Traditional Chinese medicine composition for treating icteric hepatitis and pharmaceutical application and data mining method thereof

Abstract

The invention relates to a traditional Chinese medicine composition for treating icteric hepatitis as well as pharmaceutical application and a data mining method thereof. The traditional Chinese medicine composition is prepared from herba artemisiae scopariae, radix curcumae, radix et rhizoma rhei and radix paeoniae rubra. The traditional Chinese medicine composition is a core prescription for treating icteric hepatitis obtained through a data mining technology, an optimal weight ratio is preferably obtained, and experimental verification shows that compared with a compound empirical prescription yellow liver decoction, the traditional Chinese medicine composition has the technical effects that the components are obviously simplified, and the curative effect is the same or better.

Description

Technical Field

[0001] The present application relates to the field of medical technology, specifically to the field of traditional Chinese medicine technology, and more specifically to a traditional Chinese medicine composition for treating icteric hepatitis, its pharmaceutical use and data mining method. Background Art

[0002] Hepatitis caused by various causes, accompanied by yellowing of the skin and mucous membranes, and serum bilirubin exceeding the prescribed level is called icteric hepatitis, which includes clinical manifestations of both hepatitis and jaundice. Various causes of hepatitis can be diagnosed as icteric hepatitis due to the simultaneous occurrence of jaundice. Common causes include the following: infection with hepatitis viruses (A, B, C, D, E), infection with other hepatotropic viruses (Epstein-Barr virus, cytomegalovirus, etc.), damage from chemical toxins (such as carbon tetrachloride), alcohol damage, damage from drugs (remifen, rifampicin, lipid-lowering drugs), autoimmune damage, influence of genetic metabolic diseases, abnormal lipid metabolism (fatty liver), etc. These causes can lead to diffuse damage to liver cells and produce hepatitis, and jaundice appears at the same time, which is clinically diagnosed as icteric hepatitis.

[0003] According to traditional Chinese medicine, jaundice hepatitis belongs to the category of "yang jaundice" and "epidemic jaundice", with yellow eyes, yellow body and yellow urine as the main manifestations. It is mostly caused by damp-heat epidemic toxins blocking the middle jiao, dysfunction of the spleen and stomach, obstruction of the liver and gallbladder qi, and blood stasis and heat, which force the bile to leak out. Jaundice was first seen in "Suwen·Pingren Qixiang Lun": "Yellow and red urine, lying down, jaundice... Yellow eyes are called jaundice." Zhang Zhongjing pointed out in "Jingui Yaolue": "Cunkou pulse is floating and slow, floating is wind, slow is numbness, numbness is not stroke, limbs are suffering, spleen color must be yellow, blood stasis and heat are moving", which explains that damp-heat accumulation leads to jaundice. "Suwen·Yinyang Yingxiang Dalun" says "the center produces dampness, dampness produces earth, earth produces sweetness, sweetness produces spleen... in the zang it is spleen, in the color it is yellow", which explains that dampness produces yellow.

[0004] Treatment for icteric hepatitis includes: 1) Targeted treatment: Western medicine for choleretic drugs, such as ursodeoxycholic acid, adenosine methionine, etc. Chinese medicine: Yinzhihuang granules, etc.; liver protection drugs, mainly liver cell membrane stabilizers, have the effect of reducing transaminase, and there are many such drugs to choose from; supportive symptomatic treatment, mainly drugs to improve symptoms such as poor appetite, abdominal distension, and nausea. 2) Antiviral treatment, acute viral hepatitis generally does not require antiviral treatment. Chronic viral hepatitis requires antiviral treatment for the virus, etc.

[0005] Huanggan decoction is a hospital preparation that has been used clinically for many years and has a clear and significant effect in treating icteric hepatitis. In the prior art (orthogonal test to optimize the extraction process of Huanggan decoction), it has been clearly pointed out that Huanggan decoction is mainly composed of 14 Chinese medicinal herbs such as Artemisia capillaris, Angelica sinensis, Scutellaria baicalensis, Phellodendron chinense, and Toosendan fruit, and has the effects of clearing heat, promoting dampness, and relieving jaundice. It has been used clinically for nearly 40 years and is mainly used to treat acute and chronic icteric hepatitis with a definite effect. Specifically, the prior art (CN112316087 A) discloses the Huanggan decoction, i.e., a Chinese medicine pellet preparation for treating icteric hepatitis and its preparation method, wherein the mass percentage of each Chinese medicinal material is: Artemisia capillaris 18.4%, Angelica sinensis 3.70%, Scutellaria baicalensis 7.40%, Phellodendron chinense 6.13%, Gentiana 6.13%, Curcuma 6.13%, Toosendan fruit 6.13%, Poria 6.13%, Dioscorea opposita 9.20%, Plantago asiatica 6.13%, Rhubarb 6.13%, Malt 6.13%, Crataegus pinnatifida 6.13% and Liushenqu 6.13%. It can significantly reduce the ALT and AST of the model group and has a liver protective effect. However, in the further clinical application and product development process, the applicant found that the above Huanggan decoction has 14 Chinese medicine raw materials, and the interaction relationship between different raw materials is complicated, which brings obvious difficulties to further clarify the mechanism and formulation development. Therefore, those skilled in the art have a need to further simplify the above prescription.

[0006] Prior art (56 cases of jaundice viral hepatitis treated with anti-jaundice mixture) discloses a anti-jaundice mixture with therapeutic effect on jaundice viral hepatitis, which is composed of 30g each of Artemisia capillaris, red peony root, and Centella asiatica, 15g of Curcuma aromatica, and 10g of Rhubarb. The anti-jaundice mixture has the effects of clearing away heat and dampness, promoting bile and removing jaundice, etc. Artemisia capillaris is bitter and cold in the prescription, and its function is to clear away dampness and heat and remove jaundice, so it is the main medicine; Centella asiatica and Curcuma aromatica both have the functions of promoting bile and removing dampness and removing jaundice, while Curcuma aromatica promotes qi and blood circulation, cools blood and removes blood stasis; Centella asiatica can promote diuresis and relieve stranguria, and jointly assists the main medicine to strengthen the main effect; Rhubarb is used to relieve heat and remove blood stasis, and promote bowel movements; Red peony root clears heat, cools blood and removes blood stasis, and helps Curcuma aromatica to remove dampness and remove jaundice; Curcuma aromatica specializes in the liver and gallbladder meridians, can lead all medicines directly to the diseased area, and also serves as a guiding medicine. Among them, Centella asiatica is an important Chinese medicine raw material, used as an adjuvant drug, and it is specifically pointed out that "the active ingredients in Centella asiatica can promote bile secretion and excretion, relax the bile duct sphincter, and increase urine volume." However, Centella asiatica has side effects such as aggravated diarrhea or gastrointestinal dysfunction, allergic reactions, liver and kidney damage, etc. The clinical application of the anti-jaundice mixture is greatly limited, and its prescription contains 5 Chinese medicine raw materials, which is still not concise enough.

