Inflammatory bowel disease model, construction method and application thereof, and drug evaluation method based on inflammatory bowel disease model

Abstract

The invention discloses an inflammatory bowel disease model, a construction method and application thereof and a drug evaluation method based on the inflammatory bowel disease model, and belongs to the technical field of inflammatory bowel disease model construction. A highly bionic intestinal crypt-villus three-dimensional structure is formed based on self-organization of an intestinal cell line C2BBe1, the intestinal crypt-villus three-dimensional structure and a DMEM complete medium containing dextran sulfate sodium are added into an upper chamber of a double-layer culture chamber Transwell, the DMEM complete medium is added into a lower chamber of the double-layer culture chamber Transwell, culture is performed for 2 days, and the inflammatory bowel disease model is obtained. The method takes effect quickly and is highly simulated, the obtained model can simulate the space-time dynamic development process of intestinal inflammation molecular characteristics, and the natural recovery model and the drug treatment model constructed based on the model can provide a brand new platform for researching an inflammation regression mechanism and a drug intervention effect.

Description

Technical Field

[0001] The present invention belongs to the technical field of constructing inflammatory bowel disease models, and particularly relates to an inflammatory bowel disease model, a method for constructing the same, an application thereof, and a method for evaluating drugs based on the same. Background Art

[0002] Inflammatory Bowel Disease (IBD), as a complex chronic intestinal inflammatory disease, has seen a continuous increase in incidence in recent years. It mainly includes Crohn's Disease (CD) and Ulcerative Colitis (UC), characterized by recurrent intestinal inflammation. It not only seriously damages the quality of life of patients but also brings a huge socio-economic burden to the medical system. The pathogenesis of IBD involves a multi-factor, multi-level complex regulatory network, including immune system disorders, intestinal microbiota dysbiosis, genetic susceptibility, and the interaction of environmental factors, which makes the study of its pathological mechanism extremely challenging. In this context, constructing an efficient and reliable in vitro IBD model is of irreplaceable significance for revealing the occurrence and development mechanism of the disease, screening new therapeutic targets, and evaluating the efficacy and safety of clinical drugs.

[0003] Currently, IBD research and its drug screening mainly rely on two major systems: animal models and cell models. Animal models, especially mouse and rat models, have long been widely used to simulate the pathological characteristics of IBD. These models are mainly constructed by chemical induction (such as using chemical substances like Dextran Sulfate Sodium (DSS), 2,4,6-Trinitrobenzenesulfonic Acid (TNBS), etc.) or genetic engineering means. Chemical induction models can simulate the dynamic process of inflammation to a certain extent, while genetic engineering models provide a powerful tool for studying the role of specific genes in the disease. At the same time, with the rapid development of cell biology and tissue engineering technologies, cell models have gradually become an emerging platform for IBD research. From traditional 2D cell lines to the rapidly developing 3D organoid models in recent years, these in vitro systems show great potential in simulating the intestinal microenvironment, studying cell-cell interactions, and high-throughput drug screening, providing a more accurate and efficient tool for IBD research.

[0004] Although significant progress has been made in the construction of in vitro models in the field of IBD research, existing models still have many limitations, severely restricting the depth and breadth of research: (1) Due to the essential differences in gene expression, physiological mechanisms, and immune responses between species, the research results based on animal experiments are difficult to directly extrapolate to humans. In addition, the construction process of animal models is complex and time-consuming. During the modeling process, individual animals are uncontrollable, and it often takes a large amount of time and resources to obtain data from the model establishment to data acquisition. This not only increases the research cost but also seriously affects the research efficiency, making it difficult to meet the rapidly developing medical research needs. (2) Although traditional 2D cell models have the advantages of simple operation and stable sources, they lack a three-dimensional spatial structure, cannot truly simulate the complex microenvironment of the human intestine, and cannot be stably cultured for a long time, greatly limiting their application value in IBD research. (3) Although new cell models such as organoids have made breakthrough progress in simulating the three-dimensional structure of the intestine, due to technical bottlenecks such as limited culture conditions, closed lumen structures, and insufficient oxygen supply methods, it is difficult to achieve long-term stable culture, thus unable to meet the needs of long-term IBD research. In addition, although intestinal chip technology shows great potential, its complex structural design and microscopic scale limitations pose many challenges to its application in disease simulation. All of the above models have a common problem, that is, they cannot achieve long-term stable culture, are difficult to simulate the molecular spatio-temporal heterogeneity during the occurrence and development of IBD with high resolution in real time, and cannot comprehensively reflect the tissue repair process after inflammation subsides, which greatly limits the in-depth understanding of the dynamic pathological mechanism of IBD by researchers. Therefore, developing a new model with simple operation, short cycle, and capable of accurately simulating the spatio-temporal microenvironment of human IBD has become an urgent need to promote breakthrough progress in this field. Such a model should have the characteristics of long-term stable culture, high-resolution spatio-temporal simulation, and multi-dimensional parameters for drug evaluation, so as to provide a more reliable research platform for in-depth analysis of the pathogenesis of IBD, screening potential therapeutic targets, and evaluating drug efficacy. Summary of the Invention

[0005] In order to overcome the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide an inflammatory bowel disease model, its construction method, application, and a drug evaluation method based on it, so as to solve the technical problems that existing in vitro models cannot maintain long-term stable culture and drug treatment, and cannot accurately simulate the spatio-temporal molecular characteristics of human IBD.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions:

[0007] In the first aspect of the present invention, a method for constructing an inflammatory bowel disease model is disclosed. Add a three-dimensional intestinal crypt-villus structure and DMEM complete medium containing sodium dextran sulfate to the upper chamber of a Transwell double-layer culture chamber, and add DMEM complete medium to the lower chamber, and culture for 2 days to obtain an inflammatory bowel disease model.

