Method, system and equipment for evaluating treatment effect of meconopsis on hepatic fibrosis based on PPAR gamma expression level

Abstract

The invention discloses a method, a system and equipment for evaluating the treatment effect of meconopsis on hepatic fibrosis based on PPAR gamma expression level. It is found for the first time that meconopsis has the anti-hepatic fibrosis effect by activating a PPAR gamma signal channel and inhibiting an MAPK signal channel. On the basis, the invention provides a method, a system and equipment for evaluating the treatment effect of meconopsis meconopsis on hepatic fibrosis for the field, so that a doctor is assisted in evaluating the treatment effect of a hepatic fibrosis patient, and a clinician is guided to formulate an individualized treatment scheme for the patient.

Description

Technical Field

[0001] The present invention belongs to the field of bioinformatics, and in particular, relates to a method, system and device for evaluating the therapeutic effect of Meconopsis pilosula on liver fibrosis based on PPARγ expression level. Background Art

[0002] Hepatic fibrosis is a compensatory reaction in the process of tissue repair after liver inflammation or damage caused by various reasons. The pathological feature is the excessive deposition of extracellular matrix (ECM) in the liver. Hepatitis C virus (HCV) infection is chronic, with a rate of 50%-85%, 10%-30% developing into cirrhosis, and 3%-10% evolving into liver cancer. Other diseases such as alcoholic liver disease, nonalcoholic steatohepatitis (NASH), autoimmune hepatitis, and primary biliary cirrhosis (PBC) can also cause liver fibrosis and cirrhosis. Chronic liver disease caused by various reasons is accompanied by the occurrence of liver fibrosis during the course of the disease. If progressive liver fibrosis is not effectively controlled, it will eventually develop into cirrhosis and even liver cancer. Therefore, it is very important to study the pathogenesis and drug treatment of liver fibrosis.

[0003] Meconopsis is an annual or perennial herb. It is cold-resistant by effectively regulating chlorophyll fluorescence parameters at low temperatures, so it is mainly distributed in the cold Qinghai-Tibet Plateau. my country's famous medical classics "Yuewang Yaozhen", "Jingzhu Bencao", "Tibetan Medicine Records" and "Four Medical Classics" have detailed records of it: Meconopsis has the characteristics of bitterness, astringency, coldness and slight toxicity, so it can clear away heat and dampness, and belongs to the large intestine meridian and liver meridian. It is clinically used to treat heat syndrome, traumatic injuries and chest and back pain. Studies have reported that Meconopsis has anti-tumor, anti-hepatitis, and myocardial infarction relief effects, but its mechanism of anti-liver fibrosis effect has not been reported. Summary of the invention

[0004] In order to make up for the deficiencies of the prior art, the object of the present invention is to provide a method, system and device for evaluating the therapeutic effect of Meconopsis on liver fibrosis.

[0005] In order to achieve the above object, the present invention adopts the following technical solution: A first aspect of the present invention provides a method for evaluating the therapeutic effect of Meconopsis pilosula on liver fibrosis.

[0006] Furthermore, the method is performed by a computer and comprises the following steps: Obtain data: Obtain the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ in samples of patients with liver fibrosis after treatment with Meconopsis pilosula; Processing data: inputting the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ into a constructed evaluation model, wherein the evaluation model predicts the therapeutic effect of Meconopsis pilosula on patients with liver fibrosis based on the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ; Output the result.

[0007] Furthermore, the p-MAPK, p-ERK, and p-JNK refer to phosphorylated MAPK, phosphorylated ERK, and phosphorylated JNK, respectively.

[0008] Furthermore, the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ include mRNA expression level data and protein expression level data.

[0009] Furthermore, the mRNA expression level data include but are not limited to data obtained by RT-PCR, qRT-PCR, in situ hybridization and RNA sequencing.

[0010] Furthermore, the protein expression level data include but are not limited to data obtained by immunoblotting, immunohistochemistry, enzyme-linked immunosorbent assay and mass spectrometry.

[0011] Further, the steps of constructing the evaluation model are as follows: The expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ are obtained; the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ are obtained from untreated patients with liver fibrosis and patients with liver fibrosis treated with Meconopsis pilosula; the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ are input into a machine learning algorithm to construct an evaluation model.

[0012] Preferably, the step of constructing the evaluation model also includes verifying the model effectiveness, and the method of verifying the model effectiveness includes a ROC curve.

