Application of traditional Chinese medicine composition in preparation of medicine for preventing alteration of intestinal flora

Abstract

The invention provides application of a traditional Chinese medicine composition in preparation of a medicine for preventing intestinal flora imbalance. The traditional Chinese medicine composition is prepared from the following components in parts by weight: 128 to 137 parts of radix scutellariae, 128 to 137 parts of radix bupleuri, 103 to 120 parts of radix et rhizoma rhei, 128 to 137 parts of fructus aurantii, 128 to 137 parts of herba artemisiae scopariae, 171 to 200 parts of rhizoma polygoni cuspidati, 137 to 150 parts of fructus gardeniae, 250 to 342 parts of herba lysimachiae, 128 to 137 parts of radix paeoniae alba, 128 to 137 parts of radix aucklandiae, 90 to 103 parts of rhizoma pinelliae preparata and 34 to 40 parts of rhizoma zingiberis recens. The traditional Chinese medicine composition can increase the alpha-diversity index of the intestinal flora, improve the composition of the intestinal flora under the gate level and improve the composition of the intestinal flora under the genus level, and by increasing the diversity index of the intestinal flora, improve the homeostasis of the intestinal tract of a mouse and enrich and increase the diversity and uniformity of the intestinal flora, the traditional Chinese medicine composition exerts the effects of preventing the alteration of the intestinal flora and improving the immunity of the mouse. Especially, intestinal flora imbalance caused by high-fat and high-cholesterol diet can be treated.

Description

Technical Field

[0001] This invention belongs to the field of traditional Chinese medicine technology, and specifically relates to the application of a traditional Chinese medicine composition. Background Technology

[0002] With the improvement of people's living standards, the variety of food has become more and more abundant, and the intake of high-fat and high-cholesterol foods has also increased, leading to more and more serious health problems. Intestinal flora imbalance is one of the common problems.

[0003] Existing research has found that the state of the gut microbiota has many impacts on human health and is related to the occurrence and development of various diseases. For example, literature reports that Akkermansia, a mucin-degrading bacterium of the phylum Verrucomicrobia, is closely related to hyperglycemia, hyperlipidemia, and cardiovascular diseases. Lachnospiraceae_NK4A136_group, belonging to the phylum Firmicutes, is a beneficial bacterium that has a repairing effect on intestinal mucosal damage, and its content is reduced in intestinal-related diseases.

[0004] Chinese patent CN115429866A discloses a traditional Chinese medicine composition for treating cholecystitis and its preparation method. The components of this composition include: Scutellaria baicalensis, Bupleurum chinense, Rheum palmatum, Citrus aurantium, Artemisia capillaris, Polygonum cuspidatum, Gardenia jasminoides, Lysimachia christinae, Paeonia lactiflora, Aucklandia lappa, Pinellia ternata, and Zingiber officinale. The traditional Chinese medicine preparation made from this composition can be used to treat chronic cholecystitis. As an innovative traditional Chinese medicine, the research on this composition has been continuously deepening and has yielded unexpected results. Summary of the Invention

[0005] The purpose of this invention is to provide new uses for the traditional Chinese medicine composition disclosed in Chinese Patent CN115429866A.

[0006] To achieve the above objectives, the inventors have provided the following technical solutions.

[0007] The application of a traditional Chinese medicine composition in the preparation of a drug for preventing intestinal flora imbalance, wherein the raw materials of the traditional Chinese medicine composition are, by weight, 128-137 parts of Scutellaria baicalensis, 128-137 parts of Bupleurum chinense, 103-120 parts of Rheum palmatum, 128-137 parts of Citrus aurantium, 128-137 parts of Artemisia capillaris, 171-200 parts of Polygonum cuspidatum, 137-150 parts of Gardenia jasminoides, 250-342 parts of Lysimachia christinae, 128-137 parts of Paeonia lactiflora, 128-137 parts of Aucklandia lappa, 90-103 parts of Pinellia ternata, and 34-40 parts of Zingiber officinale.

[0008] In the above applications, the preferred raw material composition of the traditional Chinese medicine composition by weight is: 128 parts of Scutellaria baicalensis, 128 parts of Bupleurum chinense, 120 parts of Rheum palmatum, 128 parts of Citrus aurantium, 128 parts of Artemisia capillaris, 200 parts of Polygonum cuspidatum, 150 parts of Gardenia jasminoides, 250 parts of Lysimachia christinae, 128 parts of Paeonia lactiflora, 128 parts of Aucklandia lappa, 90 parts of Pinellia ternata, and 40 parts of Zingiber officinale.

[0009] In the above applications, the raw material composition of the traditional Chinese medicine composition, by weight, can preferably be: 137 parts of Scutellaria baicalensis, 137 parts of Bupleurum chinense, 103 parts of Rheum palmatum, 137 parts of Citrus aurantium, 137 parts of Artemisia capillaris, 171 parts of Polygonum cuspidatum, 137 parts of Gardenia jasminoides, 342 parts of Lysimachia christinae, 137 parts of Paeonia lactiflora, 137 parts of Aucklandia lappa, 103 parts of Pinellia ternata, and 34 parts of Zingiber officinale.

[0010] In the above applications, the preparation method of the traditional Chinese medicine composition includes the following steps:

[0011] A. Weigh out ginger and Pinellia ternata, grind them into fine powder, sterilize by 60Co irradiation, and set aside;

[0012] B. Weigh out the bitter orange peel and fresh ginger, add 5-9 times the amount of water, extract the volatile oil for 8-12 hours, collect and separate the volatile oil; the distilled aqueous solution is for later use.

[0013] C. Weigh out Scutellaria baicalensis, Paeonia lactiflora, Artemisia capillaris, and Gardenia jasminoides. Add water and decoct 2-4 times. Extract for 1-3 hours for the first time, and for 1-3 hours for the second, third, and fourth times respectively. Add 7-10 times the amount of water each time. Filter the extract and combine it with the volatile oil-water extract obtained in step B. Concentrate under reduced pressure to a relative density of 1.25±0.05 at 60℃ for later use.

[0014] D. Weigh out Bupleurum, Aucklandia, Rhubarb, Polygonum cuspidatum, and Lysimachia christinae. Extract with 60-80% ethanol 2-4 times. For the first extraction, add 10-14 times the amount of ethanol and extract for 2-4 hours. For the second, third, and fourth extractions, add 8-12 times the amount of ethanol and extract for 1-3 hours each time. Filter the extract, concentrate it into a clear paste, combine it with the water extract obtained in step C, mix well, dry, and pulverize for later use.

[0015] E. The fine powder obtained in step A, the volatile oil obtained in step B, and the dried powder obtained in step D can be mixed together.

[0016] The traditional Chinese medicine composition described in this application can be prepared into various drug dosage forms as needed, including capsules, tablets, pills, oral liquids, granules, or powders.