[0008] Further, in the DMEM complete medium containing sodium dextran sulfate, the content of sodium dextran sulfate is 2%.

[0009] In the second aspect of the present invention, an inflammatory bowel disease model obtained by the above construction method is disclosed.

[0010] In the third aspect of the present invention, a method for constructing an inflammatory bowel disease recovery model is disclosed. After obtaining an inflammatory bowel disease model according to the above construction method, wash the inflammatory bowel disease model, remove the liquid in the upper chamber, and add DMEM complete medium to the lower chamber and culture for 5 days to obtain an inflammatory bowel disease recovery model.

[0011] In the fourth aspect of the present invention, an inflammatory bowel disease recovery model obtained by the above construction method is disclosed.

[0012] In the fifth aspect of the present invention, a method for constructing an inflammatory bowel disease treatment model is disclosed. After obtaining an inflammatory bowel disease model according to the above construction method, wash the inflammatory bowel disease model, remove the liquid in the upper chamber, add an inflammatory bowel disease treatment drug to the upper chamber, and add DMEM complete medium to the lower chamber and culture for 1 to 5 days to obtain an inflammatory bowel disease treatment model.

[0013] In the sixth aspect of the present invention, an inflammatory bowel disease treatment model obtained by the above construction method is disclosed.

[0014] In the seventh aspect of the present invention, the application of the above inflammatory bowel disease model, inflammatory bowel disease recovery model or inflammatory bowel disease treatment model in the study of the pathogenesis of inflammatory bowel disease, the study of treatment targets for inflammatory bowel disease or the screening of drugs for inflammatory bowel disease is disclosed.

[0015] In the eighth aspect of the present invention, a method for evaluating drugs for treating inflammatory bowel disease is disclosed, including the following steps:

[0016] Step 1: Respectively extract the structural characteristics and functional characteristics of healthy intestinal model tissues, the inflammatory bowel disease model tissues described in claim 2, and the inflammatory bowel disease treatment model tissues described in claim 6, and respectively calculate the weights of the structural characteristics and functional characteristics of each tissue to obtain a weight calculation result;

[0017] Step 2: According to the structural and functional characteristics of the healthy intestinal model tissue, the inflammatory bowel disease model tissue described in claim 2, and the inflammatory bowel disease treatment model tissue described in claim 6, calculate the similarity of the structural and functional characteristics between the inflammatory bowel disease treatment model tissue and the healthy intestinal model tissue or the inflammatory bowel disease model tissue, and obtain the similarity calculation result;

[0018] Step 3: Integrate the weight calculation result in Step 1 and the similarity calculation result in Step 2, calculate the weighted F1 score of the structural and functional characteristics of each tissue, and obtain the evaluation result of the efficacy of drugs for treating inflammatory bowel disease.

[0019] Preferably, the entropy weight method is used to calculate the objective weights of the structural and functional characteristics, and combined with the subjective weighting of experts, the weight calculation result is comprehensively obtained.

[0020] In the ninth aspect of the present invention, the application of the evaluation method in the screening of drugs for inflammatory bowel disease is disclosed.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] The method for constructing an inflammatory bowel disease model provided by the present invention uses dextran sulfate sodium (DSS) to treat the intestinal crypt-villus three-dimensional structure to obtain an inflammatory bowel disease model, which has a fast effect and high simulation. It only takes 2 days to complete the transformation of the tissue from a healthy state to an inflammatory state. Through multi-dimensional experimental verification (TEER, immunofluorescence, qPCR, Western Blot, and transcriptome sequencing), it is confirmed that this model can accurately simulate the situation of inflammatory bowel disease in real human bodies (simulating the whole process of intestinal barrier damage, inflammatory response, and signal pathway activation), and has the characteristic of high simulation. By using this model to evaluate the therapeutic effects of clinical positive drugs Tofacitinib and Upadacitinib, it is found that Upadacitinib performs optimally in terms of structural repair and inflammation inhibition, which is highly consistent with the clinical observation results. Through immunofluorescence, qPCR, and Western Blot experiments, it is proved that regardless of natural recovery or drug treatment, the survival time of damaged tissues in the IBD model is greater than 5 days. Therefore, this inflammatory bowel disease model has good stability and high repeatability, and can be used as a powerful tool for the study of the pathogenesis of inflammatory bowel disease, drug screening, and preclinical evaluation, and has important scientific significance and clinical application prospects.

[0023] The method for constructing an inflammatory bowel disease recovery model provided by the present invention, on the basis of the inflammatory bowel disease model, reveals the asynchronous phenomenon of structural repair and immune response recovery during the IBD recovery process by systematically evaluating the dynamic process of intestinal structure repair and inflammation regression, providing a new experimental tool for in-depth study of the pathological mechanism of IBD and the effect of drug intervention.

[0024] The evaluation method of drugs for treating inflammatory bowel disease provided by the present invention obtains the weight calculation result by quantifying structural features (such as height, width, curvature, etc.) and functional features (such as protein distribution, transcriptome data, etc.), so as to determine the weight of the structural or functional parameters of each group of tissues in the overall, and then evaluate the importance of the structural or functional parameters; by obtaining the similarity calculation result, to determine the similarity level between the structural or functional parameters of the inflammatory bowel disease treatment model tissue itself and the healthy intestinal model tissue or the inflammatory bowel disease model tissue, and comprehensively considering the weight calculation result and the similarity calculation result, thus constructing a scientific, comprehensive and multi-dimensional drug efficacy evaluation model for treating inflammatory bowel disease. This system can intuitively reflect the treatment effects of different drugs and provide an efficient and reliable scheme for drug screening and preclinical evaluation.

