Quality Grade Evaluation of Nvjin Pills Based on TCMRD and Application of Network Pharmacology to Explore the Anti- Polycystic Ovarian Syndrome Activity of Focused Compounds

Quality Grade Evaluation of Nvjin Pills Based on TCMRD and Application of Network Pharmacology to Explore the Anti- Polycystic Ovarian Syndrome Activity of Focused Compounds | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Quality Grade Evaluation of Nvjin Pills Based on TCMRD and Application of Network Pharmacology to Explore the Anti- Polycystic Ovarian Syndrome Activity of Focused Compounds Lin Lin, guangzhen liu, zhang dexin, fengrui yu, lejun tan, xiangrong mu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2531631/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The compound Chinese herbal medicine (CCHM) is one of the most commonly used types of synergistic herbal medicine. It is based on composite herbal formula (CHF), which makes quality evaluation of this kind of traditional Chinese medicine (TCM) difficult. Taking Nvjin Pills (NJP) as an example, this study reported the development of a novel principle of analysis in CCHM. In order to improve the effectiveness of marketed drugs related active ingredients, it was necessary to designate a more unified quality evaluation standard. The core of the experimental is to prepare 3 batches of TCM reference drugs (TCMRD) using high-quality Chinese materia medica (single Chinese herbals used in the NJP). The active ingredients identified in the herbal formula including glycyrrhizic acid, cinnamaldehyde, paeonol, baicalin, hesperidin, paeoniflorin and ferulic acid were analyzed in both 3 TCMRDs and 76 batches of commercial products from 19 manufacturers by high performance liquid chromatography (HPLC) method combined with wavelength switching. NJP is a well-known Chinese patent medicine that has been widely applied for the clinical treatment of polycystic ovarian syndrome (PCOS) and other gynecological diseases. For the first time, the relationship between the components mentioned above and their pharmacological in the treatment of PCOS was explored via network pharmacology analysis. The simple prediction results of network pharmacological analysis verified the feasibility and reliability of the established quantitative analysis method for 7 compounds in NJP, which were recommended as candidate indicators for quality evaluation ultimately. Using the TCMRD as the scientific ruler, quality grade specifications of NJP were proposed by comprehensive analysis of multiple index. Accordingly, 16, 47, and 13 batches of samples were primarily rated as first-grade, second-grade and unqualified grade respectively. This study will provide a chemical basis for quality control of NJP, which is necessary in the production process of pharmaceutical development. Compound Chinese herbal medicine (CCHM) Quality grade evaluation Traditional Chinese medicine reference drug (TCMRD) Nvjin Pills (NJP) Figures Figure 1 Figure 2 Figure 3 Figure 4 1 Introduction The compound Chinese herbal medicine (CCHM) is frequently used in traditional Chinese medicine (TCM) treatment in China and some parts of the world [ 1 , 2 ]. A typical CCHM is usually composed of two or more processed-Chinese materia medica (CMM) containing numerous chemical components. With the progress of chemical analysis technology, it is not difficult to determine the authenticity of CCHM. But, due to the uneven quality of the initially used processed-CMM and different quality control capabilities of the manufacturers, the quality of CCHM may vary significantly. In this case, the author proposed TCMRD as the standard formula of Chinese medicine control, and developed the quality grade evaluation system. TCMRD refers to the physical reference made of authenticated and standardized decoction pieces and auxiliary materials. The reference drug was prepared in strict accordance with legal procedures and production technology, and in accordance with good manufacturing practice (GMP). It is mainly used for quality evaluation and grading of CCHM to evaluate the authenticity of drug administration (including correct raw materials) and the reliability of drug dosage (whether complete drug administration is based on compound type). At present, quality grade research has become a hot spot and new field of TCM research [ 3 , 7 ],which requires more innovative methods and more systematic and in-depth work to provide reasonable theory and feasible application. CCHM is a compound synergistic Chinese herbal formula, so in the preparation process, the different properties of the chemical components contained may affect each other. TCMRD is prepared in strict accordance with prescription and corresponding preparation procedures and can provide critical information including actual background and transfer rate of ingredients from raw material to preparation [ 8 ]. Therefore, TCMRD can be used as a measuring scale to evaluate CCHM products and a powerful means to solve the uneven quality of TCM products, showing a broad application prospect in the quality control, evaluation and grading of TCM products[ 9 ]. Nvjin Pills (NJP) is a typical proprietary Chinese medicine, which is included in the Chinese Pharmacopoeia (ChP)2020 edition [ 10 ]. It is used to treat menstrual irregularities, menstrual pain caused by deficiency of qi and blood, qi stagnation and blood stasis. Polycystic ovary syndrome (PCOS) is the most common gynecological disease caused by abnormal immune function and endocrine disorders, mainly characterized by abnormal ovulation, hyperandrogenemia and polycystic changes of ovary. Without early diagnosis and effective treatment, it will seriously affect the reproductive function of patients and lead to infertility [ 11 ]. NJP is a compound preparation for regulating menstruation and nourishing blood, consisting of 23 Chinese herbs (see Table 1 ), Which proves NJP has various flavors, complex ingredients, mutual interference and intricate prescription composition. Therefore, to control its quality level in terms of ensuring safety, effectiveness, stability, etc., both the quality of medicinal materials and drug specifications should be standardized. Qualitative and quantitative analysis of NJP by high performance liquid chromatography (HPLC) [ 12 , 13 ], gas chromatography (GC) [ 14 , 15 ] and thin layer chromatography (TLC)has been reported [ 16 ]. However, there is no research on the simultaneous determination of multiple components for commercial CCHM quality rating. Using TCMRD, all 23 Chinese herbs could be detected by microscopy, TLC, UPLC-MS, X-ray diffraction and other methods. In this study, a simultaneous analysis for comprehensive quality evaluation of 9 CMMs, including Glycyrrhizae Radix Et Rhizoma (Gancao, GRER), Cinnamomi Cortex (Rougui, CC), Moutan Cortex (Mudanpi, MC), Scutellariae Radix(Huangqin, SR), Citri Reticulatae Pericarpium (Chenpi, CRP), Paeoniae Radix Alba (Baishao, PRA), Angelicae Dahuricae Radix (Baizhi, ADR), Chuanxiong Rhizoma (Chuanxiong,CR) and Ligustici Rhizoma Et Radix (Gaoben,LRER) in the NJP using 7 markers (glycyrrhizic acid, cinnamaldehyde, paeonol, baicalin, hesperidin, paeoniflorin and ferulic acid) was developed using high-performance liquid chromatography (HPLC) coupled with wavelength switching, which was also used to assay 3 batches of TCMRDs for NJP and 76 batches of commercial products from 19 manufacturers. Besides, the relationship between the 7 compounds and their key targets treatment of PCOS investigated by network-based pharmacology analytical approaches, which provided the basis for the quantitative analysis of NJP. On the basis of comprehensive analysis of the results, the quality grading standard of NJP was put forward, and the samples were graded accordingly to distinguish good products from bad ones. The integrated strategy of multi-component analysis by HPLC and TCMRD to evaluate quality grade of NJP was demonstrated in Fig. 1 . Table 1 Formulation information of Nvjin Pills. No. Ingredient Dosage (g) No. Ingredient Dosage (g) 1 Angelicae Sinensis Radix 140 13 Corydalis Rhizoma 70 2 Paeoniae Radix Alba 70 14 Ligustici Rhizoma Et Radix 70 3 Chuanxiong Rhizoma 70 15 Angelicae Dahuricae Radix 70 4 Rehmanniae Radix Praeparata 70 16 Scutellariae Radix 70 5 Codonopsis Radix 55 17 Cynanchi Atrati Radix Et Rhizoma 70 6 Atractylodis Macrocephalae Rhizoma 70 18 Cyperi Rhizoma 150 7 Poria cocos (Schw.)Wolf 70 19 Amomi Fructus 50 8 Glycyrrhizae Radix Et Rhizoma 70 20 Citri Reticulatae Pericarpium 140 9 Cinnamomi Cortex 70 21 Halloysitum Rubrum 70 2 Materials And Methods 2.1 Materials . 76 batches of Nvjin Pills (NJP) from 19 manufacturers were collected via National Post-market Drug Surveillance. All samples are manufactured in accordance with legal standards [10] and approved by the manufacturers. Respectively, 3 batches of authentic, high-quality and standardly processed CMMs, including Angelicae Sinensis Radix (Danggui, ASR), Paeoniae Radix Alba (Baishao, PRA), Chuanxiong Rhizoma (Chuanxiong, CR), Rehmanniae Radix Praeparata (Shudihuang, RRP), Codonopsis Radix (Dangshen, CR), Atractylodis Macrocephalae Rhizoma (Baizhu, AMR), Poria cocos (Schw.)Wolf (Fuli, PcW), Glycyrrhizae Radix Et Rhizoma (Gancao, GRER), Cinnamomi Cortex (Rougui, CC), Leonuri Herba(Yimucao, LH), Moutan Cortex (Mudanpi, MC), Myrrha, Corydalis Rhizoma (Yanhusuo, CR), Ligustici Rhizoma Et Radix (Gaoben, LRER), Angelicae Dahuricae Radix (Baizhi, ADR), Scutellariae Radix (Huangqin, SR), Cynanchi Atrati Radix Et Rhizoma (Baiwei, CARER), Cyperi Rhizoma (Fuzi, CR), Amomi Fructus (Sharen, AF), Citri Reticulatae Pericarpium (Chenpi, CRP), Halloysitum Rubrum (Chishizhi, HR), Cervi Cornu Degelatinatum (Lujiaoshuang, CCD) and Asini Corii Colla (Ejiao, ACC) were bought from 3 different Chinese herbal medicine markets (Bozhou Chinese herbal medicine market (Bozhou, China); Anguo Chinese herbal medicine market (Anguo, China) and Lotus Pond Chinese herbal medicine market (Chengdu, China)). The origin of each CMM was authenticated by Professor Xigui Song using character and microscopic identification according to the Chinese Pharmacopoeia, edition 2020 (ChP, 2020 Edition). The results of chemical analysis performed by the authors indicated that all the CMMs met their own national drug standards. For future reference, the specimens were deposited at the Traditional Chinese Medicine Herbarium, Shandong Institute for food and drug control (Jinan, China). Refined honey, the excipient of the big honeyed pills, was purchased from Beijing Tongrentang Co., Ltd. (Beijing, China). The materials and methods section should contain sufficient detail so that all procedures can be repeated. It may be divided into headed subsections if several methods are described. Strictly complied with the statutory production process and GMP requirements, 3 batches of TCMRD for NJP were prepared. The primary procedure was as follows [10]: Angelicae Sinensis Radix (Danggui, ASR), Paeoniae Radix Alba (Baishao, PRA), Chuanxiong Rhizoma (Chuanxiong, CR), Rehmanniae Radix Praeparata (Shudihuang, RRP), Codonopsis Radix (Dangshen, CR), Atractylodis Macrocephalae Rhizoma (Baizhu, AMR), Poria cocos (Schw.)Wolf (Fuli, PcW), Glycyrrhizae Radix Et Rhizoma (Gancao, GRER), Cinnamomi Cortex (Rougui, CC), Leonuri Herba(Yimucao, LH), Moutan Cortex (Mudanpi, MC), Myrrha, Corydalis Rhizoma (Yanhusuo, CR), Ligustici Rhizoma Et Radix (Gaoben, LRER), Angelicae Dahuricae Radix (Baizhi, ADR), Scutellariae Radix (Huangqin, SR), Cynanchi Atrati Radix Et Rhizoma (Baiwei, CARER), Cyperi Rhizoma (Fuzi, CR), Amomi Fructus (Sharen, AF), Citri Reticulatae Pericarpium (Chenpi, CRP), Halloysitum Rubrum (Chishizhi, HR), Cervi Cornu Degelatinatum (Lujiaoshuang, CCD) and Asini Corii Colla (Ejiao, ACC) were pulverized to fine powder, then were sifted and mixed well. Honey pills are made by adding 135 grams of refined honey for every 100 grams of the mixture. For specificity validation, negative control without Angelicae Sinensis Radix (Danggui, ASR), Chuanxiong Rhizoma (Chuanxiong, CR) and Ligustici Rhizoma Et Radix (Gaoben, LRER), Paeoniae Radix Alba (Baishao, PRA) and Moutan Cortex (Mudanpi, MC), Cynanchi Atrati Radix Et Rhizoma (Baiwei, CARER), Glycyrrhizae Radix Et Rhizoma (Gancao, GRER), Cinnamomi Cortex (Rougui, CC), Scutellariae Radix (Huangqin, SR) and Citri Reticulatae Pericarpium (Chenpi, CRP) was prepared by the same method with appropriate amounts of the rest of the herbal materials and the refined honey according to the formulation of NJP. 2.2 Chemicals and Reagents. Ferulic Acid (110773-201915), Paeoniflorin (110736-202145), Paeonol (110708-201908), Ammonium Glycyrrhizinate (110731-202122), Cinnamaldehyde (110710-202022), Baicalin (110721-202019) and Hesperidin were bought from National Institutes for Food and Drug Control. They were all used as reference standards. Methanol, acetonitrile, and formic acid HPLC grade, were purchased from Aladdin (Aladdin, Shanghai). Deionized water was purified by a Milli-Q system (Millipore, USA). 2.3 Preparation of Standard Solutions. Each reference substance was prepared with 90% (V/V) methanol to form a reserve solution with a concentration of approximately 0.5 mg/mL, which was then diluted with 90% (V/V) methanol to produce a series of mixed working standard solutions with five concentration levels (see Table 2). Table 2: Concentration levels of working standard solutions for multi-component determination Analyte Working Standard (mg/ml) 1 2 3 4 5 Paeoniflorin 0.004 0.007 0.011 0.014 0.018 Ferulic acid 0.001 0.002 0.003 0.003 0.004 Hesperidin 0.010 0.020 0.029 0.039 0.049 Baicalin 0.011 0.022 0.033 0.045 0.056 Cinnamaldehyde 0.001 0.002 0.003 0.003 0.004 Paeonol 0.003 0.005 0.008 0.011 0.014 Glycyrrhizic acid 1 0.002 0.005 0.007 0.010 0.012 1 The weight of glycyrrhizic acid = the weight of ammonium glycyrrhizinate/1.0207. 2.4 Preparation of Solutions of Sample, Reference Drugs, Negative Control, and Chinese Materia Medicas . NJP samples and NJP reference drugs obtained by weight variation test were ground into uniform powder. One g of powder was accurately weighed and transferred into a conical flask, into which 25 mL of 90% (V/V) methanol was accurately added. The conical flask and the whole mixture was weighed, then was heated using water bath reflux at 80 ℃ for 2 h. The content was then cooled to room temperature. The flask was weighed again, and the lost weight was replenished with 90% (V/V)methanol. The mixture was filtered through a 0.22 μm filter and the filtrate was subjected for further analysis. Then negative control solution, containing no active ingredients for specificity validation, was prepared in the same manner. To determine the transfer rates of chemical markers of reference medicinal materials from raw materials to the TCMRD, respectively 3 batches of Angelicae Sinensis Radix (Danggui, ASR), Chuanxiong Rhizoma (Chuanxiong, CR), Ligustici Rhizoma Et Radix (Gaoben,LRER), Paeoniae Radix Alba (Baishao, PRA), Moutan Cortex (Mudanpi, MC), Cynanchi Atrati Radix Et Rhizoma (Baiwei, CARER), Glycyrrhizae Radix Et Rhizoma (Gancao, GRER), Cinnamomi Cortex (Rougui, CC), Scutellariae Radix (Huangqin, SR) and Citri Reticulatae Pericarpium (Chenpi, CRP) were ground into fine powder and processed with the same method. 2.5 Instrument and Operating Conditions . The analysis of all filtrates under the item 2.4 was performed using a Waters HPLC system (Waters Co., USA) equipped with photo diodearray(PDA) detector, binary solvent manager, sample manager and column compartment. The software Empower was used for data acquisition. The separation was performed on a Agilent Eclipse plus C18 column (250 mm×4.6 mm, 5μm) using a linear gradient elution of 0.2% formic acid in acetonitrile (A) and 0.2% (v/v) formic acid in water (B): 0-25 min, 10%-35% (v/v) A; 25-37 min, 35%-59% (v/v) A; 37-40 min, 59%-75% (v/v) A; at a flow rate of 1 mL/min. The column temperature was set at 30 ℃ and the injection volume was 10μL. Multi-wavelength scanning was applied and the detection wavelengths were set at 230 nm for paeoniflorin, 316 nm for ferulic acid, 283 nm for hesperidin, 280 nm for baicalin, 290 nm for cinnamaldehyde, 274 nm for Paeonol, and 237 nm for glycyrrhizic acid, respectively. Three injections were performed for each solution. 2.6 Method Validation . The specificity, accuracy (recovery), precision, limit of detection (LOD), limit of quantitation (LOQ) and linearity of the method were verified according to the recommendations of the International Coordination Conference (ICH) guidelines [17].The specificity of the method was assessed by comparing HPLC chromatograms obtained from NJP with negative controls. The recovery test of the standard addition method was used to verify accuracy. The corresponding amount of test component standard was added to 0.5 g sample, and the same pre-treatment and analysis methods were used as those of NJP, and the test was repeated six times. For precision test, the same solution was repeatedly checked six times in one day for intraday test, and the analysis was conducted for three consecutive days for daytime test. For repeatable tests, six test solutions were prepared from the same sample and analyzed. LOD and LOQ were determined at S/N ratio of 3 and 10, respectively. Linearity was determined by establishing calibration curves for 5 concentration levels. The calibration equation and correlation coefficient (r) were calculated by least square regression for the obtained peak area and concentrations of all markers. 