Method, system and device for evaluating the therapeutic effect of artemisia for hepatic fibrosis based on pparγ expression level

Abstract

The application discloses a method, system and device for evaluating the treatment effect of artemisia on liver fibrosis based on the expression level of PPAR gamma. It is found for the first time that artemisia plays a role in resisting liver fibrosis by activating a PPAR gamma signal path and inhibiting a MAPK signal path. Based on this, the application provides a method, system and device for evaluating the treatment effect of artemisia on liver fibrosis, thereby assisting doctors in evaluating the treatment effect on patients with liver fibrosis and guiding clinicians in formulating individualized treatment plans for patients.

Description

Technical Field

[0001] This invention belongs to the field of bioinformatics. Specifically, this invention relates to a method, system, and device for evaluating the therapeutic effect of Meconopsis on liver fibrosis based on PPARγ expression levels. Background Technology

[0002] Hepatic fibrosis is a compensatory response secondary to tissue repair following liver inflammation or injury from various causes, characterized by excessive deposition of extracellular matrix (ECM) within the liver. Chronic hepatitis C virus (HCV) infection accounts for 50%-85% of cases, with 10%-30% progressing to cirrhosis and 3%-10% developing into liver cancer. Other diseases such as alcoholic liver disease, nonalcoholic steatohepatitis (NASH), autoimmune hepatitis, and primary biliary cirrhosis (PBC) can also lead to hepatic fibrosis and cirrhosis. Since chronic liver diseases from various causes are accompanied by the development of hepatic fibrosis during their course, and uncontrolled progressive hepatic fibrosis eventually leads to cirrhosis and even liver cancer, research into the pathogenesis and drug treatment of hepatic fibrosis is crucial.

[0003] Meconopsis is an annual or perennial herbaceous plant. It exhibits cold resistance by effectively regulating chlorophyll fluorescence parameters at low temperatures, thus its main distribution is in the cold Qinghai-Tibet Plateau region. Famous Chinese medical classics such as *Yuewang Yaozhen*, *Jingzhu Bencao*, *Zangyao Zhi*, and *Sibu Yidian* provide detailed records of it: Meconopsis is characterized by its bitter, astringent, cold nature, and slight toxicity; therefore, it can clear heat and promote diuresis, and enters the large intestine and liver meridians. Clinically, it is used to treat heat syndromes, traumatic injuries, and chest and back pain. Studies have reported that Meconopsis has anti-tumor, anti-hepatitis, and myocardial infarction-relieving effects, but the mechanism by which it exerts its anti-liver fibrosis effect has not yet been reported. Summary of the Invention

[0004] To overcome the shortcomings of the prior art, the purpose of this invention is to provide a method, system, and apparatus for evaluating the therapeutic effect of Meconopsis on liver fibrosis.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] The first aspect of this invention provides a method for evaluating the therapeutic effect of Meconopsis on liver fibrosis.

[0007] Furthermore, the method is performed by a computer, and the method includes the following steps:

[0008] Data Acquisition: Obtain expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ in liver fibrosis patient samples after treatment with Meconopsis.

[0009] Data processing: The expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ are input into the constructed evaluation model, which predicts the therapeutic effect of Meconopsis on patients with liver fibrosis based on the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ.

[0010] Output results.

[0011] Furthermore, p-MAPK, p-ERK, and p-JNK refer to phosphorylated MAPK, phosphorylated ERK, and phosphorylated JNK, respectively.

[0012] Furthermore, the expression data for p-MAPK, p-ERK, p-JNK, and / or PPARγ include mRNA expression level data and protein expression level data.

[0013] Furthermore, the mRNA expression level data includes, but is not limited to, data obtained by RT-PCR, qRT-PCR, in situ hybridization, and RNA sequencing.

[0014] Furthermore, the protein expression level data includes, but is not limited to, data obtained by immunoblotting, immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), and mass spectrometry.

[0015] Furthermore, the construction steps of the evaluation model are as follows:

[0016] Expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ were obtained; the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ were obtained from untreated liver fibrosis patients and liver fibrosis patients treated with Artemisia annua; the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ were input into a machine learning algorithm to construct an evaluation model.

[0017] Preferably, the evaluation model construction step further includes verifying model effectiveness, and the method for verifying model effectiveness includes ROC curves.

[0018] Furthermore, the machine learning algorithm includes algorithmic models developed using various development tools.

[0019] 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.

[0020] Preferably, the algorithm model includes, but is not limited to, linear regression model, logistic regression model, Lasso regression model, Ridge regression model, linear discriminant analysis model, nearest neighbor model, decision tree model, perceptron model, neural network model, support vector machine model, Naive Bayes model, AdaBoost model, GBDT model, XGBoost model, LightGBM model, CatBoost model, and random forest model.

