Extraction process method of functional gastrodia elata wine partner and application of functional gastrodia elata wine partner in alcoholic liver injury

Abstract

The invention discloses an extraction process method of a functional gastrodia elata wine partner and application of the functional gastrodia elata wine partner in alcoholic liver injury, and belongs to the technical field of biology. In order to improve the diversity of edible gastrodia elata products and solve the problems of long consumed time, low solubility, low leaching rate of active substances and the like of traditional gastrodia elata wine, the invention provides a new concept of gastrodia elata wine partners. Artificial intelligence and a response surface are combined, and optimal extraction process parameters are optimized and obtained as follows: the volume fraction of ethanol is 50%, the material-liquid ratio is 1: 20 g / mL, the ultrasonic time is 1.55 h, the ultrasonic temperature is 58 DEG C, and the ultrasonic power is 490 W; network pharmacology and molecular docking reveal that the gastrodia elata wine partner has a potential protection effect on alcoholic liver diseases; cell tests show that the gastrodia elata wine partner has a remarkable protection effect on HegG2 cells, and animal experiments further reveal that the gastrodia elata wine partner can effectively reduce the ethanol content of rat eye socket blood and has potential advantages in the aspects of reducing free radical damage and improving the oxidative stress state. The convenient edible product and the matching mode are expected to become beneficial supplement of the modern drinking culture, and the liver health is protected while people enjoy delicious wine.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of biotechnology, in particular to the extraction process of functional gastrodia elata wine companion and its application in alcoholic liver injury. BACKGROUND

[0002] Gastrodia elata is a kind of orchid herb, which is a native Chinese medicinal material with a long history of medicinal use. The medicinal value of gastrodia elata is also recorded in detail in the Chinese Pharmacopoeia, and its main effects include calming the nerves, anti-epilepsy, and anti-dizziness. Modern research shows that gastrodia elata is rich in active ingredients such as gastrodin and polysaccharides, and the Compendium of Materia Medica believes that gastrodia elata has the effect of calming the liver. However, the protective mechanism of gastrodia elata on the liver is rarely mentioned. In 2023, the Chinese government included gastrodia elata in the list of food and medicine materials, considering that it can be used as both a medicine and a health food, which has broad application prospects. In the traditional Chinese drinking culture, gastrodia elata tubers are often soaked in liquor to enhance the flavor and health benefits of the wine. However, the traditional soaking method has low efficiency and takes a long time, with a soaking time of about 3 months. The soaked gastrodia elata tubers cannot be eaten directly and are often discarded, leading to resource waste, and gastrodia elata ultra-fine powder is difficult to dissolve in wine. If the ultra-fine powder is directly added to the liquor, it will reduce the taste of drinking. To solve these problems, the present application proposes a new concept of "wine companion", hoping to add it to the liquor like a coffee companion, quickly dissolve it, improve the taste and health effects, and achieve efficient use of resources, and inject new vitality into the traditional drinking culture. However, to successfully develop the "wine companion", solving the solubility is the primary problem. Ultrasonic-assisted alcohol extraction has become a common method for extracting active ingredients from plants, but the extraction efficiency varies significantly for different plants. Therefore, exploring a method suitable for efficient extraction of alcohol-soluble active components from gastrodia elata is of great significance to solve the above problems.

[0003] Artificial intelligence is an interdisciplinary science that has had a significant impact on various fields in academia, mainly in methodological innovation, disciplinary application, and research process optimization. Back propagation (BP) neural networks have robust nonlinear fitting, self-learning, adaptability, and fault tolerance. Genetic algorithm (GA) is superior to traditional iterative methods, which can speed up the iteration and improve the iteration accuracy. The combination of BP neural networks and genetic algorithm has been applied in many fields. Alcoholic liver disease (ALD) is a liver disease caused by long-term or excessive alcohol consumption. ALD has become the disease with the highest incidence and mortality rate related to the liver. Long-term and excessive alcohol consumption can cause severe fatty degeneration of liver cells. There are few studies on Gastrodia elata for alcoholic liver disease, and the protective mechanism is not completely clear. The Gastrodia elata wine partner proposed in the present application is a Gastrodia elata ethanol extract, and the protective mechanism of the Gastrodia elata wine partner for alcoholic liver disease is even less. Network pharmacology is a research method that combines systems biology and multi-omics data analysis, focusing on using network biology methods to reveal the interactions between drugs, targets, and diseases, which can reveal the potential pharmacological effects of unknown components. Molecular docking can evaluate the binding affinity and drug-receptor interaction, which is of great significance for revealing the relevance and mechanism of the Gastrodia elata wine partner and alcoholic liver disease. SUMMARY

[0004] The purpose of the present application is to provide an extraction process of functional Gastrodia elata wine partner and its application in alcoholic liver injury, to solve the problems existing in the prior art, and to significantly alleviate alcoholic liver injury by using Gastrodia elata wine partner in conjunction with wine, providing a new method for enjoying wine while protecting liver health.

[0005] To achieve the above purpose, the present application provides the following solutions:

[0006] The present application provides the application of Gastrodia elata wine partner in any of the following:

[0007] (1) application in the preparation of products for improving ethanol metabolism rate;

[0008] (2) application in the preparation of products for relieving oxidative stress burden in the process of liver alcohol metabolism;

[0009] (3) application in the preparation of products for relieving alcoholic liver injury;

[0010] The Gastrodia elata wine partner is obtained by ultrasonic extraction of Gastrodia elata ultrafine powder in edible alcohol, filtration, concentration of the filtrate, and freeze-drying.

[0011] The above products include but are not limited to drugs and medicinal wine.

[0012] Preferably, the volume fraction of the edible alcohol is 50%, the solid-liquid ratio of the Gastrodia elata super-micro powder and the edible alcohol is 1g:20mL, and the Gastrodia elata super-micro powder is 80-mesh super-micro powder.

[0013] Preferably, the ultrasonic treatment is performed for 1.55h at 58℃ and with a power of 490W.

[0014] Preferably, the freeze-drying is performed at-60℃ for 48h.

[0015] Preferably, the Gastrodia elata wine partner improves the ethanol metabolism rate, relieves the oxidative stress burden in the liver alcohol metabolism process, or relieves alcoholic liver injury through the following usage modes: (1) used before drinking wine, or (2) used simultaneously with wine.

[0016] Preferably, the main active ingredients of the Gastrodia elata wine partner include barbessin A and β-sitosterol, which have a potential inhibitory effect on alcoholic liver injury.

[0017] The application further provides a Gastrodia elata wine partner, and the preparation method of the Gastrodia elata wine partner comprises the following steps: ultrasonic extraction of Gastrodia elata super-micro powder in edible alcohol with a volume fraction of 50%, filtration, freeze-drying of the concentrated filtrate, and the like.

[0018] Preferably, the solid-liquid ratio of the Gastrodia elata super-micro powder and the edible alcohol is 1g:20mL, and the Gastrodia elata super-micro powder is 80-mesh super-micro powder.

[0019] Preferably, the ultrasonic treatment is performed for 1.55h at 58℃ and with a power of 490W.

[0020] Preferably, the freeze-drying is performed at-60℃ for 48h.