2.7 Network Pharmacology Analysis. The structural formulas of tested constituents were identified by PubChem database (https://pubchem.ncbi.nlm.nih.gov/) and download its corresponding 2D structure file to make predictions and collections through the Swiss Target Prediction platform (https://www.swisstargetprediction.ch/). TCMSP (https://tcmspw.com/tcmsp.php) was used to supplement of the chemical composition targets. The protein-protein interaction (PPI) data were obtained from the STRING database (https://string-db.org/). Relied on Cytoscape 3.9.0 software, the imagement of PPI network was builted after hiding the free points. To deeply explore the pathways and biological process of the network, GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses were conducted by Metascape platform (https://metascape.org/). GO enrichment analysis encompassed cellular components (CC), biological processes (BP), and molecular functions (MF). Ranked by the KEGG analysis, the top 25 pathways related to PCOS were screened out. The information of enrichment bubble chart was visualized by the bioinformatics platform (http://www.bioinformatics.com.cn/). 3 Results And Discussion 3.1 Development of the HPLC Method. In order to simultaneously determine seven analytes with better separation and shorter time, HPLC chromatographic conditions were optimized. The ultraviolet (UV) spectra of the seven analytical markers to be measured in the reference and sample solutions was scaned. The maximum absorption of seven analytes (paeoniflorin, ferulic acid, hesperidin, baicalin, cinnamaldehyde, paeonol and glycyrrhizic acid) was set at 230 nm, 316 nm, 283 nm, 280 nm, 290 nm, 274 nm and 237 nm, respectively. On this basis, multi-wavelength switching is programmed. Agilent Eclipse plus C18 column, the most used reversed phase C18 column with wide adaptability, was found to have satisfactory separation and peak capacity. A series of mobile phases were investigated and the concentration of formic acid was optimized, including methanol-water, acetonitrile-water, acetonitrile-0.1% (V/V) formic acid aqueous solution, acetonitrile-0.2% (V/V) formic acid aqueous solution, and 0.2% (V/V) formic acid acetonitrile-0.2% (V/V) formic acid aqueous solution. The results showed that 0.2% (V/V) formic acid in acetonitrile-0.2% (V/V) formic acid solution in water could achieve better separation than other systems. The usual flow rate of 1 mL/min was used. In addition, different gradient curves were applied to improve the separation of NJP by changing the proportion of mobile phase during elution, and the optimal gradient was finally selected through several empirical attempts. The column temperature is another important parameter that needs to be controlled. The appropriate decrease of the column temperature is conducive to the improvement of the separation degree. According to the results, 30°C is selected as the best column temperature value. Representative chromatograms of each of the seven reference standards and typical samples at different wavelengths are shown in Fig. 2 . The analytes were identified by comparing their retention time and UV spectra with those of each reference standards. In addition, spiked sample and reference standards showed no additional peaks, which further confirmed the identity of the peaks. 3.2 Optimization of the Pretreatment Method. In order to improve the sensitivity and reliability of the method, pretreatment parameters such as extraction solvent, extraction method, extraction time and extraction solvent volume were optimized with the concentration of analytes as the standard. Different proportions of methanol in the range of 50%-100% (V/V) were used as the extraction solution for the experiment, and 90% (V/V) methanol was selected as the extraction solvent for further experiments based on the extraction rate of 7 detection indexes. In order to study the influence of extraction methods on extraction efficiency, ultrasonic treatment (500 W, 40 kHz) for 30 minutes and water bath heating reflux at 80 ℃ for 1 hour were compared. The results showed that the extraction efficiency of 7 detection indexes was obviously higher when heated under reflux. The reflux time was optimized in the range of 1 to 4 hours, and when the time exceeded 2 hours, the contents of all indexes reached dynamic balance. Therefore, 2 hours of extraction time was considered sufficient. Figure 2 summarized the HPLC fingerprints of 7 detection indexes of NJP sample extracts after all analytical procedures. 3.3 Verification of the HPLC Method. The specificity of the method was verified by comparing the HPLC chromatograms of the NJP control samples and the negative control samples without Angelicae Sinensis Radix (Danggui, ASR), Chuanxiong Rhizoma (Chuanxiong, CR) and Ligustici Rhizoma Et Radix (Gaoben, LRER), Paeoniae Radix Alba (Baishao, PRA) and Moutan Cortex (Mudanpi, MC), Cynanchi Atrati Radix Et Rhizoma (Baiwei, CARER), Glycyrrhizae Radix Et Rhizoma (Gancao, GRER), Cinnamomi Cortex (Rougui, CC), Scutellariae Radix (Huangqin, SR) and Citri Reticulatae Pericarpium (Chenpi, CRP). The seven analytes were well separated without interference (See Fig. 2 ), indicating that the selectivity of the method can be used for further quantification. The linearity of the method was verified by plotting the peak area (y) and the concentration of the reference standards (x). All the analytes have a good linear relationship, with correlation coefficients ( r ) > 0.9995. The LOD (S/N ≥ 3) and LOQ (S/N ≥ 10) of the seven analytes ranged from 0.14 to 0.35 µg/mL and from 0.48 to 1.16 µg/mL, respectively. The results of linearity, LOD, and LOQ are summarized in Table 3 . To confirm the precision, repeatability and accuracy of the method, intraday and interday precision, repeatability and recovery were tested and values was given in Table 4 . The relative standard deviations (RSDs) were below 2.0%, and the average recoveries for all the analytes were in the range of 97.5–101.8%. Therefore, this HPLC method is sensitive, precise, and accurate for quantification of multiple components in NJP. Table 3 Linear range, regression equation, coefficient of determination ( r ), LOD, and LOQ for HPLC analysis of seven analytes. Analyte Linear Range Regression Equation r LOD LOQ (mg/mL) y = ax + b (µg/mL) (µg/mL) Paeoniflorin 0.002–0.053 y = 1.41×10 6 x − 8.86×10 3 0.9998 0.21 0.71 Ferulic acid 0.001–0.013 y = 3.34×10 6 x − 9.19×10 2 1.0000 0.26 0.87 Hesperidin 0.006–0.146 y = 2.07×10 6 x − 2.20×10 4 1.0000 0.27 0.89 Baicalin 0.007–0.167 y = 3.30×10 6 x − 3.98×10 4 0.9999 0.35 1.16 Cinnamaldehyde 0.001–0.013 y = 7.46×10 6 x − 2.83×10 4 0.9998 0.26 0.88 Paeonol 0.002–0.041 y = 4.97×10 6 x − 1.65×10 4 0.9999 0.16 0.55 Glycyrrhizic acid 0.001–0.036 y = 3.11×10 5 x − 8.99×10 2 0.9998 0.14 0.48 Table 4 Precisions, repeatability, and recovery of seven analytes. Analyte Precisions Repeatability Recovery Intraday RSD(%,n = 6) Interday RSD(%,n = 3) RSD(%,n = 6) Mean(%) RSD(%,n = 6) Paeoniflorin 0.9 0.6 1.3 101.8 1.6 Ferulic acid 1.1 1.3 1.1 101.2 1.2 Hesperidin 1.0 0.9 0.5 98.6 0.9 Baicalin 1.6 0.9 0.8 97.5 1.9 Cinnamaldehyde 1.9 1.6 1.9 99.8 1.4 Paeonol 1.2 1.9 1.7 100.3 0.6 Glycyrrhizic acid 0.7 1.5 1.5 99.7 1.3 3.4 Simultaneous Determination of 7 Components in the Samples from Manufacturers. In the ChP 2020 edition, the markers of paeoniflorin, Angelica, ligusticum chuanxiong, ligustilia, tangerine bark, Scutellaria baicalensis, cinnamon, paeonol and glycyrrhizin were paeoniflorin, ferulic acid, hesperidin, baicalin, cinnamaldehyde, paeonol and glycyrrhizic acid respectively. According to the literature [ 18 – 27 ], these seven components are the active components of corresponding traditional Chinese medicine respectively. A total of 76 batches of NJP were quantified from 19 manufacturers (code A ~ S). As shown in Table 5 , the contents of 7 components in different samples were different. Heatmap generated by the Internet of Chinplot ( https://www.chiplot.online/ ) had a more intuitive display.Longitudinal characteristic peak clustering showed that the characteristic peaks could be divided into three categories (Fig. 3 ), in which Hesperidin and Baicalin were clustered into class I, Ferulic acid and Paeoniflorin were clustered into class II, and other ingredients were clustered into class III. It is well known that most Chinese medicine comes from cultivated herbs, and their content is inevitably affected by natural factors beyond their control. Therefore, the quality of Chinese medicinal materials can be reflected by the content of markers, but it is not necessarily proportional, but obviously lower content usually means poor quality of medicinal materials or insufficient raw materials. The contents of paeoniflorin, ferulic acid, hesperidin and baicalin varied gently with RSDs around 20%. Significant range of variations were observed for contents of cinnamaldehyde, paeonol and glycyrrhizic acid with RSDs above 40%. The variations indicated uneven quality of the raw materials and that would lead to differences in the intrinsic quality and efficacy of the commercial products. Table 5 Contents (mg/g) of 7 components in 76 batches of NJP (n = 2). No. Manufacturer Paeoniflorin Ferulic acid Hesperidin Baicalin Cinnamaldehyde Paeonol Glycyrrhizic acid 1 A1 0.41 0.04 1.48 1.02 0.22 0.19 0.30 2 A2 0.39 0.04 1.90 1.10 0.29 0.21 0.33 3 A3 0.32 0.04 2.07 1.09 0.67 0.26 0.42 4 B1 0.49 0.09 1.79 0.82 0.35 0.26 0.42 5 B2 0.51 0.08 1.79 1.02 0.39 0.22 0.36 6 B3 0.45 0.05 1.68 1.02 0.47 0.25 0.40 7 B4 0.41 0.06 1.68 1.00 0.46 0.27 0.43 8 B5 0.47 0.08 1.82 0.89 0.32 0.26 0.42 9 B6 0.34 0.08 1.72 0.87 0.41 0.19 0.31 10 B7 0.38 0.08 2.08 1.17 0.30 0.28 0.45 11 B8 0.36 0.07 2.01 1.27 0.34 0.29 0.46 12 B9 0.39 0.06 1.74 1.48 0.33 0.28 0.45 13 C1 0.57 0.07 1.53 1.23 0.40 0.27 0.44 14 C2 0.55 0.07 1.53 1.23 0.40 0.27 0.44 15 C3 0.57 0.07 1.53 1.23 0.40 0.27 0.44 16 C4 0.51 0.07 1.53 1.23 0.40 0.27 0.44 17 C5 0.61 0.07 1.53 1.23 0.40 0.27 0.44 18 D6 0.36 0.08 1.34 0.82 0.61 0.28 0.45 19 D7 0.39 0.08 1.31 1.34 0.33 0.27 0.42 20 D8 0.41 0.07 1.42 1.37 0.39 0.28 0.46 21 D9 0.42 0.07 1.35 1.45 0.39 0.29 0.39 22 D10 0.33 0.08 1.41 1.62 0.42 0.25 0.44 23 E1 0.32 0.08 1.31 1.05 0.15 0.18 0.28 24 F1 0.44 0.07 1.30 0.99 0.22 0.22 0.35 25 F2 0.49 0.07 1.54 1.10 0.23 0.26 0.42 26 F3 0.41 0.08 1.66 1.28 0.27 0.32 0.52 27 G1 0.55 0.08 1.42 1.57 0.26 0.21 0.33 28 G2 0.51 0.05 1.87 1.42 0.32 0.25 0.40 29 G3 0.50 0.07 1.91 1.42 0.52 0.24 0.38 30 G4 0.50 0.08 2.12 1.43 0.71 0.27 0.43 31 G5 0.39 0.07 1.80 1.63 0.81 0.25 0.40 32 H1 0.24 0.01 1.25 0.60 1.29 0.95 1.51 33 H2 0.31 0.04 1.36 1.66 0.42 0.91 1.46 34 H3 0.41 0.03 1.42 1.72 0.51 0.89 1.42 35 I4 0.24 0.06 1.61 1.01 0.20 0.31 0.49 36 I5 0.42 0.05 1.56 1.82 0.31 0.36 0.58 37 J1 0.45 0.06 2.06 1.11 0.36 0.25 0.40 38 J2 0.46 0.07 1.85 1.19 0.65 0.32 0.51 39 J3 0.62 0.06 2.09 1.61 0.20 0.27 0.43 40 J4 0.55 0.06 1.76 1.43 0.41 0.25 0.40 41 J5 0.53 0.06 1.78 1.51 0.92 0.35 0.56 42 J6 0.53 0.06 1.79 1.19 0.32 0.25 0.40 43 J7 0.53 0.06 1.86 1.07 0.34 0.26 0.42 44 J8 0.51 0.06 1.88 1.25 0.28 0.26 0.42 45 K1 0.38 0.08 1.37 1.43 0.32 0.26 0.42 46 K2 0.29 0.05 1.36 1.39 0.35 0.25 0.31 47 K3 0.34 0.05 1.56 1.52 0.21 0.29 0.40 48 L1 0.41 0.08 2.12 1.31 0.33 0.26 0.46 49 L2 0.38 0.08 1.63 1.42 0.37 0.31 0.33 50 L3 0.42 0.05 2.17 1.29 0.42 0.36 0.43 51 L4 0.41 0.07 1.89 1.36 0.32 0.34 0.47 52 L5 0.33 0.06 1.92 1.46 0.33 0.29 0.55 53 L6 0.34 0.07 1.77 1.52 0.35 0.42 0.42 54 M1 0.41 0.04 2.02 1.63 0.41 0.56 0.24 55 M2 0.39 0.05 1.53 1.42 0.42 0.48 0.44 56 M3 0.32 0.04 1.56 1.33 0.44 0.52 0.34 57 N1 0.24 0.06 1.62 1.42 0.22 0.25 0.29 58 N2 0.35 0.05 1.61 1.26 0.32 0.26 0.46 59 N3 0.42 0.09 1.33 1.31 0.33 0.31 0.54 60 O1 0.37 0.07 1.33 1.31 0.31 0.29 0.42 61 O2 0.31 0.06 1.42 1.29 0.37 0.33 0.37 62 O3 0.43 0.06 1.36 1.42 0.35 0.28 0.46 63 P1 0.32 0.06 2.21 1.39 0.42 0.31 0.41 64 P2 0.39 0.06 2.15 1.42 0.38 0.32 0.34 65 P3 0.27 0.06 2.11 1.55 0.31 0.27 0.43 66 Q1 0.38 0.06 1.91 1.56 0.22 0.25 0.35 67 Q2 0.33 0.07 1.52 1.62 0.27 0.26 0.41 68 Q3 0.41 0.06 1.69 1.58 0.37 0.21 0.43 69 R1 0.37 0.07 1.69 1.57 0.42 0.33 0.37 70 R2 0.32 0.05 1.67 1.62 0.39 0.32 0.41 71 R3 0.35 0.06 1.68 1.26 0.33 0.39 0.24 72 S1 0.31 0.06 1.63 1.23 0.36 0.21 0.28 73 S2 0.35 0.06 1.75 1.36 0.37 0.19 0.42 74 S3 0.38 0.05 1.97 1.52 0.33 0.17 0.34 75 S4 0.36 0.05 1.65 1.26 0.34 0.21 0.42 76 S5 0.34 0.06 1.69 1.42 0.35 0.28 0.34 Median 0.39 0.06 1.68 1.34 0.35 0.27 0.42 Mean 0.41 0.06 1.69 1.32 0.39 0.31 0.45 RSD(%) 21.4 22.5 15.1 17.9 43.3 46.1 48.5 3.5 Explore the Anti-PCOS Activity of Focused Compounds . We employed network pharmacology to explore the correlation between the 7 identifified compounds and their Anti-PCOS activity.[ 28 ] According to PPI analysis, the core targets were inputted into the network visualization software Cytoscape 3.9.0 to build the following network (Fig. 4A) which had 51 nodes and 480 edges. With regard to the degree analysis, the top six gene target were AKT1, TNF, PTGS2, IL1B, CASP3, EGFR and wighteone with 41-degree, 37-degree, 33-degree, 33-degree, 32-degree and 32-degree respectively. It was suggested that these proteins may be the key core targets of Anti-PCOS of 7 focused compounds. To deeply explore the underlying mechanism of 7 ingredients with large differences in content, GO and KEGG enrichment analyses were conducted with the Metascape platform. A total of 1051 terminologies related to biological events were chosen, specififically included positive regulation of cell migration, positive regulation of cell motility, positive regulation of cellular component movement, positive regulation of locomotion, positive regulation of cell death, etc. Concerning the enrichment analysis of cellular components, the targets were comprised of the membrane raft, membrane microdomain. Concurrently, the molecular function terms primarily comprised kinase activity, phosphotransferase activity, kinase binding, and so on (Fig. 4B). The main effects linked to the NJP of focused 7 compounds were grouped using the KEGG pathway enrichment analysis. 165 pathways were obtained from the KEGG database. A sum of 25 top-ordered pathways (Fig. 4C) were screened out (p < 0.05). Among them, the most important pathways included the Lipid and atherosclerosis signaling pathway, AGE RAGE signaling pathway, Hepatitis B signaling pathway, and other pathways. These results indicated that all the 7 compounds exhibit potential pharmacological activity associated with the treatment of Polycystic ovary syndrome. 