[0007] The prior art (Observation on the efficacy of 32 cases of neonatal pathological jaundice treated with integrated Chinese and Western medicine) discloses a traditional Chinese medicine Xiaodan decoction for treating neonatal pathological jaundice. Basic prescription: 10g of Artemisia capillaris, 6g of Curcuma aromatica, 6g of Gallus gallus domesticus, and 3g of Rhubarb. For damp-heat, add Plantago seed and Gardenia jasminoides; for cold-dampness, add Cinnamon twig, Rhizoma Alismatis, and Radix Aconiti Lateralis; for spleen deficiency and dampness, add Radix Pseudostellariae, Citrus aurantium, and Citrus reticulatae; for stasis and internal retention, add Semen Persicae, Safflower, and Curcuma zedoariae. However, due to the particularity of neonates, the etiology and pathogenesis of their jaundice are not exactly the same as those of icteric hepatitis, and lack reference significance.

[0008] Prior art (70 cases of icteric hepatitis treated with integrated Chinese and Western medicine) discloses a Chishao Yinchenhao decoction for treating icteric hepatitis: Yinchen 20-30g, rhubarb 3-10g, gardenia 5-10g, and red peony root 10-15g. Patchouli 10g and white cardamom 10g are added for patients with heavy dampness; Isatis root 10g and honeysuckle 10g are added for patients with heavy bleeding; Peony bark 10g and thistle 30g are added for patients with vomiting; Ginger 10g and Pinellia 10g are added for patients with poor appetite; Peach kernel 10g and Salvia miltiorrhiza 20g are added for patients with enlarged and hard liver. Gardenia in the prescription can clear the three energizers, guide dampness and heat downward, and guide dampness and heat out of urine. It is an important raw material of traditional Chinese medicine. However, Gardenia is mainly used to purge fire and relieve restlessness. The side effects of Gardenia mainly include liver damage, spleen and stomach damage, etc., and it is not suitable for treating icteric hepatitis.

[0009] Famous TCM experts of all dynasties have used methods such as jaundice-reducing, gallbladder-promoting, and liver-protecting to treat icteric hepatitis. However, there are large individual differences in TCM treatment, and treatment experiences and plans are not the same. As a treasure trove that has not yet been fully explored, TCM needs further in-depth research. Summary of the invention

[0010] The object of the present invention is to provide a Chinese medicine composition for treating icteric hepatitis, wherein the Chinese medicine composition has a simplified prescription, contains less than 4 Chinese medicine raw materials, and can facilitate further elucidation of the mechanism and formulation development. In addition, the Chinese medicine composition has a definite therapeutic effect, and has the same or better technical effect of treating icteric hepatitis than the traditional large compound prescription for treating icteric hepatitis.

[0011] Specifically, this application utilizes a large amount of traditional Chinese medicine prescriptions, medical records and other data generated in the literature when treating icteric hepatitis, uses data mining technology to explore the potential connections between these data, and explores the core prescriptions for treating icteric hepatitis, thereby providing a traditional Chinese medicine composition for treating icteric hepatitis with streamlined treatment and the same or better efficacy.

[0012] With the advent of the big data era, data mining technology has gradually emerged. The present invention constructs a database by searching for data such as Chinese medicine prescriptions, Chinese patent medicines, and medical records from various databases, and then uses data mining methods such as Apriori association rule algorithm, AHP hierarchical analysis method, CRITIC analysis method, and TOPSIS analysis to gradually explore the medication rules and core prescriptions of Chinese medicine for treating diseases, providing assistance for the treatment of clinical diseases and the application of Chinese medicine.

[0013] Specifically, the present invention provides a traditional Chinese medicine composition for treating icteric hepatitis, characterized in that it is made from the following traditional Chinese medicine raw materials: Artemisia capillaris, Curcuma aromatica, Rhubarb, and Red Peony Root.

[0014] That is, the Chinese medicinal raw materials of the Chinese medicine composition are composed of Artemisia capillaris, Curcuma aromatica, Rhubarb and Red Peony Root.

[0015] Furthermore, the purpose of the present invention is to provide a preferred ratio of Chinese medicinal raw materials for the Chinese medicine composition for treating icteric hepatitis, and further provide the most preferred weight ratio.

[0016] More specifically, the present invention provides a traditional Chinese medicine composition for treating icteric hepatitis, characterized in that it is made of the following traditional Chinese medicine raw materials in the following weight ratio: 11-20 grams of Artemisia capillaris, 3-9 grams of Curcuma aromatica, 3-9 grams of Rhubarb, and 11-20 grams of Red Peony Root.

[0017] Preferably, the Chinese medicine composition is made of Chinese medicine raw materials in the following weight ratio: 12-18 Artemisia capillaris, 3-7 Curcuma aromatica, 3-7 Rhubarb, and 12-18 Red Peony Root.

[0018] More preferably, the Chinese medicine composition is made of the following Chinese medicine raw materials in the following weight ratio: 14-16 Artemisia capillaris, 4-6 Curcuma aromatica, 4-6 Rhubarb, and 14-16 Red Peony Root.

[0019] Most preferably, the Chinese medicine composition is made of Chinese medicine raw materials in the following weight ratio: 15 grams of Artemisia capillaris, 5 grams of Curcuma aromatica, 5 grams of Rhubarb, and 15 grams of Red Peony Root.

[0020] The present invention also aims to provide pharmaceutical use of the traditional Chinese medicine composition.

[0021] Specifically, the present invention provides a use of the traditional Chinese medicine composition in preparing a drug for treating liver damage, wherein the liver damage is caused by icteric hepatitis.

[0022] Furthermore, the treatment of liver damage is to reduce inflammation during liver damage.

[0023] Furthermore, the treatment of liver damage is to reduce the abnormal increase of serum ALT, AST, TBIL, and TBA indicators during liver damage.

[0024] More specifically, the Chinese medicine composition is used in preparing a medicine for treating icteric hepatitis.

[0025] In addition, the present invention also aims to provide a method for obtaining the Chinese medicine composition through data mining.

[0026] Specifically, the present invention provides a data mining method for the Chinese medicine composition for treating icteric hepatitis, characterized in that it comprises the following steps: 1) constructing a database, i.e. collecting prescription information for treating icteric hepatitis from literature, medical records, and Chinese patent medicine databases as needed to form a database; 2) data mining, including raw material screening and formula analysis; 3) the optimal formula obtained by TOPSIS scoring is Artemisia capillaris, Curcuma aromatica, Rhubarb, and Red Peony Root, which is used as the core formula.

[0027] The database construction also includes a step of data standardization, using standardized names of medicinal materials, unifying extracts into original medicinal materials, and recording the nature, flavor and meridians of the medicinal materials.

[0028] The raw material screening includes raw material frequency statistics, raw material category analysis, raw material four-qi analysis, raw material five-flavor analysis, raw material meridian analysis, and raw material association rule analysis (drug association, corner drug association, and four-flavor drug association).

[0029] The formula analysis includes AHP hierarchical analysis, CRITIC analysis, cluster analysis and TOPSIS analysis.

