A method and system for environmental regulation in the process of culturing tumor immune cells

Abstract

The present invention relates to the field of biological culture equipment control technology, in particular to an environmental control method and system in the process of tumor immune cell culture. Various preset culture environment data of the culture equipment at the preset culture time node are obtained in the preset culture scheme; various actual culture environment data of the culture equipment are compared with the preset culture environment data; if the culture environment state of the culture equipment at the preset culture time node is normal, the culture equipment is not regulated; if the culture environment state of the culture equipment at the preset culture time node is abnormal, the cell state of the target tumor immune cells in the culture equipment is analyzed; the culture equipment is regulated according to the cell state of the target tumor immune cells in the culture equipment, so as to realize the dynamic optimization of the tumor immune cell culture environment and improve the success rate and efficiency of cell culture.

Description

Technical Field

[0001] The present invention relates to the technical field of biological culture equipment regulation, and in particular to an environment regulation method and system in a tumor immune cell culture process. Background Art

[0002] Tumor immune cell culture is an important technology that simulates the in vivo tumor microenvironment in vitro to study tumor immune responses and develop immunotherapy strategies. With the progress of tumor immunotherapy, the demand for environmental regulation methods in the process of tumor immune cell culture is increasing. These methods involve fine regulation of temperature, pH value, gas environment, nutrient supply, cytokine concentration and other aspects to ensure the physiological state of cells, promote immune response and optimize therapeutic effects. Traditional culture methods have certain limitations, such as difficulty in simulating tumor microenvironment characteristics such as hypoxia and acidity, and lack of real-time monitoring of cell activity and function. Therefore, it is crucial to develop an efficient and precise environmental regulation method for tumor immune cell culture, which can not only improve the success rate and stability of cell culture, but also provide more reliable experimental data and theoretical basis for tumor immunotherapy. Summary of the invention

[0003] The present invention overcomes the shortcomings of the prior art, such as difficulty in accurately regulating the culture environment characteristics and lack of real-time monitoring of cell activity and function, and provides an environment regulation method and system in the process of tumor immune cell culture.

[0004] To achieve the above object, the present invention discloses a method for regulating the environment during the culture of tumor immune cells, comprising the following steps:

[0005] Obtaining a preset culture scheme for target tumor immune cells, and obtaining various preset culture environment data of a culture device at a preset culture time node in the preset culture scheme;

[0006] Acquire various actual culture environment data of the culture equipment at the preset culture time node, compare the various actual culture environment data of the culture equipment with the preset culture environment data, and obtain the culture environment status of the culture equipment at the preset culture time node;

[0007] If the cultivation environment state of the cultivation equipment at the preset cultivation time node is normal, no regulation and control processing is performed on the cultivation equipment;

[0008] If the culture environment state of the culture device at the preset culture time node is abnormal, the cell state of the target tumor immune cells in the culture device is analyzed to obtain the cell state of the target tumor immune cells in the culture device;

[0009] regulating and processing the culture device according to the cell status of the target tumor immune cells in the culture device;

[0010] The culture environment data include temperature, pH value, carbon dioxide concentration, humidity, glucose concentration, amino acid concentration, growth factor concentration, serum concentration, osmotic pressure and conductivity.

[0011] More specifically, various actual culture environment data of the culture equipment are compared with the preset culture environment data to obtain the culture environment status of the culture equipment at the preset culture time node, specifically:

[0012] Obtaining a preset culture scheme for target tumor immune cells, and determining, according to the preset culture scheme, the limit deviation thresholds of various culture environment data of the culture device at a preset culture time node;

[0013] Calculate the difference between various actual culture environment data and corresponding preset culture environment data to obtain the deviation value of various actual culture environment data of the culture device at the preset culture time node; and compare the deviation value of various actual culture environment data with the corresponding extreme deviation threshold;

[0014] If the deviation value of a certain type of actual culture environment data is greater than the corresponding extreme deviation threshold, the actual culture environment data of the culture device is calibrated as abnormal culture environment data; if the deviation value of a certain type of actual culture environment data is not greater than the corresponding extreme deviation threshold, the actual culture environment data of the culture device is calibrated as normal culture environment data;

[0015] Analyze whether there is abnormal culture environment data in the culture device; if there is abnormal culture environment data in the culture device, mark the culture environment state of the culture device at a preset culture time node as an abnormal state;

[0016] If there is no abnormal culture environment data in the culture equipment, the culture environment status of the culture equipment at the preset culture time node is calibrated as a normal state.

[0017] More specifically, if the culture environment state of the culture device at the preset culture time node is abnormal, the cell state of the target tumor immune cells in the culture device is analyzed to obtain the cell state of the target tumor immune cells in the culture device, specifically:

[0018] Based on the big data network, the characteristic images of abnormal tumor immune cells corresponding to various abnormal cell states of target tumor immune cells are retrieved during the culture process to obtain the characteristic images of various abnormal tumor immune cells;

[0019] Constructing a knowledge graph and importing characteristic images of various abnormal tumor immune cells into the knowledge graph;

[0020] If the culture environment state of the culture device at the preset culture time node is abnormal, a microscopic image of the target tumor immune cells in the culture device is obtained based on an optical microscope;

[0021] Dividing the microscopic image into a number of grid units of fixed size based on a grid division method, and randomly selecting a preset number of grid units from all the grid units as sub-image regions; wherein each grid unit is used as a candidate region;

[0022] Adjust the contrast, brightness and sharpness of each sub-image area to the preset values ​​to make the cell features more prominent;

[0023] Based on the connected domain analysis algorithm, single target tumor immune cells in each sub-image area are separated from the background, and characteristic images of target tumor immune cells in several culture devices are extracted.

