In-vitro lung culture environment monitoring system and method based on lung repair

Abstract

The invention belongs to the technical field of lung in-vitro repair monitoring, and particularly relates to an in-vitro lung culture environment monitoring system and method based on lung repair. According to the method, various physiological condition parameters, such as oxygen concentration, carbon dioxide concentration, temperature, humidity and nutrient solution content, of the lung sample under in-vitro culture are monitored and regulated in real time, accurate control over the lung sample repairing process is achieved, and the lung sample repairing accuracy is improved by summarizing the damage amount and the repairing amount of the lung sample. And reliable data support is provided for the repair progress of the lung sample. Meanwhile, according to the repairing condition of the lung sample, the perfusion amount of each physiological condition parameter is dynamically adjusted, the repairing efficiency and success rate of the lung sample are effectively improved, the perfusion amount of each physiological condition parameter is optimized and adjusted for the lung sample in a normal state and a risk state, and the repairing efficiency of the lung sample is improved. It is ensured that the lung sample is repaired in the optimal environment, so that the in-vitro repairing quality and repairing speed of the lung sample are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of in vitro lung repair monitoring, and specifically relates to an in vitro lung culture environment monitoring system and method based on lung repair. Background Art

[0002] With the continuous deepening of biomedical research, the research and treatment methods for lung diseases are also constantly being updated. Although traditional in vivo experimental methods can simulate the occurrence and development process of lung diseases to a certain extent, their application in lung disease research is limited due to problems such as complex experimental conditions and long experimental cycles. With the continuous development of in vitro culture technology, in vitro experimental methods have gradually become an important means of studying lung diseases. They not only have the advantages of controllable experimental conditions and short experimental cycles, but can also more accurately simulate the occurrence and development process of lung diseases, providing a more effective means for the research and treatment of lung diseases.

[0003] However, existing technologies for monitoring the in vitro lung culture environment still present several challenges. For example, how to accurately monitor the physiological state of lung samples during in vitro culture, how to adjust the perfusion volume of various physiological condition parameters based on the progress and status of lung sample repair, and how to optimize lung sample repair are still important challenges. To address these challenges, the present invention proposes a method for monitoring the in vitro lung culture environment based on lung repair, aiming to address these issues. Summary of the Invention

[0004] The purpose of the present invention is to provide an in vitro lung culture environment monitoring system and method based on lung repair, which can monitor the physiological state of lung samples during in vitro culture in real time, accurately collect and analyze the repair progress and status of lung samples, and automatically adjust the perfusion volume of various physiological condition parameters according to the analysis results to achieve repair optimization of lung samples.

[0005] The technical solutions adopted by the present invention are as follows: A method for monitoring an in vitro lung culture environment based on lung repair, comprising: Obtaining various physiological condition parameters of the lung sample during in vitro culture, wherein the physiological condition parameters include oxygen concentration, carbon dioxide concentration, temperature, humidity, and nutrient solution content; Collecting the amount of damage to the lung sample and the amount of repair of the lung sample under various physiological condition parameters, and summarizing them into a benchmark data set; Evaluating and analyzing the perfusion amounts of various physiological condition parameters based on the repair amount of the lung sample to determine the perfusion state of the lung sample, wherein the perfusion state includes a normal state and a risk state; Recording each of the physiological condition parameters under the normal state as sample condition parameters, and optimizing the perfusion volume of each physiological condition parameter according to the sample condition parameters; The perfusion volume corresponding to each physiological condition parameter under the risk state is adaptively adjusted until the perfusion state of the lung sample returns to a normal state.

[0006] In a preferred embodiment, when obtaining the various physiological condition parameters of the lung sample under in vitro culture, the oxygen concentration and carbon dioxide concentration in the environment in which the lung sample is located are monitored in real time by a gas sensor, the temperature in the environment in which the lung sample is located is monitored by a temperature sensor, the humidity in the environment in which the lung sample is located is monitored by a humidity sensor, and the nutrient solution content is monitored by image recognition technology.