[0030] After obtaining the core prescription through data mining, the present invention established a traditional Chinese medicine component library, a component target library, and a disease target library for icteric hepatitis of the core prescription and Huanggan decoction; used microbial information to obtain the intersection targets of the two prescriptions and the disease, and then performed GO function and KEGG pathway enrichment analysis, and verified the stability of the combination of the target and the active ingredient of traditional Chinese medicine through molecular docking. Specifically, the core formula has 49 active ingredients such as quercetin, and 259 ingredient targets such as IL6, IL1B, PTGS2, and MAP3K3; the yellow liver decoction has 158 active ingredients such as quercetin, and 365 ingredient targets such as IL6, IL1B, SOD1, and GOT1; 105 disease targets such as IL6, IL1B, and TNF were obtained; the core formula has 13 intersection targets with icteric hepatitis, such as IL6 and IL1B, while the yellow liver decoction has 16 intersection targets such as IL6 and IL1B, and the core targets of both formulas and diseases are IL6 and IL1B; the GO enrichment analysis results of the intersection targets of the two formulas include cytokine activity, inflammatory response regulation, etc., and the KEGG pathway enrichment includes IL-17 signaling pathway and AGE-RAGE signaling pathway; the active ingredients quercetin, kaempferol, and β-sterol have good binding stability with the core targets IL6 and IL1B.

[0031] Furthermore, the pharmacodynamics experiment was used to verify its effect, and a rat model of icteric hepatitis was established. The Huanggan decoction of the test recipe was used as the positive control group. The differences in liver function indexes and pathological HE staining sections between the core recipe group and the positive control group were compared to preliminarily evaluate the efficacy of the core recipe. In the rat experiment, the three dose groups of the core recipe and the positive control group had similar abilities to improve hepatic inflammatory cell infiltration in the pathological HE staining sections; the three dose groups of the core recipe and the positive control group had similar effects in relieving weight loss and poor general condition caused by liver damage after modeling; the three dose groups of the core recipe had similar abilities to reduce TBIL in biochemical indicators, but stronger than the positive control group; the low and medium dose groups of the core recipe had similar abilities to reduce TBA, which was stronger than the positive control group; the three dose groups of the core recipe had similar abilities to reduce ALT as the positive control group; the low dose group of the core recipe and the positive control group had similar abilities to reduce AST, so the effect of the core recipe was not inferior to the positive control group, and the low dose group of the core recipe had the best effect.

[0032] Furthermore, the present application also conducts a prescription-separating experiment on the four Chinese medicinal raw materials of the Chinese medicine composition, that is, LPS is used to induce mouse mononuclear macrophages RAW264.7, an in vitro anti-inflammatory model is established, and according to the amount of nitric oxide generated, the anti-inflammatory potential of the drugs (① Artemisia capillaris, rhubarb ② Red peony root, Curcuma aromatica), horn drugs (① Artemisia capillaris, rhubarb, red peony root ② Artemisia capillaris, rhubarb, Curcuma aromatica ③ Rhubarb, red peony root, Curcuma aromatica; ④ Artemisia capillaris, red peony root, Curcuma aromatica), four drugs (Artemisia capillaris: red peony root: rhubarb: Curcuma aromatica), and similar drugs (① 30 parts each of Artemisia capillaris, red peony root, and Centella asiatica, 15 parts of Curcuma aromatica, 10 parts of rhubarb ② 10 parts of Artemisia capillaris, 6 parts of Curcuma aromatica, 6 parts of chicken's gizzard lining, 3 parts of rhubarb ③ 30 parts of Artemisia capillaris, 10 parts of rhubarb, 10 parts of Gardenia jasminoides, 15 parts of red peony root ④ 30 parts each of Artemisia capillaris, red peony root, and Centella asiatica, 10 parts of rhubarb). The results showed that the inhibition of NO by the pair drug, corner drug, quadruple drug and similar drug was different, among which the quadruple drug group could significantly reduce the NO release of inflammatory cells, and had the best technical effect.

[0033] Beneficial technical effects of the present invention: 1) The present invention conducts data mining on a large number of existing traditional Chinese medicine prescriptions for treating icteric hepatitis, and finds a traditional Chinese medicine composition consisting of only four Chinese medicine raw materials, namely, Artemisia capillaris, Curcuma aromatica, Rhubarb, and Paeonia lactiflora. The traditional Chinese medicine composition has the same or better technical effect as the large compound prescription for treating icteric hepatitis, has a simple prescription, and has a significant therapeutic effect; 2) The present invention has found the optimal weight ratio of the Chinese medicine composition through the optimization experiment of dosage ratio, that is, 15 grams of Artemisia capillaris, 5 grams of Curcuma aromatica, 5 grams of Rhubarb, and 15 grams of Red Peony Root, which has a technical effect that is significantly better than other weight ratios; 3) Compared with the prescriptions lacking some Chinese medicine raw materials such as anti-inflammatory drugs and horn drugs, the Chinese medicine composition has significantly better anti-inflammatory effects and is a significant improvement; 4) The present invention also provides a data mining method for the Chinese medicine composition, which provides a reference for finding other streamlined and preferred prescriptions in the field of traditional Chinese medicine. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The effect of different concentrations of LPS on the viability of RAW264.7 cells.

[0035] Figure 2 The effect of different concentrations of Artemisia capillaris on the viability of RAW264.7 cells.

[0036] Figure 3 The effect of different concentrations of red peony root on the viability of RAW264.7 cells.

[0037] Figure 4 The effect of different concentrations of rhubarb on the viability of RAW264.7 cells.

[0038] Figure 5 The effect of different concentrations of Curcuma aromatica on the viability of RAW264.7 cells.

[0039] Figure 6 This is the effect of different drug components on NO production in RAW264.7 cells.

[0040] Figure 7 The effect of different weight ratios on NO production in RAW264.7 cells.

[0041] Figure 8 This is a trend chart of body weight changes, where A is the normal group, B is the model group, C is the positive control group, D is the core formula low-dose group, E is the core formula medium-dose group, and F is the core formula high-dose group.

[0042] Fig. 9 Figures 2 and 3 are liver pathology results of each group, including A normal group, B model group, C positive control group, D core prescription low-dose group, E core prescription medium-dose group, and F core prescription high-dose group. DETAILED DESCRIPTION

[0043] The present invention is explained and illustrated through the following specific implementation methods. The following contents are only some typical embodiments in the research process of this application. They are only used for examples and do not constitute any limitation on the technical solution requested for protection of the present invention.