[0017] The application of the traditional Chinese medicine composition provided by this invention in the preparation of a drug for preventing intestinal flora imbalance, wherein the prevention of intestinal flora imbalance is to increase the α-diversity index of intestinal flora and / or improve the composition of intestinal flora at the phylum level and / or improve the composition of intestinal flora at the genus level.

[0018] The α-diversity index is the Pielou index, and / or the Chao1 index, and / or the Simpson index, and / or the Shanon index.

[0019] The improvement of the gut microbiota composition at the phylum level is achieved by reducing the F / B ratio in the gut, and / or increasing the abundance of Firmicutes bacteria, and / or increasing the abundance of Bacteroidota bacteria, and / or increasing the abundance of Cyanobacteria bacteria, and / or decreasing the abundance of Verrucomicrobiota bacteria.

[0020] The improvement in gut microbiota composition at the genus level is achieved by reducing the abundance of the gut Akkermansia microbiota and / or increasing the abundance of the gut Lachnospiraceae_NK4A136_group microbiota.

[0021] The gut microbiota imbalance is preferably caused by a high-fat, high-cholesterol diet.

[0022] Experimental studies have shown that the traditional Chinese medicine composition of this application exhibits unexpected effects in preventing intestinal flora imbalance caused by a high-fat, high-cholesterol diet. The results show that the traditional Chinese medicine composition of this application can significantly increase the intestinal flora diversity index in mice fed a high-fat, high-cholesterol diet, effectively improve intestinal homeostasis, enrich and increase the diversity and uniformity of intestinal flora, and effectively improve the composition of intestinal flora at both the phylum and genus levels. Therefore, it can be used for the prevention of intestinal flora imbalance. Attached Figure Description

[0023] Figure 1 This figure shows a comparison of the Pielou, Chao1, Simpson, and Shanon indices of mice in each experimental group in the experimental case. The p-values ​​in the figure are based on the Welch t-test. p < 0.05 was considered statistically significant (*), p < 0.01 was considered highly statistically significant (**), and ns indicated no statistically significant difference. Data were corrected for FDR and expressed as p-values. Data are expressed as mean ± standard deviation (n = 12).

[0024] Figure 2 The image shows the NMDS analysis of mice in each experimental group in the experimental case.

[0025] Figure 3 Phylogenetic analysis of mouse gut microbiota at the phylum level in the experimental case (n=12).

[0026] Figure 4This is a comparative analysis of the gut microbiota phylum levels in the experimental groups of mice. In the figure, A: a stacked diagram of phylum-level structures; B: analysis of variance of the Firmicutes / Bacteroidetes (F / B) ratio; CF: analysis of differences in dominant microbiota at the four functional phyla. p-values ​​were based on Welch's t-test. p < 0.05 was considered statistically significant (*), and p < 0.01 was considered highly statistically significant (**). Data were corrected for FDR and expressed as p-values. ns indicates no statistically significant difference. Data are expressed as mean ± standard deviation (n = 12).

[0027] Figure 5 This figure shows a comparative analysis of the gut microbiota at the genus level among the experimental groups of mice in the experimental case. In the figure, A: Analysis of differences in the dominant phylum-level bacteria Akkermansia; analysis of differences in the dominant phylum-level bacteria Lachnospiraceae_NK4A136_group. p-values ​​were based on Welch's t-test. p < 0.05 was considered statistically significant (*), and p < 0.01 was considered highly statistically significant (**). Data were corrected for FDR and expressed as p-values. ns indicates no statistically significant difference. Data are expressed as mean ± standard deviation (n = 12). Detailed Implementation

[0028] The present invention will be further described in detail below with reference to specific embodiments.

[0029] Example 1: Preparation of capsules containing traditional Chinese medicine composition

[0030] The raw material formula is as follows: Scutellaria baicalensis 128g, Bupleurum chinense 128g, Rheum palmatum 120g, Citrus aurantium 128g, Artemisia capillaris 128g, Polygonum cuspidatum 200g, Gardenia jasminoides 150g, Lysimachia christinae 250g, Paeonia lactiflora 128g, Aucklandia lappa 128g, Pinellia ternata 90g, and Zingiber officinale 40g.

[0031] Preparation process:

[0032] A. Weigh out ginger and Pinellia ternata, grind them into fine powder, sterilize by 60Co irradiation, and set aside;

[0033] B. Weigh out the bitter orange peel and fresh ginger, add 7 times the amount of water, extract the volatile oil for 10 hours, collect and separate the volatile oil; the distilled aqueous solution is for later use.

[0034] C. Weigh out Scutellaria baicalensis, Paeonia lactiflora, Artemisia capillaris, and Gardenia jasminoides. Add water and decoct three times. The first extraction takes 2 hours, and the second and third extractions take 1.5 hours each time. Add 9 times the amount of water each time. Filter the extract and combine it with the volatile oil-water extract obtained in step B. Concentrate under reduced pressure to a relative density of 1.25±0.05 (60℃) to obtain an extract for later use.

[0035] D. Weigh out Bupleurum, Aucklandia, Rhubarb, Polygonum cuspidatum, and Lysimachia christinae. Extract them three times with 70% ethanol. For the first extraction, add 12 times the amount of ethanol and extract for 2.5 hours. For the second and third extractions, add 10 times the amount of ethanol and extract for 2 hours each. Filter the extract, concentrate it into a clear paste, combine it with the water extract obtained in step C, mix well, dry it, and pulverize it for later use.

[0036] E. Mix the fine powder obtained in step A and the extract powder obtained in step D. Adsorb the volatile oil obtained in step B with silica and mix well. Then, fill the mixture into capsules.

[0037] Example 2: Preparation of capsules containing traditional Chinese medicine composition

[0038] The raw material formula is as follows: Scutellaria baicalensis 137g, Bupleurum chinense 137g, Rheum palmatum 103g, Citrus aurantium 137g, Artemisia capillaris 137g, Polygonum cuspidatum 171g, Gardenia jasminoides 137g, Lysimachia christinae 342g, Paeonia lactiflora 137g, Aucklandia lappa 137g, Pinellia ternata 103g, and Zingiber officinale 34g.

[0039] Preparation process:

[0040] A. Weigh out ginger and Pinellia ternata, grind them into fine powder, sterilize by 60Co irradiation, and set aside;

[0041] B. Weigh out the bitter orange peel and fresh ginger, add 9 times the amount of water, extract the volatile oil for 12 hours, collect and separate the volatile oil; the distilled aqueous solution is for later use.

[0042] C. Weigh out Scutellaria baicalensis, Paeonia lactiflora, Artemisia capillaris, and Gardenia jasminoides. Add water and decoct 14 times. The first extraction takes 13 hours, and the second and third extractions take 11 hours each. Add 110 times the amount of water each time. Filter the extract and combine it with the volatile oil-water extract obtained in step B. Concentrate under reduced pressure to obtain an extract with a relative density of 1.25±0.05 (60℃) for later use.

