Cytokinetic analysis method, electronic equipment and storage medium

Abstract

The invention relates to the field of biological medicine, and provides a cytokinetic analysis method, which is characterized in that a plurality of sections are registered to obtain a plurality of registered sections, the plurality of sections belong to the same tissue, and the plurality of registered sections are located in the same space coordinate system; constructing a three-dimensional model of the tissue on the basis of the space coordinate information of each slice in the plurality of registered slices; and performing kinetic analysis on the tissue based on the three-dimensional model, wherein the kinetic analysis comprises at least one of morphological analysis and geometric analysis. By utilizing the method, three-dimensional kinetic analysis of tissues or organs of an organism can be realized based on continuous slicing.

Description

Technical Field

[0001] The present application relates to the field of biomedicine technology, and in particular to a cell dynamics analysis method, an electronic device and a storage medium. Background Art

[0002] In the related technologies, most of the cell dynamics analysis methods are spatial transcriptomic analysis methods based on two-dimensional space, which can only obtain the transcriptomic analysis results of cells in two-dimensional space. However, since the tissues and organs of actual organisms are in three-dimensional space, the analysis results obtained by spatial transcriptomic analysis in two-dimensional space will lack the three-dimensional spatial information of cells, and cannot provide a basis for obtaining more accurate biological discoveries. Summary of the invention

[0003] In view of the above, it is necessary to propose a cell dynamics analysis method, electronic device and storage medium, which can realize three-dimensional dynamics analysis of tissues or organs of organisms based on continuous sections.

[0004] An embodiment of the present application provides a cell dynamics analysis method, the method comprising: registering multiple slices to obtain multiple registered slices, wherein the multiple slices belong to the same tissue and the multiple registered slices are in the same spatial coordinate system; constructing a three-dimensional model of the tissue based on the spatial coordinate information of each slice in the multiple registered slices; and performing dynamics analysis on the tissue based on the three-dimensional model, the dynamics analysis comprising at least one of morphological analysis and geometric analysis.

[0005] In one embodiment, the registering of the multiple slices to obtain the registered slices includes: arranging the multiple slices according to the adjacent order in the tissue; based on the optimal transmission method, using the gene expression information of each slice and the initial coordinate information of each slice, registering every two adjacent slices in pairs; taking the spatial coordinate system of the first slice of all the slices after the pairwise registration as the reference system, and sequentially rigidly transforming the spatial coordinate system of each slice after the first slice, so that the spatial coordinate systems of all slices are transformed to the reference system, and obtaining the spatial coordinate information of each slice in the same spatial coordinate system.

[0006] In one embodiment, the pairwise registration of every two adjacent slices includes: determining an optimal transfer probability matrix of the optimal transmission method, and minimizing a cost function of the optimal transmission method.

[0007] In one embodiment, the cost function is expressed as:

[0008]

[0009] Wherein, F represents the cost function; I, I′∈{1, 2, ..., t} represent the serial numbers of two adjacent slices, and I≠I′, t represents a positive integer; cell i and cell k are two cells on slice I, cell j and cell l are two cells on slice I′; S I = {G I , CO I} represents the feature set of the slice I, G I ∈N p×n represents the gene expression matrix of the slice I, N represents a natural number, p represents the total number of genes in the slice I, n represents the total number of cells on the slice I, G I The elements in are represented as represents the gene expression column vector corresponding to cell i in the slice i; CO I represents the coordinate matrix of the slice I, CO I ∈N 2×n , 2 represents two directions in the two-dimensional plane; represents the transition probability matrix, π ij represents the transition probability between cell i in slice I and cell j in slice I′, π kl represents the transition probability between the cell k in the slice I and the cell l in the slice I′; R + represents a positive real number, c represents the transfer cost function between cells, represents the transfer cost between cell i in slice I and cell j in slice I′; D∈R + n×n , D represents the distance matrix, D I represents the distance matrix between cells in the slice I, D I The element is represents the distance between cell i and cell k in the slice I; D I′ represents the distance matrix between cells in the slice I′, D I′ The element is represents the distance between cell j and cell l in the slice I′; α∈(0,1) represents a preset weight coefficient.

[0010] In one embodiment, constructing the three-dimensional model of the tissue based on the spatial coordinate information of each slice in the multiple slices after the alignment includes: constructing a three-dimensional point cloud model according to the spatial coordinate information of multiple points of each slice after the alignment; and constructing a three-dimensional mesh model of the tissue based on the three-dimensional point cloud model.

[0011] In one embodiment, the spatial coordinate information of the multiple points of each slice includes: the coordinates of the center point of each cell in each slice, and the coordinates of the edge points of each slice; constructing the three-dimensional mesh model of the tissue based on the three-dimensional point cloud model includes: constructing a three-dimensional mesh model of each cell based on the coordinates of the center point of each cell and predetermined geometric shape parameters of each cell.

[0012] In one embodiment, before performing dynamic analysis on the tissue based on the three-dimensional model, the method also includes: obtaining two three-dimensional models corresponding to two time points of the tissue during development; aligning two spatial coordinate systems where the two three-dimensional models are located, including: performing a rigid transformation on a second spatial coordinate system where the three-dimensional model at the later time point is located according to a first spatial coordinate system where the three-dimensional model at the earlier time point is located, so that the two three-dimensional models are in the same spatial coordinate system; performing the morphological analysis on the cells in the tissue based on the two aligned three-dimensional models, and the morphological analysis includes analyzing the morphological changes of the cells in the two three-dimensional models.