[0044] Example 1: Core formula mining for treating icteric hepatitis The time limit is 2000-2022; the keywords of "reducing jaundice", "promoting bile secretion" and "protecting the liver" are used to search for relevant prescriptions and Chinese patent medicines in CNKI and Wanfang Data Yaozhi Database, and relevant medical records are searched in the Ancient and Modern Medical Records Cloud Platform. Physiological jaundice, jaundice caused by non-liver damage, non-clinical research and animal experimental research, non-oral prescriptions, prescriptions or Chinese patent medicines with unclear dosages are excluded. The collected literature, medical records, and Chinese patent medicine data are entered into Excel software to establish a Chinese medicine prescription database and standardize the names of Chinese medicines. The software used includes SPSS AU, IBM SPSS Statistics26.0, and IBM SPSS Modeler18.0; 1. Statistics and analysis of the frequency of use of each drug flavor, drug flavor category, drug meridians, etc. CNKI and Wanfang databases obtained 321 documents in total; Yaozhi database obtained 51 prescriptions or Chinese patent medicine prescriptions; Gujin Medical Case Cloud Platform obtained 11 medical cases, and after removing 88 duplicate prescriptions, a total of 295 prescriptions and 267 Chinese medicines were obtained; there were 8 categories with a usage frequency of >100 times. See Table 1, Table 2, and Table 3; Table 1 Frequency table of high frequency drugs Table 2 Drug classification Drug Classification Frequency percentage(%) Diuretic and Dampness-Removing Drugs 748 24.1 Heat-clearing drugs 678 21.9 Tonic 414 13.3 Blood-activating and stasis-removing drugs 368 11.9 Digestive Medicine 163 5.3 Antipyretic drugs 160 5.2 Laxatives 146 4.7 Qi-regulating drugs 116 3.7 Table 3 Distribution of APIs at the Meridian Meridians Frequency percentage(%) Liver Meridian 1809 18.9 Spleen Meridian 1637 17.1 Stomach Meridian 1271 13.3 Lung Meridian 1267 13.2 Heart Sutra 1125 11.7 Gallbladder Meridian 735 7.7 Kidney Meridian 557 5.8 Large Intestine Meridian 412 4.3 Bladder Meridian 357 3.7 Small Intestine Meridian 266 2.8 Triple Burner Meridian 143 1.5 total 9579 100 2. Formulation Analysis 1) AHP The first-level index includes two elements: category and meridian. There are 9 second-level indexes under the category, including diuretic and dampness-introducing drugs, purgative drugs, and heat-clearing drugs. According to the theory of the internal and external organs, there are 5 second-level indexes under the meridian, including liver / gallbladder, spleen / stomach. According to the traditional Chinese medicine theory, the treatment of icteric hepatitis includes removing dampness and phlegm, clearing heat and detoxifying, promoting blood circulation and removing blood stasis, promoting gallbladder, soothing the liver, and relieving jaundice. At the same time, the functions and indications of each medicine are comprehensively considered, and 10 third-level indexes are set, including diuretic / dampness-removing, heat-clearing, gallbladder-removing, and jaundice-removing. In order to distinguish the importance of each effect, each effect is assigned a value and score, and the drug efficacy score is calculated according to the drug efficacy. "Diuretic, diuretic, and stranguria-relieving", "clearing heat, cooling blood, detoxifying, and detoxifying", "reducing jaundice", "protecting the liver and soothing the liver", "promoting gallbladder", "tonifying the spleen and strengthening the spleen", and "activating blood circulation" are assigned 5 points; "tonifying qi, replenishing qi, and promoting qi" are assigned 5 points; "moistening the intestines and relieving constipation, purging" are assigned 4 points; "digestion and appetite" are assigned 2 points. In order to avoid logical errors when assigning values ​​to construct the AHP index system, the CR value needs to be calculated. The CI value is calculated based on the maximum eigenvalue (CI = (maximum eigenvalue-n) / (n-1)). The random consistency RI value can be obtained by querying the RI value table (see Table 4), CR = CI / RI. If the CR value is greater than 0.1, it means that there is no consistency, and the judgment matrix should be appropriately adjusted and analyzed again. This study established an AHP three-level evaluation system (see Table 5 for details); Table 4 Random consistency RI table nth order 3 4 5 6 7 8 9 10 11 12 13 14 RI 0.52 0.89 1.12 1.26 1.36 1.41 1.46 1.49 1.52 1.54 1.56 1.58 Table 5 AHP index system First level indicator Secondary indicators Level 3 indicators category Diuretic and Dampness-Removing Drugs Diuretic / dampness-removing Laxatives Clearing away heat Blood-activating and stasis-removing drugs Choleretic Heat-clearing drugs Yellowing Antipyretic drugs Soothing the Liver Tonic Activate blood circulation and remove blood stasis Digestive Medicine Replenishing Qi Qi-regulating drugs Strengthen the spleen Dampness-removing drugs Laxative / laxative Meridians Lung / Large Intestine Appetite / Digestion Spleen / Stomach Liver / Gallbladder Heart / Small Intestine Kidney / bladder ① AHP hierarchical analysis of primary indicators The first-level index judgment matrix is ​​shown in Table 6. The second-level judgment matrix for meridians and categories is constructed by AHP hierarchical method as shown in Table 7. The second-level data all meet the consistency test; Table 6 AHP matrix of primary indicators Table 7 Results of AHP hierarchical analysis of primary indicators ② Secondary indicator drug category AHP hierarchical analysis The 9-order judgment matrix was constructed by scoring the secondary indicators of the 9 categories, as shown in Table 8. The characteristic vectors obtained by analysis are shown in Table 9. The maximum characteristic root is 9.980, and the calculated CR value is 0.084<0.1, and the obtained weights are consistent; Table 8 AHP matrix data of secondary indicators of drug categories Table 9 Results of AHP hierarchical analysis of secondary indicators of drug categories ③AHP hierarchical analysis of secondary meridian indicators A five-order judgment matrix was constructed for the secondary meridian indexes and the AHP hierarchical method was used for research. The constructed judgment matrix is ​​shown in Table 10, and the characteristic vector obtained by analysis is shown in Table 11. The CR value is <0.1, which is consistent; Table 10 AHP matrix data of secondary meridian indexes Heart / Small Intestine Lung / Large Intestine Kidney / bladder Liver / Gallbladder Spleen / Stomach Heart / Small Intestine 1 1 / 2 1 / 3 1 / 5 1 / 7 Lung / Large Intestine 2 1 1 / 4 1 / 5 1 / 7 Kidney / bladder 3 4 1 1 / 5 1 / 7 Liver / Gallbladder 5 5 5 1 1 / 2 Spleen / Stomach 7 7 7 2 1 Table 11 Results of AHP analysis of secondary meridian indicators 2) The weighted efficacy score of high-frequency APIs calculated by AHP hierarchical analysis ① Select the top ranked raw materials in AHP analysis as candidate raw materials, and use the calculated results as raw material efficacy scores; the frequency of occurrence in the candidate raw material database is used as the raw material frequency score. Select drugs with efficacy scores greater than 2 after weighting by AHP hierarchical analysis for CRITIC analysis, where the weighted efficacy scores calculated by AHP hierarchical analysis are used as the efficacy scores of the drugs, and the frequency of occurrence of the drugs in the prescriptions collected when the database was initially established is used as its frequency score, as shown in Tables 12 and 13; Table 12: Drug efficacy scores Table 13 AHP weighted drug substance scores ② The drugs with efficacy scores greater than 2 after weighting by AHP hierarchical analysis were selected for CRITIC analysis, in which the weighted efficacy score calculated by AHP hierarchical analysis was used as the efficacy score of the drug, and the frequency of the drug in the prescription collected when the database was initially established was used as its frequency score, see Table 14; Table 14 Efficacy-frequency score of high-frequency drugs after AHP weighting ③The objective weight values ​​of CRITIC analysis were linearly weighted to calculate the weighted score of subjective-objective combination, and the total scores of each drug were finally arranged in descending order. See Table 15; Table 15 Subjective-objective combined drug weighted scores ④ Cluster analysis was performed on the top 19 drugs ranked by AHP analysis. The internal characteristics of the categories were similar. A clustering matrix was constructed based on the drug efficacy. 