Establishment of HPLC fingerprint of Jianbi decoction

Abstract

The application provides a method for establishing an HPLC fingerprint of Juanbi decoction, and belongs to the technical field of chemical analysis. The method comprises the following steps: S1. preparing a material reference of Juanbi decoction; S2. preparing a single-ingredient medicinal slice sample; S3. preparing a negative sample; S4. preparing a standard solution; and S5. performing chromatographic analysis. The method can help screen out a pharmacodynamic material basis of JBD for resisting RA, and the research provides a solid research basis for establishing a quality evaluation standard for component screening of JBD for resisting RA and development of JBD products.

Description

Technical Field

[0001] This invention relates to the field of chemical analysis technology, specifically to a method for establishing an HPLC fingerprint of Juanbi Decoction. Background Technology

[0002] Rheumatoid arthritis (RA) is a chronic autoimmune disease with a very high rate of disability, cardiovascular complications, and the induction of malignant tumors. Its main pathological features are continuous synovitis and pannus formation in the hands, wrists, knees, and ankles, leading to synovial tissue hyperplasia. According to statistics from the International Institute of Rheumatology (ILR), the global prevalence of RA is 1%, while in China it is 0.42%. The incidence rate in women is 2-3 times higher than in men, with a heritability rate of approximately 60%. RA affects a wide population and is increasingly affecting younger people.

[0003] At present, the main means of preventing and treating RA is to take non-steroidal anti-inflammatory drugs (NSAIDs). However, long-term use of a large amount of NSAIDs can cause side effects such as gastrointestinal ulcers, liver damage, dizziness, cardiovascular diseases, etc. in patients, and there are also many insufficient consequences such as poor compliance of RA patients and high recurrence rate after drug withdrawal. Modern experiments and clinical studies have shown that many classical prescriptions and effective prescriptions in China can inhibit the inflammation of RA joint synovium, delay bone destruction, and improve the condition of patients. Based on the concept of "treating the same disease with different therapies and different diseases with the same therapy" in traditional Chinese medicine, regulating RA from multiple targets and multiple pathways can effectively reduce the side effects of patients. Juanbi Decoction (JBD) is one of the classic famous prescriptions in China. It comes from "Medical Anecdotes" and is composed of Notopterygium incisum Ting ex H.T.Chang (Notopterygium root), Angelica pubescens Maxim. (Pubescent Angelica), Gentiana macrophylla Pall. (Large-leaved Gentian), Angelica sinensis (Oliv.) Diels (Chinese Angelica), Morus alba L. (Mulberry leaf), Piper kadsura Choisy Ohwi (Kadsura pepper), Boswellia carteri Birdw. (Frankincense), Aucklandia lappa Decne. (Costus root), Ligusticum chuanxiong Hort. (Szechuan Lovage Rhizome), Angelica pubescens Maxim. (Licorice root), Cinnamomum cassia (L.) J.Presl (Cinnamon). The whole prescription is warm but not dry, and it can dredge the channels without damaging healthy qi. It is widely used in traditional Chinese medicine clinical practice to treat arthralgia caused by the combination of wind, cold and dampness, and has the effects of dispelling wind and dampness, dispelling cold, promoting blood circulation and dredging collaterals, etc. Existing studies have shown that JBD can alleviate the symptoms of collagen-induced arthritis mice and tumor necrosis factor transgenic mice by reducing the arthritis index and the thickness of the hind paws. The main chemical components of JBD are coumarins, flavonoids, volatile oils, alkaloids, terpenoids, etc. These components all have a certain effect on anti-RA. However, the pharmacodynamic substance basis of the chemical components and their effects on RA is not yet clear, which greatly restricts the quality control and clinical application of this prescription.

[0004] The spectrum-effect relationship of traditional Chinese medicine refers to a discipline that, based on the modern research of traditional Chinese medicine theory, takes the fingerprint spectrum of traditional Chinese medicine as the basis, takes effectology as the main research content, and applies bioinformatics methods to establish the relationship between the fingerprint spectrum of traditional Chinese medicine and the pharmacodynamic effect of traditional Chinese medicine. It is a new and frontier research idea in the modernization of traditional Chinese medicine. The spectrum-effect relationship is one of the research models for the pharmacodynamic substance basis of traditional Chinese medicine. By combining the fingerprint spectrum technology and the pharmacodynamic evaluation system using statistical means, the pharmacodynamic substance basis can be further clarified and the quality of traditional Chinese medicine can be evaluated. Summary of the Invention

[0005] The purpose of this invention is to propose a method for establishing an HPLC fingerprint of JBD (a traditional Chinese medicine formula) for treating rheumatism. First, a fingerprint of JBD is established using high-performance liquid chromatography (HPLC). Then, using an adjuvant-induced arthritis (RA) model, the pharmacological effects of JBD against rheumatoid arthritis (RA) are explored. Next, grey relational analysis (GRA), least squares regression analysis (OPLS), and entropy method are used to perform a spectrum-effect analysis of JBD. Finally, the relationship between JBD and its efficacy is further determined by comparing the JBD fingerprint established by HPLC with the levels of IL-1β, CRP, and RF in rat serum. This will help to screen the pharmacological basis of JBD's anti-RA effects. This study provides a solid research basis for screening the anti-RA components of JBD and establishing quality evaluation standards for the development of JBD products.