[0025] Furthermore, in the process of weight calculation, the entropy weight method and expert subjective weighting are integrated, which can ensure that the evaluation result has both the objectivity driven by data and the experience judgment of domain experts. Brief Description of the Drawings

[0026] Figure 1 It is a flowchart of the method for constructing an inflammatory bowel disease model and evaluating drugs of the present invention;

[0027] Figure 2 It is a graph of the evaluation results of the inflammatory bowel disease model of the present invention; among them, a. teer value, b. immunofluorescence result, c. RT-PCR result, d. western blot result, e. A10D2 KEGG enrichment result, f. gene comparison between IBD model, clinical samples and mouse disease model, g. KEGG enrichment result of IBD model and clinical samples, UC-patients represents the clinical data of IBD patients, and UC-mice represents the mouse IBD treatment data;

[0028] Figure 3 It is a graph of the evaluation results of the natural recovery model of inflammatory bowel disease of the present invention; among them, a. immunofluorescence result, b. RT-PCR result, c. western blot result, d. western blot result statistics, e. pro-inflammatory factor expression, f. anti-inflammatory factor expression;

[0029] Figure 4 It is a graph of the results of treating the inflammatory bowel disease model with the positive drug Tofacitinib; among them, a. immunofluorescence result, b. q-PCR result, c. Western Blot result, with GAPDH as the internal reference;

[0030] Figure 5It is the result diagram of treating the inflammatory bowel disease model with the positive drug Upadacitinib; among them, a. immunofluorescence result, b. q-PCR result, c. Western Blot result, with GAPDH as the internal reference;

[0031] Figure 6 It is the result diagram of multi-dimensional pharmacodynamic evaluation; among them, a. the weight calculation result of structural characteristics, b. the weight calculation result of functional characteristics; c. the scoring result of similarity calculation; d. the comprehensive scoring result of structure and function. Detailed implementation manners

[0032] To enable those skilled in the art to understand the features and effects of the present invention, the following only gives a general description and definition of the terms and expressions mentioned in the specification and claims. Unless otherwise specified, all technical and scientific terms used herein shall have the ordinary meaning understood by those skilled in the art for the present invention. When there is a conflict, the definition in this specification shall prevail.

[0033] The theories or mechanisms described and disclosed herein, whether right or wrong, shall not limit the scope of the present invention in any way, that is, the content of the present invention can be implemented without being limited by any specific theory or mechanism.

[0034] In this article, all features defined in the form of numerical ranges or percentage ranges, such as numerical values, quantities, contents, and concentrations, are only for the sake of brevity and convenience. Accordingly, the description of numerical ranges or percentage ranges should be regarded as having covered and specifically disclosed all possible sub-ranges and individual numerical values (including integers and fractions) within the range.

[0035] In this article, unless otherwise specified, the terms "comprising", "including", "containing", "having" or similar expressions cover the meanings of "consisting of" and "consisting essentially of". For example, "A comprises a" covers the meanings of "A comprises a and others" and "A only comprises a".

[0036] In this article, for the sake of brevity of description, all possible combinations of all technical features in each embodiment or example are not described. Therefore, as long as there is no contradiction in the combination of these technical features, the technical features in each embodiment or example can be combined arbitrarily, and all possible combinations should be considered as the scope described in this specification.

[0037] Based on the previously induced intestinal cell line C2BBe1 that self-organizes into a highly biomimetic intestinal crypt-villus three-dimensional structure, by adding 2% sodium dextran sulfate (DSS), inflammation can occur within 2 to 6 hours, and a rapid-onset and highly realistic inflammatory bowel disease (IBD) model can be obtained after 2 days of culture. This model can simulate the spatio-temporal dynamic development process of the molecular characteristics of intestinal inflammation. Based on this, we respectively constructed an IBD natural recovery model and a drug treatment model, providing a new platform for studying the mechanism of inflammation resolution and the effect of drug intervention.

[0038] The present invention also provides a method for evaluating drugs for treating inflammatory bowel disease. By quantitatively scoring the key indicators of the structure and function of the IBD model and the IBD natural recovery model before and after drug administration, the therapeutic effects of different drugs can be intuitively reflected, realizing a comprehensive evaluation of intestinal health and pathological states, and providing an efficient and reliable screening scheme for drug research and development and preclinical evaluation. This breakthrough not only provides an in vitro model closer to human physiology for IBD research, but also opens up a new research direction for drug screening and the optimization of personalized treatment strategies, with important scientific significance and clinical application value.

[0039] The following combines Figure 1 with specific embodiments to further elaborate the present invention. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of this application.

[0040] Conventional instrument equipment in the art is used in the following embodiments. For the experimental methods without specific conditions noted in the following embodiments, they are usually carried out according to conventional conditions or according to the conditions recommended by the manufacturer. Various raw materials are used in the following embodiments. Unless otherwise stated, commercially available products with conventional specifications in the art are used.

[0041] Example 1

[0042] I. Construction of an inflammatory bowel disease model

[0043] 1. Culture of the intestinal crypt-villus three-dimensional structure

[0044] Construct the intestinal crypt-villus three-dimensional structure according to the Chinese published patent CN118703421A, a method for in vitro self-organization to form an intestinal crypt-villus three-dimensional structure and its application.

[0045] 1) The first stage: Add 500 μL of complete DMEM medium (high-glucose DMEM containing 10% serum and 1% double antibody) to the lower chamber of the Transwell double-layer culture chamber, add 200 μL of complete DMEM medium to the upper chamber of the Transwell double-layer culture chamber, and then inoculate Caco-2 cells at a density of 10 5 cells / Transwell on the PET membrane in the upper chamber of the Transwell double-layer culture chamber and culture for 5 days. Change the medium every other day, and monitor the transepithelial electrical resistance in real time during this period. When the detected transepithelial electrical resistance is greater than 150 Ω·cm 2 and the ZO-1 protein shows obvious tight junctions, change the culture method to enter the second stage.