[0021] Furthermore, the evaluation model obtains results using the following criteria:

[0022] When the expression levels of any one or more of p-MAPK, p-ERK, and p-JNK are below a threshold and / or the expression level of PPARγ is above a threshold, a classification result is obtained indicating that *Meconopsis* is effective in treating patients with liver fibrosis; when the expression levels of any one or more of p-MAPK, p-ERK, and p-JNK are above a threshold and / or the expression level of PPARγ is below a threshold, a classification result is obtained indicating that *Meconopsis* is ineffective in treating patients with liver fibrosis.

[0023] In some embodiments of the present invention, the preset threshold is a representative value of normal liver fibrosis samples, including but not limited to the maximum value, the third quartile, and the mean. In some preferred embodiments of the present invention, the population sample includes 20 or more samples, such as 30, 50, 80, 100, 150, 200, 300, 500, or more.

[0024] Furthermore, the patients include humans and / or mammals.

[0025] Furthermore, the sample includes blood and / or tissue.

[0026] A second aspect of the present invention provides a system for evaluating the therapeutic effect of Meconopsis on liver fibrosis.

[0027] Furthermore, the system includes:

[0028] Data acquisition unit: used to acquire expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ in liver fibrosis patient samples after treatment with Meconopsis.

[0029] Data classification unit: used to classify and predict whether the data obtained by the data acquisition unit is effective in treating patients with liver fibrosis by using the evaluation model obtained by the construction method described in the first aspect of the present invention;

[0030] Result output unit: Used to output classification results.

[0031] A third aspect of the present invention provides a computer device.

[0032] Furthermore, the device includes:

[0033] The invention includes a memory and a processor, wherein the memory stores program instructions, and the processor invokes the program instructions to implement, when executed, the method for evaluating the therapeutic effect of *Meconopsis* on liver fibrosis as described in the first aspect of the invention.

[0034] A fourth aspect of the present invention provides a computer-readable storage medium.

[0035] Furthermore, the computer-readable storage medium stores a computer program that, when executed by a processor, implements the method for evaluating the therapeutic effect of Meconopsis on liver fibrosis as described in the first aspect of the present invention.

[0036] The fifth aspect of this invention provides the use of Meconopsis in the preparation of drugs for treating liver fibrosis.

[0037] Furthermore, the *Meconopsis* species exerts its anti-liver fibrosis effect by activating the PPARγ signaling pathway and / or inhibiting the MAPK signaling pathway.

[0038] Advantages and beneficial effects of the present invention:

[0039] This invention is the first to discover that *Meconopsis* exerts its anti-liver fibrosis effect by activating the PPARγ signaling pathway and / or inhibiting the MAPK signaling pathway. Based on this, this invention provides a method, system, and device for evaluating the therapeutic effect of *Meconopsis* on liver fibrosis, thereby assisting physicians in evaluating the treatment efficacy for patients with liver fibrosis and guiding clinicians in developing individualized treatment plans for patients. Attached Figure Description

[0040] Figure 1 This is a schematic flowchart of the method for evaluating the therapeutic effect of Meconopsis on liver fibrosis provided by the present invention.

[0041] Figure 2 A schematic diagram of the system structure provided by this invention for evaluating the therapeutic effect of Meconopsis on liver fibrosis;

[0042] Figure 3 A schematic diagram of the structure of the computer device provided by the present invention;

[0043] Figure 4 This shows the experimental grouping and arrangement for studying the effect of Meconopsis on liver fibrosis;

[0044] Figure 5 The image shows that Meconopsis ameliorate improves CCl4-induced liver fibrosis in mice; Figures A, B, and C show the results of HE staining, Masson staining, and Sirius Red staining, respectively.

[0045] Figure 6 This figure shows the effect of Meconopsis on CCl4-induced liver fibrosis in mice; Figure A shows the liver / body weight ratio in mice; Figure B shows the serum AST, ALT, and ALP levels; and Figure C shows the mRNA expression levels of ACTA2, TIM, and COL1A1.

[0046] Figure 7 The results show 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.

[0047] Figure 8 The transcriptomics analysis results are shown; Figures A and B show differentially expressed genes in the control group, CCl4 treatment group, and Meconopsis treatment group.

[0048] Figure 9 The differentially expressed gene up- and down-regulation status was shown in the control group, CCl4 treatment group, and Meconopsis treatment group.