[0043] D. Weigh out Bupleurum, Aucklandia, Rhubarb, Polygonum cuspidatum, and Lysimachia christinae. Extract them three times with 80% ethanol. For the first extraction, add 12 times the amount of ethanol and extract for 2 hours. For the second and third extractions, add 10 times the amount of ethanol and extract for 2 hours each. Filter the extract, concentrate it into a clear paste, combine it with the water extract obtained in step C, mix well, dry it, and pulverize it for later use.

[0044] E. Mix the fine powder obtained in step A and the extract powder obtained in step D, dry them, mix them with the volatile oil obtained in step B, and then fill them into capsules.

[0045] Example 3: Preparation of the Traditional Chinese Medicine Composition

[0046] Raw material formula: Scutellaria baicalensis 150g, Bupleurum chinense 70g, Rheum palmatum 90g, Citrus aurantium 90g, Artemisia capillaris 150g, Polygonum cuspidatum 100g, Gardenia jasminoides 110g, Lysimachia christinae 500g, Paeonia lactiflora 80g, Aucklandia lappa 200g, Pinellia ternata 110g, Zingiber officinale 20g.

[0047] Preparation process:

[0048] A. Weigh out ginger and Pinellia ternata, grind them into fine powder, sterilize by 60Co irradiation, and set aside;

[0049] B. Weigh out the bitter orange peel and ginger, add 5-9 times the amount of water, extract the volatile oil for 12 hours, collect and separate the volatile oil; the distilled aqueous solution is for later use.

[0050] C. Weigh out Scutellaria baicalensis, Paeonia lactiflora, Artemisia capillaris, and Gardenia jasminoides. Add water and decoct twice. Extract for 3 hours the first time, and for 3 hours the second and third times respectively. Add 7 times the amount of water each time. Filter the extract and combine it with the volatile oil-water extract obtained in step B. Concentrate under reduced pressure to a relative density of 1.25±0.05 (60℃) to obtain an extract for later use.

[0051] D. Weigh out Bupleurum, Aucklandia, Rhubarb, Polygonum cuspidatum, and Lysimachia christinae. Extract twice with 80% ethanol. For the first extraction, add 14 times the amount of ethanol and extract for 2 hours. For the second and third extractions, add 12 times the amount of ethanol and extract for 2 hours each. Filter the extract, concentrate it into a clear paste, combine it with the water extract obtained in step C, mix well, dry, and pulverize for later use.

[0052] E. The fine powder obtained in step A, the volatile oil obtained in step B, and the dried powder obtained in step D together constitute the active components of the pharmaceutical composition of the present invention.

[0053] Example 4: Preparation of Traditional Chinese Medicine Composition Tablets

[0054] Raw material formula: Scutellaria baicalensis 69g, Bupleurum chinense 205g, Rheum palmatum 52g, Citrus aurantium 205g, Artemisia capillaris 69g, Polygonum cuspidatum 255g, Gardenia jasminoides 69g, Lysimachia christinae 515g, Paeonia lactiflora 69g, Aucklandia lappa 205g, Pinellia ternata 52g, Zingiber officinale 17-52g.

[0055] Preparation process:

[0056] A. Weigh out Pinellia ternata, grind it into a fine powder, sterilize it by 60Co irradiation, and set aside for later use;

[0057] B. Weigh out the bitter orange peel and ginger, add 5 times the amount of water, extract the volatile oil for 10 hours, collect and separate the volatile oil; the distilled aqueous solution is for later use.

[0058] C. Weigh out Scutellaria baicalensis, Paeonia lactiflora, Artemisia capillaris, and Gardenia jasminoides. Add water and decoct 4 times. The first extraction takes 2 hours, and the second and third extractions take 1 hour each. Add 10 times the amount of water each time. Filter the extract and combine it with the volatile oil-water extract obtained in step B. Concentrate under reduced pressure to a relative density of 1.25±0.05 (60℃) to obtain an extract for later use.

[0059] D. Weigh out Bupleurum, Aucklandia, Rhubarb, Polygonum cuspidatum, and Lysimachia christinae. Extract them three times with 60% ethanol. For the first extraction, add 10 times the amount of ethanol and extract for 3 hours. For the second and third extractions, add 8 times the amount of ethanol and extract for 2 hours each. Filter the extract, concentrate it into a clear paste, combine it with the water extract obtained in step C, mix well, dry it, and pulverize it for later use.

[0060] E. Mix the fine powder obtained in step A and the extract powder obtained in step D, dry them, mix them with the volatile oil obtained in step B, and make them into tablets according to conventional methods.

[0061] Example 5: Preparation of Traditional Chinese Medicine Composition Granules

[0062] Raw material formula: Scutellaria baicalensis 150g, Bupleurum chinense 150g, Rheum palmatum 80g, Citrus aurantium 150g, Artemisia capillaris 90g, Polygonum cuspidatum 200g, Gardenia jasminoides 90g, Lysimachia christinae 400g, Paeonia lactiflora 90g, Aucklandia lappa 150g, Pinellia ternata 80g, Zingiber officinale 40g.

[0063] Preparation process:

[0064] A. Weigh out ginger and Pinellia ternata, grind them into fine powder, sterilize by 60Co irradiation, and set aside;

[0065] B. Weigh out the bitter orange peel and ginger, add 9 times the amount of water, extract the volatile oil for 10 hours, collect and separate the volatile oil; the distilled aqueous solution is for later use.

[0066] C. Weigh out Scutellaria baicalensis, Paeonia lactiflora, Artemisia capillaris, and Gardenia jasminoides. Add water and decoct 4 times. The first extraction takes 3 hours, and the second and third extractions take 1 hour each. Add 7 times the amount of water each time. Filter the extract and combine it with the volatile oil-water extract obtained in step B. Concentrate under reduced pressure to a relative density of 1.25±0.05 (60℃) to obtain an extract for later use.

[0067] D. Weigh out Bupleurum, Aucklandia, Rhubarb, Polygonum cuspidatum, and Lysimachia christinae. Extract twice with 80% ethanol. For the first extraction, add 10 times the amount of ethanol and extract for 2 hours. For the second and third extractions, add 10 times the amount of ethanol and extract for 1 hour each. Filter the extract, concentrate it into a clear paste, combine it with the water extract obtained in step C, mix well, dry, and pulverize for later use.

[0068] E. Mix the fine powder obtained in step A and the extract powder obtained in step D, dry them, mix them with the volatile oil obtained in step B, granulate and arrange them to obtain granules.

[0069] Experimental Example

[0070] The inventors conducted an experimental investigation into the effects of the traditional Chinese medicine composition of this application on the intestinal microbiota of mice.