[0046] 2) The second stage: Remove the complete DMEM medium from the upper chamber of the Transwell double-layer culture chamber to make the Caco-2 cells directly contact with air. Still use 500 μL of complete DMEM medium in the lower chamber of the Transwell double-layer culture chamber and culture for 10 days to form a three-dimensional structure similar to that in vivo, and obtain the three-dimensional structure of intestinal crypt-villus.

[0047] 2. Construction of the inflammatory bowel disease model

[0048] 1) Dissolve 2 g of DSS powder (product number: 42867-5G, purchased from SIGMA) in 100 mL of complete DMEM medium (high-glucose DMEM containing 10% serum and 1% double antibody) to obtain a complete medium containing 2% DSS;

[0049] 2) Add 50 μL of the complete medium containing 2% DSS to the upper chamber of the Transwell double-layer culture chamber, and maintain 500 μL of complete DMEM medium in the lower chamber. Treat the three-dimensional structure of intestinal crypt-villus for 2 days to obtain the inflammatory bowel disease model.

[0050] II. Evaluation of the inflammatory bowel disease model

[0051] Add 50 μL of the complete medium containing 2% DSS to the upper chamber of the Transwell double-layer culture chamber to treat the three-dimensional structure of intestinal crypt-villus. The tissues obtained by treating the tissue for 2, 4, and 6 hours are respectively denoted as DSS+ 2h 、DSS+ 4h 、DSS+ 6h , and the tissue obtained on the first day of treatment is denoted as A10D1, and the tissue obtained on the second day of treatment is denoted as A10D2.

[0052] At the same time, use the tissue obtained without DSS treatment as the blank control, and denote the tissue cultured to the 10th day as L5A10.

[0053] 1. Detection of transepithelial electrical resistance (TEER)

[0054] Measure the transepithelial electrical resistance of each of the above tissues respectively (instrument: EVOM TM Manual, WPI, USA).

[0055] The detection results are as Figure 2 shown in a below. After DSS treatment, the TEER value decreased significantly, and with the prolongation of the treatment time, the TEER value continued to decline, indicating that the tight junctions between cells were damaged and the intestinal barrier function was impaired.

[0056] 2. Detection of the expression of barrier function-related proteins

[0057] Fix the above tissue samples with 4% paraformaldehyde, embed and freeze-section them using the embedding agent OCT (SAKURA), and combine immunofluorescence staining technology to detect the expression of barrier function-related proteins.

[0058] The detection results are as Figure 2 shown in b below. The expression of E-Cadherin (E-Cad; catalog number: 60335-1-Ig; purchased from Proteintech) was significantly weakened 1 day after DSS treatment, and local damage of the tissue barrier occurred; after 2 days of treatment, ulcers even appeared in some areas ( Figure 2 left of b below), further confirming the significant damage of the intestinal barrier function. And it was observed in a short time that with the increase of the DSS infiltration time, the expression of the inflammatory factor TNF-α (catalog number: 17590-1-AP, purchased from Proteintech) showed a spatial distribution trend of gradually extending from the villus layer to the crypt direction ( Figure 2 right of b below), reflecting that this model can reflect the spatial molecular characteristics of the occurrence and development of IBD in real time with high resolution. Moreover, this phenomenon reveals that the intestinal barrier damage and inflammatory response induced by DSS have significant spatiotemporal heterogeneity: at the initial stage of infiltration, the damage is mainly concentrated in the surface layer of the villi, and with the increase of the infiltration depth, the inflammatory response gradually spreads to the crypt area. This spatial distribution feature not only reflects the layer-by-layer erosion effect of DSS on intestinal tissues, but also suggests the dynamic propagation mechanism of the inflammatory response. This finding is highly consistent with the pathological process of inflammation spreading from the surface layer to the deep layer observed in clinical IBD patients, further proving the high simulation and clinical application potential of the inflammatory bowel disease model obtained by this method in simulating the disease progression of IBD.

[0059] 3. Detection of the expression levels of inflammatory factors

[0060] The expression levels of inflammatory factors in the above-mentioned tissue samples were detected by RT-PCR and Western Blot techniques.

[0061] The detection results are as Figure 2 shown in c - g below. After DSS treatment, the mRNA and protein levels of the inflammation-related factors IL-6, IL-1β, and TNF-α were significantly increased ( Figure 2 shown in c and d below), indicating that the model successfully simulated the inflammatory response characteristics of IBD. In addition, through transcriptome sequencing analysis of the tissues after DSS treatment, we found that the signaling pathways related to intestinal barrier damage and inflammatory response were significantly enriched, such as the oxidative phosphorylation pathway and the FoxO signaling pathway ( Figure 2 shown in e below). To further verify the clinical relevance of the model, we compared the transcriptome data of the IBD model constructed by this method with the real human IBD data and mouse IBD data. Venn diagram analysis showed that the gene expression profiles of this model and real human IBD had higher similarity ( Figure 2 shown in f below), fully demonstrating the reliability and clinical translation potential of the model. In addition, KEGG pathway enrichment analysis of the overlapping differential genes showed that among the top 30 pathways, the signaling pathways related to immune stress were significantly enriched, and the enrichment result of the TNF signaling pathway (ranked 67th) was particularly significant ( Figure 2 shown in g below). Given that TNF-α is a key target for clinical IBD treatment, this finding further highlights the important value of the inflammatory bowel disease model obtained by this method in drug screening and treatment research.

[0062] In summary, through multi-dimensional experimental results such as TEER, immunofluorescence, qPCR, Western Blot, and transcriptome sequencing, we not only successfully constructed a highly simulated in vitro IBD model, which highly resolved and real-time reflected the molecular spatio-temporal characteristics during the occurrence and development of IBD, but also systematically verified its reliability in simulating intestinal barrier damage, inflammatory response, and signal pathway activation.