[0006] The technical solution of this invention is implemented as follows:

[0007] This invention provides a method for establishing an HPLC fingerprint of Juanbi Decoction, comprising the following steps:

[0008] S1. Preparation of the material basis of Juanbi Decoction: Weigh out Angelica sinensis, mulberry twig, Notopterygium incisum, Angelica pubescens, Gentiana macrophylla, cinnamon, stir-fried licorice, Ligusticum chuanxiong, Piper kadsura, frankincense, and costus root, add water and decoct, filter, filter through a microporous membrane, concentrate the filtrate under reduced pressure and freeze dry to obtain the material basis of Juanbi Decoction.

[0009] S2. Preparation of single-herb decoction samples: Weigh each herb, add water and decoct, filter, filter through a microporous membrane to obtain single-herb decoction samples;

[0010] S3. Preparation of negative samples: Weigh out the slices of herbs that are lacking Angelica sinensis, mulberry twig, Notopterygium incisum, Angelica pubescens, Gentiana macrophylla, cinnamon, stir-fried licorice, Ligusticum chuanxiong, Piper kadsura, frankincense, and aromatic herbs, add water to decoct, filter, filter through a microporous membrane, concentrate the filtrate under reduced pressure and freeze dry to obtain negative samples.

[0011] S4. Preparation of standard solutions: Weigh appropriate amounts of neochlorogenic acid, loganic acid, gentiopicrin, ferulic acid, glycyrrhizin, imperatorin, cinnamaldehyde, ammonium glycyrrhizate, notopterygium alcohol, ligustilide, osthol, isoimperatorin, dihydroapigenin angelic acid ester, angelicin A, and 11-carbonyl-β-acetylboswellic acid, and prepare a mixed reference solution with methanol solution to obtain the standard solution.

[0012] S5. Chromatographic analysis: Liquid chromatography was used to analyze the above-mentioned Juanbi Decoction reference material, single herbal medicine sample, negative sample, and standard solution to obtain the HPLC fingerprint of Juanbi Decoction. The chromatographic peaks of 15 components in the Juanbi Decoction reference material were identified based on the retention time of each substance in the standard solution.

[0013] As a further improvement of the present invention, the mass ratio of Angelica sinensis, mulberry twig, Notopterygium incisum, Angelica pubescens, Gentiana macrophylla, cinnamon, stir-fried licorice root, Ligusticum chuanxiong, Piper kadsura, frankincense, and costus root in step S1 is 11-12:11-12:3.6-3.9:3.6-3.9:3.6-3.9:1.7-1.9:1.7-1.9:2.5-2.7:7.3-7.6:2.8-3:2.8-3.

[0014] As a further improvement of the present invention, the solid-liquid ratio of the medicinal materials and water used for decoction is 1:8-12 g / mL.

[0015] As a further improvement of the present invention, the decocting time is 0.5-1.5 hours, and the decocting is performed 1-2 times.

[0016] As a further improvement of the present invention, the chromatographic column used in step S5 is a Thermo Fisher Acclaim 120 C18 column with a size of 4.6 × 250 mm and a particle size of 5 μm.

[0017] As a further improvement of the present invention, in step S5, the mobile phase is acetonitrile A-0.2% formic acid aqueous solution B, with gradient elution under the following conditions (A:B, v / v): 0-23 min, 8%-17% A; 23-40 min, 17%-24% A; 40-48 min, 24%-33% A; 48-62 min, 33%-34% A; 62-73 min, 34%-57% A; 73-89 min, 57%-73% A; 89-100 min, 73%-100% A; 100-110 min, 100% A.

[0018] As a further improvement of the present invention, the detection wavelength in step S5 is 1-23 min, 250 nm; 23-65 min, 300 nm; 65-110 min, 250 nm.

[0019] This invention further protects an HPLC fingerprint of the Juanbi Decoction prepared by the above method.

[0020] As a further improvement of the present invention, there are a total of 15 common peaks, namely, peak 3 neochlorogenic acid, peak 4 loganic acid, peak 8 gentiopicrin, peak 11 ferulic acid, peak 12 glycyrrhizin, peak 13 imperatorin, peak 25 cinnamaldehyde, peak 28 ammonium glycyrrhizate, peak 31 ligustilide, peak 33 ligustilide, peak 34 osthol, peak 35 isoimperatorin, peak 37 dihydroaperitol angelic acid ester, peak 39 angelic acid lactone A, and peak 42 11-carbonyl-β-acetylsalicylic acid.