[0021] The application discloses the following technical effects:

[0022] The application proposes a new concept of Gastrodia elata wine partner to improve the diversity of edible Gastrodia elata products and solve the problems of long consumption time, low solubility, and low active substance leaching rate of traditional Gastrodia elata wine.

[0023] The invention optimizes the extraction process of Gastrodia elata Blume to prepare the Gastrodia elata Blume wine partner, and the optimal extraction conditions are as follows: the volume fraction of ethanol is 50%, the solid-liquid ratio is 1:20 g / mL, the ultrasonic time is 1.55 h, the ultrasonic temperature is 58 DEG C, and the ultrasonic power is 490 W. Under the conditions, the content of gastrodin extracted from Gastrodia elata Blume is as high as 1503.739 mu g / g, and the extraction process is stable and reliable. The extract is used as a wine partner before drinking wine or at the same time with wine. Microscopic observation and oxidative stress reaction of cell test show that the Gastrodia elata Blume wine partner has a significant protective effect on HegG2 cells. Animal experiments further reveal that it can effectively reduce the ethanol content of rat orbital blood, and has potential advantages in reducing free radical damage and improving oxidative stress. This convenient edible product and collocation mode (Gastrodia elata Blume wine partner cooperates with wine) is expected to become a beneficial supplement to modern drinking culture, and protect liver health while enjoying wine. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0025] Figure 1 Gastrodia elata Blume ultrafine powder preparation and BP neural network optimization; A: fresh Gastrodia elata Blume, B: Gastrodia elata Blume slice, C: liquor partner sample, D: BP neural network structure diagram;

[0026] Figure 2 Gastrodia elata Blume wine partner ultrasonic extraction condition optimization results; A: solid-liquid ratio; B: ultrasonic time; C: ultrasonic temperature; D: ethanol volume fraction; E: ultrasonic power; F: gastrodin standard curve diagram;

[0027] Figure 3 Gastrodin standard HPLC diagram;

[0028] Figure 4 Liquor partner sample HPLC diagram;

[0029] Figure 5 Response surface diagram of the influence of alcohol volume fraction and solid-liquid ratio on the content of gastrodin;

[0030] Figure 6 Response surface diagram of the influence of alcohol volume fraction and ultrasonic time on the content of gastrodin;

[0031] Figure 7 Response surface diagram of the influence of alcohol volume fraction and ultrasonic temperature on the content of gastrodin;

[0032] Figure 8Response surface plot for the effect of ethanol volume fraction and ultrasonic power on the content of gastrodin;

[0033] Figure 9 Response surface plot for the effect of material liquid ratio and ultrasonic time on the content of gastrodin;

[0034] Figure 10 Response surface plot for the effect of material liquid ratio and ultrasonic temperature on the content of gastrodin;

[0035] Figure 11 Response surface plot for the effect of material liquid ratio and ultrasonic power on the content of gastrodin;

[0036] Figure 12 Response surface plot for the effect of ultrasonic time and ultrasonic temperature on the content of gastrodin;

[0037] Figure 13 Response surface plot for the effect of ultrasonic time and ultrasonic power on the content of gastrodin;

[0038] Figure 14 Response surface plot for the effect of ultrasonic temperature and ultrasonic power on the content of gastrodin;

[0039] Figure 15 GA-BP neural network related parameters; A: root mean square error curve; B: GA fitness curve; C: comparison of test results and predicted results; D: GA-BP neural network fitting results; E: GA-BP neural network training process; F: network structure diagram;

[0040] Figure 16 Network construction of compounds, diseases and targets; A: intersection of targets between different databases; B: Venn diagram of disease targets in different databases; C: Venn diagram of intersection targets of drugs and diseases; D: compound-target-disease interaction network; E: compound connectivity ordering bar chart;

[0041] Figure 17 Protein-protein interaction (PPI) network analysis; A: STRING interaction network; B: protein-protein interaction network; C: compound connectivity ordering column chart;

[0042] Figure 18 GO enrichment pie chart (A) and GO enrichment bubble chart (B);

[0043] Figure 19 KEGG pathway pie chart;

[0044] Figure 20 KEGG pathway bubble chart;

[0045] Figure 21 Compound-target-pathway-disease network diagram;

[0046] Figure 22 Figure 13 is a bubble chart of the TOP target and pathway;

[0047] Figure 23 Figure 14 is a pathway enrichment and docking energy heat map of the target in ALD; A: enrichment of the target related to ALD metabolic pathway; B: molecular docking energy heat map;

[0048] Figure 24 Figure 15 is a visual result of molecular docking; A: CASP8-β-sitosterol complex; B: IL-6-ParishinA complex; C: NF-κB1-ParishinA complex; D: TLR4-ParishinA complex; E: CASP3-ParishinA complex;

[0049] Figure 25 Figure 16 is the effect of liquor partner on the proliferation of HepG2 cells; A: the effect of sample concentration on the viability of HepG2 cells; B: the establishment of HepG2 cell damage model by ethanol concentration screening; C: observation of the microstructure of cells under different treatments;

[0050] Figure 26 Figure 17 is the effect of liquor partner on ethanol-induced oxidative damage of HepG2 cells; A: alcohol dehydrogenase (ADH); B: lactate dehydrogenase (LDH); C: aspartate aminotransferase (AST); D: alanine aminotransferase (ALT);

[0051] Figure 27 Figure 18 is the effect of liquor partner on ethanol-induced oxidative damage of rat liver; A: blood ethanol concentration; B: alcohol dehydrogenase (ADH); C: acetaldehyde dehydrogenase (ALDH); D: superoxide dismutase (SOD); E: malondialdehyde (MDA). DETAILED DESCRIPTION

[0052] Various exemplary embodiments of the present application will now be described in detail with reference to the drawings. The detailed description is not to be considered to limit the application in any way, but rather to explain certain aspects, features, and embodiments of the application.

[0053] It should be understood that the terms used herein are merely for the purpose of describing particular embodiments and are not intended to limit the application. In addition, for numerical ranges in the present application, it should be understood that each intermediate value between the upper limit and the lower limit of the range is specifically disclosed. Each intermediate value between any stated value or stated range, and any other stated value or stated range, is also included within the application. The upper and lower limits of these smaller ranges can be independently included or excluded from the ranges.

[0054] All technical and scientific terms used herein have, unless otherwise defined, the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present application, preferred methods and materials are described. All publications mentioned in this specification are herein incorporated by reference to disclose and describe the methods and / or materials in connection with which the publications are cited. The citation of any reference is not an admission that it is prior art with respect to the present application. All literature and similar materials cited in this application, including but not limited to, patents, genetic sequences, and other documents, are hereby expressly incorporated by reference.

[0055] Many modifications and variations of the present application described in the specific embodiments of the application can be made by those skilled in the art without departing from the spirit or scope of the application. Other implementations of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. The specification and examples given are exemplary only.

[0056] As used herein, the terms "comprises", "comprising", "includes", "including", "has", "having", "contains", "containing", or variations thereof, are intended to be open-ended terms that mean inclusion, but not limited to, the listed materials and methods.

[0057] Example 1

[0058] 1. Experimental materials

[0059] Raw materials: Gastrodia elata Blume, produced in Bijie, Guizhou, provided by Guizhou Yunchang Wumeng Gastrodia elata Biotechnology Co., Ltd.