[0071] 1 Experimental Institution

[0072] Hainan Provincial Institute for Drug Control (Safety Evaluation Research Center)

[0073] 2 Test samples, reference substances and other reagents

[0074] 2.1 Test samples

[0075] 2.1.1 Name: Traditional Chinese medicine composition of the present invention (prepared according to the formula and method provided in Example 1);

[0076] 2.1.2 Code: 22029DE-03;

[0077] 2.1.3 Source: Provided by Shijiazhuang Yiling Pharmaceutical Co., Ltd.;

[0078] 2.1.4 Specification: Each capsule contains 0.46 g (equivalent to 1.71 g of cut crude drugs);

[0079] 2.1.5 Batch number: A2112001;

[0080] 2.1.6 Appearance: The content of the hard capsule is brownish-yellow granules and powder, with a fragrant smell and a slightly bitter taste;

[0081] 2.1.7 Packaging: 0.46 g * 12 capsules * 3 boards / bag;

[0082] 2.1.8 Production date: December 27, 2021;

[0083] 2.1.9 Expiry date: November 2024;

[0084] 2.1.10 Storage conditions: Sealed;

[0085] 2.1.11 Quality inspection results: According to the finished product inspection report provided by the consignor (Report No.: BP Cheng 111 (Report) A2112001), the inspection items such as appearance, identification, inspection, and content determination of this batch of test samples all meet the requirements.

[0086] 3 Solvents for experiments

[0087] 3.1 Name: Sodium carboxymethylcellulose

[0088] 3.1. Let the source: Xilong Science Co., Ltd.;

[0089] 3.1.2 Specification: 250 g;

[0090] 3.1.3 Batch number: 2101110;

[0091] 3.1.4 Appearance: White or slightly yellowish fibrous powder, odorless and tasteless; [[ID=...]]

[0092] 3.1.5 Use: Prepared into 0.5% sodium carboxymethylcellulose solution as a solvent.

[0093] 4 Experimental systems and reasons for selection Note: There seems to be a minor error in the translation of "3.1. Let the source: Xilong Science Co., Ltd." in the original text, which should probably be "3.1. Source: Xilong Science Co., Ltd." This has been corrected in the translation for better understanding.

[0094] 4.1 Experimental system: Adult C57BL / 6J mice.

[0095] 4.2 Reason for selection: According to relevant literature, a diet containing 15% fat, 1.25% cholesterol and 0.5% bile acid can simulate a high-fat, high-cholesterol diet in humans.

[0096] 5. The strain, number, age, sex, weight range, origin, and grade of laboratory animals.

[0097] 5.1 Animal strain: C57BL / 6J mouse.

[0098] 5.2 Number of experimental animals: 150 animals are needed for the experiment, and 200 animals will be purchased.

[0099] 5.3 Sex of experimental animals: male.

[0100] 5.4 Age or weight of experimental animals: Purchased animals were approximately 7 weeks old and weighed 20-24g; at the start of the experiment, the animals were 8 weeks old and weighed 22-26g.

[0101] 5.5 Source of experimental animals: Purchased from Jiangsu Jicui Yaokang Biotechnology Co., Ltd., production license number SCXK(Su)2018-0008.

[0102] 5.6 Laboratory animal grade: SPF grade.

[0103] 5.7 Animal Quality Certificate No.: 320727230100015454.

[0104] 5.8 Handling of remaining animals: After the grouping was completed, the remaining 50 mice were used for training operations or other experimental projects.

[0105] 6. Reception and Quarantine of Laboratory Animals

[0106] The research project leader completed the "Application Form for Ethical Review of Laboratory Animal Welfare." After review by members of the Laboratory Animal Management and Use Committee (IACUC), and upon approval, the animals and feed were ordered and received according to the center's SOPs: "Ordering of Laboratory Animals and Feed," "Receiving and Placement of Laboratory Animals," and "Receiving, Storage, Issuance, and Use of Feed." The mice used in this experiment were placed in the laboratory on January 11, 2023, and underwent a 3-day quarantine period (from January 11 to January 13, 2023). During the quarantine period, the animals were observed daily, including: nutritional status, mental state, feed intake, limbs, feces, urine, fur, body surface, eyes, nose, mouth, anus, vulva, and any signs of death. These observations were recorded accurately. Animal weight was measured on the first and last days of quarantine. After passing quarantine, the mice could be used for experiments. The quarantine numbers for the mice used in this experiment ranged from 001 to 200. All mice passed quarantine and were deemed safe for use in experiments.

[0107] 7. Methods for identifying laboratory animals

[0108] According to the research center's SOP "Animal Marking and Group Numbering," the cages were marked, and labels were affixed to the cages indicating the topic code, animal species, cage number, animal number, and experiment date. After mice entered the quarantine room, their tails were marked with an oil-based marker, using numbers such as 001, 002, ..., 200 to represent the initial quarantine number. The markings should be clear and not easily confused; if blurred, they should be remarked promptly. For formal experiments, animal numbers consist of the group, sex, cage number, and animal number per cage. Groups are represented and recorded as I, II, III, etc. Each group's cage number is recorded as 01, 02, 03...36, and so on. Females are represented as F, and males as M. This experiment consisted of 5 groups: normal control group (CK), model control group (LD), low-dose test product group (LD+CH-L), medium-dose test product group (LD+CH-M), and high-dose test product group (LD+CH-H), with 30 animals in each group. The experimental groups and animal numbers are shown in Table 1.

[0109] Table 1. Experimental Groups and Corresponding Cage Numbers and Animal Numbers

[0110]

[0111]

[0112] 8. Environmental conditions for the husbandry and management of laboratory animals

[0113] 8.1 Animal Rearing Room: The animal laboratory of the research center, with the experimental animal use license number: SYXK(Qiong)2021-0009. During the quarantine period, it was reared in the quarantine isolation room in the barrier area from January 11, 2023 to January 13, 2023; during the experiment period, it was reared in Laboratory 1 in the barrier area from January 17, 2023 to March 13, 2023. According to the requirements of "National Standard of the People's Republic of China: Laboratory Animal Environment and Facilities" (GB 14925-2010): The temperature requirement is 20-26°C, and it is set at 20-26°C (the actual temperature ranges in the quarantine isolation room and Laboratory 1 in the barrier area are 21.8-24.2°C and 20.3-24.5°C respectively), the daily temperature difference ≤ 4°C, the humidity is 40-70% (the actual humidity ranges in the quarantine isolation room and Laboratory 1 in the barrier area are 54.9-61.5% and 52.7-67.4% respectively), the air change rate requirement ≥ 15 times / h, the animal illumination is 15-20 lx, and the lighting time is 12h / 12h, with alternating light and darkness. The temperature, relative humidity, and pressure in the animal laboratory are automatically recorded, once every hour. In addition, for the indicators such as temperature, relative humidity, pressure, illuminance, noise, air velocity, air change rate, dust particles, and airborne bacteria count in the animal laboratory, according to the requirements of GB 14925-2010, a qualified unit is entrusted to monitor once a year, and the results all meet the requirements of the corresponding environmental grade.

[0114] 8.2 Environmental Grade: Barrier system (SPF level).

[0115] 8.3 Cages: Composed of a cage cover and a cage rearing box. The cage cover is made of stainless steel, and the cage rearing box is a CP-3 type transparent plastic mouse cage. The cage cover is replaced once a month, the rearing box is replaced every Friday, and the bedding is replaced on Mondays, Wednesdays, and Fridays every week, in accordance with the research center's SOP "Replacement of bedding, bedding trays, and cages". The replaced rearing boxes and cage covers are cleaned, stored, and sterilized in accordance with the center's SOP "Cleaning, storage, and sterilization of cages".