[0021] The present invention has the following beneficial effects:

[0022] This invention first establishes a fingerprint of JBD using high-performance liquid chromatography (HPLC), and then explores the pharmacological effects of JBD against rheumatoid arthritis (RA) using an adjuvant-induced arthritis (RA) model. Next, grey relational analysis (GRA), least squares regression analysis (OPLS), and entropy analysis are used to perform a spectrum-effect analysis of JBD. Finally, the relationship between JBD and its efficacy is further determined by comparing the JBD fingerprint established by HPLC with the levels of IL-1β, CRP, and RF in rat serum. This will help to screen the pharmacological basis of JBD's anti-RA effects. This study provides a solid research basis for screening JBD's anti-RA components and establishing quality evaluation standards for the development of JBD products.

[0023] Traditional Chinese medicine (TCM) is characterized by its multi-component, multi-target, and holistic nature, making its quality crucial for ensuring clinical efficacy. The complex composition of TCM makes quality control difficult, and relying on single indicative components is insufficient to accurately assess its true quality. Characteristic chromatograms of TCM, as a method for evaluating the chemical components in multi-component compound systems, have become a widely used quality evaluation model in the field of TCM. Their holistic and fuzzy nature allows for a comprehensive reflection of the intrinsic quality of TCM. Chemometrics can study the differences between data to compensate for the shortcomings of characteristic chromatograms. This study established an HPLC fingerprint of JBD (Junior Highly Blended Bacteria). Methodological evaluation results showed that this method had good precision, repeatability, and stability. Similarity evaluation results indicated that the chemical composition of different batches of JBD was consistent, with small quality differences. Chemical pattern recognition classified them into two categories, indicating differences between JBD reference samples, but these differences were small and may be related to the selection of experimental samples. By comparing with the mixed reference standard, 15 components were identified, including neochlorogenic acid, loganic acid, gentiopicrin, ferulic acid, glycyrrhizin, imperatorin, cinnamaldehyde, ammonium glycyrrhizate, notopterygium alcohol, ligustilide, osthol, isoimperatorin, dihydroaperitol angelic acid ester, angelicin A, and 11-carbonyl-β-acetylsalicylic acid.

[0024] This study established a rat model of rheumatoid arthritis (RA) by intradermal injection of acetic acid (CA) into the toes. RA is a chronic autoimmune disease with a very high rate of disability, cardiovascular complications, and malignant tumor induction. Traditional Chinese medicine (TCM) believes that the pathogenesis of RA is mainly due to insufficient vital energy (Qi) in the body, leading to the invasion of external pathogens such as wind, dampness, dryness, cold, summer heat, and fire, causing dysfunction of the internal organs. Clinical manifestations include pain, swelling, synovitis, joint damage, and bone destruction, resulting in severe disability and increased mortality. The rat AA model is considered similar to human RA in both acute exacerbation and remission phases in TCM clinical practice. Its modeling method has a long history and is an effective tool for evaluating TCM treatment of RA. Furthermore, once successfully replicated, the rat model induces symptoms such as joint swelling and cartilage destruction, with rapid onset, and induces synovitis and granulomas, similar to the pathological manifestations of RA. Therefore, the AA rat model is widely used in research on new drug screening and therapeutic efficacy studies.

[0025] GRA (Graphical Relationship Analysis) is currently the most commonly used analytical method for analyzing the spectrum-efficacy relationship of traditional Chinese medicine (TCM). It is a method that measures the degree of correlation between factors based on the similarity or difference in the trends of factors, making it suitable for studying the spectrum-efficacy relationship of complex TCM components. However, GRA analysis can only clarify the magnitude of the correlation between each fingerprint peak and the efficacy index, but cannot describe the interaction between each fingerprint peak and the efficacy index. Therefore, combining GRA with OPLS analysis can further clarify the efficacy components that are positively or negatively correlated. Furthermore, the VIP histogram reflects the importance of each peak in explaining the efficacy; the larger the VIP value, the stronger the explanatory power of the independent variable on the dependent variable. Generally, a VIP value greater than 1 is considered to indicate that the peak is significant in explaining the efficacy. Combining the above two methods and three analytical approaches, common peaks with GRA correlation > 0.6, OPLS model regression coefficients < 0, and VIP values ​​greater than 1 were selected as characteristic peaks. These were then combined with entropy analysis for comprehensive analysis and ranking, finally revealing the characteristic components that significantly contribute to the efficacy of treating RA, thus determining the pharmacodynamic material basis of JBD in treating RA. Peaks 1, 4 (loganic acid), 7, 17, 20, 33 (ligustilide), 34 (ostrichol), 37 (dihydroapigenin angelic acid ester), and 38, 40, 41, and 42 (11-carbonyl-β-acetylsalicylic acid) are likely the main components by which JBD exerts its anti-RA therapeutic effect.

