Screening method for quality difference marker of Mongolian medicine Gaohubaone-6

Abstract

The invention discloses a method for screening a quality difference marker of a Mongolian medicine Gaohubaone-6, and relates to the technical field of medicine detection. Comprising the following steps: S1, carrying out multi-index quantitative analysis on the Mongolian medicine Goler Figure Bione-6 by adopting an HPLC-MS / MS technology, and screening out a quality difference component group in combination with mode recognition-machine learning-weight coefficient analysis; s2, on the basis of a serum pharmaceutical chemistry method and an HPLC-Q-Exactive MS technology, comparing the difference between the in-vitro inherent chemical components and the serum migration components of the Gaichubaone-6 by adopting an analysis process of spectrum library retrieval and mass spectrum recognition, and analyzing a serum migration component group of the Gaichubaone-6; and S3, confirming a quality difference marker based on the common components of the quality difference component group and the serum migration component group. The method not only pays attention to quality difference components of the preparation, but also considers in-vivo functional components, and the quality of the preparation can be objectively, systematically and comprehensively analyzed.

Description

Technical Field

[0001] This invention relates to the field of drug detection technology, specifically to a method for screening quality difference markers of Mongolian medicine Gaoletubao-6. Background Technology

[0002] The Mongolian medicine Goltubao-6, also known as Qingyan Liuwei San, is a classic Mongolian prescription for treating lung diseases. It was first recorded in the Tibetan medical work "Four Medical Classics" written by the Tibetan physician Yuthok Yonten Gonpo, and is now included in the "Drug Standards of the Ministry of Health of the People's Republic of China: Mongolian Medicine Volume". The prescription consists of six medicinal materials: clove, hosta flower, gypsum, licorice, costus root, and chebula. This prescription is cooling in nature and is the main prescription for clearing lung heat. Clove is the chief ingredient for clearing lung heat, hosta flower is the auxiliary ingredient for clearing heat and relieving cough, gypsum and licorice are the assistant ingredients for relieving cough, expectorating phlegm and clearing lung heat, and costus root and chebula are the adjuvant ingredients for expectorating phlegm and regulating body constitution. The combined effects of these medicines are to relieve cough and asthma, clear heat and eliminate phlegm. Clinically, it is mainly used to treat lung heat, asthma, cough, yellow or bloody sputum, lung pain and lung damage caused by blood heat, etc.

[0003] A scientific and reasonable quality evaluation system and a continuously innovative and improved quality evaluation model are important prerequisites for the sustainable development of traditional compound preparations. However, the complexity and diversity of the components contained in traditional compound preparations, coupled with the "multi-component, multi-target" characteristics of their efficacy, make it difficult to comprehensively present the overall quality and intrinsic properties of the preparation by using only one herb as an indicator of its quality. While multi-indicator quantitative analysis can more comprehensively and systematically reflect the overall quality characteristics of the preparation, the weighting process is greatly affected by human factors when using multiple indicators for comprehensive quality evaluation, resulting in a lack of objectivity in the evaluation results. Currently, the existing quality standard for Golertuber-6 only includes appearance, identification, and dosage, which is somewhat broad. In recent years, research on Golertuber-6 has focused more on pharmacodynamic evaluation and mechanism of action, while there are few reports on its quality marker screening and comprehensive quality evaluation. Therefore, constructing a multi-dimensional and multi-perspective quality evaluation system for Golertuber-6 has significant practical implications for ensuring the efficacy and safety of the preparation and promoting its clinical application. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a method for screening quality difference markers for Mongolian medicine Gaoletubao-6.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: This invention provides a method for screening quality difference markers of Mongolian medicine Gaoletubao-6, the technical flowchart of which is shown below. Figure 1 As shown, the specific steps include: S1: Screening of quality-differentiating components: HPLC-MS / MS technology was used to perform multi-index quantitative analysis on Mongolian medicine Gaoletubao-6 to evaluate its overall quality from a macroscopic perspective. Subsequently, combined with chemical pattern recognition analysis, machine learning predictive analysis, and entropy weight method weight coefficient analysis, quality-differentiating components were screened out. S2: Identification of serum migrating components: Based on serum medicinal chemistry methods and HPLC-Q-ExactiveMS technology, the analysis process of spectral library retrieval and mass spectrometry identification was used to compare the differences between the in vitro inherent chemical components and serum migrating components of Golertuber-6, and then to analyze the serum migrating components of Golertuber-6. S3: Identify quality difference markers of Golpert-6 based on common components of quality difference component groups and serum migration component groups.