[0049] Figure 10 Showing the GO enrichment analysis results;

[0050] Figure 11 The results of KEGG analysis and validation are shown; Figure A shows the results of KEGG analysis, and Figure B shows the validation results of genes related to retinol metabolism and PPAR signaling pathway.

[0051] Figure 12 The study showed that Meconopsis exerts its anti-liver fibrosis effect by activating the PPARγ signaling pathway and inhibiting the MAPK signaling pathway; Figure A shows the changes in MAPK signaling pathway-related proteins, and Figure B shows the changes in PPARγ signaling pathway proteins. Detailed Implementation

[0052] To enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0053] In some of the processes described in the specification, claims, and accompanying drawings of this invention, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to different types.

[0054] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] Figure 1 This is a schematic flowchart of a method for evaluating the therapeutic effect of *Meconopsis* on liver fibrosis provided by the present invention. Specifically, the method includes:

[0056] 101: Obtain data to acquire expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ in liver fibrosis patient samples after treatment with Artemisia annua;

[0057] In some embodiments of this invention, the applicant, through extensive and in-depth research, discovered that after treating mice with liver fibrosis with *Meconopsis*, the PPARγ signaling pathway was activated and the MAPK signaling pathway was inhibited. Specifically, 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 serve as good biomarkers for evaluating the therapeutic effect of *Meconopsis* on liver fibrosis.

[0058] In this invention, the ERK includes two members, ERK1 and ERK2. ERK1 / 2 have typical protein kinase structures and are mainly activated by phosphorylation, a process involving a multi-level kinase cascade reaction in the MARK signaling pathway.

[0059] In some embodiments, the patient may be human or non-human and may include, for example, animal strains or species used as a "model system" for research purposes. Similarly, the patient may include adults or adolescents (e.g., children). Furthermore, the patient may refer to any living organism that benefits from the *Meconopsis* described herein, preferably a mammal (e.g., human or non-human). Examples of mammals include, but are not limited to, any member of the mammalian class: humans, non-human primates (e.g., chimpanzees) and other apes and monkeys; livestock, such as cattle, horses, sheep, goats, and pigs; domestic animals, such as rabbits, dogs, and cats; and laboratory animals including rodents, such as rats, mice, and guinea pigs. Examples of non-mammals include, but are not limited to, birds, fish, etc.

[0060] In the context of this invention, the term "sample" as used refers to a composition obtained from or derived from a patient / subject that 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 fluid, lymph, 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 tissue, cell extracts, and combinations thereof. In a specific embodiment of this invention, the sample is a liver tissue sample.

[0061] In one embodiment of the present invention, we found that *Meconopsis* (MEC) can improve CCl4-induced liver fibrosis in mice. First, fresh *Meconopsis* herbs were air-dried and pulverized. The herbs were extracted three times each with 95% ethanol and 50% ethanol, respectively. The extracts were combined and concentrated to obtain an extract. The extract was further dispersed evenly with distilled water and subjected to macroporous resin chromatography. The extract was eluted with distilled water and 95% ethanol in fractional fractions to obtain the polysaccharide-free active fraction. Next, the hepatoprotective activity of *Meconopsis* in vivo was studied. C57BL / 6 male mice (20 g; Yangzhou University Comparative Medicine Center) were housed under standard conditions. The mice were acclimatized for 7 days. A total of 40 mice were randomly divided into 5 groups of 8 mice each. The five groups were administered olive oil (carrier, 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 model was established by intraperitoneal injection of 10% CCl4 (olive oil:CCl4 = 1:9) twice weekly for 6 weeks. Simultaneously, the treatment group received daily gavage. After the sixth week, blood and liver samples were collected under anesthesia. A portion of the liver was fixed with 4% paraformaldehyde, and the remainder was flash-frozen in liquid nitrogen. Experimental grouping and planning are as follows: Figure 4 As shown.

[0062] 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). Furthermore, Masson and Sirius Red staining results showed that collagen fiber deposition was significantly reduced after MEC prevention ( Figure 5 BC). Compared with the CCl4-induced model group, MEC not only brought the liver / body weight ratio closer to the normal group, but also significantly reduced the body weight of both the normal and experimental groups, which may be related to reduced 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 a return to normal liver function ( Figure 6 B). Simultaneously, the MEC prevention group suppressed the mRNA expression of actin α2 (ACTA2, a marker of muscle fibroblasts), tissue inhibitor of metalloproteinase-1 (TIM, a pro-fibrotic factor), and type I collagen α-1 (COL1A1, a fibrotic factor). Figure 6 These results indicate that MEC improves CCl4-induced liver fibrosis.

