Microchannel-based jet control method, device, electronic device and storage medium

Abstract

The present application relates to a jet control method, device, electronic device and storage medium based on a microchannel. The jet control method based on the microchannel includes: before a cell enters the jet region of the microchannel, acquiring the elastic modulus of the cell; according to the elastic modulus of the cell, adjusting the jet intensity of a jet device for perforating the cell so that the cell membrane tension of the cell is between the perforation threshold and the rupture threshold, and the jet device is located in the jet region of the microchannel. The technical solution of the present application can avoid the situations of insufficient cell perforation and cell rupture, fully perforate the cells, and not only can improve the transmembrane transduction efficiency, but also can improve the cell survival rate.

Description

Technical Field

[0001] The present invention relates to the technical field of transmembrane transport of macromolecules, and particularly relates to a jet control method, device, electronic device and storage medium based on a microchannel. Background Art

[0002] Transducing and transporting macromolecular particulate matter across the cell membrane into cells is a key step in personalized precision medicine such as cancer cell therapy and regenerative medicine.

[0003] In the related art, a cell membrane jet perforation device is proposed. By providing a jet, the cell is subjected to the action of the flow field shear force generated by the jet impact, so as to form one or more micropores on the cell membrane. In this way, the macromolecular substances in the solution can enter the cell through the micropores. When the flow field shear force of this device is controlled within an appropriate range, one or more micropores can be opened on the cell membrane, while minimizing cell damage and improving the transduction efficiency at the same time.

[0004] Therefore, how to control the jet parameters of the jet perforation device to improve the transduction efficiency and cell survival rate is a technical problem to be solved. Summary of the Invention

[0005] The purpose of the present application is to provide a jet control method, device, electronic device and storage medium based on a microchannel, which can improve the transmembrane transduction efficiency and cell survival rate.

[0006] According to the first aspect of the embodiments of the present application, a jet control method based on a microchannel is provided, including:

[0007] Before the cell enters the jet region of the microchannel, obtain the cell elastic modulus;

[0008] According to the cell elastic modulus, adjust the jet intensity of the jet device for opening holes in the cell, so that the cell membrane tension of the cell is between the opening threshold and the rupture threshold, and the jet device is located in the jet region.

[0009] In an implementation manner, the cross-sectional areas of at least two places of the microchannel are different, and the inner diameter of the narrowest region of the microchannel is greater than the cell diameter and less than twice the cell diameter, so as to prevent the cell from being directly extruded by the microchannel during the process of passing through the narrowest region, and only allow a single cell to pass through the narrowest region each time; after the cell passes through the narrowest region, it enters the jet region;

[0010] The obtaining the cell elastic modulus before the cell enters the jet region of the microchannel includes:

[0011] Obtain first cell deformation data; the first cell deformation data includes cell deformation characteristic data of elastic deformation occurring at at least one moment during the process of the cell passing through the narrowest region.

[0012] Input the first cell deformation data into a trained cell elastic modulus prediction model, so that the cell elastic modulus prediction model outputs the cell elastic modulus.

[0013] In one implementation manner, the cell elastic modulus prediction model is a fully connected neural network; the first cell deformation data further includes pressure information at the entrance of the narrowest region; the cell deformation characteristic data includes at least one of cell contour data, elongation index, non-circularity, curvature ratio, relative cell size, and reciprocal of passing time.

[0014] When the cell deformation characteristic data includes cell contour data, the cell contour data is the coordinates of the contour points on the cell contour in the cell image; for each moment, the cell contour data includes first contour data of the front view of the cell and second contour data of the top view of the cell.

[0015] In one implementation manner, the cell elastic modulus prediction model is a convolutional neural network; the first cell deformation data is a cell image; the cell image includes the front view and the top view of the cell.

[0016] In one implementation manner, adjusting the jet intensity of the jet device for opening a hole in the cell according to the cell elastic modulus includes:

[0017] Obtain target jet parameters according to the cell elastic modulus and a pre-stored first correspondence; the first correspondence is the correspondence between the elastic modulus and the jet parameters.

[0018] Adjust the jet intensity of the jet device for opening a hole in the cell according to the target jet parameters.

[0019] In one implementation manner, before adjusting the jet intensity of the jet device for opening a hole in the cell according to the cell elastic modulus, it includes:

[0020] Obtain the target model identifier of the constitutive model of the cell.

[0021] Adjusting the jet intensity of the jet device for opening a hole in the cell according to the cell elastic modulus includes:

[0022] Obtain target jet parameters according to the cell elastic modulus, the target model identifier, and a pre-stored second correspondence; the second correspondence is the correspondence between the elastic modulus, the model identifier, and the jet parameters.

[0023] Adjust the jet intensity of the jet device for perforating cells according to the target jet parameters.

[0024] In one embodiment, before adjusting the jet intensity of the jet device for perforating cells according to the cell elastic modulus, it includes:

[0025] Obtain the size data of the cells;

[0026] The adjustment of the jet intensity of the jet device for perforating cells according to the cell elastic modulus includes:

[0027] Obtain the target jet parameters according to the cell elastic modulus, the size data, and a pre-stored third correspondence relationship; the third correspondence relationship is the correspondence relationship between the elastic modulus, the cell size, and the jet parameters;

[0028] Adjust the jet intensity of the jet device for perforating cells according to the target jet parameters.

[0029] In one embodiment, before adjusting the jet intensity of the jet device for perforating cells according to the cell elastic modulus, it includes:

[0030] Obtain the target model identifier of the constitutive model of the cells;

[0031] Obtain the size data of the cells;

[0032] The adjustment of the jet intensity of the jet device for perforating cells according to the cell elastic modulus includes:

[0033] Obtain the target jet parameters according to the cell elastic modulus, the target model identifier, the size data, and a pre-stored fourth correspondence relationship; the fourth correspondence relationship is the correspondence relationship between the elastic modulus, the model identifier, the cell size, and the jet parameters;

[0034] Adjust the jet intensity of the jet device for perforating cells according to the target jet parameters.

[0035] In one embodiment, the obtaining of the size data of the cells includes:

[0036] Take a photo of the cells through a camera device to obtain the cell image;

[0037] Obtain the size data of the cells according to the cell image.

[0038] In one embodiment, the obtaining of the size data of the cells includes:

[0039] Obtain the target category of the cells;

[0040] Obtain the size data of the cell according to the target category and the fifth corresponding relationship, where the fifth corresponding relationship is the corresponding relationship between the cell category and the cell size.

[0041] In one implementation, the target jet parameters include the target jet amplitude and the target jet frequency.

[0042] According to the second aspect of the embodiments of the present application, a jet control device based on a microchannel is provided, including:

[0043] An acquisition module configured to acquire the cell elastic modulus before the cell enters the jet region of the microchannel;

[0044] An adjustment module configured to adjust the jet intensity of the jet device for opening holes in the cell according to the cell elastic modulus, so that the cell membrane tension of the cell is between the opening threshold and the rupture threshold, and the jet device is located in the jet region.

