A biological reagent protein determination integrated analysis system

Abstract

This invention relates to the field of biochemical analysis technology and discloses an integrated analysis system for protein assay using biological reagents. This system transforms passive data compensation into active reaction process control. By sensing the reagent status in real time and dynamically adjusting reaction parameters, combined with closed-loop feedback and self-learning mechanisms, it achieves intelligent protein assay with high precision and high stability. This solves the problems of inaccurate and imprecise detection and reagent waste caused by the activity drift of biological reagents during storage and use, which are due to the use of fixed and standardized reaction conditions in existing technologies.

Description

Technical Field

[0001] This invention relates to the field of biochemical analysis technology, and in particular to an integrated analytical system for the determination of proteins using biological reagents. Background Technology

[0002] Existing protein concentration assays, especially integrated analyses based on biological reagents, generally employ a model of fixed reaction conditions and periodic calibration. In this model, the analytical system uses a standardized set of reaction parameters, such as fixed reaction temperature and reaction time, for all batches and states of biological reagents.

[0003] However, the activity of biological reagents inevitably decays or drifts with changes in environmental factors such as storage time, temperature fluctuations, and light exposure. Current technologies primarily rely on establishing calibration curves to perform post-hoc compensation at the data level to correct measurement errors caused by changes in the activity of biological reagents. However, this approach cannot eliminate errors at the source of the reaction, affecting the accuracy and precision of the detection results. Summary of the Invention

[0004] This invention provides an integrated analysis system for the determination of proteins using biological reagents.

[0005] In a first aspect, the present invention provides an integrated analysis system for protein assay using biological reagents. The system includes: a reagent status sensing module, used to acquire real-time status parameters of multiple biological reagents and determine the performance indicators of the corresponding multiple biological reagents based on the multiple real-time status parameters; a reaction condition dynamic control module, used to determine the initial reaction parameters of the corresponding multiple biological reagents according to the multiple performance indicators; a reaction execution and monitoring module, used to control the corresponding reaction equipment to perform protein assay reactions on the multiple biological reagents according to the multiple initial reaction parameters, and to acquire real-time reaction data corresponding to the multiple biological reagents during the protein assay reaction; and a closed-loop feedback control module, used to determine multiple preset target data corresponding to the multiple real-time reaction data, and to adjust the initial reaction parameters corresponding to the multiple real-time reaction data to obtain adjusted reaction parameters according to the multiple real-time reaction data and the target data corresponding to the multiple real-time reaction data, and to send the multiple adjusted reaction parameters to the reaction execution and monitoring module so that the reaction execution and monitoring module controls the corresponding reaction equipment to perform protein assay reactions on the multiple biological reagents according to the multiple adjusted reaction parameters.

[0006] In this embodiment of the invention, the analysis system dynamically adjusts reaction parameters by sensing the reagent status in real time, and combines closed-loop feedback and self-learning mechanisms to achieve high-precision and high-stability intelligent protein determination. This solves the problem in existing technologies that cannot effectively address the inaccurate and imprecise detection and reagent waste caused by the activity drift of biological reagents during storage and use due to the use of fixed and standardized reaction conditions.

[0007] In one possible implementation of the first aspect above, the reaction condition dynamic control module inputs multiple performance indicators into a preset target parameter model and obtains multiple initial reaction parameters corresponding to the multiple performance indicators output by the target parameter model. The target parameter model stores the performance indicators of multiple biological reagents and multiple biological reagents.

[0008] In one possible implementation of the first aspect mentioned above, the closed-loop feedback control module updates the target parameter model based on multiple real-time reaction data, multiple target data corresponding to the multiple real-time reaction data, multiple initial reaction parameters corresponding to the multiple real-time reaction data, and multiple adjustment reaction parameters corresponding to the multiple real-time reaction data.

[0009] In one possible implementation of the first aspect above, the closed-loop feedback control module determines that the difference between the real-time reaction data and the corresponding target data is greater than a threshold, and adjusts the initial reaction parameters corresponding to the real-time reaction data; the closed-loop feedback control module determines that the difference between the real-time reaction data and the corresponding target data is less than or equal to a threshold, and does not adjust the initial reaction parameters corresponding to the real-time reaction data.

