Drug evaluation method and system

Abstract

The invention discloses a drug evaluation method and system. The method comprises the steps that original imaging data corresponding to a target area under electric field stimulation are obtained, the target area comprises a plurality of to-be-detected cells under candidate drug culture, and the plurality of to-be-detected cells have fluorescent labels; target fluorescence change jointly corresponding to the multiple to-be-detected cells is determined from the original imaging data, and the target fluorescence change is used for quantitatively representing the average change degree of membrane potentials of the multiple to-be-detected cells under electric field stimulation; and evaluating the candidate drug according to the target fluorescence change to obtain an evaluation result. The technical problem that the evaluation efficiency is low due to the fact that a drug screening method in the related technology is limited by flux on evaluation of cell electrophysiological characteristics is solved.

Description

Technical Field

[0001] The present application relates to the field of biomedical engineering technology, and in particular to a method and system for drug evaluation. Background Art

[0002] Patch clamp technology is a traditional method for evaluating the electrophysiological characteristics of cells. It can apply current stimulation to cells or clamp the cell membrane potential, and can detect the voltage and current values ​​of the entire cell membrane or even a single channel with high accuracy and time resolution. With the development of biomedical engineering, patch clamp has gradually evolved from initially clamping and recording a single cell to dual-channel, four-channel, and even multi-channel patch clamp recording. However, when performing electrophysiological tests on large-scale cells, patch clamp technology is still limited by throughput, resulting in low efficiency in drug screening and evaluation.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present application provide a method and system for drug evaluation, so as to at least solve the technical problem that drug screening methods in related technologies are limited by flux in the evaluation of cell electrophysiological characteristics, resulting in low evaluation efficiency.

[0005] According to one aspect of an embodiment of the present application, a method for drug evaluation is provided, comprising: acquiring original imaging data corresponding to a target area under electric field stimulation, wherein the target area includes a plurality of cells to be tested cultured with a candidate drug, and the plurality of cells to be tested have fluorescent markers; determining a target fluorescence change corresponding to the plurality of cells to be tested from the original imaging data, wherein the target fluorescence change is used to quantify an average degree of change in membrane potential of the plurality of cells to be tested under electric field stimulation; and evaluating the candidate drug according to the target fluorescence change to obtain an evaluation result.

[0006] In some embodiments of the present application, a target fluorescence change corresponding to multiple cells to be tested is determined from the original imaging data, including: segmenting the multiple cells to be tested in the original imaging data to obtain cell regions corresponding to the multiple cells to be tested respectively; determining a first fluorescence change corresponding to each cell region from the original imaging data, wherein the first fluorescence change is used to quantitatively represent the degree of response of the cell region to the electric field stimulation within a preset statistical period under the electric field stimulation; and determining the target fluorescence change corresponding to the multiple cells to be tested according to the first fluorescence changes corresponding to all the cell regions respectively.

[0007] In some embodiments of the present application, a first fluorescence change corresponding to each cell region is determined from the original imaging data, including: determining a second fluorescence change corresponding to each cell region, wherein the second fluorescence change is used to quantify the fluorescence intensity change over time in the cell region; determining a background region corresponding to each cell to be tested based on each cell region, and determining a third fluorescence change corresponding to the background region, wherein the third fluorescence change is used to quantify the fluorescence intensity change over time in the surrounding area of ​​each cell region; and determining the first fluorescence change based on the second fluorescence change and the third fluorescence change.

[0008] In some embodiments of the present application, a background area corresponding to each cell to be tested is determined based on each cell area, including: expanding each cell area outward by a first number of pixels to obtain a first area corresponding to each cell area; determining the area other than all first areas in the original imaging data as a second area; based on the second area, expanding each cell area outward by a second number of pixels to obtain a third area corresponding to each cell area, wherein the first number is less than the second number; and determining the intersection of the second area and the third area as the background area.

[0009] In some embodiments of the present application, the original imaging data includes multiple frames of imaging data, and multiple cells to be tested in the original imaging data are segmented, including: performing statistical averaging on the fluorescence intensity at each time point within a preset statistical period in the multiple frames of imaging data to obtain an average value projection corresponding to the original imaging data, wherein the average value projection is an image formed after statistical averaging; and segmenting the multiple cells to be tested in the average value projection.

[0010] In some embodiments of the present application, after obtaining the cell area corresponding to each cell to be tested, the method also includes: comparing the attribute information of the cell area with a first preset condition to obtain a first comparison result, wherein the first preset condition is used to screen the size and / or brightness of the cell area; when the first comparison result indicates that the attribute information does not meet the first preset condition, determining that the cell area is an invalid area.

[0011] In some embodiments of the present application, a target fluorescence change corresponding to multiple cells to be tested is determined based on the first fluorescence changes corresponding to all cell regions respectively, including: comparing the first fluorescence change with a second preset condition to obtain a second comparison result, wherein the second preset condition is used to screen the response degree of the cells to be tested corresponding to the cell region to the electric field stimulation; adding the cells to be tested corresponding to the cell region to the target cell set when the second comparison result indicates that the first fluorescence change satisfies the second preset condition; and determining the target fluorescence change based on the first fluorescence change of the cell region corresponding to the cells to be tested in the target cell set.

[0012] In some embodiments of the present application, obtaining original imaging data corresponding to a target area under electric field stimulation includes: moving a stage for carrying a plurality of cells to be tested to a first position corresponding to the target area, wherein the first position is located above a microscope objective; lowering an electrode to a second position, wherein the electrode contacts an upper surface of the plurality of cells to be tested at the second position; performing electric field stimulation on the plurality of cells to be tested using the electrode under illumination by a light source; and obtaining original imaging data corresponding to the plurality of cells to be tested acquired by an image acquisition device under electric field stimulation.

[0013] In some embodiments of the present application, a plurality of cells to be tested are located in any one of the holes in a target well plate, and a stage for carrying the plurality of cells to be tested is moved to a first position corresponding to a target area, including: receiving a selection instruction for a target object, wherein the selection instruction includes any one hole number corresponding to the target well plate; obtaining size parameters of the target well plate, wherein the size parameters include the hole center distance between two adjacent holes; determining a third position corresponding to the stage as a coordinate origin, and determining coordinate information corresponding to the hole number based on the hole center distance; and moving the area corresponding to the hole number to the first position based on the coordinate information on the basis of the third position.

[0014] In some embodiments of the present application, before moving the carrier for carrying multiple cells to be tested to a first position corresponding to the target area, the method also includes: comparing a fourth position corresponding to the electrode with a third preset condition to obtain a third comparison result, wherein the third preset condition is used to detect whether the electrode meets the movement requirements; when the third comparison result indicates that the fourth position does not meet the third preset condition, raising the electrode from the fourth position to a fifth position so that the electrode is out of contact with the multiple cells to be tested, wherein the vertical distance between the fifth position and the second position meets the preset threshold.

[0015] In some embodiments of the present application, at least one well of the target well plate contains a plurality of cells to be tested cultured with a candidate drug, and each well corresponds to at least one candidate drug, wherein the target well plate comprises a 24-well plate and / or a 96-well plate and / or a 384-well plate.

[0016] According to another aspect of the embodiment of the present application, a system for drug evaluation is also provided, including: an imaging subsystem, an electrode and a processor, wherein the imaging subsystem includes a light source and an image acquisition device, the light source is connected to the processor, and is used to provide lighting conditions for electrode stimulation before starting electrode stimulation; the electrode is connected to the processor, and is used to perform electric field stimulation on multiple cells to be tested in the target area under the candidate drug culture, wherein the multiple cells to be tested have fluorescent markers; the image acquisition device in the imaging subsystem is connected to the processor, and is used to collect raw imaging data corresponding to the target area under electric field stimulation, and send the raw imaging data to the processor; the processor is connected to the imaging subsystem, and is used to receive the raw imaging data, and determine the target fluorescence change corresponding to the multiple cells to be tested from the raw imaging data, wherein the target fluorescence change is used to quantify the average change degree of the membrane potential of the multiple cells to be tested under electric field stimulation; the candidate drug is evaluated according to the target fluorescence change to obtain an evaluation result.

[0017] In some embodiments of the present application, the system also includes a moving device, wherein the moving device includes an electric motor, which is respectively connected to the controller and the electrode, and is used to receive instructions sent by the controller and control the electrode to move in the Z-axis direction of the coordinate axis according to the instructions; the moving device also includes a stage, which is connected to the processor, and is used to carry the target well plate and move the designated area in the target well plate to the target area.