[0013] Furthermore, the machine learning algorithm includes algorithm models developed using various development tools.

[0014] Preferably, the development tools include but are not limited to TensorFlow, Scikit Learn, PyTorch, OpenNN, RapidMiner, Azure Machine Learning, Apache Mahout, Shogun, KNIME, Vertex AI, H2Oai, Anaconda, Keras, Tableau, Fast.ai, Catalyst, Amazon ML, MLJAR, and Spell.

[0015] Preferably, the algorithm model includes but is not limited to a linear regression model, a logistic regression model, a Lasso regression model, a Ridge regression model, a linear discriminant analysis model, a nearest neighbor model, a decision tree model, a perceptron model, a neural network model, a support vector machine model, a naive Bayes model, an AdaBoost model, a GBDT model, an XGBoost model, a LightGBM model, a CatBoost model, and a random forest model.

[0016] Furthermore, the evaluation model obtains results through the following criteria: When the expression levels of any one or several of the p-MAPK, p-ERK, and p-JNK are lower than a threshold value and / or the expression level of the PPARγ is higher than a threshold value, a classification result is obtained that Meconopsis is effective in treating patients with liver fibrosis; when the expression levels of any one or several of the p-MAPK, p-ERK, and p-JNK are higher than a threshold value and / or the expression level of the PPARγ is lower than a threshold value, a classification result is obtained that Meconopsis is ineffective in treating patients with liver fibrosis.

[0017] In some embodiments of the present invention, the preset threshold is a representative value of normal samples of liver fibrosis, including but not limited to a maximum value, a third quartile, and an average value. In some preferred embodiments of the present invention, the population sample includes more than 20 samples, such as 30, 50, 80, 100, 150, 200, 300, 500 or more.

[0018] Furthermore, the patient includes humans and / or mammals.

[0019] Furthermore, the sample includes blood and / or tissue.

[0020] A second aspect of the present invention provides a system for evaluating the therapeutic effect of Meconopsis pilosula on liver fibrosis.

[0021] Further, the system comprises: Data acquisition unit: used to obtain the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ in samples of patients with liver fibrosis after treatment with Meconopsis; A data classification unit is used to classify and predict the data obtained by the data acquisition unit through the evaluation model obtained by the construction method described in the first aspect of the present invention, and obtain a classification result of whether Meconopsis is effective in treating patients with liver fibrosis; Result output unit: used to output classification results.

[0022] A third aspect of the present invention provides a computer device.

[0023] Furthermore, the device comprises: A memory and a processor, wherein the memory is used to store program instructions; the processor is used to call the program instructions, and when the program instructions are executed, the method for evaluating the therapeutic effect of Meconopsis on liver fibrosis described in the first aspect of the present invention is implemented.

[0024] A fourth aspect of the present invention provides a computer-readable storage medium.

[0025] Furthermore, the computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the method for evaluating the therapeutic effect of Meconopsis pilosula on liver fibrosis described in the first aspect of the present invention is implemented.

[0026] A fifth aspect of the present invention provides use of Meconopsis pilosula in preparing a drug for resisting liver fibrosis.

[0027] Furthermore, the Meconopsis pilosula exerts its anti-liver fibrosis effect by activating the PPARγ signaling pathway and / or inhibiting the MAPK signaling pathway.

