Method and system for evaluating influence degree of target substance on gastric mucosa

Abstract

The embodiment of the invention provides a method and system for evaluating the influence degree of a target substance on gastric mucosa, and belongs to the technical field of bionic evaluation. The method comprises the following steps: determining a corresponding stomach environment in a bionic stomach to obtain a stomach model; wherein culture cells of gastric mucosa epithelial cells are added into the bionic stomach; after the target substance is placed in the bionic stomach, the stomach model is driven to start digestive movement based on the movement parameters; and after a predetermined period, collecting digestion result information in the stomach model, performing assignment of each evaluation index based on the digestion result information, and determining an evaluation result of the influence degree of the target substance on the gastric mucosa based on each evaluation index after assignment. According to the scheme, the defect that the action of movement force on cells is neglected in two-dimensional cell culture is overcome, the problems of ethical limitation and hysteresis of traditional animal experiments are solved, a more personalized and accurate evaluation means is provided, and the influence of substances on gastric mucosa can be evaluated more scientifically.

Description

Technical Field

[0001] This invention relates to the field of biomimetic evaluation technology, specifically to a method for evaluating the degree of influence of a target substance on the gastric mucosa and a system for evaluating the degree of influence of a target substance on the gastric mucosa. Background Technology

[0002] The gastric mucosa is a layer of mucous membrane lining the inner surface of the stomach. Under normal physiological conditions, its main functions include producing and secreting gastric acid, gastric juice, and digestive enzymes to aid in food digestion. Simultaneously, the gastric mucosa also secretes gastric mucus, which plays a protective role, preventing direct damage to the stomach wall from gastric acid and gastric juice. However, under pathological conditions, damage to the gastric mucosa is often closely related to the occurrence of various gastric diseases, such as gastritis, gastric ulcers, Helicobacter pylori infection, and gastric cancer. Statistics show that at least 80% of adults will experience some degree of gastric mucosal damage in their lifetime.

[0003] Many factors influence gastric mucosal health, primarily including dietary habits and medication use. Long-term consumption of spicy, greasy, excessively cold, excessively hot, or rough foods, alcohol consumption, and the use of certain medications such as nonsteroidal anti-inflammatory drugs (NSAIDs), some antibiotics, and anticancer drugs can all damage the gastric mucosa. Currently, research on the effects of substances on the gastric mucosa mainly relies on animal experiments. However, animal experiments have several limitations, including confounding factors during the experimental process, high costs, ethical controversies, and time lag in results. Furthermore, due to individual differences, animal experimental results are often difficult to precisely apply to every subject, affecting their broad applicability and accuracy.

[0004] While existing technologies have developed gastric mucosal cell models and mouse gastritis models to evaluate the effects of various substances on the gastric mucosa, these models still have limitations. First, they often neglect changes in the composition of substances within the digestive system, such as the effects of gastric acid and enzymes. Furthermore, these models cannot adequately simulate the complex environment in which gastric mucosal epithelial cells exist, including gastric motility and the digestive process. Second, cell culture models in two-dimensional media neglect the effects of the forces generated by movement on gastric mucosal cells. Moreover, subject compliance issues also affect the stability of experimental results. Therefore, existing evaluation methods cannot comprehensively and accurately reflect the actual effects of substances on the gastric mucosa, necessitating the development of more precise and personalized evaluation methods. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for evaluating the degree of influence of a target substance on the gastric mucosa, so as to at least solve the problem that existing evaluation methods cannot fully and accurately reflect the actual influence of substance components on the gastric mucosa.

[0006] To achieve the above objectives, the first aspect of the present invention provides a method for evaluating the degree of influence of a target substance on the gastric mucosa. The method includes: determining a corresponding gastric environment in a bionic stomach based on user-defined evaluation requirements to obtain a gastric model; wherein cultured gastric mucosal epithelial cells are added to the bionic stomach, and carbon dioxide gas is introduced into the bionic stomach model; generating motion parameters of the gastric model based on user-defined evaluation requirements, and driving the gastric model to begin digestive movement based on the motion parameters after the target substance is placed in the bionic stomach; after a predetermined period, collecting digestion result information in the gastric model, assigning values ​​to various evaluation indicators based on the digestion result information, and determining the evaluation result of the degree of influence of the target substance on the gastric mucosa based on the assigned evaluation indicators.

[0007] Optionally, the gastric mucosal epithelial cells are cultured in DMEM medium.

[0008] Optionally, the evaluation requirements include: fasting state evaluation and non-fasting state evaluation; the step of determining the corresponding gastric environment in the bionic stomach based on the user-defined evaluation requirements includes: determining the pH value of the gastric juice environment based on the user-defined evaluation requirements, and determining the corresponding gastric environment based on the pH value of the corresponding gastric juice environment.

[0009] Optionally, generating the gastric model's motion parameters based on the user-defined evaluation requirements includes: if the current evaluation requirement is a fasting state evaluation, then the gastric model's motion parameters are fasting motion parameters; if the current evaluation requirement is a non-fasting state evaluation, then the gastric model's motion parameters are non-fasting motion parameters.

[0010] Optionally, the rules for placing the target substance in the bionic stomach are as follows: if the target substance is a fluid, it is directly injected into the bionic stomach; if the target substance is a solid, it is chewed into chyme in the mouth before being injected into the bionic stomach.

[0011] Optional evaluation indicators include any one or more of the following: gastric mucosal epithelial cell viability indicators, pepsin activity indicators, gastric emptying indicators, and standard protein digestibility indicators.