[0024] The following steps are also included:

[0025] Extracting characteristic images of various abnormal tumor immune cells from the knowledge graph, and obtaining characteristic images of each extracted target tumor immune cell;

[0026] Calculate the cosine similarity between the characteristic images of each target tumor immune cell and the characteristic images of various abnormal tumor immune cells;

[0027] If the cosine similarity between a characteristic image of a target tumor immune cell and a characteristic image of an abnormal tumor immune cell is greater than a preset similarity threshold, the target tumor immune cell is marked as an abnormal tumor immune cell;

[0028] If the cosine similarity between the characteristic image of a target tumor immune cell and the characteristic images of various abnormal tumor immune cells is not greater than the preset similarity threshold, the target tumor immune cell is marked as a normal tumor immune cell;

[0029] Counting the total number of abnormal tumor immune cells and the total number of normal tumor immune cells; performing ratio processing on the total number of abnormal tumor immune cells and the total number of normal tumor immune cells to obtain the proportion of abnormal tumor immune cells;

[0030] Determine whether the proportion of abnormal tumor immune cells is greater than a preset proportion; if greater, mark the cell state of the target tumor immune cells currently cultured in the culture device as an abnormal state; if not greater, mark the cell state of the target tumor immune cells currently cultured in the culture device as a normal state.

[0031] More specifically, the culture device is regulated and processed according to the cell state of the target tumor immune cells in the culture device, specifically:

[0032] Acquire work log information of the culture device, and extract various abnormal culture environment data corresponding to abnormal culture environment status of the culture device during historical work processes from the work log information;

[0033] Collecting various abnormal culture environment data corresponding to abnormal culture environment states of the culture equipment during historical working processes, and obtaining feature data sets corresponding to various abnormal culture environment states of the culture equipment during historical working processes;

[0034] At the same time, the historical adjustment schemes corresponding to various abnormal conditions of the culture environment state of the culture equipment during the historical working process are obtained from the work log information, and the culture environment accuracy level of the culture equipment after adjustment by various historical adjustment schemes is obtained;

[0035] The historical adjustment scheme with the highest level of culture environment accuracy is used as the optimal adjustment scheme for the corresponding abnormal culture environment state, and the optimal adjustment scheme corresponding to various abnormal culture environment states of the culture equipment in the historical working process is obtained;

[0036] The optimal adjustment scheme corresponding to various abnormal culture environment states of the culture equipment during the historical working process is bundled with the corresponding feature data set to obtain several feature data packets; a knowledge base is constructed based on each feature data packet.

[0037] The following steps are also included:

[0038] If the culture environment state of the culture device at the preset culture time node is abnormal and the cell state of the target tumor immune cells currently cultured in the culture device is normal, then the actual culture environment data marked as abnormal culture environment data in the culture device is obtained to obtain an abnormal actual culture environment data set;

[0039] and extracting a feature data set in each feature data packet from the knowledge base, calculating a Jaccard similarity coefficient between the abnormal actual cultivation environment data set and each feature data set, and obtaining a plurality of Jaccard similarity coefficients;

[0040] Sorting the Jaccard similarity coefficients by size to obtain the maximum Jaccard similarity coefficient, defining the feature data set corresponding to the maximum Jaccard similarity coefficient as a matching feature data set, and locating the feature data packet to which the matching feature data set belongs in the knowledge base;

[0041] The corresponding optimal adjustment scheme is extracted from the located characteristic data packet, and the culture equipment is regulated and processed according to the extracted optimal adjustment scheme.

[0042] The following steps are also included:

[0043] If the culture environment status of the culture device at the preset culture time node is abnormal and the cell status of the target tumor immune cells currently cultured in the culture device is abnormal, the culture device is controlled to terminate the culture, and a culture termination information is generated, which is sent to the preset terminal for display.

[0044] In addition, to achieve the above-mentioned purpose, the present invention further discloses an environment control system in a tumor immune cell culture process, wherein the environment control system in a tumor immune cell culture process comprises a memory and a processor, wherein the memory stores an environment control method program in a tumor immune cell culture process, and when the environment control method program in a tumor immune cell culture process is executed by the processor, the following steps are implemented:

[0045] Obtaining a preset culture scheme for target tumor immune cells, and obtaining various preset culture environment data of a culture device at a preset culture time node in the preset culture scheme;

[0046] Acquire various actual culture environment data of the culture equipment at the preset culture time node, compare the various actual culture environment data of the culture equipment with the preset culture environment data, and obtain the culture environment status of the culture equipment at the preset culture time node;

[0047] If the cultivation environment state of the cultivation equipment at the preset cultivation time node is normal, no regulation and control processing is performed on the cultivation equipment;

[0048] If the culture environment state of the culture device at the preset culture time node is abnormal, the cell state of the target tumor immune cells in the culture device is analyzed to obtain the cell state of the target tumor immune cells in the culture device;

[0049] regulating and processing the culture device according to the cell status of the target tumor immune cells in the culture device;

[0050] The culture environment data include temperature, pH value, carbon dioxide concentration, humidity, glucose concentration, amino acid concentration, growth factor concentration, serum concentration, osmotic pressure and conductivity.

[0051] In addition, to achieve the above-mentioned purpose, the present invention also discloses a computer-readable storage medium, which includes a program for an environmental regulation method in a tumor immune cell culture process. When the program for an environmental regulation method in a tumor immune cell culture process is executed by a processor, the steps of any one of the environmental regulation methods in a tumor immune cell culture process are implemented.

