Cross-scale myocardial cell signal transmission method based on Belosov-Zhabotinsky reaction

Abstract

The invention discloses a cross-scale cardiac muscle cell signal transmission method based on Belosov-Zhabotinsky reaction, belongs to the technical field of cardiac muscle cell cross-scale synchronization, constructs a cardiac muscle cell cross-scale signal transmission model based on BZ reaction, and reveals that signal transmission is regulated by'topology-space '. An interference-coordination-matching three-stage mechanism of inter-cell synchronization is analyzed, cluster synchronization is self-organizing emergence of iteration integration of microscopic phase adjustment under network topology constraint, a macroscopic gradient field with dominant cells as the center is formed, the self-organizing process from local to global is adopted, and the self-organizing effect is good. The time-space orderliness of a heart conduction system is guaranteed, a novel view angle is provided for research of a cardiac muscle cell cross-scale synchronization mechanism, and a theoretical framework of multi-scale computer modeling of a complex system in an organism is expanded.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of myocardial cell cross-scale synchronization, and particularly relates to a cross-scale myocardial cell signal transmission method based on Belousov-Zhabotinsky reaction. BACKGROUND

[0002] The synchronous contraction of myocardial cells is the core physiological process for maintaining the heart pumping function. Under normal physiological conditions, the pacemaker cells of the sinoatrial node conduct action potentials with millisecond-level precision, so that all myocardial cells form a spatiotemporal ordered excitation wave, which is a cross-scale synchronization behavior from cells to tissues. This cross-scale synchronization behavior depends on both the microscopic dynamic characteristics of the cell membrane ion channel and the macroscopic regulation of the tissue-scale electrical signal conduction network. Once this synchronization mechanism is disturbed, it will lead to fatal arrhythmia. According to the data of WHO, about 170 million people die of this reason every year. Therefore, in-depth understanding of the synchronization mechanism of myocardial cells has important reference significance for the research of arrhythmia.

[0003] At present, a large number of researchers have carried out related modeling and exploration on the synchronization mechanism of myocardial cells. The research has been expanded from a single ion channel to multi-scale network modeling. On the microscopic scale (single cell), the individual rules of action potential firing are mainly analyzed through single cell electrophysiological models (such as Hodgkin-Huxley equation); on the mesoscopic scale (cell interaction), the influence of mechanical-electrical coupling between cells on phase synchronization is mainly studied through coupled oscillators or discrete network models; on the macroscopic scale (tissue), the propagation of tissue-scale excitation wave is mainly simulated based on the continuous medium theory. However, the cell-scale model cannot directly explain the emergent behavior of cluster cell synchronization, and the tissue-scale model oversimplifies the discrete interaction characteristics between cells. Therefore, the cluster synchronization behavior of myocardial cells still lacks cross-scale cognition and modeling.

[0004] The cross-scale modeling of the synchronous behavior of myocardial cells requires a dynamic process capable of describing the signal transmission between cells to the synchronization of cell clusters and supporting the expansion simulation of large-scale cells. Notably, the Belousov-Zhabotinsky (BZ) reaction system provides a novel perspective for solving this cross-scale problem. First, the excitation medium characteristics of the BZ reaction system, such as threshold response, "all or nothing", and nonlinear wave interaction, have dynamic similarities with the action potential propagation of myocardial cells, laying a foundation for establishing a physiologically relevant model. Second, the BZ system has dual characteristics of discrete droplet structure and continuous diffusion field, which is beneficial to simulate the discrete individual characteristics of myocardial cells and depict the continuous coupling process between cells to match the cross-scale characteristics of myocardial cell networks. Finally, the system can be implemented by a computer to achieve high-speed simulation, providing an efficient platform for studying the dynamic coupling of multiple cells. These three core advantages make the BZ reaction a possible model system for filling the "scale gap" in the study of myocardial cell synchronization.

