Quantitative Analysis Of Multi-components Research Articles

Analysis of an Aqueous Extract from Turkish Galls Based on Multicomponent Qualitative and Quantitative Analysis Combined with Network Pharmacology and Chemometric Analysis

The current quality control method for Turkish gall (TG) is limited to assessing total tannin or gallic acid (GA), which offers a basic level of quality control but does not fully capture the true quality of TG. Therefore, it is essential to establish a comprehensive method that utilizes multiple indicators to assess the intrinsic quality of TG. This research utilized UPLC-Q-TOF-MS/MS technology to qualitatively analyze the chemical composition of TG. Subsequently, the potential main active ingredients, targets, and pathways of TG in treating recurrent aphthous ulcers (RAU) were explored and analyzed using network pharmacology technology. Quantitative analysis of multicomponents by single marker (QAMS) was then employed to quantify the primary pharmacodynamic components in TG. Finally, chemometrics analysis was utilized to interpret the measured results and identify the markers of scavenging quality. The study identified 36 chemical components in TG, highlighting ellagic acid (EA), GA, and so on as key components in treating RAU. A method for simultaneously determining GA, EA, 1,2,3,6-tetra-O-galloyl-β-D-glucose (TEGG) and 1,2,3,4,6-penta-O-galloyl-β-D-glucose (PEGG) in TG was established. Statistical analysis revealed significant differences in the content of these 4 components across 14 batches of TG, with GA and PEGG identified as the primary contributors to the variations. This study determined a quality index for TG, providing a reference for quality evaluation and introducing a cost-effective and efficient quality control method. Furthermore, it addressed the challenge of developing new Chinese medicine by overcoming the lack of reference substances.

Experimental design approach for the quantitative analysis of multicomponents by single marker and HPLC fingerprinting of Thunbergia laurifolia aqueous extract.

Thunbergia laurifolia is used in traditional Thai medicine to reduce fever and treat mouth ulcers. However, the quantitative analysis of chemical markers has not yet been officially defined. The objective of this study is to develop a high-performance liquid chromatography (HPLC) method using a design of experiment (DoE) for the quantitative analysis of multicomponents by single marker (QAMS) and fingerprinting of the T. laurifolia aqueous extract. Critical variables were screened using a two-level fractional factorial design, followed by the optimization of the selected variables using a central composite design. The validated method was applied for quality assessment based on QAMS and fingerprinting of the extract. Optimum conditions of DoE for the analysis of caffeic acid, vicenin-2, and rosmarinic acid were determined. The relative correction factors for caffeic acid and vicenin-2 were calculated using rosmarinic acid as an internal reference standard, and their contents in 30 samples were determined. The differences between the external standard method (ESM) and QAMS were compared. No significant difference was observed in the quantitative determination, proving the consistency QAMS and ESM. HPLC fingerprints of T. laurifolia were established with 8 of 12 characteristic peaks that were structurally characterized using HPLC-diode array detection-electrospray ionization/tandem mass spectrometry. The similarity of the fingerprints in all samples was ≥0.74, and the pattern recognition of the characteristic peaks was satisfied. The proposed method efficiently detected multiple components of the T. laurifolia extract. Thus, the method is beneficial in providing references for enhancing the quality control of other herbal medicines.

Chemical fingerprinting and multicomponent quantitative analysis for quality control of Cinnamomum tamala collected from Western Himalaya by HPLC-DAD