[0013] In one embodiment, the dynamic analysis of the tissue based on the three-dimensional model includes: constructing a morphological vector field of any point in the tissue at an earlier time point based on the two aligned three-dimensional models, including: determining a vector-valued function of any point, the independent variable of the vector-valued function being the coordinates of any point, and the dependent variable of the vector-valued function being the migration speed of any point; performing the geometric analysis based on the morphological vector field, the geometric analysis including: calculating one or more of the following parameters at any point: Jacobian matrix, curl, acceleration, curvature, and torsion.

[0014] An embodiment of the present application provides a cell dynamics analysis device, which includes: a slice registration module, which is used to register multiple slices to obtain multiple registered slices, wherein the multiple slices belong to the same tissue and the multiple registered slices are in the same spatial coordinate system; a model construction module, which is used to construct a three-dimensional model of the tissue based on the spatial coordinate information of each slice in the multiple registered slices; and a dynamics analysis module, which is used to perform dynamics analysis on the tissue based on the three-dimensional model, and the dynamics analysis includes at least one of morphological analysis and geometric analysis.

[0015] An embodiment of the present application provides an electronic device, which includes a processor and a memory, wherein the processor is used to implement the cell dynamics analysis method when executing a computer program stored in the memory.

[0016] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the cell dynamics analysis method is implemented.

[0017] In summary, the cell dynamics analysis method described in the present application can align multiple slices of the same tissue to the same spatial coordinate system, and then construct a three-dimensional model of the tissue or the organ based on the spatial coordinate information of the aligned slices, and perform three-dimensional dynamics analysis on the cells in the tissue or the organ based on the three-dimensional model, which can improve the accuracy of three-dimensional reconstruction and downstream analysis of continuous slices of the spatial group, and provide a basis for obtaining more accurate research results on problems such as tissue development. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a structural diagram of an electronic device provided in one embodiment of the present application.

[0019] Figure 2 It is a flow chart of a cell dynamics analysis method provided in one embodiment of the present application.

[0020] Figure 3 This is a flow chart for registering multiple slices provided by an embodiment of the present application.

[0021] Figure 4 This is a flowchart of building a three-dimensional model provided by an embodiment of the present application.

[0022] Figure 5 This is an example diagram of aligning two three-dimensional models provided by an embodiment of the present application.

[0023] Figure 6 It is a flow chart of dynamic analysis based on a three-dimensional model provided in one embodiment of the present application.

[0024] Figure 7 This is an example diagram of a three-dimensional model provided in an embodiment of the present application.

[0025] Figure 8 This is an example diagram of visualization of dynamic analysis based on a three-dimensional model provided in one embodiment of the present application.

[0026] Fig. 9 is a structural diagram of a cell dynamics analysis device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to more clearly understand the above-mentioned purposes, features and advantages of the present application, the present application is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing the embodiments in one embodiment and are not intended to limit this application.

[0029] It should be noted that in this application, "at least one" means one or more, and "more than one" means two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The terms "first", "second", "third", "fourth", etc. (if any) in the specification, claims and drawings of this application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0030] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way. The following embodiments and features in the embodiments may be combined with each other without conflict.

[0031] Most of the related cell dynamics analysis methods are spatial transcriptomic analysis methods based on two-dimensional space, which can only obtain the transcriptomic analysis results of cells in two-dimensional space. However, since the tissues and organs of actual organisms are in three-dimensional space, the analysis results obtained by spatial transcriptomic analysis in two-dimensional space will lack the three-dimensional spatial information of cells, and cannot provide a basis for obtaining more accurate biological discoveries.

[0032] To solve the above problems, an embodiment of the present application provides a cell dynamics analysis method, which can align multiple slices of the same tissue or the same organ to the same spatial coordinate system, and then construct a three-dimensional model of the tissue or the organ based on the spatial coordinate information of the aligned slices, and perform three-dimensional dynamics analysis on the cells in the tissue or the organ based on the three-dimensional model, which can improve the accuracy of three-dimensional reconstruction and downstream analysis of continuous slices of the spatial group, and provide a basis for obtaining more accurate research results on problems such as tissue development.

[0033] The cell dynamics analysis method provided in the embodiments of the present application is applied to electronic devices, such as Figure 1As shown, it is a structural diagram of an electronic device provided in an embodiment of the present application. The electronic device may be a computer, a server, a laptop computer, a mobile phone terminal or other device. In some embodiments, the electronic device 1 is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, a dedicated integrated circuit, a programmable gate array, a digital processor, and an embedded device. The electronic device 11 may also include other external devices, for example, input and output devices such as a keyboard, a mouse, a remote control, a display, a touchpad or a voice control device.

[0034] It should be noted that the electronic device 1 is only an example, and other existing or future electronic products that are suitable for the present application should also be included in the protection scope of the present application and included here by reference.

[0035] The electronic device 1 includes, but is not limited to: a memory 11 , at least one processor 12 , at least one communication bus 13 and a transceiver 14 .

[0036] Figure 1 The structure of the electronic device shown does not constitute a limitation of the embodiments of the present application, and may be either a bus structure or a star structure. The electronic device 1 may also include more or less other hardware or software than shown in the figure, or a different component arrangement.

[0037] Figure 2 : is a flow chart of a cell dynamics analysis method provided in an embodiment of the present application. The cell dynamics analysis method is applied in electronic devices, such as Figure 1 The electronic device 1 specifically includes the following steps. According to different requirements, the order of the steps in the flowchart can be changed, and some steps can be omitted.

[0038] S21, registering the multiple slices to obtain the multiple registered slices.