[0026] The pathogenesis of rheumatoid arthritis (RA) involves the lingering of wind-cold-damp-heat pathogens in the joints and meridians over a prolonged period. This leads to stagnation of cold pathogens and obstruction of dampness, hindering the flow of qi and blood in the meridians and resulting in blood stasis and phlegm accumulation. These pathogens penetrate deep into the muscles and bones, accumulating in the joints and bones, further exacerbating the obstruction and causing joint stiffness and deformity. It has been reported that loganic acid can inhibit the overexpression of PGE2 and Bcl-2 in serum, thereby suppressing the inflammatory response in RA model rats and thus exerting a therapeutic effect on RA. Osthol can effectively inhibit the progression of RA and RA-ild by downregulating the activation of the TGM2 / Myc / WTAP positive feedback loop, inhibiting the proliferation and polarization of M2 macrophages, suppressing the aggregation of CD11b+ macrophages in the lung interstitium, and exhibiting no toxicity. 11-Carbonyl-β-acetylbosuccinic acid can increase the phagocytic capacity of macrophages, affect the cellular defense system by influencing cytokine production, and inhibit the activation of NF-κB in neutrophils. These results demonstrate the reliability of the active ingredients obtained through spectrum-effect relationship screening in this study and are of significant importance for subsequent research. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 HPLC characteristic chromatograms and reference characteristic chromatograms of 15 batches of JBD material standard (S8);

[0029] Figure 2 Identification of 15 characteristic peaks in JBD material standards; Note: 1. Neochlorogenic acid; 2. Loganilic acid; 3. Gentianoside; 4. Ferulic acid; 5. Glycyrrhizin; 6. Imperatorin; 7. Cinnamaldehyde; 8. Ammonium glycyrrhizate; 9. Notopterygium alcohol; 10. Ligusticum lactone; 11. Osthol; 12. Isoimperatorin; 13. Dihydroaperitol Angelica oleracea acid ester; 14. Angelica lactone A; 15. 11-Carbonyl-β-acetylbric acid;

[0030] Figure 3 The material reference characteristic spectrum of JBD and each single herb;

[0031] Figure 4 Reference spectra for JBD and various negative substances;

[0032] Figure 5 Results of chemical pattern recognition. (A) CA clustering dendrogram; (B) PCA analysis results; (C) OPLS results;

[0033] Figure 6JBD material-based extracts were used to alleviate AA (acute exanthematous) injury in rats. (A) Image of the inflamed right hind paw of rats; (B) Volume of the hind paw in different groups of AA rats; (C) Thickness of the hind paw in different groups of AA rats; (D) IL-1β levels in different groups; (E) CRP levels in different groups; (F) RF levels in different groups. Note: Data are expressed as mean ± SD. Compared with the control group, * P<0.05, ** P<0.01; compared with the model group, # P<0.05, ## P < 0.01. n = 10;

[0034] Figure 7 The VIP values ​​and regression coefficients of the OPLS model for each common peak and anti-IL-1β, CRP, and RA are given. Detailed Implementation

[0035] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Example 1: HPLC fingerprinting method

[0037] Preparation of S1.15 batch JBD material reference

[0038] According to ancient records, the following ingredients were used: 11.19g each of Angelica sinensis and mulberry twigs; 3.73g each of Notopterygium incisum, Angelica pubescens, and Gentiana macrophylla; 1.87g each of cinnamon and stir-fried licorice root; 2.61g of Ligusticum chuanxiong; 7.46g of Piper kadsura; and 2.98g each of frankincense and costus root. These were decocted once with water (1:10, w / v) for 1 hour each time. After concentration under reduced pressure, the extract was freeze-dried to obtain the JBD reference standard, which was then stored at room temperature. Fifteen batches of extract were prepared. 1g of JBD was added to 10mL of methanol solution and ultrasonically extracted for 30 minutes. Before testing, the filtrate was filtered through a 0.22μm microporous membrane.

[0039] S2. Preparation of single-herb medicinal slice samples

[0040] Weigh appropriate amounts of each herb, prepare unit medicinal slice material reference samples according to the preparation process of JBD material reference, and prepare each herb according to the preparation method of JBD test solution, and thus obtain the final product.

[0041] S3. Preparation of negative samples

[0042] Eleven medicinal slices, including those lacking Angelica sinensis, Notopterygium incisum, and Angelica pubescens, were weighed and prepared according to the JBD material reference preparation process to obtain each negative reference sample. Each negative reference was then prepared according to the JBD test solution preparation method.

[0043] S4. Preparation of Standard Solutions

[0044] Weigh appropriate amounts of neochlorogenic acid, loganic acid, gentiopicrin, ferulic acid, glycyrrhizin, imperatorin, cinnamaldehyde, ammonium glycyrrhizate, notopterygium alcohol, ligustilide, osthol, isoimperatorin, dihydroaperitol angelic acid ester, angelicin A, and 11-carbonyl-β-acetylbosuccinic acid, and prepare a mixed reference solution with methanol.

[0045] S5. Chromatographic conditions

[0046] Chromatographic column: Thermo Fisher Acclaim 120 C18 column (4.6×250mm, 5μm); mobile phase: acetonitrile (A)-0.2% formic acid aqueous solution (B), gradient elution. Elution conditions were as follows (A:B, v / v): 0-23 min, 8%-17% A; 23-40 min, 17%-24% A; 40-48 min, 24%-33% A; 48-62 min, 33%-34% A; 62-73 min, 34%-57% A; 73-89 min, 57%-73% A; 89-100 min, 73%-100% A; 100-110 min, 100% A; column temperature 30℃; detection wavelength (1-23 min, 250 nm; 23-65 min, 300 nm; 65-110 min, 250 nm); injection volume 10 μL; flow rate 1 mL·min. -1 .