[0006] Furthermore, in step S1, the chromatographic and mass spectrometric conditions for HPLC-MS / MS are as follows: the chromatographic column is a Shim-pack GIST-HPC. 18 The flow rate was 2.1 mm × 100 mm, 3 μm; the mobile phase was methanol (A) - 0.1% formic acid aqueous solution (B), and the flow rate was 0.25 mL·min. -1 The column temperature was 35℃, and the injection volume was 5 μL. The gradient elution program was as follows: 0.01–0.5 min, 10% → 15% A; 0.5–1.0 min, 15% → 35% A; 1–3 min, 35% → 63% A; 3.0–5.0 min, 63% → 75% A; 5.0–5.5 min, 75%–95% A; 5.5–7.0 min, 95% → 95% A; 7.0–7.01 min, 95%–10% A; 7.01–9.5 min, 10%–10% A. An ESI ion source was used. - The mode employs multiple reaction monitoring (MRM) scanning, with the heating gas flow rate set to 10 L·min. -1 The desolventization temperature was set to 526℃, and the atomizing gas flow rate was set to 3 L·min. -1 .

[0007] Furthermore, in step S1, the chemical pattern recognition analysis includes cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis.

[0008] Furthermore, in step S1, the machine learning prediction analysis includes random forest analysis, linear discriminant analysis, artificial neural network analysis, and logistic regression analysis.

[0009] Further, in step S2, the chromatographic and mass spectrometric conditions for HPLC-Q-Exactive MS are as follows: using Eclipse Plus C 18The chromatographic column was 4.6 mm × 150 mm, 5 μm; the mobile phase was methanol (A) – 0.1% formic acid aqueous solution (B); the elution program was: 0–5 min, 10% → 10% A; 5–9 min, 10% → 24% A; 9–11 min, 24% → 43% A; 11–15 min, 43% → 60% A; 15–20 min, 60% → 68% A; 20–24 min, 68% → 75% A; 24–28 min, 75% → 85% A; 28–35 min, 85% → 90% A; 35–40 min, 90% → 90% A; the column temperature was 35 °C; the flow rate was 0.35 mL / min; the injection volume was 10 μL; the ion source was a HESI ion source; and the chromatography was performed using Full MS / dd-MS. 2 Detection, Full MS, dd-MS 2 The resolutions were 700 00 and 175 00, respectively, the spray voltage was set to 3.50kV (-) / 4.20kV (+), and the collision energy was set to 30eV.

[0010] Further, step S2 specifically involves: performing HPLC-Q-Exactive MS analysis on blank animal serum and drug-containing serum to obtain a total ion chromatogram; establishing a local database of Golperturb-6; and processing and analyzing the total ion chromatogram data using mass spectrometry software; with a mass deviation not exceeding 10 × 10⁻⁶. -6 To standardize the analysis of fragmentation information from secondary mass spectrometry and relevant literature, we characterized and analyzed the in vitro intrinsic chemical components and serum migrating components of Golertuber-6. In vitro intrinsic chemical components were identified in Golertuber-6. Based on the analysis of intrinsic chemical components, serum migrating components were identified in drug-containing serum.

[0011] Further, step S3 specifically involves: importing the serum migration component groups and quality difference component groups of Golpertoire-6 into the MicroBioscience scientific research mapping platform to draw a Venn diagram, thereby identifying potential quality difference markers of Golpertoire-6.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention, on the one hand, builds upon multi-index quantitative analysis results to construct an integrated strategy based on "pattern recognition, machine learning, and weight analysis," thereby scientifically and rationally screening the "quality-difference component groups" of Gorletubao-6. On the other hand, based on the concept of serum pharmacochemistry, the ability of active ingredients to enter the bloodstream is a prerequisite for the efficacy of traditional formulations. High-resolution liquid chromatography-mass spectrometry (LC-MS) is used to comprehensively characterize the transmissible substances in serum, analyzing the "serum transmissible component groups." Finally, the "quality-difference markers" of Gorletubao-6 are identified based on the common components of the "quality-difference component groups" and the "serum transmissible component groups." This approach not only considers the overall quality of the formulation but also the in vivo efficacy components, enabling objective, systematic, and comprehensive analysis of formulation quality. This integrated strategy provides a new approach and model for screening quality-difference markers and constructing a comprehensive quality evaluation system for Gorletubao-6, offering a reference for quality control and medication safety of Gorletubao-6, and providing data support for future selection of medicinal material origins and improvement of quality standards in the production of Gorletubao-6 formulations. Attached Figure Description