[0039] In one embodiment, a two-dimensional spatial transcriptome analysis method is a method that combines high-throughput single-cell RNA sequencing and tissue slice imaging technology, and the main steps include: (1) sample sectioning: after freezing or paraffin embedding the tissue sample, a thin layer of tissue section is prepared using microdissection technology; (2) RNA sequencing: the tissue section is transferred to a single-cell RNA sequencing chip, high-throughput single-cell RNA sequencing is performed, and the gene expression profile data of each cell is obtained; (3) data analysis: the obtained gene expression profile data is pre-processed, quality controlled and analyzed to identify the type of clustered cells, identify cell-specific gene expression and explore cell-to-cell interactions; (4) spatial reconstruction: the spatial position of each cell in the tissue is reconstructed using RNA sequencing data to obtain a two-dimensional spatially resolved transcriptome map; (5) result interpretation: based on the two-dimensional spatially resolved transcriptome map, the relationship between cell differentiation, tissue structure and function can be further analyzed, the molecular mechanism of disease development can be revealed, and new ideas and methods can be provided for precision medicine.

[0040] In one embodiment, the preceding steps of the cell dynamics analysis method provided in the embodiment of the present application include the above steps (1)-(4), but improvements are made based on steps (4)-(5), which will be specifically described in conjunction with the subsequent steps.

[0041] In one embodiment, the multiple slices belong to the same tissue. It is understandable that the multiple slices may also belong to the same organ or the same embryo, and the following content will mainly be described using tissue as an example.

[0042] Since the multiple slices may be obtained from different time nodes and applied to different research scenarios, although the proximity order of the multiple slices in the tissue can be obtained according to the chronological order of acquisition, it is not easy to directly arrange the multiple slices in proximity order to obtain the arrangement position of the slices in the tissue.

[0043] Based on the above problems, based on the similarity of gene expression of any two cells between every two adjacent slices and the distance between any two cells in each slice, the idea of ​​the optimal transmission method (Fused-Gromov-Wasserstein, FGW) can be used to align multiple slices according to the cell development law of the tissue. When the closest cells between every two adjacent slices can be aligned, the alignment of every two adjacent slices can be achieved. After that, the coordinate system of all slices is converted to the same coordinate system, which is convenient for constructing a three-dimensional model of the tissue based on multiple slices in the same coordinate system in the subsequent steps, and realizing the three-dimensional downstream analysis of cells in the tissue. Among them, the measurement of whether cells are similar can be based on the physical distance between cells and the similarity between gene expression.

[0044] In one embodiment, the specific process of registering multiple slices can be referred to below for Figure 3 Detailed description of the process shown.

[0045] S22, constructing a three-dimensional model of the tissue based on the spatial coordinate information of each slice in the registered multiple slices.

[0046] In one embodiment, the spatial coordinate information includes spatial coordinate information of multiple points of each slice, including but not limited to: the coordinates of the center point of each cell in each slice, the coordinates of the edge points of each slice, etc. The edge points of each slice can be multiple points set by the user, or can be points determined at preset lengths in the edge of the slice identified by an image edge detection algorithm.

[0047] Specifically, referring to the description in step (4) in step S21, before performing slice registration, the center point coordinates of each cell in the coordinate system of the slice to which it belongs can be obtained. At this time, the center point coordinates may be two-dimensional coordinates.

[0048] After all slices are registered, the center point coordinates of each cell in each slice are converted to the same three-dimensional space coordinate system, which may include: arranging the two-dimensional plane where each slice is located according to the arrangement position in the original tissue, thereby converting the center point coordinates of each cell to the three-dimensional space where the original tissue is located. Therefore, the center point coordinates of all cells after registration can be expressed using three-dimensional coordinates in the same space coordinate system. Similarly, the coordinates of the edge points of each slice can also be expressed as three-dimensional coordinates in the same space coordinate system.

[0049] In one embodiment, after determining the coordinates of the center point and the edge point of each cell in the tissue in the same three-dimensional coordinate system, a three-dimensional model of each cell and a three-dimensional model of the entire tissue can be generated based on the geometric shape of each cell, thereby facilitating the three-dimensional dynamic analysis of the cells in subsequent steps.

[0050] In one embodiment, the specific process of constructing a three-dimensional model can be referred to below for Figure 4 Detailed description of the process shown.

[0051] S23, performing dynamic analysis on the tissue based on the three-dimensional model.

[0052] In one embodiment, in order to perform downstream analysis on cells in the tissue, before performing kinetic analysis on the tissue based on the three-dimensional model, the method further includes the following (11)-(13):

[0053] (11) Obtain two three-dimensional models corresponding to two time points during the development of the tissue.

[0054] In one embodiment, since the three-dimensional model of the tissue is constructed based on slices, it is impractical to obtain two three-dimensional models corresponding to two time points of the tissue during development in a natural environment. However, in a laboratory, after controlling the culture conditions and determining the acceptable error range, it is possible to obtain two three-dimensional models corresponding to two time points of the tissue during development, such as cloning technology.

[0055] In one embodiment, the two time points can be selected according to the developmental characteristics of the tissue. For ease of understanding, the tissue is described with Drosophila embryo as an example: the first time point can be determined as the 7th to 9th hour of Drosophila embryonic development. At this stage, Drosophila embryos will experience processes such as neurula formation, cell differentiation, and somite progenitor cell development. These processes are important factors in determining the development of the embryonic nervous system and are also critical periods that affect adult behavior and function; the second time point is determined as the 9th to 10th hour of Drosophila embryonic development. At this stage, the embryo will experience processes such as the formation of sensory hair, differentiation of feet, and formation of oral plates. These processes have an important impact on the subsequent organ morphology and functional development of the embryo. Therefore, selecting these two time nodes is more representative and valuable for research on Drosophila embryos.