[0116] 8.4 Bedding: Corn cob is used as bedding and is sterilized by high temperature and high pressure. The research center entrusts a qualified unit every year to detect heavy metals Pb, microorganisms, and aflatoxin B1, and they all meet the relevant regulations.

[0117] 8.5 Feed: High-fat and high-cholesterol feed (containing 15% fat, 1.25% cholesterol, and 0.5% cholic acid).

[0118] 8.5.1 Source: Guangdong Medical Laboratory Animal Center (Guangzhou, China).

[0119] 8.5.2 Batch Number: 20221133.

[0120] 8.5.3 Shelf Life: Nine months.

[0121] 8.5.4 Production date: 2022.11.24.

[0122] 8.5.5 Valid until: August 23, 2023.

[0123] 8.5.6 Production License No.: Yue Feed Certificate (2019) 05073.

[0124] 8.6 Drinking Water: Sterilized tap water is provided for animals to drink freely. Water bottles are changed daily, and the bottles are cleaned and reused after each use. The process follows the research center's SOP "Bottling, Sterilization, and Testing of Drinking Water," and the water undergoes high-temperature and high-pressure sterilization before use. The research center sends drinking water samples annually to a qualified institution for physicochemical and microbiological testing according to the "Standard Examination Methods for Drinking Water" (GB / T 5750-2006). All results meet the limits set by the "Standards for Drinking Water Quality" (GB 5749-2006).

[0125] 8.7 Husbandry: Five animals are housed per cage, in accordance with the requirements of "Laboratory Animal Environment and Facilities" (GB14925-2010). During quarantine, standby observation and experimentation, animals are fed once daily according to the center's SOP "Husbandry of Mice and Rats".

[0126] 9 Experimental Methods

[0127] 9.1 Grouping and Dosage Design

[0128] 9.1.1 Animal Grouping

[0129] This experiment consisted of 5 groups: normal control group (CK), model control group (LD), low-dose test product group (LD+CH-L), medium-dose test product group (LD+CH-M), and high-dose test product group (LD+CH-H). 150 qualified mice were randomly divided into the above 5 groups according to their body weight, with 30 mice in each group. The experimental groups and animal numbers are shown in Table 1.

[0130] Normal control group: fed standard mouse growth and reproduction diet and administered solvent by gavage for 8 weeks;

[0131] LD group: fed a high-fat, high-cholesterol diet and administered solvent via gavage for 8 weeks;

[0132] LD+CH-L group (0.345g powder / kg): fed a high-fat, high-cholesterol diet and administered a low dose of the test product by gavage for 8 weeks;

[0133] LD+CH-M group (0.69g powder / kg): fed a high-fat, high-cholesterol diet and administered a medium dose of the test product by gavage for 8 weeks;

[0134] LD+CH-H group (1.38g powder / kg): fed a high-fat, high-cholesterol diet and administered a high dose of the test product via gavage for 8 weeks; 9.1.2 Dosage design and basis

[0135] 9.1.2.1 Test sample dosage design

[0136] Based on the clinical usage and dosage of the traditional Chinese medicine composition in this application and the previous pharmacodynamic test data, the low, medium and high dose groups in this experiment are consistent with the previous pharmacodynamic doses, with the dosages being 1.282, 2.566 and 5.132 g crude drug / kg (including the dosage of the preparation being 0.345, 0.69 and 1.38 g powder / kg, which are equivalent to 5, 10 and 20 times the clinical dose, respectively).

[0137] 9.2 Drug Preparation

[0138] 9.2.1 Preparation of the test sample

[0139] High dose of test sample: Weigh 4.14g of drug powder, add 0.5% sodium carboxymethyl cellulose solution and stir well to prepare 30ml of high dose test sample solution with a final concentration of 0.138g / ml. Place the prepared solution in a clean preparation bottle.

[0140] Medium dose of test sample: Measure 15 ml of the high dose of test sample solution (final concentration of 0.138 g / ml), and after measuring, add 15 ml of 0.5% sodium carboxymethyl cellulose solution to dilute to a final concentration of 0.069 g / ml. Place the prepared solution in a clean preparation bottle.

[0141] Low-dose test sample: Measure 15 ml of the medium-dose test sample solution (final concentration 0.069 g / ml), add 15 ml of 0.5% sodium carboxymethyl cellulose solution to dilute to a final concentration of 0.0345 g / ml, and place the prepared solution in a clean preparation bottle.

[0142] Each time, the sample is taken according to the required amount, and it is prepared and mixed in the clean bench before use.

[0143] 9.2.2 Preparation of 0.5% sodium carboxymethyl cellulose solution

[0144] Weigh 1g of sodium carboxymethyl cellulose into a 500ml clean beaker. Add 200ml of sterile water to the beaker using a graduated cylinder, and stir thoroughly to prepare a 0.5% sodium carboxymethyl cellulose solution. Then transfer the prepared solution to a clean dispensing bottle.

[0145] 9.3 Administration Method

[0146] The normal control group was fed standard mouse feed, while the model control group and the low, medium, and high dose groups of the test substance were fed a high-fat, high-cholesterol diet. All animals had normal access to water. Administration was performed via gavage, once daily for 8 consecutive weeks. The normal and model control groups received a 0.5% sodium carboxymethyl cellulose solution, while the low, medium, and high dose groups received solutions of different concentrations of the test substance. The gavage volume per mouse was 0.1 ml / 10g (10 ml / kg).

[0147] 10. Inspection items, methods, frequency, and result judgment

[0148] 10.1 Clinical Observation

[0149] During the trial, the animals were observed for general clinical symptoms at least once a day, and their health status was observed and recorded.

[0150] 10.2 Weight Record

[0151] The weight of all mice was recorded before the experiment began. The weight of all mice was measured weekly, and the trends in weight changes were observed and recorded. Finally, a trend graph was generated for analysis.

[0152] 10.3 Specimen Collection

[0153] All mice were harvested 24 hours after the last administration of the drug at the end of the eighth week of the experiment.

[0154] 10.4 Collection of feces

[0155] After collecting blood from the orbital venous plexus of mice, the mice were euthanized by neck dislocation. The mice were dissected in a sterile operating table, and the intestinal contents were collected in sterile EP tubes. The intestines were flushed with 2 ml of physiological saline, and the contents of the cecum were collected and centrifuged at 12,000 rpm for 5 min. The precipitate was the fecal sample, which was stored at -80℃ for later use.