[0013] Figure 1 This is a flowchart of the technology of this invention; Figure 2 This is an MRM chromatogram of 9 components, where A: standards; B: sample; C: blank sample; In the figure, 1: gallic acid; 2: corilagin; 3: liquiditin; 4: rutin; 5: liquiditigenin; 6: quercetin; 7: luteolin; 8: costunolide; 9: dehydrocostus lactone. Figure 3 This is a cluster heatmap analysis of 18 batches of Gorlet-Borri-6; Figure 4 This is a PCA score chart for 18 batches of Göller-Turbo-6 samples; Figure 5 This is the OPLS-DA score chart of 18 batches of Göllertubao-6 samples; Figure 6 These are the permutation test results for the OPLS-DA model (n=200). Figure 7 It is a VIP chart of 9 components in Golbert-6; Figure 8 It is an artificial neural network analysis; Figure 9It is linear discriminant analysis; Figure 10 It is logistic regression analysis; Figure 11 It is random forest analysis; Figure 12 It is a Venn graph for machine learning; Figure 13 It is a weighting coefficient analysis; Figure 14 It is a screening of component groups with quality differences; Figure 15 This is the HPLC-Q-Exactive MS total ion chromatogram of the Golperton-6 sample. In the chromatogram, A is the total ion chromatogram in positive ion mode, B is the total ion chromatogram in negative ion mode, and C is the total number of inherent components and the proportion of each component. Figure 16 The total ion chromatogram of serum containing Golpertoire-6 is shown in HPLC-Q-Exactive MS. In this graph, A is the total ion chromatogram in positive ion mode, B is the total ion chromatogram in negative ion mode, and C is the total number of serum migrating components and the proportion of each component. Figure 17 It is a Venn diagram based on the "quality difference component group - serum migration component group". Detailed Implementation

[0014] To make the objectives and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention.

[0015] Unless otherwise specified, the instruments, reagents, and materials used in the following embodiments are all conventional instruments, reagents, and materials already available in the prior art and can be obtained through legitimate commercial channels. Unless otherwise specified, the experimental methods and detection methods used in the following embodiments are all conventional experimental methods and detection methods already available in the prior art.

[0016] Example 1 1. Materials 1.1 Instruments LC-MS8045 Triple Quadrupole Liquid Chromatography-Mass Spectrometry (Shimadzu Corporation, Japan); HPLC-QE High Performance Liquid Chromatography-Mass Spectrometry (Thermo Fisher Scientific); BSA224S 0.001% Balance (Sartorius Scientific Instruments (Beijing) Co., Ltd.); FA1204B 0.001% Electronic Balance (Qingdao Juchuang Century Environmental Protection Co., Ltd.); DS-7510DTH CNC Ultrasonic Cleaner (Shanghai Shengxi Ultrasonic Instrument Co., Ltd.); TGL-16MC High-Speed ​​Refrigerated Centrifuge (Changsha Xiangrui Centrifuge Co., Ltd.); ZLS-2 Vacuum Centrifuge Concentrator (Jiangsu Xundi Instrument Technology Co., Ltd.).

[0017] 1.2 Laboratory Animals Eight SD rats, half male and half female, weighing (250±20) g, were purchased from Beijing Spaford Laboratory Animal Center and housed at the New Drug Safety Evaluation Research Center of Inner Mongolia Medical University. They were acclimatized for 7 days and given standard feed and drinking water. The room temperature was maintained at (24±2) ℃ and the relative humidity at (55±5)%, with a 12 / 12h diurnal cycle. They were fasted for 12 hours before the experiment but were allowed normal drinking water.

[0018] 1.3 Drug Testing Eighteen batches of Gaoletubao-6 were purchased from Inner Mongolia Mongolian Medicine Co., Ltd., Aoteqi Mongolian Medicine, and Fuxin Mongolian Medicine Co., Ltd., with six batches from each manufacturer, all with a specification of 1.5g / bag. Rutin reference standard (batch number: DST210520-017, purity: 99.0%) was provided by Chengdu Desite Biotechnology Co., Ltd. Glycyrrhizin reference standard (batch number: PS021113, purity: 98.0%), Corilagin reference standard (batch number: PS011824, purity: 98.0%), Costunolide reference standard (batch number: PS012310, purity: 98.0%), Dehydrocostunolide reference standard (batch number: PS010244, purity: 98.0%), and Luteolin reference standard (batch number: M-007-181216, purity: 98.0%) were provided by Chengdu Pusi Biotechnology Co., Ltd. Glycyrrhizin reference standard (batch number: 111610-201607, purity: 98.5%), gallic acid reference standard (batch number: 110831-201204, purity: 98.0%), and quercetin reference standard (batch number: 100081-200406, purity: 98.0%) were purchased from the National Institutes for Food and Drug Control, China. Methanol (chromatographic grade, Fisher Scientific, USA), formic acid (analytical grade, Tokyo Chemical Industry Co., Ltd.), and distilled water (Watsons Co., Ltd., Guangzhou) were also supplied.