[0047] Example 2 Methodological Investigation

[0048] Chromatographic conditions were evaluated through precision, repeatability, and stability tests. Precision was achieved by injecting the sample six times consecutively under the same chromatographic conditions. Repeatability was achieved by preparing six parallel test solutions from the same batch of samples and injecting them under the same chromatographic conditions. Stability was achieved by injecting the same test solution at 0, 2, 4, 8, 16, and 24 hours, and the relative retention time and relative peak area of ​​each common peak were calculated, with peak 13 used as the reference peak.

[0049] Example 3: Establishment and Similarity Evaluation of JBD Material Reference Fingerprint Spectra

[0050] The characteristic spectra of JBD (S1-S15) reference materials were analyzed using the Traditional Chinese Medicine Fingerprint Similarity Evaluation System (2012 version), with S8 as the reference spectrum. The mean method was employed, with a time window of 0.1, for multi-point correction and peak matching, followed by similarity calculation. The peak area data of common peaks from 15 batches of JBD reference materials were imported into SPSS 26.0 for data standardization. Cluster analysis was performed using hierarchical clustering and squared Euclidean distance. Simultaneously, the peak areas of these common peaks were imported into SIMCA 14.0 for normalization to obtain reliable PCA model interpretation parameters.

[0051] JBD (S1-S15) and the mixed reference solution were injected into the HPLC chromatograph, and the chromatographic peaks of 15 components in the JBD material standard were identified based on the retention time of the mixed reference.

[0052] According to the analytical methods and validation guidelines in the Pharmacopoeia of the People's Republic of China (2020 edition), the precision test showed that the relative retention time RSD of the common peak was <0.9% and the peak area RSD was <2.85%, indicating good instrument precision. The repeatability test showed that the relative retention time RSD of each common peak was <1.1% and the peak area RSD was <2.97%, indicating good repeatability of the experimental method. The stability test showed that the relative retention time RSD of the common peak was <1.2% and the peak area RSD was <2.9%, indicating that the test solution was stable within 24 hours under these conditions.

[0053] HPLC chromatograms of 15 batches of JBD material reference samples were established, such as... Figure 1 A total of 43 common peaks were identified, with similarity ranging from 0.956 to 0.994. Comparison with the chromatographic behavior of chemical reference standards revealed 15 common peaks: peak 3 (neochlorogenic acid), peak 4 (loganic acid), peak 8 (gentiopicrin), peak 11 (ferulic acid), peak 12 (glycyrrhizin), peak 13 (imperatorin), peak 25 (cinnamaldehyde), peak 28 (ammonium glycyrrhizate), peak 31 (notopterygium alcohol), peak 33 (ligustilide), peak 34 (ostrichol), peak 35 (isoimperatorin), peak 37 (dihydroaperitol angelicoside), peak 39 (angelicoside A), and peak 42 (11-carbonyl-β-acetylsalicylic acid). Figure 2 .Depend on Figure 3 Single-flavor sample solutions and Figure 4 The chromatograms of negative sample solutions can be used to determine the peak assignments for each common peak, as shown in Table 1.

[0054] Cluster analysis (HCA) Figure 5 A) and Principal Component Analysis (PCA) Figure 5B) The results showed that when the squared Euclidean distance was 0.6, the 15 batches of JBD material references could be divided into two categories: S5 in one category and the rest in another. This indicates that different batches of samples have inter-group differences in common components due to differences in the batches of medicinal materials. In order to better screen out the components with quality differences among different batches of samples, OPLS-DA analysis was performed on the basis of PCA, and the OPLS-DA model was obtained. Figure 5 C) Components with a VIP > 1 were considered to have a significant impact. The results showed that the components with a VIP > 1 were P3 (neochlorogenic acid), 6, 7, 10, 13 (imperatorin), 19, 21, 22, 28 (ammonium glycyrrhizate), 29, 30, 33 (ligustilide), 34 (ostrichol), 35 (isoimperatorin), and 36. These 15 components can serve as the basis for subsequent spectroscopic-efficacy relationship analysis of JBD, representing the components contributing to the quality difference.

[0055] Table 1. Peak Attribution

[0056]