1 represents existence and 0 represents non-existence. The clustering matrix was imported into IBM SPSSStatistics 26.0 software, and systematic clustering was selected to perform cluster analysis on the drugs. There were some differences between the categories, which could classify the data more objectively and reduce the influence of subjective judgment, as shown in Table 16; Table 16 Clustering matrix ⑤ According to the drug scores of AHP-CRITIC subjective and objective combined analysis, the results of system clustering and the pharmacological effects of each drug, seven drugs, namely, Artemisia capillaris, Rhubarb, Gardenia jasminoides, Lysimachia chinensis, Curcuma aromatica, Paeonia lactiflora and Poria cocos, were selected for the subsequent core prescription compatibility; 3) After matrix transformation, the data was imported into SPSS.Modeler 18.0 software for Apriori association rule analysis ① With confidence > 80%, frequent item sets in drug combinations were screened out, and then support > 10% was set to screen out item sets with strong associations. Finally, with lift > 1, positively correlated drug combinations were screened out, and 18 groups of data were obtained. The relevant data were displayed in descending order of support. Commonly used drug combinations include Artemisia capillaris and Rhubarb, Artemisia capillaris and Red Peony Root, Artemisia capillaris and Salvia miltiorrhiza, Artemisia capillaris and Curcuma aromatica, etc., as shown in Table 17; Table 17 Analysis results of drug Apriori association rules Drug 1 Drug 2 Support (%) Confidence(%) Lift Artemisia capillaris rhubarb 45.58 88.06 1.11 Artemisia capillaris Red Peony Root 44.90 84.09 1.06 Artemisia capillaris Salvia miltiorrhiza 39.46 84.48 1.07 Artemisia capillaris Turmeric 39.12 80.87 1.02 Artemisia capillaris Gardenia 38.10 92.86 1.17 Artemisia capillaris Poria 37.07 80.73 1.02 Artemisia capillaris Moneywort 36.05 80.19 1.01 Artemisia capillaris Licorice 33.67 85.86 1.08 Artemisia capillaris Knotweed 27.21 85.00 1.07 Artemisia capillaris Scutellaria baicalensis 24.49 81.94 1.03 Artemisia capillaris Isatis root 15.31 97.78 1.23 Artemisia capillaris Plantago 13.27 92.31 1.16 Artemisia capillaris Alisma orientalis 12.93 94.74 1.20 Artemisia capillaris Tangerine peel 12.24 86.11 1.09 Poria Poria 11.56 82.35 2.22 Artemisia capillaris Hedyotis diffusa 10.88 96.88 1.22 Red Peony Root Peony bark 10.20 83.33 1.86 Artemisia capillaris Peony bark 10.20 80.00 1.01 ② With confidence>80% and support>10%, positively correlated horn medicine combinations were screened. The relevant data were displayed in descending order of support. Commonly used horn medicine combinations included: Artemisia capillaris, rhubarb and red peony root; Artemisia capillaris, Salvia miltiorrhiza and red peony root; Artemisia capillaris, Gardenia jasminoides and rhubarb; Artemisia capillaris, Bupleurum chinense and rhubarb, etc. 21 groups of data are shown in Table 18; Table 18 Results of Apriori association rule analysis of horn medicine ③ Confidence>80%, support>10%, screen positively correlated four-drug combinations. The relevant data are displayed in descending order of support. Commonly used four-drug combinations include Artemisia capillaris, rhubarb, Danshen and red peony root; Artemisia capillaris, rhubarb, gardenia and red peony root; Artemisia capillaris, curcuma, rhubarb and red peony root, as shown in Table 19; Table 19 Apriori association rule analysis results for four drugs Drug 1 Drug 2 + Drug 3 + Drug 4 Support (%) Confidence(%) Lift Artemisia capillaris Salvia miltiorrhiza + rhubarb + red peony root 17.01 90.00 1.14 rhubarb Gardenia+Red Peony Root+Mushroom 16.33 83.33 1.83 Artemisia capillaris Curcuma+Rhubarb+Red Peony Root 13.95 92.68 1.17 Artemisia capillaris Gardenia + Rhubarb + Red Peony Root 13.61 100.00 1.26 Artemisia capillaris Lysimachia chinensis + Rhubarb + Red Peony Root 12.93 94.74 1.20 Artemisia capillaris Bupleurum+rhubarb+red peony root 11.56 94.12 1.19 Artemisia capillaris Gardenia + Bupleurum + Rhubarb 11.56 97.06 1.22 Artemisia capillaris Poria cocos + rhubarb + red peony root 10.88 93.75 1.18 Artemisia capillaris Curcuma+Salvia miltiorrhiza+Red peony root 10.54 80.65 1.02 Artemisia capillaris Lysimachia chinensis + Curcuma zedoaria + Paeonia lactiflora 10.54 83.87 1.06 Artemisia capillaris Gardenia + Curcuma + Rhubarb 10.54 96.77 1.22 rhubarb Curcuma+Salvia miltiorrhiza+Red peony root 10.54 80.65 1.77 Artemisia capillaris Curcuma+Salvia+Rhubarb 10.20 86.67 1.09 Red Peony Root Curcuma+Salvia+Rhubarb 10.20 83.33 1.86 4) TOPSIS analysis method was used to comprehensively evaluate the selected core prescriptions, and the top-ranked core prescription was selected for subsequent research. The drug association rules contained 18 groups of data, and the corner drug association rules contained 21 groups of data. The data covering 7 candidate raw materials were selected and combined with traditional Chinese medicine theory to formulate prescriptions; among the 15 groups of data in the four-drug association rules, 5 groups of data included 7 candidate raw materials, and these 5 groups of data were used as candidate core prescriptions. The candidate formulas were constructed by the above grouping method, as shown in Table 20 and Table 21; Table 20 Candidate formulations The candidate recipes are scored and ranked by TOPSIS, and the score matrix of each recipe is shown in Table 21; Table 21 Candidate formulation TOPSIS matrix Prescription Number effect Frequency 1 0.66 594.83 2 0.70 597.73 3 0.80 589.02 4 0.72 591.93 5 0.68 568.71 6 0.67 576.45 7 0.77 567.75 8 0.69 570.65 9 0.61 571.62 10 0.55 574.52 11 0.81 570.65 12 0.83 564.84 The above formula score matrix was imported into SPSS AU to perform TOPSIS method to find the positive and negative ideal solution values ​​(A+ and A-) of the evaluation index. The positive ideal solution of the efficacy score was 0.83, the negative ideal solution was 0.55, the positive ideal solution of the frequency score was 597.73, and the negative ideal solution was 564.84. The TOPSIS results of all candidate formulas are shown in Table 22; Table 22 TOPSIS results of candidate formulations serial number D D- C Sorting results 1 2.905 29.99 0.912 2 2 0.13 32.89 0.996 1 3 8.71 24.181 0.735 4 4 5.801 27.091 0.824 3 5 29.02 3.872 0.118 10 6 21.281 11.611 0.353 5 7 29.98 2.918 0.089 11 8 27.08 5.812 0.177 9 9 26.111 6.78 0.206 7 10 23.212 9.68 0.294 6 11 27.08 5.816 0.177 8 12 32.89 0.28 0.008 12 The distance values ​​D+ and D- between each evaluation object and the positive and negative ideal solutions, as well as the degree of proximity (C value) between each evaluation object and the optimal solution were calculated, and the formula was ranked according to the C value. The first one was formula 2: Artemisia capillaris, Curcuma zedoaria, Rhubarb, and Paeonia lactiflora, with a positive ideal solution distance of 0.13, a negative ideal solution distance of 32.89, and a relative degree of proximity of 0.996; Artemisia capillaris, Curcuma zedoaria, Rhubarb, and Paeonia lactiflora were selected as the core formula for subsequent research.