[0056] (12) Aligning the two spatial coordinate systems where the two three-dimensional models are located, including: performing a rigid transformation on the second spatial coordinate system where the three-dimensional model at the later time point is located according to the first spatial coordinate system where the three-dimensional model at the earlier time point is located, so that the two three-dimensional models are in the same spatial coordinate system.

[0057] In one embodiment, since the number, volume, etc. of cells in the tissue at two time nodes change, there will also be significant changes between the corresponding two three-dimensional models. In order to perform downstream analysis of the cells based on the two three-dimensional models, the two three-dimensional models need to be aligned so that the two three-dimensional models are in the same three-dimensional coordinate system.

[0058] Please refer to the description in the subsequent step S32. Since the weight of the slice registration in this case is focused on the similarity of gene expression based on the optimal transmission method during slice registration, the influence of morphological changes in the cell development process on the alignment of the two three-dimensional models can be reduced, so that the two three-dimensional models are in the same spatial coordinate system.

[0059] In addition, referring to the description in the subsequent step S33, the alignment of the two three-dimensional models can be achieved by aligning every two corresponding points in the two three-dimensional models based on the generalized Procrustes Analysis with Weights (GPA) technology. The GPA technology can align two similar but not identical point sets corresponding to the two three-dimensional models, and find a common coordinate system through rigid transformations such as rotation, scaling and translation, so that the positions of the objects in the two point sets in the coordinate system are closest.

[0060] For example Figure 5 As shown, it is an example diagram of aligning two three-dimensional models provided by an embodiment of the present application, wherein the three-dimensional space is represented as XYZ, the upper point set belongs to the three-dimensional model of the fruit fly embryonic development at 7-9 hours, and the lower point set belongs to the three-dimensional model of the fruit fly embryonic development at 9-10 hours, and the connecting line between the upper and lower point sets is used to indicate the correspondence between the two corresponding points in the upper point set and the lower point set.

[0061] (13) Performing a morphological analysis on the cells in the tissue based on the two aligned three-dimensional models, wherein the morphological analysis includes analyzing the morphological changes of the cells in the two three-dimensional models.

[0062] In one embodiment, the morphological changes include, but are not limited to, changes in cell length, volume, surface area, density, distribution, etc. Morphological analysis of cells can reveal morphological changes of cells during organ or embryonic development.

[0063] In one embodiment, the dynamic analysis includes at least one of morphological analysis and geometric analysis. The specific process of dynamic analysis of tissue based on three-dimensional model can be referred to the following for Figure 6 Detailed description of the process shown.

[0064] In one embodiment, Figure 3 FIG. 1 is a flowchart of registering multiple slices provided by an embodiment of the present application, which specifically includes the following steps:

[0065] S31, arranging the plurality of slices according to the adjacent order in the tissue.

[0066] In one embodiment, in order to align the slices, the slices may be arranged in a neighboring order.

[0067] S32, based on the optimal transmission method, using the gene expression information of each slice and the initial coordinate information of each slice, perform pairwise registration on every two adjacent slices.

[0068] In one embodiment, referring to the description in step S21, the gene expression information includes gene expression spectrum data obtained by RNA sequencing; the initial coordinate information includes the two-dimensional center point coordinates of each cell in each slice.

[0069] In one embodiment, the pairwise registration of every two adjacent slices includes: determining the optimal transfer probability matrix of the optimal transmission method based on the similarity of gene expression of any two cells between every two adjacent slices and the distance between any two cells in each slice, and minimizing the cost function of the optimal transmission method.

[0070] In one embodiment, the cost function is expressed as:

[0071]

[0072] Wherein, F represents the cost function;

[0073] I, I′∈{1, 2, ..., t} represent the numbers of two adjacent slices, and I≠I′, t represents a positive integer;

[0074] Cell i and cell k are two cells on slice I, and cell j and cell l are two cells on slice I′;

[0075] S I = {G I , CO I} represents the feature set of the slice I, G I ∈N p×n represents the gene expression matrix of the slice I, N represents a natural number, p represents the total number of genes in the slice I, n represents the total number of cells on the slice I, G I The elements in are represented as represents the gene expression column vector corresponding to cell i in the slice i; CO I represents the coordinate matrix of the slice I, COI ∈N 2×n , 2 represents two directions in the two-dimensional plane;

[0076] represents the transition probability matrix, π ij represents the transition probability between cell i in slice I and cell j in slice I′, π kl represents the transition probability between the cell k in the slice I and the cell l in the slice I′;

[0077] R + represents a positive real number, c represents the transfer cost function between cells, represents the transfer cost between the cell i in the slice I and the cell j in the slice I′;

[0078] D∈R + n×n , D represents the distance matrix, D I represents the distance matrix between cells in the slice I, D I The element is represents the distance between cell i and cell k in the slice I; D I′ represents the distance matrix between cells in the slice I′, D I′ The element is represents the distance between cell j and cell l in the slice I′;

[0079] α∈(0,1), represents the preset weight coefficient.

[0080] In one embodiment, the above formula is based on the idea of ​​the optimal transmission method, using two cells i and k that are closer in slice I to find two cells j and l that are more similar in the adjacent slice I', which can maintain the local topological structure when registering between slices and improve the accuracy of slice registration. Among them, the measurement of whether cells are similar is based on the physical distance between cells and the similarity between gene expressions.