[0156] 10.5 16S rRNA sequencing and gut microbiota analysis

[0157] 10.5.1 Sample DNA Extraction

[0158] Genomic DNA extraction of intestinal microbiota from mice in each experimental group was performed according to the instructions of the TIANamp Bacteria DNA Kit. Buffer GD and wash buffer PW were prepared using anhydrous ethanol. After resuspending the bacterial culture in 200 μl of buffer GA, 20 μl of proteinase K solution was added and mixed well, followed by 220 μl of buffer GB. The mixture was shaken for 15 seconds and incubated at 70°C for 10 minutes. Once the solution was clear, it was briefly centrifuged to allow water droplets to collect at the bottom of the tube. Then, 220 μl of anhydrous ethanol was added, and the mixture was shaken thoroughly for 15 seconds to ensure complete mixing. The above solution and precipitate were collected in adsorption column CB3, centrifuged at 12,000 rpm for 30 s, the supernatant was discarded, and 500 μl of buffer GD was added. After thorough mixing, the mixture was centrifuged at 12,000 rpm for 30 s. After discarding the supernatant, 600 μl of wash buffer PW was added, and the mixture was centrifuged at 12,000 rpm for 30 s. The supernatant was discarded, and the washing process was repeated twice. The remaining wash buffer was allowed to air dry at room temperature before the next step. The adsorption column CB3 was transferred to a centrifuge tube, and 200 μl of elution buffer TE was added dropwise to the adsorption membrane. After incubation at room temperature for 5 min, the mixture was centrifuged at 12,000 rpm for 2 min. The supernatant was collected and used for Illumina sequencing.

[0159] 10.5.2 Illumina Sequencing and Data Analysis

[0160] 10.5.2.1 Sequencing Data Quality Assessment

[0161] The original data was concatenated using FLASH (version 1.2.11), the resulting sequence was quality filtered using Trimmomatic (version 0.33), and chimeras were removed using UCHIME (version 8.1) to obtain a quality Tags sequence.

[0162] 10.5.2.2 OTU Analysis

[0163] The tags were clustered using the USEARCH (version 10.0) platform with a similarity level of 97%, and OTUs were filtered out using 0.005% of the total number of sequences sequenced.

[0164] 10.5.2.3 Species Composition Analysis

[0165] Microbial species are generally classified into seven levels: kingdom, phylum, class, order, family, genus, and species. Each OTU / ASV represents a set of species at a certain classification level. Therefore, species annotation based on OTU / ASV sequence information can correlate analytical results with actual biological significance, thereby enabling the study of species variation relationships within a community.

[0166] 10.5.2.4 Indicator Species Analysis

[0167] Indicator species, or biomarkers, are species that indicate characteristics such as grouping. Simply put, for example, in a disease group and a healthy group, if a certain species is found to be significantly enriched in the disease group, then that species is considered a potential indicator species for disease detection.

[0168] 10.5.2.5 Diversity Analysis

[0169] The software used for Alpha diversity analysis is Mothur (version v.1.30), which is commonly used to evaluate Alpha diversity. The indexes include the Chao abundance index, the Shannon diversity index, and the Simpson diversity index. The Chao abundance index is positively correlated with bacterial abundance, the Shannon diversity index is positively correlated with bacterial diversity, and the Simpson diversity index is negatively correlated with bacterial diversity and stability.

[0170] The dilution curve can evaluate whether the sequencing depth covers all taxa and indirectly reflects the species richness of the sample. When the curve approaches a flat point or reaches a stable level, it can be considered that the sequencing depth basically covers the species contained in the sample; conversely, it indicates that there are still many undetected species in the sample.

[0171] Beta diversity analysis was conducted using the R language platform to generate principal coordinate analysis (PCoA) and unweighted pair-group method with arithmetic mean (UPGMA) plots. The PCoA plot identifies the most significant coordinates in the distance matrix, allowing observation of differences between sample groups. The unweighted unifrac algorithm was used to calculate the distances between samples.

[0172] 10.5.2.6 PICRUSt2 Community Function Prediction

[0173] PICRUSt2 first correlates the 16S rRNA sequences of prokaryotes in the KEGG database with the 16S rRNA sequences in the SILVA database. Then, it breaks down the existing prokaryotic genomes in the KEGG database and uses UProC to count the KO sequences of all genomes. Finally, it corrects the number of species using the 16S copy number and performs KEGG prediction and KO abundance statistics.

[0174] 11 Data Statistical Processing Methods

[0175] Data are expressed as mean ± standard deviation (SD). Data processing was performed using GraphPad Prism (version 8.0). One-way ANOVA was used to analyze the data. Duncan's multiple comparison test was used to determine significance; P < 0.05 was considered significant, and P < 0.01 was considered highly significant. In the multiple comparison analysis of 16S rRNA data, the q-value was used to represent the corrected false positive error of the FDR detection results, and a q-value < 0.1 was considered significant.

[0176] 12 Experimental Materials and Methods

[0177] 12.1 Reagents and Instruments

[0178] Table 2. Main Instruments and Equipment Used in the Experiment

[0179]

[0180]

[0181] Table 3. Main reagents used in the experiment

[0182]

[0183]

[0184]

[0185] 12.2 Experimental Methods

[0186] 12.2.1 16S rRNA sequencing

[0187] Sample DNA extraction: The extraction of genomic DNA from the mouse gut microbiota was performed according to the instructions of the TIANamp Bacteria DNA Kit.

[0188] (1) Prepare buffer GD and wash buffer PW with anhydrous ethanol according to the kit instructions.

[0189] (2) Add 200 μl of buffer GA to the sample to resuspend the bacterial culture, then add 20 μl of proteinase K solution and mix well. Then add 220 μl of buffer GB, shake for 15 s, and incubate in a 70°C water bath for 10 min. After the solution is clear, centrifuge slightly to allow water droplets to collect at the bottom of the tube wall and cap. Then add 220 μl of anhydrous ethanol and shake thoroughly for 15 s to mix the solution thoroughly.

[0190] (3) Collect the above solution and precipitate in the adsorption column CB3, centrifuge at 12000 rpm for 30 s, discard the supernatant, add 500 μl of buffer GD, mix thoroughly, centrifuge at 12000 rpm for 30 s, discard the supernatant, add 600 μl of washing buffer PW, centrifuge at 12000 rpm for 30 s, discard the supernatant, repeat the washing process twice, and air dry the remaining washing buffer at room temperature before the next step.

[0191] The 16S rRNA V3+V4 region was amplified using primers 806R (CCTAYGGGRBGCASCAG) and (GGACTACNNGGGTATCTAAT) with primer 341. DNA was purified using a DNA extraction kit according to the manufacturer's instructions and quantified using an ABI Step OnePlus real-time PCR system. The purified amplicon was sequenced on an Illumina platform in PE-250 mode on a Hiseq 2500 (CapitalBio Technology Co., Ltd., Beijing, China). The raw data was spliced ​​using FLASH (version 1.2.11), and the resulting sequences were quality filtered using Trimmomatic (version 0.33) and chimeras were removed using UCHIME (version 8.1) to obtain high-quality tag sequences.

[0192] 13 Experimental Results and Analysis

[0193] 13.1 The Influence of General Animal Condition

[0194] During the experiment, mice in the normal control group, model control group, low-dose test product group, medium-dose test product group, and high-dose test product group showed good general condition in terms of appearance, signs, behavior, fur, glandular secretion, respiration, and fecal characteristics. No animals died, and no significant differences were observed.