[0012] Optionally, the step of assigning values ​​to each evaluation index based on the digestion result information includes: performing preprocessing on the digestion result information and classifying the preprocessed digestion result information to obtain an evaluation dataset corresponding to each evaluation index; determining the assignment results of each evaluation index based on each evaluation dataset; and determining the evaluation results of the degree of influence of the target substance on the gastric mucosa based on the assigned evaluation indicators includes: using the assigned evaluation indicators as input parameters of the evaluation model and outputting the evaluation score of the target substance based on the evaluation model; and determining the degree of influence of the target substance on the gastric mucosa based on the score range corresponding to the degree of influence level of the evaluation score.

[0013] Optionally, the evaluation model is:

[0014]

[0015] Where X is the evaluation score of the target substance; ω i x is the weight of the i-th evaluation indicator; i This represents the value assigned to the i-th evaluation index.

[0016] A second aspect of the present invention provides a system for evaluating the degree of influence of a target substance on the gastric mucosa. The system includes: a model building unit, used to determine a corresponding gastric environment in a bionic stomach based on user-defined evaluation requirements to obtain a gastric model; wherein cultured gastric mucosal epithelial cells are added to the bionic stomach; a driving unit, used to generate motion parameters of the gastric model based on user-defined evaluation requirements, and drive the gastric model to begin digestive movement based on the motion parameters after the target substance is placed in the bionic stomach; and an evaluation unit, used to collect digestion result information in the gastric model after a predetermined period, and assign values ​​to various evaluation indicators based on the digestion result information, and determine the evaluation result of the degree of influence of the target substance on the gastric mucosa based on the assigned evaluation indicators.

[0017] On the other hand, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described method for evaluating the degree of influence of the target substance on the gastric mucosa.

[0018] Through the above technical solution, this invention generates a stomach model that meets user-defined requirements by simulating the real gastric juice environment in a bionic stomach and combining it with gastric mucosal epithelial cell culture. By setting motion parameters, the bionic stomach can simulate the digestive movements of the stomach, ensuring that the evaluation process more closely resembles the actual human digestive system environment. After the target substance is placed in the bionic stomach, digestive movement is performed over a predetermined period, and digestive result data is collected. Based on this data, various evaluation indicators are assigned values, thereby quantifying and accurately assessing the impact of the target substance on the gastric mucosa. This method overcomes the ethical limitations and time lag issues of traditional animal experiments, providing a more personalized and precise evaluation method that helps to more scientifically assess the impact of substances on the gastric mucosa.

[0019] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0020] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0021] Figure 1 This is a flowchart of the steps of a method for evaluating the degree of influence of a target substance on the gastric mucosa provided in one embodiment of the present invention;

[0022] Figure 2 This is a schematic diagram illustrating a bionic stomach provided in one embodiment of the present invention;

[0023] Figure 3 This is a system structure diagram of a system for evaluating the degree of influence of a target substance on the gastric mucosa provided in one embodiment of the present invention. Detailed Implementation

[0024] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0025] Figure 1 This is a flowchart of a method for evaluating the degree of influence of a target substance on the gastric mucosa, provided in one embodiment of the present invention. Figure 1 As shown, this invention provides a method for evaluating the degree of influence of a target substance on the gastric mucosa, the method comprising:

[0026] Step S10: Based on the evaluation requirements set by the user, determine the corresponding stomach environment in the bionic stomach to obtain a stomach model.

[0027] Specifically, such as Figure 2 This is a biomimetic stomach model provided in one embodiment of the present application. The biomimetic stomach contains cultured gastric mucosal epithelial cells, which are cultured in DMEM medium.

[0028] In this embodiment of the invention, cultured gastric mucosal epithelial cells were added to the biomimetic stomach, thereby enabling the model to better simulate the physiological environment within a real stomach. These gastric mucosal epithelial cells were cultured in DMEM medium, a common cell culture medium containing various essential nutrients such as amino acids, glucose, and vitamins, which effectively support cell growth and metabolism. Specifically, this approach used normal human gastric mucosal epithelial cells GES-1 as the model cells. GES-1 cells were derived from the Beijing Cancer Prevention and Treatment Institute, and the culture medium used included 10% fetal bovine serum, 100U of penicillin, and 100U of streptomycin, components that contribute to healthy cell growth and immune defense.

[0029] Furthermore, GES-1 cells are a commonly used cell line in gastric mucosal biology research, exhibiting strong stability and reproducibility, and can effectively mimic the physiological functions of the human gastric mucosa in vitro. By incorporating these cells into a biomimetic stomach model, researchers can more realistically simulate the gastric mucosal environment, making the digestion and absorption of target substances in the stomach more closely resemble actual human conditions. Particularly in fields such as drug screening and food safety evaluation, this cell model can more accurately assess the impact of external substances on the gastric mucosa, helping to identify substances that may damage the gastric mucosa or have protective effects.

[0030] Based on the present invention, by culturing real gastric mucosal epithelial cells within a biomimetic stomach, the state of the gastric mucosa in a complex digestive environment can be better simulated. This in vitro culture-based cell approach avoids the ethical issues and uncertainties arising from species differences inherent in traditional animal experiments, while also reducing experimental costs. Secondly, the biomimetic stomach model enables quantitative evaluation, achieving chemical analysis of target substances through precise digestive movements and control of the gastric juice environment. The application of this technology not only improves the accuracy and reliability of experiments but also helps in the development of more precise drugs, food additives, and other products, while reducing their potential damage to the gastric mucosa.