[0010] In one possible implementation of the first aspect described above, the system further includes a reagent protection module for adjusting the storage conditions of multiple biological reagents after the protein assay reaction according to different performance indicators.

[0011] In one possible implementation of the first aspect above, the real-time state parameters include one or more of temperature, light intensity, and impedance; the initial reaction parameters include one or more of reaction temperature, reaction time, and sample loading amount.

[0012] Secondly, the present invention provides an integrated analysis method for protein assay using biological reagents. The method includes: acquiring real-time state parameters of multiple biological reagents and determining performance indicators of the corresponding multiple biological reagents based on the multiple real-time state parameters; determining initial reaction parameters of the corresponding multiple biological reagents based on the multiple performance indicators; controlling corresponding reaction devices to perform protein assay reactions on the multiple biological reagents based on the multiple initial reaction parameters; acquiring real-time reaction data corresponding to the multiple biological reagents during the protein assay reaction; determining multiple preset target data corresponding to the multiple real-time reaction data; adjusting the initial reaction parameters corresponding to the multiple real-time reaction data to obtain adjusted reaction parameters based on the multiple real-time reaction data and the target data corresponding to the multiple real-time reaction data; adjusting the multiple initial reaction parameters to the corresponding adjusted reaction parameters; and controlling corresponding reaction devices to perform protein assay reactions on the multiple biological reagents based on the multiple adjusted reaction parameters.

[0013] In one possible implementation of the second aspect above, the method further includes: adjusting the storage conditions of the corresponding biological reagents after the protein assay reaction according to different performance indicators.

[0014] Thirdly, embodiments of the present invention provide a computer-readable storage medium storing instructions that, when executed on an electronic device, cause the electronic device to perform the functions of any of the biological reagent protein assay integrated analysis systems provided by the first aspect and various possible implementations of the first aspect, as well as to perform any of the methods provided by the second aspect and various possible implementations of the second aspect.

[0015] Fourthly, embodiments of the present invention provide an electronic device comprising: a memory for storing instructions executed by one or more processors of the electronic device; and a processor, one of the processors of the electronic device, for executing the instructions stored in the memory to implement the functions of any of the integrated analysis systems for biological reagent protein assays provided by the first aspect and various possible implementations of the first aspect, and to implement any of the methods provided by the second aspect and various possible implementations of the second aspect.

[0016] Fifthly, embodiments of the present invention provide a program product including instructions that, when executed by an electronic device, enable the electronic device to perform the functions of any of the biological reagent protein assay integrated analysis systems provided by the first aspect and various possible implementations of the first aspect, as well as to perform any of the methods provided by the second aspect and various possible implementations of the second aspect. Attached Figure Description

[0017] Figure 1According to some embodiments of the present invention, a schematic diagram of a module example of an integrated analytical system for protein assay using biological reagents is shown; Figure 2 According to some embodiments of the present invention, a flowchart of an integrated analytical method for the determination of proteins using biological reagents is shown; Figure 3 According to some embodiments of the present invention, an example schematic diagram of an electronic device is shown. Detailed Implementation

[0018] The illustrative embodiments of the present invention include, but are not limited to, an integrated analytical system for the determination of proteins using biological reagents.

[0019] The following description is intended to disclose the present invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art. The basic principles of the invention defined in the following description can be applied to other embodiments, modifications, improvements, equivalents, and other technical solutions that do not depart from the spirit and scope of the invention.

[0020] As mentioned earlier, the activity of biological reagents inevitably decays or drifts with changes in environmental factors such as storage time, temperature fluctuations, and light exposure. Current technologies primarily rely on establishing calibration curves to perform post-hoc compensation at the data level to correct systematic errors caused by changes in reagent activity. However, this approach cannot eliminate errors at the source of the reaction, limiting the accuracy and precision of the detection results. Furthermore, to ensure the reliability of the detection results, reagents whose activity has decayed to a certain level must be discarded, resulting in a short effective lifespan for the reagents and high detection costs.