3.6 Grade Evaluation of Nvjin Pills . To evaluate the “excellence or inferior grade” of NJP, the traditional Chinese medicine standard (TCMRD) was introduced into the multi-component analysis of TCM decoction pieces using authentic and high quality Chinese medicinal materials(CMM), in strict accordance with the prescription and technology, and in compliance with GMP.The source, harvesting time and processing method of CMM were identified according to legal standards. It was necessary to further investigate the true growing environment, medicinal resources and quality status, then, purchase real raw materials from correct original plants and grow under good agricultural practices (GAP). The selected CMM was tested separately to meet its statutory standards. In addition, other tests were conducted to eliminate safety risks such as pesticide residues, heavy metals, mycotoxins, sulfur dioxide, adulteration, and illegal staining. Finally, the production of NJP reference materials are carried out in strict accordance with the provisions of GMP, and all raw materials are in accordance with the official legal standards of crushing, or the amount after crushing. To compensate for the inevitable fluctuation of components in CMM, three batches of TCMRDs were made from authentic, high-quality and standardized Chinese herbal decoction pieces from three different suppliers. Then the TCMRDs and their corresponding raw materials were determined by the same HPLC method for the NJP samples. As indicated in Table 6 , variations were found in contents of the seven markers in three batches of TCMRD, especially hesperidin, cinnamaldehyde and glycyrrhizic acid. Those might be due to naturally existed fluctuation of chemical components and the different growth years of Citri Reticulatae Pericarpium (Chenpi, CRP), Cinnamomi Cortex (Rougui, CC) and Moutan Cortex (Mudanpi, MC). Nevertheless, the transfer rates of all the analytes were stable, which provided valuable information for formulating grading limits. Table 6 Contents and transfer rates of 7 components in NJP Reference Drugs (n = 2). Analyte Paeoniflorin Ferulic acid Hesperidin Baicalin Cinnamaldehyde Paeonol Glycyrrhizic acid Reference Drug 1 Contents (mg/g) 0.68 0.04 0.83 2.04 0.63 0.29 0.75 Transfer rates (%) 95.7 88.8 97.6 94.5 82.1 97.7 95.3 Reference Drug 2 Contents (mg/g) 0.34 0.07 1.35 1.62 0.35 0.44 0.45 Transfer rates (%) 94.9 90.2 96.2 94.2 82.4 95.9 94.2 Reference Drug 3 Contents (mg/g) 0.45 0.08 1.97 1.34 0.23 0.50 0.23 Transfer rates (%) 96.5 89.2 95.9 93.4 81.5 96.6 93.3 Mean Contents (mg/g) 0.49 0.06 1.38 1.67 0.40 0.41 0.48 Transfer rates (%) 95.7 89.4 96.6 94.0 82.0 96.7 94.3 RSD(%) Contents (mg/g) 35.9 37.8 41.3 21.1 50.8 26.6 55.1 Transfer rates (%) 0.8 0.8 0.9 0.6 0.6 0.9 1.1 In general, the product quality grade refers to the first and second grade products should be specified. The second grade refers in principle to the level of quality to be achieved using a predetermined quantity of qualified raw materials and standardized manufacturing processes. The first grade refers to the level of quality to be achieved through the use of high-quality raw materials, predetermined quantities and standardized manufacturing processes. In this study, hesperidin, baicalin, cinnamaldehyde and glycyrrhizic acid were used as the quality evaluation indexes of Citri Reticulatae Pericarpium (Chenpi, CRP), Scutellariae Radix (Huangqin, SR), Cinnamomi Cortex (Rougui, CC) and Glycyrrhizae Radix Et Rhizoma (Gancao, GRER) in NJP. The minimum values of these four markers and the maximum moisture values in the corresponding CMM are specified in ChP 2020. The second-grade limits of hesperidin, baicalin, cinnamaldehyde and glycyrrhizic acid in NJP were calculated as following: minimum limit of the marker in the corresponding CMM% × (100%-maximum limit of water in the corresponding CMM%) × proportion of the corresponding CMM in NJP% × average transfer rate of the marker in the NJP%. The first-grade limits of hesperidin, baicalin, cinnamaldehyde and glycyrrhizic acid in NJP were specified comparing with the median contents in 76 batches of samples and their mean contents in 3 batches of TCMRDs, based on dispersion of the data. If the mean contents were larger than the median contents, the first-grade limits were specified as 80% of the mean contents. On the contrary, the first grade limits were specified as the mean contents. As for paeoniflorin, ferulic acid and paeonol, these three indicative components exist in the multi-CMMs in the herbal formula of NJP, but their minimum limits in the corresponding CMM are not specified all, and their contents vary greatly [ 29 – 38 ]. Therefore, the second grade limit for the three markers in NJP was specified as 60% of their mean contents in three TCMRDs. On the basis of comprehensive analysis, the quality grade specifications of 7 markers in NJP are listed in Table 7 . Accordingly, 76 batches of samples from 19 manufacturers were preliminarily divided into three quality grades: 16 batches of first grade, 47 batches of second grade, and 13 batches unqualified. Table 7 Quality grade specifications of the seven markers and quality rating results of NJP. Analyte First Grade Second Grade Specification Batches Qualified Batches Qualified All 7 Specifications Specification Batches Qualified Batches Qualified All 7 Specifications Paeoniflorin N/A N/A 16 ≥ 0.29mg/g 72 47 Ferulic acid N/A N/A ≥ 0.04mg/g 74 Hesperidin ≥ 1.38mg/g 66 ≥ 0.62mg/g 76 Baicalin ≥ 1.33mg/g 39 ≥ 0.98mg/g 71 Cinnamaldehyde ≥ 0.32mg/g 58 ≥ 0.16mg/g 75 Paeonol N/A N/A ≥ 0.25mg/g 63 Glycyrrhizic acid ≥ 0.38mg/g 56 ≥ 0.22mg/g 76 4 Conclusions In conclusion, a new principle of multi-component analysis and evaluation was used to evaluate the quality grade of the compound Chinese herbal medicine (CCHM). In this study,7 compounds in NJP, including Paeoniflorin, Ferulic acid, Hesperidin, Baicalin, Cinnamaldehyde, Paeonol, Glycyrrhizic acid, were identified by high performance liquid chromatography (HPLC) method combined with wavelength switching. A sensitive and accurate method for simultaneous determination of 7 markers in NJP was established. The specificity, linearity, LOD, LOQ, precision and accuracy of the method were verified and used for the analysis of NJP samples and TCMRD. The Anti-PCOS components in NJP were mined through network pharmacology for the first time,which provided the basis for the quantitative analysis of NJP. Taking into account the measurement results and the quality status of the corresponding CMM, the specifications of the first grade and the second grade were put forward, and the samples were classified on the basis of this. With combination of results obtained from former safety examinations, according to the overall strategy, the listed samples are graded to distinguish between "good" and "bad". The challenge posed by the great variability of a few markers in reference drugs deserves further and deeper study. Declarations Data Availability The data used to support the fifinding of this study are available from the corresponding author upon request. Conflicts of Interest The authors declare that there is no conflict of interest regarding the publication of this paper. Authors’ Contributions Yongqiang Lin and Guangzhen Liu conceived and designed the study. Lin Lin wrote the article and analyzed data. Dexin Zhang, Fengrui Yu, Lejun Tan, Xiangrong Mu revised the article. Acknowledgments This project was funded by Shandong Institute for Food and Drug Control, Shandong Engineering Laboratory for Standard Innovation and Quality Evaluation of TCM. References Wang WY, Zhou H, Wang YF, Sang BS, Liu L (2021) Current Policies and Measures on the Development of Traditional Chinese Medicine in China. Pharmacol Res 163:105187. Cyranoski D (2018) Why Chinese medicine is heading for clinics around the world. Nature 561:448-450. Dong ZW, Tian MY, Zhao YM, Wang C, Wang HF, Wang J, Huang QW (2022) Grading of rhizoma coptidis based on appearance trait and intrinsic quality correlation and multivariate statistical analysis. WJTCM 17:1214-1219. Wei ZJ, Ren XH, Zhang Y, Dai X, Guo R, Zhao ZH, Liu LL, Liu Y, Li WD (2022) Study on quality grade standard of premature Forsythia suspensa. J China Pharm 33: 842-847. Xie XT, Huang P, Zhou GL, Wang Q, Wang NB, Guan SQ, Lu QT (2021) Evaluation of quality grade of Guangjincao decoction pieces based on PLS regression analysis. Li shizhen Med Mater Med Res 32:1749-1752. Nie LX, Qian XY, Zhang Y, Wei F, Dai Z, Ma SC (2021) Discussion on the research principles and methods of the quality grade standard of proprietary Chinese medicine. J Shenyang Pharm Univ 38:1327-1333. Ding RW, Wei HZ, Lv S, Song XZ, Qi JF, Jin HX, Cao YX, RaoY (2021) Study on quality grade of plantaginis Semen based on multivariate statistical analysis. Chin Arch Tradit Chin Med 38:673-679. Nie LX, Dai Z, Ma SC (2017) Guideline principle and technical requirement for preparing traditional Chinese medicine reference. China J Chin Mater Med 42:3672–3675. Nie LX, Zha YF, Yu JD, Shuai K, Zhong D, Ma SC, Kelvin C (2022) Quality Grade Evaluation of Niuhuang Qingwei Pills Based on UPLC and TCM Reference Drug-A Novel Principle of Analysis of Multiple Components in Ready-Made Chinese Herbal Medicine. Processes 10: 1166. ChP 2020 edition: Beijing China 2020. Liu AM (2011) "Nvjin Pill" a good medicine for gynecology. Neimengggu J Tradit Chin Med 30:123. Lin L, Yu FR, Xu LH, Lin YQ (2019) HPLC fingerprintcluster analysis and principal component analysis of Nvjin Pills. J China Pharm 30:1339-1343. Lin L, Liu GZ, Yu FR, Xu LH (2018) Simultaneous determination of twelve constituents in Nvjin Pills by HPLC combined with wavelength switching. Chin Pharm J 53:1511-1515. Lin YQ, Liu GZ, Xu LH, Lin L (2019) Study of HPLC fingerprint in Nvjin Pill. Chin J Mod Appl Pharm 36:456-460. Lin L, Yu FR, Xu LH, Lin YQ (2018) Content Determination of 7 Volatile Components in Nvjin Pill by GC. Chin J Exp Tradit Med Form 24:73-77. Dai J, Yang XJ, Hao PP, Feng L, Li JC (2010) Study on TLC identification method of Nvjin Pill. CHIN TRADIT PAT MED 32:2021-2025. Chandran S, Singh RS (2007) Comparison of various international guidelines for analytical method validation. Die Pharmazie-An International Journal of Pharmaceutical Sciences 62: 4-14. Kudoh C, Hori T, Yasaki S, Ubagai R, Tabira T (2020) Effects of Ferulic Acid and Angelica archangelica Extract (Feru-guard ®) on Mild Cognitive Impairment: A Multicenter, Randomized, Double-Blind, Placebo-Controlled Prospective Trial. J Alzheimers Dis Rep 4:393-398. Yan N, Tang Z, Xu Y, Li X, Wang Q (2020) Pharmacokinetic Study of Ferulic Acid Following Transdermal or Intragastric Administration in Rats. AAPS PharmSciTech 21:169. Liu JS, Zhang XY, Li B, Wei XP, Qi YD, Liu HT, Zhang BG (2022) Anti-inflammatory active component in raw materials of Ligustici Rhizoma et Radix based on spectrum-effect relationship. CHIN TRADIT PAT MED 47:3295-3302. Park HR, Choi HJ, Kim BS, Chung TW , Kim KJ , Joo JK , Ryu D , Bae SJ , Ha KT (2021) Paeoniflorin Enhances Endometrial Receptivity through Leukemia Inhibitory Factor. Biomolecules 11:439. Yuan Y, Yu J, Jiang C, Li MH, Lin SF, Wang XM, Huang LQ (2013) Functional diversity of genes for the biosynthesis of paeoniflorin and its derivatives in Paeonia. Int J Mol Sci 14:18502-18519. Su YS, Zhang XY, Guo QM (2021) Advances in chemical constituents and pharmacology of Baiwei(Cynanchi Atrati Radix et Rhizoma). Chin Arch Tradit Chin Med 39:171-177. Chen M, Zhu J, Kang J, Lai X, Gao Y, Gan H, Yang F (2019) Exploration in the Mechanism of Action of Licorice by Network Pharmacology. Molecules 24:2959. Lee JH, Kwak HJ, Shin D, Seo HJ, Park SJ, Hong BH, Shin MS, Kim SH, Kang KS (2022) Mitigation of Gastric Damage Using Cinnamomum cassia Extract: Network Pharmacological Analysis of Active Compounds and Protection Effects in Rats. Plants (Basel) 11:716. Shah M, Mubin S, Hassan SSU, Tagde P, Ullah O, Rahman MH, Al-Harrasi A, Rehman NU, Murad W (2022) Phytochemical Profiling and Bio-Potentiality of Genus Scutellaria: Biomedical Approach. Biomolecules 12:936. K. Pyrzynska (2022) Hesperidin: A Review on Extraction Methods, Stability and Biological Activities. Nutrients 14: 2387. Xue M, Zhao Y, Cui Y, Yang J, Wang Y, Chai X (2022) Quantitative Analysis of Multicomponents in Qufeng Zhitong Capsule and Application of Network Pharmacology to Explore the Anti-Inflammatory Activity of Focused Compounds. J Anal Methods Chem 2022, Article ID 4229945. Zhang K, Yan M, Han S, Cong L, Wang L, Zhang L, Sun L, Bai H, Wei G, Du H, Jiang M, Bai G, Yang Z (2019) Identification of Chemical Markers for the Discrimination of Radix Angelica sinensis Grown in Geoherb and Non-Geoherb Regions Using UHPLC-QTOF-MS/MS Based Metabolomics. Molecules 24:3536. Liu JL, Zheng SL, Fan QJ, Yuan JC, Yang SM, Kong FL (2014) Optimization of high-pressure ultrasonic-assisted simultaneous extraction of six major constituents from Ligusticum chuanxiong rhizome using response surface methodology. Molecules 19:1887-1911. Liang H, Pan XJ, Lv WS, Liang WH (2021) Fingerprint Establishment of Rhizoma Ligustici from Different Origins and Their Chemometrics Analysis. J China Pharm 32: 2358-2362. Jo BG, Kang KH, Yang MH (2020) Development and Validation of a HPLC-PDA Method for the Simultaneous Determination of Berberine Palmatine Geniposide and Paeoniflorin in Haedoksamul-tang. Appl Sci 10:5482. Li RR, Liu HX, Peng PH, Hu XR (2021) Study on UPLC fingerprint of Paeonia decomposita- cortex and simultaneous determination of four components. CHINA MEASUREMENT & TEST 47:77-82. Xia CK, Zhan YW, Hu YF, Fang CW (2019) Simultaneous determination of thirteen components of Mortan Cortex in different regions by HPLC. Chin Tradit Herbal Drugs 50:970-974. Xiang H, Zhang L, Song J, Fan B, Nie Y, Bai D, Lei H (2016) The Profiling and Identification of the Absorbed Constituents and Metabolites of Guizhi Decoction in Rat Plasma and Urine by Rapid Resolution Liquid Chromatography Combined with Quadrupole-Time-of-Flight Mass Spectrometry. Int J Mol Sci 17:1409. Farag MA, Khaled SE, El Gingeehy Z, Shamma SN, Zayed A (2022) Comparative Metabolite Profiling and Fingerprinting of Medicinal Cinnamon Bark and Its Commercial Preparations via a Multiplex Approach of GC-MS, UV, and NMR Techniques. Metabolites 12: 614. Chen JC, Wu HL,Wang T, Dong MY, Chen Y, Yu RQ (2022) High-Performance Liquid Chromatography-Diode Array Detection Combined with Chemometrics for Simultaneous Quantitative Analysis of Five Active Constituents in a Chinese Medicine Formula Wen-Qing-Yin. Chemosensors 10: 238. Liu LC, Wang XY, Li LN, Yang L, Wang ZT (2022) Research advances of chemical constituents and analytical methods of Citri Reticulatae Pericarpium Viride and Citri Reticulatae Pericarpium.China J. Chin. Mater. Med 47: 2866-2879. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2531631","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":172978587,"identity":"db8a5ba9-75d7-4fc0-95db-4522a704efd2","order_by":0,"name":"Lin Lin","email":"","orcid":"","institution":"Shandong Institute for Food and Drug Control","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Lin","suffix":""},{"id":172978588,"identity":"0dd3d405-7087-43ee-bdcb-02bd79beea04","order_by":1,"name":"guangzhen liu","email":"","orcid":"","institution":"Shandong Institute for Food and Drug Control","correspondingAuthor":false,"prefix":"","firstName":"guangzhen","middleName":"","lastName":"liu","suffix":""},{"id":172978589,"identity":"14e3352e-1286-4be6-818a-53520e8dc66e","order_by":2,"name":"zhang dexin","email":"","orcid":"","institution":"Shandong Institute for Food and Drug Control","correspondingAuthor":false,"prefix":"","firstName":"zhang","middleName":"","lastName":"dexin","suffix":""},{"id":172978590,"identity":"40b3e014-e6f4-418c-b08c-fccb3019c7f4","order_by":3,"name":"fengrui yu","email":"","orcid":"","institution":"Shandong Institute for Food and Drug Control","correspondingAuthor":false,"prefix":"","firstName":"fengrui","middleName":"","lastName":"yu","suffix":""},{"id":172978591,"identity":"4291bf03-c849-46e0-b5e7-9dba0240f36a","order_by":4,"name":"lejun tan","email":"","orcid":"","institution":"Shandong Institute for Food and Drug Control","correspondingAuthor":false,"prefix":"","firstName":"lejun","middleName":"","lastName":"tan","suffix":""},{"id":172978592,"identity":"93205ba8-f6d2-4dbe-9460-30e35aa9908b","order_by":5,"name":"xiangrong mu","email":"","orcid":"","institution":"Shandong Institute for Food and Drug Control","correspondingAuthor":false,"prefix":"","firstName":"xiangrong","middleName":"","lastName":"mu","suffix":""},{"id":172978593,"identity":"dd676a2a-ee36-4f91-958a-c7aef60663aa","order_by":6,"name":"yongqiang lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYBACNv7mgw8kDGzq25gZEh8kVNQQ1sIncSzZwKIijbGPveGxwYMzxwhrkWPIMROoOHOIcR7PwWeSD1uYiXAYw7E0hpttB5jZJJLTKhIb2Bj427sT8Gthbj72cGbbHTY2ibS0G4k7ZBgkzpzdQMiWdGPJtmc8bBI5QC1n2BgMJHIJackxk/7bdliCTSL/W0EiMNyI0iIhceawARvPgTQG4rSAAlmiIi2Bjb0hWSLhzDEegn6R74dEZYJ8M0Pixx8VNXL87b34tWAAHtKUj4JRMApGwSjACgDf+Ut6zQpOXQAAAABJRU5ErkJggg==","orcid":"","institution":"Shandong Institute for Food and Drug Control","correspondingAuthor":true,"prefix":"","firstName":"yongqiang","middleName":"","lastName":"lin","suffix":""}],"badges":[],"createdAt":"2023-01-31 00:59:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2531631/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2531631/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":32533190,"identity":"483a7856-1cbd-470b-9eba-87f8170b9fec","added_by":"auto","created_at":"2023-02-06 14:46:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":808525,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram illustrating the overall procedures for quality grade evaluation of Nvjin Pills.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2531631/v1/c150949155aaceacf4136625.png"},{"id":32534312,"identity":"10ecdd4d-1312-40e4-b2fc-199c18183a21","added_by":"auto","created_at":"2023-02-06 14:54:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81594,"visible":true,"origin":"","legend":"\u003cp\u003eChromatograms of the reference solutions of paeoniflorin (1), ferulic acid (2), hesperidin (3), baicalin (4), cinnamaldehyde (5), Paeonol (6), glycyrrhizic acid (7) and the sample solution of NJP (s) was set at 230 nm (A), 316 nm (B), 283 nm (C), 280 nm (D), 290 nm (E), 274 nm (F) and 237 nm (G), respectively.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2531631/v1/ae0692b88e1b2ce2521269cf.png"},{"id":32534313,"identity":"86ebe1f4-6045-4935-a489-61a16822f4be","added_by":"auto","created_at":"2023-02-06 14:54:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":582115,"visible":true,"origin":"","legend":"\u003cp\u003eResult of heat map analysis on the determination of 76 batches of NJP from 19 manufacturers.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-2531631/v1/b453144bd54937fa4edb6877.png"},{"id":32533191,"identity":"be673fe9-4281-4e45-9fdc-fe40e98bf752","added_by":"auto","created_at":"2023-02-06 14:46:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":636488,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork pharmacological analysis of NJP: (A) PPI network, (B) GO enrichment analyze, and (C) KEGG enrichment analyze.