[0018] In some embodiments of the present application, the system further includes a stimulation isolator, wherein the stimulation isolator is connected to the electrode, and is used to isolate and amplify the voltage signal emitted by the electrode, and output a pulse voltage to a plurality of cells to be tested.

[0019] In some embodiments of the present application, the processor is also used to: segment multiple cells to be tested in the original imaging data to obtain cell regions corresponding to the multiple cells to be tested; determine a first fluorescence change corresponding to each cell region from the original imaging data, wherein the first fluorescence change is used to quantitatively represent the degree of response of the cell region to the electric field stimulation within a preset statistical period under the electric field stimulation; determine the target fluorescence change corresponding to multiple cells to be tested based on the first fluorescence changes corresponding to all the cell regions.

[0020] In some embodiments of the present application, the processor is also used to: determine a second fluorescence change corresponding to each cell region, wherein the second fluorescence change is used to quantify the time-varying trend of the fluorescence intensity in the cell region; determine a background region corresponding to each cell to be tested based on each cell region, and determine a third fluorescence change corresponding to the background region, wherein the third fluorescence change is used to quantify the time-varying trend of the fluorescence intensity in the surrounding area of ​​each cell region; determine the first fluorescence change based on the second fluorescence change and the third fluorescence change.

[0021] According to another aspect of the embodiments of the present application, a device for drug evaluation is also provided, including: an acquisition module, used to acquire original imaging data corresponding to a target area under electric field stimulation, wherein the target area includes multiple cells to be tested cultured with a candidate drug, and the multiple cells to be tested have fluorescent markers; a determination module, used to determine a target fluorescence change corresponding to the multiple cells to be tested from the original imaging data, wherein the target fluorescence change is used to quantify the average degree of change in the membrane potential of the multiple cells to be tested under electric field stimulation; an evaluation module, used to evaluate the candidate drug according to the target fluorescence change to obtain an evaluation result.

[0022] According to another aspect of the embodiments of the present application, a non-volatile storage medium is provided, which includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the above-mentioned drug evaluation method by running the computer program.

[0023] According to another aspect of the embodiments of the present application, a computer program product is provided, including computer instructions, which implement the above-mentioned drug evaluation method when executed by a processor.

[0024] In the embodiments of the present application, electric field stimulation and fluorescent labeling technology are used to evaluate ion channel-related drugs by high-throughput recording of the differences in cell potential changes caused by different drugs under electric field stimulation, thereby achieving the purpose of synchronous electrophysiological detection and optical recording of large-scale cells, thereby achieving the technical effect of reducing the complexity of experimental operations and improving the efficiency of drug screening and evaluation, and further solving the technical problem of low evaluation efficiency due to the limitation of flux in the evaluation of cell electrophysiological characteristics in drug screening methods in related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0026] Figure 1 It is a hardware structure block diagram of a computer terminal of a method for drug evaluation according to an embodiment of the present application;

[0027] Figure 2 is a flow chart of a method for drug evaluation according to an embodiment of the present application;

[0028] Figure 3 is an overall flow chart of a method for drug evaluation according to an embodiment of the present application;

[0029] Figure 4is a schematic diagram of cell segmentation in a target area of ​​a drug evaluation method according to an embodiment of the present application;

[0030] Figure 5 is a schematic diagram of a background area of ​​a target area of ​​a drug evaluation method according to an embodiment of the present application;

[0031] Figure 6 This is a schematic diagram of the average fluorescence change and sensitivity distribution of cells in a target area of ​​a drug evaluation method according to an embodiment of the present application;

[0032] Figure 7 This is a schematic diagram of representative regional distribution of fluorescence changes of high-response cells in a target area of ​​a drug evaluation method according to an embodiment of the present application;

[0033] Figure 8 is an operation flow chart of a method system for drug evaluation according to an embodiment of the present application;

[0034] Fig. 9 is a schematic diagram of system operation speed analysis of a method for drug evaluation according to an embodiment of the present application;

[0035] Fig.10 It is a schematic diagram of the structure of a drug evaluation device according to an embodiment of the present application. DETAILED DESCRIPTION

[0036] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0037] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0038] In order to better understand the embodiments of the present application, the technical terms involved in the embodiments of the present application are explained as follows:

[0039] Electric Field Stimulation (EFS): In biomedical research, an external electric field is used to stimulate cells or tissues to study their electrophysiological properties or evaluate the effects of drugs on excitable cells (such as nerve cells and cardiomyocytes). It is also called electric field stimulation in this application.

[0040] Fluorophore: A molecule that absorbs light of a specific wavelength and emits fluorescence at a longer wavelength. It is the basis of fluorescent probes and fluorescent dyes.

[0041] Fluorescence Signal: A light signal emitted by a biological molecule or cell marker (fluorescent probe) after absorbing light of a specific wavelength, which is used for quantitative analysis of expression level, activity and location in cell biology and biomedical research.

[0042] Membrane Potential: The potential difference caused by the difference in ion concentration inside and outside the cell membrane is the basis of cell electrophysiological activities and is crucial to the excitability and signal transduction of nerve, muscle and gland cells.

[0043] HEK 293T cell line (Human Embryonic Kidney 293T Cell Line, referred to as HEK 293T): A laboratory cell line derived from human embryonic kidney cells, used for gene expression, protein production, and research on cell signaling and drug action mechanisms.

[0044] There are many limitations in the technologies used for screening and evaluating ion channel-related drugs in related technologies. First, the patch clamp technology requires independent electrode clamping and current recording for each cell, which is extremely inefficient when processing a large number of cell samples. In addition, the patch clamp requires physical contact with the cells and clamps part of the cell membrane through electrodes. This operation causes certain mechanical and electrical interference to the cells, which can easily lead to changes in the physiological state of the cells and affect the accuracy of the results. Secondly, EEG (Electroencephalography) and EMG (Electromyography) technologies collect electrical signals by placing electrodes on the scalp or skin surface, which makes it impossible to accurately distinguish the electrical signals of specific cell populations and lacks specificity at the cellular level, that is, it has non-cell selectivity. In addition, behavioral experiments on animal models often have the characteristics of high cost and long cycle.

[0045] In order to solve the above technical problems, the embodiments of the present application provide corresponding solutions, which are described in detail below.

[0046] The method embodiment of drug evaluation provided in the embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 FIG. 1 shows a hardware structure block diagram of a computer terminal for implementing a method for drug evaluation. Figure 1 As shown, the computer terminal 10 may include one or more (102a, 102b, ..., 102n are used to illustrate) processors (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission module 106 for communication functions connected via a wired and / or wireless network. In addition, it may also include: a display, a keyboard, a cursor control device, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, and a BUS bus. Those skilled in the art will understand that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0047] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10. As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0048] The memory 104 can be used to store software programs and modules of application software, such as program instructions / data storage devices corresponding to the method of drug evaluation in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, realizing the above-mentioned method of drug evaluation. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0049] The transmission module 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission module 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission module 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0050] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 .

[0051] It should be noted that, in some optional embodiments, the above Figure 1 The computer terminal shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of hardware elements and software elements. It should be noted that Figure 1 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the computer terminal described above.

[0052] In the above-mentioned operating environment, an embodiment of the present application provides a method embodiment for drug evaluation. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0053] Figure 2 is a flow chart of a method for drug evaluation according to an embodiment of the present application, such as Figure 2 As shown, the method comprises the following steps:

[0054] Step S202, obtaining original imaging data corresponding to a target area under electric field stimulation, wherein the target area includes a plurality of cells to be tested cultured with a candidate drug, and the plurality of cells to be tested are fluorescently labeled.

[0055] In the above step S202, in a high-throughput drug screening experiment, the target area specifically refers to the cell culture area in one or more wells of a well plate, and these areas contain the cell population for testing the candidate drug.

[0056] Multiple cells to be tested are fluorescently labeled, which means that cells are labeled with fluorescent probes or fluorescent proteins, so that specific physiological states of cells (such as changes in membrane potential) can be visualized under an optical microscope, and the changes in the intensity of the fluorescent signal reflect the response of the cells to electric field stimulation.

[0057] In some embodiments of the present application, the original imaging data corresponding to the target area under electric field stimulation can be obtained by the following steps, specifically: moving the stage for carrying multiple cells to be tested to a first position corresponding to the target area, wherein the first position is located above the microscope objective; lowering the electrode to a second position, wherein the electrode contacts the upper surface of the multiple cells to be tested at the second position; under the illumination of a light source, performing electric field stimulation on the multiple cells to be tested using the electrode; and obtaining the original imaging data corresponding to the multiple cells to be tested acquired by the image acquisition device under electric field stimulation.