[0021] This application provides an integrated analysis system for protein assay using biological reagents. It transforms passive data compensation into active reaction process control. By sensing the reagent status in real time and dynamically adjusting reaction parameters, combined with closed-loop feedback and self-learning mechanisms, it achieves intelligent protein assay with high precision and high stability. This solves the problems of inaccurate and imprecise detection and reagent waste caused by the activity drift of biological reagents during storage and use, which are due to the use of fixed and standardized reaction conditions in the prior art.

[0022] The following is in conjunction with the appendix Figures 1 to 3 The technical solution of the present invention will be introduced. Figure 1 According to some embodiments of the present invention, a schematic diagram illustrating a module example of an integrated analytical system 10 for the determination of proteins using biological reagents is shown. Figure 1As shown, the analysis system 10 includes: a reagent status sensing module 11, a reaction condition dynamic control module 12, a reaction execution and monitoring module 13, and a closed-loop feedback control module 14.

[0023] For example, the reagent state sensing module 11 is used to acquire the real-time state parameters of multiple biological reagents in real time, and determine the performance indicators of the corresponding multiple biological reagents based on the multiple real-time state parameters; then, the reagent state sensing module 11 sends the determined multiple performance indicators to the reaction condition dynamic control module 12.

[0024] In some embodiments, real-time state parameters include one or more of temperature, light intensity, and impedance. It is understood that real-time state parameters are environmental factors that affect the activity of biological reagents, and monitoring them can provide direct and effective input for calculating performance indicators.

[0025] In some embodiments, a performance index refers to one or a set of numerical values ​​used to quantify the current performance of a biological reagent. For example, a performance index may be an activity factor, which integrates changes in temperature, light history, and its own physicochemical properties (such as impedance) experienced by the biological reagent, reflecting the reagent's effective activity level in numerical form (e.g., between 0 and 1).

[0026] In some embodiments, the activity factor can be calculated using a preset mathematical model or weighted formula. The activity factor is an indicator that specifically characterizes the current catalytic or reactive ability of a biological reagent. For example, the activity factor can be calculated using the formula: Activity Factor The calculation yields the result. Where T is the real-time temperature, T_ref is the preset reference temperature (e.g., 5℃), I is the light intensity, and Z is the current impedance. is the initial impedance, N is the number of times the lid is opened, and k1 to k4 are the reagent-specific decay coefficients determined by accelerated aging experiments; the smaller the value of the activity factor (A), the more severe the activity decay.

[0027] It is understandable that the reagent status sensing module 11 improves the personalized design and accuracy of the analysis results of the analysis system 10 by collecting and judging multiple different biological reagents in real time.

[0028] For example, the reaction condition dynamic control module 12 is used to receive multiple performance indicators sent by the reagent status sensing module 11, and determine the initial reaction parameters of the corresponding multiple biological reagents according to the multiple performance indicators; then, the reaction condition dynamic control module 12 sends the multiple initial reaction parameters to the reaction execution and monitoring module 13.

[0029] It is understandable that different biological reagents with different activities require different reaction conditions (such as temperature and time) to reach the same ideal reaction endpoint. For example, a reagent with lower activity may require a higher reaction temperature or a longer reaction time to compensate. Thus, the dynamic reaction condition control module 12 determines the initial reaction parameters of different biological reagents according to their different performance indicators, ensuring that each biological reagent reaches the ideal reaction endpoint during the reaction process, thereby improving the accuracy of protein assay.

[0030] It is understood that this application does not use a fixed reaction parameter to perform protein assays on multiple biological reagents, thus avoiding errors in the protein assay results caused by the fixed parameter affecting the activity of the biological reagents. This achieves the elimination or reduction of systematic errors introduced by the difference in reagent activity from the source of the reaction.

[0031] In some embodiments, the initial reaction parameters include one or more of the following: reaction temperature, reaction time, and sample volume.

[0032] In some embodiments, multiple performance indicators are input into a preset target parameter model, and multiple initial reaction parameters corresponding to the multiple performance indicators output by the target parameter model are obtained. The target parameter model stores the correspondence between the performance indicators of multiple biological reagents and the initial reaction parameters of multiple biological reagents.