[0060] Cells: human hepatoma cells (HepG2 cells).

[0061] Experimental animals: 30 male SD rats, provided by Jinan Pengyue Experimental Animal Breeding Co., Ltd., weighing 280-320 g, with Chinese Experimental Animal Use License (SYXK(Lu)202230032) and Chinese Experimental Animal Production License (SCXK(Lu)20220006). After 3-5 days of adaptation, the test was started.

[0062] 2. Experimental methods

[0063] 2.1 Preparation of Gastrodia elata Blume ultrafine powder

[0064] Select fresh Gastrodia elata Blume with good quality (A), slice (B), dry at 65°C constant temperature with hot air until constant weight, crush with a crusher, pass through an 80-mesh sieve, and crush with an ultrafine crusher. Figure 1 Figure 1 2.2 Optimization of ultrasonic extraction conditions of Gastrodia elata Blume wine companion and preparation

[0065] 2.2 Optimization of ultrasonic extraction conditions of Gastrodia elata Blume wine companion and preparation

[0066] ​Using Gastrodia elata ultrafine powder as the matrix, a single factor experiment was carried out with the ethanol volume fraction (45%, 50%, 55%, 60%, 65%), solid-liquid ratio (1:10, 1:15, 1:20, 1:25, 1:30), ultrasonic time (0.5h, 1h, 1.5h, 2h, 2.5h), ultrasonic temperature (40, 45, 50, 55, 60℃), ultrasonic power percentage (60%, 70%, 80%, 90%, 100%) as factors, and gastrodin content as the evaluation index. Gastrodin was determined using high-performance liquid chromatography (HPLC) on an Agilent ZORBA SB-C18 column (4.6 × 250 mm, 5 μm). The mobile phase consisted of 0.5% phosphoric acid in water and acetonitrile (95:5). UV detection was performed at a wavelength of 225 nm. The injection volume was 20 μL, the flow rate was 1 mL / min, and the column temperature was 25°C. Based on the results of a single-factor experiment, a response surface optimization experiment with five factors (ethanol volume fraction, material-liquid ratio, ultrasonic time, ultrasonic temperature, and ultrasonic power) and three levels was conducted using the Box-Behnken design principle (Table 1). Each experiment was replicated three times, and the results were averaged. Response surface design and analysis were performed using Design-Expert 10.0 software.

[0067] Table 1 Factors and levels of response surface experiment

[0068]

[0069]

[0070] 2.3GA-BP neural network design

[0071] Combined with the results of response surface experiment, BP neural network was designed using Metlab 2024b ( Figure 1 D), in this work, the five neurons of the input layer are ethanol concentration, material-liquid ratio, ultrasonic time, ultrasonic temperature, and ultrasonic power percentage, and the output layer is the gastrodin content. Five hidden layers are set up, and the 46 groups of data from the response surface test are used as samples, which are divided into three parts: training set (70%), validation set (15%), and test set (15%). The mapminmax function is used to normalize the data and map the data to [0, 1]. A feedforward neural network with 5 hidden layer nodes is established by the newff function. In the parameter setting, the maximum number of iterations is set to 1000, and the error threshold is 10 -6, learning rate is 0.001. Next, the genetic algorithm initialization parameter setting is carried out, the genetic algorithm is initialized and set through the initializega function, and the gabpEval function is combined for evaluation. In the genetic algorithm optimization process, the iteration number is set to 100, the optimization parameter is 5 factors, and the parameter range is defined according to the rationality of the test. The training process is executed by the train function, and through selection, crossover and mutation operations, the optimal solution is finally found. Combined with the response surface test results and the GA-BP neural network prediction results, considering the safety of food, the same volume fraction of edible alcohol is used to replace ethanol for ultrasonic extraction, filtration, and the filtrate is concentrated by a rotary evaporator, and then frozen at-60℃ for 48 hours. The dried sample is collected and stored in a drying box Figure 1 C) in the middle.

[0072] 2.4 Network pharmacology

[0073] 2.4.1 Active ingredients and targets of Gastrodia elata wine companion

[0074] Active chemical components of Gastrodia elata were screened by using HERB / TCMSP / BATMAN / ETCM / SYMMAP / TCM-ID databases. The SMILE / InChI structure of the components was collected by using the database PubChem, and the drug-like property of the compounds was evaluated by using SwissADME, and the target prediction was performed by using SwissTargetPrediction / BATMAN / TargetNet / SuperPred. The obtained targets were standardized, de-duplicated, and non-alcohol-soluble active ingredients were discarded. The alcohol-soluble active substances of Gastrodia elata were comprehensively searched from the literature, and finally the active ingredients and action targets of the drug were obtained.

[0075] 2.4.2 Screening of Gastrodia elata wine companion and disease-related targets

[0076] The disease-related targets were searched from CTD / GeneCards / OpenTargets / DrugBank databases by using “ALD” as the keyword, and the disease target genes were summarized and de-duplicated. Finally, the potential targets of the disease were obtained. The Venn diagram of the intersection of targets in different databases was drawn. The compound targets obtained above and the disease targets downloaded from the database were intersected in R (4.2.1), and the common targets were obtained as the targets related to the treatment of diseases by Gastrodia elata wine companion, which were used for the next step of analysis. The intersection targets were drawn by using RVennDiagram1.7.3.

[0077] 2.4.3 Construction and analysis of compound-target-disease network

[0078] The one-to-one correspondence between the active ingredients of Gastrodia wine companion and the target points was introduced into Cytoscape3.9.1 software, a drug-compound-target-disease network graph was constructed, and the NetworkAnalyzer plug-in was used to analyze the network topology properties and calculate the degree value of the node.

[0079] 2.4.4 Protein-protein interaction network construction and analysis

[0080] A protein-protein interaction (PPI) network graph was constructed using the STRING database, and the wine companion acting on the intersection target points related to diseases was introduced into the STRING database. The species was selected as "Homo sapiens", and the confidence was set to ≥0.7. The interaction relationship between proteins was obtained, and the TSV and PNG files were saved. The Cytoscape software was introduced, the isolated target points without intersection were deleted, the network topology properties were analyzed, and the core target points were screened according to the degree value of the topological structure (CC / BC / degree sorting).

[0081] 2.4.5 GO function enrichment and KEGG pathway enrichment analysis

[0082] The related target points of Gastrodia wine companion and diseases were analyzed by R clusterProfiler4.6.2 package for gene ontology (GO) function enrichment analysis and KEGG pathway enrichment analysis, respectively. The GO enrichment analysis took P<0.05 as the screening condition, and the top 20 biological entries with P value less than 0.05 in the selected results were used to draw a bar chart. The KEGG enrichment analysis also took P<0.05 as the significant enrichment screening condition, and the top 30 signal pathways with P<0.05 were selected to draw a bubble chart for visual analysis.

[0083] 2.4.6 Compound-target-pathway-disease network construction and analysis

[0084] In order to find the potential mechanism of drug action, the inventors selected the core TOP pathway, the key target points and active ingredients therein, and constructed a "compound-target-pathway-disease" network. In order to better show the mutual relationship between the important active ingredients and target points of the drug and some important pathways, and to play a synergistic role.