Cinnamomum tamala, commonly known as “Indian bay leaf” or “Tejpat”, is an economically important plant widely used in medicine, food and cosmetic industries. Growing demand for its leaf and bark in the herbal trade and non-availability of quality materials lead to large-scale species admixture and adulteration in the global market. The present study aims at developing a validated HPLC-DAD (High-performance liquid chromatography coupled with diode array detection) method and multiple markers-based chemical fingerprints for quality evaluation of C. tamala leaf extracts. Five bioactive compounds, viz., coumarin, cinnamyl alcohol, cinnamic acid, cinnamaldehyde and cinnamyl acetate, were identified and quantified in 28 samples collected from the western Himalayan region of India. The chromatographic separation was achieved on Shimadzu Shimpak C18 column (dimension 250 × 4.6 mm, pore size 5 μm) with a gradient elution of mobile phase using acetonitrile and 0.1 percent phosphate buffer and the chromatograms were obtained at a wavelength of 265 nm. The method validation was done by analyzing the linearity, LOD, LOQ, precision, stability, repeatability and recovery rates of standard compounds for quantitative analysis. The values of coefficient of correlation (R2) were found to be close to 1 for linearity and similarity analysis; and standard deviation was less than 3 percent in case of precision, stability, repeatability and recovery rates. The content of target compounds such as coumarin, cinnamyl alcohol, cinnamic acid, cinnamaldehyde and cinnamyl acetate varied in the range of 0–1.09, 0–0.05, 0.07–0.51, 0.39–1.27 and 0–0.27 percent, respectively. In the chemical fingerprint of C. tamala leaves, a total of 13 peaks were assigned as common peaks. The results of the study indicated that the HPLC method now developed combining chemical fingerprint with quantification of analytes could serve as a useful tool for quality evaluation of herbal raw materials of C. tamala and a valuable reference for further study.

New Quality Evaluation of Qizhi Xiangfu Pills Based on Fingerprint with Chemometric Analysis and Quantitative Analysis of Multi-Components by Single Marker.

Qizhi Xiangfu Pills (QZXFPs) is one of the most commonly used traditional Chinese medicine preparations for the treatment of dysmenorrhea, but the existing quality evaluation standards have certain shortcomings and deficiencies. An effective and scientific quality evaluation method plays a vital role in medication safety. In this study, fingerprint combined with chemometric analysis and quantitative analysis of multi-components by a single marker (QAMS) method was used to comprehensively evaluate the quality of QZXFPs. The fingerprints of 28 batches samples were established and 23 common peaks were distinguished, of which 7 peaks were identified as albiflorin, paeoniflorin, baicalin, ligustilide, cyperotundone, nootkatone and α-cyperone. The content of these seven active ingredients was determined simultaneously by the QAMS method and there was no significantly different between QAMS and the external standard method. Additionally, similarity analysis, hierarchical cluster analysis, principal component analysis and orthogonal partial least squares discrimination analysis were applied for classifying the 28 batches of samples, and to find the main components causing the quality differences between different batches. In conclusion, the established method can comprehensively evaluate the consistency of quality between different batches and provide a reference for formulation quality evaluation to ensure safe and effective application of QZXFPs.

Determination of 13 chemical components of Epimedii Folium in pharmacopoeia by UPLC method combined with quantitative analysis of multicomponents by single-marker

The quantitative analysis of multicomponents by single-marker(QAMS) was established for 13 chemical components of Epimedii Folium, including neoglycolic acid, chlorogenic acid, cryo-chlorogenic acid, magnolidine, hypericin, epimedin A, epimedin B, epimedin C, icariin, baohuoside Ⅱ, sagittatoside A, icariin subside Ⅰ, and baohuoside Ⅰ, so as to investigate the feasibility and accuracy of this method in evaluating the quality of Epimedii Folium materials from different origins and different varieties. Through the scientific and accurate investigation of the experimental method, the external standard method was used to determine the content of 13 chemical components in epimedium brevieornu. At the same time, icariin was used as the internal standard, and the relative correction factors of icariin with neoglycolic acid, chlorogenic acid, cryo-chlorogenic acid, magnolidine, hypericin, epimedin A, epimedin B, epimedin C, icariin, baohuoside Ⅱ, sagittatoside A, icariin subside Ⅰ, and baohuoside Ⅰ were established, respectively. The contens of neoglycolic acid, chlorogenic acid, cryo-chlorogenic acid, magnolidine, hypericin, epimedin A, epimedin B, epimedin C, icariin, baohuoside Ⅱ, sagittatoside A, icariin subside Ⅰ, and baohuosideⅠ in Epimedii Folium were calculated by QAMS. Finally, the difference between the measured value and the calculated value was compared to verify the accuracy and scientific nature of QAMS in the determination. The relative correction factor of each component had better repeatability, and there was no significant difference between the results of the external standard method and those of QAMS. With icariin as the internal standard, QAMS simultaneously determining neoglycolic acid, chlorogenic acid, cryo-chlorogenic acid, magnolidine, hypericin, epimedin A, epimedin B, epimedin C, icariin, baohuoside Ⅱ, sagittatoside A, icariin subside Ⅰ, and baohuoside Ⅰ can be used for quantitative analysis of Epimedii Folium.