[0033] For example, the target parameter model is stored as a pre-established mathematical model or database that stores the mapping relationship (such as correspondence) between the performance indicators of multiple biological reagents and the initial reaction parameters of multiple biological reagents.

[0034] For example, the target parameter model can be a neural network model or a support vector machine model trained based on historical experimental data, or it can be a relatively simple multidimensional look-up table, without any specific restrictions.

[0035] For example, the reaction execution and monitoring module 13 is used to receive the initial reaction parameters sent by the reaction condition dynamic control module 12, control the corresponding reaction equipment (such as temperature control equipment, photometric control equipment, protein assay equipment, etc.) to perform protein assay reactions on multiple biological reagents according to the multiple initial reaction parameters, and to acquire real-time reaction data corresponding to multiple biological reagents during the protein assay reaction, such as acquiring absorbance or fluorescence signal values ​​once per second; subsequently, the reaction execution and monitoring module 13 sends the real-time reaction data to the closed-loop feedback control module 14.

[0036] It is understandable that the reaction execution and monitoring module 13 provides an observation window for the reaction process of the analysis system 10. Although the initial reaction parameters are determined by different performance indicators of different biological reagents, the actual reaction process may still be affected by unpredictable factors such as sample matrix effects and minor environmental fluctuations. By acquiring continuous real-time reaction data during the protein assay reaction, the reaction execution and monitoring module 13 provides a basis for subsequent online calibration, solving the problem that traditional endpoint methods cannot provide insight into the dynamics of the reaction process.

[0037] For example, the closed-loop feedback control module 14 is used to receive real-time reaction data sent by the reaction execution and monitoring module 13, and determine multiple preset target data (such as standard reaction kinetic curves) corresponding to the multiple real-time reaction data respectively. Based on the multiple real-time reaction data and the target data corresponding to the multiple real-time reaction data, the initial reaction parameters corresponding to the multiple real-time reaction data are adjusted to obtain adjusted reaction parameters. Furthermore, the closed-loop feedback control module 14 is also used to send the multiple adjusted reaction parameters to the reaction execution and monitoring module, so that the reaction execution and monitoring module controls the corresponding reaction equipment to perform protein assay reactions on multiple biological reagents according to the multiple adjusted reaction parameters.

[0038] In some embodiments, when the closed-loop feedback control module 14 determines that the difference between the real-time reaction data and the corresponding target data meets the adjustment conditions, it adjusts the initial reaction parameters corresponding to the real-time reaction data. For example, if the closed-loop feedback control module 14 determines that the reaction rate (corresponding to an example of the real-time reaction data) is lower than the preset reaction rate (corresponding to an example of the target data), the closed-loop feedback control module 14 may extend the reaction time or increase the reaction temperature to improve the reaction rate of the biological reagent in the protein assay process. In other embodiments, when the closed-loop feedback control module determines that the difference between the real-time reaction data and the corresponding target data does not meet the adjustment conditions, it does not adjust the initial reaction parameters corresponding to the real-time reaction data.

[0039] It is understandable that the closed-loop feedback control module 14 enables the analysis system 10 to form a complete negative feedback closed-loop control system. Through real-time negative feedback closed-loop control, the problem of being unable to cope with sudden disturbances during the process by relying solely on the initial settings is solved, ensuring that the reaction process always proceeds on the optimal track, thereby achieving high accuracy and precision of the final detection results.

[0040] In some embodiments, the closed-loop feedback control module 14 updates the target parameter model based on multiple real-time reaction data, multiple target data corresponding to the multiple real-time reaction data, multiple initial reaction parameters corresponding to the multiple real-time reaction data, and multiple adjusted reaction parameters corresponding to the multiple real-time reaction data. For example, after completing one feedback control, the closed-loop feedback control module 14 updates and optimizes the target parameter model using a self-learning algorithm based on the real-time reaction data, target data, initial reaction parameters, and adjusted reaction parameters corresponding to this feedback control. It can be understood that by updating and optimizing the target parameter model, the closed-loop feedback control module 14 enables the target parameter model to perform self-learning and self-optimization, solving the problems of static models that cannot adapt to the characteristics of new batches of reagents or long-term environmental changes, thus enabling the entire analytical system to have the ability to self-evolve and maintain a high level of performance over a long period of time.