[0085] 2.5 Molecular docking

[0086] The screened important compounds were docked with the core target molecules. The 3D structure of the main active compound was downloaded from the PubChem database, and the 3D structure of the core target protein was downloaded from the Protein Data Bank (https: / / www.rcsb.org / ) database. The core target protein was preliminarily processed by removing solvent molecules, etc. using Pymol 2.6.0 software, and further hydrogenation processing and charge processing were performed using AutoDockTools 1.5.7. The core target protein and the active compound were saved as "pdbqt" format files, and appropriate grid positions and sizes were set. Finally, the docking of the components and the target was completed by Autodock Vina. The docking results were visualized using PyMOL software.

[0087] 2.6 Effects of Gastrodia elata Liquor Companions on the Proliferation of HepG2 Cells

[0088] Sample preparation: The prepared liquor companions were dissolved in pure water according to the sample screening concentration.

[0089] Cell recovery and passage: After taking the HepG2 cells out of the liquid nitrogen tank, they were quickly placed in a 37°C constant temperature water bath to thaw, and then quickly added to MEM complete culture medium, centrifuged at 1000 r / min, 25°C for 5 min, the supernatant was discarded, and fresh complete culture medium was added to resuspend the cells, 3 mL of which were inoculated into a T25 cell culture bottle, which was placed in a 5% CO2, 37°C incubator for culture. After 1 day, the liquid was changed, and when the cell confluence reached 80%, the cells were passaged. The cell supernatant was discarded, washed twice with 2 mL of PBS, gently shaken, and the waste liquid was discarded. 1 mL of trypsin was added for digestion, and the digestion was observed under an inverted microscope. After complete digestion, 3 mL of cell culture medium was added to terminate the digestion. The cells were resuspended and transferred to an EP tube, centrifuged at 1000 r / min, 25°C for 5 min. The supernatant was discarded, and the cells were resuspended in culture medium and subcultured in culture bottles in a 5% CO2, 37°C incubator.

[0090] Sample concentration determination (cytotoxicity determination): The CCK-8 method was used to evaluate the effect of different concentrations of liquor companions on the viability of HepG2 cells. 5x10 4 HepG2 cells were inoculated into a 96-well plate and cultured for 24 h, and then 1, 1.5, 2, 2.5, 3, 3.5, and 4 mg / mL of liquor companions were added to the serum-free culture medium for 24 h. After the culture ended, 100 μL of serum-free MEM medium containing 10% CCK-8 was added to each well, and incubation was continued for 1 h. The absorbance at 450 nm was measured using a microplate reader. The cell survival rate was represented by the ratio of the absorbance between the treated and control groups. The IC 90 was used as the subsequent loading concentration.

[0091] HepG2 cell alcohol-induced liver injury model establishment (IC 50 ): Collect HepG2 cells in logarithmic growth phase, adjust the cell suspension concentration to 10 6 × 10^6 / mL using a cell counting plate, inoculate 100 μL per well in a 96-well plate, 6 replicates per group, place in a 5% CO2, 37°C incubator, and replace the medium when the cell confluence is 90-100%, and set up control and model groups, replace the medium with incomplete MEM medium for the control group, and add 350, 450, 550, 650, 750, 850, 950, 1050 mmol / L concentration of ethanol medium for the model group, replace the medium and place in a 5% CO2, 37°C incubator for 24 h, determine cell viability using the CCK-8 method, and select the semi-lethal concentration (IC 50 ) of alcohol concentration as the modeling concentration.

[0092] Effect of Gastrodia liquor companion on HepG2 cell oxidative damage: Three groups of tests were designed according to the order of sample loading, namely, sample loading first and damage later (Damage after, DA), damage first and sample loading later (Damage first, DF), and damage and sample loading simultaneously (Damage and sample together, DT), with control and model groups and test and ethanol combined treatment groups within each group. The control group was the group in which the cells grew normally, and the medium given after 24 h was a medium without FBS. The model group was the group in which the cells were stimulated by ethanol at the modeling concentration for 24 h. The treatment groups were DA, DF, and DT groups, and after 48 h of cell culture, the cell culture medium was used to determine lactate dehydrogenase (LDH), alcohol dehydrogenase (ADH), glutamic-pyruvic transaminase (ALT / GPT), and glutamic-oxaloacetic transaminase (AST / GOT).

[0093] 2.7 Gastrodia liquor companion liver protection animal experiment

[0094] Grouping and modeling: 30 male SD rats were randomly divided into 5 groups, 6 rats per group, namely, a control group (CK), a model group (Model), a Gastrodia liquor companion low-dose group (LD), a medium-dose group (MD), and a high-dose group (HD), which were respectively given 0.8 mL / 100 g of 50% ethanol by gavage, continuously for 8 days, and the control group was given an equal amount of animal drinking water.

[0095] Test administration: administration 30 min before gavage, the low-dose, medium-dose, and high-dose groups were respectively given 0.2 g / kg, 0.6 g / kg, and 1 g / kg of liquor companion by gavage, continuously for 8 days, and the control and model groups were given an equal amount of animal drinking water.

[0096] Evaluation index determination: 60 minutes after the last ethanol gavage, blood was collected from the orbital cavity of each group of rats to test the blood ethanol content (using a blood ethanol determination kit); 60 minutes after the last gavage, the animals were killed, the fresh liver was dissected and removed, and an appropriate amount of tissue from the same position of the rat liver was taken. 0.9% ice saline was added at a ratio of 1:9 (g / mL), and the tissue was broken in a low-temperature tissue homogenizer. The tissue fluid was centrifuged at 3500 rpm for 15 minutes, and the supernatant was separated to obtain 10% liver homogenate. ADH, ALDH, SOD activities and MDA content were determined using a kit.

[0097] 3. Experimental results and analysis

[0098] 3.1 Optimization of ultrasonic extraction conditions and preparation of Tianma wine companion

[0099] The standard curve of gastrodin content was drawn by high performance liquid chromatography (such as Figure 2 (As shown in F), by comparing the Tianma liquor companion sample and the standard product, the peak time of gastrodin is about 6.2min, and its HPLC chart is as follows Figure 4 Combined with the standard curve, the gastrodin content of each liquor companion sample under single factor conditions was determined (HPLC chart of gastrodin standard, see Figure 3 ).