[0045] In one implementation, the cross-sectional areas of at least two parts of the microchannel are different, and the inner diameter of the narrowest region of the microchannel is greater than the cell diameter and less than twice the cell diameter, so as to prevent the cell from being directly squeezed by the microchannel during the process of passing through the narrowest region, and only allow a single cell to pass through the narrowest region each time; after the cell passes through the narrowest region, it enters the jet region;

[0046] The acquisition module includes:

[0047] An acquisition sub-module configured to acquire first cell deformation data; the first cell deformation data includes cell deformation characteristic data of elastic deformation occurring at at least one moment during the process of the cell passing through the narrowest region;

[0048] A prediction sub-module configured to input the first cell deformation data into a trained cell elastic modulus prediction model, so that the cell elastic modulus prediction model outputs the cell elastic modulus.

[0049] According to the third aspect of the embodiments of the present application, an electronic device is provided, including a memory and a processor, where the memory is used to store a computer program executable by the processor; the processor is used to execute the computer program in the memory to implement the above method.

[0050] According to the fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and characterized in that when the executable computer program in the storage medium is executed by a processor, the above method can be implemented.

[0051] Compared with the prior art, the beneficial effects of the present application are as follows: Before the cells enter the jet region of the microchannel, the cell elastic modulus is obtained. Then, according to the cell elastic modulus, the jet intensity of the jet device for opening holes in the cells is adjusted so that the cell membrane tension is between the opening threshold and the rupture threshold. In this way, the situations of insufficient cell hole opening and cell rupture can be avoided, and the cells can be fully opened, which can not only improve the transmembrane transduction efficiency but also improve the cell survival rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 is a flowchart of a jet control method based on a microchannel according to an exemplary embodiment.

[0053] Figure 2 is a schematic structural diagram of a cell introduction microfluidic system based on zero mass jet according to an exemplary embodiment.

[0054] Figure 3 is a flowchart of a jet control method based on a microchannel according to an exemplary embodiment.

[0055] Figure 4 is a cell image of cells deforming at different times according to an exemplary embodiment.

[0056] Figure 5 is a flowchart of a jet control method based on a microchannel according to another exemplary embodiment.

[0057] Figure 6 is a cell image of cells deforming according to an exemplary embodiment.

[0058] Figure 7 is a binary cell image according to an exemplary embodiment.

[0059] Figure 8 is a cell contour image according to an exemplary embodiment.

[0060] Figure 9 is a schematic diagram of obtaining the coordinates of contour points according to a cell contour image according to an exemplary embodiment;

[0061] Figure 10 is a schematic structural diagram of a cell elastic modulus prediction model according to an exemplary embodiment.

[0062] Figure 11 is a flowchart of a training method of a cell elastic modulus prediction model according to an exemplary embodiment.

[0063] Figure 12It is a flowchart of a microchannel-based jet control method shown according to another exemplary embodiment.

[0064] Figure 13 It is a flowchart of a microchannel-based jet control method shown according to another exemplary embodiment.

[0065] Figure 14 It is a flowchart of a microchannel-based jet control method shown according to another exemplary embodiment.

[0066] Figure 15 It is a flowchart of a microchannel-based jet control method shown according to another exemplary embodiment.

[0067] Figure 16 It is a block diagram of a microchannel-based jet control device shown according to an exemplary embodiment.

[0068] Figure 17 It is a block diagram of a microchannel-based jet control device shown according to another exemplary embodiment.

[0069] Figure 18 It is a block diagram of an electronic device shown according to an exemplary embodiment. Detailed implementation manners

[0070] Unless otherwise defined, the technical terms or scientific terms used in this specification and the claims should have the ordinary meanings understood by those of ordinary skill in the technical field to which the present invention belongs. The following will describe the specific implementation manners of the present invention with reference to the accompanying drawings. It should be noted that in the process of the specific description of these implementation manners, for the sake of concise description, this specification cannot describe all the features of the actual implementation manners in detail. Without departing from the spirit and scope of the present invention, those skilled in the art can modify and replace the implementation manners of the present invention, and the obtained implementation manners are also within the protection scope of the present invention.

[0071] Figure 1 It is a flowchart of a microchannel-based jet control method shown according to an exemplary embodiment. Please refer to Figure 1 , the microchannel-based jet control method may include the following steps:

[0072] Step 101, before the cells enter the jet region of the microchannel, obtain the cell elastic modulus.

[0073] Step 102, according to the cell elastic modulus, adjust the jet intensity of the jet device for opening holes in the cells so that the cell membrane tension is between the opening threshold and the rupture threshold, and the jet device is located in the jet region of the microchannel.

[0074] Cells have different mechanical properties, and the optimal jetting conditions of the corresponding jetting device are also different. There is a one-to-one correspondence between the mechanical properties of cells and the optimal jetting conditions. For the mechanical properties of cells, they can be characterized by a constitutive model and the cell elastic modulus, and the jetting conditions of the jetting device can be characterized by the jetting intensity. Therefore, when the constitutive model of the cell is known, there is a one-to-one correspondence between the cell elastic modulus and the optimal jetting intensity. Furthermore, the jetting intensity of the jetting device can be adjusted according to the cell elastic modulus.

[0075] In this embodiment, before the cell enters the jetting region of the microchannel, the cell elastic modulus can be obtained through experimental means. Of course, the cell elastic modulus can also be obtained through other technical means.

[0076] In this embodiment, before the cell enters the jetting region of the microchannel, the cell elastic modulus is obtained. Then, according to the cell elastic modulus, the jetting intensity of the jetting device for opening holes in the cell is adjusted so that the cell membrane tension is between the opening threshold and the rupture threshold. In this way, the situations of insufficient cell hole opening and cell rupture can be avoided, and the cell can be fully opened, which can not only improve the transmembrane transduction efficiency but also improve the cell survival rate.

[0077] The above briefly introduces the jetting control method based on a microchannel provided by this application. Next, the jetting control method based on a microchannel will be introduced in detail.

[0078] The jetting control method based on a microchannel provided by this application can be applied to a cell introduction microfluidic system based on zero-mass jetting. Before introducing the jetting control method based on a microchannel in detail, the cell introduction microfluidic system based on zero-mass jetting will be introduced first.

[0079] As Figure 2 shown, the cell introduction microfluidic system based on zero-mass jetting includes a microchannel 11, a mechanical monitoring device 12, and a jetting device 13.