[0081] In one embodiment, the function Can be The Euclidean distance between them. The transition probability π ij It can also be understood as the probability that cell i in the slice I is paired or matched with cell j in the slice I′; the transition probability π ij The larger the value is, the higher the match degree between cell i in slice I and cell j in slice I′ is and the more similar they are.

[0082] After solving the cost function min F that minimizes the optimal transmission method, it can be ensured that the most similar cells between two adjacent slices are aligned, and two close cells in one slice can be mapped to two close cells in another slice.

[0083] In one embodiment, the value of α can affect whether slice registration focuses more on the physical distance between cells or the similarity between gene expressions. Specifically, the smaller the value of α, the more slice registration relies on the similarity between gene expressions; the larger the value of α, the more slice registration relies on the physical distance between cells.

[0084] In one embodiment, referring to the description in step S012, since the number and volume of cells at different time nodes change, considering cell migration or differentiation, the physical distance of cells at different time nodes will be quite different. When aligning, the focus is on the distance between the physical distances of cells, which will affect the results of the kinetic analysis in the subsequent steps. Therefore, the smaller the value of α in the above formula, the better. For example, the value of α is 0.001, which can reduce the weight of the local topological structure between slices and put more weight on the similarity of gene expression.

[0085] S33, taking the spatial coordinate system of the first slice among all the slices after the pairwise registration as the reference system, and sequentially performing a rigid transformation on the spatial coordinate system of each slice after the first slice, so that the spatial coordinate systems of all slices are transformed to the reference system, and obtaining the spatial coordinate information of each slice in the same spatial coordinate system.

[0086] In one embodiment, referring to the description in step S22, the coordinates of the center point of each cell in the initial coordinate information may be two-dimensional, but in the three-dimensional space composed of multiple slices, the coordinates of a certain direction or dimension (e.g., z dimension) of all cells in the same slice can be regarded as the same. For example, the (x, y, z) coordinates of cell i on slice I are expressed as (100, 200, 10), and the (x, y, z) coordinates of cell k are expressed as (103, 210, 10). It can be seen that the coordinate values ​​of cell i and cell k in the z direction are both 10.

[0087] In one embodiment, the spatial coordinate system of the first slice may be used as the reference system, or the spatial coordinate system of any slice may be selected as the reference system, as long as the spatial coordinate systems of all slices can be transformed into the same reference system.

[0088] In one embodiment, when the spatial coordinate system of the first slice is used as the reference system, the second slice is matched with the first slice, the coordinates of the center point of the cell on the first slice will not change, and the coordinates of the center point of the cell on the second slice will obtain new coordinates after the rigid transformation operation; then the third slice is matched with the second slice, and so on, until all slices are rigidly transformed to the same coordinate system in sequence.

[0089] In one embodiment, the rigid transformation includes rotation and translation, and the formula used includes:

[0090]

[0091] Among them, π ij (k) represents the transition probability matrix between slice k and slice k+1, R represents the rotation matrix, T represents the translation matrix, CO .i (k) represents the coordinates of cell i on slice k, CO .j (k+1) represents the coordinates of cell j on slice k+1, (RCO .j (k+1) +T) represents the coordinates of cell j on slice k+1 after rotation and translation transformation, ||CO .i (k) -(RCO .j (k+1) +T)|| represents coordinates (RCO .j (k+1) +T) and coordinates CO .i (k) The distance between.

[0092] In one embodiment, the above formula is a weighted generalized Procrustes analysis, the purpose of which is to obtain a rotation-translation transformation matrix based on a transition probability matrix, and to minimize the distance between paired cells through coordinate changes. Only in this way can the coordinates of cell j on slice k+1 be rotated and translated to obtain new coordinates of cell i in slice k, thereby achieving the purpose of registration.

[0093] In one embodiment, Figure 4 As shown, it is a flowchart of constructing a three-dimensional model provided by an embodiment of the present application, which specifically includes the following steps:

[0094] S41, constructing a three-dimensional point cloud model according to the spatial coordinate information of multiple points of each slice after registration.

[0095] In one embodiment, referring to the description in step S22, the coordinates of all points in all slices after registration are in the same spatial coordinate system, and each point contains information such as position coordinate information and transition probability with neighboring points. Therefore, each discrete point can be regarded as a point with three-dimensional coordinates in the three-dimensional point cloud model to construct a three-dimensional point cloud model. Figure 7 FIG. 1 is an example diagram of a three-dimensional model provided in an embodiment of the present application. Figure 7 Figure (a) shows the three-dimensional point cloud model.

[0096] S42, constructing a three-dimensional mesh model of the tissue based on the three-dimensional point cloud model.

[0097] In one embodiment, when constructing a three-dimensional mesh model of the tissue based on the three-dimensional point cloud model, the points in the three-dimensional point cloud model can be divided into two categories, the first category being the center points of cells in the tissue, and the second category being points that are not the center points of cells.

[0098] In one embodiment, for the first type of points, constructing the three-dimensional mesh model of the tissue based on the three-dimensional point cloud model includes: constructing a three-dimensional mesh model of each cell based on the center point coordinates of each cell and predetermined geometric shape parameters of each cell.

[0099] Among them, the geometric shape parameters of the cells can be obtained according to the predetermined attributes such as the cell category. For example, the mask of each type of cell can be obtained in advance, and the geometric shape parameters of the cells such as length, width, shape (such as cube, sphere, ellipsoid, etc.) can be determined according to the cell mask.

