Myocardial cell fusion automatic arrangement method based on micro-channel

Abstract

The invention provides a myocardial cell fusion automatic arrangement method based on a micro-channel, which comprises the following steps: initializing an operation visual field, and placing the micro-channel, myocardial cells and a microtube orifice in the same visual field; based on the current visual field image, myocardial cell detection and micro-channel and micro-tube orifice identification are carried out on the visual field image shot by the camera by using an image processing technology, and myocardial cells are numbered; determining the initial positions of myocardial cells and microtubule orifices and the target position of the microtubule orifice when the myocardial cells are moved and discharged to the microchannel, and planning the moving path of the microtubule; in order to control the position of the myocardial cells in the liquid which is sucked into or discharged out of the microtubule along with the microtubule, a sliding mode surface is constructed according to a myocardial cell movement model, and a sliding mode active-disturbance-rejection controller is designed to control a stepping motor in the process of transferring the myocardial cells by the microtubule; and according to the numbers of the myocardial cells, moving the myocardial cells in the visual field through the microtubes according to a planned path and discharging the myocardial cells into the micro-channels to finish automatic arrangement.

Description

Technical Field

[0001] The present invention relates to the field of cell-level micromanipulation, and in particular to a micro-channel-based automated arrangement method for myocardial cell fusion. Background Art

[0002] The specific arrangement and fusion of cardiomyocytes in microchannels are of great significance for studying the communication between cardiomyocytes and constructing myocardial tissue engineering. This process requires the precise capture of batches of cells without compromising cell activity and the ability to manipulate the cells to arrange in microchannels. Traditional cell transport operations mainly rely on manual operations by professionals and have high technical requirements, requiring precise manipulation skills and rich experience. Therefore, in order to improve this process, scientists are constantly exploring new technologies and methods. For example, Z. Zou et al. [Zou Z, Lee S, Ahn C HA polymer microfluidic chip with interdigitated electrodes arrays for simultaneous dielectrophoretic manipulation and impedimetric detection of microparticles [J]. IEEE Sensors Journal, 2008, 8(5): 527-535.] manufactured a high-throughput polymer microfluidic biochip and used dielectrophoresis technology to separate and manipulate microparticles in the chip. However, using this method to achieve precise cell arrangement in microchannels is difficult in microchannel network design. G. Gibson et al. [Gibson G, Carberry DM, Whyte G, et al. Holographic assembly workstation for optical manipulation [J]. Journal of Optics A: Pure and Applied Optics, 2008, 10 (4): 044009-044009.] have used optical tweezers to fix and arrange cells. However, the intensity of the optical tweezers needs to be precisely controlled to avoid potential damage to the cells caused by excessive intensity. Z. Lu et al. [Lu Z, Moraes C, Ye G, et al. Single cell deposition and patterning with a robotic system [J]. PloS One, 2010, 5 (10): e13542] developed a cell sorting system based on visual feedback, which uses a micropipette smaller than the cell diameter for cell manipulation. However, since this operation does not completely suck the entire cell into the micropipette, it may cause cell deformation during cell holding or get stuck in the micropipette hole when releasing the cell, causing release failure. Therefore, for the operation process of directional arrangement of cardiomyocytes in microchannels, it is necessary to develop a technology that can achieve precise cell capture and arrangement without damaging cell activity. Summary of the Invention

[0003] In response to the deficiencies of the existing technology, the present invention provides a microchannel-based automated arrangement method for myocardial cell fusion, which is used to achieve precise arrangement and fusion of myocardial cells in microchannels and is suitable for myocardial tissue engineering construction and intercellular communication research.

[0004] The present invention achieves this object through the following technical solutions:

[0005] A method for automated arrangement of myocardial cell fusion based on microchannels, the method comprising the following steps:

[0006] a. Place the culture dish containing the microchannel substrate and cardiomyocyte suspension on the motorized stage of the micromanipulator. The motorized micromanipulator arm controls the position of the micropipette, which is held by a needle holder. The inner diameter of the micropipette should be no smaller than the diameter of the cardiomyocyte. Initialize the operating field of view, aligning the microchannel, cardiomyocytes, and micropipette opening.

[0007] b. Based on the current field of view image, use image processing technology to detect myocardial cells and identify microchannels and microtubule openings in the field of view image captured by a high-speed industrial camera, and number the myocardial cells;

[0008] c. Determine the initial positions of the myocardial cell and the microtubule orifice, as well as the target position of the microtubule orifice when the corresponding myocardial cell moves through the microtubule and is discharged into the microchannel. Plan the path from the initial position of the microtubule orifice to the initial position of the myocardial cell, and from the microtubule orifice after the myocardial cell is drawn in to the target position of the microtubule orifice when the myocardial cell is discharged into the microchannel. Based on the planned path, set the control law for controlling the movement of the motorized stage or the motorized micromanipulator holding the microtubule.