[0195] 13.2 Effects on animal body weight

[0196] Mice body weight was recorded weekly during the experiment. C57BL / 6 mice fed with LD showed weight loss compared to CK. At week 8, mice in the test drug group showed weight gain compared to LD. The results showed that the body weight of LD-fed C57BL / 6 mice was significantly lower than that of C57BL / 6 mice fed a normal diet (CK). This LD-induced weight loss was reversed by administration of the herbal composition of this application.

[0197] 13.3 Alpha and Beta diversity analysis (impact on mouse gut microbiota diversity)

[0198] Alpha diversity refers to the diversity within a specific environment or ecosystem, primarily reflecting species richness, evenness, and sequencing depth. Alpha diversity is mainly reflected in richness and evenness using indices such as Chao1, Shannon, Simpson, and Pielou. Beta diversity refers to the species diversity between different environmental communities, which can be represented by non-multidimensional scaling (NMDS). Beta diversity, together with alpha diversity, constitutes overall diversity or the biological heterogeneity of a given environmental community.

[0199] This study used 16S rRNA gene sequencing technology to evaluate the effect of the traditional Chinese medicine composition of this application on the α-diversity of gut microbiota in mice fed a high-fat, high-cholesterol diet.

[0200] like Figure 1 As shown, after eight weeks of administration, the Pielou, Chao1, Simpson, and Shanon indices of CK mice were significantly higher than those of LD mice (p < 0.01, q = 0.000). Compared to the LD group, except for the Chao1 index in the LD+CH-L group, the α-diversity index of the gut microbiota in all other dosage groups was significantly increased (p < 0.01, q = 0.000). Chao1 mainly estimates the number of species in the community. Simpson index: one of the indices used to estimate microbial diversity in a sample; the larger the index value, the lower the community diversity. Shannon index is derived from information entropy; the larger the Shannon index, the greater the uncertainty. The greater the uncertainty, the more unknown factors there are in the community. The Pielou-e index only reflects evenness; the larger the value, the more even the community. Therefore, this indicates that after eight weeks of ingestion of the herbal composition of this application, the intestinal homeostasis of mice can be effectively improved, and diversity and evenness can be enriched and increased.

[0201] Nonmetric Multidimensional Scaling (NMDS), like traditional PCoA, is a ranking method based on a distance matrix of samples (any type of distance). Unlike PCoA, NMDS does not rely on numerical distance matrix values ​​but instead performs dimensionality reduction calculations based on distance ranking. NMDS ranking depends on the magnitude of the dissimilarity coefficients, not on the exact values ​​of those coefficients. Since the goal of ranking in this study is not to maximize the preservation of actual distances between samples, but only to reflect their ordering relationships, NMDS is suitable for Beta diversity analysis. The objective of NMDS analysis is to maintain the sample ranking relationships; therefore, if two samples are close together, it indicates a more similar species composition. In the figure, points represent samples, different colored samples belong to different groups, and the distance between points represents the degree of difference between samples. The quality of NMDS analysis results is measured by the stress coefficient. Generally, a stress value < 0.2 is considered acceptable for a two-dimensional NMDS plot, and the graph has some interpretive value; a stress value < 0.1 is considered a good ranking; and a stress value < 0.05 indicates good representativeness. Figure 2 As shown, in the NMDS analysis of this study, there were good sample differences among CK, LD, LD+CH-L, LD+CH-M, and LD+CH-H (P = 0.001). Furthermore, Stress = 0.07 indicates that the differences in bacterial communities among the groups were significant and representative of the sample groups.

[0202] 13.4 Phylogenetic analysis of mouse gut microbiota at the phylum level

[0203] In microbial ecology research, it is often necessary to study the phylogenetic relationships among microorganisms in a specific ecosystem (environment). The basic principle of sequence evolution is that the more transformations required to convert one sequence into another, the weaker the correlation between the two sequences, the earlier they diverged from a common ancestor, and the greater the evolutionary distance between them. For example... Figure 3 As shown, the top 50 species by abundance are selected for plotting. Different branches in the figure represent different genera. Different genera but the same color indicate that they belong to the same phylum. The closer two species are, the closer their evolutionary relationship is. This allows for a direct observation of the genetic relationships and biological significance of key species.

[0204] Analysis of Gut Microbiota Composition and Abundance in Mice at the Phylum Level (13.5)

[0205] Literature reports indicate that Firmicutes and Bacteroidota have long been considered the dominant species in the gut microbiota, and the Firmicutes / Bacteroidota ratio (F / B) is closely related to the occurrence of diseases.

[0206] like Figure 4 As shown in -A, at the phylum level, the top 6 most abundant phyla in the mouse gut microbiota are Verrucomicrobiota, Firmicutes, Desulfobacterota, Bacteroidota, Proteobacteria, and Actinobacteriota. Verrucomicrobiota was the most abundant bacterial phylum in the gut of LD group mice.

[0207] like Figure 4 As shown in Figure -B, the F / B ratio in the CK group was significantly lower than that in the LD group, indicating that the proportion of harmful bacteria in the intestinal flora of mice increased after consuming a high-fat, high-cholesterol diet (p < 0.01, q = 0.000). The F / B ratios of the test samples LD+CH-M and LD+CH-H were lower than those in the LD group, and the dosage was negatively correlated with the F / B ratio in mice, indicating that the intestinal microecology of mice was improved after ingestion of the traditional Chinese medicine composition of this application.

[0208] like Figure 4 As shown in -C, compared with the LD group, the abundance of Verrucomicrobiota in the test sample administration groups LD+CH-L, LD+CH-M and LD+CH-H was significantly reduced, comparable to that in the CK group mice (p<0.01, q=0.000).

[0209] like Figure 4 As shown in Figure D, the abundance of Firmicutes in the CK group was significantly higher than that in the LD group (p < 0.01, q = 0.000). LD+CH-L, LD+CH-M and LD+CH-H all significantly increased the abundance of Firmicutes in the mouse cecum (p < 0.05, q = 0.000).

[0210] like Figure 4 As shown in Figure E, the abundance of Bacteroidota in the cecum of mice in the LD group was significantly lower than that in the CK group (p < 0.01, q = 0.000), while the abundance of Bacteroidota in the LD+CH-L, LD+CH-M and LD+CH-H groups was higher than that in the LD group.

[0211] like Figure 4As shown in Figure F, the LD group significantly reduced the level of Cyanobacteria in the cecum of mice (p < 0.05, q = 0.02), while the LD+CH-M and LD+CH-H groups significantly increased the level of Cyanobacteria in the cecum of mice (p < 0.01, q = 0.000, q = 0.003).