[0005] The synchronous contraction of myocardial cells is a core physiological process for maintaining the pumping function of the heart, and abnormal mechanisms can cause fatal arrhythmia. The existing research on the synchronization mechanism of myocardial cells still lacks systematic cross-scale cognition between the micro (single cell) and macro (tissue), which is not conducive to a comprehensive understanding of the physiological and pathological mechanisms of cardiac electrical-mechanical coupling. In view of the above, it is necessary to construct a cross-scale synchronization mechanism of myocardial cells based on the cross-scale modeling requirements of myocardial cells and the characteristics of the BZ reaction system. SUMMARY

[0006] The present application proposes a cross-scale myocardial cell signal transmission method based on the Belousov-Zhabotinsky reaction, which is based on the non-decaying signal transmission characteristics of the excitation medium in the BZ reaction to construct a myocardial cell signal transmission model and reveal the cross-scale synchronization mechanism of myocardial cells.

[0007] The present application adopts the following technical solutions to solve the above problems:

[0008] A cross-scale myocardial cell signal transmission method based on the Belousov-Zhabotinsky reaction, the method comprising the following steps:

[0009] S1: based on the actual geometric discrete characteristics of in vitro myocardial cells, a two-dimensional geometric model of a single cell is constructed;

[0010] S2: the RZ equation of the excitation system about the substances HBrO2 and Fe(phen)3 3+ is applied to the two-dimensional geometric model to construct a myocardial cell model of a single cell;

[0011] S3: Apply local stimulation to the edge region of the cardiomyocyte model to induce a propagating excitation wave that diffuses from the stimulated edge region into the cell interior.

[0012] S4: Using fluorescence imaging technology, intracellular calcium transients were monitored in real time by loading the calcium ion fluorescent probe Fluo-4, and the diffusion behavior of calcium ion signals was observed.

[0013] S5: Based on the cardiomyocyte model, construct a cell pair model, apply stimulation to one of the cells, observe the transmission of excitation signals, and study adjacent cell pairs in vitro by loading the calcium ion fluorescent probe Fluo-4.

[0014] Furthermore, in S1, a single cardiomyocyte is discretized into a circular active region with a radius of 50 pixels. The active region can be excited, and the extracellular medium is modeled as a passive diffusion field to simulate gap junctions and intercellular spaces.

[0015] Furthermore, in S2, the RZ equation includes an active region kinetic equation and a passive region kinetic equation. The active region kinetic equation is applied to the cardiomyocyte itself, and the passive region kinetic equation is applied to the extracellular medium, mapping the HBrO2 concentration x to the degree of cell excitation and using it as a proxy variable for the "electrochemical excitation wave," Fe(phen)3 3+ Concentration z corresponds to the degree of cell excitation recovery.

[0016] Furthermore, the dynamic equation of the active region is:

[0017]

[0018] In equations (1) and (2), the concentration variable x represents the intensity of the intracellular excitation wave, and its spatiotemporal evolution directly corresponds to the propagation dynamics of the action potential / calcium wave.

[0019] The dynamic equation of the passive region is:

[0020]

[0021] z = 0 (4)

[0022] In equations (3) and (4), the concentration variable x represents the intensity of the excitation wave between cells, and its spatiotemporal evolution directly corresponds to the signal propagation dynamics between cells.

[0023] Furthermore, in S4, the calcium ion signal diffusion behavior is specifically manifested as follows: calcium ions are released first at the edge of some myocardial cells, and then the calcium ion signal is transmitted to the central region of the cell in the form of a progressive wavefront, which is consistent with the excitation wave diffusion behavior described in S3.

[0024] Further, in S5, the cell pair model includes cell one and cell two, the distance between cell one and cell two is 3 pixels, the radius of cell one and cell two is 50 pixels, when the center of cell one is subjected to local stimulation, the excitation wave completes the rising, diffusion and attenuation of the excitation signal in cell one, and is propagated to cell two through the passive diffusion area, and after the edge area of cell two receives the signal, the inside of cell two further propagates.