Quantitative analysis of multi-components by single marker method combined with UPLC-PAD fingerprint analysis based on saikosaponin for discrimination of Bupleuri Radix according to geographical origin.

Background: Saikosaponins are regarded as one of the most likely antipyretic constituents of Bupleuri Radix, establishing a comprehensive method that can reflect both the proportion of all constituents and the content of each saikosaponin is critical for its quality evaluation. Methods: In this study, the combination method of quantitative analysis of multiple components with a single marker (QAMS) and fingerprint was firstly established for simultaneous determination of 7 kinds of saikosaponins in Bupleuri Radix by ultra-high performance liquid chromatography (UPLC). Results: The results showed that saikosaponin d was identified as the optimum IR by evaluating the fluctuations and stability of the relative calibration factors (RCFs) under four different conditions. The new QAMS method has been confirmed to accurately quantify the 7 kinds of saikosaponins by comparing the obtained results with those obtained from external standard method and successfully classify the 20 batches of Bupleuri Radix from 8 provinces of China. The experimental time of fingerprint was significantly reduced to approximate 0.5h through UPLC-PAD method, a total of 17 common peaks were identified. Conclusion: The QAMS-fingerprint method is feasible and reliable for the quality evaluation of Bupleuri Radix. This method could be considered to be spread in the production enterprises of Bupleuri Radix.

Quality evaluation of Lonicerae Japonicae Flos from different origins based on high-performance liquid chromatography (HPLC) fingerprinting and multicomponent quantitative analysis combined with chemical pattern recognition.

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.

Evaluation of the famous classic formula Sanhua decoction based on network pharmacology and multi-component quantitative analysis

Evaluation of the famous classic formula Sanhua decoction based on network pharmacology and multi-component quantitative analysis

An optimization strategy for charged aerosol detection to linearize the detector response in the multicomponent quantitative analysis of Qishen Yiqi dripping pills.

Charged aerosol detection, increasingly recognized for quantifying pharmaceutical compounds with weak ultraviolet absorption, is a universal detection technique for high-performance liquid chromatography (HPLC). Charged aerosol detection shows a non-linear response with increasing analyte concentration over a wide range, limiting its versatility in various analytical applications. In this work, a co-optimization strategy for power function value (PFV) and power laws was proposed and applied to broaden the linear range of the standard curve of saccharides in Qishen Yiqi dripping pills using the HPLC-charged aerosol detection (HPLC-CAD) method. Power function values for all analytes were optimized based on empirical models. Subsequently, the optimum power laws were investigated based on a preferred PFV. Additionally, various regression equations were evaluated to ensure the accuracy and precision of the results. With the optimized PFV and power law, the ordinary least squares model demonstrated a satisfactory fit. The optimal PFVs and power laws expanded the standard curve's linear range by 2.7 times compared to default settings, reducing model uncertainty. This paper presents a vital method for developing a multi-component quantitative HPLC-CAD approach without external data transformation outside the provided software, especially suitable for analytical applications of traditional Chinese medicine with significant quality differences.