[0100] The material-liquid ratio, ultrasonic time, ultrasonic temperature, extractant concentration and ultrasonic frequency are all key factors in ultrasonic extraction. As the material-liquid ratio increases, the gastrodin content shows a trend of first increasing and then decreasing. The gastrodin content is highest when the material-liquid ratio is 1:20 g / mL ( Figure 2 As the ultrasound time increased, the gastrodin content gradually increased, reaching a peak at 2 h, and then tended to be stable ( Figure 2 B), too short an ultrasonic time will result in incomplete extraction, while too long may lead to degradation of the components. As the ultrasonic temperature increases, the gastrodin content first increases and then decreases, and the optimal temperature is 50℃ ( Figure 2 C), too low a temperature is not conducive to the release of components, while too high a temperature can easily destroy the activity. Different ethanol volume fractions have a significant effect on the content of gastrodin. With the increase of ethanol volume fraction, the content of gastrodin first increases and then decreases. The optimal ethanol volume fraction is 50% ( Figure 2 D), different ethanol volume fractions have significant differences in the extraction efficiency of gastrodin. High-concentration ethanol has low polarity and may not be able to effectively dissolve polar components. It may also denature the cell wall, hinder the penetration of the solvent, and thus affect the release of components. Low-concentration ethanol may not be able to fully dissolve gastrodin, resulting in reduced extraction efficiency. With the increase of ultrasonic power, the content of gastrodin showed an overall downward trend ( Figure 2In the middle E), research shows that high power ultrasound can usually improve the extraction rate, because high power can provide more energy, more conducive to the destruction of cell structure, promote the release of active ingredients, but too high power may lead to degradation of active ingredients, inactivation. According to the single factor test data design response surface test (Table 2).

[0101] Table 2 response surface test design and results

[0102]

[0103]

[0104] Response surface test factor level table a total of 46 groups of experiments, the test design and results are shown in Table 2. According to the test results of Table 2, the results are regressed by using Design expert 13.0 software, and the following regression equation is obtained:

[0105] Gastrodin content = 1554.42-31.34A+168.89B+89.49C+134.02D-38.93E-87.48AB-62.91AC+81.96AD+25.94AE+20.41BC+72.23BD-1.93BE+125.02CD+77.56CE-5.55DE-271.96A2-366.82B2-244.24C2-187.75D2-268.13E2. The regression model variance analysis results are shown in Table 3, the regression model P<0.0001, the model is extremely significant, the P value of model misfit item is 0.2315, the difference is not significant, indicating that the model conforms to the actual situation, and the model can fully explain the data. And the correlation coefficient R 2 =0.8406, and the adjusted value is close to the original value, indicating that the model fitting is good. Adeq Precision = 8.5303, that is, the signal to noise ratio is greater than 4, which further indicates that the model is reliable. The P values of B, C, D, A 2 , B 2 , C 2 , E 2 , D 2 in the model are less than 0.05, indicating that they are significant model items. According to the F value size to judge the influence size relationship of each factor on gastrodin content is B>D>C>E>A, that is, the ratio of solid to liquid > ultrasonic temperature > ultrasonic time > ultrasonic power > ethanol volume fraction.

[0106] Table 3 regression model variance analysis

[0107]

[0108]

[0109] The color response surface diagram was drawn by Design-expert13.0 software (see Figures 5 to 14 ) and a visual analysis of the experimental results was performed. A three-dimensional response surface plot shows that steeper response surface plots or more elliptical contour plots indicate a more significant interaction. Ultrasonic time and temperature are relatively steep, and the contour lines exhibit a distinct elliptical distribution pattern, indicating a significant interaction between the two. The parabolic graph of the color valence equation opens downward, indicating that this equation has a maximum. The optimal extraction process parameters obtained based on Box-Behnken model analysis are an ethanol volume fraction of 50.226%, a solid-liquid ratio of 1:13.700 g / mL, an ultrasonic time of 1.672 h, an ultrasonic temperature of 52.846°C, and an ultrasonic power percentage of 70.365%, or 492.555 W. Under these parameters, the gastrodin content reached 1571.844 μg / g. Taking into account the actual operation, the parameters were adjusted to 50% ethanol volume fraction, 1:13g / mL solid-liquid ratio, 1.7h ultrasonic time, 53℃ ultrasonic temperature, and 70% ultrasonic power percentage, i.e. 490W. After adjusting the parameters, 6 parallel tests were carried out, and the average value of the gastrodin content in the Tianma strips was 1503.739ug / g, which was close to the model predicted value, indicating that the extraction process was stable and reliable.

[0110] 3.2GA-BP neural network optimization analysis

[0111] The GA-BP neural network uses the Levenberg-Marquardt algorithm and randomly divides the data into training (70%), validation (15%) and test (15%), with 5 input and 5 hidden layers ( Figure 15 F). When the number of validation checks reached 6, Epochs was 34, training stopped, and the root mean square error decreased to 0.00137 ( Figure 15 During the operation of the GA-BP neural network, as the number of epochs increases, the root mean square error (MSE) decreases rapidly, which shows that the model is constantly being optimized. The MSE of Validation reaches a minimum of 0.0072792 at the 28th time. Figure 15 A in the middle), indicating that the model has reached convergence and is highly stable, suitable for subsequent experimental analysis. The regression analysis results on training, validation, testing, and all data sets show that the regression prior relationship R value is higher than 0.9, and R test > R verification, indicating that the model can well capture the complex relationship in the data and make effective predictions, and accurately predict new data without overfitting. The R prediction value is greater than 0.9 ( Figure 15 D), indicating that the model does not suffer from underfitting.

[0112] The optimal extraction conditions were determined using a genetic algorithm, and the results of the GA were influenced by the population size, mutation rate, crossover, and selection function. The root mean square error (RMSE) of real and predict was 55.2757 Figure 15 In the training process, the fitness value of the GA decreased in steps as the number of iterations increased, and the fitness value tended to be stable at 63 iterations Figure 15 In the training process, the fitness value of the GA decreased in steps as the number of iterations increased, and the fitness value tended to be stable at 63 iterations The optimal extraction conditions were obtained as follows: when the ethanol percentage was 49.9463, the solid-liquid ratio was 1:19.88, the ultrasonic time was 1.5552 h, the ultrasonic temperature was 50.7719℃, and the ultrasonic power percentage was 67.6813% (487.30536 W), the content of gastrodin was 1726.4029 ug / g, and the prediction accuracy was 99.4722%. Considering the actual situation, the parameters were adjusted to an ethanol percentage of 50%, a solid-liquid ratio of 1:20, an ultrasonic time of 1.55 h, an ultrasonic temperature of 58℃, and an ultrasonic power of 490 W for verification experiments, and six groups of parallel experiments were set. As shown in Table 4, the maximum content of gastrodin predicted by the GA-BP neural network was 1726.4029 ug / g, which was significantly higher than the value predicted by RSM. The relative error between the predicted value of GA-BP and the verification value was lower than that of RSM, and the verification result of GA-BP was better than that of RSM, further verifying that the accuracy of the prediction of GA-BP was better than that of RSM. This is due to the inherent advantages of the GA-BP model in processing complex nonlinear data, as well as the high-efficiency optimization ability of the genetic algorithm in optimizing network weights and biases. In summary, the final selected double-frequency ultrasonic extraction parameters of the application were an ethanol percentage of 50%, a solid-liquid ratio of 1:20, an ultrasonic time of 1.55 h, an ultrasonic temperature of 58℃, and an ultrasonic power of 490 W.