[0100] After obtaining the geometric shape parameters, the three-dimensional mesh model of each cell can be directly constructed with the center point of the cell as the center point. For example, when it is determined that the cell is spherical and the length of the cell is obtained, the center point of the cell can be used as the center point of the sphere, and half of the length of the cell can be used as the radius to generate the corresponding three-dimensional mesh model of the sphere.

[0101] In one embodiment, for the second type of points, an algorithm capable of generating a three-dimensional surface mesh according to a three-dimensional point cloud data set may be directly used to construct a three-dimensional mesh model, for example, the algorithm includes but is not limited to the MarchingCubes algorithm. The Marching Cubes algorithm divides the three-dimensional point cloud data set into small cubes, applies an isosurface extraction function on each cube, and the isosurface extraction function takes the data values ​​of all vertices in any cube as input and outputs a representation describing how the isosurface passes through the cube to determine how the surface passes through the cube, and finally uses a triangular mesh connecting all edges and intersections to represent the entire surface.

[0102] In one embodiment, when the slice is an organ or embryo composed of tissue, a three-dimensional mesh model of the organ composed of multiple cells can be constructed based on the three-dimensional mesh model of the cells, for example Figure 7 As shown, Figure 7 Figure (b) shows a three-dimensional mesh model containing cells. Figure 7 Figure (c) shows a three-dimensional mesh model of a Drosophila embryo containing organs composed of cells.

[0103] In one embodiment, Figure 6 As shown, it is a flowchart of dynamic analysis based on a three-dimensional model provided in an embodiment of the present application, which specifically includes the following steps:

[0104] S61, constructing a morphological vector field of any point in the tissue at an earlier time point based on the two aligned three-dimensional models.

[0105] In one embodiment, based on the two aligned three-dimensional models, constructing the morphological vector field of any point in the tissue at an earlier time point includes: determining a vector valued function of any point, the independent variable of the vector valued function being the coordinates of any point, and the dependent variable of the vector valued function being the migration speed of any point.

[0106] In one embodiment, in order to better study the development of living organisms, organs will be used as analysis objects below. In other embodiments, embryos and the like may also be used as research objects.

[0107] The velocity vector of each cell migrating during organ development can be expressed as: t =CO t+1 -CO t , where CO t is the coordinate of the center point of any cell in the organ at the previous time point t between the two time points, CO t+1 is the coordinate of the center point of the cell corresponding to any of the cells at the later time point t+1 in the two time points. The corresponding relationship here is determined when the two three-dimensional models are aligned, and CO t+1 is the coordinate after registration and alignment, i.e. CO t+1 With CO t In the same coordinate system. Since the coordinates CO t+1 With CO t is a known parameter, so the v of any cell at time point t can be calculated t .

[0108] In one embodiment, the morphological vector field at each point is reconstructed based on the sparseVFC (Sparse Vector Field Convolution) method. SparseVFC regards each point as a vector and uses a block-based acceleration structure to divide the vector field into multiple small blocks. Each point (such as the center point of a cell) is convolved with the vectors of surrounding points, and only the non-zero elements are convolved, which can reduce the number of convolutions and improve operating efficiency.

[0109] The vector-valued function can be expressed as f: CO∈R 3 →v∈R 3 , that is, f(CO)=v. The vector value function assumes that the morphological changes of organs follow a smooth, differentiable three-dimensional space vector field. By inputting the coordinates of any point at time point t (the earlier of the two time points), the migration speed of this point at time point t during the development process can be output. The loss function of the vector value function can be exemplarily expressed as:

[0110]

[0111] in, CO i is the coordinate of the center point of cell i at time point t, v i is the actual migration velocity of cell i at time point t, n is the total number of cells in the organ, λ is the regularization coefficient, and p i represents the weight of cell i, and σ is the noise parameter.

[0112] The center point of each cell of the organ at time point t is regarded as a fixed point, and a set of discrete points consisting of all fixed points of the organ is used to learn the vector value function f of the continuous morphological migration of the organ. The function f can be exemplarily expressed as the sum of Gaussian kernel functions of fixed points:

[0113]

[0114] Where m represents the number of fixed points. represents the coordinates of the jth fixed point, CO represents the coordinates of any point in the organ, c j ∈R 3 is the coefficient vector, ω is the parameter of the Gaussian kernel, and the EM (Expectation-Maximization) iterative optimization algorithm is used to solve it.

[0115] S62, performing the geometric analysis based on the morphological vector field.

[0116] In one embodiment, the geometric analysis can be performed on any point in the organ based on the vector value function of the morphological vector field at any point in the organ, and the geometric analysis includes but is not limited to: calculating one or more of the following parameters or features (Feature) at any point: Jacobian matrix, curl (or rotation intensity, curl), acceleration, curvature, and torsion.

[0117] In one embodiment, according to the definition of a vector field, any vector field can be represented as the sum of a scalar field and a vector field, and the Jacobian matrix can be used to represent the derivative of the vector field. The Jacobian matrix can be exemplarily represented as:

[0118]

[0119] The Jacobian matrix describes the differential structure of a vector-valued function, reflecting how a small change in the input variable will lead to a change in the output variable. In addition, the dimension of the Jacobian matrix is ​​determined by the input and output variables of the vector-valued function. The vector-valued function f: CO∈R 3 →v∈R 3 , so the Jacobian matrix J is a 3*3 dimensional matrix.

[0120] Specifically, each element in the Jacobian matrix J represents the partial derivative of each output variable (the velocity of each cell) of the vector-valued function with respect to each element in each input variable (the position coordinate of each cell).