[0028] Advantages and beneficial effects of the present invention: The present invention first discovered that Meconopsis pilosa exerts its anti-liver fibrosis effect by activating the PPARγ signaling pathway and / or inhibiting the MAPK signaling pathway. Based on this, the present invention provides a method, system and device for evaluating the therapeutic effect of Meconopsis pilosa on liver fibrosis in the art, thereby assisting doctors in evaluating the therapeutic effect of liver fibrosis patients and guiding clinicians to formulate individualized treatment plans for patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A schematic flow chart of a method for evaluating the therapeutic effect of Meconopsis pilosula on liver fibrosis provided by the present invention; Figure 2 A schematic diagram of the system structure for evaluating the therapeutic effect of Meconopsis pilosula on liver fibrosis provided by the present invention; Figure 3 A schematic diagram of the structure of a computer device provided by the present invention; Figure 4 Shows the experimental grouping and arrangement of studying the effect of Meconopsis on liver fibrosis; Figure 5It shows that Meconopsis improves CCl4-induced liver fibrosis in mice; Figures A, B, and C show the results of HE staining, Masson and Sirius Red staining, respectively; Figure 6 The results show the effect of Meconopsis pilosula on CCl4-induced liver fibrosis in mice; Figure A shows the liver / body weight ratio of mice; Figure B shows the serum AST, ALT and ALP levels; Figure C shows the mRNA expression levels of ACTA2, TIM and COL1A1; Figure 7 It shows that Meconopsis inhibits liver fibrosis by regulating oxidative stress and inflammatory response; Figure A shows the results of MDA level and SOD activity detection; Figure B shows the results of IL-1β and IL-6 mRNA level detection; Figure 8 The results of transcriptomic analysis are shown; Figures A and B show the differentially expressed genes in the control group, CCl4 treatment group, and Meconopsis treatment group; Fig. 9 The up- and down-regulation of differentially expressed genes in the control group, CCl4 treatment group, and Meconopsis treatment group were shown; Fig.10 Display GO enrichment analysis results; Fig.11 Display KEGG analysis results and verification results; Figure A shows the KEGG analysis results, and Figure B shows the verification results of genes related to retinol metabolism and PPAR signaling pathways; Fig.12 It shows that Meconopsis globulus exerts its anti-liver fibrosis effect by activating PPARγ signaling pathway and inhibiting MAPK signaling pathway; Figure A shows the changes in proteins related to the MAPK signaling pathway, and Figure B shows the changes in proteins in the PPARγ signaling pathway. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0031] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0033] Figure 1 The present invention provides a method for evaluating the therapeutic effect of Meconopsis pilosula on liver fibrosis. Specifically, the method comprises: 101: Obtain data, obtain the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ in samples of patients with liver fibrosis after treatment with Meconopsis pilosula; In some embodiments of the present invention, the applicant has found through extensive and in-depth research that after Meconopsis treated mice with liver fibrosis, the PPARγ signaling pathway of the mice was activated and the MAPK signaling pathway was inhibited, which was specifically manifested in that after Meconopsis treated mice with liver fibrosis, the expression levels of p-MAPK (phosphorylated MAPK), p-ERK (phosphorylated ERK) and p-JNK (phosphorylated JNK) were significantly reduced, while the expression level of PPARγ was significantly increased. This suggests that p-MAPK, p-ERK, p-JNK and PPARγ can be used as good markers to evaluate the therapeutic effect of Meconopsis on liver fibrosis.

[0034] In the present invention, the ERK includes two members, ERK1 and ERK2. ERK1 / 2 has a typical protein kinase structure, which is mainly activated by phosphorylation, and this activation process involves a multi-stage kinase cascade reaction of the MARK signal transduction pathway.

[0035] In some embodiments, the patient can be human or non-human, and can include, for example, animal strains or species used as a "model system" for research purposes. Likewise, patients can include adults or adolescents (e.g., children). In addition, patients can refer to any living organism that benefits from the Meconopsis described herein, preferably mammals (e.g., humans or non-humans). Examples of mammals include, but are not limited to, any member of the class of mammals: humans, non-human primates (e.g., chimpanzees), and other apes and monkeys; livestock, such as cattle, horses, sheep, goats, pigs; domestic animals, such as rabbits, dogs, and cats; experimental animals include rodents, such as rats, mice, and guinea pigs, etc. Examples of non-mammals include, but are not limited to, birds, fish, etc.

[0036] In the context of the present invention, the term "sample" as used herein refers to a composition obtained from or derived from a patient / subject, which contains cells and / or other molecular entities to be characterized and / or identified based on, for example, physical, biochemical, chemical and / or physiological characteristics. For example, a sample refers to any sample derived from a patient / subject that is expected or known to contain cells and / or molecular entities to be characterized. Samples include, but are not limited to, tissue samples, primary or cultured cells or cell lines, cell cultures, cell supernatants, cell lysates, platelets, serum, plasma, vitreous humor, lymphatic fluid, synovial fluid, follicular fluid, semen, pancreatic juice, amniotic fluid, milk, whole blood, blood-derived cells, urine, cerebrospinal fluid, saliva, sputum, tears, sweat, mucus, tissue culture fluid, tissue extracts, homogenized tissues, cell extracts, and combinations thereof. In a specific embodiment of the present invention, the sample is a liver tissue sample.