[0058] The stage is used to carry samples (such as cell culture well plates) and can move in the x-axis and y-axis directions of the coordinate axes according to experimental requirements to accurately locate the target area. The first position refers to the position where the stage moves to the position directly above the microscope objective lens, for example, the starting position of the stage when preparing to collect the fluorescent signal of cells in a specific well, to ensure that the objective lens can face the target area and provide stable and accurate focus for high-resolution imaging. In some embodiments of the present application, the stage can be controlled to move to a preset first position through the interface between the MATLAB environment and the stage driver, and the first position ensures that the microscope objective lens faces the target area.

[0059] The electrode is a device for generating an electric field and applying it to the cell. For example, it can be made of a conductive material such as a platinum electrode. Through the contact between the electrode and the cell, an electric field can be formed around the cell, thereby simulating the scene of cell stimulation and evaluating the effect of candidate drugs on the electrophysiological properties of the cell. In some embodiments of the present application, MATLAB is driven by a controller to lower the electrode to a second position in contact with the upper surface of the cell, ensuring that the electrical stimulation can accurately act on the target cell and avoiding uneven electric field distribution caused by improper electrode position.

[0060] The light source refers to a light source that provides sufficient brightness to observe fluorescently labeled cells during microscope imaging, which can be an LED light source or a laser light source. In some embodiments of the present application, the MATLAB environment can simultaneously control electrode stimulation and light source illumination, so that while the electrode is applying electric field stimulation, the light source provides stable illumination, ensuring that during the stimulation process, the image acquisition device can record a clear fluorescent signal. For example, MATLAB controls the light source output through a data acquisition card, and at the same time, outputs electrode stimulation commands and outputs pulsed voltages through a stimulation isolator. The two are precisely synchronized through TTL (Transistor-Transistor Logic) signals.

[0061] When the electrode starts to stimulate, the image acquisition device is triggered by the data acquisition card and starts to synchronously collect data according to preset parameters such as sampling rate, exposure time and bin value (binning, pixel merging method) to obtain raw imaging data.

[0062] In order to avoid experimental errors caused by improper electrode position, before moving the stage for carrying multiple cells to be tested to the first position corresponding to the target area, it is also possible to detect whether the position of the electrode meets the movement requirements. Specifically: the fourth position corresponding to the electrode is compared with the third preset condition to obtain a third comparison result, wherein the third preset condition is used to detect whether the electrode meets the movement requirements; when the third comparison result indicates that the fourth position does not meet the third preset condition, the electrode is raised from the fourth position to the fifth position so that the electrode is out of contact with the multiple cells to be tested, wherein the vertical distance between the fifth position and the second position meets the preset threshold.

[0063] Since the electrode needs to at least dive to the position of contacting the upper surface of the cell during stimulation, after electric field stimulation, the electrode may still be at or close to the position of contacting the cell. The fourth position refers to the actual position of the electrode after the stimulation is completed.

[0064] The preset threshold refers to the vertical distance required for the electrode to move from the second position to the fifth position after stimulation, and is set to prevent the electrode from causing damage to the cells or touching the well plate during movement. In some embodiments of the present application, during the experiment, there are situations such as switching the field of view within the well (switching the field of view in the same target well) and switching the field of view between wells (the field of view switches from the first target well to the second target well). The preset threshold (first preset threshold) when switching within the well is less than the preset threshold (second preset threshold) when switching between wells. The preset threshold can be determined based on the time consumed by the electrode displacement distance. A shorter displacement distance can reduce the time consumed in the field of view switching process.

[0065] In the case where multiple cells to be tested are located in any one of the wells in the target well plate, precise positioning of any well in the target well plate can be achieved through the following steps: receiving a selection instruction for the target object, wherein the selection instruction includes any one of the well numbers corresponding to the target well plate; obtaining size parameters of the target well plate, wherein the size parameters include the hole center distance between two adjacent holes; determining the third position corresponding to the stage as the coordinate origin, and determining the coordinate information corresponding to the hole number based on the hole center distance; on the basis of the third position, moving the area corresponding to the hole number to the first position based on the coordinate information.

[0066] The target object's selection instructions are instructions provided by the target object through the software interface or script to specify the specific well number in the well plate that you want to image and stimulate. For example, in the MATLAB environment, the target object can specify the target well through the GUI (Graphical User Interface) or directly enter the well number at the command line.

[0067] In some embodiments of the present application, the control program in the MATLAB environment can set the default stage position (third position) to the coordinate origin (0, 0). When it is necessary to locate other holes, the position coordinates of the target hole relative to the coordinate origin can be calculated based on the target hole number and the hole center distance. Specifically, after the stage is initialized, the stage will move to the position where the starting hole (such as the A1 port of the 96-well plate) of the target well plate (such as a 96-well plate) is located above the objective lens in the preset state, and the position coordinates are set to (0, 0). At this time, the relative coordinates of the center position of each hole can be obtained according to the size parameters of the target well plate and loaded into the coordinate table in the subfunction. Taking a 96-well plate (bottom diameter of 6.4 mm, hole center distance of 9 mm) as an example, starting from A1, every other row (letter increases by 1), the ordinate decreases by 9 mm; starting from A1, every other column (number increases by 1), the abscissa decreases by 9 mm. When you want to switch holes, you can directly enter the number of the hole you want to image (such as "A8", "G12"). For example, when moving from hole A1 to hole A8, the MATLAB program will move the stage 7×9 mm=63 mm in the y-axis direction based on the hole center distance of 9 mm, thereby moving hole A8 to the position directly below the microscope objective (the first position).

[0068] In some embodiments of the present application, at least one well of the target well plate contains a plurality of cells to be tested cultured with a candidate drug, and each well corresponds to a treatment condition (such as concentration and time) of at least one candidate drug, wherein the target well plate includes a 24-well plate and / or a 96-well plate and / or a 384-well plate.

[0069] A target well plate refers to a multi-well plate used to culture cells to be tested in high-throughput drug screening experiments. Depending on the throughput requirements of the experiment, the target well plate can be a 24-well plate, a 96-well plate, or a 384-well plate, etc. Each well can independently culture cell samples and perform different drug treatments.

[0070] Step S204, determining the target fluorescence change corresponding to the multiple cells to be tested from the original imaging data, wherein the target fluorescence change is used to quantify the average degree of change of the membrane potential of the multiple cells to be tested under the electric field stimulation.

[0071] In the above step S204, the target fluorescence change is obtained by statistically analyzing the fluorescence changes of the identified cells in the original imaging data, reflecting the overall response of the cell population to the stimulus. The average degree of change refers to the overall change amplitude and trend of the fluorescence signal when the cell population is stimulated by the electric field to cause the membrane potential to change. For example, by comparing the calculated target fluorescence change with the baseline fluorescence when there is no stimulation, the amplitude of the fluorescence change, that is, the ΔF / F value, can be obtained to reflect the degree of change of the cell's membrane potential under electric field stimulation or drugs. The fluorescence change amplitude ΔF / F of all cells is averaged to obtain the target fluorescence change. For each stimulation pulse, the peak value of the target fluorescence change can be used to indicate the intensity of the response, and the time for the fluorescence signal to return to the baseline can reflect the duration of the response.

[0072] In some embodiments of the present application, the target fluorescence change can be determined by the following steps: segmenting multiple cells to be tested in the original imaging data to obtain cell regions corresponding to the multiple cells to be tested; determining a first fluorescence change corresponding to each cell region from the original imaging data, wherein the first fluorescence change is used to quantitatively represent the degree of response of the cell region to the electric field stimulation within a preset statistical period under the electric field stimulation; and determining the target fluorescence change corresponding to the multiple cells to be tested based on the first fluorescence changes corresponding to all the cell regions.

[0073] Cell segmentation is to automatically identify and separate the boundaries of each cell from the original imaging data, and decompose the complex cell population in the image into multiple independent cell regions. In some embodiments of the present application, the cpCyto2 model of Cellpose2 can be used to analyze the original imaging data, and the boundaries of the cells can be automatically identified by computer vision algorithms, and separated from the background to form independent cell regions. The parameters of the model include average cell diameter (averageCellDiameter), cell probability threshold (cellThreshold) and flow field threshold (flowThreshold), etc. In order to efficiently divide the contours of individual cells under cell density and membrane positioning conditions and ensure the accuracy of segmentation, the cell threshold parameter and the flow threshold parameter can be equal.