[0057] Example 4: Study on the anti-RA effect of JBD material benchmark in rats

[0058] (1) Animal grouping, drug administration and modeling

[0059] After 7 days of acclimatization, 180 SD rats were divided into two groups according to body weight: a control group and a model group. Before modeling, the volume and thickness of the left and right hind paws of the rats were measured using a toe volume analyzer. Except for the control group, each rat received a subcutaneous injection of 0.1 ml of Freund's Complete Adjuvant (CFA) at the right hind paw pad. The control group rats received an injection of 0.1 ml of physiological saline at the same site on their right paw. After injecting half of the CFA, the needle was reversed and the entire CFA was injected. The needle was withdrawn and pressure was applied for a certain period of time to prevent spillage. This was recorded as day 0, which served as the first adjuvant exposure to stimulate the immune response and establish an adjuvant-induced arthritis model in rats. On day 7 after adjuvant injection, the swelling of the paw at the injection site (right hind paw) was examined using a toe volume analyzer. Rats with redness and swelling of both paws and paw pads (compared with normal rats, P < 0.05, indicating a significant difference between groups) were identified as adjuvant-induced arthritis model rats and used for subsequent experiments. Methotrexate is used as a first-line drug for the treatment of rheumatoid arthritis (RA) in China and was also used as a positive control in this study. On day 15 after modeling, the paw volume of the non-inflammatory side of the rats was measured using a paw volume analyzer, and the swelling degree of the non-inflammatory side of the paw was calculated. Based on the swelling degree of the rat paw, 180 AA rats were randomly divided into a blank group, a model group, a methotrexate tablet group (positive drug group), and the 1st to 15th batch drug administration groups, with 10 rats in each group.

[0060] Based on the preliminary experimental results, a medium dose (0.48 g / ml) was selected as the dosage for this experiment. JBD (S1-S15) was extracted and evaporated to 0.48 g / ml using a rotary evaporator. The JBD (S1-S15) group was administered 0.45 g / ml once a day for 3 consecutive weeks. The methotrexate tablet group was administered 0.9 mg / kg once a week. The blank group and the model group were given purified water according to body weight. All groups were administered the drug according to the rat's body weight (1 mL / 0.1 kg).

[0061] (2) Detection indicators and methods

[0062] During the paw swelling and thickness measurement experiment, the volume of the rat's right hind paw was measured every 4 days using a toe volume analyzer, and the toe thickness was measured every 3 days using vernier calipers. The paw swelling and thickness were recorded and calculated.

[0063] ELISA was used to detect serum inflammatory markers IL-1β, CRP, and RF levels. After the serum was allowed to stand for 2 hours, it was centrifuged at 8000 r·min⁻¹ at 4℃ for 15 min. The serum was then used to detect the levels of serum IL-1β, CRP, and RF strictly according to the kit instructions.

[0064] (3) Statistical processing

[0065] Statistical analysis was performed using SPSS 23 software. Data are expressed as mean ± standard deviation (xˉ±s). Independent samples t-tests were used for comparisons between two groups, and one-way ANOVA was used for comparisons among multiple groups. P < 0.05 was considered statistically significant, and P < 0.01 was considered statistically significant.

[0066] (4) Different batches of JBD material benchmarks can alleviate lesions in RA rats.

[0067] 1) Measurement of RF levels in rat serum

[0068] To examine the effect of JBD on the serum inflammatory factor RF levels in AA model rats, the volume and thickness of the right hind paw were measured. Images of the inflamed right hind paw of the rats are shown below. Figure 6 As shown in Figure A. The results showed that the volume and thickness of the right hind paw in the model group were significantly higher than those in the normal group. After 21 days of drug administration, compared with the model group, the volume of the right hind paw in rats from batches JBD1-4, 6-10, and 12-15 was significantly lower in the model group. Figure 6 B); The thickness of the right hind paw of rats in batches 1-15 of JBD was significantly lower than that in the model group (B). Figure 6 C). RF is a key indicator for the clinical diagnosis of RA. JBD extract can reduce RF levels in AA rats, suggesting that it has an anti-rheumatoid arthritis effect. Figure 6D). Rat joints are frequently affected, leading to swelling, and are associated with the production of autoantibodies, including RF. The results indicate that JBD can effectively alleviate joint swelling in rats, reduce RF levels, and effectively inhibit the expression of inflammatory factors.

[0069] 2) Anti-RA effect of JBD material benchmark on AA rats

[0070] During the pathogenesis of rheumatoid arthritis (RA), multiple pro-inflammatory cascade reactions occur, producing numerous pro-inflammatory cytokines, including interleukin-1β (IL-1β) and C-reactive protein (CRP), causing significant pain to patients. To verify the therapeutic effect of JBD on RA, this study used ELISA to measure the serum levels of IL-1β and CRP in SD rats. The results showed that the serum levels of IL-1β and CRP in the model group were significantly higher than those in the normal group. After 21 days of treatment with JBD 1-15, the serum IL-1β levels in rats treated with JBD 1-3, 5-9, and 11-15 were significantly lower than those in the model group. Figure 6 E). The serum CRP levels in JBD2, 3, 5-15 batches of rats were significantly lower than those in the model group ( Figure 6 F). The results showed that complete Freund's adjuvant increased the level of inflammatory response in rats, while JBD inhibited the expression of inflammatory cytokines (P<0.05 or P<0.01).

[0071] Example 5: Spectrum-Effect Relationship Analysis

[0072] Z-score normalization was performed on the common peak area data of JBD(S1-15) fingerprint spectrum and the efficacy indicators of JBD(S1-15) in treating RA rats, namely IL-1β, CRP, and RF, using the SPSSAU system.

[0073] (1) Grey Relational Analysis (GRA)

[0074] Grey relational analysis was used, with the levels of IL-1β, CRP, and RF in the serum of each batch of rheumatoid arthritis rats as the parent sequence and the peak areas of 43 common peaks in the baseline fingerprint of the Bu Yi Tang substance as the child sequence. The resolution coefficient ρ was set to 0.5, and the correlation between the peak areas of the common peaks in each batch and each efficacy index was calculated.