[0113] Table 4 Comparison of model optimization results and verification

[0114]

[0115] 3.3 Network pharmacology

[0116] 3.3.1 Collection of active ingredients and prediction of target points

[0117] Through the drug database, the components of Gastrodia elata were retrieved, and repeated components were deleted, and a total of 5 Gastrodia elata ethanol-soluble components were obtained, namely Beta-Sitosterol, Clionasterol, Suchilactone, Calycosin, Rhynchophylline, and 8 common Gastrodia elata ethanol-soluble active components were obtained through literature retrieval, namely Gastrodin, Parishin A, Parishin B, Parishin C, Parishin F, 4-Hydroxybenzyl alcohol, Vanillin, and Vanillyl alcohol. The compounds were mapped to the pubchem database to obtain compound InChI SMILES information, and imported into SwissADME to evaluate compound drug-likeness indicators. Through SwissTargetPrediction (Score>0.01), TargetNet (Score>0.7), BATMAN (Score>70), and SuperPred (Score>70) databases, the potential action targets of the active ingredients of the drugs were predicted, and after deleting the repeated targets, a total of 434 drug targets were obtained, as shown in Table A. Figure 16

[0118] 3.3.2 Collection of disease-related targets and screening of therapeutic action targets

[0119] After retrieving the disease results through CTD Score≥50 / GeneCards Score≥40 / OpenTargets Score≥0.05 / DrugBank databases, the threshold was screened, the gene names of the standardized disease targets were summarized and de-duplicated. The potential targets of the disease were selected, and a total of 570 disease targets were obtained. The intersection of the selected active ingredient targets and the disease targets was determined after mapping, and 97 common action targets were determined as the potential targets of Gastrodia elata wine partners acting on diseases. The acquisition of disease targets is shown in Table B, and the intersection targets are shown in Table C. Figure 16 Figure 16

[0120] 3.3.3 Compound-target-disease network construction and analysis

[0121] The compound-target-disease network is shown in Table D. Figure 16 ​​​In Figure D, the network diagram has 111 nodes and 335 edges, each representing the target relationship between the compound and the target. Thirteen active ingredients act on 97 targets. The Network Analyzer plug-in was used to analyze the network topology. In the network diagram, the size of the node represents the degree of the node. The larger the degree, the stronger the hub role of the node in the network. The degree values ​​(CC closeness / BC betweenness / degree connectivity) are ranked, and the main component degree values ​​are ranked as follows: Figure 16 As shown in E.

[0122] 3.3.4 PPI Network Diagram Analysis

[0123] The intersection targets of 97 active ingredients for the treatment of ALD were imported into the STRING database to obtain the PPI relationship, which was then imported into Cytoscape software for analysis. The network diagram had 86 nodes and 611 edges ( Figure 17 In A), the edges represent the associations between targets. The NetworkAnalyzer plug-in is used to analyze the network topology, calculate the degree value, set the color depth and node size to reflect the degree value, select the top 30 core nodes according to the degree value (CC / BC / degree), and draw the network diagram. Figure 17 Middle C. The core targets are AKT1, STAT3, JUN, EGFR, BCL2, IL6, etc. ( Figure 17 Middle B), as a key target for Gastrodia elata wine companion in the treatment of ALD.

[0124] 3.3.5 GO functional enrichment analysis and KEGG pathway analysis

[0125] Based on R clusterProfiler, GO enrichment analysis was performed on 97 intersection targets related to the treatment of diseases by Gastrodia elata wine companions ( Figure 18 In Figure A), the top 20 items of biological process (BP), molecular function (MF), and cellular component (CC) with P < 0.05 were selected to draw bar graphs, such as Figure 18As shown in FIG. 12B, the vertical coordinate represents each entry of GO, and the horizontal coordinate represents the number of enrichment to the target of the entry. BP mainly involves cellular response to reactive oxygen, response to reactive oxygen species (ROS), cellular response to oxidative stress, etc., and previous studies have shown that oxidative stress caused by alcohol consumption can damage the functions of important antioxidants such as glutathione peroxidase (GPX), superoxide dismutase (SOD), and catalase (CAT), so oxidative stress can be considered as an evaluation index of liver injury in cell experiments and animal experiments. MF mainly includes 3', 5'-cyclic-AMP phosphodiesterase activity, 3', 5'-cyclic-nucleotide phosphodiesterase, cyclic-nucleotide phosphodiesterase activity, etc.; and CC mainly contains cyclin-dependent protein kinase holoenzyme complex, caveola, plasma menmbrane raft, serine / threonine protein kinase complex, etc. KEGG pathway enrichment analysis was performed on the target points Figure 19 ), a total of 166 signal pathways were enriched, the top 30 pathways with P<0.05 were visualized by drawing a bubble chart Figure 20 ), and the top target points and top pathways were jointly drawn into a mulberry bubble chart Figure 22). The enrichment results show that the main pathways involved in the treatment of diseases are AGE-RAGE signaling pathway in diabetic, Lipid and atherosclerosis, Hepatitis B, etc. through synergistic effects. Non-alcoholic fatty liver disease and Alcoholic liver disease are both in the top 30 pathways. This shows that Gastrodia elata wine partners may have a positive effect on ALD we are concerned about, and have potential therapeutic effects in the treatment of complications of diabetes, blood lipid atherosclerosis, non-alcoholic fatty liver disease, etc.

[0126] 3.3.6 Construction and analysis of compound-target-pathway-disease network

[0127] The core TOP pathway, key targets and active ingredients were selected to construct the "compound-target-pathway-disease" network. As shown in Figure 21 , the network consists of 141 nodes and 830 edges (13 components, 97 targets, 30 signaling pathways, diseases), different node shapes represent different active ingredients, key targets and regulated pathways in gastrodia elata wine partners, and the color depth represents the degree weight in the network. Each active ingredient corresponds to multiple targets, and each target connects multiple components, reflecting the mechanism of multi-component, multi-target drug treatment of diseases. Multiple pathways are connected by common targets, rather than being independent, which shows that the pathways have synergistic effects.

[0128] 3.4 Molecular docking

[0129] Based on the ranking of the degree value of the active ingredient in the active ingredient-target network and literature research, the core active ingredients and the top 20 core targets in the PPI network were docked. The docking energy results are shown in Figure 23 B. The smaller the binding energy, the higher the binding activity, and the easier the compound binds to the target. The binding energy ≤-5.0 kcal / mol is good, and the binding energy ≤-7.5 kcal / mol is very good. After the important active ingredients and core proteins were screened and docked by AutoDockVina1.2.3 software, the binding energy between each active ingredient ligand and the receptor protein was obtained. The lower the binding energy of the ligand and the receptor docking indicates that the molecular binding is more stable, and the possibility of interaction is higher. Combined with the analysis of the ALD metabolic pathway Figure 23Figure A, the red part of the figure is the target point enriched, the ALD pathway includes three important parts, including ethanol metabolism and oxidative stress, lipid metabolism disorder and intestinal-liver axis regulation. Ethanol is metabolized to acetaldehyde by alcohol dehydrogenase (ADH) and cytochrome CYP2E1, acetaldehyde inhibits the AMPK signaling pathway, thereby reducing fatty acid degradation to form fatty liver, and ethanol oxidation by oxidase NOX4 produces a large amount of reactive oxygen species (ROS), and ROS can act on DNA through the NF-kB signaling pathway to cause inflammatory response, and the control docking result figure Figure 23 Figure B, NF-kB1 has a low binding energy with Parishin A, which has a potential inhibitory effect on the NF-kB signaling pathway. In addition, ethanol can activate IL-17A into liver macrophages / stellate cells and cause neutrophil and macrophage infiltration through the IL-17 signaling pathway and the NF-kB signaling pathway, thereby causing liver inflammation in alcoholic liver disease. The effective combination of NF-kB1 and Parishin A can also inhibit this process. In the regulation of the intestinal-liver axis, ethanol can increase intestinal permeability, leading to endotoxin (such as LPS) into the blood to cause high expression of TLR4, activate kupffer cell / Stellate cell release pro-inflammatory factors such as TNFα, IL-1β, IL-6, etc., not only aggravate the inflammatory response, but also cause cell fibrosis. Studies have shown that blocking TLR4 can reduce liver damage in ALD mice. Parishin A has a low binding energy with TLR4 and IL-6, which has a potential effect of blocking TLR4, NF-kB and even IL-6. In addition, the pro-inflammatory factor TNFα binds to the tumor necrosis factor TNF-R1 on the membrane of hepatocytes, not only triggering the NF-kB signaling cascade, but also activating the caspase-8 / 3 cascade through the Fas / FasL pathway to induce hepatocyte programmed death. CASP8 and Beta-Sitosterol, CASP3 and Parishin A have a low binding energy, which has a potential inhibitory effect on hepatocyte apoptosis. The docking results of TLR4 with Parishin A, NF-kB1 with Parishin A, IL-6 with Parishin A, CASP8 with Beta-Sitosterol, and CASP3 with Parishin A were visualized by PyMOL 2.6.0 software and Discovery Studio( Figure 24 )。In summary, it is believed that the liquor companion has a potential therapeutic effect on alcoholic liver disease, and Parishin A and Beta-Sitosterol are the main functional components.