[0074] In some embodiments of the present application, the original imaging data includes multiple frames of imaging data. Before segmenting the multiple cells to be tested in the original imaging data, the following steps can also be performed: statistically average the fluorescence intensity at each time point within a preset statistical period in the multiple frames of imaging data to obtain an average value projection corresponding to the original imaging data, wherein the average value projection is an image formed after statistical averaging; and segment the multiple cells to be tested in the average value projection.

[0075] For example, in the MATLAB environment, the data processing function can be used to perform statistical averaging on multiple frames of image data within a preset statistical period. Specifically, all images within the statistical period can be superimposed, and then the fluorescence intensity of each pixel can be averaged, and the resulting image is the average projection. For example, for a specific statistical period (such as a time window after an electrical stimulation), all image frames within the period are superimposed, and then the fluorescence value of each pixel is averaged to reduce signal noise and fluctuations, and obtain a clearer cell fluorescence expression image.

[0076] Through the average projection, the fluorescence expression of cells in the statistical period can be more clearly seen. Using the cpCyto2 model of Cellpose2 to segment the image, the boundaries of each cell to be tested can be more accurately identified and separated. For example, based on the average projection image, the cpCyto2 model can identify the cell outline and separate different cell areas from the background, which is convenient for the subsequent calculation of the first fluorescence change.

[0077] After obtaining the cell area corresponding to each cell to be tested, the following steps can also be performed: comparing the attribute information of the cell area with a first preset condition to obtain a first comparison result, wherein the first preset condition is used to screen the size and / or brightness of the cell area; when the first comparison result indicates that the attribute information does not meet the first preset condition, determining that the cell area is an invalid area.

[0078] The attribute information of the cell region refers to the characteristic data of each cell region obtained after cell segmentation, including but not limited to the size (area) and brightness information of the cell region. In some embodiments of the present application, in the MATLAB environment, image processing and data analysis functions can be used to measure the attribute information (such as size and brightness) of each cell region and compare it with the preset screening conditions. For example, by calculating the area and average brightness of each cell region, it is determined whether they fall within the preset size and brightness range.

[0079] In high-throughput drug screening experiments, it is crucial to accurately and effectively analyze the changes in fluorescence signals of each cell to be tested. However, not all cell regions obtained by cell segmentation are valid or suitable for further analysis. Cell regions that are too small or too low in brightness may be caused by the failure of cells to successfully express fluorescent probes or by some technical limitations in the imaging process (such as insufficient resolution or background noise).

[0080] Some cell regions are marked as invalid regions because they are too small or too low in brightness and do not meet the preset screening conditions. These excluded invalid regions can still play a role in the subsequent determination of background regions. By expanding all the cell regions obtained by the initial segmentation and then negating them, a global background region containing pixels around all cell regions can be obtained (for specific implementation, please refer to the description of the second region below). When determining the global background region, the cell regions corresponding to the invalid regions are regarded as normal cell regions, and the invalid regions are also expanded and negated to ensure that even if the cell regions are marked as invalid, these regions can still be used to determine the background signal, reduce data misreading caused by inaccurate background signal deduction, and ensure that the calculation of the first fluorescence change and the target fluorescence change is based on pure cell signals.

[0081] The first fluorescence change refers to the change in fluorescence intensity of a single cell region under electric field stimulation within a preset statistical period, including the change in the true fluorescence intensity of each cell region after removing the background effect, which is used to quantify the response degree of the region to electric field stimulation. In some embodiments of the present application, for each segmented cell region, its average fluorescence intensity change during the electrical stimulation process can be calculated, wherein the preset statistical period is the duration of each electrical stimulation plus the time interval between stimulations, for example, under the condition that the stimulation frequency is 3.28 Hz and each stimulation lasts for 10.18 milliseconds, the statistical period will include a complete stimulation and recovery process. By analyzing the curve of the change of fluorescence intensity over time in the cell region, the first fluorescence change can be calculated, including parameters such as peak fluorescence intensity, amplitude of fluorescence intensity change and recovery time, so as to evaluate the sensitivity and response degree of the cell to stimulation.

[0082] In some embodiments of the present application, the first fluorescence change can be determined in the following manner: determining the second fluorescence change corresponding to each cell region, wherein the second fluorescence change is used to quantify the fluorescence intensity change over time in the cell region; determining the background region corresponding to each cell to be tested based on each cell region, and determining the third fluorescence change corresponding to the background region, wherein the third fluorescence change is used to quantify the fluorescence intensity change over time in the surrounding area of ​​each cell region; determining the first fluorescence change based on the second fluorescence change and the third fluorescence change.

[0083] The second fluorescence change refers to the trend of the internal fluorescence intensity of each cell region changing over time under the stimulation of the electric field. The second fluorescence change can be determined by analyzing the change of the average fluorescence intensity of each cell region over time within a preset statistical period, for example, by calculating the change of the average fluorescence intensity of all pixels in the cell region over time to obtain the second fluorescence change.

[0084] When determining the background area corresponding to each cell to be tested, the surrounding background area of ​​each cell can be defined based on the cell area obtained after cell segmentation through certain expansion operations (such as using structural elements), and the change trend of the fluorescence intensity of the background area over time, that is, the third fluorescence change, can be extracted from the original imaging data.

[0085] In some embodiments of the present application, the second fluorescence change can be corrected by subtracting the third fluorescence change of each cell region (ie, the fluorescence change of the background region) to obtain the first fluorescence change.

[0086] Through two expansion operations, the background area corresponding to each cell to be tested can be determined, specifically: each cell area is expanded outward by a first number of pixels to obtain a first area corresponding to each cell area; the area other than all first areas in the original imaging data is determined as a second area; on the basis of the second area, each cell area is expanded outward by a second number of pixels to obtain a third area corresponding to each cell area, wherein the first number is less than the second number; the intersection of the second area and the third area of ​​each cell is determined as the background area of ​​the cell.

[0087] The first number of pixels refers to the number of pixels for performing a preliminary expansion operation (first expansion) on each cell region when determining the background region, which is usually small and is used to preliminarily define the boundary range of the cell to avoid directly including the cell region in the background region. The first region is the region formed after each cell region expands outward by the first number of pixels, which includes the cell region and the non-cell portion near the cell boundary. In some embodiments of the present application, a specific structural element (such as an octagonal structural element) can be combined to perform an expansion operation on the cell region to define a preliminary background range near the cell boundary.

[0088] The second number of pixels refers to the number of pixels for further dilation of each cell region (second dilation) after determining the second region. The second number is greater than the first number and is used to more comprehensively define the background region of each cell to ensure that the background region is large enough to accurately reflect nonspecific fluorescence changes. The third region is the region formed after each cell region is dilated by the second number of pixels.

[0089] In some embodiments of the present application, the first expansion and the second expansion may use the same structural element or different structural elements. Each cell region may use the same structural element for expansion operation, and multiple cell regions may use different structural elements for expansion operation, which is not limited here. For example, the shape and size of the expansion structural element may be automatically adjusted based on the morphological information (shape parameters) of each cell region, such as aspect ratio, convexity, area, etc. Specifically:

[0090] Step 1: Extract the morphological features of each cell region.

[0091] (1) Loading cell region data: Load the contour information of all cell regions from the binary image output by Cellpose2 or other cell segmentation algorithms.

[0092] (2) Calculation of morphological features: Calculate the aspect ratio, convexity, area and other characteristic data of each cell region.

[0093] Step 2: Design and generate shape-adaptable structural elements.

[0094] (1) Determine the expansion shape: Determine the shape of the expansion structure element based on the first characteristic data of the cell region (such as aspect ratio and direction). For example, if the cell region is long and narrow, an elliptical or rectangular structure element can be used; if the shape of the cell region is more complex, a polygonal structure element can be used.

[0095] (2) Calculate the dilation parameter: Based on the secondary characteristic data of the cell area (such as area and convexity), calculate the size of the structural element. Cells with larger areas may require larger structural elements to fully cover their edges, while cells with lower convexity (meaning irregular shapes) may require finer structural elements.

[0096] (3) Generate structural elements: Generate structural elements corresponding to each cell region based on the expansion shape and expansion parameters.

[0097] Step 3: Perform a shape-adaptive dilation operation.

[0098] (1) Apply structural element for dilation: For each cell region, use the shape-adaptive structural element generated in step 2 to perform a dilation operation to preliminarily define the background range.