[0031] Preferably, the evaluation requirements include: fasting state evaluation and non-fasting state evaluation; the step of determining the corresponding gastric environment in the bionic stomach based on the user-defined evaluation requirements includes: determining the pH value of the gastric juice environment based on the user-defined evaluation requirements, and determining the corresponding gastric environment based on the pH value of the corresponding gastric juice environment.

[0032] In this embodiment of the invention, the evaluation requirements are divided into fasting state evaluation and non-fasting state evaluation. This allows the bionic stomach model to more accurately simulate the gastric environment of the human body under different physiological states. Specifically, based on the evaluation requirements set by the user, the gastric juice environment within the bionic stomach can be adjusted, especially the pH value of the gastric juice, which is a key parameter in the evaluation process. For example, in a fasting state, human gastric juice is usually in a strongly acidic state, with a pH value close to 2; while in a non-fasting state, as food enters and neutralizes, the acidity of the gastric juice increases, and the pH value is usually around 3. Therefore, the bionic stomach can accurately simulate the gastric environment under these two different states by adjusting the pH value of the gastric juice, thereby improving the accuracy and specificity of the evaluation.

[0033] Furthermore, the gastric juice environment within this bionic stomach includes not only pH regulation but also adjustment of the concentration of digestive enzymes such as pepsin. For example, the bionic stomach can be formulated with pepsin at the same concentration as actual human gastric juice, typically 2000 U / mL. This enzyme is responsible for the initial breakdown of food in the stomach, especially the digestion of proteins. Therefore, by precisely adjusting the pepsin concentration and pH value, the bionic stomach can realistically reflect the digestive environment under different physiological conditions, thus making the evaluation of target substances more closely resemble actual human conditions.

[0034] Based on this invention, by precisely controlling the pH value of gastric juice, the biomimetic stomach model can accurately simulate the gastric environment under fasting and non-fasting conditions, avoiding the problem of traditional evaluation methods failing to consider different digestive states in the human body. This simulation not only improves the reliability of experiments but also makes the evaluation results more valuable. Especially in the evaluation of substances such as drugs and food additives, different pH environments have a significant impact on the absorption and metabolism of substances. By adjusting the pH value of gastric juice, a more comprehensive understanding of the behavior of substances in the human body can be obtained. In addition, the biomimetic stomach can quantitatively assess the impact of substances on the gastric mucosa under different gastric juice environments, providing a scientific basis for optimizing the design of drugs or foods, while reducing the risk of side effects on the human body. This method not only meets the needs of researchers for precise experimental data but also provides stronger protection for the health and safety of consumers.

[0035] Step S20: Generate motion parameters of the stomach model based on the evaluation requirements set by the user, and drive the stomach model to start digestion movement based on the motion parameters after the target material is placed in the bionic stomach.

[0036] Specifically, if the current evaluation requirement is for a fasting state, then the gastric model's motion parameters are the fasting motion parameters; if the current evaluation requirement is for a non-fasting state, then the gastric model's motion parameters are the non-fasting motion parameters.

[0037] In this embodiment of the invention, the solution generates corresponding gastric model motion parameters based on user-defined evaluation requirements, simulating the digestive movements of the human stomach under different physiological states. This design not only more realistically reflects the complex dynamics of the human digestive process but also allows for flexible adjustment based on the evaluation requirements of the target substance. For example, if the user-defined evaluation requirement is a test under fasting conditions, the gastric model's motion parameters will be set based on the gastric motion characteristics under fasting conditions; if the evaluation requirement is a non-fasting condition, the gastric model will use the motion parameters under non-fasting conditions.

[0038] In a fasting state, gastric peristalsis is more vigorous and frequent, gastric juice secretion is lower, but gastric acid concentration is higher, resulting in stronger mechanical action of the stomach. Correspondingly, a bionic stomach will generate motion parameters based on these characteristics in a fasting state, simulating higher frequency peristalsis and stronger stomach wall movement. On the other hand, in a non-fasting state, gastric peristalsis is slower and more stable, and gastric juice secretion increases. Therefore, motion parameters in a non-fasting state will reflect gentler digestive movements, simulating the gradual decomposition and absorption process of the stomach.

[0039] Based on the present invention, this solution can highly simulate the actual motion state of the human stomach, making the biomimetic stomach model closer to the human digestive process. This simulation not only solves the problem of the lack of kinetic factors in traditional static models, but also provides more comprehensive test data. For example, in drug release studies, gastric motility under different states has a significant impact on the dissolution, absorption, and metabolism of drugs. By using different motion parameters, the behavior of target substances in the actual digestive environment can be accurately evaluated. This dynamic simulation can also provide a more comprehensive assessment, enabling researchers to better predict the effects of substances in the human body, especially the different performances of substances in fasting and non-fasting states.

[0040] Furthermore, the rules for placing the target substance in the bionic stomach are as follows: if the target substance is a fluid, it is processed into a suspension before being injected into the bionic stomach; if the target substance is a solid, it is processed into chyme before being injected into the bionic stomach.

[0041] In this embodiment of the invention, the target material needs to undergo different processing depending on its morphology before being placed into the bionic stomach. If the target material is a fluid, it is first processed into a suspension before being injected into the bionic stomach; if the target material is a solid, it is processed into chyme. The optimal processing method is for the target evaluation subject to convert the solid material into chyme through oral processing methods such as chewing before injecting it into the bionic stomach. This processing method can more realistically simulate the initial digestion process of food in the oral environment, ensuring that the behavior of the target material in the stomach is consistent with the actual digestion process.