[0080] As Figure 1As shown in the figure, the microchannel 11 is a variable cross-section channel, with at least two different cross-sectional areas. The microchannel 11 includes a cell inlet in1, a first channel segment S1, a second channel segment S2, a third channel segment S3, and a fourth channel segment S4 connected in sequence, a jet inlet in2, and a cell outlet out. The cross-sectional areas of the first channel segment S1, the third channel segment S3, and the fourth channel segment S4 are larger than the cross-sectional area of the second channel segment S2, and the second channel segment S2 is the narrowest region of the microchannel 11. The inner diameter of the narrowest region of the microchannel 11 is larger than the cell diameter and smaller than twice the cell diameter, so as to avoid the cells being directly squeezed by the microchannel 11 during the process of passing through the narrowest region, and only allow a single cell to pass through the narrowest region each time. The fourth channel segment S4 is a jet region. The cells enter the jet region after passing through the narrowest region. The cell inlet in1 is arranged on one side of the first channel segment S1, the cell outlet out is arranged on the side of the fourth channel segment S4 away from the cell inlet in1, and the jet inlet in2 is arranged on the wall of the fourth channel segment S4. The inner diameters of all parts of the microchannel 11 are relatively small, and are of the same order of magnitude as the size of the cells 14.

[0081] The mechanical monitoring device 12 includes a camera device 121 and a processor 122, and the camera device 121 is connected to the processor 122. The camera device 121 is arranged on the periphery of the second channel segment S2 and is used to collect the cell images after the cells are deformed, so that the processor 122 can process the cell images to obtain the cell elastic modulus.

[0082] The jet device 13 includes a jet nozzle hole 131, and the jet nozzle hole 131 is opposite to the jet inlet in2 on the microchannel 11 and can be coaxially arranged. The jet device 13 is used to provide a jet to perforate the cells to achieve transmembrane transport of substances.

[0083] After the cells 14 enter the microchannel 11 through the cell inlet in1, they are squeezed and deformed at the second channel segment S2. The camera device 121 collects the cell images of the deformed cells 15, so that the processor 122 can process the cell images to obtain the cell elastic modulus, so as to adjust the jet intensity of the jet device 13 to perforate the cells, so that the cell membrane tension of the cells is between the perforation threshold and the rupture threshold, so that the cells are fully perforated, avoiding the situations of insufficient cell perforation and cell rupture, and improving the transmembrane transduction efficiency and cell survival rate.

[0084] It should be noted that the cell introduction microfluidic system based on zero-mass jet is a device integrating mechanical measurement and perforation. If no jet operation is performed, it is simply a mechanical measurement device.

[0085] The above briefly introduces the cell introduction microfluidic system based on zero-mass jet. Next, the jet control method based on microchannels will be introduced in detail.

[0086] Figure 3 is a flowchart of a microchannel-based jet control method shown according to an exemplary embodiment. Please refer to Figure 3 , the microchannel-based jet control method may include the following steps:

[0087] Step 301, obtaining first cell deformation data; the first cell deformation data includes cell deformation characteristic data of elastic deformation occurring at at least one moment during the process of the cell passing through the narrowest region of the microtube.

[0088] In this embodiment, the inner diameter of the narrowest region of the microtube 11 is greater than the cell diameter and less than twice the cell diameter. In this way, it is possible to avoid the cell being directly squeezed by the microtube during the process of passing through the microtube, and only allow a single cell to pass through the narrowest region each time. In this way, there is only one cell in the cell image collected by the imaging device 121 each time, which is convenient for the processor 122 to process and can improve the processing efficiency.

[0089] Preferably, the inner diameter of the narrowest region of the microtube 11 is greater than the cell diameter and less than 1.5 times the cell diameter. In this way, it is possible to better achieve allowing only a single cell to pass through the narrowest region each time, that is, at any position in the narrowest region at the same moment, there is only one cell.

[0090] In this embodiment, the pressure on the side of the second pipe section S2 close to the cell inlet in1 is greater than the pressure on the side close to the cell outlet out, so that the cell can flow out of the second pipe section S2. After the undeformed cell 14 enters the second pipe section S2, it undergoes elastic deformation due to being squeezed.

[0091] In this embodiment, as Figure 4 shown, the cell undergoes different degrees of elastic deformation at different moments during the process of passing through the narrowest region of the microtube. For example, at the first moment t1, the cell does not undergo elastic deformation, and the front view P11 and the top view P12 of the cell are both circular. At the second moment t2, the third moment t3, and the fourth moment t4, the cell undergoes different degrees of elastic deformation, and the front view P21 and the top view P22 of the cell at the second moment t2, the front view P31 and the top view P32 of the cell at the third moment t3, and the front view P41 and the top view P42 of the cell at the fourth moment t4 are all irregular.

[0092] In this embodiment, the first cell deformation data includes cell deformation characteristic data of elastic deformation occurring at multiple moments during the process of the cell passing through the narrowest region of the microtube. In other embodiments, the first cell deformation data may also only include cell deformation characteristic data of elastic deformation occurring at a certain moment during the process of the cell passing through the narrowest region of the microtube.

[0093] In this embodiment, the cell deformation feature data is cell contour data. The first cell deformation data further includes the pressure information at the entrance of the narrowest region, where the entrance of the narrowest region is located on the side of the second pipe segment S2 close to the cell entrance in1. The cell contour data is the coordinates of the contour points on the cell contour in the cell image. The cell image includes the front view and top view of the cell. For each moment, the cell contour data includes the first contour data of the front view of the cell and the second contour data of the top view of the cell. In other embodiments, the cell image may include only the front view or the top view of the cell.

[0094] In this embodiment, the cell contour data is the coordinates of 180 contour points on the cell contour in the cell image. Among them, the 180 contour points are evenly distributed on the cell contour. In other embodiments, the number of contour points may be other numbers, not limited to 180 in this embodiment.

[0095] In this embodiment, as Figure 5 shown, for each cell image, the method for obtaining the cell contour data may include the following steps:

[0096] Step 501, photograph the cell with a camera device to obtain a cell image.

[0097] In this embodiment, taking the example of obtaining the coordinates of the contour points on the cell contour in the front view of the cell for illustration.

[0098] In this step, as Figure 6 shown, photographing the front of the cell with a camera device can obtain a cell image 51 including a cell 15 that has undergone elastic deformation. The cell image 51 is the front view of the cell.

[0099] Step 502, binarize the cell image to obtain a binarized cell image.

[0100] In this step, as Figure 7 shown, binarize the Figure 6 shown cell image 51 to obtain a binarized cell image 61.

[0101] Step 503, extract the cell contour from the binarized cell image to obtain the cell contour.

[0102] In this step, as Figure 8 shown, the boundary following algorithm proposed by Suzuki et al. can be used to detect the cell contour in the binarized cell image 61 to obtain a cell contour image 71. The cell contour image 71 includes a cell contour 72. Other algorithms can also be used to extract the cell contour. Among them, the cell contour is a footprint contour, rather than a cross-sectional contour.

[0103] Step 504: Determine the centroid of the cell contour.

[0104] In this step, calculate the centroid of the cell contour 72. As Figure 9 shown, the centroid D is located within the cell contour 72 and is also the centroid of the cell contour 72.

[0105] Step 505: With the centroid as the origin, starting from a specified contour point on the cell contour, extract contour points counterclockwise at a specified angular interval to obtain N contour points, where N = 360 / α and α is the specified angular interval.