[0099] (2) Adjusting the expansion range: In some embodiments of the present application, the expansion range can be further adjusted according to the brightness and size information of the cell area. For example, cells with lower brightness or smaller size may require a larger expansion range to ensure that the background area is fully covered.

[0100] The background region is the intersection of the second region and the third region, and this region is used to determine the surrounding environment of each cell region for subsequent fluorescence change analysis to subtract nonspecific fluorescence changes.

[0101] In a specific embodiment, each segmented cell region can be expanded outward by 9 pixels (about 15.6 microns) according to the structural elements of the octagon, and then the remaining area in the whole field of view after deducting each expanded cell region is defined as the global background selection area (i.e., the second area). On the basis of this global background selection area, the background selection area (i.e., the background area) corresponding to each cell region is defined as the intersection of the octagon formed by expanding outward by 108 pixels (about 187.2 microns) in each direction according to the structural elements of the octagon and the global background selection area obtained by expanding outward by 3 pixels for all cells, respectively, so as to reduce the influence of uneven illumination of the imaging field of view on the accuracy of the background subtraction operation. For the background signal corresponding to each region (i.e., the third fluorescence change), a notch operation of 2.5-30 Hz and a smoothing process at intervals of 1 stimulation cycle (60 frames, about 305 milliseconds) can also be used to avoid introducing new noise in the background subtraction operation one by one.

[0102] The target fluorescence change can be determined by summing up the first fluorescence changes of all cell regions and using statistical methods such as mean, median or specific percentile. For example, the MATLAB program will analyze the fluorescence changes of the effective cell region, and then sort or set a threshold according to the change amplitude, and select representative changes as the target fluorescence change to evaluate the response of the overall cell population to electric field stimulation.

[0103] In some embodiments of the present application, in order to improve data precision and confidence, before determining the target fluorescence change, the first fluorescence change can also be used to screen the test cells (or cell areas) to obtain a test cell set for determining the target fluorescence change. Specifically: the first fluorescence change is compared with the second preset condition to obtain a second comparison result, wherein the second preset condition is used to screen the response degree of the test cells corresponding to the cell area to the electric field stimulation; when the second comparison result indicates that the first fluorescence change satisfies the second preset condition, the test cells corresponding to the cell area are added to the target cell set; and the target fluorescence change is determined according to the first fluorescence change of the cell area corresponding to the test cells in the target cell set.

[0104] The second preset condition can be set as the amplitude of the first fluorescence change exceeding a preset percentage (such as 5%), or the response intensity of the first fluorescence change is before a preset position (such as the first 1 / 3) among all cells to be tested.

[0105] The target cell set refers to a set of all cells to be tested that meet the second preset condition after screening. The target fluorescence change obtained based on the first fluorescence change data of all cells to be tested (i.e., cell area) in the target cell set is a representative fluorescence intensity change trend, reflecting the most significant response of the entire cell population to the electric field stimulation.

[0106] The above implementation ensures that cells that have a significant response to electric field stimulation are accurately screened out from a large number of cell samples, and then the target fluorescence changes representing the degree of response of these cell populations are calculated, providing more accurate data support for subsequent drug screening and evaluation. In high-throughput drug screening experiments, this method can significantly improve screening efficiency and the reliability of results, avoid misjudgments caused by nonspecific responses or background noise interference, and ensure that cell populations that truly respond to drugs are screened out.

[0107] Step S206, evaluating the candidate drug according to the target fluorescence change to obtain an evaluation result.

[0108] In the above step S206, the effect of the drug on the electrophysiological response of the cell can be evaluated by comparing the target fluorescence change with the fluorescence change of the drug-free control group. For example, the effect of the candidate drug on the electrophysiological response of the cell can be quantified by calculating the difference or ratio between the target fluorescence change amplitude (such as ΔF / F) and the fluorescence change of the control group. One or more quantitative indicators, such as the fluorescence change amplitude, response time, frequency or duration, etc., can also be defined to evaluate the drug effect. For example, an efficacy indicator (such as EC50 or IC50) can be set to calculate the half effective concentration or inhibitory concentration of the drug by fitting the relationship between the drug concentration and the first fluorescence change to evaluate the efficacy or selectivity of the drug.

[0109] In some embodiments of the present application, the drug screening process can also be optimized based on the evaluation results, that is, based on the feedback of the evaluation results, the conditions and parameters of drug screening are optimized to improve the screening efficiency and the reliability of the results. For example, according to the evaluation results, the conditions and parameters of drug screening, such as electric field strength, stimulation frequency, stimulation action time, drug concentration range, etc., are adjusted to optimize the screening process and improve the screening efficiency.

[0110] Through the above steps S202 to S206, electric field stimulation and fluorescent labeling technology are used to evaluate ion channel-related drugs by high-throughput recording of the differences in cell potential changes caused by different drugs under electric field stimulation, thereby achieving the purpose of synchronous electrophysiological detection and optical recording of large-scale cells, thereby achieving the technical effect of reducing the complexity of experimental operations and improving the efficiency of drug screening and evaluation, and further solving the technical problem of low evaluation efficiency due to the limitation of flux in the evaluation of cell electrophysiological characteristics in drug screening methods in related technologies.

[0111] Figure 3 is an overall flow chart of a method for drug evaluation according to an embodiment of the present application, such as Figure 3 As shown, the specific steps include:

[0112] Step 302: Input the raw imaging data (image sequence) of the HEK 293T cell line expressing a genetically-encoded voltage indicator (GEVI) Cepheid1b under 10 field stimulations (frequency 3.28 Hz, stimulation duration 10.18 milliseconds, i.e., duty cycle 3.33%), which records the changes in the cell fluorescence signal (600 frames, sampling rate 196.6 Hz. A total of 3.053 seconds).

[0113] Step 304: Generate an average projection of the original imaging data to identify the cell distribution in the entire field of view, providing a basis for subsequent cell segmentation and signal analysis; enhance the membrane boundary contrast by sharpening and median filtering the average projection to highlight the cell outline, providing a clear image basis for subsequent analysis; use the "cpCyto2" model of Cellpose2 to perform cell segmentation and identify the area of ​​all cells in the field of view.

[0114] Step 3061: Calculate the average fluorescence trace (i.e., the second fluorescence change) of each identified cell region (regions of interest, ROIs), i.e., the change trend of the fluorescence intensity of each cell over time under field stimulation. For example, for each ROI, extract the corresponding time series fluorescence signal from the stored original imaging data; average the fluorescence intensity of all pixels in each ROI in time sequence to obtain a time series representing the change of the average fluorescence intensity of the cell region, i.e., the average fluorescence trace.

[0115] Step 3081: Use an octagonal structural element to expand each cell region outward to 187 microns to form a local background region (i.e., the third region) of each cell for subsequent calculation of background signals.

[0116] Step 3062: Each segmented cell region (ROI) is expanded outward by 16 microns and inverted to obtain a global background region (i.e., the second region), i.e., the region not occupied by cells, for evaluation of the overall background level.

[0117] Step 3082: Calculate the average local background trace (third fluorescence change) of each ROI from the intersection of the corresponding local background area and the global background area (ie, the background area).

[0118] Step 310: The local background trace of each ROI is filtered using a notch filter in the frequency range of 2.5-3.5 Hz, and a self-smoothing window of size 181 frames (equivalent to 0.92 seconds, corresponding to the duration of 3 stimulation cycles) is used for smoothing; the background signal is subtracted from the processed average local background trace to generate a normalized trace.

[0119] Step 312: Perform data analysis and information extraction, including: screening out cell regions with low brightness and small area, excluding these regions that may not contain valid cells or have poor cell status; calculating the average fluorescence change (i.e., target fluorescence change) of each valid cell region during field stimulation to reflect the degree of cell response to electric field stimulation; analyzing the average fluorescence trace (first fluorescence change) of each cell region to extract key information, such as the fluorescence change amplitude of the Ca²+ / voltage indicator to each stimulation pulse, or the spike rate of the cell to the stimulation pulse, etc., for evaluating the effect of the drug or the functional status of the cell.