[0063] Example 2

[0064] I. Construction of an inflammatory bowel disease model

[0065] Referring to the method of Example 1, 50 μL of complete medium containing 2% DSS was added to the upper chamber of the double-layer culture insert Transwell, and the intestinal crypt-villus three-dimensional structure was treated for two days to obtain an inflammatory bowel disease model.

[0066] II. Construction of an inflammatory bowel disease natural recovery model

[0067] After the inflammatory bowel disease model was constructed, the liquid in the upper chamber of the Transwell of the double-layer culture chamber was discarded, and the tissues in the upper chamber were washed with PBS, DMEM, and complete DMEM medium respectively. Subsequently, the tissues were continuously cultured for 5 days under the condition that no liquid was added to the upper chamber and 500 μL of complete DMEM medium was maintained in the lower chamber to obtain an inflammatory bowel disease natural recovery model.

[0068] III. Evaluation of the inflammatory bowel disease natural recovery model

[0069] Add 50 μL of complete medium containing 2% DSS to the upper chamber of the Transwell of the double-layer culture chamber and treat the intestinal crypt-villus three-dimensional structure for two days to obtain an inflammatory bowel disease model; discard the liquid in the upper chamber of the Transwell of the double-layer culture chamber, and wash the tissues in the upper chamber with PBS, DMEM, and complete DMEM medium respectively. Subsequently, the tissues were continuously cultured under the condition that no liquid was added to the upper chamber and 500 μL of complete DMEM medium was maintained in the lower chamber. The tissues cultured to the 2nd day were designated as A10D2R2, and the tissues cultured to the 5th day were designated as A10D2R5.

[0070] Meanwhile, the tissues not treated with DSS were used as blank controls, and the tissues cultured to the 10th day were designated as L5A10. A10D2 was used as a negative control.

[0071] 1. Evaluate the dynamic changes of intestinal structure and inflammatory factors

[0072] Samples of each group were taken respectively, and the dynamic changes of intestinal structure and inflammatory factors were systematically evaluated by immunofluorescence staining, RT-PCR, and Western Blot.

[0073] The experimental results are as Figure 3 shown: Figure 3 As shown in a, under the natural recovery state, although the intestinal structure damaged by DSS was repaired to a certain extent, it could not completely return to the intact state before treatment; Figure 3 b, c, and d further showed that the mRNA and protein expression levels of inflammatory factors IL-6, IL-1β, and TNF-α in the natural recovery group were significantly higher than those in the control group, suggesting that although the inflammatory response was alleviated to some extent, it still persisted. In addition, Figure 3Transcriptome analysis results of e and f also verified this phenomenon: Although the gene expression levels of some pro-inflammatory factors decreased during the recovery process, their expression levels were still significantly higher than those in the control group, indicating that the resolution of the inflammatory response is a slow and incomplete process. These findings are highly consistent with the reported studies: There is an asynchronous phenomenon between the structural repair and the recovery of the immune response during the recovery process of IBD. Although the intestinal barrier function may gradually recover, the remission of the inflammatory response often lags behind. Especially in the chronic IBD model, the "tolerant" state of the immune system may not be able to rapidly eliminate all inflammatory markers. For example, in the DSS-induced murine colitis model, the repair of the intestinal epithelium and the regression of the local immune response are not completely synchronous, and the inflammation is alleviated but still persists. Our experimental results not only confirmed this phenomenon but also further demonstrated that the natural recovery model of inflammatory bowel disease constructed by this method can more realistically simulate the dynamic process of in vivo disease recovery, and has higher physiological relevance and clinical translation value compared with the traditional model.

[0074] Example 3

[0075] I. Construction of an inflammatory bowel disease model

[0076] Referring to the method of Example 1, add 50 μL of complete medium containing 2% DSS to the upper chamber of the double-layer culture chamber Transwell, and treat the intestinal crypt-villus three-dimensional structure for two days to obtain an inflammatory bowel disease model.

[0077] II. Construction of an inflammatory bowel disease drug treatment model

[0078] The first-generation JAK inhibitor Tofacitinib (Tofacitinib; product number: HY-40354; purchased from MCE) and the second-generation JAK inhibitor Upadacitinib (Upadacitinib; product number: HY-19569; purchased from MCE) are both commonly used drugs in the clinic for inflammatory bowel disease. On the basis of the inflammatory bowel disease model, an inflammatory bowel disease treatment model was constructed as follows:

[0079] After constructing the inflammatory bowel disease model, discard the medium containing DSS in the upper chamber of the double-layer culture chamber Transwell, wash the upper chamber tissue with PBS, DMEM, and DMEM containing 10% fetal bovine serum (FBS) respectively, and then add 50 μL of the drug solution (10 μg / mL Tofacitinib or 5 μM Upadacitinib) to the upper chamber of Transwell, and maintain 500 μL of DMEM complete medium in the lower chamber, and culture for 1-5 days to obtain an inflammatory bowel disease treatment model.

[0080] III. Evaluation of the inflammatory bowel disease treatment model

[0081] Add 50 μL of complete medium containing 2% DSS to the upper chamber of the double-layer culture insert Transwell and treat the intestinal crypt-villus three-dimensional structure for two days to obtain an inflammatory bowel disease model. Discard the liquid in the upper chamber of the double-layer culture insert Transwell, wash the tissue in the upper chamber with PBS, DMEM, and DMEM complete medium respectively, then add 50 μL of 10 μg / mL Tofacitinib to the upper chamber, and continuously culture under the condition that 500 μL of DMEM complete medium is maintained in the lower chamber. The tissues cultured until the second, third, fourth, and fifth days are denoted as D2T2, D2T3, D2T4, and D2T5 respectively.