[0019] 2. Methods and Results 2.1 Quantitative Analysis of Goretura-6 2.1.1 Chromatographic-Mass Spectrometry Conditions The chromatographic column was a Shim-pack GIST-HPC. 18 (2.1 mm × 100 mm, 3 μm), the mobile phase was methanol (A) - 0.1% formic acid aqueous solution (B), and the flow rate was 0.25 mL·min. -1 The column temperature was 35℃, and the injection volume was 5μL. The gradient elution program was as follows: 0.01~0.5min, 10%→15%A; 0.5~1.0min, 15%→35%A; 1~3min, 35%→63%A; 3.0~5.0min, 63%→75%A; 5.0~5.5min, 75%~95%A; 5.5~7.0min, 95%→95%A; 7.0~7.01min, 95%~10%A; 7.01~9.5min, 10%~10%A.

[0020] Using an ESI ion source, ESI - The mode employs multiple reaction monitoring (MRM) scanning, with the heating gas flow rate set to 10 L·min. -1 The desolventization temperature was set to 526℃, and the atomizing gas flow rate was set to 3 L·min. -1 .

[0021] 2.1.2 Preparation of test solution Take 0.2 g of Golpertur-6 sample into a 50 mL Erlenmeyer flask, add 5 mL of 70% methanol aqueous solution, weigh, seal, and sonicate for 40 min (power 200 W, frequency 70 kHz). After cooling to room temperature, add 70% methanol aqueous solution to make up the weight, shake well, take the above solution, dilute 100 times with 70% methanol aqueous solution, filter through a 0.22 μm filter membrane to obtain the Golpertur-6 test solution, store at 4℃ for LC-MS analysis.

[0022] 2.1.3 Preparation of reference solution Accurately weigh 3.53 mg of glycyrrhizin, 4.25 mg of gallic acid, 5.11 mg of corilagin, 3.43 mg of costunolide, 3.70 mg of rutin, 3.87 mg of luteolin, 3.21 mg of quercetin, 3.74 mg of glycyrrhizin, and 3.21 mg of dehydrocostunolide. Place each in a 10 mL volumetric flask, dissolve in methanol using ultrasonication, and dilute to volume. Prepare glycyrrhizin, gallic acid, corilagin, costunolide, rutin, luteolin, quercetin, glycyrrhizin, and dehydrocostunolide with mass concentrations of 353.00, 425.00, 511.00, 343.00, 370.00, 387.00, 321.00, 374.00, and 321.00 μg·mL, respectively. -1For the preparation of single reference standard stock solutions, accurate amounts of each stock solution were measured and placed in the same 10 mL volumetric flask, then diluted to volume with 70% methanol to obtain mass concentrations of 1926.00, 187.00, 193.50, 1496.00, 2044.00, 321.00, 2550.00, 1372.00, and 706.00 ng·mL, respectively. -1 Mix the reference solution and store at 4°C for LC-MS analysis.

[0023] 2.1.4 Preparation of blank control solution Without adding Golperturb-6, prepare a blank control solution according to the test solution preparation method in section "2.1.2".

[0024] 2.1.5 Specificity Examination Nine analytes were subjected to precursor ion scanning, product ion scanning, voltage optimization, and chromatographic elution procedures to obtain the MRM quantitative mass spectrometry parameters for each component (Table 1). MRM chromatograms of the mixed reference solution, the Golperturb-6 test solution, and the blank control solution were obtained using the chromatographic-mass spectrometry conditions described in section "2.1.1". Figure 2 The results showed that the retention time of the analyte in the spectrum of the test solution was consistent with that of each reference standard, while the blank control solution showed no interference at the corresponding position.

[0025] Table 19 MRM mass spectrometry analysis parameters for the analytes

[0026] 2.1.6 Examination of Linear Relationships Accurately measure 0.01, 0.10, 0.20, 0.40, 0.60, 0.80, and 1.00 mL of the mixed reference solution under section "2.1.3" into 1.0 mL volumetric flasks, and dilute to 1.0 mL with 70% methanol aqueous solution to prepare each series of mixed reference solutions. Inject and analyze according to the analytical method under section "2.1.1", and express the results as the mass concentration (X, ng·mL) of each component. -1 The x-axis is denoted by (x) and the y-axis is denoted by (y). The linear relationship of each component to be measured was fitted using the "browser" function of LabSolutions software in the MS system. The results are shown in Table 2.

[0027] Table 2. Regression equations and linear ranges of the nine components in Golbert-6.