[0121] For example, in the OXYZ coordinate system, the coordinate CO of the cell contains elements in three directions (X, Y, Z). The coordinate CO of cell 1 can be exemplarily represented as (X1, Y1, Z1). The migration speed from the previous time point to the next time point also has three directions (X, Y, Z). So for example, the Jacobian matrix J in It represents the influence of the change of the first element X1 in the coordinate CO on the value of the first direction (i.e., X direction) of the velocity f. For another example, the Jacobian matrix J It represents the influence of the change of the second element Y1 in the coordinate CO on the value of the velocity f in the third direction (ie, the Z direction).

[0122] In one embodiment, for a three-dimensional vector field, its divergence is a scalar field. Exemplarily, the trace of the Jacobian matrix is ​​the divergence, that is, the divergence can be expressed as:

[0123]

[0124] Divergence can be used to indicate whether an organ is expanding. Still shrinking

[0125] In one embodiment, for a three-dimensional vector field, its curl is a vector field. Exemplarily, the curl can be expressed as:

[0126]

[0127] In one embodiment, the acceleration and curvature at each point can be calculated by calculating the high-order differentials of f, where acceleration is the differential of velocity and can be exemplarily expressed as:

[0128]

[0129] The curvature can be defined as the derivative of the unit tangent vector (unit velocity) Divide by the length of the tangent vector |v|, which can be represented by:

[0130]

[0131] In one embodiment, the formula used to calculate the twist at each point can be exemplarily expressed as:

[0132]

[0133] Where a represents the acceleration calculated above, and the distortion can quantify the degree of distortion of the three-dimensional model.

[0134] In one embodiment, Figure 8 As shown, it is an example diagram of visualization of dynamic analysis based on a three-dimensional model provided in one embodiment of the present application.

[0135] In one embodiment, the method provided in the embodiment of the present application can align multiple slices of the same tissue or the same organ to the same spatial coordinate system, and then construct a three-dimensional model of the tissue or the organ based on the spatial coordinate information of the aligned slices, and perform three-dimensional dynamic analysis on the cells in the tissue or the organ based on the three-dimensional model, which can improve the accuracy of three-dimensional reconstruction and downstream analysis of continuous slices of the spatial group, and provide a basis for obtaining more accurate research results on problems such as tissue development.

[0136] Fig. 9 It is a structural diagram of the cell dynamics analysis device provided in the embodiment of the present application.

[0137] In some embodiments, the cell dynamics analysis device 90 may include a plurality of functional modules composed of computer program segments. The computer programs of the various program segments in the cell dynamics analysis device 90 may be stored in a memory of an electronic device and executed by at least one processor to perform (see Figure 2Description) Function of cell dynamics analysis.

[0138] In this embodiment, the cell dynamics analysis device 90 can be divided into multiple functional modules according to the functions it performs. The functional modules may include: a slice registration module 901, a model building module 902, and a dynamics analysis module 903. The module referred to in this application refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functional implementation of each module in the cell dynamics analysis device 90 can refer to the above definition of the cell dynamics analysis method, and will not be repeated here.

[0139] The slice registration module 901 is used to register multiple slices to obtain multiple registered slices, wherein the multiple slices belong to the same tissue and the multiple registered slices are in the same spatial coordinate system.

[0140] The model building module 902 is used to build a three-dimensional model of the tissue based on the spatial coordinate information of each slice in the registered multiple slices.

[0141] The dynamic analysis module 903 is used to perform dynamic analysis on the tissue based on the three-dimensional model, and the dynamic analysis includes at least one of morphological analysis and geometric analysis.

[0142] Continuing from the above Figure 1 The memory 11 stores a computer program, and when the computer program is executed by the at least one processor 12, all or part of the steps in the cell dynamics analysis method are implemented. The memory 11 includes a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0143] Furthermore, the computer-readable storage medium may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function, etc.; the data storage area may store data created according to the use of the blockchain node, etc.

[0144] In one embodiment of the present application, the computer readable storage medium stores a computer program, which, when executed by the processor 12, implements the following Figure 2 Alternatively, when the computer program is executed by a processor, the following is achieved: Fig. 9 The functions of each module / unit in the cell dynamics analysis device shown, e.g. Fig. 9 Modules 901-903 in.

[0145] In some embodiments, the at least one processor 12 is the control core (ControlUnit) of the electronic device 1, and uses various interfaces and lines to connect the various components of the entire electronic device 1, and executes or executes the program or module stored in the memory 11, and calls the data stored in the memory 11 to perform various functions of the electronic device 1 and process data. For example, when the at least one processor 12 executes the computer program stored in the memory, it implements all or part of the steps of the cell dynamics analysis method described in the embodiment of the present application; or implements all or part of the functions of the cell dynamics analysis device. The at least one processor 12 can be composed of an integrated circuit, for example, it can be composed of a single packaged integrated circuit, or it can be composed of multiple integrated circuits with the same function or different functions, including one or more central processing units (CPU), microprocessors, digital processing chips, graphics processors, and various control chips. Combination, etc.

[0146] In some embodiments, the at least one communication bus 13 is configured to implement connection communication between the memory 11 and the at least one processor 12, etc.

[0147] Although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 12 through a power management device, so that the power management device can manage charging, discharging, and power consumption. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, camera devices, etc., which will not be repeated here.

[0148] The above-mentioned integrated unit implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, electronic device, or network device, etc.) or a processor to execute part of the method described in each embodiment of the present application.