[0025] Further, in S5, by loading calcium ion fluorescent probe Fluo-4, the calcium transients in the adjacent cell pair in vitro are monitored, the calcium ions in cell one are released first, and at this time, cell two is in a resting state; then, the calcium ions in cell one are gradually recovered, and at this time, the calcium ions in cell two begin to be released, and the release sequence and release intensity of the calcium ions in the two cells are consistent with the transmission of the excitation wave.

[0026] Further, in S5, based on the myocardial cell model, the transmission of the excitation signal is observed by constructing a plurality of cell pair symmetry structure models, irregularly distributed myocardial cell network models and myocardial cell cluster matrix models, and is verified by loading calcium ion fluorescent probe Fluo-4, mechanical intervention experiment and optical flow method.

[0027] Compared with the prior art, the present application has the beneficial effects that:

[0028] (1) The myocardial cell signal transmission follows the "topology-space" mechanism: the network topology structure presets the signal conduction path, so that the excitation wave is transmitted through the intermediate cells; and the cell space arrangement determines the signal propagation range by regulating the coupling strength.

[0029] (2) The synchronization between myocardial cells is realized through a "intervention-coordination-matching" three-stage process: the leading cell intervenes in the excitation process of the subordinate cell by using the advanced phase, resets the rhythm of the subordinate cell through the nonlinear excitation wave, and the subordinate cell adjusts through multiple coordination, and finally realizes phase matching and synchronization with the leading cell.

[0030] (3) The myocardial cell cluster synchronizes through the iterative superposition and integration of the "intervention-coordination-matching" mechanism between each two cells in space, and the phase adjustment at the microscopic scale finally emerges as a macro gradient synchronization mode at the cluster level.

[0031] In summary, based on the cross-scale modeling requirements of cardiomyocytes and the characteristics of BZ reaction system, a set of research system of cross-scale synchronization mechanism of cardiomyocytes is constructed. By mapping the excitation medium characteristics in BZ reaction to the electrical-mechanical coupling system of cardiomyocytes, the intercellular signal transmission model is established, and the cell signal transmission behavior, two-cell synchronization behavior and cluster synchronization behavior are simulated; in order to verify the reliability of the model, a multi-modal experiment method is adopted; the calcium ion imaging technology is used to capture the dynamic of calcium ion in the cell, and the excitation of the cell is characterized; the mechanical intervention experiment is adopted to capture the force transmission behavior between cells, and the excitation transmission path between cells is characterized; the light flow method is used to analyze the spatiotemporal coordination of cluster contraction, and the synchronization behavior of cluster cell emergence is characterized; through the double verification of calculation and experiment, the cross-scale synchronization mechanism of cardiomyocytes is revealed. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the specific embodiments of the present application, the drawings required in the description of the specific embodiments will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0033] Figure 1 is a flowchart of the present application;

[0034] Figure 2 is a single cell excitation behavior modeling and verification schematic diagram of the present application;

[0035] Figure 2 (a) is a schematic diagram of the geometry of cardiomyocytes;

[0036] Figure 2 (b) is a schematic diagram of a two-dimensional discrete model;

[0037] Figure 2 (c) is a simulation concentration wave propagation and calcium release experiment schematic diagram;

[0038] Figure 2 (d), Figure 2 (e) is a schematic diagram of the excitation wave dynamics mechanism;

[0039] Figure 3 is a cell intercellular signal transmission modeling and calcium transient verification schematic diagram of the present application;

[0040] Figure 3 (a) is a single cell edge excitation simulation and calcium imaging schematic diagram;

[0041] Figure 3 (b) is a schematic diagram of the signal transmission timing of the cell;

[0042] Figure 3(c) is Figure 3 (b) is a schematic diagram of the intensity of the simulated cell excitation wave;

[0043] Figure 3 (d) is Figure 3 (b) is a schematic diagram of the intensity of the calcium ion concentration of the calcium imaging cell;

[0044] Figure 3 is a schematic diagram of the signal cascade propagation in the four-cell symmetric network of the present application;

[0045] Figure 4 (a) is a schematic diagram of the simulated signal transmission path;