[0082] Add 50 μL of complete medium containing 2% DSS to the upper chamber of the double-layer culture insert Transwell and treat the intestinal crypt-villus three-dimensional structure for two days to obtain an inflammatory bowel disease model. Discard the liquid in the upper chamber of the double-layer culture insert Transwell, wash the tissue in the upper chamber with PBS, DMEM, and DMEM complete medium respectively, then add 50 μL of 10 μg / mL Upadacitinib to the upper chamber, and continuously culture under the condition that 500 μL of DMEM complete medium is maintained in the lower chamber. The tissues cultured until the first, second, third, fourth, and fifth days are denoted as D2U1, D2U2, D2U3, D2U4, and D2U5 respectively.

[0083] Meanwhile, A10D2 is used as a negative control.

[0084] Through cryosection, immunofluorescence staining, q-PCR, and Western Blot, comprehensively evaluate the recovery of the intestinal barrier function and the dynamic changes of inflammatory factors in each of the above tissues.

[0085] The results of Tofacitinib treatment are as Figure 4 shown. The immunofluorescence staining results show that after 3 days of Tofacitinib treatment, a significant recovery of the intestinal three-dimensional structure occurs, but with the extension of the treatment time, the structure is partially damaged again ( Figure 4 a in it). The q-PCR results show that the gene expression level of the barrier protein ZO-1 presents a trend of first increasing and then decreasing, while the expression of the inflammatory factor IL-6 shows no obvious change, and the expression of TNF-α first rises and then falls ( Figure 4 b in it). The Western Blot results further show that the protein level of TNF-α decreases at the initial stage of treatment but then rebounds, although it is still lower than the DSS treatment group overall ( Figure 4 c in it). These results indicate that Tofacitinib can effectively promote the recovery of intestinal barrier function in the short term, but long-term use may lead to a rebound of the inflammatory response, suggesting its potential side effect risk.

[0086] The results of upadacitinib treatment are as Figure 5 shown. Immunofluorescence staining showed that under upadacitinib treatment, the three-dimensional structure of the intestine gradually recovered over time ( Figure 5 as shown in a) in []. The results of q-PCR showed that the expression level of the ZO-1 gene also showed a trend of first increasing and then decreasing, while the expression of the inflammatory factors IL-6 and TNF-α decreased significantly on the 3rd day of treatment and then rebounded slightly ( Figure 5 as shown in b) in []. The results of Western Blot showed that the protein level of TNF-α was continuously lower than that of the untreated group during the whole treatment period, confirming the significant effect of upadacitinib in inhibiting the inflammatory response ( Figure 5 as shown in c) in []. These results suggest that upadacitinib shows high efficiency in promoting structural recovery and inhibiting the inflammatory response, and its effect is more persistent.

[0087] Based on the above results, we found that both drugs can promote the expression of the barrier protein ZO-1 and help the three-dimensional structure of the intestine to recover, but there are differences in the recovery effect and stability. Although tofacitinib and upadacitinib have significant effects in the short term, side effects still need to be vigilant during long-term use. The second-generation JAK inhibitor upadacitinib is more rapid and persistent in reducing the systemic inflammation level. These findings are highly consistent with clinical observations: tofacitinib may exacerbate the condition of ulcerative colitis when used at high doses or for a long time; while the side effects of upadacitinib are relatively mild, mainly manifested as mild gastrointestinal discomfort. This study not only verified the mechanism of action of these drugs, but also provided important experimental basis for their clinical application, laying a scientific foundation for the optimization of personalized treatment strategies for IBD.

[0088] Example 4

[0089] In this study, by systematically analyzing the structural and functional changes of the inflammatory bowel disease model after different drug treatments, it was found that there were significant differences in the repair effect of the three-dimensional intestinal barrier function and the regulation effect of the inflammatory level of the drugs, and a single index was difficult to comprehensively reflect the comprehensive efficacy of the drugs. Therefore, an evaluation method for drugs treating inflammatory bowel disease was proposed, aiming to construct a scientific and comprehensive pharmacodynamic evaluation model by quantifying structural and functional characteristics and combining subjective and objective weighting methods, providing a reliable tool for drug screening and efficacy evaluation.

[0090] I. Evaluation Method for Drugs Treating Inflammatory Bowel Disease

[0091] 1. Feature Extraction

[0092] Referring to the Chinese published patent CN118797363A, a method, system, device and storage medium for evaluating the similarity between an in vitro reconstructed intestine and a real intestine, respectively extract the structural features and functional features of tissues of an inflammatory bowel disease model before and after administration, an inflammatory bowel disease natural recovery model, and a healthy intestine model. The steps are as follows:

[0093] 1) Structural feature extraction

[0094] a. As shown in Table 1, based on immunofluorescence staining images, the structural features of tissues of the inflammatory bowel disease model (A10D2) before administration, the inflammatory bowel disease model (D2T2, D2U2) after administration, the natural recovery model (A10D2R2) tissue, and the healthy intestine model tissue (L5A10) are respectively divided into local structural features and global structural features.

[0095] Table 1 Composition of parameter feature division and scoring function

[0096]

[0097] b. Use deep learning to extract the local structural features of each group of intestines. Specifically: First, according to the crypt-villus characteristics, use the label-me software to label the biological images of the structural samples of each group of models for image segmentation; then, pass the processed and labeled data set through the U-Net neural network for deep learning and training. Subsequently, perform prediction processing on the image to be processed, and extract information from the predicted image through the Auto-Encoder to obtain the local structural feature data of the crypt-villus structure of each group of models.