[0007] In a preferred embodiment, after the various physiological condition parameters of the lung sample under in vitro culture are obtained, a preprocessing operation is simultaneously performed, and the preprocessing includes data cleaning, outlier removal and standardization.

[0008] In a preferred embodiment, the step of collecting the amount of damage to the lung sample and the amount of repair of the lung sample under various physiological condition parameters includes: Obtaining initial damage images of lung samples during the culture process and extracting the damaged area of ​​the lung samples; extracting an edge curve of the damaged area, calculating an area parameter of the damaged area based on the edge curve, and recording the area parameter as the damage amount of the lung sample; The repaired image of the lung sample after the cultivation of various physiological parameters is collected in real time, and the deviation area between the repaired image and the initial damage image is extracted synchronously, and the area of ​​the deviation area is recorded as the repair amount of the lung sample.

[0009] In a preferred embodiment, the step of evaluating and analyzing the perfusion amount of various physiological condition parameters based on the repair amount of the lung sample to determine the perfusion state of the lung sample includes: Obtaining the repair amount of the lung sample and recording it as a parameter to be evaluated; Obtaining an evaluation interval, and comparing the parameter to be evaluated with the evaluation interval; If the parameter to be evaluated belongs to the evaluation interval, it indicates that the repair progress of the lung sample is normal, and the perfusion state of the lung sample is recorded as normal; If the parameter to be evaluated does not belong to the evaluation interval, it indicates that the repair progress of the lung sample is abnormal, and the perfusion state of the lung sample is recorded as a risk state.

[0010] In a preferred embodiment, under the normal state, the repair progress of the lung sample is collected and recorded as a prediction condition parameter; Obtaining a prediction function, inputting the prediction condition parameters into the prediction function, and recording an output result of the prediction function as a prediction period; Based on the time length of the predicted period, a forward offset process is performed on the current repair node of the lung sample to obtain a repair completion node of the lung sample.

[0011] In a preferred embodiment, the step of optimizing the perfusion volume of each physiological condition parameter according to the sample condition parameter includes: Obtaining all the sample condition parameters, adding sample serial numbers one by one, and then sorting the sample parameters with the sample serial numbers added to obtain the optimization priority of each of the sample condition parameters; Extracting corresponding sample condition parameters one by one according to the optimization priority and recording them as parameters to be optimized, and then recording the unextracted sample condition parameters as base parameters; Establishing a sampling period, and keeping the basal parameters unchanged during the sampling period, performing supplemental perfusion or subtractive perfusion treatment on the parameters to be optimized, and simultaneously collecting the repair volume of the lung sample during the sampling period and recording it as the condition parameter to be evaluated; The optimization effect of the parameter to be optimized is evaluated according to the condition parameter to be evaluated, and the process stops when the parameter to be optimized reaches the optimal perfusion volume.

[0012] In a preferred embodiment, in the risk state, the repair deviation of the lung sample is collected; Assessing the risk level of the lung sample according to the repair deviation and determining the repair priority of the lung sample, wherein the higher the risk level of the lung sample, the higher the corresponding repair priority; The perfusion volume corresponding to each physiological condition parameter under the risk state is adjusted according to the repair priority of the lung sample until the perfusion state of the lung sample returns to a normal state.

[0013] The present invention also provides an in vitro lung culture environment monitoring system based on lung repair, using the above-mentioned in vitro lung culture environment monitoring method based on lung repair, comprising: A parameter acquisition module, which is used to obtain various physiological condition parameters of the lung sample during in vitro culture, wherein the physiological condition parameters include oxygen concentration, carbon dioxide concentration, temperature, humidity, and nutrient solution content; A data statistics module, which is used to collect the amount of damage to the lung sample and the amount of repair of the lung sample under various physiological condition parameters, and summarize them into a benchmark data set; A status assessment module, configured to assess and analyze the perfusion amount of various physiological condition parameters based on the repair amount of the lung sample, and determine the perfusion state of the lung sample, wherein the perfusion state includes a normal state and a risk state; a first optimization module, configured to record the physiological condition parameters under the normal state as sample condition parameters, and optimize the perfusion volume of the physiological condition parameters according to the sample condition parameters; The second optimization module is used to adaptively adjust the perfusion volume corresponding to each physiological condition parameter under the risk state until the perfusion state of the lung sample returns to a normal state.