[0045] Example 2: Dosage ratio and split analysis of the core recipe NO is closely related to liver damage and inflammatory response. Studies have found that the serum NO level and inducible nitric oxide synthase (iNOS) level in hepatitis patients are significantly higher than those in normal people, and are positively correlated with alanine aminotransferase (ALT) levels, indicating that NO and iNOS play an important role in the development of hepatitis. Therefore, the study of NO helps to deeply understand the pathogenesis of icteric hepatitis and may provide important clues for the development of new therapeutic strategies. Based on lipopolysaccharide (LPS)-induced mouse mononuclear macrophage RAW264.7, an in vitro anti-inflammatory model was established. LPS binds to lipopolysaccharide binding protein (LBP) on the cell membrane to form an LPS-LBP complex, which then binds to CD14 and is presented to the MD-2-TLR4 complex. This process triggers the dimerization of TLR4, initiates a signal transduction cascade, and promotes the synthesis of proinflammatory cytokines and iNOS. Overexpression of iNOS catalyzes the production of NO, and excessive NO has a toxic effect on cells. Therefore, the anti-inflammatory potential of the drugs, such as the angle drug and the fourth drug, was preliminarily evaluated by measuring the NO content; 1. Effects of different concentrations of LPS on the survival rate of RAW264.7 cells RAW264.7 macrophages were cultured at a density of 1×10 5 100 μL per well was inoculated into a 96-well plate and cultured in a cell culture incubator for 24 h. After induction with culture medium containing 0.1, 0.5, 1, 2, 5, 10, 20, and 50 μg / mL LPS for 24 h, CCK-8 was used to detect cell viability, and the optimal concentration of LPS was determined based on cell viability (see Appendix Figure 1 ). The above experimental results show that with the increase of LPS concentration, the survival rate of RAW264.7 cells decreased. When the LPS concentration was 50μg / mL, the cell viability was significantly inhibited (P<0.01), so the LPS concentration for modeling was selected as 1μg / mL; 2. Effect of single drug on LPS-induced RAW264.7 cell survival rate RAW264.7 macrophages were cultured at a density of 1×10 5 / mL, 100μL per well was inoculated in a 96-well plate and cultured in a cell culture incubator for 24h. After induction with culture medium containing 0, 25, 50, 100, 200μg / mL of Artemisia capillaris, red peony root, rhubarb, and Curcuma australis for 24h, CCK-8 was used to detect cell viability, and the optimal dosage concentration of Artemisia capillaris, red peony root, rhubarb, and Curcuma australis was determined according to cell viability (see Appendix Figure 2 ). The experimental results showed that with the increase of the concentration of Artemisia capillaris, red peony root, rhubarb and curcuma, the survival rate of RAW264.7 cells decreased. Therefore, the selected concentrations of Artemisia capillaris, red peony root, rhubarb and curcuma were all 25μg / mL; 3. Anti-inflammatory effects of different drug components (1) Dilute the well-cultured RAW264.7 cell suspension to 1×10 5 / mL, placed on a 96-well plate, and incubated in a 37°C, 5% CO2 incubator for 24 h. (2) (2) The 96-well plate was divided into 13 groups. Blank group (containing cells only), model group (cells + LPS), group ① (cells + LPS + Artemisia capillaris, rhubarb), group ② (cells + LPS + red peony root, curcuma), group ③ (cells + LPS + Artemisia capillaris, rhubarb, red peony root), group ④ (cells + LPS + Artemisia capillaris, rhubarb, curcuma), group ⑤ (cells + LPS + rhubarb, red peony root, curcuma), group ⑥ (cells + LPS + Artemisia capillaris, rhubarb, curcuma), group ⑦ (cells + LPS + Artemisia capillaris, rhubarb, red peony root, curcuma), group ⑧ (cells + LPS + Artemisia capillaris, red peony root, Lysimachia 30 parts each, curcuma 15 parts, rhubarb 10 parts), group ⑨ (cells + LPS + Artemisia capillaris 10 parts, curcuma 6 parts, chicken gizzard 6 parts, rhubarb 3 parts), group ⑩ (cells + LPS + Artemisia capillaris 30 parts, rhubarb 10 parts, gardenia 10 parts, red peony root 15 parts), (Cells + LPS + 30 portions each of Artemisia capillaris, Paeonia lactiflora, and Lysimachia chinensis, and 10 portions of Rhubarb), with 6 replicate wells in each group. (3) After overnight, discard the old culture medium, directly add 300 μL of fresh culture medium to the model group and blank group, and add 300 μL of solution containing different drugs (paired drugs, horn drugs, and four drugs) according to the concentration determined in (2.3.2) to each well of the experimental group. (4) After 1 hour, add LPS to stimulate the cells so that the final concentration of LPS is 1 μg / mL. (5) Continue to culture for 24 hours, then discard the supernatant and add 50 μL of GriessReagent I and 50 μL of GriessReagent II at room temperature to each well. (6) Measure the absorbance at 540 nm with an enzyme reader and substitute it into the standard curve to calculate the NO content. (See Appendix Figure 3 ). The experimental results showed that compared with the blank group, the amount of NO released by RAW264.7 cells after LPS induction was significantly increased (P<0.05), and the inhibition of NO by the drug, the corner drug, and the four drugs was different. Among them, the seventh group (P<0.001) could significantly reduce the amount of NO released by inflammatory cells, which was better than other groups. It proved that the combination of Artemisia capillaris, Curcuma aromatica, Rhubarb, and Red Peony Root had the best compatibility and synergistic effect; 4. Anti-inflammatory effects of different ratios (1) Dilute the well-cultured RAW264.7 cell suspension to 1×10 5 / mL, placed on a 96-well plate. To prevent edge effects, 100μL PBS should be added to each well around the plate and incubated in a 37μ, 5% CO2 incubator for 24h. (2) The 96-well plate is divided into 10 groups. Blank group (containing only cells), model group (cells + LPS), group ① (cells + LPS + Artemisia capillaris 3: red peony root 3: rhubarb 1: curcuma 1), group ② (cells + LPS + Artemisia capillaris 2: red peony root 2: rhubarb 1: curcuma 1), group ③ (cells + LPS + Artemisia capillaris 1: red peony root 1: rhubarb 1: curcuma 1), group ④ (cells + LPS + Artemisia capillaris 1: red peony root 1: rhubarb 3: curcuma 3), group ⑤ (cells + LPS + Artemisia capillaris 1: red peony root 1: rhubarb 2: curcuma 2), group ⑥ (cells + LPS + Artemisia capillaris 1: red peony root 3: rhubarb 3: curcuma 1), group ⑦ (cells + LPS + Artemisia capillaris 1: red peony root 2: rhubarb 2: curcuma 1), group ⑧ (cells + LPS + Artemisia capillaris 1: red peony root 3: rhubarb 1: curcuma 1), each group with 6 replicate wells. (3) After overnight, discard the old culture medium, directly add 300 μL of fresh culture medium to the model group and blank group, and add 300 μL of solution containing different doses of the four drugs (according to the concentration determined in 2.3.2) to each well of the experimental group. (4) After 1 hour, add LPS to stimulate the cells so that the final concentration of LPS is the optimal LPS concentration determined in 2.3.1. (5) Continue to culture for 24 hours, then discard the supernatant and add 50 μL of Griess Reagent I and 50 μL of Griess Reagent II at room temperature to each well. (6) Measure the absorbance at 540 nm with an enzyme reader and substitute it into the standard curve to calculate the NO content (see Appendix). Figure 4 ). The experimental results showed that compared with the blank group, the NO release of RAW264.7 cells in the model group after LPS induction was significantly increased (P<0.001); compared with the model group, the NO release of different drug administration groups was significantly reduced (P<0.001). The first group of different doses of drug administration can more significantly reduce the NO release of inflammatory cells. It proves that the group of Artemisia capillaris 3: red peony root 3: rhubarb 1: curcuma 1 has the best effect.