[0075] (2) Orthogonal Partial Least Squares (OPLS)

[0076] The peak area data of 43 common peaks in the fingerprint spectrum were selected as independent variables, and the efficacy index of each sample was selected as dependent variables. The spectrum-efficacy relationship was analyzed by using SIMCA 14.1 software combined with OPLS analysis method.

[0077] (3) Entropy method

[0078] Each spectrum-effect correlation analysis method has its limitations and applicability. In previous studies, a single spectrum-effect correlation analysis was generally used to study practical problems involving multiple indicators, which often resulted in biased results. To obtain more scientific and reliable results, this study took the intersection of the results of the above three spectrum-effect correlation analyses and used the entropy method to screen out the peaks with high correlation between JBD and anti-RA efficacy indicators.

[0079] (6) Study on the spectrum-effect relationship of different batches of JBD material benchmarks against RA

[0080] 1) Data conversion of efficacy indicators for antirheumatoid arthritis drugs

[0081] The fingerprint data of JBD material reference batches 1-15 include peak area data and the efficacy indicators of JBD material reference batches 1-15 in treating RA rats, IL-1β, CRP, and RF, which were Z-score standardized using the SPSSAU system.

[0082] 2) Spectrum-Effect Relationship Analysis Based on Grey Relational Analysis (GRA)

[0083] Grey relational analysis was used, with the levels of IL-1β, CRP, and RF in the serum of rheumatoid arthritis rats from each batch as the parent sequence, and the peak areas of 43 common peaks in the JBD material fingerprint as the child sequence. The resolution coefficient ρ was set to 0.5, and the correlation between the peak areas of the common peaks and each efficacy index was calculated. The results (Table 2) show that the correlations between the peak areas of each common peak and the levels of IL-1β, CRP, and RF were 0.610–0.916, 0.606–0.917, and 0.611–0.909, respectively. Except for peaks 4, 14, 15, 21, 26, and 43, the correlations between the remaining 37 common peaks and the anti-rheumatoid arthritis effect were all >0.8, reflecting a high correlation between these 37 peaks and the anti-rheumatoid arthritis efficacy. The remaining 6 peaks had correlations greater than 0.6, with peak 11 (ferulic acid) showing the highest correlation. Peaks 11 (ferulic acid), 2, 8 (gentiopicrin), and 27 were observed. The contributions of each common peak to the above indicators varied, suggesting that the anti-rheumatoid arthritis effect of JBD is achieved through the synergistic action of different components. The components corresponding to peaks 11 (ferulic acid), 2, 8 (gentiopicrin), and 27 may be the main pharmacologically active components of JBD in exerting its anti-rheumatoid arthritis effect. At the same time, except for peaks 14 and 26, the overall correlation between the three factors and anti-rheumatoid arthritis in JBD was greater than 0.7, revealing that the ability to exert anti-RA is the result of the combined action of various components in JBD.

[0084] 3) Spectrum-Effect Relationship Based on Partial Least Squares Regression Analysis (OPLS)

[0085] Peak area data of common peaks in 43 fingerprint spectra were selected as independent variables, and efficacy indicators of each sample were selected as dependent variables. The spectrum-efficacy relationship was analyzed using the OPLS method with SIMCA 14.1 software. R 2 The explanatory power of the model is represented by the area of ​​each common peak and the R-squared value of IL-1β, CRP, and RF. 2 The values ​​were 0.906, 0.799, and 0.889, respectively, indicating that the regression models for different efficacy indicators all had strong fitting and explanatory power. The results for the variable importance in projection (VIP) and regression coefficients (OPLS-CoeffCS) are shown below. Figure 7 The results showed that 24 chromatographic peaks of the JBD reference material were negatively correlated with IL-1β and RF, and 16 chromatographic peaks were negatively correlated with CRP. Furthermore, 14, 22, and 14 chromatographic peaks, respectively, had VIP values ​​greater than 1 for the efficacy of IL-1β, CRP, and RF. Through screening, peaks 1, 7, 17, 33, 34, 37, 41, and 42 were found to be significantly negatively correlated with the efficacy of IL-1β; peaks 4, 7, 20, 34, 38, 40, and 42 were significantly negatively correlated with the efficacy of CRP; and peaks 1, 7, 17, 33, 34, 37, 41, and 42 were significantly negatively correlated with the efficacy of RF.