[0046] Figure 4 (b) is a schematic diagram of the signal transmission in the calcium imaging experiment;

[0047] Figure 4 (c), Figure 4 (d) is a statistical diagram of the signal delay between cells in simulation and calcium imaging;

[0048] Figure 4 is a schematic diagram of the signal spatial attenuation characteristics in the irregular network of the present application;

[0049] Figure 5 (a) is a schematic diagram of the experimental cell network;

[0050] Figure 5 (b) is Figure 5 (a) is a schematic diagram of the corresponding simulation model;

[0051] Figure 5 (c) is a schematic diagram of the force transmission path in the mechanical intervention experiment;

[0052] Figure 5 (d) is a schematic diagram of the excitation conduction path in simulation;

[0053] Figure 5 is a schematic diagram of the "trigger-reset-lock" mechanism of cell synchronization of the present application;

[0054] Figure 6 (a) is a schematic diagram of two-cell synchronization in simulation;

[0055] Figure 6 (b) is a schematic diagram of two-cell synchronization in calcium imaging;

[0056] Figure 6 (c) is a schematic diagram of the two-cell phase adjustment process in simulation;

[0057] Figure 6 (d) is a schematic diagram of the two-cell phase adjustment process in experiment;

[0058] Figure 6is a schematic diagram of the gradient emergence process of cluster synchronization of the application;

[0059] Figure 7 (a) is a schematic diagram of concentric circle diffusion of single stimulation;

[0060] Figure 7 (b) is a schematic diagram of phase gradient field evolution under periodic stimulation;

[0061] Figure 7 (c) is a schematic diagram of in vitro cell cluster circular wave captured by the optical flow method. DETAILED DESCRIPTION

[0062] In order to enable those skilled in the art to better understand the technical solutions of the present application, the present application will be described in detail below in combination with the drawings and specific embodiments.

[0063] The present application discloses a myocardial cell cross-scale synchronization model based on BZ reaction, reveals that signal transmission is controlled by "topology-space", and analyzes the three-stage mechanism of "intervention-coordination-matching" of cell synchronization (triggering excitation → resetting rhythm → phase locking), and clarifies that cluster synchronization is a self-organizing emergence of iterative integration of microscopic phase adjustment under network topology constraint, forming a macroscopic gradient field with the pacemaker as the center. This fills the gap between single cell electrical activity and tissue excitation conduction, provides a new perspective for arrhythmia mechanism, and provides a universal framework for multi-scale modeling of complex systems in vivo.

[0064] As Figure 7 shown, the embodiment of the present application discloses a cross-scale myocardial cell signal transmission method based on Belousov-Zhabotinsky reaction, i.e. BZ reaction, which specifically comprises the following steps:

[0065] S1: based on the actual geometric dispersion characteristics of in vitro myocardial cells, a two-dimensional geometric model of single cells is constructed; a single myocardial cell is discretized into a circular active area with a radius of 50 pixels, the active area can be excited, and the extracellular medium is modeled as a passive diffusion field, simulating gap junctions and intercellular gaps.

[0066] S2: the concentration of substance HBrO2 and Fe(phen)3 3+The RZ equation of the excitation system is applied to the two-dimensional geometric model to construct a single-cell myocardial cell model. The RZ equation is the Rovinsky-Zhabotinsky equation, which includes an active region dynamics equation and a passive region dynamics equation. The active region dynamics equation is applied to the myocardial cell body, and the passive region dynamics equation is applied to the extracellular medium. The HBrO2 concentration x is mapped to the cell excitation degree and used as an "electro-chemical excitation wave" proxy variable. The Fe(phen)3 3 + concentration z corresponds to the cell excitation recovery degree.

[0067] The active region dynamics equation is:

[0068]

[0069] In formula (1) and formula (2), the concentration variable x represents the intensity of the intracellular excitation wave, and the spatiotemporal evolution thereof directly corresponds to the propagation dynamics of the action potential / calcium wave.