[0014] And, an electronic device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned in vitro lung culture environment monitoring method based on lung repair.

[0015] The technical effects achieved by the present invention are: The present invention achieves precise control over the lung sample repair process by real-time monitoring and regulation of various physiological parameters during in vitro culture, such as oxygen concentration, carbon dioxide concentration, temperature, humidity, and nutrient solution content. By summarizing the amount of damage and repair in lung samples, reliable data support is provided for the progress of lung sample repair. Simultaneously, the perfusion volume of various physiological parameters is dynamically adjusted based on the lung sample's repair status, effectively improving the efficiency and success rate of lung sample repair. The perfusion volume of various physiological parameters is optimized and adjusted for lung samples in both normal and risky states, ensuring that lung samples are repaired under optimal conditions, thereby enhancing the quality and speed of in vitro lung sample repair. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic flow chart of the method of the present invention; Figure 2 It is a schematic diagram of the system modules of the present invention; Figure 3 It is a schematic structural diagram of an electronic device of the present invention. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0018] 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. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive of other embodiments.

[0020] See also Figure 1 As shown, the present invention provides an in vitro lung culture environment monitoring method based on lung repair, comprising: S1. Obtain various physiological condition parameters of the lung sample during in vitro culture, wherein the physiological condition parameters include oxygen concentration, carbon dioxide concentration, temperature, humidity, and nutrient solution content; In step S1, when performing in vitro lung culture, it is first necessary to obtain various physiological condition parameters of the lung sample in the in vitro culture environment. The physiological condition parameters cover multiple key indicators such as oxygen concentration, carbon dioxide concentration, temperature, humidity, and nutrient solution content. Based on this, the in vitro culture environment of the lung sample is comprehensively monitored, thereby achieving precise control of the repair progress of the lung sample. Specifically, when obtaining various physiological condition parameters of the lung sample under in vitro culture, the oxygen concentration and carbon dioxide concentration in the environment in which the lung sample is located are monitored in real time by a gas sensor, the temperature in the environment in which the lung sample is located is monitored by a temperature sensor, the humidity in the environment in which the lung sample is located is monitored by a humidity sensor, and the nutrient solution content is monitored by image recognition technology; Specifically, in the process of obtaining the key physiological condition parameters of the lung samples in vitro culture, high-precision sensors and technical means are needed for real-time monitoring. Specifically, through gas sensors, the oxygen concentration and carbon dioxide concentration in the culture environment of the lung samples can be monitored in real time to ensure that the gas environment meets physiological needs. At the same time, the temperature sensor is used to continuously monitor the temperature of the environment in which the lung samples are located to maintain a constant and appropriate temperature condition. In addition, humidity sensors are also used to monitor the humidity level in the environment in which the lung samples are located to ensure that the humidity is within an appropriate range and to avoid adverse effects on the samples due to improper humidity. In order to further ensure the optimization of the culture environment, advanced image recognition technology is also used to dynamically monitor the content of the nutrient solution so as to adjust the supply of the nutrient solution in time to ensure Lung samples can obtain sufficient nutritional support during the in vitro culture process, so as to fully grasp the various physiological condition parameters of the lung samples in the in vitro culture environment and provide strong guarantees for the smooth progress of the experiment. In addition, after the various physiological condition parameters of the lung samples under in vitro culture are obtained, preprocessing operations are performed simultaneously. Preprocessing includes data cleaning, outlier removal and standardization. The purpose of data cleaning is to remove invalid, incomplete or erroneous data to improve data quality. Outlier removal is to eliminate extreme values ​​that are obviously deviated from the normal range to avoid interference with subsequent analysis. Standardization is to convert the data into a unified scale to facilitate comparison and analysis between different parameters. By preprocessing the various physiological condition parameters of the lung samples under in vitro culture, the accuracy and reliability of the data can be further ensured.