[0120] Figures 4 to 7 This is a schematic diagram of imaging and analyzing a target area of ​​a drug evaluation method according to an embodiment of the present application, showing the level of fluorescence brightness changes of the fluorescence signals of multiple cells to be tested in the target area with the field stimulation pulse, and selecting the cells with the top 1 / 3 (or more than 5% of the cells) in the field of view (i.e., the target area) in terms of the amplitude of fluorescence signal change, wherein: Figure 4 The original image is shown after average projection (A), edge sharpening to highlight the cell edges (B), and cell segmentation using Cellpose2 (cpCyto2 model) to identify 76 cells (C). After excluding areas that are too small or too low in brightness, 67 qualified cells are obtained (D). Figure 5 The global background area (A) is shown after dilation and negation of 76 cells obtained by cell segmentation in this field of view. For a specific cell obtained by segmentation (B), the intersection of its dilated area and the blue area is its own local background selection area (C). Figure 6 (A) shows Figure 4 (D) The average fluorescence brightness change (normalized fluorescence intensity F) of the marked 67 qualified cells under 10 field stimulations (positions indicated by red dots), and the blue triangles represent the positions of the peaks corresponding to the 10 stimulations identified by the global signal; Figure 6 (B) shows the fluorescence intensity variation of each effective cell ( ), where the grey dotted line and the black dotted line represent the relative change amplitude of fluorescence in all cells at the first 1 / 3 position and the position with a relative change amplitude of 5%, respectively. Figure 7 The distribution of cell regions in the field of view whose fluorescence changes exceeded 5% (A, 53 in total) and whose relative changes ranked in the top 1 / 3 (B, 23 in total) during field stimulation are shown.

[0121] Specifically, in Figure 4In this study, cells were transfected with liposomes to express the membrane potential probe Cepheid1b mutant, which stably expressed Kir2.1 and Na V 1.5-channel HEK 293T cell line, which can synchronously generate global depolarization like cardiomyocyte action potential under field stimulation of 300 V / cm, pulse width of 10.18 milliseconds, and frequency of 3.28 Hz. When the user inputs the average projection of the fluorescence signal change of Cepheid1b mutant recorded at 196.6 Hz during the above process ( Figure 4 (A) ), the system will sharpen it to highlight the cell edges ( Figure 4 (B) ) and 76 cells were segmented using cellpose2 ( Figure 4 (C) ), excluding the areas with too small size and too low brightness as described above, 67 qualified cells were obtained ( Figure 4 (D)). After dilating and negating the 76 cells obtained by the initial segmentation, the global background area can be obtained ( Figure 5 Targeting a specific cell ( Figure 5 (B) The intersection of the expanded area and the blue area is its own local background selection area ( Figure 5 (C)). Then, the fluorescence signal changes obtained from the 67 qualified cell regions obtained above were subtracted from the background using the data of their local background regions, and the average fluorescence signal change of all cells in the field of view was obtained ( Figure 6 (A)) and the average sensitivity distribution of each cell calculated in turn ( Figure 6 (B)). Since the cell regions obtained by cell segmentation may not all be cells that respond to field stimulation, if one wants to evaluate the level of fluorescence brightness change in living cells expressing the mutant, the analysis program can calculate the average fluorescence brightness change of all cells during field stimulation by more than 5% ( Figure 6 (B) The black dotted line indicates the position of 53 cells, corresponding to Figure 7 (A) Each region) or the first 1 / 3 of cells ( Figure 6 (B) The gray dotted line in the right figure shows a total of 53 cells, corresponding to Figure 7 The various areas shown in (B) are used as a representative set of cells (fluorescence change levels) in the field of view to evaluate the level of fluorescence brightness change (i.e., information such as the amplitude and width of membrane potential depolarization) of the cells in the field of view under this scenario.

[0122] The present application also provides a drug evaluation system, comprising: an imaging subsystem, an electrode and a processor, wherein the imaging subsystem comprises a light source and an image acquisition device, the light source is connected to the processor, and is used to provide lighting conditions for electrode stimulation before starting electrode stimulation; the electrode is connected to the processor, and is used to perform electric field stimulation on multiple cells to be tested in a target area cultured with a candidate drug, wherein the multiple cells to be tested have fluorescent markers; the image acquisition device in the imaging subsystem is connected to the processor, and is used to collect raw imaging data corresponding to the target area under electric field stimulation, and send the raw imaging data to the processor; the processor is connected to the imaging subsystem, and is used to receive the raw imaging data, and determine the target fluorescence change corresponding to the multiple cells to be tested from the raw imaging data, wherein the target fluorescence change is used to quantitatively represent the average response degree of the multiple cells to be tested to the electric field stimulation; the candidate drug is evaluated according to the target fluorescence change to obtain an evaluation result.

[0123] By pre-triggering the light source, it is possible to ensure that the target area has stable illumination before the electrode stimulation begins, so that the image acquisition device can clearly record the cell state. For example, before the electrode stimulation begins, the processor controls the light source to preheat it within a preset time to stabilize the light intensity; at the same time, the light intensity is calibrated to ensure the consistency and accuracy of the lighting conditions.

[0124] The processor can set the voltage parameters of electrode stimulation according to experimental requirements, including voltage amplitude, frequency and duration, etc., to stimulate cells to produce electrophysiological responses. In addition, the processor ensures the synchronization of electrode stimulation and image acquisition through synchronous control with the image acquisition device, so as to record the real-time response of cells to stimulation.

[0125] The image acquisition device continuously records images of the target area under electrode stimulation and sends the raw imaging data to the processor for analysis and processing. The processor can set the parameters of the image acquisition device, such as exposure time, readout speed, binning value, etc., to adapt to experimental conditions and ensure image quality. The image acquisition device performs real-time image acquisition under the control of the processor, records the fluorescence changes of cells before and after electrode stimulation, generates raw imaging data, and sends the collected raw imaging data to the processor through the communication interface, which performs subsequent data analysis and storage.

[0126] In some embodiments of the present application, the system also includes a moving device, wherein the moving device includes an electric motor, which is respectively connected to the controller and the electrode, and is used to receive instructions sent by the controller and control the electrode to move in the Z-axis direction of the coordinate axis according to the instructions; the moving device also includes a stage, which is connected to the processor, and is used to carry the target well plate and move the designated area in the target well plate to the target area.

[0127] In the MATLAB environment, the processor sends instructions to the controller, and after the controller interprets the instructions, it drives the electric motor to control the up and down movement of the electrode to achieve precise contact or separation between the electrode and the cell sample. For example, before the electrode is stimulated, the processor sends instructions to the controller to control the electrode to descend to a position close to or in contact with the surface of the cell sample; after the stimulation, the processor sends instructions to lift the electrode, separate from the cell sample, and prepare to move to the next target hole or area.

[0128] In addition, the processor can control the movement of the stage in the X-axis and Y-axis directions by sending instructions to the stage driver, and accurately move the specified area in the target well plate to the center of the field of view of the imaging device, that is, the target area. For example, according to the experimental process and the layout of the target well plate, the processor calls the stage driver through MATLAB to control the movement of the stage, so that each well of the target well plate enters the field of view of the imaging device one by one; after imaging each well, the processor controls the stage to move to the position of the next well, realizing automated well plate traversal and drug evaluation.

[0129] In some embodiments of the present application, the system further includes a stimulation isolator, wherein the stimulation isolator is connected to the electrode, and is used to isolate and amplify the voltage signal emitted by the electrode, and output a pulse voltage to a plurality of cells to be tested.

[0130] The processor outputs the electrical stimulation command signal through the port of the data acquisition card. After the stimulation isolator receives the signal, the internal circuit isolates and amplifies the signal and outputs the set pulse voltage to the electrode. For example, the processor can send a control signal to the stimulation isolator through the data acquisition card driver in the MATLAB environment, triggering the operation of the internal circuit of the stimulation isolator to achieve signal isolation and amplification.

[0131] In some embodiments of the present application, the processor is also used to: segment multiple cells to be tested in the original imaging data to obtain cell regions corresponding to the multiple cells to be tested; determine a first fluorescence change corresponding to each cell region from the original imaging data, wherein the first fluorescence change is used to quantitatively represent the degree of response of the cell region to the electric field stimulation within a preset statistical period under the electric field stimulation; determine the target fluorescence change corresponding to multiple cells to be tested based on the first fluorescence changes corresponding to all the cell regions.

[0132] In some embodiments of the present application, the processor is also used to: determine a second fluorescence change corresponding to each cell region, wherein the second fluorescence change is used to quantify the time-varying trend of the fluorescence intensity in the cell region; determine a background region corresponding to each cell to be tested based on each cell region, and determine a third fluorescence change corresponding to the background region, wherein the third fluorescence change is used to quantify the time-varying trend of the fluorescence intensity in the surrounding area of ​​each cell region; determine the first fluorescence change based on the second fluorescence change and the third fluorescence change.

[0133] It should be noted that the processor in the drug evaluation system can execute Figure 2 The method of drug evaluation shown will not be repeated here.