[0098] c. Extract the global structural features of each group of model samples through Image-J software. First, convert the intestinal image into a binary image through the Image>Adjust>Threshold function in ImageJ software to highlight the outline of the intestinal structure. Subsequently, divide the image into two regions of structure and background through the Process>Binary>Make Binary function to create a boundary. Then, create a contour curve through the Process>Binary>Outline function, frame the contour range and intercept it. Subsequently, generate a contour curve graph and export the contour curve coordinate data through Analyze>Tools>Analyze Line Graph. After normalizing the extracted contour data of each group, according to the method of "extracting the contour of the top of the villus from the overall perspective, and then comparing the KL divergence of the contour data of the inflammatory bowel disease model before and after administration and the inflammatory bowel disease natural recovery model, the smaller the result, the more similar, and the larger the result, the less similar", calculate the KL divergence value of each group of contours and analyze and extract the global structural feature data of each group of models.

[0099] 2) Functional feature extraction

[0100] a. As shown in Table 1, based on the immunofluorescence staining of key proteins and transcriptome sequencing technology, the functional features of the tissues of the inflammatory bowel disease model and the natural recovery model of inflammatory bowel disease before and after drug administration are divided into local functional features and global functional features. Among them, the local functional features include the protein distribution on the cell membrane, the similarity of Crypt-villi protein distribution, the percentage of Crypt-villi villi / middle / crypt protein distribution, and the Crypt-villi villi / crypt protein distribution ratio. The global functional features include qPCR.

[0101] b. Through the distribution of key proteins at different spatial positions, the local functional features of the cells of each group of models are extracted. By extracting the spatial distribution features (linear or rectangular) of each specific protein in the immunofluorescence biological images of the cells of each group of models, and performing fluorescence intensity analysis on the immunofluorescence biological images through ImageJ software, a protein fluorescence intensity distribution map is obtained. Then, by comparing the fluorescence intensities of the protein distributions in the whole crypt-villi and the regions of villi, middle segment, and crypt, the similarities among the inflammatory bowel disease model, the natural recovery model of inflammatory bowel disease, and the healthy model (L5A10) before and after drug administration are evaluated, and the KL divergence and the protein distribution percentage are obtained.

[0102] c. Using real-time fluorescence quantitative (qPCR) technology to analyze the expression of key genes representing several representative functions in Table 2, the global functional features of the cells of each group of models are extracted, and the similarity is quantitatively characterized by fold change.

[0103] Table 2 Key proteins characterizing intestinal function

[0104]

[0105]

[0106] 2. Pharmacodynamic scoring evaluation system

[0107] 1) Weight calculation

[0108] Perform min-max normalization on the obtained structural features and functional features to eliminate dimensional differences. The entropy weight method is used to calculate the objective weights of each feature, and combined with the subjective weighting of experts, the final weights are comprehensively determined to ensure that the evaluation results have both the objectivity driven by data and the experience judgment of domain experts. The specific operations are as follows:

[0109] We calculated the weights of structural features and functional features separately. Let X and Y represent the structural feature matrix and the functional feature matrix respectively: X contains local features such as height and width, as well as global features such as contours, jointly depicting the detailed contours and overall framework of the structure; Y contains local features such as the distribution of VIL protein (KL value) and global features such as transcriptome data, demonstrating functional characteristics from both microscopic and macroscopic levels.

[0110] Specifically, for the feature data of each of the above experimental groups, we first performed maximum-minimum normalization to eliminate the dimensional difference and control the input value within the range of 0-1:

[0111]

[0112] where: X i,j represents the structural feature value of the jth column in the ith experimental group, and X i,max,j and X i,min,j represent the maximum and minimum values of the jth structural feature in the ith experimental group respectively; Y i,j represents the functional feature value of the jth column in the ith experimental group, and Y i,max,j and Y i,min,j represent the maximum and minimum values of the jth functional feature in the ith experimental group respectively. Subsequently, we used the entropy weight method to calculate the objective weights of each feature:

[0113]

[0114] where, e j represents the information entropy of the jth feature, and its calculation formula is as follows:

[0115]

[0116] where, p ijt represents the normalized value of the jth feature in the ith experimental group on the tth sample; this value can be calculated through the above X i,normalized,j and Y i,normalized,j ; finally, the objective weight takes the mean of the calculation results of the four experimental groups, and the calculation formula is as follows:

[0117]

[0118] After calculating the objective weights based on the experimental group data, we assigned subjective weights according to professional knowledge (it should be noted that structural and functional features are equally important at the local and global scales). By taking the mean value, the subjective and objective weights were organically integrated to finally determine the composite weights of each index:

[0119]

[0120] In the formula, wobjective represents the weight obtained based on objective data analysis; w subjective represents the weight assigned based on subjective evaluation.

[0121] Based on the above calculation process, the Figure 6 weight results of each parameter of a and b in

[0122] 2) Similarity calculation

[0123] For the global functional feature data, extract the gene intersection and calculate the cosine similarity. For the distribution type features (such as global structure, key protein distribution, etc.), calculate the KL divergence between them and the healthy intestinal model L5A10, and quantify the similarity through 1 - KL value. For other data, use the Wasserstein distance to evaluate the similarity between data. The specific calculation methods are as follows:

[0124] Given that different features have different biological meanings, we adopted a multi - method strategy when calculating the similarity between each group and the real intestine. Specifically, let Z control and Z respectively represent the feature data of the control group and other groups. The main calculation methods are as follows:

[0125] Global functional feature data (reflecting global function): First, extract the common gene set of the two groups, and calculate the cosine similarity based on these shared genes to quantify the similarity between groups:

[0126]

[0127] For the data characterized by KL divergence (such as contour KL value, membrane protein distribution KL value, MUC2 distribution KL value), since KL divergence itself can quantify the difference between two groups of data, we convert it into a similarity measure by calculating 1 - KL value. This method reverses the representational meaning of KL divergence from "difference" to "similarity": when the 1 - KL value approaches 1, it indicates that the two groups of data are highly similar; when it approaches 0, it indicates low similarity.