[0042] Furthermore, the process of processing solid matter into chyme is crucial because chyme is a mixture formed after food undergoes mechanical chewing in the mouth and chemical action of saliva. Once in the stomach, the breakdown and absorption of chyme more closely resemble the body's natural processes. Through this simulation, researchers can more realistically assess the behavior of substances in the stomach, thereby obtaining more accurate experimental data. For example, some drugs or nutritional supplements begin to decompose or transform in the mouth, directly affecting their absorption and efficacy in the stomach. Therefore, simulating the oral environment allows for a more comprehensive representation of the behavior of substances throughout the digestive process.

[0043] Based on the present invention, the accuracy and personalization of the biomimetic stomach model are improved by refining the processing methods of the target material. First, fluid substances are processed into a suspension before being injected into the biomimetic stomach, ensuring uniform distribution and sufficient contact of the substance within the gastric juice, thus leading to more consistent evaluation results. For solid substances, they are processed into chyme, which not only simulates the mechanical and chemical processing of substances in the oral cavity but also allows the substance to be digested in a more natural form after entering the stomach. This processing method reflects the individual's actual eating process, reducing biases caused by individual differences or different processing methods in experiments, making the results of each test more reliable and accurate.

[0044] Step S30: After a predetermined period, digestion result information in the gastric model is collected, and each evaluation index is assigned a value based on the digestion result information. The evaluation result of the degree of influence of the target substance on the gastric mucosa is determined based on the assigned evaluation index.

[0045] Specifically, the evaluation indicators include any one or more of the following: gastric mucosal epithelial cell viability indicators, pepsin activity indicators, gastric emptying indicators, and standard protein digestibility indicators.

[0046] Furthermore, the step of assigning values ​​to each evaluation index based on the digestion result information includes: performing preprocessing on the digestion result information and classifying the preprocessed digestion result information to obtain the evaluation dataset corresponding to each evaluation index; determining the assignment results of each evaluation index based on each evaluation dataset; and determining the evaluation results of the degree of influence of the target substance on the gastric mucosa based on the assigned evaluation indicators includes: using the assigned evaluation indicators as input parameters of the evaluation model and outputting the evaluation score of the target substance based on the evaluation model; and determining the degree of influence of the target substance on the gastric mucosa based on the score range corresponding to the degree of influence level of the evaluation score.

[0047] Furthermore, the evaluation model is as follows:

[0048]

[0049] Where X is the evaluation score of the target substance; ω i x is the weight of the i-th evaluation indicator; i This represents the value assigned to the i-th evaluation index.

[0050] In this embodiment of the invention, the evaluation indicators cover multiple key physiological and digestive parameters, such as gastric mucosal epithelial cell viability, pepsin enzyme activity, gastric emptying rate, and digestibility of standard proteins. These indicators reflect the specific performance of the target substance during digestion from different perspectives and provide a solid foundation for subsequent quantitative analysis.

[0051] In one possible implementation, the assignment rules for each evaluation index are as follows:

[0052] 1. Gastric mucosal epithelial cell survival rate (A value): The gastric mucosal epithelial cell survival rate reflects the degree of protection or damage to gastric mucosal epithelial cells by the target substance and is an important parameter for assessing the health status of the gastric mucosa. Its assignment rules are as follows:

[0053] A = Gastric mucosal epithelial cell vitality after 2 hours / Initial gastric mucosal epithelial cell vitality;

[0054] The initial viability is the cell viability measured at the beginning of the experiment, and the viability after 2 hours is the viability measured after 2 hours of treatment in the biomimetic stomach. The higher the A value, the higher the survival rate of gastric mucosal epithelial cells, and the less damage or even protective effect of the target substance on the gastric mucosal epithelial cells; the lower the A value, the more likely it is that the target substance has a damaging effect on the cells.

[0055] 2. Pepsin activity change rate (B value): Pepsin is the main enzyme in the stomach that digests proteins. Changes in its activity reflect whether a target substance will affect the normal digestive function of the stomach. The assignment rules are as follows:

[0056] B = Pepsin activity after 2 hours / Initial pepsin activity;

[0057] Initial pepsin activity refers to the enzyme activity level at the start of the experiment, while the enzyme activity after 2 hours refers to the enzyme activity state of the target substance after 2 hours of treatment in the biomimetic stomach. The B value reflects the change in pepsin activity. If the B value is close to 1, it indicates that the target substance has little effect on pepsin; if the B value is significantly lower than 1, it indicates that the target substance may inhibit pepsin activity; if the B value is higher than 1, it may indicate that the target substance enhances pepsin activity.

[0058] 3. Standard protein hydrolysis rate (C value): The standard protein hydrolysis rate is an important indicator for measuring the digestive effect of a target substance on proteins in the stomach, reflecting the impact of the target substance on the efficiency of protein digestion. Its assignment rules are as follows:

[0059] C = Protein content after 2 hours of gastric digestion / Initial standard protein content;

[0060] The initial standard protein content refers to the initial amount of standard protein injected into the bionic stomach at the start of the experiment, and the protein content after 2 hours represents the amount of hydrolyzed protein. A higher C value indicates a higher degree of protein digestion; a lower C value indicates a lower rate of protein hydrolysis. Therefore, the C value reflects the promoting or inhibiting effect of the target substance on the protein digestion process.