[0021] S2. Collect the damage amount of lung samples and the repair amount of lung samples under various physiological conditions and parameters, and summarize them into a benchmark dataset; In step S2, during the in vitro repair of the lung sample, it is necessary to determine the extent of damage to the lung sample and the extent of repair of the lung sample under various physiological parameters, and to perform comprehensive data aggregation to form a comprehensive benchmark data set. The steps of collecting the extent of damage to the lung sample and the extent of repair of the lung sample under various physiological parameters include: Obtaining initial damage images of lung samples during the culture process and extracting the damaged area of ​​the lung samples; Extract the edge curve of the damaged area, calculate the area parameter of the damaged area based on the edge curve, and record it as the damage amount of the lung sample; Real-time acquisition of repaired images of lung samples after cultivation of various physiological parameters, simultaneous extraction of the deviation area between the repaired image and the initial damaged image, and recording the area of ​​the deviation area as the repair amount of the lung sample; Specifically, when collecting the amount of damage to the lung sample and the amount of repair of the lung sample under various physiological condition parameters, first, obtain the initial damage image of the lung sample during the culture process, then carefully analyze the obtained image to extract the obvious damage area in the lung sample, then use image processing technology to further process the damage area, extract the edge curve of the damage area, and accurately calculate the area parameter of the damage area based on the extracted edge curve, and record this area parameter as the damage amount of the lung sample. Subsequently, after the lung sample has been cultured and processed with various physiological parameters, the repaired image of the lung sample is collected in real time, and the deviation area between the repaired image and the initial damage image is simultaneously extracted. Through comparative analysis, the area of ​​the deviation area is calculated and recorded as the repair amount of the lung sample, thereby fully understanding the damage and repair of the lung sample under different physiological conditions. Among them, the area calculation formulas of the damage area and the deviation area can be calculated using the following formula, and the calculation formulas involved are specifically as follows: ; Where, Indicates the area of ​​the damaged area or deviation area, Indicates the number of inflection points of the edge curve corresponding to the damaged area or deviation area, The horizontal coordinate of the inflection point, and Both represent the vertical coordinate of the inflection point. The degree of damage of the lung sample can be determined based on the area of ​​the damaged area, while the repair effect of the lung sample can be evaluated based on the area of ​​the deviation area.

[0022] S3. Evaluate and analyze the perfusion volume of various physiological condition parameters based on the repair volume of the lung sample to determine the perfusion status of the lung sample, which includes a normal state and a risk state; In step S3, after the repair volume of the lung sample is determined, the perfusion volume of various physiological condition parameters is evaluated and analyzed based on the repair effect of the lung sample to determine the perfusion state of the lung sample. In this embodiment, the perfusion state is mainly divided into two categories: normal state and risk state. The steps of evaluating and analyzing the perfusion volume of various physiological condition parameters based on the repair volume of the lung sample to determine the perfusion state of the lung sample include: The repair volume of the lung sample was obtained and recorded as the parameter to be evaluated; Obtain an evaluation interval and compare the parameter to be evaluated with the evaluation interval; If the parameter to be evaluated falls within the evaluation interval, it indicates that the repair progress of the lung sample is normal, and the perfusion state of the lung sample is recorded as normal; If the parameter to be evaluated does not fall within the evaluation interval, it indicates that the repair progress of the lung sample is abnormal, and the perfusion status of the lung sample is recorded as a risk status; Specifically, when conducting a comprehensive and detailed evaluation and analysis of the perfusion volume of various physiological condition parameters based on the repair volume of the lung sample, first, obtain the repair volume data of the lung sample and record it in detail as the key parameter to be evaluated. Secondly, clarify and set the evaluation interval range, and compare and analyze the key parameters to be evaluated with the set evaluation interval one by one. If the key parameters to be evaluated fall within the evaluation interval, it can be determined that the repair progress of the lung sample is within the normal range. At this time, the perfusion status of the lung sample needs to be clearly recorded as normal. Conversely, if the key parameters to be evaluated do not fall within the evaluation interval, it indicates that there is an abnormality in the repair progress of the lung sample. At this time, the perfusion status of the lung sample needs to be promptly recorded as a risk status so that further corresponding treatment measures can be taken.