[0041] For example, a self-learning algorithm can be an algorithm capable of iteratively updating an existing model using new data. For instance, a self-learning algorithm can be a machine learning algorithm such as gradient descent or Bayesian optimization; there are no specific limitations. In some embodiments, the analysis system 10 also includes a reagent protection module (not shown in the figures). The reagent protection module is used to adjust the storage conditions of multiple biological reagents after the protein assay reaction according to different performance indicators. It is understood that the environmental parameters of the biological reagents will change during the protein assay reaction. For example, the ideal reaction endpoint for the biological reagents' activity treatment when performing a protein assay reaction with the biological reagents by adjusting the initial reaction parameters or reaction parameters, as mentioned above, is affected. After the protein assay reaction is completed, in order to improve the utilization rate of the biological reagents, the reagent protection module dynamically regulates the storage conditions of the biological reagents according to the performance indicators calculated by the reagent status sensing module. For example, it adjusts the storage temperature, or optimizes the single-use amount and / or usage interval of the biological reagent, to extend the service life of the biological reagents and facilitate the re-performing of protein assay reactions or other chemical experiments.

[0042] Understandably, since the analysis system 10 can accurately assess the remaining activity of the reagents, it can adopt more refined management strategies to slow down their degradation. For example, conventional storage can be used when the reagent activity is still high, and a more stringent low-temperature storage mode can be switched when the activity begins to decline. By actively managing the reagents rather than passively accepting degradation, the problem of premature failure and waste caused by the "one-size-fits-all" storage and use methods in existing technologies is solved. Thus, without changing the reagent formulation, the additional technical effects of extending the effective life of the reagents and reducing the detection cost are achieved.

[0043] In some embodiments, to efficiently and accurately acquire real-time status parameters and real-time reaction data of biological reagents, the analysis system 10 may employ smart reagent tags. Exemplarily, the smart reagent tag directly integrates sensor and data recording functions onto the reagent container, recording the complete environmental journey of the biological reagent from manufacturing to use. By using smart reagent tags, the problems of inaccurate, incomplete, or difficult-to-trace data resulting from traditional reliance on manual recording or external environmental monitoring are solved, ensuring that the data input into the performance index calculation model is authentic and accurate, thus providing a solid data foundation for the precise operation of the entire analysis system 10.

[0044] In some embodiments, the smart reagent tag is physically attached to or integrated onto the reagent bottle. The internal structure of the smart reagent tag may include an RFID (Radio Frequency Identification) or NFC (Near Field Communication) chip for storing data and communicating with the outside world, and one or more microsensors connected to the chip. Real-time status parameters and real-time reaction data of the biological reagent are acquired through one or more microsensors; for example, a micro thermistor is used to record temperature changes, a photodiode is used to record cumulative light exposure, and a pair of microelectrodes are used to measure impedance changes of the reagent itself. Subsequently, the RFID or NFC chip reads the data acquired by the one or more microsensors and sends it to the analysis system 10. It is understood that different biological reagents have different smart reagent tags, and each smart reagent tag has a unique identifier. The analysis system 10 can identify different biological reagents through different tag identifiers, and identify the real-time status parameters, initial reaction parameters, real-time reaction data, target data, and adjustment reaction data corresponding to different biological reagents through different tag identifiers, so as to ensure that the analysis system 10 can accurately identify the real-time status parameters, initial reaction parameters, real-time reaction data, target data, and adjustment reaction data corresponding to different biological reagents through unique tag identifiers.

[0045] Figure 2 According to some embodiments of the present invention, a flowchart of an integrated analytical method for the determination of proteins using biological reagents is shown. It can be understood that... Figure 2 The processes shown are all executed by electronic devices. For the sake of simplicity, the following description will be further elaborated upon. Figure 2 The execution entity will not be described again in the illustrated process. For example, as shown... Figure 2 As shown, an integrated analytical method for protein assay using biological reagents includes, but is not limited to, the following steps: S21: Acquire the real-time status parameters of multiple biological reagents, and determine the performance indicators of the corresponding multiple biological reagents based on the multiple real-time status parameters.