[0106] In this embodiment, α is 2° and N is 180.

[0107] In this step, as Figure 9 shown, starting from the specified contour point A on the cell contour 72, extract contour points counterclockwise at an angular interval of 2° to obtain 180 contour points.

[0108] In this embodiment, taking 180 contour points from the cell contour 72 is sufficient to depict the cell contour 72, and it can reduce the computational amount and improve the calculation speed. Of course, in other embodiments, other numbers of contour points can also be extracted.

[0109] Of course, in other embodiments, the method of extracting contour points from the cell contour is not limited to the method in this embodiment. For example, starting from the specified contour point A on the cell contour 72, extract contour points clockwise at an angular interval of 2° to obtain 180 contour points.

[0110] Step 506: For each contour point, use the vector connecting the origin and the contour point as the coordinates of the contour point.

[0111] In this step, as Figure 9 shown, for each contour point 81, connect the origin O and the contour point 81 to obtain the corresponding vector, and use this vector as the coordinates of the contour point 81. The combination of these 180 vectors is an array describing the cell contour and is also a set of input data for the cell elastic modulus prediction model. If this array is denoted as X1(180,2), then the array X1(180,2) is as follows:

[0112] <![CDATA[x1]]> <![CDATA[y1]]> <![CDATA[x2]]> <![CDATA[y2]]> <![CDATA[x3]]> <![CDATA[y3]]> …… …… <![CDATA[x 180 > <![CDATA[y 180 >

[0113] In one embodiment, after obtaining the coordinates of the contour points, it is also necessary to normalize the coordinates of the contour points. Normalization can make the value range of the data input into the cell elastic modulus prediction model within a relatively consistent interval. Moving the centroid D to the origin O can make normalization easier. Moreover, normalizing the data input into the cell elastic modulus prediction model helps to increase the convergence speed of the model, provide the robustness of the model, and avoid the differences between features.

[0114] The method for obtaining cell contour data is introduced above. The first contour data of the front view of the cell and the second contour data of the top view of the cell can both be obtained by the above method, and will not be introduced one by one here.

[0115] Step 302, input the first cell deformation data into the trained cell elastic modulus prediction model, so that the cell elastic modulus prediction model outputs the cell elastic modulus.

[0116] In this embodiment, the selected model for the cell is a shell structure cell model, and it is considered that the cell membrane is a shell structure, and the inside and outside of the cell are viscous liquids. For the shell structure cell model, the cell membrane constitutive model adopts the Hookean model, Mooney-Rivlin model, Neo-Hookean model, Skalak model or Evans & Skalak model. For example, in this embodiment, the cell membrane constitutive model can adopt the Mooney-Rivlin model.

[0117] Among them, the constitutive model can also be called the constitutive equation. For example, the following equation is a constitutive model, where c1 and c2 are elastic moduli. Among them, the elastic modulus can also be called the constitutive parameter.

[0118]

[0119] Among them, U is the strain energy density, I1, I2, and I3 are respectively the three deformation invariants of the Cauchy-Green tensor, and κ is a material constant used to describe the nonlinear characteristics of the cell.

[0120] If the known condition is that the cell membrane constitutive model adopts the above equation, the elastic modulus in it can be predicted by using the cell elastic modulus prediction model trained for the above equation.

[0121] In this embodiment, the cell elastic modulus prediction model is used to predict the cell elastic modulus for a specified constitutive model. For example, if the cell membrane constitutive model adopts the Mooney-Rivlin model, the cell elastic modulus prediction model is used to predict the cell elastic modulus when the cell membrane constitutive model adopts the Mooney-Rivlin model.

[0122] In this step, the obtained first cell deformation data is input into the trained cell elastic modulus prediction model, and the cell elastic modulus prediction model outputs the cell elastic modulus.

[0123] In this embodiment, as Figure 10 shown, the cell elastic modulus prediction model is a fully connected neural network. The fully connected neural network includes an input layer input, a flattening layer flatten, a fusion layer merge, hidden layers hide1, hide2, hide3, and an output layer output that are connected in sequence. Among them, the number of hidden layers can be other numbers, not limited to 3 layers.

[0124] The input layer input is used to input the first cell deformation data. Among them, the input layer includes 2n + 1 input nodes 91, which are used to input the cell contour data from the first moment t1 to the nth moment (t n ) and the pressure information at the entrance of the narrowest area. Among them, n is a positive integer. The pressure information at the entrance of the narrowest area is a constant value, which can be denoted as an array P(1). Each input node 91 is used to input an array. For example, at the first moment t1, the cell contour data includes the first contour data of the front view of the cell (denoted as X1(180,2)) and the second contour data of the top view of the cell (denoted as X2(180,2)). At the second moment t2, the cell contour data includes the first contour data of the front view of the cell (denoted as X3(180,2)) and the second contour data of the top view of the cell (denoted as X4(180,2)), ……, at the nth moment (t n ), the cell contour data includes the first contour data of the front view of the cell (denoted as X 2n-1 (180,2)) and the second contour data of the top view of the cell (denoted as X 2n (180,2)). The 2n + 1 input nodes 91 of the input layer input are respectively used to input the arrays X1(180,2), X2(180,2), X3(180,2), X4(180,2), ……, X 2n-1 (180,2), X 2n (180,2) and P(1). Among them, the cell contour data can be obtained by processing cell images through the CV2 library (computer vision library) in Python.

[0125] The flattening layer flatten is used to flatten the first cell deformation data to obtain the flattened first cell deformation data. Among them, the flattening layer flatten includes 2n + 1 flattening nodes 92, and the 2n + 1 flattening nodes 92 are connected to the 2n + 1 input nodes 91 in a one-to-one correspondence. The flattening node 92 is used to flatten the data received by the corresponding input node 91.

[0126] The merge layer is used to perform a fusion process on the flattened first cell deformation data to obtain fusion data, where the fusion data is a tensor. The merge layer is connected to all the flattening nodes 92 in the flatten layer. In this embodiment, the Concatenate function can be used to concatenate the flattened first cell deformation data to obtain the fusion data, but it is not limited thereto. The merge layer is fully connected to the hidden layers hide1, hide2, and hide3.

[0127] The hidden layer hide1 includes 2n + 1 neuron nodes 93, and each neuron node 93 in the hidden layer hide1 is respectively connected to the merge layer. The hidden layer hide2 also includes 2n + 1 neuron nodes 93, and each neuron node 93 in the hidden layer hide2 is respectively connected to each neuron node 93 in the hidden layer hide1 and is respectively connected to each neuron node 93 in the hidden layer hide3.

[0128] The hidden layer hide3 is connected to the output layer output, and the output layer output is used to output the cell elastic modulus. The output layer output includes output nodes 94, and the number of output nodes 94 is the same as the number of cell elastic moduli. Each output node 94 is used to output a cell elastic modulus. For example, when the cell elastic moduli include c1 and c2, the output layer output includes two output nodes 94, one output node 94 is used to output c1, and the other output node 94 is used to output c2.