[0009] d. The microtubule is connected to a pneumatic syringe via a catheter. A stepper motor connected to the pneumatic syringe's lead screw is controlled to control the position of the cardiomyocytes within the fluid drawn into or expelled from the microtubule. A sliding surface is constructed based on the cardiomyocyte movement model, and a sliding mode active disturbance rejection controller is designed to control the stepper motor during microtubule transfer of the cardiomyocytes.

[0010] e. According to the cardiomyocyte number, the cardiomyocytes in the field of view are arranged in sequence along the planned path by moving the microtube to the target position and placing the cardiomyocytes into the microchannel to complete the automated arrangement.

[0011] Furthermore, the specific operation in step a is, in the initial state, adjusting the position of the manually controlled robotic arm and the stage so that the microchannel is vertical and located on one side of the field of view, the microtubule is horizontal and located on the other side of the field of view with the microtubule opening facing the direction of the microchannel, and adjusting the focal plane to the cell plane.

[0012] Furthermore, in step b, a target area point boundary tracking method based on a binary image is used to detect cell contours and extract cell center points. The specific steps are: binarize the grayscale image of the current field of view; traverse the image pixels and calculate the standard deviation of the pixels in the 3×3 neighborhood of each pixel point. When the standard deviation is greater than 0.3, it is considered to be a cell area, and the pixel value of the corresponding pixel point is set to 255, and the values ​​of the remaining pixels are all set to 0; perform morphological operations such as closing and opening operations on the image; detect contours and count them; extract contours in the image and calculate the contour area. When the contour area is between 10-30 μm, the corresponding contour is considered to be a cell contour, and the center point of the least squares fitted ellipse is the cell center point, and half the width of the rectangle circumscribing the cell contour is the cell radius; sort the cells detected in the field of view; and record the information of each cell after the sorting is completed.

[0013] Furthermore, the cardiomyocytes detected in the field of view are sorted in the groove in the vertical order from bottom to top. If there are two adjacent cardiomyocytes whose vertical distance is less than the microtubule width, the cardiomyocytes close to the microgroove are selected in the front and the cardiomyocytes far from the microgroove are sorted in the back. The information of each cell after the sorting is completed is recorded.

[0014] Furthermore, in step b, a line detection algorithm based on Hough transform is used to identify the position of microchannels. The specific steps are as follows: edge detection is performed on the grayscale image of the current field of view to obtain an edge image; straight lines are detected using probabilistic Hough transform and the slopes of the straight lines are calculated; the detected straight lines are screened and the average slope of the two contour lines of the detected microchannels is calculated as the slope of the microchannels in the field of view; the target positions of all myocardial cells to be arranged are calculated based on the starting point of the target position of myocardial cell arrangement and the slope of the microchannel.

[0015] Furthermore, the target position of the microtubule orifice in step c is planned as follows: the bottom endpoint of the identified microchannel contour line close to the center of the field of view is used as a reference, and the numbered myocardial cells are arranged in order from bottom to top so that the center points of the myocardial cells are located on the microchannel contour line. The coordinates of the center points of each myocardial cell on the contour line are used as the target position of the coordinates of the center position of the outermost diameter contour line of the microtubule orifice after the myocardial cells are absorbed.

[0016] Furthermore, the automatic control method described in step d is specifically a sliding mode auto-disturbance rejection control based on an expansion state observer to maintain the myocardial cells at the microtubule orifice. Considering the interaction between the motor, air pressure, fluid, and myocardial cells, the myocardial cells are taken as the control target, and a dynamic model of the myocardial cells is established as follows:

[0017]

[0018] Where x1 is the cell position, x2 is the cell movement speed, u is the motor speed, i.e., the system control input, A1 is the syringe cross-sectional area, A2 is the microtube cross-sectional area, P0 is the initial cavity pressure of the system pneumatic syringe, V0 is the initial gas volume when the system syringe piston does not move, m is the mass of the cell, r is the radius of the cell, and μ is the dynamic viscosity coefficient. represents the instantaneous rate of change of the pressure in the enclosed air cavity, and the disturbance term f(·) is the concentrated uncertainty, which includes the uncertainty of the model parameters, unmodeled dynamics, the hysteresis effect of the enclosed air pressure, and other disturbances.

[0019] Let θ1 = 6πμr / m, θ2 = V0 / P0A2, b = A1 / A2, the second formula of the above equation can be written as:

[0020]

[0021] Let b0 = bθ1, The above formula can be written as:

[0022]

[0023] At this time, the system control model can be written as follows, where F represents the total disturbance of the system and h represents the differential of the total disturbance:

[0024]

[0025] in It represents the differential of the total disturbance F of the system, that is, the rate of change of the disturbance over time;

[0026] A linear extended state observer based on a second-order system is used to estimate the state variables, where x=[x1,x2,x3] T Estimated value of:

[0027]

[0028] Among them, β1, β2, and β3 are observer gain parameters;

[0029] The characteristic polynomial of the observer is:

[0030] λ(s)=s 3 +β1s 2 +β2s+β3

[0031] Define β1=3w0,β2=3w0 2 , β3=w0 3 , then the above characteristic polynomial is equal to (s+w0) 3 , the pole is configured at -w0, w0 is the bandwidth parameter of the extended state observer;

[0032] In this control system, x1 represents the actual position of the cell, x d represents the expected trajectory of the cell, and the position error is defined as:

[0033] e=x1-x d

[0034] The state estimation error is defined as:

[0035]

[0036] The sliding surface is defined as follows:

[0037]

[0038] For the above sliding surface, a sliding mode active disturbance rejection controller is designed to make the tracking error of the cell position converge to zero:

[0039]

[0040] where k p is the control gain, η is the switching gain, β1 and β2 are the observer gains, sat(σ) is the saturation function, β represents the boundary layer thickness, and β>0.

[0041] Furthermore, the specific control method steps for controlling the positioning of cardiomyocytes in microtubules are as follows:

[0042] Step S1: Perform microtubule detection: extract the microtubule orifice template, magnify the area where it is located as the region of interest for tracking, and set it as the background image B1(x,y);

[0043] Step S2: Get the current frame field of view image F(x,y) and set the target image X N The (x, y) pixels are all 0, and the current frame image is subtracted from the background image within the ROI. The result is thresholded and assigned to the target image to identify the position of the current moving object. Before the next frame arrives, the background is updated to improve robustness. The background update method is as follows:

[0044] B N+1 (x,y)=αF(x,y)+(1-α)B N (x,y),0≤α≤1

[0045] Where α is the background update weight;

[0046] The subtraction operation is as follows:

[0047]

[0048] Where T is the subtraction operation threshold;

[0049] Step S3: Calculate the current position and expected position of the cell P c If the error is less than a certain threshold, the control is exited. Otherwise, the output of the positioning controller in the microtube is calculated and the output signal is transmitted to the motor to control the target to move.

[0050] Step S4: Update the error information, enter the next frame, and return to step S2.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] This invention implements an automated microchannel-based cardiomyocyte fusion alignment method. First, using image processing, key positioning techniques for cell detection and microchannel identification are addressed. Second, automated control techniques are employed to address key control techniques for stage control and cell positioning within microtubes. Finally, a microchannel-based automated cardiomyocyte alignment process is designed, enabling automated alignment and fusion of cardiomyocytes within microchannels. The invention employs a micropipette larger than the cell diameter to manipulate cells, preventing damage caused by cell deformation during capture. The invention provides key techniques for cell detection and microchannel identification, as well as stage control and cell positioning within microtubes, enabling automated alignment and fusion of cardiomyocytes within microchannels. This method achieves precise cell capture while avoiding damage caused by cell deformation during capture, enabling precise control of cell alignment within microchannels, and achieving oriented alignment and fusion of cardiomyocytes within microchannels. This automated method can be used in other somatic cell alignment and fusion experiments, as well as in automated and precise construction of myocardial tissue engineering and research on intercellular communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a flow chart of the method of the present invention;

[0054] Figure 2 It is a micromanipulation system used in microchannel-based myocardial cell automated arrangement and fusion experiments;

[0055] Figure 3 It is a diagram of the cell detection process of the present invention;

[0056] Figure 4 It is a diagram of the microchannel identification process of the present invention;

[0057] Figure 5 is a diagram of the motion control results of the stage;

[0058] Figure 6 It is a graphic representation of the results of cellular positioning control within microtubules;

[0059] Figure 7 It is a flowchart of cardiomyocyte arrangement based on microchannels;

[0060] Figure 8 This is a diagram showing the arrangement and fusion of myocardial cells. DETAILED DESCRIPTION

[0061] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present invention and the features within the embodiments may be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0062] See Figures 1 to 8 The present invention discloses an embodiment of a method for automated arrangement of cardiomyocyte fusion based on microchannels. This embodiment uses this method to evaluate the arrangement and fusion of cardiomyocytes in microchannels.

[0063] The process of the micro-channel-based myocardial cell fusion automated arrangement method of the present invention is as follows: Figure 1 shown.

[0064] The cells used in this example are primary cardiomyocytes extracted from SD rats at 1-3 days old. The cardiomyocytes were obtained as follows:

[0065] SD puppies were ordered from the Animal Experiment Center. The puppies were anesthetized by immersion in 75% alcohol. With the left hand, hold the large forceps to pinch the skin on the back of the puppies' neck to fully expose the chest. With the right hand, take a pair of ophthalmic curved scissors to cut the skin, cut the ribs upward along the lower left edge of the sternum, and then cut the sternum horizontally in the middle of the incision. Then, hold the ophthalmic straight forceps with the left hand and the ophthalmic straight scissors with the right hand, gently push the chest cavity, and the puppies' heart will jump out. Clamp the heart with the ophthalmic straight forceps, and use the ophthalmic straight scissors to cut the ventricle part directly from the middle of the heart and place it in the ice-bathed D-Hank's solution. Repeat the above process until the sample is collected. Use a pair of ophthalmic straight forceps in each hand to remove the blood clots and fibrous tissue around the heart in the culture dish, place it in a new ice-bathed D-Hank's solution, and wash it again. After washing, remove the D-Hank's solution and use ophthalmic straight scissors to cut the heart tissue into pieces of about 1mm. 3Add 4 ml of trypsin (0.25%) to the heart mud, transfer it and the mud together to a 15 ml centrifuge tube, and add trypsin to 5 ml. Place the centrifuge tube in a 37°C water bath, shake for 5 minutes, and then let it stand for 5 minutes. After standing, use a pipette to carefully aspirate the supernatant in the tube and place it in a new centrifuge tube. Add an equal amount of complete culture medium to the new centrifuge tube to stop digestion, and add the aspirated trypsin to 5 ml in the centrifuge tube containing the heart mud. Repeat the above steps of shaking, standing and aspirating the supernatant 7-8 times until the heart mud is observed to be digested. After digestion is complete, discard the supernatant obtained from the first digestion, pool all the supernatants into a 50 ml centrifuge tube, and place it in a centrifuge at 1000 rpm for 6 minutes. Discard the supernatant, resuspend the cells with 10 ml of complete culture medium containing 20% ​​serum, filter the cell suspension with a 20 μm cell strainer, and obtain a cell suspension containing cardiomyocytes, fibroblasts and endothelial cells. Inoculate it into a 75 cm 2 The cells were placed in a plastic culture flask and cultured in an incubator at 37°C and 5% CO2 for 2 hours. The adherent cells were discarded and the non-adherent cell suspension was removed. The cells were repeatedly aspirated with a pipette to evenly mix the cells in the culture medium to obtain a cardiomyocyte suspension for cell arrangement.

[0066] The micromanipulation system used Figure 2 The NK-MR901 micromanipulation system shown in Figure 1 is based on a standard inverted microscope (Eclipse TI-E, Nikon, Japan) and is equipped with a high-speed industrial camera (aca640-120gm / gc, Basler, Germany) to acquire microscopic grayscale images with a resolution of 640 × 480 pixels and a frame rate of 50 frames / s. In addition, the system also includes a motorized stage (ProScan III, Prior, UK) for placing the culture dish; two three-degree-of-freedom motorized micromanipulator arms (MP285, Sutter, USA) for controlling the position of the micropipette; a needle holder (HI-7, Narishige, Japan) for clamping the micropipette; a pneumatic syringe (Narishige, IM-11B, Japan) connected to the micropipette through a catheter; a stepper motor (Sanyo, 103H546-0410, Japan) connected to the pneumatic syringe lead screw through a coupling; a syringe motor controller (Vince, VSMD101_025T, China) to drive the stepper motor; and an industrial computer connected to the computer and multiple devices on the workbench for motion control and processing of microscopic images.

[0067] During the experiment, the inner diameter of the microtube used was 20μm, and the microchannel was a groove 20μm wide and 20μm deep on a polydimethylsiloxane base plate. The cells used were suspended cardiomyocytes that had just been digested and extracted from the heart of a suckling mouse, with a diameter of about 10-20μm. The experiment used the right manipulator to move the microtube, and the movement of the cells and microchannel was controlled by the movement of the stage. Before the experiment, image detection was first performed to detect the microtubes, cells, and microchannels separately to obtain position information. The transportation of cells and microchannels was then completed through stage control, and the picking and placement of cells was completed through cell positioning control in the microtubes. The cells were operated in a cycle until the arrangement of the predetermined number of cells was completed.

[0068] The present invention will be further described below with reference to the accompanying drawings. The specific implementation of the method provided by the present invention is as follows:

[0069] Initialize the field of view. Initially, manually move the robotic arm and stage to the appropriate position, positioning the microtubule in the lower right portion of the field of view, roughly horizontally, with multiple cells in the field of view, and the microchannel in the left half of the field of view, roughly vertically. Adjust the focal plane to the plane of the cells.

[0070] Second, based on the current field of view image, image processing technology is used to detect the location of myocardial cells and microchannels.

[0071] Image processing technology is used to detect cells and microchannels. For the detection and sorting of cardiomyocytes, the target area point boundary tracking method based on binary images is considered to detect the cell boundaries and extract the cell contours. The implementation process is as follows:

[0072] Step S1: Binarize the grayscale image of the current field of view. Traverse the image pixels and calculate the standard deviation of the pixels in the 3×3 neighborhood of each pixel. If the calculated standard deviation is greater than 0.3, it is considered to be a cell area. The pixel value of the corresponding pixel is set to 255, and the values ​​of the remaining pixels are set to 0.

[0073] Step S2: Perform morphological operations of closing and opening on the image.