[0046] In some embodiments, real-time state parameters include one or more of temperature, light intensity, and impedance, and performance indicators may be activity factors. It is understood that real-time state parameters are environmental factors affecting the activity of biological reagents, and monitoring them can provide direct and effective input for calculating performance indicators. A detailed explanation of step S21 can be found in the foregoing description related to the reagent state sensing module 11, and will not be repeated here. S22: Determine the initial reaction parameters of the corresponding biological reagents based on multiple performance indicators.

[0047] In some embodiments, the electronic device inputs multiple performance indicators into a preset target parameter model and obtains multiple initial reaction parameters corresponding to the multiple performance indicators output by the target parameter model. The target parameter model stores the correspondence between the performance indicators of multiple biological reagents and the initial reaction parameters of the multiple biological reagents. It is understood that this application does not perform protein assays on multiple biological reagents using a fixed reaction parameter, thus avoiding errors in the protein assay results due to the influence of fixed parameters on the activity of the biological reagents. This achieves the elimination or reduction of systematic errors introduced by differences in reagent activity at the source of the reaction. A detailed explanation of step S22 can be found in the foregoing description related to the dynamic control module 12 of the reaction conditions, and will not be repeated here.

[0048] S23: Control the corresponding reaction equipment according to multiple initial reaction parameters to perform protein assay reactions on multiple biological reagents respectively.

[0049] In some embodiments, the initial reaction parameters are determined by different performance indicators of different biological reagents. By controlling the corresponding reaction equipment according to different initial reaction parameters to perform protein assay reactions on multiple biological reagents, the reaction rate and assay accuracy of biological reagents in the protein assay reaction process can be improved.

[0050] S24: Real-time acquisition of reaction data corresponding to multiple biological reagents during the protein assay reaction.

[0051] In some embodiments, although the initial reaction parameters are determined by different performance indicators of different biological reagents, the actual reaction process may still be affected by unpredictable factors such as sample matrix effects and minor environmental fluctuations. The electronic device acquires continuous real-time reaction data during the protein assay process, providing a basis for subsequent online calibration and solving the problem that traditional endpoint methods cannot provide insight into the dynamics of the reaction process. Detailed explanations of steps S23 and S24 can be found in the foregoing description related to the reaction execution and monitoring module 13, and will not be repeated here. S25: Determine multiple preset target data corresponding to multiple real-time reaction data, and adjust the initial reaction parameters corresponding to the multiple real-time reaction data according to the multiple real-time reaction data and the target data corresponding to the multiple real-time reaction data to obtain the adjusted reaction parameters.

[0052] In some embodiments, when the electronic device determines that the difference between the real-time reaction data and the corresponding target data meets the adjustment conditions, it adjusts the initial reaction parameters corresponding to the real-time reaction data. For example, if the electronic device determines that the reaction rate (corresponding to an example of the real-time reaction data) is lower than a preset reaction rate (corresponding to an example of the target data), the electronic device may extend the reaction time or increase the reaction temperature to improve the reaction rate of the biological reagent in the protein assay process. In other embodiments, when the electronic device determines that the difference between the real-time reaction data and the corresponding target data does not meet the adjustment conditions, it does not adjust the initial reaction parameters corresponding to the real-time reaction data.

[0053] S26: Adjust multiple initial reaction parameters to corresponding adjusted reaction parameters, and control the corresponding reaction equipment to perform protein assay reactions on multiple biological reagents according to the multiple adjusted reaction parameters.

[0054] In some embodiments, the electronic device adjusts the initial reaction parameters based on real-time reaction data, forming a complete negative feedback closed-loop control system. This real-time negative feedback closed-loop control solves the problem of being unable to cope with sudden disturbances during the process if only the initial settings are relied upon, ensuring that the reaction process always proceeds on the optimal trajectory, thereby achieving high accuracy and precision in the final detection results. Detailed explanations of steps S25 and S26 can be found in the foregoing description related to the closed-loop feedback control module 14, and will not be repeated here.