[0129] The method for predicting the cell elastic modulus using the trained cell elastic modulus prediction model is introduced above. Next, the training method of the cell elastic modulus prediction model is introduced.

[0130] As Figure 11 shown, the training method of the cell elastic modulus prediction model may include the following steps:

[0131] Step 1101, calculate using a specified constitutive model and elastic modulus to obtain second cell deformation data.

[0132] Step 1102, use the second cell deformation data as training data to train the cell elastic modulus prediction model until the cell elastic modulus prediction model meets the specified conditions to obtain the trained cell elastic modulus prediction model.

[0133] In this embodiment, the specified constitutive model and elastic modulus can be used for calculation to obtain the corresponding second cell deformation data as training data. For example, the specified constitutive model can be the above equation, and then prepare M sets of values of c1 and c2, where M can be 3*10 6, but not limited to this. The values of c1 and c2 in each group are different. For each group of values of c1 and c2, the corresponding second cell deformation data is calculated using the above equation to describe the shape of the cell after deformation.

[0134] Then, the calculated training data is input into the cell elastic modulus prediction model, and the cell elastic modulus prediction model is trained until the cell elastic modulus prediction model meets the specified conditions, and a trained cell elastic modulus prediction model is obtained. Among them, the specified conditions are that the training loss and the validation loss reach 10 -5 ~10 -4 , and the accuracy of the test set reaches more than 99%.

[0135] Using the calculation method to obtain training data can quickly obtain a large amount of training data, improve the training speed, and save the training cost. Of course, the training data can also be experimental data.

[0136] In this embodiment, by obtaining the first cell deformation data and inputting the first cell deformation data into the trained cell elastic modulus prediction model, the cell elastic modulus prediction model outputs the cell elastic modulus. In this way, it is faster and has a higher throughput than using a laboratory measurement tool to measure the cell elastic modulus. Moreover, since no force is applied to the cell by the measurement tool, damage to the cell can be avoided. Therefore, the technical solution provided by this application can improve the throughput of detecting the cell elastic modulus and reduce the damage to the cell.

[0137] In other embodiments, the cell deformation feature data may further include any one or any combination of cell contour data, elongation index, non-circularity, curvature ratio, relative cell size, and reciprocal of transit time. For example, in one embodiment, the cell deformation feature data may include cell contour data and elongation index. In another embodiment, the cell deformation feature data may include relative cell size.

[0138] In one embodiment, the calculation formula of the elongation index is

[0139] D1 = (W - H) / (W + H)

[0140] where D1 is the elongation index, W is the maximum length of the cell after deformation, and H is the minimum length of the cell after deformation.

[0141] In another embodiment, the calculation formula of the elongation index is

[0142]

[0143] where W is the maximum length of the cell after deformation, and H is the minimum length of the cell after deformation.

[0144] In another embodiment, the calculation formula of the elongation index is

[0145]

[0146] Among them, D t is the deformation of the cell at time t, D t+1 is the deformation of the cell at time t + 1, W t is the maximum length after the cell deformation at time t, H t is the minimum length after the cell deformation at time t, W t+1 is the maximum length after the cell deformation at time t + 1, H t+1 is the minimum length after the cell deformation at time t + 1.

[0147] In another embodiment, the calculation formula of the extension index is

[0148] D1 = W / 2R1

[0149] Among them, R1 is the radius of the cell when it is not deformed, and W is the maximum length after the cell is deformed.

[0150] The calculation formula of the non-circularity is as follows:

[0151] O = 1 - c

[0152]

[0153] Among them, O is the non-circularity, c is the circularity, A is the area of the cross-section of the cell deformation, and p is the perimeter of the cross-section of the cell deformation.

[0154] The calculation formula of the curvature ratio is as follows:

[0155] ratio = κ min / κ max

[0156] Among them, ratio is the curvature ratio, κ min is the minimum curvature of the cross-section of the cell deformation, κ max is the maximum curvature of the cross-section of the cell deformation.

[0157] The calculation formula of the relative cell size is as follows:

[0158] D2 = R1 / R2

[0159] Among them, D2 is the relative cell size, R1 is the radius of the cell when it is not deformed, and R2 is the radius of the inner wall cross-section of the second pipeline segment S2.

[0160] The calculation formula of the reciprocal of the passing time is as follows:

[0161]

[0162] Among them, D3 is the reciprocal of the passage time, and Passage time is the duration for the cell to pass through the second pipe segment S2. Step 303: According to the cell elastic modulus, adjust the jet intensity of the jet device for opening holes in the cell so that the cell membrane tension is between the opening threshold and the rupture threshold. The jet device is located in the jet region of the micro-pipe.

[0163] In this embodiment, after the cell passes through the narrowest region, it enters the jet region, and the jet device provides a jet to open a hole in the cell. For each group of cell elastic moduli, there is a corresponding optimal jet intensity. For each optimal jet intensity, there is a corresponding set of jet parameters. Therefore, for each group of cell elastic moduli, there is a corresponding set of jet parameters. By using this set of jet parameters, the jet device can provide the optimal jet intensity so that the cell membrane tension is between the opening threshold and the rupture threshold. In this way, the situations of insufficient cell hole opening and cell rupture can be avoided, and the cells can be fully opened, which can not only improve the transmembrane transduction efficiency but also improve the cell survival rate.

[0164] In this embodiment, the jet intensity of the jet device for opening holes in the cell is adjusted by adjusting the jet parameters of the jet device. Among them, the jet parameters include the jet frequency and the jet amplitude.

[0165] In this embodiment, as Figure 12 shown, step 303 may include the following steps:

[0166] Step 1201: Obtain the target jet parameters according to the cell elastic modulus and the pre-stored first correspondence; the first correspondence is the correspondence between the elastic modulus and the jet parameters.

[0167] Step 1202: Adjust the jet intensity of the jet device for opening holes in the cell according to the target jet parameters.

[0168] In this embodiment, the constitutive model is known, and only the correspondence between the elastic modulus and the jet parameters needs to be pre-stored. After obtaining the cell elastic modulus, the first correspondence can be queried according to the cell elastic modulus to obtain the corresponding target jet parameters. Among them, the target jet parameters include the target jet amplitude and the target jet frequency. The query logic is simple and the efficiency is high.

[0169] The first correspondence can be obtained by the method of numerical simulation and experimental verification, which is roughly as follows: For a single cell, the constitutive model is known. For each elastic modulus, the jet parameters of the jet device are adjusted. From the multiple jet conditions provided by the jet device when working with multiple groups (for example, 90 groups) of jet parameters, the optimal jet condition is selected, and the jet parameters corresponding to the optimal jet condition are associated with the elastic modulus and stored in the first correspondence.