[0052] The present invention solves the technical defects existing in the background technology, and has the following beneficial effects: obtaining various preset culture environment data of the culture equipment at the preset culture time node in the preset culture scheme; comparing various actual culture environment data of the culture equipment with the preset culture environment data; if the culture environment state of the culture equipment at the preset culture time node is normal, then the culture equipment is not regulated; if the culture environment state of the culture equipment at the preset culture time node is abnormal, then the cell state of the target tumor immune cells in the culture equipment is analyzed to obtain the cell state of the target tumor immune cells in the culture equipment; the culture equipment is regulated according to the cell state of the target tumor immune cells in the culture equipment. The present invention realizes dynamic optimization and emergency intervention of the tumor immune cell culture environment through real-time monitoring, data analysis and intelligent decision-making, which not only improves the success rate and efficiency of cell culture, but also ensures the controllability and safety of the cell culture process. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0054] Figure 1 This is a flow chart of the overall method of an environmental regulation method in the process of culturing tumor immune cells;

[0055] Figure 2 A partial method flow chart of a method for environmental regulation in the process of culturing tumor immune cells;

[0056] Figure 3 This is a system block diagram of an environmental control system during the tumor immune cell culture process. DETAILED DESCRIPTION

[0057] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0058] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0059] like Figure 1 As shown, the present invention discloses a method for regulating the environment in the process of culturing tumor immune cells, comprising the following steps:

[0060] S102: Obtaining a preset culture scheme for target tumor immune cells, and obtaining various preset culture environment data of a culture device at a preset culture time node in the preset culture scheme;

[0061] S104: acquiring various actual cultivation environment data of the cultivation equipment at a preset cultivation time node, comparing the various actual cultivation environment data of the cultivation equipment with the preset cultivation environment data, and obtaining the cultivation environment status of the cultivation equipment at the preset cultivation time node;

[0062] S106: If the culture environment state of the culture device at the preset culture time node is normal, no regulation or control is performed on the culture device;

[0063] S108: If the culture environment state of the culture device at the preset culture time node is abnormal, analyzing the cell state of the target tumor immune cells in the culture device to obtain the cell state of the target tumor immune cells in the culture device;

[0064] S110: regulating and processing the culture device according to the cell status of the target tumor immune cells in the culture device;

[0065] The culture environment data include temperature, pH value, carbon dioxide concentration, humidity, glucose concentration, amino acid concentration, growth factor concentration, serum concentration, osmotic pressure and conductivity.

[0066] It should be noted that the preset culture program for target tumor immune cells refers to a set of detailed and standardized operating procedures designed in advance by relevant technical personnel for specific tumor types or specific immune cell subpopulations, which aims to simulate or create an ideal cell growth environment to promote the proliferation, differentiation, activation and function of target immune cells. The preset culture program usually includes culture medium formula, various preset culture environment data, cell culture density and the extreme deviation threshold of culture environment data.

[0067] More specifically, if Figure 2As shown, various actual culture environment data of the culture equipment are compared with the preset culture environment data to obtain the culture environment status of the culture equipment at the preset culture time node, specifically:

[0068] S202: Obtaining a preset culture scheme for target tumor immune cells, and determining, according to the preset culture scheme, a limit deviation threshold of various culture environment data of a culture device at a preset culture time node;

[0069] S204: Calculate the difference between various actual cultivation environment data and corresponding preset cultivation environment data to obtain the deviation value of various actual cultivation environment data of the cultivation device at the preset cultivation time node; and compare the deviation value of various actual cultivation environment data with the corresponding extreme deviation threshold;

[0070] S206: if the deviation value of a certain type of actual culture environment data is greater than the corresponding extreme deviation threshold, the actual culture environment data of the culture device is calibrated as abnormal culture environment data; if the deviation value of a certain type of actual culture environment data is not greater than the corresponding extreme deviation threshold, the actual culture environment data of the culture device is calibrated as normal culture environment data;

[0071] S208: analyzing whether there is abnormal culture environment data in the culture device; if there is abnormal culture environment data in the culture device, marking the culture environment state of the culture device at a preset culture time node as an abnormal state;

[0072] S210: If there is no abnormal culture environment data in the culture device, the culture environment state of the culture device at the preset culture time node is calibrated as a normal state.

[0073] It should be noted that the limit deviation thresholds of various culture environment data (such as temperature, humidity, gas composition, nutrient concentration, etc.) of the culture equipment at a specific time node are determined by the preset culture scheme. This step ensures that the culture conditions are strictly controlled within the allowable range at the set time point to provide the best environment for cell growth and function. Next, the deviation value is calculated by real-time monitoring of the actual culture environment data and comparing it with the preset limit deviation threshold. When it is found that the deviation value of a certain actual culture environment data exceeds the preset limit threshold, it means that the environmental condition may have an adverse effect on the growth or function of the cell, and it is marked as "abnormal culture environment data". On the contrary, if the deviation value does not exceed the threshold, the environmental data is considered to be "normal". Further, by analyzing the environmental data in the culture equipment as a whole, it can be determined whether there is any abnormal culture environment data. If there is indeed an abnormality, it will be regarded as the "abnormal state" of the culture equipment at a specific time node, indicating that measures need to be taken to adjust the culture conditions to restore to a normal state. On the contrary, if all environmental data are within the normal range, it can be confirmed that the current culture state is "normal state". This method realizes real-time monitoring and precise management of environmental data during the tumor immune cell culture process. Through accurate calculation and comparison of deviation values, it can timely discover and correct environmental problems that may affect cell growth and function, thereby improving the success rate of cell culture.

[0074] More specifically, if the culture environment state of the culture device at the preset culture time node is abnormal, the cell state of the target tumor immune cells in the culture device is analyzed to obtain the cell state of the target tumor immune cells in the culture device, specifically:

[0075] Based on the big data network, the characteristic images of abnormal tumor immune cells corresponding to various abnormal cell states of target tumor immune cells are retrieved during the culture process to obtain the characteristic images of various abnormal tumor immune cells;

[0076] Constructing a knowledge graph and importing characteristic images of various abnormal tumor immune cells into the knowledge graph;

[0077] If the culture environment state of the culture device at the preset culture time node is abnormal, a microscopic image of the target tumor immune cells in the culture device is obtained based on an optical microscope;

[0078] Dividing the microscopic image into a number of grid units of fixed size based on a grid division method, and randomly selecting a preset number of grid units from all the grid units as sub-image regions; wherein each grid unit is used as a candidate region;

[0079] Adjust the contrast, brightness and sharpness of each sub-image area to the preset values ​​to make the cell features more prominent;

[0080] Based on the connected domain analysis algorithm, single target tumor immune cells in each sub-image area are separated from the background, and characteristic images of target tumor immune cells in several culture devices are extracted.