[0074] Step S3: Detect and count contours. Contours were extracted from the image and their areas were calculated. If the contour area was between 10 and 30 μm, the corresponding contour was considered the cell contour. The center of the least squares fitted ellipse was taken as the cell center, and half the width of the rectangle circumscribing the cell contour was taken as the cell radius.

[0075] Step S4: Sort the cells detected in the field of view. To prevent collisions between microtubules and unsorted cells during stage movement, sort the cells in y-coordinate order from bottom to top. If the y-distance between two adjacent cells is less than the microtubule width, the cardiomyocyte closest to the microchannel is ranked first. Record the information of each cell after sorting.

[0076] 2.2 The implementation process of micro-channel recognition in the current field of view image and calculation of the target position of cell arrangement is as follows:

[0077] Step S1: Perform edge detection on the grayscale image of the current field of view to obtain an edge image.

[0078] Step S2: Detect the straight line using the probabilistic Hough transform and calculate the slope of the straight line.

[0079] Step S3: Screen the detected straight lines. To simplify subsequent operations, set the slope of the vertical line to 0 and remove the straight lines with an absolute value of the slope less than 1.

[0080] Step S4: Calculate the average slope of the remaining lines and use this as the slope of the microchannel in the field of view. If there is a line with a slope of 0, the microchannel slope is also set to 0. The lower endpoint of the rightmost line among the remaining lines is selected as the point of the lower right corner of the microchannel, i.e., the starting point of the target cell arrangement position.

[0081] Step S5: Based on the target starting point and the microchannel slope, calculate the target positions of all cells to be arranged, that is, the arrival positions of the microtubule orifices to transport cells, in the order of y-direction coordinates from bottom to top. i is the i-th target point, l is p i The distance between the lower end point of the straight line along the right side of the microchannel in the field of view, k is the slope of the microchannel.

[0082]

[0083] p ix =p 0x , p iy =p 0y -il, k=0

[0084] p ix and p iy For p i The horizontal and vertical coordinates of the point, p 0x and p 0y The coordinates of the lower endpoint of the groove along the contour line on the right side of the microchannel serve as the reference point for the target position of cell arrangement.

[0085] Based on the current field of view image, the position of the myocardial cells in the field of view is detected and obtained using the target area point tracking boundary tracking method based on binary image. Figure 3 The results of cell detection were shown. Figure 3 (a) Original image of the cell, Figure 3 (b) is the image after the original image is binarized and morphologically operated. Figure 3 (c) is the cell contour extraction result. Figure 3 (d) shows the cell sorting result. Based on the current field of view image, the position of the microchannel in the field of view is detected using a line detection algorithm based on Hough transform. Figure 4 The micro-channel detection results are shown, where Figure 4 (a) is the original image of the microchannel. Figure 4 (b) is the edge detection result, Figure 4 (c) is the straight line detection result, Figure 4 (d) is the target ranking result.

[0086] Third, based on the position information of cells and microchannels, a proportional-integral-derivative (PID) controller and a sliding mode active disturbance rejection control based on an extended state observer are used for stage movement and cell positioning in microchannels, respectively. Figure 5 and Figure 6 The results of stage motion control and cell positioning control in microtubules are shown. Figure 5 (a) is a comparison diagram of the x-axis cell movement trajectory and the expected trajectory. Figure 5 (b) is a comparison diagram of the cell movement trajectory on the y-axis and the expected trajectory.

[0087] Based on the position information of cells and microchannels, automatic control is designed to control the stage and the positioning of cells in microtubules.

[0088] Based on the obtained position information data of cells and microchannels, automatic control is designed to control the movement of the stage to transport cells or microchannels to the microtubule orifice, and control the positioning of cells in the microtubule at the microtubule orifice. The microtubule orifice coordinates are the center point coordinates of the leftmost orifice diameter contour line identified after microtubule detection.

[0089] For the motion control of the stage, a proportional-integral-derivative (PID) controller is used. It forms the deviation e(t) based on the given value and the actual output value, and then the proportion (P), integral (I) and differential (D) of the deviation are calculated by setting three control parameters K. p , K i and K d After linear combination, the control quantity u(t) is formed to control the controlled object. The control law is as follows:

[0090]

[0091] The implementation process of stage or micro-manipulation arm motion control is as follows:

[0092] Step S1: The coordinates of a cardiomyocyte in the pixel coordinate system of the visual field image are P c , the coordinate of the microtubule opening in the pixel coordinate system is P p The objective lens calibration coefficient is C, which is used to convert between the pixel coordinate system and the world coordinate system. Since microchannel identification only needs to be performed once, while cell identification may be performed in multiple fields of view, when switching fields of view, the pixel coordinate system of the new field of view image will correspond to the new world coordinate system coordinates as the stage moves. The cardiomyocytes to be aligned are positioned at the microtubule orifices by horizontally moving the stage or micromanipulator.

[0093] Step S2: Get the current position information of the loading platform and calculate the error between the loading platform's target position and the current position. If the error is less than a set value, exit the control thread, otherwise proceed to the next step.