The Development and Validation of Simultaneous Multi-Component Quantitative Analysis via HPLC–PDA Detection of 12 Secondary Metabolites Isolated from Drynariae Rhizoma

Drynariae Rhizoma (DR) is a functional food and traditional medicine that has been widely used for bone and joint disorders for thousands of years. In this study, 14 compounds were isolated from DR, and their structures were identified using UPLC/QTOF–MS, UPLC–ESI/LTQ–Orbitrap–HRMS, and 2D NMR and compared with those obtained in previous studies. An HPLC–PDA multi-component simultaneous quantitative determination method was developed for 12 of the 14 DR-derived compounds, excluding compounds with a content <1.5 mg. The developed HPLC method was validated based on linearity (r2 ≥ 0.999), limit of detection (0.01–0.65 μg/mL), limit of quantification (0.04–1.97 μg/mL), intra-day precision and accuracy ranges (0.06–2.85% and 95.03–104.75%, respectively), and inter-day precision and accuracy ranges (0.24–2.83% and 95.75–105.75%, respectively). The developed analysis method improved the resolution of compounds 4 and 5. In addition, this is the first quantitative analysis of compounds 7, 8, and 11 and the first simultaneous quantitative analysis of 12 compounds, including compounds 4, 7, 8, 10, 11, and 14. This study developed a rapid, accurate, and economical HPLC method for performing the simultaneous quantitative analysis of 12 secondary metabolites isolated from DR.

Integrated quality control strategy for red yeast rice combining DSC and HPLC profiles

Red yeast rice (RYR) is a popular food product with significant quality control challenges. This study first established a gradient elution tower plate theory suitable for gradient elution and proposed a dual-label system calibration method to monitor and correct chromatographic systems for changes. Subsequently, high-performance liquid chromatography as the analytical method, and a five-wavelength maximization profile was employed to obtain comprehensive chromatographic information on RYR. A novel multi-marker assay by monolinear method (MAML) was employed for the accurate quantitative determination of quality markers. A differential scanning calorimetry (DSC) quantized fingerprint was established to study complete thermal changes. The comprehensive linear quantitative fingerprint method (CLQFM) was also developed to evaluate fingerprints. Results showed that the CLQFM divides the samples into four quality grades, MAML yielded better results than quantitative analysis of multi-components by a single marker method. Thermal analysis revealed that treatment temperatures higher than 193.7 °C for extended periods should be avoided to maintain sample quality. This study promotes the dual control of the quality and thermal stability of RYR, providing a new direction for food control.

Integration of fingerprint-activity relationship and chemometric analysis to accurately screen Q-markers for the quality control of traditional Chinese medicine compound preparation: Jinlian Qingre granules as an example

This study aims to develop a comprehensive strategy that accurately screens and quantifies quality markers (Q-markers) by combining LC-MS metabolomics with fingerprint-effect relationships, chemometrics, and QAMS methods for the quality control in traditional Chinese medicine compound preparations (CMP). First, the chemical compositions in Jinlian Qingre granules (JQG) were analyzed and identified using ultrahigh-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). Next, the HPLC fingerprint of JQG was established, and chemometrics were employed to evaluate JQG quality. Then, potential anti-inflammatory bioactive constituents were screened using a fingerprinting-effect relationship model utilizing partial least squares regression (PLSR) and a back propagation neural network optimized using a genetic algorithm (GA-BPNN). On this basis, Q-markers of JQG were determined and analyzed using quantitative analysis of multi-components by the single marker (QAMS) employing three components as reference substances (RS). 24 chemical constituents in JQG were characterized using UHPLC-HRMS. Twenty-four common peaks were assigned to the fingerprint. Six compounds, mangiferin, 2′'-O-beta-L-galactopyranosylorientin, orientin, veratric acid, vitexin, and harpagoside, identified from the common peaks associated with anti-inflammatory efficacy, could be used as Q-markers of JQG. The content determination results displayed no significant difference in the content of Q-markers in 20 batches of JQG samples measured using the external standard method and QAMS. Q-markers could be efficiently screened and determined by integrating multidisciplinary technologies. This comprehensive strategy could be beneficial for the thorough evaluation of CMP.