[0134] In a specific embodiment, the microscope can realize continuous imaging in well plate screening without adding additional media such as water or lens oil, while providing good photon utilization. The camera (image acquisition device) needs to be sampled at a rate of at least about 200 Hz. In order to overcome the effect of the reduction of the camera field of view on the detection flux when imaging at 200 Hz or higher (when imaging at about 200 Hz, the effective maximum field of view occupies half of the middle of the microscope target surface; when the imaging sampling rate increases, the field of view (number of horizontal lines) decreases in proportion, the focal lengths of the tubelens at the excitation end and the emission end of the objective lens with a default tube lens of 200 mm are selected as 125 mm and 150 mm respectively, and the distance between the emission end tube lens and the objective lens and the distance between the camera and the emission end tube lens are adjusted to 150 mm, which can achieve an equivalent magnification of 15x, so as to complete the simultaneous recording of hundreds of positive cells at a sampling rate of about 200 Hz. Between the tube lens at the imaging end and the camera, an electric filter wheel (filter wheel) with a fluorescent filter can also be installed. Wheel) to filter light, support high-speed and stable switching between fluorescence filters, multi-color time-lapse imaging (such as simultaneous recording of calcium signals and membrane potential fluorescence signals) and ratiometric imaging (such as a variety of commercial calcium dyes). In this application, the configuration shown in Table 1 can be used to set the light source, dichroic mirror and fluorescence filter selected when imaging the fluorescent chromophore (fluorescent marker):

[0135] Table 1: Dichroic mirror / fluorescence filter set table.

[0136]

[0137] In the present application, the field stimulation electrode used can be a platinum electrode made by 3D printing, the distance between the two electrodes can be set as needed, and it is fixed to the x-axis and y-axis direction adjustment bracket for fine adjustment of the position in the x-axis and y-axis directions, and the bracket is installed on the electric motor, and the up and down (z-axis direction) displacement of the field stimulation electrode is controlled by the controller. In actual work, the height of the z-axis can be controlled by the official driver of the controller through the MATLAB environment, and the position in the x-axis and y-axis directions can be adjusted manually by the user or controlled by the processor. In addition, the electrode used for stimulation also outputs a pulse voltage through the stimulation isolator to induce the membrane potential depolarization of the cell sample to be tested, which can be controlled by the digital acquisition card inside the device computer to trigger the voltage pulse command to control the output. For example, the maximum output voltage can be 100V, and the maximum effective field strength that can be achieved between the electrodes is about 333 V / cm. It should be noted that before triggering the camera to start recording, the illumination light can be turned on for about 1s to eliminate possible light intensity instability, and the illumination light output can be turned off after the stimulation to reduce photobleaching.

[0138] Figure 8 is an operation flow chart of a drug evaluation system according to an embodiment of the present application, such as Figure 8 As shown,

[0139] Step 802: Initialize and connect the hardware in the MATLAB environment, including: camera, stage, LED or laser light source, Z-axis motorized stage, and position for loading fluorescent filters. Move the stage to well A1 of the 96-well plate (as an example), and reset the position (x, y) of the stage to (0, 0).

[0140] Step 804: Start diagonal traversal of the stage from hole A1, or move the stage to a specific hole of interest for imaging.

[0141] Step 806: The user determines whether to stimulate after judging the cell status and the brightness of the fluorescent probe in the current well. If yes, lower the electrode and execute step 808; if no, skip stimulation and execute step 812.

[0142] Step 808: Perform electric field stimulation and synchronous imaging, including: lowering the electrode to a position above the cell; starting light source illumination; performing electric field stimulation and 196.6 Hz synchronous fluorescence imaging; turning off the light source and checking the average time trajectory of the region of interest (ROI); writing the movie data to the hard disk, and raising the electrode to a default height.

[0143] Step 810: Move the stage to the next region of interest (ROI) in the hole and repeat step 808 or directly execute step 812.

[0144] Step 812: Move the stage to the next adjacent hole.

[0145] Fig. 9 is a schematic diagram of system operation speed analysis of a drug evaluation according to an embodiment of the present application, such as Fig. 9 As shown, the average speed of data acquisition, storage and analysis of this system is shown, among which, Fig. 9 (A) The time required to complete a total of 4.68 seconds of field stimulation commands using a maximum imaging field of view of 200 Hz, store the resulting 720 frames of data into memory, and generate a global average fluorescence signal change curve. The data comes from the timing results of 206 consecutive acquisition commands; Fig. 9 (B) Fig. 9 (A) The time taken to transfer the data obtained by 206 consecutive acquisition commands from the memory to the hard disk (bin format video file (737 MB) and mat format parameter file (about 3 MB)); Fig. 9 (C) Mean time required for analyzing each field of view when analyzing 50 consecutive screening videos of 200 Hz field stimulation using a laboratory workstation with 64 GB of memory (green line) and a regular laptop with 16 GB of memory (blue line). Error bars represent the standard deviation of five analyses of the same field of view.

[0146] Fig. 9 (A) and Fig. 9 (B) shows the time required for each data acquisition and writing to memory (i.e., MATLAB workspace variables, and the "global average trace" of the average signal intensity change of the entire field of view) during 206 consecutive standard field stimulation synchronous imaging processes, and the time required for writing the imaging raw data in memory and the relevant parameters during acquisition (including the number of rows and columns of the camera, bin value, exposure time, and stage coordinates, etc.) from memory to the hard disk. Specifically, the time required to complete the acquisition command and input the data into the memory during the 206 acquisition processes was 7.20 ± 0.10 seconds (mean ± standard deviation, the same below), and the time required to write the data to the hard disk was 0.33 ± 0.05 seconds. These data prove that the data acquisition and storage time is short and stable. Fig. 9 (C) shows the time taken by the automatic data analysis program to continuously process 50 cells in different fields of view and repeat this process 5 times. When a workstation with 64 GB of memory and a personal laptop with 16 GB of memory were used for simulation, it can be found that even with the laptop, the slowest field of view analyzed will not exceed 1 minute. If a workstation is used, most fields of view generally take 20-40 seconds to complete (the more independent cells segmented and identified in the field of view, the slower the processing speed). This shows that the automatic analysis and processing program demonstrates a high data processing speed and program operation stability.

[0147] Fig.10 is a structural diagram of a drug evaluation device according to an embodiment of the present application, such as Fig.10 As shown, the device comprises:

[0148] An acquisition module 1002 is used to acquire raw imaging data corresponding to a target area under electric field stimulation, wherein the target area includes a plurality of cells to be tested cultured with a candidate drug, and the plurality of cells to be tested are fluorescently labeled;

[0149] A determination module 1004 is used to determine the target fluorescence change corresponding to the multiple cells to be tested from the original imaging data, wherein the target fluorescence change is used to quantitatively represent the average response degree of the multiple cells to be tested to the electric field stimulation;

[0150] The evaluation module 1006 is used to evaluate the candidate drug according to the target fluorescence change to obtain an evaluation result.

[0151] It should be noted that Fig.10 The drug evaluation apparatus shown is used to perform Figure 2 The method of drug evaluation shown here is therefore Figure 2 The relevant explanations in the methods for drug evaluation in Fig.10 The device for drug evaluation shown will not be described in detail here.

[0152] An embodiment of the present application further provides a non-volatile storage medium, which includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the steps of the drug evaluation method in each embodiment of the present application by running the computer program.

[0153] An embodiment of the present application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the steps of the drug evaluation method in each embodiment of the present application.

[0154] The embodiments of the present application also provide a computer program, which, when executed by a processor, implements the steps of the drug evaluation method in each embodiment of the present application.

[0155] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0156] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0157] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0158] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0159] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0160] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc., which can store program code.

[0161] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for drug evaluation, characterized in that: include: Acquiring original imaging data corresponding to a target area under electric field stimulation, wherein the target area includes a plurality of cells to be tested cultured with a candidate drug, and the plurality of cells to be tested are fluorescently labeled; Determine the target fluorescence change corresponding to the multiple cells to be tested from the original imaging data, wherein the target fluorescence change is used to quantitatively represent the average change degree of the membrane potential of the multiple cells to be tested under the electric field stimulation; The candidate drug is evaluated according to the target fluorescence change to obtain an evaluation result.

2. The method according to claim 1, characterized in that Determining the target fluorescence change corresponding to the plurality of cells to be tested from the original imaging data includes: Segmenting the multiple cells to be tested in the original imaging data to obtain cell regions corresponding to the multiple cells to be tested; Determining a first fluorescence change corresponding to each of the cell regions from the raw imaging data, wherein the first fluorescence change is used to quantitatively represent the degree of response of the cell region to the electric field stimulation within a preset statistical period under the electric field stimulation; The target fluorescence change commonly corresponding to the plurality of cells to be tested is determined according to the first fluorescence changes respectively corresponding to all the cell regions.