[0028] 2.1.7 Precision Test Take a 2.5-fold diluted mixed reference solution from section “2.1.6” (the mass concentrations of glycyrrhizin, gallic acid, corilagin, costunolide, rutin, luteolin, quercetin, glycyrrhizin, and dehydrocostunolide are 282.4, 1020.0, 128.4, 548.8, 74.8, 77.4, 128.4, 598.4, and 770.4 ng / mL, respectively, and the concentrations of the reference solution are as follows). Six consecutive injections were performed under the analytical conditions described in section "2.1.1", and the peak areas were recorded. The RSDs of the peak areas of glycyrrhizin, gallic acid, corilagin, costone lactone, rutin, luteolin, quercetin, glycyrrhizin, and dehydrocostone lactone were 1.93%, 1.61%, 2.97%, 1.81%, 2.85%, 2.26%, 2.11%, 2.75%, and 1.55%, respectively, indicating that the instrument has good precision.

[0029] 2.1.8 Stability Test Approximately 0.2 g of the Golpertoire-6 sample was weighed and the test solution was prepared according to the method described in section "2.1.2". The solution was left at room temperature and analyzed at 0, 2, 4, 8, 12, 18, and 24 hours according to the method described in section "2.1.1". The peak areas RSD of glycyrrhizin, gallic acid, corilagin, costenolide, rutin, luteolin, quercetin, glycyrrhizin, and dehydrocostenolide were 2.92%, 2.26%, 2.10%, 1.72%, 2.98%, 1.88%, 2.94%, 1.66%, and 2.87%, respectively, indicating that the test solution had good stability within 24 hours of being left at room temperature.

[0030] 2.1.9 Repeatability Test Approximately 0.2 g of Golpertur-6 sample was weighed and prepared in six parallel replicates. The test solution was prepared according to the method described in section "2.1.2" and analyzed by injection according to the method described in section "2.1.1". The result showed that the glycyrrhizin content was 486.484 μg·g. -1 (1.98%), gallic acid content was 2900.346 μg·g. -1 (RSD was 2.14%), Corilagin content was 307.076 μg·g. -1 (RSD was 2.91%), and the content of costunolide was 1228.509 μg·g. -1 (RSD was 2.63%), rutin content was 10.656 μg·g -1 (RSD was 2.16%), luteolin content was 12.725 μg·g. -1 (RSD was 2.99%), quercetin content was 65.685 μg·g. -1 (RSD was 1.99%), glycyrrhizin content was 3339.859 μg·g. -1(RSD was 2.33%), and the content of dehydroauratelactone was 1873.069 μg·g. -1 (RSD of 2.79%) indicates that the method has good reproducibility.

[0031] 2.1.10 Recovery rate analysis Accurately weigh 6 portions of Golpertur-6 sample, 0.1 g each, and add 1 mL of mixed reference solution to each portion at an approximate 1:1 ratio. Prepare test solutions according to the method in section "2.1.2" and analyze them according to the method in section "2.1.1". The average recovery rates of each component were calculated to be between 98.26% and 103.42%, and the RSD values ​​were between 0.92% and 1.86%, indicating that the method has good accuracy.

[0032] 2.1.1 Determination of the content of 9 components in batch 1118 of Goler Tubao-6 Take 18 batches of Golertuber-6, weigh 3 samples from each batch, prepare Golertuber-6 test solutions according to the method under "2.1.2", inject and determine the content under the conditions under "2.1.1", calculate the average content, and the results are shown in Table 3.

[0033] Table 318 shows the content of 9 components in batch 318 of Goletopure-6.

[0034] 2.2 Chemical Pattern Recognition Analysis 2.2.1 Cluster Analysis (CA) Cluster analysis of the average content of nine components was performed using the MicroBio Information online analysis platform, and a cluster heatmap was generated. Figure 3 Clustering results showed that 18 batches of Goletubao-6 were clustered into two major categories: batches from manufacturers A and C were clustered into one category, and batches from manufacturer B were clustered into another category. At the same time, batches from manufacturers A and C were clustered separately, indicating that there are certain differences in the quality of Goletubao-6 from different manufacturers.

[0035] 2.2.2 Principal Component Analysis (PCA) and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) PCA was performed on the average content of the nine components using SIMCA14.1 software. Figure 4 Consistent with the cluster analysis results, the GOLET-6 samples from each manufacturer were clustered separately; further construction of the OPLS-DA model showed that ( Figure 5 The resulting supervised model R 2 X 0.623, R 2 Y It is 0.894. Q2 The P-value was 0.795, and all parameters were greater than 0.5, indicating that the established OPLS-DA model was stable, feasible, and had good predictive ability. The OPLS-DA results were consistent with the CA and PCA analysis results, suggesting that there were certain quality differences among different batches of Goretto-Borre-6. To prevent overfitting of the OPLS-DA model and the occurrence of false positive results, the model was validated by a permutation test with 200 random permutations. (See Figure...) Figure 6 It can be seen that, Q 2 All in R 2 Under these circumstances, at the same time Q 2 The Y-intercept of the fitted regression line was -0.547 < 0, further confirming the effectiveness of the model.