[0094] Step S3: The error information is passed to the proportional-integral controller to calculate the control output, that is, the movement speed of the stage in the x-direction and the y-direction, and is transmitted to the stage to make it move according to the speed.

[0095] Step S4: Update the error information, including the integral of the error, and return to step S2 to obtain the current stage position information.

[0096] For the positioning control of cells in microtubes, a sliding mode auto-disturbance rejection control based on an expansion state observer is considered. A pneumatic syringe system is used to control cell positioning. In this system, the stepper motor and the syringe piston are rigidly connected through a screw-guide rail. The forward and reverse rotation of the motor can drive the piston to move forward and backward, causing the pressure in the syringe to change. The gas-liquid interface in the microtube also changes with the pressure change, and the cells move with the movement of the liquid. In this system, the position of the cell obtained by visual feedback is used as the output of the system, and the speed of the stepper motor is used as the input of the system. Considering the interaction between the motor, air pressure, fluid, and cells, the cell is taken as the control target, and the cell dynamic model is established as follows:

[0097]

[0098] Where x1 is the cell position, x2 is the cell movement speed, u is the motor speed (i.e., the system control input), A1 is the syringe cross-sectional area, A2 is the microtube cross-sectional area, P0 is the initial cavity pressure of the system pneumatic syringe, V0 is the initial gas volume when the system syringe piston does not move, m is the mass of the cell, r is the radius of the cell, and μ is the dynamic viscosity coefficient. represents the instantaneous rate of change of the pressure in the enclosed air cavity, and the disturbance term f(·) is the concentrated uncertainty, which includes the uncertainty of the model parameters, unmodeled dynamics, the hysteresis effect of the enclosed air pressure, and other disturbances.

[0099] Let θ1 = 6πμr / m, θ2 = V0 / P0A2, b = A1 / A2, the second formula of the above equation can be written as:

[0100]

[0101] Let b0 = bθ1, The above formula can be written as:

[0102]

[0103] At this time, the system control model can be written as follows, where F represents the total disturbance of the system and h represents the differential of the total disturbance:

[0104]

[0105] in It represents the differential of the total disturbance F of the system, that is, the rate of change of the disturbance over time.

[0106] The extended state observer is a very important part of the active disturbance rejection control. It can estimate the disturbances caused by factors such as model inaccuracy, external intervention and internal coupling, and thus perform real-time compensation. Consider using a linear extended state observer based on a second-order system to estimate the state variables, where x=[x1,x2,x3] T The estimated value of , x1 represents the actual position of the cell, x2 represents the cell movement speed, and x3 represents the integral state of the total disturbance F of the system:

[0107]

[0108] Among them, β1, β2, and β3 are observer gain parameters, which are used to adjust the convergence speed of the observer.

[0109] The characteristic polynomial of the observer is:

[0110] λ(s)=s 3 +β1s 2 +β2s+β3

[0111] Define β1=3w0,β2=3w0 2 , β3=w0 3 , then the above characteristic polynomial is equal to (s+w0) 3, configuring the pole at -w0. w0 is the bandwidth parameter of the extended state observer; w0>0, this parameter does not affect the structure of the sliding mode surface. Adjusting w0 enables the extended state observer to estimate quickly and accurately, and then adjusting the sliding mode parameters to optimize tracking performance.

[0112] In this control system, w1 represents the actual position of the cell, x d represents the expected trajectory of the cell, and the position error is defined as:

[0113] e=x1-x d

[0114] The state estimation error is defined as:

[0115]

[0116] The sliding surface is defined as follows:

[0117]

[0118] For the above sliding surface, a sliding mode active disturbance rejection controller is designed to make the tracking error of the cell position converge to zero:

[0119]

[0120] where k p is the control gain, η is the switching gain, β1 and β2 are the observer gains, sat(σ) is the saturation function, β represents the boundary layer thickness, and β>0. The optimal value of β is determined by experimental debugging.

[0121] The above describes the specific control method for the positioning control of cells in microtubules. The following are the implementation steps:

[0122] Step S1: Perform microtubule detection. Extract the microtubule orifice template and magnify the area where it is located as the region of interest (ROI) for tracking. Set it as the background image B1(x, y).

[0123] Step S2: Get the current frame field of view image F(x,y) and set the target image X N The (x,y) pixels are all 0. The current frame image is subtracted from the background image within the ROI. The result is thresholded and assigned to the target image to identify the position of the current moving object. Before the next frame arrives, the background is updated to improve robustness. The background update method is as follows:

[0124] B N+1 (x,y)=αF(x,y)+(1-α)B N (x,y),0≤α≤1

[0125] Where α is the background update weight. The subtraction operation method is as follows, where T is the subtraction operation threshold.

[0126]

[0127] Step S3: Calculate the error between the current position of the cell and the expected position. If it is less than a certain threshold, exit the control. Otherwise, calculate the output of the microtubule positioning controller, transmit the output signal to the motor, and control the target to move.