[0149] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0150] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0151] In addition, each functional module in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0152] It is obvious to those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and that the present application can be implemented in other specific forms without departing from the spirit or basic features of the present application. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present application is limited by the attached claims rather than the above description, so it is intended to include all changes that fall within the meaning and scope of the equivalent elements of the claims in the present application. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "including" does not exclude other units or, and the singular does not exclude the plural. Multiple units or devices stated in the specification can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical solution of the present application may be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present application.

Claims

1. A cell dynamics analysis method, characterized in that: The method comprises: Registering the multiple slices to obtain multiple registered slices, wherein the multiple slices belong to the same tissue and the multiple registered slices are in the same spatial coordinate system; constructing a three-dimensional model of the tissue based on the spatial coordinate information of each slice in the registered multiple slices; A dynamic analysis is performed on the tissue based on the three-dimensional model, wherein the dynamic analysis includes at least one of a morphological analysis and a geometric analysis.

2. The cell dynamics analysis method according to claim 1, characterized in that The registering of the multiple slices to obtain the registered multiple slices includes: Arranging the plurality of slices according to the adjacent order in the tissue; Based on the optimal transmission method, the gene expression information of each slice and the initial coordinate information of each slice are used to perform pairwise registration of every two adjacent slices. The spatial coordinate system of the first slice among all the slices after the pairwise registration is used as the reference system, and the spatial coordinate system of each slice after the first slice is rigidly transformed in turn, so that the spatial coordinate systems of all slices are transformed to the reference system, and the spatial coordinate information of each slice in the same spatial coordinate system is obtained.

3. The cell dynamics analysis method according to claim 2, characterized in that: The pairwise registration of every two adjacent slices comprises: An optimal transition probability matrix of the optimal transmission method is determined, and a cost function of the optimal transmission method is minimized.

4. The cell dynamics analysis method according to claim 3, characterized in that: The cost function is expressed as: Wherein, F represents the cost function; I, I′∈{1,2,…,t} represent the numbers of two adjacent slices, and I≠I′, t represents a positive integer; Cell i and cell k are two cells on slice I, and cell j and cell l are two cells on slice I′; S I = {G I ,CO I } represents the feature set of the slice I, G I ∈N p×n represents the gene expression matrix of the slice I, N represents a natural number, p represents the total number of genes in the slice I, n represents the total number of cells on the slice I, G I The elements in are represented as represents the gene expression column vector corresponding to cell i in the slice i; CO I represents the coordinate matrix of the slice I, CO I ∈N 2×n , 2 represents two directions in the two-dimensional plane; represents the transition probability matrix, π ij represents the transition probability between cell i in slice I and cell j in slice I′, π kl represents the transition probability between the cell k in the slice I and the cell l in the slice I′; R + represents a positive real number, c represents the transfer cost function between cells, represents the transfer cost between the cell i in the slice I and the cell j in the slice I′; D∈R + n×n , D represents the distance matrix, D I represents the distance matrix between cells in the slice I, D I The element is represents the distance between cell i and cell k in the slice I; D I′ represents the distance matrix between cells in the slice I′, D I′ The element is represents the distance between cell j and cell l in the slice I′; α∈(0,1), represents the preset weight coefficient.

5. The cell dynamics analysis method according to claim 1, characterized in that: The constructing of the three-dimensional model of the tissue based on the spatial coordinate information of each slice in the registered multiple slices includes: Construct a three-dimensional point cloud model based on the spatial coordinate information of multiple points of each slice after registration; Based on the three-dimensional point cloud model, a three-dimensional mesh model of the tissue is constructed.

6. The cell dynamics analysis method according to claim 5, characterized in that: The spatial coordinate information of the multiple points of each slice includes: the coordinates of the center point of each cell in each slice, and the coordinates of the edge points of each slice; The constructing of the three-dimensional mesh model of the tissue based on the three-dimensional point cloud model includes: constructing a three-dimensional mesh model of each cell based on the center point coordinates of each cell and predetermined geometric shape parameters of each cell.

7. The cell dynamics analysis method according to claim 1, characterized in that: Before performing dynamic analysis on the tissue based on the three-dimensional model, the method further includes: Obtaining two three-dimensional models corresponding to two time points during the development of the tissue; Aligning the two spatial coordinate systems where the two three-dimensional models are located, including: performing a rigid transformation on a second spatial coordinate system where the three-dimensional model at a later time point is located, based on a first spatial coordinate system where the three-dimensional model at an earlier time point is located, so that the two three-dimensional models are in the same spatial coordinate system; The morphological analysis is performed on the cells in the tissue based on the two aligned three-dimensional models, and the morphological analysis includes analyzing the morphological changes of the cells in the two three-dimensional models.

8. The cell dynamics analysis method according to claim 7, characterized in that: The performing dynamic analysis on the tissue based on the three-dimensional model comprises: Based on the aligned two three-dimensional models, constructing a morphological vector field of any point in the tissue at an earlier time point, comprising: determining a vector valued function of the any point, wherein the independent variable of the vector valued function is the coordinate of the any point, and the dependent variable of the vector valued function is the migration speed of the any point; Based on the morphological vector field, the geometric analysis is performed, and the geometric analysis includes: calculating one or more of the following parameters at any point: Jacobian matrix, curl, acceleration, curvature, twist.

9. An electronic device, characterized in that: The electronic device comprises a processor and a memory, and the processor is used to implement the cell dynamics analysis method according to any one of claims 1 to 8 when executing a computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the cell dynamics analysis method according to any one of claims 1 to 8 is implemented.

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