[0036] 2.2.3 Screening of potential quality difference markers To screen for components that cause significant inter-batch variability, components with quality differences were screened using a variable importance in projection (VIP) value > 1. The results showed that ( Figure 7 There were 6 components with a VIP value > 1, namely dehydroauratelactone (VIP=1.221), corilagin (VIP=1.209), glycyrrhizin (VIP=1.178), quercetin (VIP=1.022), costunolide (VIP=1.022), and glycyrrhizin (VIP=1.022). It is inferred that these 6 components may be the key components that cause the difference between batch 6 and batch 7 of Goltopur.

[0037] 2.3 Machine Learning Predictive Analysis To screen feature components with significant differences, six confusion matrix training models were constructed using 70% of the sample datasets from manufacturers A, B, and C: Linear Discriminant Analysis (LDA), Random Forest (RF), K-Nearest Neighbors (KNN), Artificial Neural Network (ANN), Generalized Linear Model (GLM), and Logistic Regression (LR). The results showed that ANN, LDA, LR, and RF models exhibited good predictive performance. To reduce the number of variables and improve recognition efficiency, these four models were used to build confusion matrix test models for the remaining 30% of the sample datasets from manufacturers A, B, and C. The test models achieved 100% accuracy and precision. The contributions of all feature variables under the four machine learning models were ranked. Figures 8 to 11 A Venn diagram was plotted using the top 5 components from the four machine learning models. Figure 12 The results showed that three cross-linked components were obtained: glycyrrhizin, glycyrrhizin, and dehydroauracetin.

[0038] 2.4 Weighting Coefficient Analysis The content determination results of nine components in 18 batches of Goretura-6 were imported into the SPSSAU online analysis platform (https: / / spssau.com / indexs.html). Entropy weight analysis was performed using the entropy weight method to calculate the information entropy value and weight coefficient. The information entropy value reflects the dispersion trend of the evaluation index. The smaller the value, the greater the dispersion of the evaluation index. The larger the weight coefficient, the greater its contribution to the difference in the comprehensive quality evaluation. The results are shown in [Figure number missing]. Figure 13 The top 5 ingredients by weighting coefficient are glycyrrhizin, glycyrrhizin, luteolin, corilagin, and dehydroauracetin.

[0039] 2.5 Screening of Quality Difference Components A Venn diagram was plotted using machine learning predictive analysis to obtain three components (dehydroauracetin, glycyrrhizin, and glycyrrhizin), weighted coefficient analysis to obtain five components (dehydroauracetin, glycyrrhizin, glycyrrhizin, luteolin, and corilagin), and chemical pattern recognition analysis to obtain six components (dehydroauracetin, corilagin, glycyrrhizin, quercetin, costane lactone, and glycyrrhizin). The results identified three groups of components with varying quality: dehydroauracetin, glycyrrhizin, and glycyrrhizic acid. Figure 14 ).

[0040] 2.6 Identification of Goretoura-6 serum migrating components 2.6.1 Chromatographic and Mass Spectrometric Conditions Using Eclipse Plus C 18 A 4.6 mm × 150 mm, 5 μm column was used. The mobile phase was methanol (A) – 0.1% formic acid aqueous solution (B). The elution program was as follows: 0–5 min, 10% → 10% A; 5–9 min, 10% → 24% A; 9–11 min, 24% → 43% A; 11–15 min, 43% → 60% A; 15–20 min, 60% → 68% A; 20–24 min, 68%–75% A; 24–28 min, 75%–85% A; 28–35 min, 85%–90% A; 35–40 min, 90% → 90% A. The column temperature was 35 °C, the flow rate was 0.35 mL / min, and the injection volume was 10 μL. An HESI ion source was used. Full MS / dd-MS was employed. 2 Detection, Full MS, dd-MS 2 The resolutions were 700 00 and 175 00, respectively, the spray voltage was set to 3.50kV (-) / 4.20kV (+), and the collision energy was set to 30eV.

[0041] 2.6.2 Preparation of reference solution Accurately weigh 3.53 mg of glycyrrhizin, 4.25 mg of gallic acid, 5.11 mg of corilagin, 3.43 mg of costunolide, 3.70 mg of rutin, 3.87 mg of luteolin, 3.21 mg of quercetin, 3.74 mg of glycyrrhizin, and 3.21 mg of dehydrocostunolide. Place each in a 10 mL volumetric flask, dissolve in methanol using ultrasonication, and dilute to volume. Prepare glycyrrhizin, gallic acid, corilagin, costunolide, rutin, luteolin, quercetin, glycyrrhizin, and dehydrocostunolide with mass concentrations of 353.00, 425.00, 511.00, 343.00, 370.00, 387.00, 321.00, 374.00, and 321.00 μg·mL, respectively. -1 For the preparation of single reference standard stock solutions, accurately measure 10 μL of each of the above single reference standard stock solutions and place them in the same 10 mL volumetric flask. Dilute to volume with 70% methanol to obtain mass concentrations of 1353.00, 425.00, 511.00, 343.00, 370.00, 387.00, 321.00, 374.00, and 321.00 ng·mL, respectively. -1 Mix the reference solution and store at 4°C for LC-MS analysis.