A quality evaluation method of lotus leaf based on its lipid lowering components using QAMS and chemometrics

IntroductionLotus leaf has long been used as food and medicine in China and is well-known for its lipid-lowering effects. However, there is a lack of a comprehensive quality evaluation for lotus leaf due to the absence of consideration of the correlation between various components and their efficacy. ObjectivesThis study aims to find out the key bioactive components that can be used for quality evaluation of lotus leaf on lipid-lowering effect. MethodsThirteen compounds were characterized in the lotus leaf using ultra-high- performance liquid chromatography-time-of-fight mass spectrometry (UPLC-Q-TOF-MS). Five alkaloids and four flavonoids were identified according to their lipid-lowering activities reported in literatures. Then, the contents of these nine components were analyzed in 39 batches of lotus leaves growing in different locations using high performance liquid chromatography diode-array detector (HPLC-DAD), and further evaluated by quantitative analysis of multi-components by single marker (QAMS) and chemometrics. The anti-adipogenic activity of lotus leaves were evaluated for their inhibitory effect on the PPARγ expression by luciferase assay. ResultsThe 39 batches were clustered into two regions, the north and the south, based on the contents of these components. Three alkaloids, nuciferine, N-nornuciferine, and asimilobine, and three flavonoids, astragalin, hyperoside, and trifolioside, were found to serve as the key factors behind the region differences. Their contents were higher in Guangchang County of Jiangxi Province than other habitat locations. Moreover, the luciferase assay combined with chemometrics showed that these components were positively correlated with lipid-lowering activity of lotus leaf. ConclusionsThree alkaloids and three flavonoids were screened out and could be used as key compounds for quality evaluation of lotus leaf on lipid-lowering effect.

A multi-strategy platform for Q-markers screening and quality control of Wuzi Yanzong Wan based on fingerprint and network pharmacology

Wuzi Yanzong Wan (WZYZW) is a classic formula for tonifying the kidneys in Traditional chinese medicine (TCM) and is widely used clinically in diseases of the reproductive system, immune system and nervous system. Therefore, the quality control and prediction quality markers (Q-markers) of WZYZW is of positive significance.In this study, We first established the fingerprints, calibrated 28 common peaks, identified 12 common peaks of gallic acid, geniposidic acid, chlorogenic acid, ellagic acid, rutin, hyperoside, verbascoside, astragalin, kaempferol, schisandrol A, schisandrol B and schisandrin B, and the similarity was greater than 0.9 of 10 batches.Then, withing network pharmacology, we screened 41 core targets such as PIK3CA, AKT1, PIK3CB, potential pathways such as pathways in cancer and PI3K-Akt signalling pathway of 12 components. The results showed that they were tightly connected to predicated targets and pathways. Finally, by using the hyperoside as internal reference standard, a Quantitative analysis of multi-components (QAMS) for WZYZW was established to determine the contents of WZYZW. The percent difference(%) showed that there was no significant difference between the quantitative results of external standard method (ESM) and QAMS method. Contents of the 11 components above were 0.0091 ∼ 0.0185 %, 0.1019 ∼ 0.1361 %, 0.0518 ∼ 0.0718 %, 0.0130 ∼ 0.0320 %, 0.0084 ∼ 0.0190 %, 0.0621 ∼ 0.1192 %, 0.0127 ∼ 0.0419 %, 0.0006 ∼ 0.0089 %, 0.0212 ∼ 0.0261 %, 0.0061 ∼ 0.0400 %, 0.0084 ∼ 0.0103 %, respectively. Overall, the method developed was applied to the quality evaluation and Q-markers research of WZYZW as well as provided guiding significance for the Q-marker research of TCM.

Complete composition analysis of polysaccharides based on HPAEC-PAD coupled with quantitative analysis of multi-components by single marker.