[0081] Among them, the characteristic images corresponding to tumor immune cells refer to the unique image performances captured under a microscope or through imaging technology, which can significantly distinguish and identify different types of tumor immune cells. These characteristic images usually contain information such as cell morphology, size, expression of surface markers, intracellular structure, and interaction with other cells or extracellular matrix. The characteristic images corresponding to tumor immune cells can be obtained through advanced imaging technologies such as fluorescence microscopy, confocal microscopy, electron microscopy, and high-throughput imaging technology.

[0082] It should be noted that, through big data network retrieval, a large number of characteristic images of target tumor immune cells when various cell states are abnormal during the culture process are collected and integrated to build a database containing various abnormal cell features. Then, by constructing a knowledge graph, these abnormal characteristic images are structured and stored for subsequent query and analysis. When the system is running, when the culture device is detected to be in an abnormal state at a preset time node, an optical microscope is started to obtain a microscopic image of the target tumor immune cells in the current culture device. Then, the grid division method is used to divide these microscopic images into multiple small, fixed-size grid units, and some grid units are randomly selected as sub-image areas to further refine the analysis object. In order to make the cell features more prominent, the contrast, brightness and sharpness of each sub-image area are uniformly preset and adjusted. Finally, the connected domain analysis algorithm is used to separate individual tumor immune cells from these sub-image areas, extract and analyze their features, and thus obtain the characteristic images of the target tumor immune cells in the culture device. Through online monitoring and instant analysis, the system can identify abnormal conditions that occur during the culture process in real time, take timely environmental control measures to avoid deterioration of cell status, and achieve efficient and accurate monitoring of the culture status of tumor immune cells.

[0083] It should be noted that the connected domain analysis algorithm finds connected cell regions by identifying and connecting pixels or regions with similar features. In cell images, cells usually have specific brightness, contrast and texture features, which form a clear contrast with the background. The algorithm first preprocesses each sub-image area, such as denoising, edge detection, etc., to enhance the boundaries and details of the cells. Then, by calculating the statistical features of each pixel or region (such as grayscale value, texture features, etc.), and comparing them with the preset cell feature template, the parts that may belong to the same cell are identified. Once the connected cell region is identified, the algorithm is further refined to accurately separate individual cells through methods such as threshold segmentation and morphological operations. In this process, the segmentation technology of the cell nucleus and cytoplasm may be applied to more accurately identify different parts of the cell. Finally, in the sub-image area processed by the connected domain analysis algorithm, a single target tumor immune cell is successfully identified and separated from the background.

[0084] The following steps are also included:

[0085] Extracting characteristic images of various abnormal tumor immune cells from the knowledge graph, and obtaining characteristic images of each extracted target tumor immune cell;

[0086] Calculate the cosine similarity between the characteristic images of each target tumor immune cell and the characteristic images of various abnormal tumor immune cells;

[0087] If the cosine similarity between a characteristic image of a target tumor immune cell and a characteristic image of an abnormal tumor immune cell is greater than a preset similarity threshold, the target tumor immune cell is marked as an abnormal tumor immune cell;

[0088] If the cosine similarity between the characteristic image of a target tumor immune cell and the characteristic images of various abnormal tumor immune cells is not greater than the preset similarity threshold, the target tumor immune cell is marked as a normal tumor immune cell;

[0089] Counting the total number of abnormal tumor immune cells and the total number of normal tumor immune cells; performing ratio processing on the total number of abnormal tumor immune cells and the total number of normal tumor immune cells to obtain the proportion of abnormal tumor immune cells;

[0090] Determine whether the proportion of abnormal tumor immune cells is greater than a preset proportion; if greater, mark the cell state of the target tumor immune cells currently cultured in the culture device as an abnormal state; if not greater, mark the cell state of the target tumor immune cells currently cultured in the culture device as a normal state.

[0091] It should be noted that the system first collects and analyzes the characteristic images of various abnormal tumor immune cells through the constructed knowledge graph. These characteristic images include cell morphology, size, color, texture, etc., which are important bases for identifying cell status. Then, the system evaluates whether the target cell exhibits an abnormal state by calculating the cosine similarity between the characteristic image of the target tumor immune cell and the characteristic image of the abnormal cell in the knowledge graph. Cosine similarity is an indicator to measure the similarity between two vectors, and is used here to quantify the similarity between the target cell and the known abnormal cell. If the cosine similarity between the characteristic image of the target cell and the characteristic image of a certain abnormal cell exceeds the preset threshold, it means that the target cell is highly similar to the abnormal cell in terms of morphology, structure, etc., and is therefore marked as an abnormal tumor immune cell. Conversely, if the similarity of all comparisons does not exceed the threshold, the target cell is judged to be a normal tumor immune cell. After that, the system counts the number of abnormal cells and normal cells and calculates the abnormal cell ratio, that is, the ratio of the number of abnormal cells to the total number of cells. This ratio directly reflects the presence of abnormal cells in the culture environment and is a key indicator for evaluating cell status. Finally, the cell status label is determined based on whether the abnormal cell ratio exceeds the preset threshold. If the proportion exceeds the threshold, it means that the proportion of abnormal cells is high, and the cell state is marked as abnormal; otherwise, the cell state is marked as normal. This method can realize the automated and precise evaluation of the state of tumor immune cells, timely discover and deal with abnormal cells, provide more reliable data support for tumor immune cell culture, reduce the subjectivity of human judgment, improve the accuracy and efficiency of cell state evaluation, and further improve the accuracy of subsequent regulation of culture equipment.