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-2531631/v1/63ee22738f3a57e0868b5506.png"},{"id":32596535,"identity":"fc423122-6d8d-4dff-957f-3bfba2308b77","added_by":"auto","created_at":"2023-02-07 15:14:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1455233,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2531631/v1/e85aad1c-9c0c-4c59-ad7d-d00371108fd6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quality Grade Evaluation of Nvjin Pills Based on TCMRD and Application of Network Pharmacology to Explore the Anti- Polycystic Ovarian Syndrome Activity of Focused Compounds","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe compound Chinese herbal medicine (CCHM) is frequently used in traditional Chinese medicine (TCM) treatment in China and some parts of the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A typical CCHM is usually composed of two or more processed-Chinese materia medica (CMM) containing numerous chemical components. With the progress of chemical analysis technology, it is not difficult to determine the authenticity of CCHM. But, due to the uneven quality of the initially used processed-CMM and different quality control capabilities of the manufacturers, the quality of CCHM may vary significantly.\u003c/p\u003e \u003cp\u003eIn this case, the author proposed TCMRD as the standard formula of Chinese medicine control, and developed the quality grade evaluation system. TCMRD refers to the physical reference made of authenticated and standardized decoction pieces and auxiliary materials. The reference drug was prepared in strict accordance with legal procedures and production technology, and in accordance with good manufacturing practice (GMP). It is mainly used for quality evaluation and grading of CCHM to evaluate the authenticity of drug administration (including correct raw materials) and the reliability of drug dosage (whether complete drug administration is based on compound type). At present, quality grade research has become a hot spot and new field of TCM research [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e],which requires more innovative methods and more systematic and in-depth work to provide reasonable theory and feasible application.\u003c/p\u003e \u003cp\u003eCCHM is a compound synergistic Chinese herbal formula, so in the preparation process, the different properties of the chemical components contained may affect each other. TCMRD is prepared in strict accordance with prescription and corresponding preparation procedures and can provide critical information including actual background and transfer rate of ingredients from raw material to preparation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, TCMRD can be used as a measuring scale to evaluate CCHM products and a powerful means to solve the uneven quality of TCM products, showing a broad application prospect in the quality control, evaluation and grading of TCM products[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNvjin Pills (NJP) is a typical proprietary Chinese medicine, which is included in the Chinese Pharmacopoeia (ChP)2020 edition [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. It is used to treat menstrual irregularities, menstrual pain caused by deficiency of qi and blood, qi stagnation and blood stasis. Polycystic ovary syndrome (PCOS) is the most common gynecological disease caused by abnormal immune function and endocrine disorders, mainly characterized by abnormal ovulation, hyperandrogenemia and polycystic changes of ovary. Without early diagnosis and effective treatment, it will seriously affect the reproductive function of patients and lead to infertility [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. NJP is a compound preparation for regulating menstruation and nourishing blood, consisting of 23 Chinese herbs (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), Which proves NJP has various flavors, complex ingredients, mutual interference and intricate prescription composition. Therefore, to control its quality level in terms of ensuring safety, effectiveness, stability, etc., both the quality of medicinal materials and drug specifications should be standardized. Qualitative and quantitative analysis of NJP by high performance liquid chromatography (HPLC) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], gas chromatography (GC) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and thin layer chromatography (TLC)has been reported [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, there is no research on the simultaneous determination of multiple components for commercial CCHM quality rating.\u003c/p\u003e \u003cp\u003eUsing TCMRD, all 23 Chinese herbs could be detected by microscopy, TLC, UPLC-MS, X-ray diffraction and other methods. In this study, a simultaneous analysis for comprehensive quality evaluation of 9 CMMs, including Glycyrrhizae Radix Et Rhizoma (Gancao, GRER), Cinnamomi Cortex (Rougui, CC), Moutan Cortex (Mudanpi, MC), Scutellariae Radix(Huangqin, SR), Citri Reticulatae Pericarpium (Chenpi, CRP), Paeoniae Radix Alba (Baishao, PRA), Angelicae Dahuricae Radix (Baizhi, ADR), Chuanxiong Rhizoma (Chuanxiong,CR) and Ligustici Rhizoma Et Radix (Gaoben,LRER) in the NJP using 7 markers (glycyrrhizic acid, cinnamaldehyde, paeonol, baicalin, hesperidin, paeoniflorin and ferulic acid) was developed using high-performance liquid chromatography (HPLC) coupled with wavelength switching, which was also used to assay 3 batches of TCMRDs for NJP and 76 batches of commercial products from 19 manufacturers. Besides, the relationship between the 7 compounds and their key targets treatment of PCOS investigated by network-based pharmacology analytical approaches, which provided the basis for the quantitative analysis of NJP. On the basis of comprehensive analysis of the results, the quality grading standard of NJP was put forward, and the samples were graded accordingly to distinguish good products from bad ones. The integrated strategy of multi-component analysis by HPLC and TCMRD to evaluate quality grade of NJP was demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFormulation information of Nvjin Pills.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIngredient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDosage (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIngredient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDosage (g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAngelicae Sinensis Radix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCorydalis Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaeoniae Radix Alba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLigustici Rhizoma Et Radix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChuanxiong Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAngelicae Dahuricae Radix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRehmanniae Radix Praeparata\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eScutellariae Radix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCodonopsis Radix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCynanchi Atrati Radix Et Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAtractylodis Macrocephalae Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCyperi Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoria cocos\u0026nbsp;(Schw.)Wolf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAmomi Fructus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlycyrrhizae Radix Et Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCitri Reticulatae Pericarpium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCinnamomi Cortex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHalloysitum Rubrum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2 Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1\u0026nbsp;Materials\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e.\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e76 batches of Nvjin Pills (NJP) from 19 manufacturers were collected via National \u0026nbsp;Post-market Drug Surveillance. All samples are manufactured in accordance with legal standards [10] and approved by the manufacturers. Respectively, 3 batches of authentic, high-quality and standardly processed CMMs, including Angelicae Sinensis Radix (Danggui, ASR), Paeoniae Radix Alba\u0026nbsp;(Baishao, PRA),\u0026nbsp;Chuanxiong Rhizoma\u0026nbsp;(Chuanxiong, CR), Rehmanniae Radix Praeparata (Shudihuang, RRP), Codonopsis Radix (Dangshen, CR), Atractylodis Macrocephalae Rhizoma (Baizhu, AMR), Poria cocos (Schw.)Wolf \u0026nbsp;(Fuli, PcW),\u0026nbsp;Glycyrrhizae Radix Et Rhizoma\u0026nbsp;(Gancao, GRER),\u0026nbsp;Cinnamomi Cortex\u0026nbsp;(Rougui, CC), Leonuri Herba(Yimucao, LH),\u0026nbsp;Moutan Cortex\u0026nbsp;(Mudanpi, MC), Myrrha, Corydalis Rhizoma (Yanhusuo, CR),\u0026nbsp;Ligustici Rhizoma Et Radix\u0026nbsp;(Gaoben, LRER), Angelicae Dahuricae Radix (Baizhi, ADR),\u0026nbsp;Scutellariae Radix\u0026nbsp;(Huangqin, SR), Cynanchi Atrati Radix Et Rhizoma (Baiwei, CARER), Cyperi Rhizoma (Fuzi, CR), Amomi Fructus (Sharen, AF),\u0026nbsp;Citri Reticulatae Pericarpium\u0026nbsp;(Chenpi, CRP), Halloysitum Rubrum (Chishizhi, HR), Cervi Cornu Degelatinatum (Lujiaoshuang, CCD) and Asini Corii Colla (Ejiao, ACC) were bought from 3 different Chinese herbal medicine markets (Bozhou Chinese herbal medicine market (Bozhou, China); Anguo Chinese herbal medicine market (Anguo, China) and Lotus Pond Chinese herbal medicine market (Chengdu, China)). The origin of each CMM was authenticated by Professor Xigui Song using character and microscopic identification according to the Chinese Pharmacopoeia, edition 2020 (ChP, 2020 Edition). The results of chemical analysis performed by the authors indicated that all the CMMs met their own national drug standards. For future reference, the specimens were deposited at the Traditional Chinese Medicine Herbarium, Shandong Institute for food and drug control (Jinan, China). Refined honey, the excipient of the big honeyed pills, was purchased from Beijing Tongrentang Co., Ltd. (Beijing, China).\u0026nbsp;The materials and methods section should contain sufficient detail so that all procedures can be repeated. It may be divided into headed subsections if several methods are described.\u003c/p\u003e\n\u003cp\u003eStrictly complied with the statutory production process and GMP requirements, 3 batches of TCMRD for NJP were prepared. The primary procedure was as follows [10]: Angelicae Sinensis Radix (Danggui, ASR), Paeoniae Radix Alba\u0026nbsp;(Baishao, PRA),\u0026nbsp;Chuanxiong Rhizoma\u0026nbsp;(Chuanxiong, CR), Rehmanniae Radix Praeparata (Shudihuang, RRP), Codonopsis Radix (Dangshen, CR), Atractylodis Macrocephalae Rhizoma (Baizhu, AMR), Poria cocos (Schw.)Wolf \u0026nbsp;(Fuli, PcW),\u0026nbsp;Glycyrrhizae Radix Et Rhizoma\u0026nbsp;(Gancao, GRER),\u0026nbsp;Cinnamomi Cortex\u0026nbsp;(Rougui, CC), Leonuri Herba(Yimucao, LH),\u0026nbsp;Moutan Cortex\u0026nbsp;(Mudanpi, MC), Myrrha, Corydalis Rhizoma (Yanhusuo, CR),\u0026nbsp;Ligustici Rhizoma Et Radix\u0026nbsp;(Gaoben, LRER), Angelicae Dahuricae Radix (Baizhi, ADR),\u0026nbsp;Scutellariae Radix\u0026nbsp;(Huangqin, SR), Cynanchi Atrati Radix Et Rhizoma (Baiwei, CARER), Cyperi Rhizoma (Fuzi, CR), Amomi Fructus (Sharen, AF),\u0026nbsp;Citri Reticulatae Pericarpium\u0026nbsp;(Chenpi, CRP), Halloysitum Rubrum (Chishizhi, HR), Cervi Cornu Degelatinatum (Lujiaoshuang, CCD) and Asini Corii Colla (Ejiao, ACC) were pulverized to fine powder, then were sifted and mixed well. Honey pills are made by adding 135 grams of refined honey for every 100 grams of the mixture. For specificity validation, negative control without Angelicae Sinensis Radix\u003cem\u003e\u0026nbsp;\u003c/em\u003e(Danggui, ASR),\u0026nbsp;Chuanxiong Rhizoma\u0026nbsp;(Chuanxiong, CR)\u003cem\u003e\u0026nbsp;\u003c/em\u003eand Ligustici Rhizoma Et Radix\u003cem\u003e\u0026nbsp;\u003c/em\u003e(Gaoben, LRER), Paeoniae Radix Alba\u0026nbsp;(Baishao, PRA)\u0026nbsp;and\u0026nbsp;Moutan Cortex\u0026nbsp;(Mudanpi, MC),\u0026nbsp;Cynanchi Atrati Radix Et Rhizoma (Baiwei, CARER),\u0026nbsp;Glycyrrhizae Radix Et Rhizoma\u0026nbsp;(Gancao, GRER),\u0026nbsp;Cinnamomi Cortex\u0026nbsp;(Rougui, CC),\u0026nbsp;Scutellariae Radix\u0026nbsp;(Huangqin, SR)\u0026nbsp;and\u0026nbsp;Citri Reticulatae Pericarpium\u0026nbsp;(Chenpi, CRP)\u0026nbsp;was prepared by the same method with appropriate amounts of the rest of the herbal materials and the refined honey according to the formulation of NJP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2\u003c/strong\u003e \u003cstrong\u003eChemicals and Reagents.\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFerulic Acid (110773-201915), Paeoniflorin (110736-202145), Paeonol (110708-201908), Ammonium Glycyrrhizinate (110731-202122), Cinnamaldehyde (110710-202022), Baicalin (110721-202019) and Hesperidin were bought from National Institutes for Food and Drug Control. They were all used as reference standards. Methanol, acetonitrile, and formic acid HPLC grade, were purchased from Aladdin (Aladdin, Shanghai). Deionized water was purified by a Milli-Q system (Millipore, USA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Preparation of Standard Solutions.\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEach reference substance was prepared with 90% (V/V) methanol to form a reserve solution with a concentration of approximately 0.5 mg/mL, which was then diluted with 90% (V/V) methanol to produce a series of mixed working standard solutions with five concentration levels (see Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2:\u0026nbsp;Concentration levels of working standard solutions for multi-component determination\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"529\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"26.843100189035916%\"\u003e\n \u003cp\u003eAnalyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" width=\"73.15689981096408%\"\u003e\n \u003cp\u003eWorking Standard (mg/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"21.85089974293059%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.53727506426735%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.53727506426735%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.53727506426735%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.53727506426735%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"26.741996233521657%\"\u003e\n \u003cp\u003ePaeoniflorin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.0075329566855%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"26.741996233521657%\"\u003e\n \u003cp\u003eFerulic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.0075329566855%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"26.741996233521657%\"\u003e\n \u003cp\u003eHesperidin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.0075329566855%\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"26.741996233521657%\"\u003e\n \u003cp\u003eBaicalin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.0075329566855%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"26.741996233521657%\"\u003e\n \u003cp\u003eCinnamaldehyde\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.0075329566855%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"26.741996233521657%\"\u003e\n \u003cp\u003ePaeonol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.0075329566855%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"26.741996233521657%\"\u003e\n \u003cp\u003eGlycyrrhizic acid\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.0075329566855%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.312617702448211%\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eThe weight of glycyrrhizic acid = the weight of ammonium glycyrrhizinate/1.0207.