Monosaccharide compositions analysis (MCA) is indispensable for structural characterisations and structure-activity relationships of plant polysaccharides. To develop a concise and direct MCA method, we established a quantitative analysis of the multi-monosaccharaides by single marker (QAMS) by high-performance anion-exchange chromatography with pulsed-amperometric detection (HPAEC-PAD) method. A stable and reproducible HPAEC-PAD method for simultaneous determination of aldoses, ketoses and uronic acids (i.e., l-arabinose, d-xylose, d-ribose, l-rhamnose, d-fucose, d-mannose, d-glucose, d-galactose, d-fructose, d-glucuronic acid and d-galacturonic acid) was established by systematic optimisation of stationary phases, column temperatures and elution programmes. On this basis, the QAMS method was proposed through comprehensive investigations of relative correction factor (RCF) variations under different influencing factors, for example, sample concentrations, flow rates, and column temperatures. Using rhamnose as an internal reference standard, the contents of the other monosaccharidecomponents in polysaccharides from Panax quinquefolium L. and Achyranthes bidentata Bl. samples were simultaneously determined by QAMS, and there was no significant difference between the results from the QAMS and external standard method (t test, P > 0.520). In addition, a MCA fingerprinting of 30 batches of P. quinquefolium polysaccharide was established by HPAEC-PAD, and six common peaks were assigned and determined. The established HPAEC-PAD-QAMS method was successfully applied to the MCA of polysaccharides from P. quinquefolium and A. bidentata after optimisation of hydrolysis conditions. HPAEC-PAD-QAMS was proposed and established for MCA of plant polysaccharides for the first time.

Quality Evaluation of Sanguisorbae Radix via Python Aided Optimization Fingerprint Chromatography Combined with Quantitative Analysis of Multi-components by Single Marker

Quality Evaluation of Sanguisorbae Radix via Python Aided Optimization Fingerprint Chromatography Combined with Quantitative Analysis of Multi-components by Single Marker

Multicomponent Analysis of Liuwei Dihuang Pills by a Single Marker Quantification Method and Chemometric Discrimination of Fingerprints.

An effective and comprehensive quality evaluation method for Liuwei Dihuang pills (LDP) was established by the simultaneous determination of 8 active components in LDP by the quantitative analysis of multicomponents by single marker (QAMS) method and high-performance liquid chromatography (HPLC) fingerprint combined with chemometrics. These 8 active components were determined by QAMS and the external standard method (ESM), and the quantitative results of the two methods were compared to validate the accuracy and feasibility of the QAMS method. 8 active components showed good linear relationships within their ranges, whose average recoveries were 99.7∼102.3%. No significant difference was found (P > 0.05) in the quantitative results determined by QAMS and ESM. Furthermore, the fingerprint of LDP was also established, with 11 common peaks identified, and the similarity of the fingerprints of 21 batches of LDP was greater than 0.95. The 21 batches of LDP were basically divided into 3 groups by hierarchical cluster analysis (HCA) and principal component analysis (PCA), and 3 differential markers were screened out by orthogonal partial least squares discriminant analysis (OPLS-DA). The established QAMS method is accurate, economical, fast, and convenient and can simultaneously determine the content of 8 active components in LDP. HPLC fingerprint combined with chemometric analysis more comprehensively evaluated the quality consistency of different batches of LDP and analyzed the markers that cause quality differences between batches. It can provide a scientific basis and reference of quality consistency evaluation for the manufacturers and drug regulatory departments of the preparation.

Quality Evaluation of Volatile Oil in Yanyangke Mixture (YM) Based on GC-MS Fingerprint, GC Multicomponent Quantitative Analysis and Chemical Pattern Recognition Analysis.

Yanyangke mixture (YM) is composed of 12 kinds of traditional Chinese medicine (TCM) used for the treatment of patients with cough, dry throat and other diseases caused by acute or chronic pharyngitis or patients with difficulty in expectoration. With the wide application of YM in clinical practice, its quality control has attracted huge attention. Based on the multi-component characteristics of Chinese herbal medicines, it is pertinent to establish a quality evaluation system. A new idea is to adopt gas chromatography-mass spectrometry (GC-MS) chemical composition identification, GC-MS fingerprint, and GC content determination as a potential quality control index of the volatile oil in YM. In this study, the volatile oil of YM was extracted by steam distillation, and the chemical components of the volatile oil were analyzed by GC-MS, and 43 chemical components were identified. The fingerprint of the volatile oil from YM was established and the similarity evaluation was performed. Combined with chemometric methods, such as cluster analysis, principal component analysis and partial least squares analysis, the chemical composition differences of the volatile oil from different batches of YM were compared and the symbolic components affecting the quality of the volatile oil from different batches of YM were excavated. Finally, three components were selected as the potential active component markers of YM and the GC content determination method of these three components was established. A rapid, reasonable, and effective quality evaluation and control method of YM volatile oil was established, which provided a reference for further development and research on YM, as well as a new idea for research on other TCM prescriptions.