[0130] 3.5 Effects of Gastrodia elata Liquor Companion on HepG2 Cell Proliferation

[0131] 3.5.1 The effective concentration of Tianma wine companion and the establishment of HepG2 cell alcoholic liver injury model

[0132] In order to explore the effect of Gastrodia elata wine companion on the proliferation of HepG2 cells, HepG2 cells were treated with sample concentrations from low to high, such as Figure 25 As shown in A, treatment with high concentrations of Gastrodia elata wine companion can cause cytotoxicity. According to the CCK-8 test method, the cell group cultured in complete culture medium was used as the control, and the cell-free complete culture medium was used as the blank to determine the cell survival rate. The results showed that with the increase of sample concentration, the cell survival rate gradually decreased. When the sample concentration was 1 mg / mL, the cell survival rate was as high as 95%. After that, the cell survival rate dropped sharply with the increase of sample concentration. When the sample concentration was 2.5 mg / mL, the cell survival rate dropped to 72%. Linear fitting was performed on the data, and it was calculated that the concentration of Gastrodia elata wine companion when the cell survival rate was 90% was 1.06 mg / mL, that is, IC 90 The concentration of Tianma Baijiu was 1.06 mg / mL. It can be assumed that the cytotoxicity is low when the concentration is below 1.06 mg / mL. Therefore, a concentration of 1 mg / mL was selected for subsequent experiments.

[0133] HepG2 cells were treated with different concentrations of ethanol to establish an alcoholic liver injury model. Figure 25 As shown in Figure B, the results show that with the increase of ethanol concentration, the survival rate of HepG2 cells showed a downward trend. When the ethanol concentration was 250mmol / L, the cell survival rate reached 91.10%, indicating that the toxicity to HepG2 cells at this concentration was low. When the ethanol concentration was higher than 850mmol / L, the cell survival rate dropped sharply. The data were linearly fitted to calculate the IC 50 The concentration of ethanol in HepG2 cells was 942.76 mmol / L, and a HepG2 cell alcoholic liver injury model was established based on this. Based on this model, subsequent experiments used 950 mmol / L ethanol to treat HepG2 cells to simulate alcoholic liver injury.

[0134] 3.5.2 Effects of Tianma Wine Companion on the Microstructure of HepG2 Cells

[0135] After determining the alcoholic liver injury model, we explored the effect of Gastrodia elata wine companion on the proliferation of HepG2 cells. Three modes were set according to different drinking methods. Mode A is the prevention mode, that is, Gastrodia elata wine companion is given first and then ethanol is added. Mode B is the synergistic mode, that is, ethanol and Gastrodia elata wine companion are added at the same time. Mode C is the repair mode, that is, ethanol is added first and then Gastrodia elata wine companion is given. After analysis under an inverted microscope, the results are as follows Figure 25As shown in FIG. 8, in the prevention mode (mode A), after the administration of Gastrodia elata wine partner, the cell morphology was relatively complete, and the intercellular space was small. After the addition of ethanol, compared with the ethanol model group, the degree of cell damage was lighter, the cell survival rate was higher, and the number of suspended dead cells was less. In the synergistic mode (mode B), under the simultaneous action of ethanol and Gastrodia elata wine partner, the cells were in close contact, and the cell density was significantly higher than that of the ethanol model group, but there were a large number of suspended dead cells. In the repair mode group (mode C), after the treatment of ethanol, Gastrodia elata wine partner was added, the cell morphology recovered, the intercellular space decreased, and the cell density was slightly higher than that of the ethanol model group. There were a large number of suspended dead cells in both the ethanol model group and the repair mode group. Through the simulation of three different drinking modes in vitro, it was found by microscopic analysis that Gastrodia elata wine partner could reduce the damage of ethanol to HepG2 cells in different drinking modes, and the effects of the synergistic mode and the prevention mode were the best, and the repair mode was the second, which indicated that Gastrodia elata wine partner had potential in preventing alcoholic liver injury, and provided an important basis for further research.

[0136] 3.5.3 Effect of Gastrodia elata Wine Partner on Oxidative Damage of HepG2 Cells

[0137] After centrifugation of HepG2 cells in three modes, the supernatant was taken for oxidative stress index detection, such as Figure 26As shown in the results, the ethanol dehydrogenase (ADH) activity of the cell group (CK) was low, between 2-3 U / mL, the ethanol dehydrogenase (ADH) activity of the model group (Model) treated with ethanol was much higher than that of the CK group, but after treatment with Gastrodia elata wine companion, the ethanol dehydrogenase (ADH) activity decreased, but was still higher than that of the CK group. Compared with the three modes, the ADH activity of the Model group and the control group of mode A and mode B was lower than that of mode C, and the difference between the Control group and the Model group of mode A and mode B was higher than that of mode C, which indicated that in the prevention and synergy mode, Gastrodia elata wine companion could more effectively inhibit the increase of ADH activity caused by ethanol. In the three modes, after treatment with ethanol, the lactate dehydrogenase (LDH) activity showed an upward trend, after treatment with Gastrodia elata wine companion, the LDH activity of mode A and mode B decreased, close to the level of the CK group, while the LDH activity of mode C decreased significantly, but was still much higher than that of the CK group, which may be related to the degree of cell damage. Although Gastrodia elata wine companion can improve the LDH activity caused by ethanol to some extent in the repair mode, it is still far from the original state of the cells. In the three modes, the levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) increased significantly after ethanol treatment, indicating that cell damage was aggravated. However, after treatment with Gastrodia elata wine companion, the levels of AST and ALT decreased significantly, but there was still a gap with the normal cell group. Especially in the repair mode, the regulatory effect of Gastrodia elata wine companion on AST and ALT levels was not as obvious as in the prevention and synergy modes. This conclusion is consistent with the above microscopic observation results, and these results together reveal the differences in the regulation of oxidative stress response of Gastrodia elata wine companion in different modes, further verifying its potential in alleviating alcoholic liver damage.