[0092] More specifically, the culture device is regulated and processed according to the cell state of the target tumor immune cells in the culture device, specifically:

[0093] Acquire work log information of the culture device, and extract various abnormal culture environment data corresponding to abnormal culture environment status of the culture device during historical work processes from the work log information;

[0094] Collecting various abnormal culture environment data corresponding to abnormal culture environment states of the culture equipment during historical working processes, and obtaining feature data sets corresponding to various abnormal culture environment states of the culture equipment during historical working processes;

[0095] At the same time, the historical adjustment schemes corresponding to various abnormal conditions of the culture environment state of the culture equipment during the historical working process are obtained from the work log information, and the culture environment accuracy level of the culture equipment after adjustment by various historical adjustment schemes is obtained;

[0096] The historical adjustment scheme with the highest level of culture environment accuracy is used as the optimal adjustment scheme for the corresponding abnormal culture environment state, and the optimal adjustment scheme corresponding to various abnormal culture environment states of the culture equipment in the historical working process is obtained;

[0097] The optimal adjustment scheme corresponding to various abnormal culture environment states of the culture equipment during the historical working process is bundled with the corresponding feature data set to obtain several feature data packets; a knowledge base is constructed based on each feature data packet.

[0098] Among them, the work log information of the culture equipment is a series of detailed information automatically generated and recorded by the culture equipment. This information covers various key parameters and states of the equipment during operation, including but not limited to time, date, equipment operating status, environmental parameters (such as temperature, humidity, light intensity, gas composition, etc.), equipment fault alarms, maintenance records, sample processing steps, abnormal events during the culture process, control records, etc.

[0099] The historical adjustment plan corresponding to various abnormal culture environment conditions that occurred in the culture equipment during its historical operation refers to a series of targeted adjustment measures taken during the operation of the equipment to restore the environmental parameters to the normal range when it is detected that the culture environment parameters (such as temperature, humidity, gas composition, etc.) deviate from the predetermined standards. These measures include but are not limited to adjusting the heating or cooling system, changing the gas flow, adjusting the ventilation rate, modifying the humidity control strategy, etc.

[0100] It should be noted that the system first obtains and parses the work log information of the culture equipment to extract the abnormal culture environment status and the corresponding abnormal culture environment data encountered in the historical work, such as the abnormal values ​​of parameters such as temperature, humidity, and gas composition. These data are collected and organized to form a feature data set for subsequent analysis and learning. Then, the system further obtains the historical adjustment schemes taken for these abnormal situations from the work log, as well as the accuracy level of the culture environment after these schemes are executed. The higher the accuracy level, the more effective the adjustment scheme. Based on this, the system selects the adjustment scheme that performs best in dealing with specific abnormal situations, takes it as the best adjustment scheme, and bundles it with the corresponding feature data set to generate a series of feature data packets. Finally, these feature data packets are used to build a knowledge base to form a culture environment adjustment knowledge system based on historical experience and data-driven. The knowledge base not only records the best adjustment strategies under specific abnormal situations, but also contains the principles and logic behind these strategies, providing a reference for the environmental regulation of culture equipment. Based on the constructed knowledge base, the system can predict possible abnormal situations in the culture environment and quickly recommend appropriate adjustment schemes to improve response speed and processing efficiency.

[0101] The following steps are also included:

[0102] If the culture environment state of the culture device at the preset culture time node is abnormal and the cell state of the target tumor immune cells currently cultured in the culture device is normal, then the actual culture environment data marked as abnormal culture environment data in the culture device is obtained to obtain an abnormal actual culture environment data set;

[0103] and extracting a feature data set in each feature data packet from the knowledge base, calculating a Jaccard similarity coefficient between the abnormal actual cultivation environment data set and each feature data set, and obtaining a plurality of Jaccard similarity coefficients;

[0104] Sorting the Jaccard similarity coefficients by size to obtain the maximum Jaccard similarity coefficient, defining the feature data set corresponding to the maximum Jaccard similarity coefficient as a matching feature data set, and locating the feature data packet to which the matching feature data set belongs in the knowledge base;

[0105] The corresponding optimal adjustment scheme is extracted from the located characteristic data packet, and the culture equipment is regulated and processed according to the extracted optimal adjustment scheme.

[0106] The following steps are also included:

[0107] If the culture environment status of the culture device at the preset culture time node is abnormal and the cell status of the target tumor immune cells currently cultured in the culture device is abnormal, the culture device is controlled to terminate the culture, and a culture termination information is generated, which is sent to the preset terminal for display.

[0108] It should be noted that by monitoring the environmental state of the culture equipment at the preset time node and the state of the target tumor immune cells currently being cultured, a series of intelligent control measures are taken to optimize the culture environment and ensure the quality and efficiency of cell culture. Specifically, first, when the culture equipment detects an abnormal environmental state at a preset time point, but the cell state is still considered normal, the system will obtain and analyze the abnormal culture environment data to form an abnormal actual culture environment data set. At the same time, the system extracts feature data packets related to cell culture from the knowledge base, which contain information about the best adjustment scheme under the historical environment. The system calculates the Jaccard similarity coefficient between the abnormal actual culture environment data set and each feature data set, which is an indicator of the similarity between two sets and is used to find the historical environment data that best matches the abnormal environment. By comparison, the system identifies the historical environment data set that best matches the abnormal environment, the so-called "matching feature data set". Subsequently, the system locates and extracts the historical best adjustment scheme corresponding to the data set, which is used to guide the culture equipment to adjust the environment to restore to suitable culture conditions.

[0109] If an abnormal environmental state is detected at a preset time point, and the cell state is also abnormal, this indicates that the current culture environment is no longer suitable for cell growth. The system will immediately control the culture equipment to terminate the culture process and generate information on terminating the culture, which will be displayed through the preset terminal. In this way, the system can not only adjust the environment in a timely manner to maintain suitable conditions for cell growth, but also take decisive measures when the environment deteriorates irreversibly, and terminate the culture of cells with abnormal activity status in a timely manner, saving culture resources and avoiding unnecessary waste.