[0063] In one embodiment of the invention, we found that *Meconopsis* inhibits liver fibrosis by modulating oxidative stress and suppressing inflammatory responses. ROS levels were significantly increased in mice treated with CCl4, while ROS levels were significantly decreased in mice treated with MEC. Furthermore, 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). CCl4 treatment significantly increased the mRNA levels of IL-1β and IL-6 in mice, while MEC treatment suppressed the mRNA expression of pro-inflammatory factors. These results indicate that MEC can alleviate liver inflammation and slow the progression of liver fibrosis in mice. Figure 7 B).

[0064] Next, we performed transcriptomic analysis. Principal component analysis (PCA) results showed that samples were dispersed between groups and clustered within groups, indicating a greater number of differentially expressed genes (DEGs) among the three groups (CON, CCl4, and High-MEC). Figure 8 A). The number of differentially expressed genes among the three groups is shown in the statistical bar chart ( Figure 8 B), heatmaps and volcano plots show that, compared to the normal group, the CCl4 group had 1111 downregulated genes and 2200 upregulated genes, while the High-MEC group had 1273 downregulated genes and 963 upregulated genes compared to the CCl4 group. Figure 9 GO analysis of DEGs from the CCl4 and WT (CON) and MEC (High-MEC) and CCl4 groups revealed enrichment of genes in various biological processes, including cellular processes, responses to stimuli, metabolic processes, biological regulation, biological process regulation, and multicellular biological processes; molecular functions, such as binding, catalytic activity, molecular functional regulators, molecular transducer activity; and cellular components, such as cellular anatomical entities and protein-containing complexes. Figure 10 In particular, GO enrichment analysis revealed differentially expressed pathways including the extracellular matrix, fatty acid metabolism, and oxidoreductase activity. Consistent with our previous findings, MEC exerts its anti-fibrotic effect by regulating ECM processes, modulating oxidase activity and fatty acid metabolism to reduce oxidative stress, thus exhibiting lipid-lowering and weight-loss effects. Furthermore, we analyzed 137 genes in three differentially expressed pairs (CCl4 vs WT, High-MEC vs CCl4, High-MEC vs WT). KEGG analysis showed that DEGs were enriched in the metabolism of substances such as retinol, PPAR, and the PI3K-Akt signaling pathway. Figure 11A). Metabolism, PPAR, and the PI3K-Akt signaling pathway may be the biological processes by which MEC exerts its anti-fibrotic effect and thus alleviates liver fibrosis. We validated genes associated with retinol metabolism and the PPAR signaling pathway, such as Ehhadh, Angptl4, Cyp4a31, Scd2, Col1a2, and Itga6, which were consistent with our experimental results. Figure 11 B).

[0065] Next, we tested the effects of MEC on the PPARγ / MAPK pathway in mice in the normal, experimental, and drug-treated groups. The levels of p-MAPK, p-ERK1 / 2, and p-JNK were significantly increased in the CCl4 group. After MEC prevention, phosphorylation levels decreased, approaching the levels of the normal group. Figure 12 A). Furthermore, PPARγ expression was significantly increased in the high MEC group ( Figure 12 B). The results showed that MEC exerts its anti-liver fibrosis effect through the PPARγ / MAPK signaling pathway.

[0066] 102: Process the data by inputting the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ into the constructed evaluation model, which predicts the therapeutic effect of Meconopsis on patients with liver fibrosis based on the expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ.

[0067] In some embodiments of the present invention, the methods for constructing the evaluation model are known to those skilled in the art, and the steps of associating the expression levels of p-MAPK, p-ERK, p-JNK and / or PPARγ with a certain probability or risk can be implemented and realized in different ways.

[0068] In the context of this invention, the term "machine learning" refers to the use of computers to simulate or implement human learning activities. Technicians typically use various development tools to build machine learning algorithmic models. These 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. The algorithmic models include, but are not limited to, linear regression models, logistic regression models, Lasso regression models, Ridge regression models, linear discriminant analysis models, nearest neighbor models, decision tree models, perceptron models, neural network models, support vector machine models, Naive Bayes models, AdaBoost models, GBDT models, XGBoost models, LightGBM models, CatBoost models, or random forest models.

[0069] In one embodiment, after constructing the evaluation model, the effectiveness of the model can be evaluated using ROC curve analysis.