[0023] S4. Recording various physiological condition parameters under normal conditions as sample condition parameters, and optimizing the perfusion volume of various physiological condition parameters according to the sample condition parameters; The various physiological condition parameters under normal conditions are recorded in detail as sample condition parameters. Based on these sample condition parameters, the perfusion volume of each physiological condition parameter is optimized to ensure that the lung sample is repaired in the optimal culture environment. In particular, under normal conditions, the repair progress of the lung sample is collected and recorded as the predicted condition parameter; Obtain a prediction function, input prediction condition parameters into the prediction function, and record the output result of the prediction function as a prediction period; Based on the length of the prediction period, a forward offset process is performed on the current repair node of the lung sample to obtain the repair completion node of the lung sample; Specifically, under normal working conditions, the repair progress of the collected lung samples will first be tracked and recorded as prediction condition parameters. Then, a pre-set prediction function model will be obtained, and the prediction condition parameters will be input into the prediction function one by one. After the prediction function is operated and processed, the prediction time period required for the completion of the lung sample repair can be obtained. Finally, based on the length of the obtained prediction time period, the current repair node of the lung sample is positively offset, so that the repair completion node of the lung sample can be determined, providing an accurate reference basis for subsequent work. The expression of the prediction function is: ; Where, represents the forecast period, Indicates the progress of demand repair, Indicates the current repair progress. Indicates the duration of lung sample repair under normal conditions, represents the number of prediction conditional parameters, and Indicates the prediction condition parameters under the adjacent progress collection nodes; In addition, under normal conditions, the perfusion volume of various physiological condition parameters will be optimized according to the sample condition parameters, including: Obtain all sample condition parameters, add sample numbers one by one, and then sort the sample parameters with added sample numbers to obtain the optimization priority of each sample condition parameter; Extract the corresponding sample condition parameters one by one according to the optimization priority and record them as the parameters to be optimized, and then record the unextracted sample condition parameters as the base parameters; Establish a sampling period, keep the basal parameters unchanged during the sampling period, perform supplemental or subtractive perfusion on the parameters to be optimized, and simultaneously collect the repair volume of the lung sample during the sampling period and record it as the condition parameter to be evaluated; Evaluate the optimization effect of the parameters to be optimized based on the condition parameters to be evaluated until the parameters to be optimized reach the optimal perfusion volume; In the above, when optimizing the perfusion volume of each physiological condition parameter according to the sample condition parameter, first, all the sample condition parameters are fully acquired, and a unique sample serial number is added to each sample condition parameter one by one for subsequent identification and management. Then, the sample parameters to which the sample serial number has been added are sorted, so that the optimization priority of each sample condition parameter can be clearly obtained to ensure the orderly progress of the optimization process. Then, according to the determined optimization priority, the corresponding sample condition parameters are extracted one by one and recorded as parameters to be optimized. At the same time, the sample condition parameters that have not yet been extracted are recorded as base parameters so as to be maintained in the subsequent optimization process. Its stability is measured, and then a sampling period is constructed. During this sampling period, the basal parameters are ensured to remain unchanged, thereby providing a stable reference benchmark for the optimization process. On this basis, the parameters to be optimized are supplemented or reduced to determine the optimal perfusion volume. During the processing, the repair volume of the lung samples within the sampling period is synchronously collected and recorded as the condition parameters to be evaluated. Finally, based on the condition parameters to be evaluated, a comprehensive evaluation is performed on the optimization effect of the parameters to be optimized. Through continuous adjustment and evaluation, until the parameters to be optimized reach the optimal perfusion volume, the optimization process can be stopped at this time to ensure that the perfusion volume of various physiological condition parameters reaches the best state.