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4\u0026nbsp;Preparation of Solutions of Sample, Reference Drugs, Negative Control, and Chinese Materia Medicas\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNJP samples and NJP reference drugs obtained by weight variation test were ground into uniform powder. One g of powder was accurately weighed and transferred into a conical flask, into which 25 mL of 90%\u0026nbsp;(V/V) methanol was accurately added. The conical flask and the whole mixture was weighed, then was heated using water bath reflux at 80\u0026nbsp;℃ for 2\u0026nbsp;h. The content was then cooled to room temperature. The flask was weighed again, and the lost weight was replenished with 90%\u0026nbsp;(V/V)methanol. The mixture was filtered through a 0.22\u0026nbsp;\u0026mu;m filter and the filtrate was subjected for further analysis. Then negative control solution, containing no active ingredients for specificity validation, was prepared in the same manner. To determine the transfer rates of chemical markers of reference medicinal materials from raw materials to the TCMRD, respectively 3 batches of\u0026nbsp;\u0026nbsp;Angelicae Sinensis Radix (Danggui, ASR), Chuanxiong Rhizoma\u0026nbsp;(Chuanxiong, CR), Ligustici Rhizoma Et Radix\u0026nbsp;(Gaoben,LRER),\u0026nbsp;Paeoniae Radix Alba\u0026nbsp;(Baishao, PRA), Moutan Cortex\u0026nbsp;(Mudanpi, MC),\u0026nbsp;Cynanchi Atrati Radix Et Rhizoma (Baiwei, CARER), Glycyrrhizae Radix Et Rhizoma\u0026nbsp;(Gancao, GRER), Cinnamomi Cortex\u0026nbsp;(Rougui, CC), Scutellariae Radix\u0026nbsp;(Huangqin, SR)\u0026nbsp;and Citri Reticulatae Pericarpium\u0026nbsp;(Chenpi, CRP)\u0026nbsp;were ground into fine powder and processed with the same method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5\u0026nbsp;Instrument and Operating Conditions\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of all filtrates under the item 2.4 was performed using a Waters HPLC system (Waters Co., USA) equipped with photo diodearray(PDA) detector, binary solvent manager, sample manager and column compartment. The software Empower was used for data acquisition. The separation was performed on a Agilent Eclipse plus C18 column (250 mm\u0026times;4.6 mm, 5\u0026mu;m) using a linear gradient elution of 0.2% formic acid in acetonitrile (A) and 0.2% (v/v) formic acid in water (B): 0-25 min, 10%-35% (v/v) A; 25-37 min, 35%-59% (v/v) A; 37-40 min, 59%-75% (v/v) A; at a flow rate of 1 mL/min. The column temperature was set at 30\u0026nbsp;℃\u0026nbsp;and the injection volume was 10\u0026mu;L. Multi-wavelength scanning was applied and the detection wavelengths were set at 230 nm for paeoniflorin, 316 nm for ferulic acid, 283 nm for hesperidin, 280 nm for baicalin, 290 nm for cinnamaldehyde, 274 nm for Paeonol, and 237 nm for glycyrrhizic acid, respectively. Three injections were performed for each solution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Method Validation\u003c/strong\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe specificity, accuracy (recovery), precision, limit of detection (LOD), limit of quantitation (LOQ) and linearity of the method were verified according to the recommendations of the International Coordination Conference (ICH) guidelines [17].The specificity of the method was assessed by comparing HPLC chromatograms obtained from NJP with negative controls. The recovery test of the standard addition method was used to verify accuracy. The corresponding amount of test component standard was added to 0.5 g sample, and the same pre-treatment and analysis methods were used as those of NJP, and the test was repeated six times. For precision test, the same solution was repeatedly checked six times in one day for intraday test, and the analysis was conducted for three consecutive days for daytime test. For repeatable tests, six test solutions were prepared from the same sample and analyzed. LOD and LOQ were determined at S/N ratio of 3 and 10, respectively. Linearity was determined by establishing calibration curves for 5 concentration levels. The calibration equation and correlation coefficient (r) were calculated by least square regression for the obtained peak area and concentrations of all markers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7 Network Pharmacology Analysis.\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe structural formulas of tested constituents were identified by PubChem database (https://pubchem.ncbi.nlm.nih.gov/) and download its corresponding 2D structure file to make predictions and collections through the Swiss Target Prediction platform (https://www.swisstargetprediction.ch/). TCMSP (https://tcmspw.com/tcmsp.php) was used to supplement of the chemical composition targets. The protein-protein interaction (PPI) data were obtained from the STRING database (https://string-db.org/). Relied on Cytoscape 3.9.0 software, the imagement of PPI network was builted after hiding the free points. To deeply explore the pathways and biological process of the network, GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses were conducted by Metascape platform (https://metascape.org/). GO enrichment analysis encompassed cellular components (CC), biological processes (BP), and molecular functions (MF). Ranked by the KEGG analysis, the top 25 pathways related to PCOS were screened out. The information of enrichment bubble chart was visualized by the bioinformatics platform (http://www.bioinformatics.com.cn/).\u0026nbsp;\u003c/p\u003e"},{"header":"3 Results And Discussion","content":"\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.1 Development of the HPLC Method.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eIn order to simultaneously determine seven analytes with better separation and shorter time, HPLC chromatographic conditions were optimized. The ultraviolet (UV) spectra of the seven analytical markers to be measured in the reference and sample solutions was scaned. The maximum absorption of seven analytes (paeoniflorin, ferulic acid, hesperidin, baicalin, cinnamaldehyde, paeonol and glycyrrhizic acid) was set at 230 nm, 316 nm, 283 nm, 280 nm, 290 nm, 274 nm and 237 nm, respectively. On this basis, multi-wavelength switching is programmed.\u003c/p\u003e\n \u003cp\u003eAgilent Eclipse plus C18 column, the most used reversed phase C18 column with wide adaptability, was found to have satisfactory separation and peak capacity. A series of mobile phases were investigated and the concentration of formic acid was optimized, including methanol-water, acetonitrile-water, acetonitrile-0.1% (V/V) formic acid aqueous solution, acetonitrile-0.2% (V/V) formic acid aqueous solution, and 0.2% (V/V) formic acid acetonitrile-0.2% (V/V) formic acid aqueous solution. The results showed that 0.2% (V/V) formic acid in acetonitrile-0.2% (V/V) formic acid solution in water could achieve better separation than other systems. The usual flow rate of 1 mL/min was used. In addition, different gradient curves were applied to improve the separation of NJP by changing the proportion of mobile phase during elution, and the optimal gradient was finally selected through several empirical attempts. The column temperature is another important parameter that needs to be controlled. The appropriate decrease of the column temperature is conducive to the improvement of the separation degree. According to the results, 30\u0026deg;C is selected as the best column temperature value.\u003c/p\u003e\n \u003cp\u003eRepresentative chromatograms of each of the seven reference standards and typical samples at different wavelengths are shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The analytes were identified by comparing their retention time and UV spectra with those of each reference standards. In addition, spiked sample and reference standards showed no additional peaks, which further confirmed the identity of the peaks.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.2 Optimization of the Pretreatment Method.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eIn order to improve the sensitivity and reliability of the method, pretreatment parameters such as extraction solvent, extraction method, extraction time and extraction solvent volume were optimized with the concentration of analytes as the standard. Different proportions of methanol in the range of 50%-100% (V/V) were used as the extraction solution for the experiment, and 90% (V/V) methanol was selected as the extraction solvent for further experiments based on the extraction rate of 7 detection indexes. In order to study the influence of extraction methods on extraction efficiency, ultrasonic treatment (500 W, 40 kHz) for 30 minutes and water bath heating reflux at 80 ℃ for 1 hour were compared. The results showed that the extraction efficiency of 7 detection indexes was obviously higher when heated under reflux. The reflux time was optimized in the range of 1 to 4 hours, and when the time exceeded 2 hours, the contents of all indexes reached dynamic balance. Therefore, 2 hours of extraction time was considered sufficient. Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e summarized the HPLC fingerprints of 7 detection indexes of NJP sample extracts after all analytical procedures.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.3 Verification of the HPLC Method.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe specificity of the method was verified by comparing the HPLC chromatograms of the NJP control samples and the negative control samples without Angelicae Sinensis Radix (Danggui, ASR), Chuanxiong Rhizoma (Chuanxiong, CR) and Ligustici Rhizoma Et Radix (Gaoben, LRER), Paeoniae Radix Alba (Baishao, PRA) and Moutan Cortex (Mudanpi, MC), Cynanchi Atrati Radix Et Rhizoma (Baiwei, CARER), Glycyrrhizae Radix Et Rhizoma (Gancao, GRER), Cinnamomi Cortex (Rougui, CC), Scutellariae Radix (Huangqin, SR) and Citri Reticulatae Pericarpium (Chenpi, CRP). The seven analytes were well separated without interference (See Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating that the selectivity of the method can be used for further quantification. The linearity of the method was verified by plotting the peak area (y) and the concentration of the reference standards (x). All the analytes have a good linear relationship, with correlation coefficients (\u003cem\u003er\u003c/em\u003e)\u0026thinsp;\u0026gt;\u0026thinsp;0.9995. The LOD (S/N\u0026thinsp;\u0026ge;\u0026thinsp;3) and LOQ (S/N\u0026thinsp;\u0026ge;\u0026thinsp;10) of the seven analytes ranged from 0.14 to 0.35 \u0026micro;g/mL and from 0.48 to 1.16 \u0026micro;g/mL, respectively. The results of linearity, LOD, and LOQ are summarized in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. To confirm the precision, repeatability and accuracy of the method, intraday and interday precision, repeatability and recovery were tested and values was given in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. The relative standard deviations (RSDs) were below 2.0%, and the average recoveries for all the analytes were in the range of 97.5\u0026ndash;101.8%. Therefore, this HPLC method is sensitive, precise, and accurate for quantification of multiple components in NJP.\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cp class=\"CaptionNumber\"\u003eTable 3\u003c/p\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLinear range, regression equation, coefficient of determination (\u003cem\u003er\u003c/em\u003e), LOD, and LOQ for HPLC analysis of seven analytes.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003eAnalyte\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eLinear Range\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eRegression Equation\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u003cem\u003er\u003c/em\u003e\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eLOD\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eLOQ\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e(mg/mL)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ey\u0026thinsp;=\u0026thinsp;ax\u0026thinsp;+\u0026thinsp;b\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e(\u0026micro;g/mL)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e(\u0026micro;g/mL)\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePaeoniflorin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.002\u0026ndash;0.053\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ey\u0026thinsp;=\u0026thinsp;1.41\u0026times;10\u003csup\u003e6\u003c/sup\u003ex \u0026minus;\u0026thinsp;8.86\u0026times;10\u003csup\u003e3\u003c/sup\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.9998\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.71\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eFerulic acid\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.001\u0026ndash;0.013\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ey\u0026thinsp;=\u0026thinsp;3.34\u0026times;10\u003csup\u003e6\u003c/sup\u003ex \u0026minus;\u0026thinsp;9.19\u0026times;10\u003csup\u003e2\u003c/sup\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.0000\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.87\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHesperidin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.006\u0026ndash;0.146\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ey\u0026thinsp;=\u0026thinsp;2.07\u0026times;10\u003csup\u003e6\u003c/sup\u003ex \u0026minus;\u0026thinsp;2.20\u0026times;10\u003csup\u003e4\u003c/sup\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.0000\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.89\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eBaicalin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.007\u0026ndash;0.167\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ey\u0026thinsp;=\u0026thinsp;3.30\u0026times;10\u003csup\u003e6\u003c/sup\u003ex \u0026minus;\u0026thinsp;3.98\u0026times;10\u003csup\u003e4\u003c/sup\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.9999\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.16\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCinnamaldehyde\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.001\u0026ndash;0.013\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ey\u0026thinsp;=\u0026thinsp;7.46\u0026times;10\u003csup\u003e6\u003c/sup\u003ex \u0026minus;\u0026thinsp;2.83\u0026times;10\u003csup\u003e4\u003c/sup\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.9998\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.88\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePaeonol\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.002\u0026ndash;0.041\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ey\u0026thinsp;=\u0026thinsp;4.97\u0026times;10\u003csup\u003e6\u003c/sup\u003ex \u0026minus;\u0026thinsp;1.65\u0026times;10\u003csup\u003e4\u003c/sup\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.9999\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.16\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.55\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eGlycyrrhizic acid\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.001\u0026ndash;0.036\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ey\u0026thinsp;=\u0026thinsp;3.11\u0026times;10\u003csup\u003e5\u003c/sup\u003ex \u0026minus;\u0026thinsp;8.99\u0026times;10\u003csup\u003e2\u003c/sup\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.9998\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.14\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.48\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab4\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cp class=\"CaptionNumber\"\u003eTable 4\u003c/p\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrecisions, repeatability, and recovery of seven analytes.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003eAnalyte\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003ePrecisions\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eRepeatability\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003eRecovery\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eIntraday RSD(%,n\u0026thinsp;=\u0026thinsp;6)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eInterday RSD(%,n\u0026thinsp;=\u0026thinsp;3)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eRSD(%,n\u0026thinsp;=\u0026thinsp;6)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eMean(%)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eRSD(%,n\u0026thinsp;=\u0026thinsp;6)\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePaeoniflorin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e101.8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.6\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eFerulic acid\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e101.2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.2\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHesperidin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.0\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e98.6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.9\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eBaicalin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e97.5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.9\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCinnamaldehyde\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e99.8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.4\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePaeonol\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e100.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.6\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eGlycyrrhizic acid\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e99.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.3\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e3.4 Simultaneous Determination of 7 Components in the Samples from Manufacturers.\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIn the ChP 2020 edition, the markers of paeoniflorin, Angelica, ligusticum chuanxiong, ligustilia, tangerine bark, Scutellaria baicalensis, cinnamon, paeonol and glycyrrhizin were paeoniflorin, ferulic acid, hesperidin, baicalin, cinnamaldehyde, paeonol and glycyrrhizic acid respectively. According to the literature [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e], these seven components are the active components of corresponding traditional Chinese medicine respectively. A total of 76 batches of NJP were quantified from 19 manufacturers (code A\u0026thinsp;~\u0026thinsp;S). As shown in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, the contents of 7 components in different samples were different. Heatmap generated by the Internet of Chinplot (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.chiplot.online/\u003c/span\u003e\u003c/span\u003e) had a more intuitive display.Longitudinal characteristic peak clustering showed that the characteristic peaks could be divided into three categories (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), in which Hesperidin and Baicalin were clustered into class I, Ferulic acid and Paeoniflorin were clustered into class II, and other ingredients were clustered into class III. It is well known that most Chinese medicine comes from cultivated herbs, and their content is inevitably affected by natural factors beyond their control. Therefore, the quality of Chinese medicinal materials can be reflected by the content of markers, but it is not necessarily proportional, but obviously lower content usually means poor quality of medicinal materials or insufficient raw materials. The contents of paeoniflorin, ferulic acid, hesperidin and baicalin varied gently with RSDs around 20%. Significant range of variations were observed for contents of cinnamaldehyde, paeonol and glycyrrhizic acid with RSDs above 40%. The variations indicated uneven quality of the raw materials and that would lead to differences in the intrinsic quality and efficacy of the commercial products.