[0086] 4) Comprehensive analysis of correlation results

[0087] Each spectrum-effect correlation analysis method has its limitations and applicability. In previous studies, a single spectrum-effect correlation analysis was generally used to study practical problems with multiple indicators, and the results often had some bias. In order to obtain more scientific and reliable results, this study took the intersection of the results of the above three spectrum-effect correlation analyses and used the entropy method to screen out the peaks with high correlation between JBD and anti-RA efficacy indicators, as shown in Table 2. Based on the combined results of GRA and OPLS analyses, peaks with GRA values ​​greater than 0.6 and peaks with VIP values ​​greater than 1 and regression coefficients less than 0 in OPLS analysis were integrated. Peaks satisfying both criteria were selected, and peaks 1, 4, 7, 17, 20, 33, 34, 37, 38, 40, 41, and 42 were found to be significantly associated with the inhibition of RF, IL-1β, and CRP expression, and are key components in anti-RA therapy. Peaks 7, 34 (osthol) and 42 (11-carbonyl-β-acetylbosuccinic acid) simultaneously met both criteria and were considered to be the most important spectrum-effect related components in JBD for anti-RA therapy. The TOPSIS method, used to synthesize scores, revealed that the top 10 chromatographic peaks contributing most to the anti-RA effect were, in descending order: 11 (ferulic acid), 39 (angelicin A), 33 (ligustilide), 34 (ostrichol), 7, 1, 29, 42 (11-carbonyl-β-acetylboswellic acid), 25 (cinnamaldehyde), and 41. Analysis of their known structures revealed that these peaks are indicative components of Notopterygium incisum, Angelica sinensis, Ligusticum chuanxiong, Angelica pubescens, and Boswellia carterii. Literature reports indicate that these components have significant therapeutic effects on RA; therefore, these compounds are considered the main effective components of JBD in treating RA.

[0088] Table 2 shows the correlation and overall score of 43 components in JBD with pharmacodynamic indicators.

[0089]

[0090]

[0091] 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 establishing an HPLC fingerprint of a traditional Chinese medicine formula for treating numbness and pain, characterized in that, Includes the following steps: S1. Preparation of the material basis of Juanbi Decoction: Weigh out Angelica sinensis, mulberry twig, Notopterygium incisum, Angelica pubescens, Gentiana macrophylla, cinnamon, stir-fried licorice, Ligusticum chuanxiong, Piper kadsura, frankincense and costus root, add water and decoct, filter, filter through a microporous membrane, concentrate the filtrate under reduced pressure and freeze dry to obtain the material basis of Juanbi Decoction. S2. Preparation of single-herb decoction samples: Weigh each herb, add water and decoct, filter, filter through a microporous membrane to obtain single-herb decoction samples; S3. Preparation of negative samples: Weigh out the slices of herbs that are lacking Angelica sinensis, mulberry twig, Notopterygium incisum, Angelica pubescens, Gentiana macrophylla, cinnamon, stir-fried licorice, Ligusticum chuanxiong, Piper kadsura, frankincense, and aromatic herbs, add water to decoct, filter, filter through a microporous membrane, concentrate the filtrate under reduced pressure and freeze dry to obtain negative samples. S4. Preparation of standard solutions: Weigh appropriate amounts of neochlorogenic acid, loganic acid, gentiopicrin, ferulic acid, glycyrrhizin, imperatorin, cinnamaldehyde, ammonium glycyrrhizate, notopterygium alcohol, ligustilide, osthol, isoimperatorin, dihydroaperitol angelic acid ester, angelicin A, and 11-carbonyl-β-acetylboswellic acid, and prepare a mixed reference solution with methanol solution to obtain the standard solution. S5. Chromatographic Analysis: High-performance liquid chromatography (HPLC) was used to analyze the above-mentioned Juanbi Decoction reference standard, single-herb medicinal slices, negative samples, and standard solutions to obtain the HPLC fingerprint of Juanbi Decoction. Based on the retention times of each substance in the standard solutions, the chromatographic peaks of 15 components in the Juanbi Decoction reference standard were identified. The chromatographic column used was a Thermo Fisher Acclaim 120 C18 column; the mobile phase was acetonitrile A-0.2% formic acid aqueous solution B, with gradient elution. The elution conditions were as follows: 0-23 min, 8%-17% A; 23-40 min, 17%-24% A; 40-48 min, 24%-33% A; 48-62 min, 24%-33% A. min, 33%-34%A; 62-73 min, 34%-57%A; 73-89 min, 57%-73%A; 89-100 min, 73%-100%A; 100-110 min, 100%A; detection wavelength is 1-23 min, 250 nm; 23-65 min, 300 nm; 65-110 min, 250 nm.

2. The method according to claim 1, characterized in that, The mass ratio of Angelica sinensis, mulberry twig, Notopterygium incisum, Angelica pubescens, Gentiana macrophylla, cinnamon, stir-fried licorice root, Ligusticum chuanxiong, Piper kadsura, frankincense, and costus root in step S1 is 11-12:11-12:3.6-3.9:3.6-3.9:3.6-3.9:1.7-1.9:1.7-1.9:2.5-2.7:7.3-7.6:2.8-3:2.8-3.

3. The method according to claim 1, characterized in that, The solid-liquid ratio of the medicinal materials and water used in the decoction is 1:8-12 g / mL.

4. The method according to claim 1, characterized in that, The decocting time is 0.5-1.5 hours, and the decocting is performed 1-2 times.

5. The method according to claim 1, characterized in that, In step S5, the chromatographic column used for chromatography has a size of 4.6 × 250 mm and a particle size of 5 μm.

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