[0042] 2.6.3 Preparation of Goretura-6 test solution Take 0.2 g of Golpertur-6 sample into a 50 mL Erlenmeyer flask, add 5 mL of 70% methanol aqueous solution, weigh, seal, sonicate for 40 min (power 200 W, frequency 70 kHz), bring to room temperature, add 70% methanol aqueous solution to make up the weight, shake well, filter through a 0.22 μm filter membrane to obtain the Golpertur-6 test solution, store at 4℃ for LC-MS analysis.

[0043] 2.6.4 Preparation of serum samples Weigh 15.55 g of Golpertur-6 sample into a 50 mL centrifuge tube, add 50 mL of purified water and sonicate to dissolve, preparing a concentration of 311 mg / mL. -1 Golerturi-6 suspension. Simultaneously, SD rats were randomly divided into a blank control group and a drug group according to body weight. The rats were fasted the night before gavage but allowed free water. The drug group received 3.11 g / kg. -1 The control group was given Golerturide-6 suspension, while the control group was given purified water, with a gavage volume of 10 mL / kg. -1 Once daily for 3 consecutive days, blood samples were collected from each group at 0.5, 1.0, 1.5, 2.0, and 4.0 hours after the last administration. The blood was collected from the fundus venous plexus and incubated at 4°C at 3000 rpm. -1 Centrifuge for 10 minutes, collect the supernatant serum, and store at -20°C for subsequent analysis.

[0044] 2.6.5 Serum Sample Processing Serum samples collected at different time points (400 μL each) were combined into 10 mL centrifuge tubes. Then, 6.0 mL of chromatographic methanol was added, and the mixture was vortexed for 1 min, followed by centrifugation at 12000 rpm at 4 °C. -1 Centrifuge at 10 min, concentrate and evaporate the supernatant to dryness, then reconstitute with 100 μL of chromatographic methanol, and centrifuge at 4 °C and 12000 r·min. -1 Centrifuge for 10 min under the specified conditions, take the supernatant and transfer it to the inner liner, and store it at 4°C for subsequent analysis.

[0045] Under section “2.6.2”, take 100 μL of the mixed control solution and add it to 500 μL of blank serum. Prepare a serum sample containing the mixed control according to the serum sample processing procedure described above.

[0046] 2.6.6 Analysis of inherent chemical composition and serum migrating components The test solution of Golperturb-6 and the serum sample solution containing the drug were analyzed according to the analytical method under section "2.6.1" to obtain the total ion chromatograms in positive and negative ion modes. Figure 15 , Figure 16 Based on databases such as the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), CNKI, and Wanfang, a local database of Goretum-6 was established (including compound names, ion modes, and fragment ions). Mass spectrometry software was used to process and analyze the total ion current data (processing included: molecular formula fitting, peak extraction, accurate molecular weight calculation, and deviation calculation), with a mass deviation not exceeding 10 × 10⁻⁶. -6 To standardize the analysis, we combined secondary mass spectrometry fragmentation information with relevant literature data to characterize and analyze the in vitro intrinsic chemical components and serum migrating components of Golertuber-6. A total of 67 intrinsic chemical components were identified in Golertuber-6, as shown in Table 4. Based on the in vitro component analysis, 25 exogenous compounds were identified in the drug-containing serum of rats, as shown in Table 5.

[0047] Table 4. HPLC-Q-Exactive MS identification results of chemical components of Golbert-6. , ,

[0048] Table 5. HPLC-Q-Exactive MS identification results of Golperturb-6 serum migrating components. ,

[0049] 2.7 Confirmation of Potential Quality Difference Markers for Gorlet-6 Twenty-five serum migrating components from Golbert-6 (citric acid, gallic acid, gallic acid-3-O-β-D-glucoside, protocatechuic acid, methyl gallate, corilagin, 1,3,6-tri-O-galloylglucose, 1,2,3,6-tetragalloylglucose, glycyrrhizin, glycyrrhizin, apigenin, ferulic acid, isoglycyrrhizin, isoglycyrrhizin, glycyrrhizin chalcone B, luteolin, rutin, stigmosiderin, glycyrrhizin H, glycyrrhizin B, glycyrrhizin G, costunolide, dehydrocostunolide, glycyrrhizic acid, glycyrrhizin chalcone C) and three mass-difference components (dehydrocostunolide, glycyrrhizin, glycyrrhizin) were imported into the BioInformatics Scientific Mapping Platform (https: / / www.bioinformatics.com.cn / ) to generate a Venn diagram. The results are as follows: Figure 17 As shown, under this research strategy, dehydroauracetamide, glycyrrhizin, and glycyrrhizin were identified as potential markers of quality variation in Golertuber-6.