\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab5\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cp class=\"CaptionNumber\"\u003eTable 5\u003c/p\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eContents (mg/g) of 7 components in 76 batches of NJP (n\u0026thinsp;=\u0026thinsp;2).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eNo.\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eManufacturer\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePaeoniflorin\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eFerulic acid\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eHesperidin\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eBaicalin\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eCinnamaldehyde\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePaeonol\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eGlycyrrhizic acid\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eA1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.48\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.02\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.19\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.30\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eA2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.90\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.10\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eA3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.09\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.67\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.49\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.09\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.79\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.82\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.51\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.79\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.02\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.36\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.45\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.68\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.02\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.47\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.68\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.00\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.46\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.43\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.47\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.82\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.89\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.72\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.87\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.19\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e10\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.38\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.17\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.30\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.28\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.45\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e11\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.01\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.46\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.74\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.48\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.28\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.45\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e13\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eC1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.57\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.44\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e14\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eC2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.55\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.44\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e15\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eC3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.57\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.44\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e16\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eC4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.51\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.44\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e17\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eC5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.44\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e18\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eD6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.82\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.28\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.45\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e19\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eD7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e20\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eD8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.28\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.46\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eD9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.45\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eD10\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.62\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.44\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eE1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.15\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.18\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.28\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e24\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eF1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.44\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.30\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.99\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eF2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.49\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.54\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.10\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eF3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.66\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.28\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.52\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eG1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.55\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.57\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e28\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eG2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.51\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.87\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eG3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.50\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.91\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.52\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.24\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.38\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e30\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eG4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.50\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.43\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.71\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.43\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eG5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.80\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.63\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.81\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eH1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.24\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.01\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.60\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.95\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.51\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eH2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.66\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.91\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.46\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eH3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.03\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.72\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.51\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.89\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eI4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.24\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.01\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.20\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.49\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eI5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.56\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.82\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.58\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eJ1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.45\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.11\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e38\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eJ2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.46\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.85\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.19\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.65\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.51\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eJ3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.62\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.09\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.20\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.43\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e40\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eJ4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.55\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.76\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.43\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eJ5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.78\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.51\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.92\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.56\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eJ6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.79\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.19\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e43\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eJ7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.86\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e44\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eJ8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.51\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.88\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.28\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e45\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eK1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.38\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.43\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e46\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eK2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e47\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eK3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.56\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.52\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e48\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eL1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.46\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e49\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eL2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.38\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.63\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e50\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eL3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.17\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.43\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e51\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eL4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.89\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.47\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e52\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eL5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.92\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.46\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.55\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eL6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.77\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.52\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e54\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.02\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.63\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.56\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.24\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e55\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.48\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.44\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e56\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.56\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.44\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.52\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e57\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eN1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.24\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.62\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.29\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e58\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eN2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.46\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e59\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eN3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.09\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.54\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e60\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eO1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e61\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eO2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.37\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e62\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eO3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.43\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.28\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.46\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e63\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eP1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e64\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eP2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.15\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.38\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e65\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eP3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.11\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.55\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.43\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e66\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eQ1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.38\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.91\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.56\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e67\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eQ2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.52\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.62\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e68\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eQ3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.69\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.58\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.43\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e69\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eR1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.69\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.57\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.37\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e70\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eR2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.67\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.62\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e71\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eR3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.68\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.24\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e72\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eS1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.63\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.28\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e73\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eS2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.75\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.19\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e74\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eS3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.38\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.97\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.52\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.17\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e75\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eS4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.36\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.65\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e76\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eS5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.69\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.42\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.28\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003eMedian\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.68\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.27\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.42\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003eMean\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.69\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.45\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003eRSD(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e21.4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e22.5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e15.