[0061] 4. Gastric Emptying Score (D-score): The gastric emptying score reflects the effect of the target substance on gastric emptying function. Gastric emptying refers to the process by which food, after entering the stomach, is digested and passes through the pylorus into the small intestine. By measuring the time it takes for food to empty from the stomach, it is possible to assess whether the target substance affects the normal gastric emptying process. Specific scoring rules are as follows:

[0062] 1) Empty the target food within 30 minutes: 100 points;

[0063] 2) Empty the target food within 30 to 60 minutes: 80 minutes

[0064] 3) Empty the target food within 60 to 90 minutes: 60 minutes

[0065] 4) Empty the target food within 90 to 120 minutes: 40 minutes

[0066] 5) Empty the target food within 120 to 180 minutes: 20 minutes

[0067] Emptying the target food in more than 180 minutes: 0 points

[0068] This scoring system reflects the impact of the target substance on gastric emptying rate by assigning a graded value to gastric emptying time. A higher score indicates a faster gastric emptying rate, suggesting that the target substance has a smaller impact on the gastric emptying process or even promotes it; a lower score indicates a slower gastric emptying process, suggesting that the target substance may inhibit gastric emptying function.

[0069] Furthermore, to ensure the accuracy of data analysis, this invention proposes preprocessing and classification of digestion results information. The preprocessing steps include standardization and noise reduction of the collected data to ensure the reliability and stability of the evaluation results. The classified digestion results dataset allows each evaluation indicator to be analyzed independently and tailored to specific physiological states (e.g., fasting or non-fasting). By assigning values ​​to each evaluation indicator, multi-dimensional evaluation data can be obtained. When determining the evaluation score of the target substance, all assigned values ​​are used as input to the evaluation model. This evaluation model can calculate the final evaluation score of the target substance by combining the weights of each evaluation indicator. The weights are flexible and can be adjusted according to specific testing needs. For example, users may be more concerned about the survival rate of gastric mucosal cells; in this case, the weights can be tilted towards this indicator to highlight its importance in the overall evaluation.

[0070] Based on this invention, the method achieves precise assessment of the effects of target substances on the gastric mucosa, overcoming the limitations of traditional experimental methods in quantification. Through combined analysis of multiple physiological indicators, researchers can gain a more comprehensive understanding of the safety and efficacy of the target substance. Furthermore, based on quantified evaluation scores, the degree of influence of the substance can be clearly classified, providing a scientific basis for decision-making. This has significant application value in fields such as drug development and food additive evaluation, helping to improve the accuracy and efficiency of experiments while ensuring the safety of products for human use.

[0071] Example 1: Gastric mucosa evaluation model and scoring under simulated fasting conditions.

[0072] Step 1: Culture human normal gastric mucosal epithelial cells GES-1. These cells were purchased from Beijing Cancer Prevention and Treatment Institute. Culture medium: The basic culture medium for GES-1 cells was DMEM medium (10% FBS, 100U penicillin, 100U streptomycin).

[0073] Step 2: Biomimetic stomach and gastric juice environment: Prepare human gastric juice and pepsin 2000U / mL, and adjust pH=2.

[0074] Step 3: Simulate the dynamics of a bionic stomach and set the motion parameters of the stomach on an empty stomach.

[0075] Step 4: GES-1 gastric mucosal epithelial cells in the logarithmic growth phase were seeded into a gastric model, and cell viability, pepsin activity, gastric emptying index, and standard protein digestibility were observed after 2 hours.

[0076] Step 5: Result Evaluation and Model Evaluation

[0077] Two hours later, the cell viability was 90% of the initial value, and the score was A=90;

[0078] The pepsin activity was equivalent to the initial activity of 2000 U / mL, and the score was B = 100.

[0079] Standard protein digestibility score: No protein is digested under fasting conditions, so this index is C=0;

[0080] When the stomach is empty and no food or other components are emptied, the gastric emptying score is D = 0.

[0081] Impact Index X = Impact Index X = ∑0.62 × gastric mucosal epithelial cell survival score A + 0.15 × pepsin activity score B + standard protein hydrolysis rate score C + 0.08 × gastric emptying score D = 0.62 × 90 + 0.15 × 100 + 0 + 0 = 65.8.

[0082] Example 2: Evaluation model and scoring of gastric mucosa under simulated standard protein consumption.

[0083] Step 1: Culture human normal gastric mucosal epithelial cells GES-1. These cells were purchased from Beijing Cancer Prevention and Treatment Institute. Culture medium: The basic culture medium for GES-1 cells was DMEM medium (10% FBS, 100U penicillin, 100U streptomycin).

[0084] Step 2: Biomimetic stomach and gastric juice environment: Prepare human gastric juice and pepsin 2000U / mL, and adjust pH=3.

[0085] Step 3: Simulate the dynamics of a bionic stomach, set the motion parameters of the stomach on an empty stomach, and prepare a whey protein solution to digest the stomach so that the volume ratio of gastric juice to whey protein solution is 1:1.

[0086] Step 4: GES-1 gastric mucosal epithelial cells in the logarithmic growth phase were seeded into a gastric model, and cell viability, pepsin activity, gastric emptying index, and standard protein digestibility were observed after 2 hours.

[0087] Step 5: Result Evaluation and Model Evaluation

[0088] Two hours later, the cell viability was 92% of the initial value, and the score was A=92;

[0089] The pepsin activity was equivalent to the initial activity of 2000 U / mL, and the score was B = 100.

[0090] Standard protein hydrolysis rate: After 2 hours of digestion, whey protein undergoes approximately 10% hydrolysis, and this indicator is C=10.