[0070] An ROC curve is a graph of the true positive rate (sensitivity) versus the false positive rate (100% specificity) of an experiment. It is useful for depicting the performance of a specific characteristic when distinguishing between two populations. Typically, characteristic data are selected across the entire population in ascending order based on the values ​​of a single characteristic. Then, for each value of that characteristic, 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 values ​​higher than the characteristic value and dividing by the total number of cases. The false positive rate is determined by counting the number of controls with values ​​higher than the characteristic value and dividing by the total number of controls. While this definition refers to cases where the characteristic is higher in cases compared to controls, it also applies to cases where the characteristic is lower in cases compared to controls (in which case samples with values ​​lower than the characteristic value are counted). ROC curves can be generated with respect to individual characteristics and can also be generated with respect to other individual outputs. For example, combinations of two or more characteristics can be mathematically combined (e.g., addition, subtraction, multiplication, etc.) to provide individual sum values ​​that can be plotted on the ROC curve. Furthermore, any combination of multiple features derived from individual output values ​​can be plotted on a ROC curve.

[0071] 103: Output results.

[0072] 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.

[0073] 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.

[0074] Data acquisition unit: used to acquire expression data of p-MAPK, p-ERK, p-JNK and / or PPARγ in liver fibrosis patient samples after treatment with Meconopsis.

[0075] Data classification unit: used to classify and predict whether the data obtained by the data acquisition unit is effective in treating patients with liver fibrosis by using the evaluation model obtained by the construction method described in the first aspect of the present invention;

[0076] Result output unit: Used to output classification results.

[0077] The system may be a user's electronic device or a computer system remotely located relative to that electronic device.

[0078] Figure 3 A schematic diagram of the structure of the computer device provided by the present invention.

[0079] 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 performs the method described above for evaluating the therapeutic effect of Meconopsis on liver fibrosis.

[0080] The processor 301 can also be referred to as a CPU (Central Processing Unit). The processor 301 may be an integrated circuit chip with signal processing capabilities. The processor 301 can 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, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0081] Computer device 300 can be a mobile electronic device.

[0082] It should be understood that the systems, apparatuses, and methods described in this invention can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections between devices or modules through some interfaces, and may be electrical, mechanical, or other forms.

[0083] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0084] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0085] The above are merely embodiments of this application and do not limit the scope of this patent application. Any equivalent structural or procedural changes made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of this application.

Claims

1. A method for evaluating the therapeutic effect of *Meconopsis* on liver fibrosis, characterized in that, The method is performed by a computer and includes the following steps: Data Acquisition: Obtain expression data of p-MAPK, p-ERK, p-JNK, and PPARγ in liver fibrosis patient samples after treatment with Meconopsis. Data processing: The expression data of p-MAPK, p-ERK, p-JNK and PPARγ are input into the constructed evaluation model, which predicts the therapeutic effect of Meconopsis on patients with liver fibrosis based on the expression data of p-MAPK, p-ERK, p-JNK and PPARγ. Output results; The evaluation model was constructed by inputting the expression data of p-MAPK, p-ERK, p-JNK, and PPARγ from untreated liver fibrosis patients and liver fibrosis patients treated with Meconopsis into a machine learning algorithm.

2. The method according to claim 1, characterized in that, The evaluation model construction steps also include verifying model effectiveness, and the method for verifying model effectiveness includes plotting ROC curves.

3. The method according to claim 1, characterized in that, The machine learning algorithm is a linear regression model, logistic regression model, linear discriminant analysis model, nearest neighbor model, perceptron model, support vector machine model, naive Bayes model, AdaBoost model, GBDT model, XGBoost model, LightGBM model, CatBoost model, or random forest model.

4. A system for evaluating the therapeutic effect of *Meconopsis* on liver fibrosis, characterized in that, The system is used to implement the method for evaluating the therapeutic effect of *Meconopsis* on liver fibrosis as described in any one of claims 1-3, the system comprising: Data acquisition unit: Acquire expression data of p-MAPK, p-ERK, p-JNK and PPARγ in liver fibrosis patient samples after treatment with Meconopsis. Data classification unit: The expression data of p-MAPK, p-ERK, p-JNK and PPARγ are input into the constructed evaluation model, which predicts the therapeutic effect of Meconopsis on patients with liver fibrosis based on the expression data of p-MAPK, p-ERK, p-JNK and PPARγ. Result output unit: Used to output classification results; The evaluation model was constructed by inputting the expression data of p-MAPK, p-ERK, p-JNK, and PPARγ from untreated liver fibrosis patients and liver fibrosis patients treated with Meconopsis into a machine learning algorithm.

5. A computer device, characterized in that, The device includes: A memory and a processor, wherein the memory is used to store program instructions; and the processor is used to invoke the program instructions, which, when executed, implement the method for evaluating the therapeutic effect of *Meconopsis* on liver fibrosis as described in any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method for evaluating the therapeutic effect of Meconopsis on liver fibrosis as described in any one of claims 1-3.

Images