[0170] In this embodiment, first cell deformation data is obtained and input into a trained cell elastic modulus prediction model, so that the cell elastic modulus prediction model outputs the cell elastic modulus. Then, according to the cell elastic modulus, the jet intensity of the jet device for opening holes in the cells is adjusted so that the cell membrane tension of the cells is between the opening threshold and the rupture threshold. In this way, the situations of insufficient cell hole opening and cell rupture can be avoided, and the cells can be fully opened, which can not only improve the transmembrane transduction efficiency but also improve the cell survival rate.

[0171] Moreover, the cell elastic modulus is measured when the cell is moving in the microchannel and before entering the jet region. The data has strong timeliness and is more accurate. Therefore, the jet intensity of the jet device for opening holes in the cells can be adjusted more accurately.

[0172] Furthermore, the jet control method based on the microchannel integrates the measurement of the cell elastic modulus and the adjustment of the jet intensity. The process is closely connected, which can greatly save time and improve the transmembrane transduction efficiency.

[0173] Figure 13 It is a flowchart of a jet control method based on a microchannel shown according to another exemplary embodiment. Please refer to Figure 13 This jet control method based on the microchannel may include the following steps:

[0174] Step 1301: Obtain first cell deformation data; the first cell deformation data includes cell deformation characteristic data of elastic deformation occurring at least at one moment during the process of the cell passing through the narrowest region of the microchannel.

[0175] Step 1302: Input the first cell deformation data into a trained cell elastic modulus prediction model so that the cell elastic modulus prediction model outputs the cell elastic modulus.

[0176] In this embodiment, steps 1301 to 1302 are similar to steps 301 to 302 and will not be elaborated here.

[0177] Step 1303: Obtain the target model identifier of the constitutive model of the cell.

[0178] In this embodiment, the processor 122 can provide multiple cell elastic modulus prediction models, and each cell elastic modulus prediction model is used to predict the cell elastic modulus of the corresponding constitutive model. Therefore, in addition to the elastic modulus, the corresponding target jet parameters can be determined only according to the target model identifier of the constitutive model.

[0179] In this embodiment, the cell elastic modulus prediction model corresponds one-to-one with the constitutive model, and the identifier of the cell elastic modulus prediction model can be used as the identifier of the corresponding constitutive model. Therefore, in this embodiment, the target model identifier of the constitutive model of the cell can be obtained by acquiring the identifier of the cell elastic modulus prediction model.

[0180] Of course, the target model identifier of the constitutive model of the cell can also be obtained by other means. For example, receiving the target model identifier of the constitutive model of the cell input by the user.

[0181] Step 1304: Obtain target jet parameters according to the cell elastic modulus, the target model identifier, and the pre-stored second correspondence; the second correspondence is the correspondence between the elastic modulus, the model identifier, and the jet parameters.

[0182] In this embodiment, the correspondence between the elastic modulus, the model identifier, and the jet parameters is pre-stored. After obtaining the target model identifier of the constitutive model of the cell and the cell elastic modulus, the second correspondence can be queried according to the cell elastic modulus and the target model identifier to obtain the target jet parameters.

[0183] The second correspondence can also be obtained by numerical simulation and experimental verification methods, which are roughly as follows: For a single cell, for each elastic modulus of each constitutive model, adjust the jet parameters of the jet device, and select the best jet condition from the multiple jet conditions provided by the jet device when working with multiple sets (for example, 90 sets) of jet parameters, and associate and save the model identifier, elastic modulus, and jet parameters corresponding to the best jet condition in the second correspondence.

[0184] Step 1305: Adjust the jet intensity of the jet device for opening holes in the cell according to the target jet parameters.

[0185] In this embodiment, in a scenario where multiple constitutive models of cells can be used, after switching the constitutive model of the cell, the target model identifier of the constitutive model of the cell and the cell elastic modulus can be obtained first, and then the second correspondence can be queried according to the cell elastic modulus and the target model identifier to obtain the target jet parameters. Therefore, even if the constitutive model of the cell is switched, the jet intensity of the jet device for opening holes in the cell can be adjusted conveniently.

[0186] Another exemplary embodiment of the present application also provides a jet control method based on a microchannel. As Figure 14 shown, the jet control method based on the microchannel may include the following steps:

[0187] Step 1401: Obtain first cell deformation data; the first cell deformation data includes cell deformation characteristic data of elastic deformation occurring at at least one moment during the process of the cell passing through the narrowest area of the microchannel.

[0188] Step 1402: Input the first cell deformation data into the trained cell elastic modulus prediction model, so that the cell elastic modulus prediction model outputs the cell elastic modulus.

[0189] In this embodiment, steps 1401 - 1402 are similar to steps 301 - 302, and thus will not be elaborated here.

[0190] Step 1403: Obtain the size data of the cell.

[0191] In this embodiment, since cells have different sizes, the optimal jet intensity for the jet device to perforate cells is also different. Therefore, it is also necessary to determine the target jet parameters according to the size data of the cells.

[0192] In this embodiment, the cell can be photographed by a camera device to obtain a cell image, and then the size data of the cell can be obtained according to the cell image. In this way, the obtained size data of the cell is more targeted, making the adjustment of the jet intensity for perforating the cell more targeted, and enabling the jet intensity for each cell to be accurately controlled.

[0193] In one embodiment, the undeformed cell can be photographed by a camera device to obtain a front view as the cell image, and then the size data of the cell can be obtained according to the cell image. In this way, the data processing is simpler and faster, which can improve the efficiency.

[0194] Step 1404: Obtain the target jet parameters according to the cell elastic modulus, the size data of the cell, and the pre - stored third correspondence; the third correspondence is the correspondence between the elastic modulus, the cell size, and the jet parameters.

[0195] In this embodiment, the correspondence between the elastic modulus, the cell size, and the jet parameters is pre - stored. After obtaining the size data and the cell elastic modulus of the cell, the third correspondence can be queried according to the cell elastic modulus and the size data of the cell to obtain the target jet parameters.

[0196] The third correspondence can also be obtained by numerical simulation and experimental verification methods, which are roughly as follows: For a single cell, given the constitutive model, for each elastic modulus of each cell size, adjust the jet parameters of the jet device, and select the best jet condition from the multiple jet conditions provided by the jet device when operating with multiple groups (for example, 90 groups) of jet parameters, and associate and save the size data, elastic modulus, and jet parameters of the cell corresponding to the best jet condition in the third correspondence.

[0197] Step 1405: Adjust the jet intensity of the jet device for perforating the cell according to the target jet parameters.

[0198] In this embodiment, the size data and elastic modulus of the cell can be obtained first, and then, according to the elastic modulus of the cell and the size data of the cell, the third corresponding relationship is queried to obtain the target jet parameters. Therefore, even if the elastic modulus of the cell and the size of the cell are switched, the jet intensity of the jet device for opening holes in the cell can be conveniently adjusted.