[0024] S5. Adaptively adjust the perfusion volume corresponding to various physiological condition parameters under the risk state until the perfusion state of the lung sample returns to a normal state.

[0025] In step S5, the perfusion volume corresponding to each physiological condition parameter in the risk state is adaptively adjusted, and continuous monitoring and adjustment are performed until the perfusion state of the lung sample returns to normal, thereby ensuring the stability and effectiveness of the in vitro lung culture environment. In the risk state, the repair deviation of the lung sample is collected; The risk level of the lung sample is assessed based on the repair deviation, and the repair priority of the lung sample is determined. The higher the risk level of the lung sample, the higher the corresponding repair priority. Adjust the perfusion volume corresponding to various physiological condition parameters under risk conditions according to the repair priority of the lung sample until the perfusion state of the lung sample returns to normal; Specifically, when collecting a lung sample, the first step is to determine the repair deviation of the lung sample. The repair deviation refers to the degree of deviation between the current repair progress of the lung sample and the expected repair progress. This can intuitively reflect whether there are any abnormalities in the lung sample's repair process. Subsequently, the risk level of the lung sample is assessed based on the obtained repair deviation. When assessing the risk level, multiple factors such as the size and duration of the repair deviation and the overall condition of the lung sample are comprehensively considered, thereby more accurately determining the risk level of the lung sample. The higher the risk level, the more difficult the lung sample is to repair and the more priority it needs to be treated. After determining the risk level of the lung sample, the perfusion volume corresponding to various physiological condition parameters under the risk state can be adjusted according to its repair priority. During the adjustment process, the system will continuously monitor the repair status of the lung sample and the dynamic changes of various physiological condition parameters. The perfusion volume is adjusted in real time through a feedback mechanism to ensure that each adjustment can accurately respond to the actual needs of the lung sample. Once the perfusion status of the lung sample returns to normal, the adjustment will automatically stop and maintain the current optimal perfusion configuration to ensure the stability and efficiency of the in vitro lung culture environment.

[0026] See also Figure 2 A system for monitoring an in vitro lung culture environment based on lung repair, using the above-mentioned method for monitoring an in vitro lung culture environment based on lung repair, comprises: A parameter acquisition module is used to obtain various physiological condition parameters of lung samples under in vitro culture, wherein the physiological condition parameters include oxygen concentration, carbon dioxide concentration, temperature, humidity, and nutrient solution content; The data statistics module is used to collect the amount of damage to lung samples and the amount of repair of lung samples under various physiological conditions and parameters, and summarize them into a benchmark data set; A status assessment module is used to evaluate and analyze the perfusion volume of various physiological condition parameters based on the repair volume of the lung sample, and determine the perfusion state of the lung sample, which includes a normal state and a risk state; a first optimization module, the first optimization module being used to record various physiological condition parameters under normal conditions as sample condition parameters, and to optimize the perfusion volume of various physiological condition parameters according to the sample condition parameters; The second optimization module is used to adaptively adjust the perfusion volume corresponding to various physiological condition parameters under the risk state until the perfusion state of the lung sample returns to a normal state.

[0027] In the above, the parameter acquisition module is responsible for collecting various physiological condition parameters of the lung sample under the in vitro culture environment. Physiological condition parameters cover multiple aspects such as oxygen concentration, carbon dioxide concentration, temperature, humidity, and nutrient solution content. The data statistics module not only records the amount of damage to the lung sample, but also records in detail the amount of repair of the lung sample under various physiological condition parameters. Both are aggregated into a benchmark dataset to provide data support for subsequent analysis and optimization. The state assessment module, based on the benchmark dataset, conducts an in-depth assessment of the perfusion volume of various physiological condition parameters to determine the current perfusion state of the lung sample. When the lung sample is in a normal state, the first optimization module will intervene and record the current physiological condition parameters as sample condition parameters. Based on the sample condition parameters, the perfusion volume is further optimized to ensure repair efficiency and stability. If the lung sample enters a risk state, the second optimization module will adaptively adjust the perfusion volume of various physiological condition parameters based on the lung sample's risk level and repair priority. Through continuous monitoring and adjustment, it ensures that the lung sample can return to normal as soon as possible and ensures the stability of the in vitro lung culture environment.