[0110] In general, through real-time monitoring, data analysis and intelligent decision-making, dynamic optimization and emergency intervention of the tumor immune cell culture environment are achieved, which not only improves the success rate and efficiency of cell culture, but also ensures the controllability and safety of the cell culture process. In this way, the system effectively integrates historical data and real-time monitoring information, providing intelligent decision-making support for cell culture.

[0111] In addition, the method further comprises the following steps:

[0112] Acquire the control function information of each sub-environment control module in the culture device, and perform feature extraction processing on various culture environment data that need to be regulated in the culture device to obtain data feature information of various culture environment data;

[0113] The Granger causality test method is used to analyze the correlation weight value between the regulatory function information of each sub-environment regulation module and the data feature information of various culture environment data;

[0114] If the correlation weight value between the control function information of a certain sub-environment control module and the data feature information of a certain type of cultivation environment data is greater than a preset weight value, the sub-environment control module is marked as a causal correlation sub-environment control module of the cultivation environment data;

[0115] Repeat the above steps to analyze and obtain the causal correlation sub-environment regulation modules of various cultivation environment data; and construct a second knowledge graph according to the causal correlation sub-environment regulation modules of various cultivation environment data;

[0116] If the deviation value of a certain type of actual cultivation environment data is greater than the corresponding limit deviation threshold, the actual cultivation environment data is input into the second knowledge graph for pairing, and the causal correlation sub-environment regulation module of the actual cultivation environment data is obtained by pairing;

[0117] Obtaining electrical parameter information of the causal correlation sub-environment control module of the actual cultivation environment data, the electrical parameter information including current, voltage and operating power;

[0118] The electrical parameter information of the causal correlation sub-environment control module of the actual cultivation environment data is imported into a pre-trained support vector machine model for fault diagnosis, and the fault probability of the causal correlation sub-environment control module is obtained by diagnosis;

[0119] If the failure probability is greater than the preset failure probability, failure warning information is generated.

[0120] It should be noted that, first, the control function information of each sub-environment control module is extracted from the culture equipment, and the feature extraction of the culture environment data to be regulated is performed to obtain the data feature information. Then, the Granger causality test method is used to analyze the correlation weight value between the control function information and the data feature information to determine which sub-environment control modules have a causal relationship with the specific culture environment data. When the correlation weight value of a sub-environment control module exceeds the preset threshold, the module is identified as having a causal relationship with the specific culture environment data and is marked as the corresponding causal correlation sub-environment control module. By repeating this process, the system constructs a second knowledge graph containing causal correlation sub-environment control modules of various culture environment data. In actual operation, if it is detected that the deviation value of a certain actual culture environment data exceeds the limit deviation threshold, the system will input the data into the second knowledge graph for pairing to find the corresponding causal correlation sub-environment control module. Next, the system obtains the electrical parameter information of the module, including current, voltage and operating power, and inputs this information into the pre-trained support vector machine (SVM) model for fault diagnosis, thereby calculating the fault probability. If the calculated failure probability exceeds the preset failure probability threshold, the system will generate a fault warning message to prompt the operator or maintenance personnel to conduct inspection and repair. It can timely detect potential equipment problems, reduce the downtime of culture equipment, and improve the reliability and efficiency of culture equipment.

[0121] Among them, the support vector machine model (SVM) is a commonly used model for fault diagnosis and analysis. Here is a brief overview of its working and training principles: In the fault diagnosis of the environmental control module, the support vector machine model identifies and predicts faults by analyzing the electrical parameter information of the control module (such as current, voltage, and operating power). SVM is a supervised learning algorithm that finds an optimal hyperplane in a high-dimensional space that can maximize the separation of data of different categories. The SVM model first needs to be learned through a training data set, where the training data set contains electrical parameter information and corresponding fault labels (normal or faulty). Through this process, the SVM model can learn the complex relationship between electrical parameter information and fault status, and construct a decision boundary to distinguish between normal and faulty states. When new electrical parameter information is input into the trained SVM model, the model predicts which category (i.e., normal or faulty) the data belongs to based on the learned decision boundary. If the prediction result shows that the decision boundary between the electrical parameter information and the fault state is very close or crosses the boundary, the SVM model will give a high fault probability, thereby issuing a fault warning.

[0122] In addition, the method further comprises the following steps:

[0123] Acquire an actual mitochondrial membrane potential distribution map of tumor immune cells in a culture medium at a preset time point, and calculate a structural similarity index between the actual mitochondrial membrane potential distribution map and a preset mitochondrial membrane potential distribution map;

[0124] If the structural similarity index between the actual mitochondrial membrane potential distribution map and the preset mitochondrial membrane potential distribution map is not greater than the preset index threshold, the actual mitochondrial membrane potential distribution map is subjected to matrix transformation processing to obtain a grayscale co-occurrence matrix of the actual mitochondrial membrane potential distribution map, thereby obtaining a first grayscale co-occurrence matrix;

[0125] and performing matrix change processing on the preset mitochondrial membrane potential distribution map to obtain a grayscale co-occurrence matrix of the preset mitochondrial membrane potential distribution map, thereby obtaining a second grayscale co-occurrence matrix;

[0126] Traversing the elements of the first gray level co-occurrence matrix and the second gray level co-occurrence matrix at the same matrix position; calculating the element difference between the elements of the first gray level co-occurrence matrix and the second gray level co-occurrence matrix at the same matrix position;

[0127] If the element difference between the elements at the same matrix position of the first gray level co-occurrence matrix and the second gray level co-occurrence matrix is ​​greater than a preset difference threshold, recalibrating the elements of the corresponding matrix position nodes in the first gray level co-occurrence matrix to 0;