[0128] similarity = 1 - KL(Z,Z control ) (7)

[0129] For the remaining types of data, we first calculate the Wasserstein distance. Specifically, regard the data to be compared and the control group data as two probability distributions, and calculate the distribution difference between them through the following formula:

[0130] W(p,q)=inf γ～Π(p,q) E x,y～γ [‖x - y‖] (8)

[0131] Among them, the marginal distributions of these joint distributions are p and q respectively. After finding the distance, we calculate the similarity through the following equation:

[0132] similarity=e -α·W(p,q) (9)

[0133] According to the calculation process of this section, we can get Figure 6 Similarity scoring results of c.

[0134] 3) Weighted Similarity Score

[0135] By calculating the weighted F1 score of structure and function, we comprehensively evaluate the similarity between the inflammatory bowel disease model before and after drug administration, the inflammatory bowel disease natural recovery model and the healthy intestinal model, and comprehensively reflect the efficacy of the drug in structural repair and functional recovery. We quantify this similarity by calculating the F1 score. As a comprehensive evaluation indicator, the F1 score can consider the performance characteristics of the sample in both structure and function at the same time: the calculation formula is as follows:

[0136]

[0137] Where: similarity structure is the structural similarity, which indicates the matching degree of samples in morphological features; functional It is the functional similarity, which reflects the degree of consistency of samples in biological functional characteristics.

[0138] Based on this method, it can be calculated Figure 6 The scoring results of medium d.

[0139] Validation of evaluation methods for drugs used to treat inflammatory bowel disease

[0140] The above evaluation method was used to comprehensively evaluate the IBD model after treatment with two drugs (Tofacitinib and Upadacitinib). The results showed that the scores of the two drug treatments were significantly higher than those of the natural recovery group, confirming that drug intervention can significantly promote the recovery of the IBD model. Upadacitinib had the highest comprehensive score in structural repair and inflammation inhibition, suggesting that its therapeutic effect is better than Tofacitinib, a result that is highly consistent with clinical observations. The scoring results of this evaluation method are consistent with the clinical medication effect, verifying its reliability and application potential in drug screening and efficacy evaluation.

[0141] The above evaluation method for drugs treating inflammatory bowel disease, through multi-dimensional and multi-index quantitative analysis, not only provides a scientific basis for the efficacy evaluation of IBD drugs, but also lays a theoretical foundation for the optimization of personalized treatment strategies. In the future, this system can be further extended to the research of other disease models, providing strong technical support for drug development and clinical translation, and having important scientific significance and clinical application value.

[0142] The above content is only to illustrate the technical idea of the present invention, and the protection scope of the present invention cannot be limited thereby. Any modification made on the basis of the technical solution according to the technical idea proposed by the present invention falls within the protection scope of the claims of the present invention.

Claims

1. A method for constructing an inflammatory bowel disease model, characterized in that: The intestinal crypt-villus three-dimensional structure and DMEM complete medium containing sodium dextran sulfate were added to the upper chamber of the double-layer culture chamber Transwell, and DMEM complete medium was added to the lower chamber. The culture was carried out for 2 days to obtain an inflammatory bowel disease model.

2. The inflammatory bowel disease model obtained by the construction method according to claim 1.

3. A method for constructing an inflammatory bowel disease recovery model, characterized in that: After the inflammatory bowel disease model is obtained according to the construction method of claim 1, the inflammatory bowel disease model is cleaned, the liquid in the upper chamber is removed, and DMEM complete medium is added to the lower chamber for culturing for 5 days to obtain an inflammatory bowel disease recovery model.

4. The inflammatory bowel disease recovery model obtained by the construction method of claim 3.

5. A method for constructing a therapeutic model for inflammatory bowel disease, characterized in that: After obtaining the inflammatory bowel disease model according to the construction method of claim 1, the inflammatory bowel disease model is cleaned, the liquid in the upper chamber is removed, the inflammatory bowel disease treatment drug is added to the upper chamber, and DMEM complete culture medium is added to the lower chamber for culturing for 1 to 5 days to obtain the inflammatory bowel disease treatment model.

6. The inflammatory bowel disease treatment model obtained by the construction method of claim 5.

7. Use of the inflammatory bowel disease model of claim 2, the inflammatory bowel disease recovery model of claim 4, or the inflammatory bowel disease treatment model of claim 6 in the study of the pathogenesis of inflammatory bowel disease, the study of therapeutic targets for inflammatory bowel disease, or the screening of drugs for inflammatory bowel disease.

8. A method for evaluating a drug for treating inflammatory bowel disease, characterized in that: The following steps are involved: Step 1, respectively extracting the structural characteristics and functional characteristics of the healthy intestinal model tissue, the inflammatory bowel disease model tissue described in claim 2, and the inflammatory bowel disease treatment model tissue described in claim 6, and respectively calculating the weights of the structural characteristics and functional characteristics of each tissue to obtain a weight calculation result; Step 2, based on the structural characteristics and functional characteristics of the healthy intestinal model tissue, the inflammatory bowel disease model tissue according to claim 2, and the inflammatory bowel disease treatment model tissue according to claim 6, calculate the similarity of the structural characteristics and functional characteristics between the inflammatory bowel disease treatment model tissue and the healthy intestinal model tissue or the inflammatory bowel disease model tissue to obtain a similarity calculation result; Step 3: Combining the weight calculation results of step 1 and the similarity calculation results of step 2, the weighted F1 scores of the structural characteristics and functional characteristics of each tissue are calculated to obtain the evaluation results of the efficacy of the drug for treating inflammatory bowel disease.

9. The method for evaluating drugs for treating inflammatory bowel disease according to claim 8, characterized in that: In step 1, the entropy weight method is used to calculate the objective weights of structural features and functional features, and combined with the subjective weighting of experts, the weight calculation results are obtained comprehensively.

10. Use of the evaluation method according to claim 8 or 9 in screening drugs for inflammatory bowel disease.

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