[0128] Step S4: Update the error information, enter the next frame, and return to step S2.

[0129] 4. The specific arrangement process is as follows Figure 7 As shown, microtubule detection and microchannel identification are first performed to obtain the coordinates of the microtubule orifice and the coordinates of the lower endpoint of the microchannel's right groove along the contour line, which serve as the target position reference coordinates. The stage position information is then acquired, and the cardiomyocytes within the microscopic field of view are numbered and the target position is planned. The microtubule or stage is controlled to position the cardiomyocyte at the microtubule orifice. After the microtubule absorbs the cell, the microtubule orifice is moved to the target position of the cardiomyocyte, so that the coordinates of the microtubule orifice and the target position of the cardiomyocyte coincide. The microtubule then ejects the cell into the microchannel, moving it one by one in the order of cell number. After switching the field of view, the stage returns to the origin after each cell is moved, which becomes the stage origin for the new field of view.

[0130] 5. The results of myocardial cell arrangement and fusion are as follows Figure 8 As shown, Figure 8 (a) shows an image of cardiomyocytes arranged in order according to their numbers into microchannels. Figure 8 (b) is an image after the cells in the microchannel are fused. The experimental results show that the method of the present invention can achieve precise arrangement and fusion of cardiomyocytes in the microchannel.

[0131] The present invention has been described in detail above through the embodiments, but the contents described are only exemplary embodiments of the present invention and cannot be considered to limit the scope of implementation of the present invention. The scope of protection of the present invention is defined by the claims. Any use of the technical solution described in the present invention, or any person skilled in the art who, inspired by the technical solution of the present invention, designs a similar technical solution within the essence and scope of protection of the present invention to achieve the above-mentioned technical effects, or any equivalent changes and improvements made to the scope of application, shall still fall within the scope of protection covered by the patent of the present invention. It should be noted that for the sake of clarity, the description of some components and processes that have no direct and obvious connection with the scope of protection of the present invention but are known to those skilled in the art are omitted in the description of the present invention.

Claims

1. A method for automated arrangement of myocardial cell fusion based on microchannels, characterized in that: The method comprises the following steps: a. Place the culture dish containing the microchannel substrate and cardiomyocyte suspension on the motorized stage of the micromanipulator. The motorized micromanipulator arm controls the position of the micropipette, which is held by a needle holder. The inner diameter of the micropipette should be no smaller than the diameter of the cardiomyocyte. Initialize the operating field of view, aligning the microchannel, cardiomyocytes, and micropipette opening. b. Based on the current field of view image, use image processing technology to detect myocardial cells and identify microchannels and microtubule openings in the field of view image captured by a high-speed industrial camera, and number the myocardial cells; c. Determine the initial positions of the myocardial cell and the microtubule orifice, as well as the target position of the microtubule orifice when the corresponding myocardial cell moves through the microtubule and is discharged into the microchannel. Plan the path from the initial position of the microtubule orifice to the initial position of the myocardial cell, and from the microtubule orifice after the myocardial cell is drawn in to the target position of the microtubule orifice when the myocardial cell is discharged into the microchannel. Based on the planned path, set the control law for controlling the movement of the motorized stage or the motorized micromanipulator holding the microtubule. d. The microtubule is connected to a pneumatic syringe via a catheter. A stepper motor connected to the pneumatic syringe's lead screw is controlled to control the position of the cardiomyocytes within the fluid drawn into or expelled from the microtubule. A sliding surface is constructed based on the cardiomyocyte movement model, and a sliding mode active disturbance rejection controller is designed to control the stepper motor during microtubule transfer of the cardiomyocytes. e. According to the cardiomyocyte number, the cardiomyocytes in the field of view are arranged in sequence along the planned path by moving the microtube to the target position and placing the cardiomyocytes into the microchannel to complete the automated arrangement.

2. The method according to claim 1, characterized in that The specific operation in step a is to adjust the position of the manually controlled robotic arm and the stage in the initial state so that the microchannel is vertical and located on one side of the field of view, the microtubule is horizontal and located on the other side of the field of view with the microtubule opening facing the direction of the microchannel, and the focal plane is adjusted to the cell plane.

3. The method according to claim 1, characterized in that In step b, a target area point boundary tracking method based on a binary image is used to detect cell contours and extract cell center points. The specific steps are as follows: binarize the grayscale image of the current field of view; traverse the image pixels and calculate the standard deviation of the pixels in the 3×3 neighborhood of each pixel. When the standard deviation is greater than 0.3, it is considered to be a cell area, and the pixel value of the corresponding pixel is set to 255, and the values ​​of the remaining pixels are all set to 0; perform morphological operations such as closing and opening operations on the image; detect contours and count them; extract contours in the image and calculate the contour area. When the contour area is between 10-30 μm, the corresponding contour is considered to be a cell contour, and the center point of the least squares fitted ellipse is the cell center point, and half the width of the rectangle circumscribing the cell contour is the cell radius; sort the cells detected in the field of view; and record the information of each cell after sorting.