[0028] See also Figure 3 , an electronic device, the electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the above-mentioned in vitro lung culture environment monitoring method based on lung repair.

[0029] The processor of the above-mentioned electronic device can be a central processing unit (CPU), a graphics processing unit (GPU) or a digital signal processor (DSP), etc. The processor realizes the various functions of the above-mentioned in vitro lung culture environment monitoring method based on lung repair by reading and executing the computer program stored in the memory. The memory can be a high-speed RAM memory or a stable non-volatile memory, such as a disk memory. Through the cooperation of the memory, the electronic device can efficiently process and analyze a large amount of physiological condition parameter data. In addition, the electronic device may also include other components, such as an arithmetic unit, an input device, an output device, a network interface, etc. The arithmetic unit can be an arithmetic logic unit (ALU), which is responsible for performing various arithmetic and logical operations; the input device can be a keyboard, a mouse or a touch screen, etc., for receiving user operation instructions; the output device can be a display screen or a printer, etc., for displaying processing results or printing reports; the network interface is used to realize network communication between the electronic device and other devices to facilitate data transmission and sharing.

[0030] The foregoing is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art may make various improvements and modifications without departing from the principles of the present invention, and such improvements and modifications are also within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained herein shall, unless otherwise specified or limited, be implemented in accordance with conventional means in the art.

Claims

1. A method for monitoring an in vitro lung culture environment based on lung repair, characterized by: include: Obtaining various physiological condition parameters of the lung sample during in vitro culture, wherein the physiological condition parameters include oxygen concentration, carbon dioxide concentration, temperature, humidity, and nutrient solution content; Collecting the amount of damage to the lung sample and the amount of repair of the lung sample under various physiological condition parameters, and summarizing them into a benchmark data set; Evaluating and analyzing the perfusion amounts of various physiological condition parameters based on the repair amount of the lung sample to determine the perfusion state of the lung sample, wherein the perfusion state includes a normal state and a risk state; Recording each of the physiological condition parameters under the normal state as sample condition parameters, and optimizing the perfusion volume of each physiological condition parameter according to the sample condition parameters; The perfusion volume corresponding to each physiological condition parameter under the risk state is adaptively adjusted until the perfusion state of the lung sample returns to a normal state.

2. The method for monitoring an in vitro lung culture environment based on lung repair according to claim 1, characterized in that: When obtaining the various physiological condition parameters of the lung sample under in vitro culture, the oxygen concentration and carbon dioxide concentration in the environment in which the lung sample is located are monitored in real time through a gas sensor, the temperature in the environment in which the lung sample is located is monitored through a temperature sensor, the humidity in the environment in which the lung sample is located is monitored through a humidity sensor, and the nutrient solution content is monitored through image recognition technology.

3. The method for monitoring an in vitro lung culture environment based on lung repair according to claim 1, characterized in that: After the various physiological condition parameters of the lung samples under in vitro culture are obtained, preprocessing operations are performed simultaneously, and the preprocessing includes data cleaning, outlier removal and standardization.

4. The method for monitoring an in vitro lung culture environment based on lung repair according to claim 1, characterized in that: The step of collecting the damage amount of the lung sample and the repair amount of the lung sample under various physiological condition parameters includes: Obtaining initial damage images of lung samples during the culture process and extracting the damaged area of ​​the lung samples; extracting an edge curve of the damaged area, calculating an area parameter of the damaged area based on the edge curve, and recording the area parameter as the damage amount of the lung sample; The repaired image of the lung sample after the cultivation of various physiological parameters is collected in real time, and the deviation area between the repaired image and the initial damage image is extracted synchronously, and the area of ​​the deviation area is recorded as the repair amount of the lung sample.