[0199] In this embodiment, the target jet parameters can be obtained according to the elastic modulus of the cell, the size data of the cell, and the pre-stored third corresponding relationship, so as to adjust the jet intensity of the jet device for opening holes in the cell. Therefore, even if the elastic modulus of the cell and the cell size change, the jet intensity of the jet device for opening holes in the cell can be conveniently adjusted. Moreover, in this embodiment, the jet intensity of the jet device for opening holes in the cell can be adjusted more pertinently, and the jet intensity for each cell can be controlled more precisely.

[0200] Another exemplary embodiment of the present application further provides a jet control method based on a microchannel. As Figure 15 shown, the jet control method based on the microchannel may include the following steps:

[0201] Step 1501, obtain the first cell deformation data; the first cell deformation data includes the cell deformation characteristic data of the cell undergoing elastic deformation at at least one moment during the process of passing through the narrowest area of the microchannel.

[0202] Step 1502, input the first cell deformation data into the trained cell elastic modulus prediction model so that the cell elastic modulus prediction model outputs the cell elastic modulus.

[0203] In this embodiment, steps 1501-1502 are similar to steps 301-302 and will not be elaborated here.

[0204] Step 1503, obtain the target model identifier of the constitutive model of the cell.

[0205] In this embodiment, step 1503 is similar to step 1303 and will not be elaborated here.

[0206] Step 1504, obtain the size data of the cell.

[0207] In this embodiment, when the cell sizes are different, the optimal jet intensities of the jet device for opening holes in the cells are also different. Therefore, it is also necessary to determine the target jet parameters according to the size data of the cells.

[0208] In this embodiment, the target category of the cell can be obtained first, and according to the target category and the fifth corresponding relationship, the size data of the cell can be obtained, where the fifth corresponding relationship is the corresponding relationship between the cell category and the cell size. Among them, the way to obtain the target category of the cell can be: receiving the target category of the cell input by the user. It can also be: the cell can be photographed by a camera device to obtain a cell image, and then, the target category of the cell can be obtained according to the cell image.

[0209] Step 1505: Obtain target jet parameters according to the cell elastic modulus, the target model identifier, the size data of the cell, and the pre-stored fourth corresponding relationship; the fourth corresponding relationship is the corresponding relationship between the elastic modulus, the model identifier, the cell size, and the jet parameters.

[0210] In this embodiment, after obtaining the cell elastic modulus, the target model identifier, and the size data of the cell, the fourth corresponding relationship can be queried according to the cell elastic modulus, the target model identifier, and the size data of the cell to obtain the target jet parameters.

[0211] The fourth corresponding relationship can also be obtained by the method of numerical simulation and experimental verification, which is roughly as follows: for a single cell, for each elastic modulus of each constitutive model for each cell size, adjust the jet parameters of the jet device, and select the best jet condition from the multiple jet conditions provided by the jet device when operating under multiple groups (for example, 90 groups) of jet parameters, and associate and save the size data, model identifier, elastic modulus, and jet parameters of the cell corresponding to the best jet condition in the fourth corresponding relationship.

[0212] Step 1506: Adjust the jet intensity of the jet device for opening holes in the cell according to the target jet parameters.

[0213] In this embodiment, the target jet parameters can be obtained according to the cell elastic modulus, the target model identifier, the size data of the cell, and the pre-stored fourth corresponding relationship to adjust the jet intensity of the jet device for opening holes in the cell. Therefore, even if the constitutive model and the cell elastic modulus of the cell are switched and the cell size also changes, the jet intensity of the jet device for opening holes in the cell can be conveniently adjusted. Moreover, in this embodiment, the jet intensity of the jet device for opening holes in the cell can be adjusted more pertinently, and the jet intensity for each cell can be controlled more precisely.

[0214] Figure 16 It is a block diagram of a jet control device based on a microchannel shown according to an exemplary embodiment. As Figure 16 shown, in this embodiment, the jet control device based on the microchannel includes:

[0215] An acquisition module 161, configured to acquire the cell elastic modulus before the cell enters the jet region of the microchannel;

[0216] An adjustment module 162, configured to adjust the jet intensity of the jet device for perforating cells according to the cell elastic modulus, so that the cell membrane tension of the cells is between the perforation threshold and the rupture threshold, and the jet device is located in the jet region.

[0217] In one embodiment, the cross-sectional areas of at least two places of the microchannel are different, and the inner diameter of the narrowest area of the microchannel is greater than the cell diameter and less than twice the cell diameter, so as to prevent the cells from being directly extruded by the microchannel during the process of passing through the narrowest area, and only allow a single cell to pass through the narrowest area each time; after the cells pass through the narrowest area, they enter the jet region. As Figure 17 shown, the obtaining module 161 includes:

[0218] An obtaining sub-module 1611, configured to obtain first cell deformation data; the first cell deformation data includes cell deformation characteristic data of the cells that undergo elastic deformation at least at one moment during the process of passing through the narrowest area;

[0219] A prediction sub-module 1612, configured to input the first cell deformation data into a trained cell elastic modulus prediction model, so that the cell elastic modulus prediction model outputs the cell elastic modulus.

[0220] An embodiment of the present application also provides an electronic device, including a processor and a memory; the memory is used to store a computer program executable by the processor; the processor is used to execute the computer program in the memory to implement the jet control method based on a microchannel in any of the above embodiments.

[0221] An embodiment of the present application also provides a computer-readable storage medium, when the executable computer program in the storage medium is executed by a processor, it can implement the jet control method based on a microchannel in any of the above embodiments.

[0222] Regarding the device in the above embodiments, the specific manner in which the processor performs operations has been described in detail in the embodiments related to the method, and will not be elaborated here.

[0223] Figure 18 is a block diagram of an electronic device shown according to an exemplary embodiment. For example, the electronic device 1800 may be provided as a server. Refer to Figure 18, Device 1800 includes a processing component 1822, which further includes one or more processors, and memory resources represented by a memory 1832 for storing instructions executable by the processing component 1822, such as application programs. The application programs stored in the memory 1832 may include one or more modules each corresponding to a set of instructions. In addition, the processing component 1822 is configured to execute instructions to perform the above-described microchannel-based jet control method.

[0224] Device 1800 may also include a power component 1826 configured to perform power management of the device 1800, a wired or wireless network interface 1850 configured to connect the device 1800 to a network, and an input / output (I / O) interface 1858. Device 1800 may operate based on an operating system stored in the memory 1832, such as Windows ServerTM, MacOS XTM, UnixTM, LinuxTM, FreeBSDTM or the like.

[0225] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as the memory 1832 including instructions, and the above instructions can be executed by the processing component 1822 of the device 1800 to complete the above method. For example, the non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0226] In the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance. The term "plurality" refers to two or more, unless otherwise clearly defined.

[0227] The above description of the embodiments is to enable those of ordinary skill in the art to understand and apply the present application. Those skilled in the art can obviously make various modifications to these embodiments easily and apply the general principles described herein to other embodiments without creative efforts. Therefore, the present application is not limited to the embodiments herein, and the improvements and modifications made by those skilled in the art within the scope and spirit of the present application disclosed are within the scope of the present application.