[0037] In one embodiment of the present invention, we found that Meconopsis pilosa (MEC) can improve CCl4-induced liver fibrosis in mice. First, fresh Meconopsis pilosa was dried in the shade and crushed, and the medicinal materials were extracted three times with 95% ethanol and 50% ethanol respectively, and the extracts were combined and concentrated to obtain an extract. The extract was further dispersed evenly with distilled water, chromatographed with a macroporous resin, and eluted with distilled water and 95% respectively to obtain an active part without polysaccharides. Then, the in vivo hepatoprotective activity of Meconopsis pilosa was studied. C57BL / 6 male mice (20 g; Comparative Medicine Center, Yangzhou University) were raised under standard conditions. The mice were adapted to the environment for 7 days. A total of 40 mice were randomly divided into 5 groups, with 8 mice in each group. The five groups were given olive oil (vehicle, control), CCl4 (model), CCl4+100 mg / kg MEC (Low-MEC), CCl4+400 mg / kg MEC (High-MEC) and CCl4+100 mg / kg RES (RES), respectively. The CCl4 modeling method was to intraperitoneally inject 10% CCl4 (olive oil: CCl4 = 1:9) at a dose of 5 ml / kg twice a week for 6 weeks. At the same time, the drug-treated group was gavaged continuously every day. After the sixth week, blood and liver samples were collected after anesthesia. Part of the liver was fixed with 4% paraformaldehyde, and the rest was quickly frozen with liquid nitrogen. The experimental grouping and plan are as follows Figure 4 shown.

[0038] HE staining showed that MEC significantly improved the morphological changes of CCl4-induced liver fibrosis, such as the reduction of hepatocyte vacuoles and lipid droplets ( Figure 5 A). In addition, Masson and Sirius Red staining results showed that the deposition of collagen fibers was significantly reduced after MEC prevention ( Figure 5 BC). Compared with the CCl4-induced model group, MEC not only made the liver / body weight ratio approach that of the normal group, but also significantly reduced the body weight of the normal group and the experimental group, which may be related to the reduction of lipid accumulation ( Figure 6 A). MEC significantly reduced the levels of three key diagnostic markers used in liver function tests, namely serum AST, ALT, and ALP, indicating that liver function returned to normal ( Figure 6 B). Meanwhile, the MEC prevention group suppressed the mRNA expressions of actin alpha 2 (ACTA2, a marker of muscle fibroblasts), tissue inhibitor of metalloproteinase-1 (TIM, a profibrotic factor), and type I collagen alpha-1 (COL1A1, a fibrotic factor) ( Figure 6 C), These results indicate that MEC improves CCl4-induced liver fibrosis.

[0039] In one embodiment of the present invention, we found that Meconopsis inhibited liver fibrosis by regulating oxidative stress and inhibiting inflammatory response. ROS levels in mice treated with CCl4 were significantly increased, while those in mice treated with MEC were significantly reduced. In addition, MEC reversed the increase in MDA levels and the decrease in SOD activity in the CCl4 group. These data indicate that MEC has significant antioxidant capacity ( Figure 7 A). The mRNA levels of IL-1β and IL-6 in mice treated with CCl4 were significantly increased, while the mRNA expression of proinflammatory factors in mice treated with MEC was inhibited. These results suggest that MEC can reduce liver inflammation and alleviate the development of liver fibrosis in mice ( Figure 7 B).

[0040] Next, we performed transcriptomic analysis. The results of principal component analysis (PCA) showed that samples between groups should be dispersed, and samples within groups were clustered together, indicating that there were more differentially expressed genes (DEGs) among the three groups (CON, CCl4, and High-MEC) ( Figure 8 A). The number of genes differentially expressed between the three groups is shown in the statistical bar graph ( Figure 8 B), heat map and volcano map showed that compared with the normal group, there were 1111 down-regulated genes and 2200 up-regulated genes in the CCl4 group, and compared with the CCl4 group, there were 1273 down-regulated genes and 963 up-regulated genes in the High-MEC group ( Fig. 9 GO analysis of DEGs in the CCl4 vs WT (CON) and MEC (High-MEC) vs CCl4 groups revealed that genes were enriched in biological processes such as cellular processes, responses to stimuli, metabolic processes, biological regulation, biological process regulation, and multicellular biological processes; molecular functions such as binding, catalytic activity, molecular function regulators, molecular transducer activity, and cellular components such as cellular anatomical entities, protein-containing complexes ( Fig.10 ). In particular, the results of GO enrichment analysis showed that the differentially expressed pathways were extracellular matrix, fatty acid metabolic process, and oxidoreductase activity. Consistent with our previous research results, MEC achieves anti-fibrotic effects by regulating the process of ECM, regulates oxidase activity and fatty acid metabolism to reduce oxidative stress, and has the effect of lowering fat and losing weight. In addition, we analyzed 137 genes in three differential pairs (CCl4vs WT, High-MEC vsCCl4, High-MEC vs WT). The results of KEGG analysis showed that DEGs were enriched in the metabolism of substances such as retinol, PPAR, and PI3K-Akt signaling pathways ( Fig.11A). Metabolism, PPAR and PI3K-Akt signaling pathways may be the biological processes by which MEC exerts anti-fibrotic effects and thus alleviates liver fibrosis. We verified genes related to retinol metabolism and PPAR signaling pathways, such as Ehhadh, Angptl4, Cyp4a31, Scd2, Col1a2, Itga6, etc., which are consistent with the experimental results ( Fig.11 B).