[0046] Example 3: Preparation Example Take 750g of Artemisia capillaris, 250g of Curcuma aromatica, 250g of Rhubarb, and 750g of Red Peony Root, add appropriate amount of water and soak for 30 minutes, heat and boil twice, the first time for 2 hours and the second time for 1 hour, combine the decoctions, filter, heat and concentrate the filtrate to 1000mL, package and sterilize.

[0047] Example 4: Preparation Example Take 1000g of Artemisia capillaris, 150g of Curcuma aromatica, 250g of Rhubarb, and 550g of Red Peony Root, add appropriate amount of water and soak for 30 minutes, heat and boil for 3 times, the first time for 2 hours, the second time for 1 hour, and the third time for 1 hour, combine the decoctions, filter, concentrate, dry, and prepare into capsules.

[0048] Example 5: Preparation Example Take 550g of Artemisia capillaris, 150g of Curcuma aromatica, 150g of Rhubarb, and 550g of Red Peony Root, add appropriate amount of 60% ethanol and soak for 60 minutes, heat and reflux to extract twice, the first time for 1 hour and the second time for 1 hour, combine the decoctions, concentrate under reduced pressure, dry, add appropriate excipients, and prepare tablets.

[0049] Example 6: Preparation Example Take 1000g of Artemisia capillaris, 450g of Curcuma aromatica, 450g of Rhubarb, and 1000g of Red Peony Root, add appropriate amount of water and soak for 30 minutes, heat and boil twice, the first time for 2 hours and the second time for 1 hour, combine the decoctions, filter, heat and concentrate the filtrate, add auxiliary materials, and prepare it as an oral solution.

[0050] Example 7: Preparation Example Take 600g of Artemisia capillaris, 150g of Curcuma aromatica, 150g of Rhubarb, and 600g of Red Peony Root, add appropriate amount of water and soak for 30 minutes, heat and boil twice, the first time for 2 hours and the second time for 1 hour, extract the residues with 90% ethanol reflux once, combine the decoctions, concentrate under reduced pressure, add auxiliary materials, and prepare granules.

[0051] Example 8: Preparation Example Take 900g of Artemisia capillaris, 350g of Curcuma aromatica, 350g of Rhubarb, and 900g of Red Peony Root, extract them 3 times with 70% ethanol reflux, combine the decoctions, concentrate under reduced pressure, add auxiliary materials, and prepare a paste.

[0052] Example 9: Preparation Example Take 700g of Artemisia capillaris, 200g of Curcuma aromatica, 200g of Rhubarb, and 700g of Red Peony Root, add appropriate amount of water and soak for 30 minutes, heat and boil twice, the first time for 2 hours and the second time for 1 hour, combine the decoctions, filter, heat and concentrate the filtrate to 1000mL, package and sterilize.

[0053] Example 10: Preparation Example Take 800g of Artemisia capillaris, 300g of Curcuma aromatica, 300g of Rhubarb, and 800g of Red Peony Root, add appropriate amount of water and soak for 30 minutes, heat and boil twice, the first time for 2 hours and the second time for 1 hour, extract the residues with 90% ethanol reflux once, combine the decoctions, concentrate under reduced pressure, add auxiliary materials, and prepare granules.