[0050] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for screening quality difference markers of Mongolian medicine Gaoletubao-6, characterized in that: Specifically, it includes the following steps: S1: Screening of quality-differentiating components: HPLC-MS / MS technology was used to perform multi-index quantitative analysis on Mongolian medicine Gaoletubao-6 to evaluate its overall quality from a macroscopic perspective. Subsequently, combined with chemical pattern recognition analysis, machine learning predictive analysis, and entropy weight method weight coefficient analysis, quality-differentiating components were screened out. The chemical pattern recognition analysis includes cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis. The machine learning predictive analysis includes random forest analysis, linear discriminant analysis, artificial neural network analysis, and logistic regression analysis; S2: Identification of serum migrating components: Based on serum medicinal chemistry methods and HPLC-Q-ExactiveMS technology, the analysis process of spectral library retrieval and mass spectrometry identification was used to compare the differences between the in vitro inherent chemical components and serum migrating components of Golertuber-6, and then to analyze the serum migrating components of Golertuber-6. S3: Identify quality difference markers of Golpert-6 based on common components of quality difference component groups and serum migration component groups.

2. The screening method according to claim 1, characterized in that: In step S1, the HPLC-MS / MS chromatographic conditions are as follows: the chromatographic column is a Shim-pack GIST-HPC. 18 The flow rate was 2.1 mm × 100 mm, 3 μm; the mobile phase was methanol (A) - 0.1% formic acid aqueous solution (B), and the flow rate was 0.25 mL·min. -1 The column temperature was 35℃, and the injection volume was 5μL; the gradient elution program was 0.01~0.5min, 10%→15%A. 0.5~1.0min, 15%→35%A; 1~3min, 35%→63%A; 3.0~5.0min, 63%→75%A; 5.0~5.5min, 75%~95%A ;5.5~7.0min, 95%→95%A; 7.0~7.01min, 95%~10%A; 7.01~9.5min, 10%~10%A; using ESI ion source, ESI - The mode employs multiple reaction monitoring (MRM) scanning, with the heating gas flow rate set to 10 L·min. -1 The desolventization temperature was set to 526℃, and the atomizing gas flow rate was set to 3 L·min. -1 .

3. The screening method according to claim 1, characterized in that: In step S2, the chromatographic and mass spectrometric conditions for HPLC-Q-Exactive MS are as follows: using Eclipse Plus C 18 Chromatographic column, 4.6 mm × 150 mm, 5 μm; Mobile phase: methanol (A) - 0.1% formic acid aqueous solution (B); elution program: 0–5 min, 10% → 10% A; 5–9 min, 10% → 24% A; 9–11 min, 24% → 43% A; 11–15 min, 43% → 60% A; 15–20 min, 60% → 68% A; 20–24 min, 68%–75% A; 24–28 min, 75%–85% A; 28–35 min, 85%–90% A; 35–40 min, 90% → 90% A; column temperature: 35 °C; flow rate: 0.35 mL / min; injection volume: 10 μL; ion source: HESI ion source; Full MS / dd-MS. 2 Detection, Full MS, dd-MS 2 The resolutions were 700 00 and 175 00, respectively, the spray voltage was set to 3.50kV (-) / 4.20kV (+), and the collision energy was set to 30eV.

4. The screening method according to claim 1, characterized in that: Step S2 specifically involves: performing HPLC-Q-Exactive MS analysis on blank animal serum and drug-containing serum to obtain the total ion chromatogram; establishing a local database of Golbert-6; and processing and analyzing the total ion chromatogram data using mass spectrometry software; with a mass deviation not exceeding 10 × 10⁻⁶. -6 To standardize the analysis of fragmentation information from secondary mass spectrometry, the in vitro intrinsic chemical components and serum migrating components of Golertuber-6 were characterized and analyzed. In vitro intrinsic chemical components were identified in Golertuber-6. Based on the analysis of intrinsic chemical components, serum migrating components were identified in drug-containing serum.

5. The screening method according to claim 1, characterized in that: Step S3 specifically involves importing the serum migration component groups and quality difference component groups of Golertuber-6 into the MicroBioScientia scientific research mapping platform to draw a Venn diagram and identify potential quality difference markers of Golertuber-6.

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