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e17.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e43.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e46.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e48.5\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec13\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.5 Explore the Anti-PCOS Activity of Focused Compounds\u003c/strong\u003e.\u003c/p\u003e\n \u003cp\u003eWe employed network pharmacology to explore the correlation between the 7 identifified compounds and their Anti-PCOS activity.[\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e] According to PPI analysis, the core targets were inputted into the network visualization software Cytoscape 3.9.0 to build the following network (Fig. 4A) which had 51 nodes and 480 edges. With regard to the degree analysis, the top six gene target were AKT1, TNF, PTGS2, IL1B, CASP3, EGFR and wighteone with 41-degree, 37-degree, 33-degree, 33-degree, 32-degree and 32-degree respectively. It was suggested that these proteins may be the key core targets of Anti-PCOS of 7 focused compounds. To deeply explore the underlying mechanism of 7 ingredients with large differences in content, GO and KEGG enrichment analyses were conducted with the Metascape platform. A total of 1051 terminologies related to biological events were chosen, specififically included positive regulation of cell migration, positive regulation of cell motility, positive regulation of cellular component movement, positive regulation of locomotion, positive regulation of cell death, etc. Concerning the enrichment analysis of cellular components, the targets were comprised of the membrane raft, membrane microdomain. Concurrently, the molecular function terms primarily comprised kinase activity, phosphotransferase activity, kinase binding, and so on (Fig. 4B). The main effects linked to the NJP of focused 7 compounds were grouped using the KEGG pathway enrichment analysis. 165 pathways were obtained from the KEGG database. A sum of 25 top-ordered pathways (Fig. 4C) were screened out (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Among them, the most important pathways included the Lipid and atherosclerosis signaling pathway, AGE RAGE signaling pathway, Hepatitis B signaling pathway, and other pathways. These results indicated that all the 7 compounds exhibit potential pharmacological activity associated with the treatment of Polycystic ovary syndrome.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec14\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.6 Grade Evaluation of Nvjin Pills\u003c/strong\u003e.\u003c/p\u003e\n \u003cp\u003eTo evaluate the \u0026ldquo;excellence or inferior grade\u0026rdquo; of NJP, the traditional Chinese medicine standard (TCMRD) was introduced into the multi-component analysis of TCM decoction pieces using authentic and high quality Chinese medicinal materials(CMM), in strict accordance with the prescription and technology, and in compliance with GMP.The source, harvesting time and processing method of CMM were identified according to legal standards. It was necessary to further investigate the true growing environment, medicinal resources and quality status, then, purchase real raw materials from correct original plants and grow under good agricultural practices (GAP). The selected CMM was tested separately to meet its statutory standards. In addition, other tests were conducted to eliminate safety risks such as pesticide residues, heavy metals, mycotoxins, sulfur dioxide, adulteration, and illegal staining. Finally, the production of NJP reference materials are carried out in strict accordance with the provisions of GMP, and all raw materials are in accordance with the official legal standards of crushing, or the amount after crushing. To compensate for the inevitable fluctuation of components in CMM, three batches of TCMRDs were made from authentic, high-quality and standardized Chinese herbal decoction pieces from three different suppliers. Then the TCMRDs and their corresponding raw materials were determined by the same HPLC method for the NJP samples. As indicated in Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, variations were found in contents of the seven markers in three batches of TCMRD, especially hesperidin, cinnamaldehyde and glycyrrhizic acid. Those might be due to naturally existed fluctuation of chemical components and the different growth years of Citri Reticulatae Pericarpium (Chenpi, CRP), Cinnamomi Cortex (Rougui, CC) and Moutan Cortex (Mudanpi, MC). Nevertheless, the transfer rates of all the analytes were stable, which provided valuable information for formulating grading limits.\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab6\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cp class=\"CaptionNumber\"\u003eTable 6\u003c/p\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eContents and transfer rates of 7 components in NJP Reference Drugs (n\u0026thinsp;=\u0026thinsp;2).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003eAnalyte\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePaeoniflorin\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eFerulic\u003cbr\u003eacid\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eHesperidin\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eBaicalin\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eCinnamaldehyde\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePaeonol\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eGlycyrrhizic acid\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003eReference\u003cbr\u003eDrug 1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eContents\u003cbr\u003e(mg/g)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.68\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.83\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.63\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.75\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTransfer rates\u003cbr\u003e(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e95.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e88.8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e97.6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e94.5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e82.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e97.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e95.3\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003eReference\u003cbr\u003eDrug 2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eContents\u003cbr\u003e(mg/g)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.62\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.35\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.44\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.45\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTransfer rates\u003cbr\u003e(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e94.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e90.2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e96.2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e94.2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e82.4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e95.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e94.2\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003eReference\u003cbr\u003eDrug 3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eContents\u003cbr\u003e(mg/g)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.45\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.08\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.97\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.50\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.23\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTransfer rates\u003cbr\u003e(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e96.5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e89.2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e95.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e93.4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e81.5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e96.6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e93.3\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003eMean\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eContents\u003cbr\u003e(mg/g)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.49\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.38\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.67\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.40\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.48\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTransfer rates\u003cbr\u003e(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e95.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e89.4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e96.6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e94.0\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e82.0\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e96.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e94.3\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003eRSD(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eContents\u003cbr\u003e(mg/g)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e35.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e37.8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e41.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e21.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e50.8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e26.6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e55.1\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTransfer rates\u003cbr\u003e(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.1\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eIn general, the product quality grade refers to the first and second grade products should be specified. The second grade refers in principle to the level of quality to be achieved using a predetermined quantity of qualified raw materials and standardized manufacturing processes. The first grade refers to the level of quality to be achieved through the use of high-quality raw materials, predetermined quantities and standardized manufacturing processes. In this study, hesperidin, baicalin, cinnamaldehyde and glycyrrhizic acid were used as the quality evaluation indexes of Citri Reticulatae Pericarpium (Chenpi, CRP), Scutellariae Radix (Huangqin, SR), Cinnamomi Cortex (Rougui, CC) and Glycyrrhizae Radix Et Rhizoma (Gancao, GRER) in NJP. The minimum values of these four markers and the maximum moisture values in the corresponding CMM are specified in ChP 2020. The second-grade limits of hesperidin, baicalin, cinnamaldehyde and glycyrrhizic acid in NJP were calculated as following: minimum limit of the marker in the corresponding CMM% \u0026times; (100%-maximum limit of water in the corresponding CMM%) \u0026times; proportion of the corresponding CMM in NJP% \u0026times; average transfer rate of the marker in the NJP%. The first-grade limits of hesperidin, baicalin, cinnamaldehyde and glycyrrhizic acid in NJP were specified comparing with the median contents in 76 batches of samples and their mean contents in 3 batches of TCMRDs, based on dispersion of the data. If the mean contents were larger than the median contents, the first-grade limits were specified as 80% of the mean contents. On the contrary, the first grade limits were specified as the mean contents.\u003c/p\u003e\n \u003cp\u003eAs for paeoniflorin, ferulic acid and paeonol, these three indicative components exist in the multi-CMMs in the herbal formula of NJP, but their minimum limits in the corresponding CMM are not specified all, and their contents vary greatly [\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]. Therefore, the second grade limit for the three markers in NJP was specified as 60% of their mean contents in three TCMRDs.\u003c/p\u003e\n \u003cp\u003eOn the basis of comprehensive analysis, the quality grade specifications of 7 markers in NJP are listed in Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e. Accordingly, 76 batches of samples from 19 manufacturers were preliminarily divided into three quality grades: 16 batches of first grade, 47 batches of second grade, and 13 batches unqualified.\u003c/p\u003e\n \u003ctable border=\"1\" id=\"Tab7\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cp class=\"CaptionNumber\"\u003eTable 7\u003c/p\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eQuality grade specifications of the seven markers and quality rating results of NJP.