4. The method according to claim 1, wherein The myocardial cells detected in the field of view are sorted in the groove in the vertical order from bottom to top. If the vertical distance between two adjacent myocardial cells is less than the width of the microtubule, the myocardial cells close to the microgroove are selected in the front and the myocardial cells far away from the microgroove are sorted in the back. The information of each cell after the sorting is completed is recorded.

5. The method according to claim 1, wherein In step b, a line detection algorithm based on Hough transform is used to identify the position of microchannels. The specific steps are as follows: edge detection is performed on the grayscale image of the current field of view to obtain an edge image; straight lines are detected using probabilistic Hough transform and the slope of the straight lines is calculated; the detected straight lines are screened and the average slope of the two contour lines of the detected microchannels is calculated as the slope of the microchannel in the field of view; the target positions of all myocardial cells to be arranged are calculated based on the starting point of the target position of myocardial cell arrangement and the slope of the microchannel.

6. The method according to claim 1, characterized in that The target position of the microtubule orifice in step c is planned as follows: the bottom endpoint of the identified microchannel contour line close to the center of the field of view is used as a reference, and the numbered cardiomyocytes are arranged in order from bottom to top so that the center points of the cardiomyocytes are located on the microchannel contour line. The coordinates of the center points of each cardiomyocyte on the contour line are used as the target position of the coordinates of the center position of the outermost diameter contour line of the microtubule orifice after the cardiomyocytes are absorbed.

7. The method according to claim 1, characterized in that The automatic control method described in step d is specifically based on the sliding mode anti-disturbance control of the expansion state observer to maintain the cardiomyocytes at the microtube orifice. Considering the interaction between the motor, air pressure, fluid, and cardiomyocytes, the cardiomyocytes are taken as the control target, and the cardiomyocyte dynamic model is established as follows: Where x1 is the cell position, x2 is the cell movement speed, u is the motor speed, i.e., the system control input, A1 is the syringe cross-sectional area, A2 is the microtube cross-sectional area, P0 is the initial cavity pressure of the system pneumatic syringe, V0 is the initial gas volume when the system syringe piston does not move, m is the mass of the cell, r is the radius of the cell, and μ is the dynamic viscosity coefficient. represents the instantaneous rate of change of the pressure in the enclosed air cavity, and the disturbance term f(·) is the concentrated uncertainty, which includes the uncertainty of the model parameters, unmodeled dynamics, the hysteresis effect of the enclosed air pressure, and other disturbances. Let θ1 = 6πμr / m, θ2 = V0 / P0A2, b = A1 / A2, the second formula of the above equation can be written as: Let b0 = bθ1, The above formula can be written as: At this time, the system control model can be written as follows, where F represents the total disturbance of the system and h represents the differential of the total disturbance: in It represents the differential of the total disturbance F of the system, that is, the rate of change of the disturbance over time; A linear extended state observer based on a second-order system is used to estimate the state variables, where x=[x1,x2,x3] T Estimated value of: Among them, β1, β2, and β3 are observer gain parameters; The characteristic polynomial of the observer is: λ(s)=s 3 +β1s 2 +β2s+β3 Define β1=3w0,β2=3w0 2 , β3=w0 3 , then the above characteristic polynomial is equal to (s+w0) 3 , the pole is configured at -w0, w0 is the bandwidth parameter of the extended state observer; In this control system, x1 represents the actual position of the cell, x d represents the expected trajectory of the cell, and the position error is defined as: and=x1-x d The state estimation error is defined as: The sliding surface is defined as follows: For the above sliding surface, a sliding mode active disturbance rejection controller is designed to make the tracking error of the cell position converge to zero: where k p is the control gain, η is the switching gain, β1 and β2 are the observer gains, sat(σ) is the saturation function, β represents the boundary layer thickness, and β>0.

8. The method according to claim 7, characterized in that The specific control method steps for controlling the positioning of cardiomyocytes in microtubules are as follows: Step S1: Perform microtubule detection: extract the microtubule orifice template, magnify the area where it is located as the region of interest for tracking, and set it as the background image B1(x,y); Step S2: Get the current frame field of view image F(x,y) and set the target image X N The (x, y) pixels are all 0, and the current frame image is subtracted from the background image within the ROI. The result is thresholded and assigned to the target image to identify the position of the current moving object. Before the next frame arrives, the background is updated to improve robustness. The background update method is as follows: B N+1 (x,y)=αF(x,y)+(1-α)B N (x,y),0≤α≤1 Where α is the background update weight; The subtraction operation is as follows: Where T is the subtraction operation threshold; Step S3: Calculate the current position and expected position of the cell P c If the error is less than a certain threshold, the control is exited. Otherwise, the output of the positioning controller in the microtube is calculated and the output signal is transmitted to the motor to control the target to move. Step S4: Update the error information, enter the next frame, and return to step S2.

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