C. cicadae and T. dujiaolongae, and similarity evaluation, cluster analysis(CA), principal component analysis(PCA), and partial least squares discriminant analysis(PLS-DA) were applied to investigate the chemical pattern recognition. The result showed that the sources of these two species were different, and there were 115 stable differential sites in ITS sequences of C. cicadae and T. dujiao-longae. The phylogenetic tree could distinguish them effectively. HPLC fingerprints of 18 batches of C. cicadae and 5 batches of T. dujiaolongae were established. The results of CA, PCA, and PLS-DA were consistent, which could distinguish them well, indicating that there were great differences in chemical components between C. cicadae and T. dujiaolongae. The results of PLS-DA showed that six components such as uridine, guanosine, adenosine, and N~6-(2-hydroxyethyl) adenosine were the main differential markers of the two species. ITS sequences and HPLC fingerprint combined with the chemical pattern recognition method can serve as the identification and differentiation methods for C. cicadae and T. dujiaolongae.

Purpose: To investigate the spectrum-effect relationships between high performance liquid chromatography (HPLC) fingerprints and duodenum contractility of charred areca nut (CAN) on rats.Methods: An HPLC method was used to establish the fingerprint of charred areca nut (CAN). The promoting effect on contractility of intestinal smooth was carried out to evaluate the duodenum contractility of CAN in vitro. In addition, the spectrum-effect relationships between HPLC fingerprints and bioactivities of CAN were investigated using multiple linear regression analysis (backward method).Results: Fourteen common peaks were detected and peak 3 (5-Hydroxymethyl-2-furfural, 5-HMF) was selected as the reference peak to calculate the relative retention time of 13 other common peaks. In addition, the equation of spectrum-effect relationships {Y = 3.818 - 1.126X1 + 0.817X2 - 0.045X4 - 0.504X5 + 0.728X6 - 0.056X8 + 1.122X9 - 0.247X13 - 0.978X14 (p < 0.05, R2 = 1)} was established in the present study by the multiple linear regression analysis (backward method). According to the equation, the absolute value of the coefficient before X1, X2, X4, X5, X6, X8, X9, X13, X14 was the coefficient between the component and the parameter.Conclusion: The model presented in this study successfully unraveled the spectrum-effect relationship of CAN, which provides a promising strategy for screening effective constituents of areca nut.Keywords: Charred areca nut, Spectrum-effect relationships, HPLC fingerprints, Duodenum contractility

A simple and fast high-performance liquid chromatography (HPLC) fingerprint method combining reference standard extract for the identification of bilberry extract was developed and validated. Six batches of bilberry extract collected from different manufactures were used to establish the HPLC fingerprint. Other berry extracts—such as blueberry extracts, mulberry extracts, cranberry extracts, and black rice extracts—were also analyzed for their HPLC chromatograms. The fingerprints of five batches of bilberry extract showed high similarities, while one batch was distinguished from others. Additionally, the content of anthocyanin Cyanidin-3-O-glucoside (Cy-3-glc) in each berry extract was analyzed and compared. The results indicate that this HPLC fingerprint method, combining reference standard extracts, could be used for the authentication and quality control of bilberry extracts.

Separation power was limited when the conventional high-performance liquid chromatography (HPLC) fingerprinting method based on a single column was used to analyze very complex traditional Chinese medicine (TCM) preparations. In this research, a novel HPLC fingerprinting method based on column switching technology by using a single pump was established for evaluating the quality of Tianmeng oral liquid (TMOL). Twelve batches of TMOL samples were used for constructing HPLC fingerprints. Compared with the 16 common peaks in fingerprinting with a single column, 25 common peaks were achieved with two columns connected through a six-way valve. The similarity analysis combined with bootstrap method was applied to determine the similarity threshold, which was 0.992 to distinguish expired samples and unexpired samples. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) were also applied to classify the TMOL samples, and results revealed that expired and unexpired samples are classified into two categories. The HPLC fingerprinting based on column switching technology with better separation power and higher peak capacity could characterize chemical composition information more comprehensively, providing an effective and alternative method to control and evaluate the quality of TMOL, which would offer a valuable reference for other TCM preparations.

Application of HPLC fingerprint based on acid amide components in Chinese prickly ash (Zanthoxylum)