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003eAnalyte\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003eFirst Grade\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003eSecond Grade\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eSpecification\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eBatches Qualified\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eBatches Qualified All 7 Specifications\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eSpecification\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eBatches Qualified\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eBatches Qualified All 7 Specifications\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePaeoniflorin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eN/A\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eN/A\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"7\"\u003e16\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;0.29mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e72\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"7\"\u003e47\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eFerulic acid\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eN/A\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eN/A\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;0.04mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e74\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHesperidin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;1.38mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e66\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;0.62mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e76\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eBaicalin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;1.33mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e39\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;0.98mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e71\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCinnamaldehyde\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;0.32mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e58\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;0.16mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e75\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePaeonol\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eN/A\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eN/A\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;0.25mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e63\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eGlycyrrhizic acid\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;0.38mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e56\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026ge;\u0026thinsp;0.22mg/g\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e76\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"4 Conclusions","content":"\u003cp\u003eIn conclusion, a new principle of multi-component analysis and evaluation was used to evaluate the quality grade of the compound Chinese herbal medicine (CCHM). In this study,7 compounds in NJP, including Paeoniflorin, Ferulic acid, Hesperidin, Baicalin, Cinnamaldehyde, Paeonol, Glycyrrhizic acid, were identified by high performance liquid chromatography (HPLC) method combined with wavelength switching. A sensitive and accurate method for simultaneous determination of 7 markers in NJP was established. The specificity, linearity, LOD, LOQ, precision and accuracy of the method were verified and used for the analysis of NJP samples and TCMRD. The Anti-PCOS components in NJP were mined through network pharmacology for the first time,which provided the basis for the quantitative analysis of NJP. Taking into account the measurement results and the quality status of the corresponding CMM, the specifications of the first grade and the second grade were put forward, and the samples were classified on the basis of this. With combination of results obtained from former safety examinations, according to the overall strategy, the listed samples are graded to distinguish between \"good\" and \"bad\". The challenge posed by the great variability of a few markers in reference drugs deserves further and deeper study.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used to support the fifinding of this study are available from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors\u0026nbsp;declare that there is no conflict of interest regarding the publication of this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYongqiang Lin and \u0026nbsp;Guangzhen Liu conceived and designed the study. Lin Lin wrote the article and analyzed data. \u0026nbsp;Dexin Zhang, Fengrui Yu, Lejun Tan, Xiangrong Mu revised the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded by Shandong Institute for Food and Drug Control, Shandong Engineering Laboratory for Standard Innovation and Quality Evaluation of TCM.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWang WY, Zhou H, Wang YF, Sang BS, Liu L (2021) Current Policies and Measures on the Development of Traditional Chinese Medicine in China. Pharmacol Res 163:105187.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCyranoski D\u0026nbsp;(2018)\u0026nbsp;Why Chinese medicine is heading for clinics around the world. Nature\u0026nbsp;561:448-450.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDong ZW, Tian MY, Zhao YM, Wang C, Wang HF, Wang J, Huang QW\u0026nbsp;(2022)\u0026nbsp;Grading of rhizoma coptidis based on appearance trait and intrinsic quality correlation and multivariate statistical analysis. WJTCM\u0026nbsp;17:1214-1219.\u003c/li\u003e\n \u003cli\u003eWei ZJ, Ren XH, Zhang Y, Dai X, Guo R, Zhao ZH, Liu LL, Liu Y, Li WD\u0026nbsp;(2022)\u0026nbsp;Study on quality grade standard of premature Forsythia suspensa. J China Pharm\u0026nbsp;33:\u0026nbsp;842-847.\u003c/li\u003e\n \u003cli\u003eXie XT,\u0026nbsp;Huang P,\u0026nbsp;Zhou GL,\u0026nbsp;Wang Q,\u0026nbsp;Wang NB,\u0026nbsp;Guan SQ,\u0026nbsp;Lu QT\u0026nbsp;(2021)\u0026nbsp;Evaluation of quality grade of Guangjincao decoction pieces based on PLS regression analysis. Li shizhen Med Mater Med Res\u0026nbsp;32:1749-1752.\u003c/li\u003e\n \u003cli\u003eNie LX, Qian XY, Zhang Y, Wei F, Dai Z, Ma SC\u0026nbsp;(2021)\u0026nbsp;Discussion on the research principles and methods of the quality grade standard of proprietary Chinese medicine. J Shenyang Pharm Univ\u0026nbsp;38:1327-1333.\u003c/li\u003e\n \u003cli\u003eDing RW, Wei HZ, Lv S, Song XZ, Qi JF, Jin HX, Cao YX, RaoY\u0026nbsp;(2021)\u0026nbsp;Study on quality grade of plantaginis Semen based on multivariate statistical analysis. Chin Arch Tradit Chin Med\u0026nbsp;38:673-679.\u003c/li\u003e\n \u003cli\u003eNie LX, Dai Z, Ma SC\u0026nbsp;(2017)\u0026nbsp;Guideline principle and technical requirement for preparing traditional Chinese medicine reference. China J Chin\u0026nbsp;Mater\u0026nbsp;Med\u0026nbsp;42:3672\u0026ndash;3675.\u003c/li\u003e\n \u003cli\u003eNie\u0026nbsp;LX, Zha\u0026nbsp;YF, Yu\u0026nbsp;JD, Shuai K, Zhong D, Ma\u0026nbsp;SC, Kelvin\u0026nbsp;C\u0026nbsp;(2022)\u0026nbsp;Quality Grade Evaluation of Niuhuang Qingwei Pills Based on UPLC and TCM Reference Drug-A Novel Principle of Analysis of Multiple Components in Ready-Made Chinese Herbal Medicine. Processes\u0026nbsp;10:\u0026nbsp;1166.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eChP 2020 edition: Beijing China 2020.\u003c/li\u003e\n \u003cli\u003eLiu\u0026nbsp;AM\u0026nbsp;(2011)\u0026nbsp;\u0026quot;Nvjin Pill\u0026quot; a good medicine for gynecology.\u0026nbsp;Neimengggu J Tradit Chin Med\u0026nbsp;30:123.\u003c/li\u003e\n \u003cli\u003eLin L, Yu FR, Xu LH, Lin YQ (2019)\u0026nbsp;HPLC\u0026nbsp;fingerprintcluster\u0026nbsp;analysis and\u0026nbsp;principal\u0026nbsp;component\u0026nbsp;analysis of Nvjin Pills. J China Pharm 30:1339-1343.\u003c/li\u003e\n \u003cli\u003eLin L, Liu GZ, Yu FR, Xu LH\u0026nbsp;(2018)\u0026nbsp;Simultaneous determination of twelve constituents in Nvjin Pills by HPLC combined with wavelength switching. Chin Pharm J\u0026nbsp;53:1511-1515.\u003c/li\u003e\n \u003cli\u003eLin YQ, Liu GZ, Xu LH, Lin L\u0026nbsp;(2019)\u0026nbsp;Study of HPLC fingerprint in Nvjin Pill. Chin J Mod Appl Pharm\u0026nbsp;36:456-460.\u003c/li\u003e\n \u003cli\u003eLin L, Yu FR, Xu LH, Lin YQ (2018)\u0026nbsp;Content Determination of 7 Volatile Components in Nvjin Pill by GC. Chin J Exp Tradit Med Form 24:73-77.\u003c/li\u003e\n \u003cli\u003eDai J, Yang XJ, Hao PP, Feng L, Li JC (2010)\u0026nbsp;Study on TLC\u0026nbsp;identification method of Nvjin Pill. CHIN TRADIT PAT MED 32:2021-2025.\u003c/li\u003e\n \u003cli\u003eChandran S, Singh RS (2007) Comparison of various international guidelines for analytical method validation. Die Pharmazie-An International Journal of Pharmaceutical Sciences\u0026nbsp;62:\u0026nbsp;4-14.\u003c/li\u003e\n \u003cli\u003eKudoh C, Hori T, Yasaki S, Ubagai R, Tabira T\u0026nbsp;(2020)\u0026nbsp;Effects of Ferulic Acid and Angelica archangelica Extract (Feru-guard \u0026reg;) on Mild Cognitive Impairment: A Multicenter, Randomized, Double-Blind, Placebo-Controlled Prospective Trial. J Alzheimers Dis Rep\u0026nbsp;4:393-398.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eYan N, Tang Z, Xu Y, Li X, Wang Q\u0026nbsp;(2020)\u0026nbsp;Pharmacokinetic Study of Ferulic Acid Following Transdermal or Intragastric Administration in Rats.\u0026nbsp;AAPS PharmSciTech\u0026nbsp;21:169.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLiu JS, Zhang XY, Li B, Wei XP, Qi YD, Liu HT, Zhang BG (2022) Anti-inflammatory active component in raw materials of Ligustici Rhizoma et Radix based on spectrum-effect relationship. CHIN TRADIT PAT MED\u0026nbsp;47:3295-3302.\u003c/li\u003e\n \u003cli\u003ePark HR, Choi HJ, Kim BS, Chung \u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/?term=Chung+TW\u0026cauthor_id=33809755\"\u003eTW\u003c/a\u003e, \u0026nbsp;Kim\u0026nbsp;\u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/?term=Kim+KJ\u0026cauthor_id=33809755\"\u003eKJ\u003c/a\u003e, \u0026nbsp;Joo\u0026nbsp;\u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/?term=Joo+JK\u0026cauthor_id=33809755\"\u003eJK\u003c/a\u003e,\u0026nbsp;Ryu\u0026nbsp;\u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/?term=Ryu+D\u0026cauthor_id=33809755\"\u003eD\u003c/a\u003e,\u0026nbsp;Bae\u0026nbsp;\u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/?term=Bae+SJ\u0026cauthor_id=33809755\"\u003eSJ\u003c/a\u003e,\u0026nbsp;Ha\u0026nbsp;\u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/?term=Ha+KT\u0026cauthor_id=33809755\"\u003eKT\u0026nbsp;\u003c/a\u003e(2021)\u0026nbsp;Paeoniflorin Enhances Endometrial Receptivity through Leukemia Inhibitory Factor.\u0026nbsp;Biomolecules\u0026nbsp;11:439.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eYuan Y, Yu J, Jiang C, Li MH, \u0026nbsp; Lin\u0026nbsp;SF, Wang\u0026nbsp;XM, Huang\u0026nbsp;LQ\u0026nbsp;(2013)\u0026nbsp;Functional diversity of genes for the biosynthesis of paeoniflorin and its derivatives in Paeonia.\u0026nbsp;Int J Mol Sci\u0026nbsp;14:18502-18519.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSu YS, Zhang XY, Guo QM (2021) Advances in chemical constituents and pharmacology of Baiwei(Cynanchi Atrati Radix et Rhizoma). Chin Arch Tradit Chin Med 39:171-177.\u003c/li\u003e\n \u003cli\u003eChen M, Zhu J, Kang J, Lai X, Gao Y, Gan H, Yang F\u0026nbsp;(2019)\u0026nbsp;Exploration in the Mechanism of Action of Licorice by Network Pharmacology. Molecules\u0026nbsp;24:2959.\u003c/li\u003e\n \u003cli\u003eLee\u0026nbsp;JH, Kwak\u0026nbsp;HJ, Shin\u0026nbsp;D, Seo HJ, Park SJ, Hong BH, Shin MS, Kim SH, Kang KS\u0026nbsp;(2022)\u0026nbsp;\u0026nbsp;Mitigation of Gastric Damage Using\u0026nbsp;Cinnamomum cassia\u0026nbsp;Extract: Network Pharmacological Analysis of Active Compounds and Protection Effects in Rats.\u0026nbsp;Plants (Basel)\u0026nbsp;11:716.\u003c/li\u003e\n \u003cli\u003eShah M, Mubin S, Hassan SSU, Tagde P, Ullah O, Rahman MH, Al-Harrasi A, Rehman NU, Murad W (2022) Phytochemical Profiling and Bio-Potentiality of Genus Scutellaria: Biomedical Approach. \u0026nbsp;Biomolecules 12:936.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eK.\u0026nbsp;Pyrzynska\u0026nbsp;(2022)\u0026nbsp;Hesperidin: A Review on Extraction Methods, Stability and Biological Activities. Nutrients\u0026nbsp;14: 2387.\u003c/li\u003e\n \u003cli\u003eXue M, Zhao Y, Cui Y, Yang J, Wang Y, Chai X (2022) Quantitative Analysis of Multicomponents in Qufeng Zhitong Capsule and Application of Network Pharmacology to Explore the Anti-Inflammatory Activity of Focused Compounds. \u0026nbsp;J Anal Methods Chem 2022, Article ID\u0026nbsp;4229945.\u003c/li\u003e\n \u003cli\u003eZhang K, Yan M, Han S, Cong L, Wang L, Zhang L, Sun L, Bai H, Wei G, Du H, Jiang M, Bai G, Yang Z\u0026nbsp;(2019)\u0026nbsp;Identification of Chemical Markers for the Discrimination of Radix\u0026nbsp;Angelica sinensis\u0026nbsp;Grown in Geoherb and Non-Geoherb Regions Using UHPLC-QTOF-MS/MS Based Metabolomics.\u0026nbsp;Molecules\u0026nbsp;24:3536.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLiu JL, Zheng SL, Fan QJ, Yuan JC, Yang SM, Kong FL (2014)\u0026nbsp;\u0026nbsp;Optimization of high-pressure ultrasonic-assisted simultaneous extraction of six major constituents from Ligusticum chuanxiong rhizome using response surface methodology.\u0026nbsp;Molecules\u0026nbsp;19:1887-1911. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLiang\u0026nbsp;H, Pan\u0026nbsp;XJ, Lv\u0026nbsp;WS,\u0026nbsp;\u0026nbsp;Liang\u0026nbsp;WH\u0026nbsp;(2021)\u0026nbsp;Fingerprint Establishment of Rhizoma Ligustici from Different Origins and Their Chemometrics Analysis. J China Pharm\u0026nbsp;32:\u0026nbsp;2358-2362. \u0026nbsp; \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eJo\u0026nbsp;BG, Kang\u0026nbsp;KH, Yang\u0026nbsp;MH\u0026nbsp;(2020)\u0026nbsp;Development and Validation of a HPLC-PDA Method for the Simultaneous Determination of Berberine Palmatine Geniposide and Paeoniflorin in Haedoksamul-tang.\u0026nbsp;Appl Sci\u0026nbsp;10:5482.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLi RR, Liu HX, Peng PH, Hu XR (2021) Study on UPLC fingerprint of Paeonia decomposita- cortex and simultaneous determination of four components.\u003cem\u003e\u0026nbsp;\u003c/em\u003eCHINA\u0026nbsp;MEASUREMENT\u0026nbsp;\u0026amp;\u0026nbsp;TEST 47:77-82.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eXia CK, Zhan YW, Hu YF, Fang CW (2019) Simultaneous determination of thirteen components of Mortan Cortex in different regions by HPLC. Chin Tradit Herbal Drugs 50:970-974.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eXiang H, Zhang L, Song J, Fan B, Nie Y, Bai D, Lei H (2016)\u0026nbsp;The Profiling and Identification of the Absorbed Constituents and Metabolites of Guizhi Decoction in Rat Plasma and Urine by Rapid Resolution Liquid Chromatography Combined with Quadrupole-Time-of-Flight Mass Spectrometry.\u0026nbsp;Int J Mol Sci\u0026nbsp;17:1409.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eFarag MA, Khaled SE, El Gingeehy Z, Shamma SN, Zayed A\u0026nbsp;(2022)\u0026nbsp;Comparative Metabolite Profiling and Fingerprinting of Medicinal Cinnamon Bark and Its Commercial Preparations via a Multiplex Approach of GC-MS, UV, and NMR Techniques.\u0026nbsp;Metabolites\u0026nbsp;12:\u0026nbsp;614.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eChen\u0026nbsp;JC,\u0026nbsp;\u0026nbsp;Wu\u0026nbsp;HL,Wang T,\u0026nbsp;Dong MY, Chen Y, Yu RQ\u0026nbsp;(2022)\u0026nbsp;High-Performance Liquid Chromatography-Diode Array Detection Combined with Chemometrics for Simultaneous Quantitative Analysis of Five Active Constituents in a Chinese Medicine Formula Wen-Qing-Yin. \u003cem\u003eChemosensors\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e10:\u0026nbsp;238. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLiu LC, Wang XY, Li LN, Yang L, Wang ZT (2022) Research advances of chemical constituents and analytical methods of Citri Reticulatae Pericarpium Viride and Citri Reticulatae Pericarpium.China J. Chin. Mater. Med 47: 2866-2879. \u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Compound Chinese herbal medicine (CCHM), Quality grade evaluation, Traditional Chinese medicine reference drug (TCMRD), Nvjin Pills (NJP)","lastPublishedDoi":"10.21203/rs.3.rs-2531631/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2531631/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe compound Chinese herbal medicine (CCHM) is one of the most commonly used types of synergistic herbal medicine. It is based on composite herbal formula (CHF), which makes quality evaluation of this kind of traditional Chinese medicine (TCM) difficult. Taking Nvjin Pills (NJP) as an example, this study reported the development of a novel principle of analysis in CCHM. In order to improve the effectiveness of marketed drugs related active ingredients, it was necessary to designate a more unified quality evaluation standard. The core of the experimental is to prepare 3 batches of TCM reference drugs (TCMRD) using high-quality Chinese materia medica (single Chinese herbals used in the NJP). The active ingredients identified in the herbal formula including glycyrrhizic acid, cinnamaldehyde, paeonol, baicalin, hesperidin, paeoniflorin and ferulic acid were analyzed in both 3 TCMRDs and 76 batches of commercial products from 19 manufacturers by high performance liquid chromatography (HPLC) method combined with wavelength switching. NJP is a well-known Chinese patent medicine that has been widely applied for the clinical treatment of polycystic ovarian syndrome (PCOS) and other gynecological \u0026nbsp;diseases. For the first time, the relationship between the components mentioned above and their pharmacological in the treatment of PCOS was explored via network pharmacology analysis. The simple prediction results of network pharmacological analysis verified the feasibility and reliability of the established quantitative analysis method for 7 compounds in NJP, which were recommended as candidate indicators for quality evaluation ultimately. Using the TCMRD as the scientific ruler, quality grade specifications of NJP were proposed by comprehensive analysis of multiple index. Accordingly, 16, 47, and 13 batches of samples were primarily rated as first-grade, second-grade and unqualified grade respectively. This study will provide a chemical basis for quality control of NJP, which is necessary in the production process of pharmaceutical development.\u003c/p\u003e","manuscriptTitle":"Quality Grade Evaluation of Nvjin Pills Based on TCMRD and Application of Network Pharmacology to Explore the Anti- Polycystic Ovarian Syndrome Activity of Focused Compounds","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-02-06 14:46:14","doi":"10.21203/rs.3.rs-2531631/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0c8dc05c-578c-451a-b85f-ac7025a5746b","owner":[],"postedDate":"February 6th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-02-07T15:14:47+00:00","versionOfRecord":[],"versionCreatedAt":"2023-02-06 14:46:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2531631","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2531631","identity":"rs-2531631","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}