[0138] 3.6 Animal experiment results of Gastrodia elata wine companion for liver protection

[0139] 3.6.1 Effect of Gastrodia elata wine companion on blood ethanol content in rats

[0140] The ethanol content of the blood of rats in each group was tested, and the results are shown in Table 5. The blood ethanol content of the model group (Model) treated with alcohol by gavage was significantly higher than that of the control group (CK), increased by about 13 times, indicating that the alcohol poisoning rat model was successfully modeled. After treatment with Gastrodia elata wine companion, the blood ethanol content decreased significantly. As shown in Table 5, the blood ethanol content of the Model group treated with Gastrodia elata wine companion was significantly lower than that of the Model group treated with alcohol by gavage, and was close to the level of the CK group. This result indicates that Gastrodia elata wine companion can effectively reduce the blood ethanol content of alcohol poisoning rats. Figure 27As shown in Table 5, Model group showed significant difference with each dose group, which indicated that Gastrodipendus could effectively accelerate the metabolism of ethanol in blood. With the increase of Gastrodipendus dose, the trend of decreasing blood ethanol content became more and more significant, and when the dose increased to high dose group, it showed significant difference, which indicated that Gastrodipendus could more effectively promote ethanol metabolism at high dose. Further analysis showed that the metabolic rate of medium and high dose groups was significantly different, while there was no statistical significance between low dose group and medium dose group. This may mean that there is a minimum effective dose, and the metabolic rate will be more obvious after exceeding this dose. In summary, Gastrodipendus has dose-dependent effect on improving the rate of ethanol metabolism.

[0141] Table 5 Blood ethanol concentration of rats in each group

[0142]

[0143] 3.6.2 Effect of Gastrodipendus on oxidative stress in rat liver

[0144] The oxidative stress indicators of liver homogenate of each group of rats were determined. The ethanol dehydrogenase (ADH) of the model group was significantly higher than that of the control group Figure 27 The increase of ADH in a short period of time is due to the compensatory mechanism of liver cells to alcohol toxicity, which requires higher ADH to assist in the decomposition of ethanol. However, after the synergistic treatment of Gastrodipendus and ethanol, the ADH activity in the liver homogenate of rats in each dose group was lower than that of the model group. After multiple comparison analysis of the data, each dose group showed extremely significant difference with Model group, and different dose groups showed significant difference, indicating that the liver of rats treated with Gastrodipendus does not need high-dose ADH to decompose ethanol, reducing the burden of mouse liver cells, but the difference between low dose group and medium dose group is significant, which may also mean that there is a minimum effective dose, which is consistent with the results of the change of blood ethanol content. Figure 27 As shown in Table 5, Model group showed significant difference with each dose group, which indicated that Gastrodipendus could effectively accelerate the metabolism of ethanol in blood. With the increase of Gastrodipendus dose, the trend of decreasing blood ethanol content became more and more significant, and when the dose increased to high dose group, it showed significant difference, which indicated that Gastrodipendus could more effectively promote ethanol metabolism at high dose. Further analysis showed that the metabolic rate of medium and high dose groups was significantly different, while there was no statistical significance between low dose group and medium dose group. This may mean that there is a minimum effective dose, and the metabolic rate will be more obvious after exceeding this dose. In summary, Gastrodipendus has dose-dependent effect on improving the rate of ethanol metabolism.

[0145] Free radicals produced in the process of alcohol metabolism can consume a large amount of SOD, and at the same time, the level of MDA will increase, as shown in Table 5. Figure 27As shown in Figs. 5 and 6, the SOD activity in the liver homogenate of the model group was significantly lower than that of the control group, while the MDA level was significantly higher. After the use of the Gastrodia elata wine partner, the SOD activity in the liver homogenate of each dose group was significantly improved, and the MDA level also decreased, and the difference was statistically significant compared with the model group. Among them, the effect of the high-dose group was the most significant, while the difference between the medium-dose and low-dose groups was not statistically significant, which indicated that the Gastrodia elata wine partner had a potential dose-dependent advantage in reducing free radical damage and improving oxidative stress. The significant effect of the high-dose group may indicate the existence of an optimal dose range. In summary, the Gastrodia elata wine partner showed a positive effect in alleviating the oxidative stress burden during the alcohol metabolism of the rat liver.

[0146] The above-described embodiments are merely preferred modes of the present application and are not intended to limit the scope of the present application. Various modifications and improvements to the technical solutions of the present application made by those of ordinary skill in the art without departing from the design spirit of the present application shall fall within the scope of protection of the present application as defined by the claims.

Claims

1. Application of Tianma Wine Companion in any of the following: (1) Application in the preparation of products that increase the rate of ethanol metabolism; (2) Application in the preparation of products for alleviating the oxidative stress burden during liver alcohol metabolism; (3) Application in the preparation of products for alleviating alcoholic liver damage; in, The Gastrodia elata wine companion is obtained by ultrasonically extracting Gastrodia elata superfine powder in edible alcohol, filtering, concentrating the filtrate and then freeze-drying it.

2. The use according to claim 1, characterized in that The volume fraction of the edible alcohol is 50%, the material-liquid ratio of the Gastrodia elata superfine powder and the edible alcohol is 1g:20mL, and the Gastrodia elata superfine powder is 80-mesh superfine powder.

3. The use according to claim 1, characterized in that The ultrasonic conditions are as follows: ultrasonic time 1.55 h, ultrasonic temperature 58° C., and ultrasonic power 490 W.

4. The use according to claim 1, wherein The freeze drying step is as follows: performing low-temperature freeze drying at -60°C for 48 hours.

5. The use according to claim 1, characterized in that The Gastrodia elata wine companion increases the ethanol metabolism rate, relieves the oxidative stress burden in the liver during alcohol metabolism, or relieves alcoholic liver damage by the following usage: (1) before drinking wine, or (2) drinking with wine at the same time.

6. The use according to claim 5, characterized in that The main active ingredients of the Gastrodia elata wine companion include barisonoside A and beta-sitosterol.

7. A Gastrodia elata wine companion, characterized in that: The preparation method of the gastrodia elata wine companion comprises the following steps: ultrasonically extracting gastrodia elata superfine powder in edible alcohol with a volume fraction of 50%, filtering, concentrating the filtrate and freeze-drying the obtained product.

8. The Gastrodia elata wine companion as claimed in claim 7, characterized in that The solid-liquid ratio of the Gastrodia elata superfine powder and the edible alcohol is 1g:20mL, and the Gastrodia elata superfine powder is 80-mesh superfine powder.

9. The Gastrodia elata wine companion according to claim 7, characterized in that The ultrasonic conditions are as follows: ultrasonic time 1.55 h, ultrasonic temperature 58° C., and ultrasonic power 490 W.

10. The Gastrodia elata wine companion according to claim 7, characterized in that The freeze drying step is as follows: performing low-temperature freeze drying at -60°C for 48 hours.

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