[0041] Next, we tested the effect of MEC on the PPARγ / MAPK pathway in mice in the normal group, experimental group, and drug group. The levels of p-MAPK, p-ERK1 / 2, and p-JNK were significantly increased in the CCl4 group. After MEC prevention, the phosphorylation level decreased and was close to the level of the normal group ( Fig.12 A). In addition, the expression of PPARγ in the high MEC group was significantly increased ( Fig.12 B). The results showed that MEC achieved anti-liver fibrosis effect through PPARγ / MAPK signaling pathway.

[0042] 102: Processing data, inputting the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ into a constructed evaluation model, wherein the evaluation model predicts the therapeutic effect of Meconopsis pilosula on patients with liver fibrosis based on the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ; In some embodiments of the present invention, the method of constructing the evaluation model is known to those skilled in the art, and the step of associating the expression level of p-MAPK, p-ERK, p-JNK and / or PPARγ with a certain possibility or risk can be implemented and realized in different ways.

[0043] In the context of the present invention, the term "machine learning" refers to the use of computers to simulate or implement human learning activities, and technicians usually use different development tools to build machine learning algorithm models. The development tools include but are not limited to TensorFlow, Scikit Learn, PyTorch, OpenNN, RapidMiner, Azure Machine Learning, ApacheMahout, Shogun, KNIME, Vertex AI, H2Oai, Anaconda, Keras, Tableau, Fast.ai, Catalyst, Amazon ML, MLJAR, Spell. The algorithm model includes but is not limited to a linear regression model, a logistic regression model, a Lasso regression model, a Ridge regression model, a linear discriminant analysis model, a neighbor model, a decision tree model, a perceptron model, a neural network model, a support vector machine model, a naive Bayes model, an AdaBoost model, a GBDT model, an XGBoost model, a LightGBM model, a CatBoost model, or a random forest model.

[0044] In one embodiment, after the evaluation model is constructed, the performance of the model can be evaluated using ROC curve analysis.

[0045] ROC curve is a graph of the true positive rate (sensitivity) of a test against the false positive rate (100%-specificity) of the test. It is useful for describing the performance of a specific feature when distinguishing between two populations. Typically, feature data is selected across the entire population in ascending order based on the value of a single feature. Then, for each value of the feature, the true positive and false positive rates of the data are calculated. The true positive rate is determined by counting the number of cases with a value higher than the feature and divided by the total number of cases. The false positive rate is determined by counting the number of controls with a value higher than the feature and divided by the total number of controls. Although this definition refers to the case where the feature is increased compared to the control, the definition is also applied to the case where the feature is lower compared to the control (in this case, the sample with a value lower than the feature will be counted). ROC curves can be generated with respect to individual features, and can be generated with respect to other individual outputs, for example, a combination of two or more features can be combined with mathematical methods (e.g., addition, subtraction, multiplication, etc.) to provide a separate sum value, and the separate sum value can be plotted in the ROC curve. Additionally, any combination of multiple features where the combination is derived from separate output values ​​can be plotted in a ROC curve.

[0046] 103: Output results.

[0047] Figure 2 This is a schematic diagram of the system structure provided by the present invention for evaluating the therapeutic effect of Meconopsis on liver fibrosis.

[0048] The system is programmed or otherwise configured to include a data acquisition unit 201, a data classification unit 202, and a result output unit 203: Data acquisition unit: used to obtain the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ in samples of patients with liver fibrosis after treatment with Meconopsis; A data classification unit is used to classify and predict the data obtained by the data acquisition unit through the evaluation model obtained by the construction method described in the first aspect of the present invention, and obtain a classification result of whether Meconopsis is effective in treating patients with liver fibrosis; Result output unit: used to output classification results.