[0091] Gastric emptying score of whey protein solution: If whey protein solution can be expelled from the stomach within 30 minutes, the gastric emptying score is D=100;

[0092] The influence index X = ∑0.62 × gastric mucosal epithelial cell survival score A + 0.15 × pepsin activity score B + standard protein hydrolysis rate score C + 0.08 × gastric emptying score D = 0.62 × 92 + 0.15 × 100 + 10 + 0.08 × 100 = 90.0.

[0093] Example 3: Evaluation model and scoring of gastric mucosa after simulating drinking baijiu on an empty stomach.

[0094] Step 1: Culture human normal gastric mucosal epithelial cells GES-1. These cells were purchased from Beijing Cancer Prevention and Treatment Institute. Culture medium: The basic culture medium for GES-1 cells was DMEM medium (10% FBS, 100U penicillin, 100U streptomycin).

[0095] Step 2: Biomimetic stomach and gastric juice environment: Prepare human gastric juice and pepsin 2000U / mL, and adjust pH=2.

[0096] Step 3: Simulate the dynamics of a bionic stomach, set the stomach motility parameters, and administer 50mL of baijiu (Chinese white liquor) into the stomach to make the ratio of baijiu to gastric juice 1:1.

[0097] Step 4: GES-1 gastric mucosal epithelial cells in the logarithmic growth phase were seeded into a gastric model, and cell viability, pepsin activity, gastric emptying index, and standard protein digestibility were observed after 2 hours.

[0098] Step 5: Result Evaluation and Model Evaluation

[0099] Two hours later, cell viability was 5%, and the score was A=5;

[0100] The pepsin activity was approximately 20% of the initial value, and the score was B = 20.

[0101] When fasting, no protein is digested, so this indicator C = 0;

[0102] If 50mL of baijiu is expelled from the stomach within 30 minutes, the gastric emptying score D=100;

[0103] The impact index X = ∑0.62 × gastric mucosal epithelial cell survival score A + 0.15 × pepsin activity score B + standard protein hydrolysis rate score C + 0.08 × gastric emptying score D = 0.62 × 5 + 0.15 × 20 + 0 + 0.08 × 100 = 14.1.

[0104] Example 4: Evaluation model and scoring of gastric mucosa after simulating drinking baijiu (Chinese liquor) after a meal.

[0105] Step 1: Culture human normal gastric mucosal epithelial cells GES-1. These cells were purchased from Beijing Cancer Prevention and Treatment Institute. Culture medium: The basic culture medium for GES-1 cells was DMEM medium (10% FBS, 100U penicillin, 100U streptomycin).

[0106] Step 2: Biomimetic stomach and gastric juice environment: Prepare human gastric juice and pepsin 2000U / mL, and adjust pH=3.

[0107] Step 3: Simulate the dynamics of a bionic stomach, set the stomach motility parameters, and administer 40mL of baijiu (Chinese liquor) and 10mL of whey protein solution into the stomach to make the ratio of (baijiu + whey protein solution) to gastric juice 1:1.

[0108] Step 4: GES-1 gastric mucosal epithelial cells in the logarithmic growth phase were seeded into a gastric model, and cell viability, pepsin activity, gastric emptying index, and standard protein digestibility were observed after 2 hours.

[0109] Step 5: Result Evaluation and Model Evaluation

[0110] Two hours later, cell viability was 8%, and the score was A=8;

[0111] The pepsin activity was approximately 30% of the initial value, and the score was B = 30.

[0112] The protein hydrolysis rate is 10%, and the corresponding index C = 10.

[0113] If 50mL of baijiu is expelled from the stomach within 30 minutes, the gastric emptying score D=100;

[0114] The influence index X = ∑0.62 × gastric mucosal epithelial cell survival score A + 0.15 × pepsin activity score B + standard protein hydrolysis rate score C + 0.08 × gastric emptying score D = 0.62 × 8 + 0.15 × 30 + 10 + 0.08 × 100 = 25.6.

[0115] Example 5: Evaluation model and scoring of gastric mucosa after simulating consumption of Grifola frondosa polysaccharide.

[0116] Step 1: Culture human normal gastric mucosal epithelial cells GES-1. These cells were purchased from Beijing Cancer Prevention and Treatment Institute. Culture medium: The basic culture medium for GES-1 cells was DMEM medium (10% FBS, 100U penicillin, 100U streptomycin).

[0117] Step 2: Biomimetic stomach and gastric juice environment: Prepare human gastric juice and pepsin 2000U / mL, and adjust pH=2.

[0118] Step 3: Simulate the dynamics of a bionic stomach, set the stomach motion parameters, and inject 40 mL of Grifola frondosa polysaccharide solution and 10 mL of whey protein solution into the stomach model to make the ratio of chyme to gastric juice 1:1.

[0119] Step 4: GES-1 gastric mucosal epithelial cells in the logarithmic growth phase were seeded into a gastric model, and cell viability, pepsin activity, gastric emptying index, and standard protein digestibility were observed after 2 hours.

[0120] Step 5: Result Evaluation and Model Evaluation

[0121] Two hours later, cell viability was 95%, and the score was A=95;

[0122] The pepsin activity is approximately 90% of that initially prepared, and the score is B=90.

[0123] The protein hydrolysis rate is 12%, and the index C = 12.