Claims

1. A jet control method based on a microchannel, characterized in that, Comprising: Before the cell enters the jet region of the microchannel, obtaining the elastic modulus of the cell; According to the elastic modulus of the cell, adjusting the jet intensity of the jet device for opening a hole in the cell so that the cell membrane tension is between the opening threshold and the rupture threshold, and the jet device is located in the jet region; The cross-sectional areas of at least two places of the microchannel are different, and the inner diameter of the narrowest region of the microchannel is greater than the cell diameter and less than twice the cell diameter, so as to prevent the cell from being directly squeezed by the microchannel during the process of passing through the narrowest region, and only allowing a single cell to pass through the narrowest region each time; The cell enters the jet region after passing through the narrowest region; Before the cell enters the jet region of the microchannel, obtaining the elastic modulus of the cell includes: Obtaining first cell deformation data; the first cell deformation data includes cell deformation characteristic data of elastic deformation occurring at least at one moment during the process of the cell passing through the narrowest region; Inputting the first cell deformation data into a trained cell elastic modulus prediction model so that the cell elastic modulus prediction model outputs the cell elastic modulus; The cell elastic modulus prediction model is a fully connected neural network or a convolutional neural network. When the cell elastic modulus prediction model is a fully connected neural network, the first cell deformation data further includes the pressure information at the entrance of the narrowest region; the cell deformation characteristic data includes at least one of cell contour data, elongation index, non-roundness, curvature ratio, relative cell size, and reciprocal of passing time; When the cell elastic modulus prediction model is a convolutional neural network, the first cell deformation data is a cell image; the cell image includes the front view and top view of the cell; When the cell deformation characteristic data includes cell contour data, the cell contour data is the coordinates of the contour points on the cell contour in the cell image; for each moment, the cell contour data includes the first contour data of the front view of the cell and the second contour data of the top view of the cell.

2. The microchannel-based jet control method according to claim 1, characterized in that, According to the elastic modulus of the cell, adjusting the jet intensity of the jet device for opening a hole in the cell includes: Obtaining target jet parameters according to the elastic modulus of the cell and a pre-stored first correspondence relationship; the first correspondence relationship is the correspondence relationship between the elastic modulus and the jet parameters; Adjusting the jet intensity of the jet device for opening a hole in the cell according to the target jet parameters.

3. The jet control method based on a microchannel according to claim 1, characterized in that Before adjusting the jet intensity of the jet device for opening a hole in the cell according to the elastic modulus of the cell, it includes: Obtaining the target model identifier of the constitutive model of the cell; According to the elastic modulus of the cell, adjusting the jet intensity of the jet device for opening a hole in the cell includes: Obtaining target jet parameters according to the elastic modulus of the cell, the target model identifier, and a pre-stored second correspondence relationship; the second correspondence relationship is the correspondence relationship between the elastic modulus, the model identifier, and the jet parameters; Adjusting the jet intensity of the jet device for opening a hole in the cell according to the target jet parameters.

4. The jet control method based on a microchannel according to claim 1, wherein, Before adjusting the jet intensity of the jet device for opening a hole in the cell according to the elastic modulus of the cell, it includes: Obtaining the size data of the cell; Adjusting the jet intensity of the jet device for perforating cells according to the cell elastic modulus includes: Obtaining target jet parameters according to the cell elastic modulus, the size data, and a pre-stored third correspondence relationship; the third correspondence relationship is the correspondence relationship between the elastic modulus, cell size, and jet parameters; Adjusting the jet intensity of the jet device for perforating cells according to the target jet parameters.

5. The jet control method based on a microchannel according to claim 1, wherein Before adjusting the jet intensity of the jet device for perforating cells according to the cell elastic modulus, it includes: Obtaining the target model identifier of the constitutive model of the cell; Obtaining the size data of the cell; Adjusting the jet intensity of the jet device for perforating cells according to the cell elastic modulus includes: Obtaining target jet parameters according to the cell elastic modulus, the target model identifier, the size data, and a pre-stored fourth correspondence relationship; the fourth correspondence relationship is the correspondence relationship between the elastic modulus, model identifier, cell size, and jet parameters; Adjusting the jet intensity of the jet device for perforating cells according to the target jet parameters.

6. The microchannel-based jet control method according to claim 4 or 5, characterized in that Obtaining the size data of the cell includes: Taking a photo of the cell through a camera device to obtain the cell image; Obtaining the size data of the cell according to the cell image.

7. The microchannel-based jet control method according to claim 4 or 5, characterized in that Obtaining the size data of the cell includes: Obtaining the target category of the cell; Obtaining the size data of the cell according to the target category and a fifth correspondence relationship, and the fifth correspondence relationship is the correspondence relationship between the cell category and the cell size.

8. The jet control method based on a microchannel according to any one of claims 2 to 5, characterized in that The target jet parameters include a target jet amplitude and a target jet frequency.

9. A jet control device based on a microchannel, characterized in that, It includes: An acquisition module configured to acquire the cell elastic modulus before the cell enters the jet region of the microchannel; An adjustment module configured to adjust the jet intensity of the jet device for perforating cells according to the cell elastic modulus so that the cell membrane tension is between the perforation threshold and the rupture threshold, and the jet device is located in the jet region; The cross-sectional area of at least two places of the microchannel is different, and the inner diameter of the narrowest region of the microchannel is greater than the cell diameter and less than twice the cell diameter to prevent the cell from being directly squeezed by the microchannel during the process of passing through the narrowest region, and only one cell is allowed to pass through the narrowest region each time; The cell enters the jet region after passing through the narrowest region; The acquisition module includes: An acquisition sub-module configured to acquire first cell deformation data; the first cell deformation data includes cell deformation characteristic data of the cell undergoing elastic deformation at at least one moment during the process of passing through the narrowest region; A prediction sub-module configured to input the first cell deformation data into a trained cell elastic modulus prediction model so that the cell elastic modulus prediction model outputs the cell elastic modulus; The cell elastic modulus prediction model is a fully connected neural network or a convolutional neural network. When the cell elastic modulus prediction model is a fully connected neural network, the first cell deformation data further includes the pressure information at the entrance of the narrowest region; the cell deformation feature data includes at least one of cell contour data, elongation index, non-circularity, curvature ratio, relative cell size, and reciprocal of passage time. When the cell elastic modulus prediction model is a convolutional neural network, the first cell deformation data is a cell image; the cell image includes the front view and top view of the cell. When the cell deformation feature data includes cell contour data, the cell contour data is the coordinates of the contour points on the cell contour in the cell image; for each moment, the cell contour data includes the first contour data of the front view of the cell and the second contour data of the top view of the cell.

10. An electronic device, characterized in that, It includes a memory and a processor. The memory is used to store the computer program executable by the processor; the processor is used to execute the computer program in the memory to implement the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the executable computer program in the storage medium is executed by the processor, it can implement the method according to any one of claims 1 to 8.

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