5. The method for monitoring an in vitro lung culture environment based on lung repair according to claim 1, characterized in that: The step of evaluating and analyzing the perfusion amount of various physiological condition parameters based on the repair amount of the lung sample to determine the perfusion state of the lung sample includes: Obtaining the repair amount of the lung sample and recording it as a parameter to be evaluated; Obtaining an evaluation interval, and comparing the parameter to be evaluated with the evaluation interval; If the parameter to be evaluated belongs to the evaluation interval, it indicates that the repair progress of the lung sample is normal, and the perfusion state of the lung sample is recorded as normal; If the parameter to be evaluated does not belong to the evaluation interval, it indicates that the repair progress of the lung sample is abnormal, and the perfusion state of the lung sample is recorded as a risk state.

6. The method for monitoring an in vitro lung culture environment based on lung repair according to claim 1, characterized in that: Under the normal state, the repair progress of the lung sample is collected and recorded as a prediction condition parameter; Obtaining a prediction function, inputting the prediction condition parameters into the prediction function, and recording an output result of the prediction function as a prediction period; Based on the time length of the predicted period, a forward offset process is performed on the current repair node of the lung sample to obtain a repair completion node of the lung sample.

7. The method for monitoring an in vitro lung culture environment based on lung repair according to claim 1, characterized in that: The step of optimizing the perfusion volume of various physiological condition parameters according to the sample condition parameters includes: Obtaining all the sample condition parameters, adding sample serial numbers one by one, and then sorting the sample parameters with the sample serial numbers added to obtain the optimization priority of each of the sample condition parameters; Extracting corresponding sample condition parameters one by one according to the optimization priority and recording them as parameters to be optimized, and then recording the unextracted sample condition parameters as base parameters; Establishing a sampling period, and keeping the basal parameters unchanged during the sampling period, performing supplemental perfusion or subtractive perfusion treatment on the parameters to be optimized, and simultaneously collecting the repair volume of the lung sample during the sampling period and recording it as the condition parameter to be evaluated; The optimization effect of the parameter to be optimized is evaluated according to the condition parameter to be evaluated, and the process stops when the parameter to be optimized reaches the optimal perfusion volume.

8. The method for monitoring an in vitro lung culture environment based on lung repair according to claim 1, characterized in that: Under the risk state, collecting the repair deviation of the lung sample; Assessing the risk level of the lung sample according to the repair deviation and determining the repair priority of the lung sample, wherein the higher the risk level of the lung sample, the higher the corresponding repair priority; The perfusion volume corresponding to each physiological condition parameter under the risk state is adjusted according to the repair priority of the lung sample until the perfusion state of the lung sample returns to a normal state.

9. An in vitro lung culture environment monitoring system based on lung repair, characterized by: The method for monitoring an in vitro lung culture environment based on lung repair according to any one of claims 1 to 8 comprises: A parameter acquisition module, which is used to obtain various physiological condition parameters of the lung sample during in vitro culture, wherein the physiological condition parameters include oxygen concentration, carbon dioxide concentration, temperature, humidity, and nutrient solution content; a data statistics module, which is used to collect the amount of damage to the lung sample and the amount of repair of the lung sample under various physiological condition parameters, and summarize them into a benchmark data set; A status assessment module, configured to assess and analyze the perfusion amount of various physiological condition parameters based on the repair amount of the lung sample, and determine the perfusion state of the lung sample, wherein the perfusion state includes a normal state and a risk state; a first optimization module, configured to record the physiological condition parameters under the normal state as sample condition parameters, and optimize the perfusion volume of the physiological condition parameters according to the sample condition parameters; The second optimization module is used to adaptively adjust the perfusion volume corresponding to each physiological condition parameter under the risk state until the perfusion state of the lung sample returns to a normal state.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the in vitro lung culture environment monitoring method based on lung repair according to any one of claims 1 to 8.

Images