Quality evaluation of Compound Cheqian Tablets based on UPLC-Q-TOF-MS/MS, network pharmacology and "double external standards" QAMS

The Compound Cheqian Tablets are derived from Cheqian Power in Comprehensive Recording of Divine Assistance, and they are made by modern technology with the combination of Plantago asiatica and Coptis chinensis. To investigate the material basis of Compound Cheqian Tablets in the treatment of diabetic nephropathy, in this study, the chemical components of Compound Cheqian Tablets were characterized and analyzed by UPLC-Q-TOF-MS/MS, and a total of 48 chemical components were identified. The identified chemical compounds were analyzed by network pharmacology. By validating with previous literature, six bioactive compounds including acteoside, isoacteoside, coptisine, magnoflorine, palmatine, and berberine were confirmed as the index components for qua-lity evaluation. Furthermore, the content of the six components in the Compound Cheqian Tablets was determined by the "double external standards" quantitative analysis of multi-components by single marker(QAMS), and the relative correction factor of isoacteoside was calculated as 1.118 by using acteoside as the control; the relative correction factors of magnoflorine, palmatine, and berberine were calculated as 0.729, 1.065, and 1.126, respectively, by using coptisine as the control, indicating that the established method had excellent stability under different conditions. The results obtained by the "double external standards" QAMS approximated those obtained by the external standard method. This study qualitatively characterized the chemical components in the Compound Cheqian Tablets by applying UPLC-Q-TOF-MS/MS and screened the pharmacodynamic substance basis for the treatment of diabetic nephropathy via network pharmacology, and primary pharmacodynamic substance groups were quantitatively analyzed by the "double external stan-dards" QAMS method, which provided a scientific basis for clarifying the pharmacodynamic substance basis and quality control of Compound Cheqian Tablets.

Quality Evaluation of Bioactive Ingredients in Lianhua Qingwen Capsule Based on Quantitative Analysis of Multicomponent by the Single Marker Method and the Chemical Recognition Patterns Method

Based on high performance liquid chromatography with the diode array detector (HPLC-DAD), a new strategy for simultaneous determination of ten bioactive ingredients in Lianhua Qingwen capsule (LHQW) was developed for comprehensive quality assessment of LHQW. In this work, with rhein regarded as the internal reference substance (IRS), the relative correction factors (RCFs) of neochlorogenic acid, amygdalin, chlorogenic acid, forsythoside A, quercitrin, phillyin, glycyrrhizic acid, isoforsythiaside, and (+) pinoresinol-β-D-glucoside were calculated for simultaneous determination of ten bioactive ingredients. More importantly, compared to previous work, the simultaneous determination of the content of ten pharmacologically important active ingredients at one detection wavelength with only one reference substance has been achieved. Based on the contents of ten bioactive ingredients, the quality of the 20 batches of LHQW samples was further analyzed by chemical recognition patterns method. Ten bioactive ingredients showed a good linear relationship in their respective concentration ranges (r ≥ 0.999). The relative standard deviations (RSDs) of precision (≤4.62%), stability (≤4.04%), repeatability (≤3.87%), and the average recovery of ten bioactive components (99.8%∼104.1%) demonstrated the QAMS developed for LHQW which had good durability. The correlation coefficient ( P > 0.05 ) showed that no significant difference existed in the results of QAMS and external standard method (ESM). Hierarchical clustering analysis (HCA) divided samples into three main groups. Radar plot analysis and principal component analysis (PCA) found some quality differences existed between the three groups of samples. Orthogonal partial least-squares discrimination analysis (OPLS-DA) showed that forsythoside A could be used as the primary marker responsible for the quality differences. In conclusion, the established QAMS method combined with chemometric analysis can simultaneously determine the content of 10 active components and comprehensively evaluate the quality of different batches of LHQW. It can provide scientific basis and reference of quality consistency evaluation for the formulation manufacturers and drug regulatory authorities.