[0049] The system may be the user's electronic device or a computer system located remotely from the electronic device.

[0050] Figure 3 A schematic diagram of the structure of a computer device provided by the present invention.

[0051] The computer device 300 includes a processor 301 and a memory 302 coupled to the processor 301 . The memory 302 stores program instructions. When the program instructions are executed by the processor 301 , the processor 301 executes the above-mentioned method for evaluating the therapeutic effect of Meconopsis on liver fibrosis.

[0052] The processor 301 may also be referred to as a CPU (Central Processing Unit). The processor 301 may be an integrated circuit chip having signal processing capabilities. The processor 301 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0053] The computer device 300 may be a mobile electronic device.

[0054] It should be understood that the systems, devices and methods described in the present invention can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0055] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0056] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0057] The above are only implementation methods of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for evaluating the therapeutic effect of Meconopsis pilosula on liver fibrosis, characterized in that: The method is performed by a computer and comprises the following steps: Obtain data: Obtain the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ in samples of patients with liver fibrosis after treatment with Meconopsis pilosula; Processing data: inputting the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ into a constructed evaluation model, wherein the evaluation model predicts the therapeutic effect of Meconopsis pilosula on patients with liver fibrosis based on the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ; Output the result.

2. The method according to claim 1, characterized in that The steps for constructing the evaluation model are as follows: The expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ are obtained; the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ are obtained from untreated patients with liver fibrosis and patients with liver fibrosis treated with Meconopsis pilosula; the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ are input into a machine learning algorithm to construct an evaluation model.

3. The method according to claim 2, characterized in that The step of constructing the evaluation model also includes verifying the model effectiveness, and the method of verifying the model effectiveness includes ROC curve.

4. The method according to claim 2, characterized in that: The machine learning algorithm includes an algorithm model developed using various development tools; Preferably, the development tools include but are not limited to TensorFlow, Scikit Learn, PyTorch, OpenNN, RapidMiner, Azure Machine Learning, Apache Mahout, Shogun, KNIME, Vertex AI, H2Oai, Anaconda, Keras, Tableau, Fast.ai, Catalyst, Amazon ML, MLJAR, Spell; Preferably, the algorithm model includes but is not limited to a linear regression model, a logistic regression model, a Lasso regression model, a Ridge regression model, a linear discriminant analysis model, a nearest neighbor model, a decision tree model, a perceptron model, a neural network model, a support vector machine model, a naive Bayes model, an AdaBoost model, a GBDT model, an XGBoost model, a LightGBM model, a CatBoost model, and a random forest model.

5. The method according to claim 1, characterized in that The evaluation model obtains results through the following criteria: When the expression levels of any one or several of the p-MAPK, p-ERK, and p-JNK are lower than a threshold value and / or the expression level of the PPARγ is higher than a threshold value, a classification result is obtained that Meconopsis is effective in treating patients with liver fibrosis; when the expression levels of any one or several of the p-MAPK, p-ERK, and p-JNK are higher than a threshold value and / or the expression level of the PPARγ is lower than a threshold value, a classification result is obtained that Meconopsis is ineffective in treating patients with liver fibrosis.

6. A system for evaluating the therapeutic effect of Meconopsis pilosula on liver fibrosis, characterized in that: The system comprises: Data acquisition unit: used to obtain the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ in samples of patients with liver fibrosis after treatment with Meconopsis; Data classification unit: used for classifying and predicting the data obtained by the data acquisition unit through the evaluation model obtained by the construction method described in claims 2-3, and obtaining a classification result of whether Meconopsis is effective in treating patients with liver fibrosis; Result output unit: used to output classification results.

7. A computer device, characterized in that: The device comprises: A memory and a processor, wherein the memory is used to store program instructions; the processor is used to call the program instructions, and when the program instructions are executed, the method for evaluating the therapeutic effect of Meconopsis on liver fibrosis described in any one of claims 1-5 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for evaluating the therapeutic effect of Meconopsis on liver fibrosis according to any one of claims 1 to 5 is implemented.

9. Application of Meconopsis pilosula in the preparation of drugs against liver fibrosis.

10. The use according to claim 9, characterized in that: The Meconopsis pilosula exerts an anti-liver fibrosis effect by activating the PPARγ signaling pathway and / or inhibiting the MAPK signaling pathway.

Images