[0070] The passive region (extracellular medium) dynamics equation is:

[0071]

[0072] z = 0 (4)

[0073] In formula (3) and formula (4), the concentration variable x represents the intensity of the intercellular excitation wave, and the spatiotemporal evolution thereof directly corresponds to the intercellular signal propagation dynamics.

[0074] S3: Local stimulation is applied to the edge region of the myocardial cell model to induce a propagable excitation wave, which spreads from the stimulated edge region to the interior of the cell.

[0075] S4: Real-time monitoring of intracellular calcium transients is performed by loading the calcium ion fluorescent probe Fluo-4 using fluorescence imaging technology to observe the calcium ion signal diffusion behavior. The calcium ion signal diffusion behavior specifically manifests as: the edge of part of the myocardial cells releases calcium ions first, and then the calcium ion signal conducts to the central region of the cell in the form of a progressive wave front, which is consistent with the excitation wave diffusion behavior in S3.

[0076] S5: Based on the myocardial cell model, a cell pair model is constructed, a stimulation is applied to one of the cells, the excitation signal transmission is observed, and the in vitro adjacent cell pair is studied by loading the calcium ion fluorescent probe Fluo-4.

[0077] The cell pair model includes cell one and cell two, the distance between cell one and cell two is 3 pixels, and the radius of cell one and cell two is 50 pixels. When a local stimulus is applied to the center of cell one, the excitation wave completes the rise, diffusion and attenuation of the excitation signal in cell one, propagates to cell two through the passive diffusion area, and the edge area of cell two receives the signal and further propagates inside.

[0078] By loading calcium ion fluorescent probe Fluo-4, the calcium transients in the adjacent cell pairs in vitro are monitored, and the calcium ions in cell one are released first, and at this time, cell two is in a resting state; then, the calcium ions in cell one are gradually recycled, and at this time, the calcium ions in cell two begin to release, and the release sequence and intensity of the calcium ions in the two cells are consistent with the transmission of the excitation wave.

[0079] Based on the myocardial cell model, a plurality of cell pair symmetry structure models, irregularly distributed myocardial cell network models and myocardial cell cluster matrix models are constructed to observe the transmission of excitation signals, which are verified by loading calcium ion fluorescent probe Fluo-4, mechanical intervention experiment and optical flow method.

[0080] The myocardial cell signal transmission method is further illustrated by specific embodiments.

[0081] Embodiment 1

[0082] As shown in Figure 1 , Figure 2 , this embodiment studies the modeling of single cell excitation behavior and the signal transmission modeling between two cell pairs.

[0083] As shown in Figure 3 (a)、 Figure 2 (b), this embodiment studies the actual geometric dispersion characteristics of myocardial cells in vitro, and constructs a two-dimensional geometric model of a single cell. A single myocardial cell is discretized into a circular active area (black area) with a radius of 50 pixels, which can be excited. The extracellular medium (white area) is modeled as a passive diffusion field, simulating gap junctions and intercellular gaps. The RZ equation of the excitation system of the substances HBrO2 and Fe(phen)3 3+ is used. The chemical reaction equation is applied to the myocardial cell 2D geometric model constructed above. By mapping the HBrO2 concentration x to the cell excitation degree, and taking it as an "electro-chemical excitation wave" proxy variable, the Fe(phen)3 3+ concentration z corresponds to the cell excitation recovery degree, and the myocardial cell model is constructed.

[0084] Active area (myocardial cell body) kinetic equation:

[0085]

[0086] The concentration variable x in the above equation represents the intensity of the excitation wave within the cell, whose spatiotemporal evolution directly corresponds to the propagation dynamics of the action potential / calcium wave.

[0087] Passive region (extracellular medium) dynamics equation:

[0088]

[0089] z = 0 (4)

[0090] The concentration variable x in the above equation represents the intensity of the excitation wave between cells, whose spatiotemporal evolution directly corresponds to the intercellular signal propagation dynamics.