[0128] If the element difference between the elements at the same matrix position of the first gray level co-occurrence matrix and the second gray level co-occurrence matrix is ​​not greater than a preset difference threshold, the elements of the corresponding matrix position nodes in the first gray level co-occurrence matrix are recalibrated as;

[0129] And so on, until all elements in the same matrix position of the first gray level co-occurrence matrix and the second gray level co-occurrence matrix are traversed to obtain a new first gray level co-occurrence matrix;

[0130] The position region marked as 0 in the new first gray-level co-occurrence matrix is ​​obtained, and is defined as an abnormal tumor immune cell proliferation region; the position region marked as 1 in the new first gray-level co-occurrence matrix is ​​obtained, and is defined as a normal tumor immune cell proliferation region;

[0131] The abnormal tumor immune cell proliferation area is sent to a preset terminal for display, so as to formulate a nutrient delivery plan for the abnormal tumor immune cell proliferation area.

[0132] It should be noted that the actual mitochondrial membrane potential distribution map of tumor immune cells in the culture medium is obtained at a preset time node, and compared with the preset mitochondrial membrane potential distribution map, and the structural similarity index between the two is calculated. If the structural similarity index between the actual potential distribution map and the preset potential distribution map is lower than the preset threshold, it indicates that there may be a problem with the cell proliferation state. For further analysis, the system performs matrix transformation processing on the actual potential distribution map to generate a first grayscale co-occurrence matrix, and performs the same processing on the preset potential distribution map to generate a second grayscale co-occurrence matrix. By comparing the elements of the two grayscale co-occurrence matrices at the same position, the element difference between them is calculated. If the difference exceeds the preset threshold, the system marks the corresponding element in the first grayscale co-occurrence matrix as 0, indicating that the cell proliferation in the area is abnormal; if the difference is not greater than the preset threshold, it is marked as 1, indicating that the cell proliferation is normal. In this way, the system can identify abnormal and normal areas of tumor immune cell proliferation, and send the information of the abnormal area to the preset terminal for display. This helps to timely discover cell proliferation problems and formulate corresponding nutrient delivery plans to optimize cell culture conditions and improve the success rate and efficiency of cell culture.

[0133] In addition, the present invention also discloses an environmental control system in the process of culturing tumor immune cells, such as Figure 3 As shown, the environmental control system in the tumor immune cell culture process includes a memory 41 and a processor 62. The memory 41 stores an environmental control method program in the tumor immune cell culture process. When the environmental control method program in the tumor immune cell culture process is executed by the processor 62, the following steps are implemented:

[0134] Obtaining a preset culture scheme for target tumor immune cells, and obtaining various preset culture environment data of a culture device at a preset culture time node in the preset culture scheme;

[0135] Acquire various actual culture environment data of the culture equipment at the preset culture time node, compare the various actual culture environment data of the culture equipment with the preset culture environment data, and obtain the culture environment status of the culture equipment at the preset culture time node;

[0136] If the cultivation environment state of the cultivation equipment at the preset cultivation time node is normal, no regulation and control processing is performed on the cultivation equipment;

[0137] If the culture environment state of the culture device at the preset culture time node is abnormal, the cell state of the target tumor immune cells in the culture device is analyzed to obtain the cell state of the target tumor immune cells in the culture device;

[0138] regulating and processing the culture device according to the cell status of the target tumor immune cells in the culture device;

[0139] The culture environment data include temperature, pH value, carbon dioxide concentration, humidity, glucose concentration, amino acid concentration, growth factor concentration, serum concentration, osmotic pressure and conductivity.

[0140] In addition, the present invention also discloses a computer-readable storage medium, which includes a program for an environmental regulation method in a tumor immune cell culture process. When the program for an environmental regulation method in a tumor immune cell culture process is executed by a processor, the steps of any one of the methods for environmental regulation in a tumor immune cell culture process are implemented.