3. The method according to claim 2, characterized in that Determining a first fluorescence change corresponding to each of the cell regions from the raw imaging data includes: Determining a second fluorescence change corresponding to each of the cell regions, wherein the second fluorescence change is used to quantitatively represent a trend of fluorescence intensity within the cell region over time; Determine the background area corresponding to each of the cells to be tested based on each of the cell areas, and determine the third fluorescence change corresponding to each of the background areas, wherein the third fluorescence change is used to quantitatively represent the time-dependent change trend of the fluorescence intensity of the surrounding area of ​​each of the cell areas; The first fluorescence change is determined according to the second fluorescence change and the third fluorescence change.

4. The method according to claim 3, characterized in that Determining the background area corresponding to each of the cells to be tested based on each of the cell areas includes: Expand each of the cell regions outward by a first number of pixels to obtain a first region corresponding to each of the cell regions; Determine an area in the original imaging data other than all the first areas as a second area; On the basis of the second area, each of the cell areas is expanded outward by a second number of pixels to obtain a third area corresponding to each of the cell areas, wherein the first number is smaller than the second number; An intersection of the second area and the third area is determined as the background area.

5. The method according to claim 2, characterized in that: The original imaging data includes multiple frames of imaging data, and segmenting the multiple cells to be detected in the original imaging data includes: Performing statistical averaging on the fluorescence intensity at each time point within the preset statistical period in the multiple frames of imaging data to obtain a mean value projection corresponding to the original imaging data, wherein the mean value projection is an image formed after performing the statistical averaging; The multiple cells to be tested in the average projection are segmented.

6. The method according to claim 2, characterized in that After obtaining the cell region corresponding to each of the cells to be tested, the method further includes: Comparing the attribute information of the cell region with a first preset condition to obtain a first comparison result, wherein the first preset condition is used to screen the size and / or brightness of the cell region; When the first comparison result indicates that the attribute information does not satisfy the first preset condition, the cell region is determined to be an invalid region.

7. The method according to claim 2, characterized in that Determining the target fluorescence change commonly corresponding to the plurality of cells to be tested according to the first fluorescence changes respectively corresponding to all the cell regions comprises: Comparing the first fluorescence change with a second preset condition to obtain a second comparison result, wherein the second preset condition is used to screen the response degree of the cells to be tested corresponding to the cell region to the electric field stimulation; When the second comparison result indicates that the first fluorescence change satisfies the second preset condition, adding the cells to be tested corresponding to the cell area to the target cell set; The target fluorescence change is determined according to a first fluorescence change of a cell region corresponding to the cells to be detected in the target cell set.

8. The method according to claim 1, characterized in that Obtain the original imaging data corresponding to the target area under electric field stimulation, including: Moving a stage for carrying the plurality of cells to be tested to a first position corresponding to the target area, wherein the first position is located above the objective lens of a microscope; Lowering the electrode to a second position, wherein the electrode contacts the upper surfaces of the plurality of cells to be tested at the second position; Under the illumination of the light source, using the electrodes to perform electric field stimulation on the plurality of cells to be tested; The original imaging data corresponding to the plurality of cells to be tested acquired by an image acquisition device under the stimulation of the electric field are acquired.

9. The method according to claim 8, characterized in that The plurality of cells to be tested are located in any one of the wells in the target well plate, and a stage for carrying the plurality of cells to be tested is moved to a first position corresponding to the target area, comprising: Receiving a selection instruction of a target object, wherein the selection instruction includes any hole number corresponding to the target well plate; Acquire the size parameters of the target orifice plate, wherein the size parameters include the hole center distance between two adjacent holes; Determine the third position corresponding to the stage as the coordinate origin, and determine the coordinate information corresponding to the hole number according to the hole center distance; On the basis of the third position, the area corresponding to the hole number is moved to the first position according to the coordinate information.

10. The method according to claim 8, characterized in that Before moving the stage for carrying the plurality of cells to be tested to a first position corresponding to the target area, the method further includes: Comparing a fourth position corresponding to the electrode with a third preset condition to obtain a third comparison result, wherein the third preset condition is used to detect whether the electrode meets the movement requirement; When the third comparison result indicates that the fourth position does not satisfy the third preset condition, the electrode is raised from the fourth position to a fifth position so that the electrode is out of contact with the multiple cells to be tested, wherein the vertical distance between the fifth position and the second position satisfies a preset threshold.

11. The method according to claim 9, characterized in that At least one well of the target well plate contains a plurality of cells to be tested cultured with a candidate drug, and each well corresponds to at least one candidate drug, wherein the target well plate comprises a 24-well plate and / or a 96-well plate and / or a 384-well plate.

12. A drug evaluation system, characterized in that: include: An imaging subsystem, electrodes, and a processor, wherein: The imaging subsystem includes a light source and an image acquisition device, wherein the light source is connected to the processor and is used to provide lighting conditions for the electrode stimulation before starting the electrode stimulation; The electrode is connected to the processor and is used to perform electric field stimulation on a plurality of cells to be tested in a target area cultured with a candidate drug, wherein the plurality of cells to be tested are fluorescently labeled; The image acquisition device in the imaging subsystem is connected to the processor and is used to acquire raw imaging data corresponding to the target area under the electric field stimulation and send the raw imaging data to the processor; The processor is connected to the imaging subsystem, and is used to receive the raw imaging data, and determine the target fluorescence change corresponding to the multiple cells to be tested from the raw imaging data, wherein the target fluorescence change is used to quantify the average degree of change of the membrane potential of the multiple cells to be tested under the electric field stimulation; the candidate drug is evaluated according to the target fluorescence change to obtain an evaluation result.

13. The system according to claim 12, characterized in that The system further comprises a mobile device, wherein: The moving device includes an electric motor, which is connected to the controller and the electrode respectively, and is used to receive instructions sent by the controller and control the electrode to move in the Z-axis direction of the coordinate axis according to the instructions; The moving device further comprises a stage, which is connected to the processor and is used for carrying the target well plate and moving the designated area in the target well plate to the target area.

14. The system according to claim 12, characterized in that The system further comprises a stimulation isolator, wherein the stimulation isolator is connected to the electrode, and is used to isolate and amplify the voltage signal emitted by the electrode, and output a pulse voltage to the plurality of cells to be tested.

15. The system according to claim 12, characterized in that The processor is further configured to: Segmenting the multiple cells to be tested in the original imaging data to obtain cell regions corresponding to the multiple cells to be tested; Determining a first fluorescence change corresponding to each of the cell regions from the raw imaging data, wherein the first fluorescence change is used to quantitatively represent the degree of response of the cell region to the electric field stimulation within a preset statistical period under the electric field stimulation; The target fluorescence change commonly corresponding to the plurality of cells to be tested is determined according to the first fluorescence changes respectively corresponding to all the cell regions.

16. The system according to claim 15, characterized in that The processor is further configured to: Determining a second fluorescence change corresponding to each of the cell regions, wherein the second fluorescence change is used to quantitatively represent a trend of fluorescence intensity within the cell region over time; Determine the background area corresponding to each of the cells to be tested based on each of the cell areas, and determine the third fluorescence change corresponding to the background area, wherein the third fluorescence change is used to quantitatively represent the time-dependent change trend of the fluorescence intensity of the surrounding area of ​​each of the cell areas; The first fluorescence change is determined according to the second fluorescence change and the third fluorescence change.

17. A drug evaluation device, characterized in that: include: An acquisition module, used for acquiring raw imaging data corresponding to a target area under electric field stimulation, wherein the target area includes a plurality of cells to be tested cultured with a candidate drug, and the plurality of cells to be tested are fluorescently labeled; A determination module, used to determine the target fluorescence change commonly corresponding to the multiple cells to be tested from the original imaging data, wherein the target fluorescence change is used to quantitatively represent the average degree of change of the membrane potential of the multiple cells to be tested under the electric field stimulation; An evaluation module is used to evaluate the candidate drug according to the target fluorescence change to obtain an evaluation result.

18. A non-volatile storage medium, characterized in that: The non-volatile storage medium includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the method for drug evaluation according to any one of claims 1 to 11 by running the computer program.

19. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by a processor, the method for drug evaluation according to any one of claims 1 to 11 is implemented.

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