[0055] In other embodiments, the electronic device adjusts the storage conditions of multiple biological reagents after the protein assay reaction based on different performance indicators. It is understood that the environmental parameters of the biological reagents change during the protein assay reaction. For example, the ideal reaction endpoint is reached when the biological reagents are subjected to protein assay reactions with initial or adjusted reaction parameters. After the protein assay reaction is completed, to improve the utilization rate of the biological reagents, the electronic device dynamically regulates the storage conditions of the biological reagents based on calculated performance indicators. For example, it adjusts the storage temperature or optimizes the single-use amount and / or usage interval of the biological reagent to extend its lifespan and facilitate further protein assay reactions or other chemical experiments.

[0056] Figure 3 According to some embodiments of the present invention, a schematic diagram of the structure of an electronic device 100 is shown. For example... Figure 3As shown, the electronic device 100 includes a processor 101, a communication interface 103, and a memory 102. The processor 101, communication interface 103, and memory 102 can be interconnected via an internal bus 104, or they can communicate via wireless transmission or other means. This embodiment of the invention uses the connection via bus 104 as an example. Bus 104 can be a peripheral component interconnect express (PCIe) bus, an extended industry standard architecture (EISA) bus, a unified bus (Ubus or UB), a compute express link (CXL), a cache coherent interconnect for accelerators (CCIX), etc. Bus 104 can be divided into address bus, data bus, control bus, etc. In addition to the data bus, bus 104 can also include a power bus, a control bus, and a status signal bus. For clarity, all buses are labeled as bus 104 in the figure.

[0057] Processor 101 may consist of at least one general-purpose processor, such as a central processing unit (CPU), or a combination of a CPU and a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof. Processor 101 executes various types of digital storage instructions, such as software or firmware programs stored in memory 102, enabling electronic device 100 to provide a variety of services.

[0058] Memory 102 may include volatile memory, such as random access memory (RAM); memory 102 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); memory 102 may also include combinations of the above types.

[0059] The communication interface 103 can be a wired interface (e.g., an Ethernet interface), an internal interface (e.g., a PCIe bus interface), a wired interface (e.g., an Ethernet interface), or a wireless interface (e.g., a cellular network interface or a wireless LAN interface), for communicating with other devices or modules.

[0060] It needs to be explained that, Figure 3 This is merely one possible implementation of an embodiment of the present invention. In actual applications, the electronic device 100 may include more or fewer components, which will not be elaborated here.

[0061] In some embodiments, the present invention also provides a computer-readable medium storing program code that, when run on a computer, causes the computer to perform the methods described in the above aspects.

[0062] In some embodiments, the present invention also provides a computer program product comprising: computer program code that, when run on a computer, causes the computer to perform the methods described above.

[0063] In the accompanying drawings, some structural or methodological features may be shown in a specific arrangement and / or order. However, it should be understood that such a specific arrangement and / or order may not be necessary. Rather, in some embodiments, these features may be arranged in a manner and / or order different from that shown in the illustrative drawings. Furthermore, the inclusion of structural or methodological features in a particular figure does not imply that such features are required in all embodiments, and in some embodiments, these features may be omitted or may be combined with other features.

[0064] It should be noted that the units / modules mentioned in the various device embodiments of the present invention are all logical units / modules. Physically, a logical unit / module can be a physical unit / module, a part of a physical unit / module, or a combination of multiple physical units / modules. The physical implementation of these logical units / modules themselves is not the most important factor; the combination of functions implemented by these logical units / modules is the key to solving the technical problem proposed by the present invention. Furthermore, to highlight the innovative aspects of the present invention, the above-described device embodiments of the present invention have not introduced units / modules that are not closely related to solving the technical problem proposed by the present invention. This does not mean that the above-described device embodiments do not contain other units / modules.

[0065] It should be noted that in the examples and description of this patent, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0066] Although the invention has been illustrated and described with reference to certain preferred embodiments thereof, those skilled in the art will understand that various changes in form and detail may be made therein without departing from the scope of the invention.