[0212] Analysis of Gut Microbiota Composition and Abundance in Mice at the Genus Level (13.6)

[0213] Distribution of gut microbiota at the genus level in mice of each experimental group as follows: Figure 5 As shown in the diagram, the stacked map only displays the top five abundance species. Sequencing results show that the top five abundance species are Akkermansia, Desulfovibrionaceae, Lachnospiraceae_NK4A136_group, Muribauculaceae, and Clostridiales.

[0214] Akkermansia is a mucin-degrading bacterium belonging to the phylum Verrucomicrobia. Studies have shown that Akkermansia increases intestinal permeability in mice, leading to impaired mucus protection, increased bacterial adhesion, and an increased inflammatory microbiota. Repeated gavage administration of Akkermansia can increase the severity of colitis in mice. A high-fat diet increases Akkermansia abundance, thereby affecting intestinal epithelial integrity and permeability.

[0215] In this study, such as Figure 5 As shown in -A, the abundance of Akkermansia in the LD group mice was significantly higher than that in the CK group. The abundance of Akkermansia in the LD+CH-L, LD+CH-M and LD+CH-H groups was significantly lower than that in the LD group (p<0.01, q=0.000), similar to that in the CK group, and showed a concentration-dependent relationship.

[0216] Lachnospiraceae_NK4A136_group belongs to the Firmicutes phylum and is a beneficial bacterium that has a repairing effect on intestinal mucosal damage. Its content is reduced in intestinal-related diseases.

[0217] In this study, such as Figure 5 As shown in Figure -B, the Lachnospiraceae_NK4A136_group was enriched in the CK group and significantly higher than that in the LD group (p < 0.01, q = 0.018). The abundance of Lachnospiraceae_NK4A136_group in the intestines of mice in the LD+CH-L, LD+CH-M, and LD+CH-H groups was higher than that in the LD group and similar to that in the CK group.

[0218] In summary, the analysis of the intestinal flora status of mice on a high-fat, high-cholesterol diet in this study showed that the traditional Chinese medicine composition of this application can significantly increase the intestinal flora diversity index of mice on a high-fat, high-cholesterol diet, effectively improve intestinal homeostasis, and enrich and increase the diversity and uniformity of intestinal flora. The traditional Chinese medicine composition of this application significantly improved the intestinal microecology of mice at the phylum level and significantly improved the abundance of Akkermansia and Lachnospiraceae_NK4A136_group bacteria at the genus level.

Claims

1. The application of a traditional Chinese medicine composition in the preparation of a drug for preventing intestinal flora imbalance, characterized in that, The raw materials of the traditional Chinese medicine composition, by weight, are as follows: Scutellaria baicalensis 128-137 parts, Bupleurum chinense 128-137 parts, Rheum palmatum 103-120 parts, Citrus aurantium 128-137 parts, Artemisia capillaris 128-137 parts, Polygonum cuspidatum 171-200 parts, Gardenia jasminoides 137-150 parts, Lysimachia christinae 250-342 parts, Paeonia lactiflora 128-137 parts, Aucklandia lappa 128-137 parts, Pinellia ternata 90-103 parts, and Zingiber officinale 34-40 parts.

2. The application according to claim 1, characterized in that, The raw materials of the traditional Chinese medicine composition, by weight, are: 128 parts of Scutellaria baicalensis, 128 parts of Bupleurum chinense, 120 parts of Rheum palmatum, 128 parts of Citrus aurantium, 128 parts of Artemisia capillaris, 200 parts of Polygonum cuspidatum, 150 parts of Gardenia jasminoides, 250 parts of Lysimachia christinae, 128 parts of Paeonia lactiflora, 128 parts of Aucklandia lappa, 90 parts of Pinellia ternata, and 40 parts of Zingiber officinale.

3. The application according to claim 1, characterized in that, The raw materials of the traditional Chinese medicine composition, by weight, are as follows: 137 parts of Scutellaria baicalensis, 137 parts of Bupleurum chinense, 103 parts of Rheum palmatum, 137 parts of Citrus aurantium, 137 parts of Artemisia capillaris, 171 parts of Polygonum cuspidatum, 137 parts of Gardenia jasminoides, 342 parts of Lysimachia christinae, 137 parts of Paeonia lactiflora, 137 parts of Aucklandia lappa, 103 parts of Pinellia ternata, and 34 parts of Zingiber officinale.

4. The application according to claim 1, characterized in that, The preparation method of the traditional Chinese medicine composition includes the following steps: A. Weigh out ginger and Pinellia ternata, grind them into fine powder, sterilize by 60Co irradiation, and set aside; B. Weigh out the bitter orange peel and fresh ginger, add 5-9 times the amount of water, extract the volatile oil for 8-12 hours, collect and separate the volatile oil; the distilled aqueous solution is for later use. C. Weigh out Scutellaria baicalensis, Paeonia lactiflora, Artemisia capillaris, and Gardenia jasminoides. Add water and decoct 2-4 times. Extract for 1-3 hours for the first time, and for 1-3 hours for the second, third, and fourth times respectively. Add 7-10 times the amount of water each time. Filter the extract and combine it with the volatile oil-water extract obtained in step B. Concentrate under reduced pressure to a relative density of 1.25±0.05 at 60℃ for later use. D. Weigh out Bupleurum, Aucklandia, Rhubarb, Polygonum cuspidatum, and Lysimachia christinae. Extract with 60-80% ethanol 2-4 times. For the first extraction, add 10-14 times the amount of ethanol and extract for 2-4 hours. For the second, third, and fourth extractions, add 8-12 times the amount of ethanol and extract for 1-3 hours each time. Filter the extract, concentrate it into a clear paste, combine it with the water extract obtained in step C, mix well, dry, and pulverize for later use. E. The fine powder obtained in step A, the volatile oil obtained in step B, and the dried powder obtained in step D can be mixed together.

5. The application according to claim 1, characterized in that, The drug dosage forms prepared from the traditional Chinese medicine composition include capsules, tablets, pills, oral liquids, granules, or powders.

6. The application according to claim 1, characterized in that, The prevention of gut microbiota dysbiosis involves increasing the gut microbiota α-diversity index and / or improving the composition of gut microbiota at the phylum level and / or improving the composition of gut microbiota at the genus level.

7. The application according to claim 6, characterized in that, The α-diversity index is the Pielou index, and / or the Chao1 index, and / or the Simpson index, and / or the Shanon index.

8. The application according to claim 6, characterized in that, The improvement of the gut microbiota composition at the phylum level is achieved by reducing the F / B ratio in the gut, and / or increasing the abundance of Firmicutes bacteria, and / or increasing the abundance of Bacteroidota bacteria, and / or increasing the abundance of Cyanobacteria bacteria, and / or decreasing the abundance of Verrucomicrobiota bacteria.

9. The application according to claim 6, characterized in that, The improvement in gut microbiota composition at the genus level is achieved by reducing the abundance of the gut Akkermansia microbiota and / or increasing the abundance of the gut Lachnospiraceae_NK4A136_group microbiota.

10. The application according to claim 1, characterized in that, The gut microbiota imbalance mentioned refers to gut microbiota imbalance caused by a high-fat, high-cholesterol diet.

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