[0054] Example 11: Pharmacodynamics Experiment The effect of the core formula was evaluated from the perspective of drug efficacy by establishing an icteric hepatitis rat model; 1. Experimental Animals Healthy male SD rats weighing 200 ± 20 g were provided by the Experimental Animal Center of Ningxia Medical University (Experimental Animal License No.: SNXK (Ning) 2020-000). They were adaptively raised in a natural environment for 3 days with unlimited access to water and food; 2. Preparation of medicines Preparation of ANIT oil solution: Prepare 2% ANIT (20 mg / mL) oil solution with olive oil as solvent, and set aside. Note that it should be prepared and used immediately and protected from light; Preparation of yellow liver decoction: The yellow liver decoction is prepared according to the drug instructions of the in-hospital preparation: Take 300g of Artemisia capillaris, 60g of Angelica sinensis, 120g of Scutellaria baicalensis, 100g of Phellodendron chinense, 100g of Gentiana scabra, 100g of Curcuma aromatica, 100g of Chuanxiongzi, 100g of Poria cocos, 150g of Dioscorea opposita, 100g of Plantago, 100g of Rhubarb, Malt, Hawthorn, and Liushenqu, soak in water for 30 minutes, heat and decoct twice, the first time for 2 hours. The second time for 1 hour, combine the two filtrates, heat and concentrate to 1000mL, package and sterilize to obtain a yellow liver decoction preparation with a concentration of 1.63g / mL; Preparation of the core formula mixture: The dosage of each medicine in the core formula shall be based on the most commonly used dosage obtained by data mining, and the concentration of the core formula shall be determined by the concentration of Huanggan decoction and the dosage. Take 750g of Artemisia capillaris, 250g of Curcuma zedoariae, 250g of Rhubarb, and 750g of Red Peony Root, add appropriate amount of water and soak for 30 minutes, heat and boil twice, the first time for 2 hours, the second time for 1 hour, combine the decoction, filter, heat and concentrate the filtrate to 1000mL, package and sterilize to obtain the core formula with a high-dose concentration of 1.76g / mL, dilute to obtain a medium-dose concentration of 0.96g / mL and a low-dose concentration of 0.48g / mL; 3. Grouping and Modeling After three days of adaptive feeding, 36 SD male rats were randomly divided into 6 groups, 6 rats in each group, and the dosage was converted according to the rat dosage of 6.3 times the dosage of 70kg adults. The specific grouping and dosing were normal group, model group, positive control group of Huanggan decoction (26.4g / kg), low-dose group of core prescription (7.2g / kg), medium-dose group of core prescription (14.4g / kg), and high-dose group of core prescription (28.8g / kg). The positive control group and each dose group of core prescription were administered once a day for 10 consecutive days. The normal group and model group were given the same volume of purified water. Except for the normal group, the other groups were given 2% ANIT oil solution (100mg / kg) by gavage 2h after administration on the 8th day. The normal group was given an equal amount of olive oil solution by gavage, and the samples were collected on the 11th day; Sample collection and processing: Under 3% pentobarbital (40mg / kg) anesthesia, blood was collected from the eye sockets. After the blood was placed at room temperature for 30 minutes, it was centrifuged at 4℃, 3000r / min for 15min. Transfer the upper serum to a clean centrifuge tube, mark it, and store it in a -80℃ water tank. After the blood is collected from the eyeball, the rat is immediately dissected, and the rat liver is separated from the diaphragm. After weighing, it is placed in a culture dish containing a small amount of physiological saline prepared in advance, and shaken to remove the blood residue on the surface of the liver. The same position of the cut liver is immediately soaked in a 10% neutral formalin fixation tube for subsequent pathological HE staining sections; 4. Observation indicators General situation: During the experiment, the changes in eating habits, weight, hair loss and yellowing, changes in bowel movements, mental status, etc. of each group of rats were recorded; Observation of liver pathological sections: Observe the HE-stained (hematoxylin-eosin-stained) sections of each group under an optical microscope: the infiltration of inflammatory cells, the presence of hepatocyte degeneration, and the arrangement of hepatocyte cords and hepatic lobules; Biochemical index detection: Use automatic biochemical analyzer to detect serum ALT, AST, TBIL, and TBA biochemical indicators; Statistical analysis: SPSS 26.0 was used to analyze the data. The data analyzed in this chapter were all quantitative data, expressed as mean ± standard deviation. If the normal distribution was met and the variance was equal, one-way analysis of variance was used for inter-group comparison. Otherwise, non-parametric rank sum test was used, and p < 0.05 was considered statistically significant. 5. Results 1) General comparison Before modeling, the rats in each group had an increasing weight, normal eating, good condition, shiny fur, light yellow urine, and normal activity. After the modeling drug was administered, the rats in the model group had a significantly reduced appetite, a significantly reduced weight, more hair loss on the back and abdomen, and severe yellowing, a significantly reduced activity, curled up in a corner, and golden urine; the general condition of the rats in the positive control group and the core prescription groups had no significant difference in the naked eye, and they were in better condition than the model group; the normal group was in good condition, with no reduced activity, hair loss, etc., as shown in Table 22; Table 22 General condition of rats before and after modeling Note: ↑ represents an increase in the corresponding index, ↓ represents a decrease in the corresponding index, - represents no change, and the number of arrows represents the degree of increase or decrease↓↓↓; 2) Pathology of liver tissue sections. HE staining results showed that the hepatocyte structure of rats in the normal group was intact, the hepatic lobules were not damaged, the hepatocyte cords were arranged intact, and there was no inflammatory cell infiltration. A large number of cells with darker staining, i.e., inflammatory cells, were observed in the portal area of ​​the liver of rats in the model group, but there was no obvious damage to the hepatocytes and hepatic lobules. Compared with the model group, the inflammatory cell infiltration in the core prescription dosage groups and the positive control group was significantly reduced, and the hepatocyte and hepatic lobule structure was intact. The number of inflammatory cell infiltration in the core prescription dosage groups was similar and less than that in the positive control group. HE staining pathological sections of each group (×100 times, ×400 times) were shown. Fig. 9 ; 3) Comparison of biochemical indicators The ALT, AST, TBA, and TBIL indexes of the model group rats were higher than those of the normal group and the differences were statistically significant (p < 0.05), indicating that the model was successfully established; the three dose groups of the core prescription had similar abilities to reduce TBIL, all stronger than the positive control group; the low and medium dose groups of the core prescription had similar abilities to reduce TBA and stronger than the positive control group; the three dose groups of the core prescription had similar abilities to reduce ALT as the positive control group; the low dose group of the core prescription and the positive control group had similar abilities to reduce AST. Therefore, it was preliminarily inferred that the core prescription and the positive control group had similar effects on ALT, AST, TBA, and TBIL indexes, and the low dose group of the core prescription had the best effect, as shown in Table 23; Table 23 Statistical analysis of biochemical indicators Note: * All indicators of the representative model group were higher than those of the normal group and had statistically significant differences (p<0.05); # The TBA of the low-dose group and the medium-dose group of the core formula were lower than the TBA of the positive control group and the difference was statistically significant (p<0.05). ## The TBIL of the representative model group was higher than that of the three dosage groups of the core formula and the difference was statistically significant (p<0.05); ** The TBA of the representative model group was lower than that of the positive control group and the difference was statistically significant (p<0.05); *** The ALT levels of the representative model group were higher than those of the positive control group and the three dose groups of the core formula, and the differences were statistically significant (p<0.05); ### The AST of the representative model group was higher than that of the positive control group and the low-dose core formula group, and the difference was statistically significant (p<0.05).

Claims

1. A Chinese medicine composition for treating icteric hepatitis, characterized in that: The invention is prepared from Chinese medicinal raw materials in the following weight ratio: 11-20 parts of Artemisia capillaris, 3-9 parts of Curcuma aromatica, 3-9 parts of Rhubarb and 11-20 parts of Red Peony Root.

2. The Chinese medicine composition for treating icteric hepatitis according to claim 1, characterized in that: The drug is prepared from Chinese medicinal raw materials in the following weight ratio: 12-18 grams of Artemisia capillaris, 3-7 grams of Curcuma aromatica, 3-7 grams of Rhubarb, and 12-18 grams of Red Peony Root.

3. The Chinese medicine composition for treating icteric hepatitis according to claim 2, characterized in that: The drug is prepared from Chinese medicinal raw materials in the following weight ratio: 14-16 grams of Artemisia capillaris, 4-6 grams of Curcuma aromatica, 4-6 grams of Rhubarb, and 14-16 grams of Red Peony Root.

4. The Chinese medicine composition for treating icteric hepatitis according to claim 3, characterized in that: The drug is prepared from Chinese medicinal raw materials in the following weight ratio: 15 grams of Artemisia capillaris, 5 grams of Curcuma aromatica, 5 grams of Rhubarb, and 15 grams of Red Peony Root.

5. Use of the Chinese medicine composition according to claims 1-4 in the preparation of a drug for treating liver injury, wherein the treatment of liver injury is to reduce inflammation during liver injury; and / or to reduce the abnormal increase of serum ALT, AST, TBIL, and TBA indicators during liver injury.

6. Use of the Chinese medicine composition according to claims 1-4 in preparing a drug for treating icteric hepatitis.

7. A data mining method for the Chinese medicine composition for treating icteric hepatitis according to claims 1-4, characterized in that: The steps include: 1) Building a database, i.e. collecting prescription information on the treatment of icteric hepatitis from literature, medical records, and Chinese patent medicine databases as needed to form a database; 2) Data mining, including raw material screening and formula analysis; 3) The best formula scored by TOPSIS was Artemisia capillaris, Curcuma aromatica, Rhubarb and Paeonia lactiflora, which was used as the core formula.

8. The method according to claim 7, characterized in that The database construction also includes a step of data standardization, using standardized names of medicinal materials, unifying extracts as original medicinal materials, and recording the nature, flavor and meridians of the medicinal materials.

9. The method according to claim 7, characterized in that: The raw material screening includes raw material frequency statistics, raw material category analysis, raw material four-qi analysis, raw material five-flavor analysis, raw material meridian analysis, and raw material association rule analysis, and the raw material association rule analysis includes pair-drug association, corner-drug association, and four-flavor drug association; and / or the formula analysis includes AHP hierarchical analysis, CRITIC analysis, cluster analysis, and TOPSIS analysis.

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