[0141] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0142] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0143] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0144] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0145] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0146] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for environmental regulation in the process of culturing tumor immune cells. It is characterized in that The following steps are involved: Obtaining a preset culture scheme for target tumor immune cells, and obtaining various preset culture environment data of a culture device at a preset culture time node in the preset culture scheme; Acquire various actual culture environment data of the culture equipment at the preset culture time node, compare the various actual culture environment data of the culture equipment with the preset culture environment data, and obtain the culture environment status of the culture equipment at the preset culture time node; If the cultivation environment state of the cultivation equipment at the preset cultivation time node is normal, no regulation and control processing is performed on the cultivation equipment; If the culture environment state of the culture device at the preset culture time node is abnormal, the cell state of the target tumor immune cells in the culture device is analyzed to obtain the cell state of the target tumor immune cells in the culture device; regulating and processing the culture device according to the cell status of the target tumor immune cells in the culture device; The culture environment data include temperature, pH value, carbon dioxide concentration, humidity, glucose concentration, amino acid concentration, growth factor concentration, serum concentration, osmotic pressure and conductivity; Among them, if the culture environment state of the culture device at the preset culture time node is abnormal, the cell state of the target tumor immune cells in the culture device is analyzed to obtain the cell state of the target tumor immune cells in the culture device, specifically: Based on the big data network, the characteristic images of abnormal tumor immune cells corresponding to various abnormal cell states of target tumor immune cells are retrieved during the culture process to obtain the characteristic images of various abnormal tumor immune cells; Constructing a knowledge graph and importing characteristic images of various abnormal tumor immune cells into the knowledge graph; If the culture environment state of the culture device at the preset culture time node is abnormal, a microscopic image of the target tumor immune cells in the culture device is obtained based on an optical microscope; Dividing the microscopic image into a number of grid units of fixed size based on a grid division method, and randomly selecting a preset number of grid units from all the grid units as sub-image regions; wherein each grid unit is used as a candidate region; Adjust the contrast, brightness and sharpness of each sub-image area to the preset values ​​to make the cell features more prominent; Based on the connected domain analysis algorithm, a single target tumor immune cell in each sub-image area is separated from the background, and characteristic images of the target tumor immune cells in several culture devices are extracted; The following steps are also included: Extracting characteristic images of various abnormal tumor immune cells from the knowledge graph, and obtaining characteristic images of each extracted target tumor immune cell; Calculate the cosine similarity between the characteristic images of each target tumor immune cell and the characteristic images of various abnormal tumor immune cells; If the cosine similarity between a characteristic image of a target tumor immune cell and a characteristic image of an abnormal tumor immune cell is greater than a preset similarity threshold, the target tumor immune cell is marked as an abnormal tumor immune cell; If the cosine similarity between the characteristic image of a target tumor immune cell and the characteristic images of various abnormal tumor immune cells is not greater than the preset similarity threshold, the target tumor immune cell is marked as a normal tumor immune cell; Counting the total number of abnormal tumor immune cells and the total number of normal tumor immune cells; performing ratio processing on the total number of abnormal tumor immune cells and the total number of normal tumor immune cells to obtain the proportion of abnormal tumor immune cells; Determine whether the abnormal tumor immune cell ratio is greater than a preset ratio; if so, mark the cell state of the target tumor immune cell currently cultured in the culture device as an abnormal state; if not, mark the cell state of the target tumor immune cell currently cultured in the culture device as a normal state; Among them, the culture device is regulated and processed according to the cell state of the target tumor immune cells in the culture device, specifically: Acquire work log information of the culture device, and extract various abnormal culture environment data corresponding to abnormal culture environment status of the culture device during historical work processes from the work log information; Collecting various abnormal culture environment data corresponding to abnormal culture environment states of the culture equipment during historical working processes, and obtaining feature data sets corresponding to various abnormal culture environment states of the culture equipment during historical working processes; At the same time, the historical adjustment schemes corresponding to various abnormal conditions of the culture environment state of the culture equipment during the historical working process are obtained from the work log information, and the culture environment accuracy level of the culture equipment after adjustment by various historical adjustment schemes is obtained; The historical adjustment scheme with the highest level of culture environment accuracy is used as the optimal adjustment scheme for the corresponding abnormal culture environment state, and the optimal adjustment scheme corresponding to various abnormal culture environment states of the culture equipment in the historical working process is obtained; The optimal adjustment scheme corresponding to various abnormal conditions of the culture environment state of the culture equipment in the historical working process is bundled with the corresponding feature data set to obtain several feature data packets; a knowledge base is constructed based on each feature data packet; The following steps are also included: If the culture environment state of the culture device at the preset culture time node is abnormal and the cell state of the target tumor immune cells currently cultured in the culture device is normal, then the actual culture environment data marked as abnormal culture environment data in the culture device is obtained to obtain an abnormal actual culture environment data set; and extracting a feature data set in each feature data packet from the knowledge base, calculating a Jaccard similarity coefficient between the abnormal actual cultivation environment data set and each feature data set, and obtaining a plurality of Jaccard similarity coefficients; Sorting the Jaccard similarity coefficients by size to obtain the maximum Jaccard similarity coefficient, defining the feature data set corresponding to the maximum Jaccard similarity coefficient as a matching feature data set, and locating the feature data packet to which the matching feature data set belongs in the knowledge base; The corresponding optimal adjustment scheme is extracted from the located characteristic data packet, and the culture equipment is regulated and processed according to the extracted optimal adjustment scheme.

2. The method for controlling the environment in the process of culturing tumor immune cells according to claim 1, It is characterized in that Compare various actual cultivation environment data of the cultivation equipment with the preset cultivation environment data to obtain the cultivation environment status of the cultivation equipment at the preset cultivation time node, specifically: Obtaining a preset culture scheme for target tumor immune cells, and determining, according to the preset culture scheme, the limit deviation thresholds of various culture environment data of the culture device at a preset culture time node; Calculate the difference between various actual culture environment data and corresponding preset culture environment data to obtain the deviation value of various actual culture environment data of the culture device at the preset culture time node; and compare the deviation value of various actual culture environment data with the corresponding extreme deviation threshold; If the deviation value of a certain type of actual culture environment data is greater than the corresponding extreme deviation threshold, the actual culture environment data of the culture device is calibrated as abnormal culture environment data; if the deviation value of a certain type of actual culture environment data is not greater than the corresponding extreme deviation threshold, the actual culture environment data of the culture device is calibrated as normal culture environment data; Analyze whether there is abnormal culture environment data in the culture device; if there is abnormal culture environment data in the culture device, mark the culture environment state of the culture device at a preset culture time node as an abnormal state; If there is no abnormal culture environment data in the culture equipment, the culture environment status of the culture equipment at the preset culture time node is calibrated as a normal state.

3. The method for controlling the environment in the process of culturing tumor immune cells according to claim 1, It is characterized in that The following steps are also included: If the culture environment status of the culture device at the preset culture time node is abnormal and the cell status of the target tumor immune cells currently cultured in the culture device is abnormal, the culture device is controlled to terminate the culture, and a culture termination information is generated, which is sent to the preset terminal for display.

4. An environmental control system in the process of culturing tumor immune cells. It is characterized in that The environmental control system in the tumor immune cell culture process includes a memory and a processor, and the memory stores a program of the environmental control method in the tumor immune cell culture process. When the program of the environmental control method in the tumor immune cell culture process is executed by the processor, the steps of the environmental control method in the tumor immune cell culture process as described in any one of claims 1 to 3 are implemented.

5. A computer-readable storage medium, Features: The computer-readable storage medium includes a program for an environmental regulation method during tumor immune cell culture. When the program for an environmental regulation method during tumor immune cell culture is executed by a processor, the steps of the environmental regulation method during tumor immune cell culture as described in any one of claims 1 to 3 are implemented.

Images