[0124] Grifola frondosa polysaccharide solution emptied from the stomach in 30 minutes, with a gastric emptying score of D=100;

[0125] The impact index X = ∑0.62 × gastric mucosal epithelial cell survival score A + 0.15 × pepsin activity score B + standard protein hydrolysis rate score C + 0.08 × gastric emptying score D = 0.62 × 95 + 0.15 × 90 + 12 + 0.08 × 100 = 92.4.

[0126] Example 6: Evaluation model and scoring of gastric mucosa after consuming high-fiber foods (represented by dehydrated cabbage).

[0127] Step 1: Select dehydrated vegetables from healthy adults and collect 40 grams of the chyme.

[0128] Step 2: Culture human normal gastric mucosal epithelial cells GES-1. These cells were purchased from Beijing Cancer Prevention and Treatment Institute. Culture medium: The basic culture medium for GES-1 cells was DMEM medium (10% FBS, 100U penicillin, 100U streptomycin).

[0129] Step 3: Biomimetic stomach and gastric juice environment: Prepare human gastric juice and pepsin 2000U / mL, and adjust pH=3.

[0130] Step 4: Simulate the dynamics of a bionic stomach, set the stomach motion parameters, and inject 40mL of dehydrated cabbage puree and 10mL of whey protein into the stomach model to make the ratio of (dehydrated cabbage puree + whey protein solution) to gastric juice 1:1.

[0131] Step 5: GES-1 gastric mucosal epithelial cells in the logarithmic growth phase were seeded into a gastric model, and cell viability, pepsin activity, gastric emptying index, and standard protein digestibility were observed after 2 hours.

[0132] Step 6: Result Evaluation and Model Evaluation

[0133] Two hours later, cell viability was 60%, and the score was A=60;

[0134] The pepsin activity is approximately 80% of that initially prepared, and the score is B=80.

[0135] The protein hydrolysis rate is 5%, and this indicator C = 5;

[0136] The chyme empties from the stomach in 120–180 minutes, with a gastric emptying score of D = 20;

[0137] The impact index X = ∑0.62 × gastric mucosal epithelial cell survival score A + 0.15 × pepsin activity score B + standard protein hydrolysis rate score C + 0.08 × gastric emptying score D = 0.62 × 60 + 0.15 × 80 + 5 + 0.08 × 20 = 55.8.

[0138] Example 7: Evaluation model and scoring of gastric mucosa after simulating consumption of grain foods (represented by millet).

[0139] Step 1: Select healthy adults to eat millet porridge and collect 40 grams of the porridge.

[0140] Step 2: Culture human normal gastric mucosal epithelial cells GES-1. These cells were purchased from Beijing Cancer Prevention and Treatment Institute. Culture medium: The basic culture medium for GES-1 cells was DMEM medium (10% FBS, 100U penicillin, 100U streptomycin).

[0141] Step 3: Biomimetic stomach and gastric juice environment: Prepare human gastric juice and pepsin 2000U / mL, and adjust pH=3.

[0142] Step 4: Simulate the dynamics of a bionic stomach, set the stomach motion parameters, and inject 40mL of millet porridge and 10mL of whey protein into the stomach model to make the ratio of (millet porridge + whey protein solution) to gastric juice 1:1.

[0143] Step 5: GES-1 gastric mucosal epithelial cells in the logarithmic growth phase were seeded into a gastric model, and cell viability, pepsin activity, gastric emptying index, and standard protein digestibility were observed after 2 hours.

[0144] Step 6: Result Evaluation and Model Evaluation

[0145] Two hours later, cell viability was 80%, and the score was A=80;

[0146] The pepsin activity is approximately 90% of that initially prepared, and the score is B=90.

[0147] The protein hydrolysis rate is 10%, and the corresponding index C = 10.

[0148] The chyme emptied from the stomach within 90 minutes, with a gastric emptying score of D = 60.

[0149] The impact index X = ∑0.62 × gastric mucosal epithelial cell survival score A + 0.15 × pepsin activity score B + standard protein hydrolysis rate score C + 0.08 × gastric emptying score D = 0.62 × 80 + 0.15 × 90 + 10 + 0.08 × 60 = 77.9.

[0150] In one possible implementation, the qualitative assessment results are as follows: Impact index X < 50: severe damage to the gastric mucosa; Impact index X between 50 and 60: slight damage to the gastric mucosa, but based on actual conditions, it affects gastric emptying, digestive enzyme function, and epithelial cell vitality; Impact index X between 60 and 70: essentially no effect on the gastric mucosa; Impact index X between 70 and 85: protective effect on the gastric mucosa; Impact index X > 85: good protective effect on the gastric mucosa. Table 1 shows the evaluation results of the target substances for each embodiment:

[0151] Table 1. Evaluation of the impact index on gastric mucosa under different modes

[0152]

[0153]

[0154] Based on the solution of the present invention, the following beneficial effects can be achieved:

[0155] 1. The gastric mucosa model established in this invention is not subject to ethical restrictions, partially reduces the killing of animals, and is environmentally friendly;

[0156] 2. The gastric mucosa model established in this invention uses human gastric mucosal cells and integrates simulations of the physiological morphology, movement and stress of the stomach, which is very close to the environment of the gastric mucosa in real environment.

[0157] 3. This invention considers the comprehensive effects of various forms of substances, such as solids, semi-solids, and liquids, on the survival of gastric mucosal epithelial cells, the rate of change in pepsin activity, the hydrolysis rate of standard proteins, and gastric emptying after passing through a gastric model, which is closer to the real situation than previous single indicators.