Claims

1. An integrated analytical system for protein assay using biological reagents, characterized in that, The system includes: The reagent status sensing module is used to acquire real-time status parameters of multiple biological reagents and determine the corresponding performance indicators of the multiple biological reagents based on the multiple real-time status parameters. A dynamic reaction condition control module is used to determine the initial reaction parameters of the corresponding biological reagents based on the multiple performance indicators. The reaction execution and monitoring module is used to control the corresponding reaction equipment to perform protein assay reactions on the multiple biological reagents according to the multiple initial reaction parameters, and to acquire real-time reaction data corresponding to the multiple biological reagents during the protein assay reaction. A closed-loop feedback control module is used to determine multiple preset target data corresponding to multiple real-time reaction data, and to adjust the initial reaction parameters corresponding to the multiple real-time reaction data to obtain adjusted reaction parameters based on the multiple real-time reaction data and the target data corresponding to the multiple real-time reaction data. The module is also used to send the multiple adjusted reaction parameters to the reaction execution and monitoring module, so that the reaction execution and monitoring module controls the corresponding reaction equipment to perform protein assay reactions on multiple biological reagents according to the multiple adjusted reaction parameters.

2. The system according to claim 1, characterized in that, The dynamic control module for reaction conditions inputs multiple performance indicators into a preset target parameter model and obtains multiple initial reaction parameters corresponding to the multiple performance indicators output by the target parameter model. The target parameter model stores the correspondence between the performance indicators of multiple biological reagents and the initial reaction parameters of multiple biological reagents.

3. The system according to claim 2, characterized in that, The closed-loop feedback control module updates the target parameter model based on multiple real-time reaction data, multiple target data corresponding to the multiple real-time reaction data, multiple initial reaction parameters corresponding to the multiple real-time reaction data, and multiple adjustment reaction parameters corresponding to the multiple real-time reaction data.

4. The system according to claim 1, characterized in that, The closed-loop feedback control module determines that the difference between the real-time reaction data and the corresponding target data meets the adjustment conditions, and adjusts the initial reaction parameters corresponding to the real-time reaction data. The closed-loop feedback control module determines that the difference between the real-time reaction data and the corresponding target data does not meet the adjustment conditions, and therefore does not adjust the initial reaction parameters corresponding to the real-time reaction data.

5. The system according to any one of claims 1 to 4, characterized in that, Also includes: A reagent protection module is used to adjust the storage conditions of the corresponding biological reagents after the protein assay reaction according to different performance indicators.

6. The system according to any one of claims 1 to 4, characterized in that, The real-time status parameters include one or more of temperature, light intensity, and impedance; The initial reaction parameters include one or more of the following: reaction temperature, reaction time, and sample volume.

7. An integrated analytical method for the determination of proteins using biological reagents, characterized in that, The method includes: The real-time status parameters of multiple biological reagents are acquired in real time, and the performance indicators of the corresponding multiple biological reagents are determined based on the multiple real-time status parameters. The initial reaction parameters of the corresponding biological reagents are determined based on the various performance indicators. Based on the multiple initial reaction parameters, the corresponding reaction devices are controlled to perform protein assay reactions on the multiple biological reagents respectively; Real-time reaction data corresponding to multiple biological reagents are acquired during the protein assay reaction. Multiple preset target data corresponding to multiple real-time reaction data are determined, and the initial reaction parameters corresponding to the multiple real-time reaction data are adjusted according to the multiple real-time reaction data and the target data corresponding to the multiple real-time reaction data to obtain the adjusted reaction parameters; The initial reaction parameters are adjusted to the corresponding adjusted reaction parameters, and the corresponding reaction devices are controlled according to the adjusted reaction parameters to perform protein assay reactions on the biological reagents.

8. The method according to claim 7, characterized in that, Also includes: The storage conditions of the corresponding biological reagents after the protein assay reaction are adjusted according to the different performance indicators.

9. A computer-readable storage medium, characterized in that, The readable storage medium stores instructions that, when executed on an electronic device, cause the electronic device to perform the functions of the system according to any one of claims 1 to 6 and the method according to any one of claims 7 and 8.

10. An electronic device, characterized in that, include: Memory is used to store instructions executed by one or more processors of an electronic device; And a processor, one of the processors of the electronic device, for executing instructions stored in the memory to implement the functions of the system of any one of claims 1 to 6 and the method of any one of claims 7 and 8.

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