[0158] 4. The evaluation model established in this invention for predicting the impact of substances on the gastric mucosa can quickly predict the impact of substances on the gastric mucosa, provide quantitative indicators, facilitate the comparison of the impact of different types of substances on the gastric mucosa, help screen for better components that have a protective effect on the gastric mucosa, and predict damage to the gastric mucosa.

[0159] 5. With ethical approval, this invention can collect the subject's own saliva or digested food residue from the mouth to more accurately assess the impact of ingested substances on the gastric mucosa, providing personalized technical support for protecting the gastric mucosa.

[0160] Figure 3 This is a system structure diagram of a system for evaluating the degree of influence of a target substance on the gastric mucosa, provided in one embodiment of the present invention. Figure 3 As shown, this invention provides a system for evaluating the impact of a target substance on the gastric mucosa. The system includes: a model building unit, used to determine the corresponding gastric environment in a bionic stomach based on user-defined evaluation requirements to obtain a gastric model; wherein cultured gastric mucosal epithelial cells are added to the bionic stomach; a driving unit, used to generate motion parameters of the gastric model based on user-defined evaluation requirements, and drive the gastric model to begin digestion based on the motion parameters after the target substance is placed in the bionic stomach; and an evaluation unit, used to collect digestion result information from the gastric model after a predetermined period, and assign values ​​to various evaluation indicators based on the digestion result information, and determine the evaluation result of the impact of the target substance on the gastric mucosa based on the assigned evaluation indicators.

[0161] The present invention also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described method for evaluating the degree of influence of the target substance on the gastric mucosa.

[0162] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0163] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details described above. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe the various possible combinations.

[0164] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the embodiments of the present invention, they should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A method for evaluating the degree of influence of a target substance on the gastric mucosa, characterized in that, The method includes: Based on user-defined evaluation requirements, a corresponding stomach environment is determined within a bionic stomach to obtain a stomach model; among which, The biomimetic stomach contains cultured cells of gastric mucosal epithelial cells. Based on the user-defined evaluation requirements, the motion parameters of the stomach model are generated, and after the target substance is placed in the bionic stomach, the stomach model is driven to start digestion based on the motion parameters. After a predetermined period, digestion results information from the gastric model is collected, and each evaluation index is assigned a value based on the digestion results information. The evaluation results of the degree of influence of the target substance on the gastric mucosa are determined based on the assigned evaluation indexes.

2. The method according to claim 1, characterized in that, The gastric mucosal epithelial cells are placed in a bionic stomach model, and carbon dioxide gas is introduced into the bionic stomach, which can be kept at a constant temperature and humidity.

3. The method according to claim 1, characterized in that, The evaluation requirements include: Fasting status assessment and non-fasting status assessment; The process of determining the corresponding gastric environment in the bionic stomach based on user-defined evaluation requirements includes: Based on the evaluation requirements set by the user, the pH value of the gastric juice environment is adjusted accordingly, and the corresponding gastric environment is determined based on the pH value of the corresponding gastric juice environment.

4. The method according to claim 3, characterized in that, The generation of gastric model motion parameters based on user-defined evaluation requirements includes: If the current evaluation requirement is for a fasting state, then the gastric model's motion parameters are the fasting motion parameters. If the current evaluation requirement is for a non-fasting state, then the motion parameters of the stomach model are the non-fasting motion parameters.

5. The method according to claim 1, characterized in that, The rules for placing the target substance in the bionic stomach are as follows: If the target substance is a fluid, it will be processed into a suspension before being injected into the bionic stomach. If the target substance is a solid substance, it will be processed into chyme before being injected into the bionic stomach.

6. The method according to claim 1, characterized in that, Evaluation indicators include: Any one or more of the following indicators: cell viability of gastric mucosal epithelial cells, pepsin activity, gastric emptying, and standard protein digestibility.

7. The method according to claim 1, characterized in that, The process of assigning values ​​to each evaluation index based on the digestion result information includes: Preprocessing is performed on the digestion results information, and the preprocessed digestion results information is classified to obtain the evaluation dataset corresponding to each evaluation index; Based on each evaluation dataset, the assigned values ​​for each evaluation indicator are determined. The evaluation results of the impact of the target substance on the gastric mucosa, determined based on the assigned evaluation indicators, include: The assigned evaluation indicators are used as input parameters of the evaluation model, and the evaluation score of the target substance is output based on the evaluation model. Based on the score range corresponding to the level of influence of the evaluation score, the level of influence of the target substance on the gastric mucosa is determined.

8. The method according to claim 7, characterized in that, The evaluation model is as follows: Where X is the evaluation score of the target substance; ω i Let be the weight of the i-th evaluation indicator; x i This represents the value assigned to the i-th evaluation index.

9. A system for evaluating the degree of influence of a target substance on the gastric mucosa, characterized in that, The system includes: The model building unit is used to determine the corresponding gastric environment in a bionic stomach based on user-defined evaluation requirements, thereby obtaining a gastric model; among which, The biomimetic stomach contains cultured cells of gastric mucosal epithelial cells. The driving unit is used to generate motion parameters of the stomach model based on the evaluation requirements set by the user, and to drive the stomach model to start digestion movement based on the motion parameters after the target substance is placed in the bionic stomach. The evaluation unit is used to collect digestion result information from the gastric model after a predetermined period, and to assign values ​​to each evaluation index based on the digestion result information, and to determine the evaluation result of the degree of influence of the target substance on the gastric mucosa based on the assigned evaluation indexes.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the method for evaluating the degree of influence of the target substance on the gastric mucosa as described in any one of claims 1-8.

Images