[0091] When a local stimulus is applied to the center of the cell, the model successfully reproduces the typical dynamic characteristics of single-cell excitation: the local stimulus triggers the rise of the excitation wave (analogous to depolarization and calcium release), the wave front propagates within the cell (corresponding to action potential conduction), and the boundary attenuates (similar to repolarization and calcium recovery). As shown in Figure 2 (c), this process is consistent with the spatiotemporal dynamics of calcium imaging experiments, demonstrating the fidelity of the model in terms of excitation threshold dependence, wave propagation continuity, and "all or nothing" characteristics, laying a foundation for single-cell dynamics in cross-scale modeling.

[0092] The electrical signal conduction and synchronization of cardiomyocytes depend on electrical coupling and chemical signal transmission between cells, which requires that individual cells not only autonomously generate excitation beats, but also have the ability to receive and transmit electrical and chemical signals. Therefore, the model not only needs to accurately simulate the excitation-contraction coupling of a single cardiomyocyte, but also needs to ensure that its edge region can respond to external electrical stimulation and trigger a conductible excitation wave.

[0093] In the simulation, as shown in Figure 2 (a), Figure 3 (a), the left side is a simulation diagram and the right side is a calcium imaging diagram. Local stimulation is applied to the edge region of the cell model to simulate the response to external electrical stimulation, successfully inducing a propagable excitation wave, and the excitation wave spreads from the stimulated edge region to the interior of the cell. Using fluorescence imaging technology, intracellular calcium transients are monitored in real time by loading calcium ion fluorescent probe Fluo-4, and it is observed that some cardiomyocyte edge regions release calcium ions first, and then the calcium signal conducts in the form of a progressive wave front to the central region of the cell, which is consistent with the signal diffusion behavior in the simulation. Combined with the calcium ion imaging experiment, the biological rationality of the model that the edge of the cell can be excited, i.e., can receive external signals, is verified.

[0094] Further, based on the single-cell model, a cell pair model with a distance of 3 pixels is constructed, where the radius of each cell is 50 pixels. As shown in Figure 3 (b), Figure 3 (c),Figure 3 (b) is a simulation diagram on the left and a calcium imaging diagram on the right. In the simulation, when a local stimulus is applied at the center of cell 1, the excitation wave not only completes the rise, diffusion and decay of the excitation signal within cell 1, but also propagates to cell 2 through the passive diffusion area. After the edge area of cell 2 receives the signal, further propagation is carried out inside. As shown in Figure 3 (b), in vitro, adjacent cell pairs were loaded with calcium ion fluorescent probe Fluo-4, and the calcium transients in the two cells were monitored. It was found that the calcium ions in cell 1 were released first, and at this time, cell 2 was in a resting state; then, the calcium ions in cell 1 were gradually recovered, and at this time, the calcium ions in cell 2 began to be released. As shown in Figure 3 (c), Figure 3 (d), the order and intensity of calcium ion release of the two cells are consistent with the cell pair model in the simulation, verifying the modeling ability of the model for intercellular signal transmission.

[0095] Example 2

[0096] Based on the modeling of myocardial cell signal transmission in Example 1, the signal transmission mechanism in myocardial cell clusters is systematically revealed by constructing a multi-cell network model and combining calcium imaging and mechanical intervention experiments.

[0097] As shown in Figure 3 (a), based on the verified minimum unit of clustered cells, a single cell and a cell pair model, a four-cell symmetric structure model was first constructed, in which the cell spacing is 3 pixels and the cell radius is 50 pixels. As shown in Figure 3 (a), Figure 4 (c), in the simulation, a local stimulus is applied to cell 1, and the excitation wave propagates to cells 2 and 3 at equal distances through diffusion. Further, the signal is finally transmitted to the distal cell 4 through the relay action of these two cells, and collision and reconstruction are carried out in cell 4. As shown in Figure 3 (b), Figure 3 (d), in vitro, the four-cell symmetric structure of myocardial cells was loaded with calcium ion fluorescent probe Fluo-4, and it was found that cell 1 released calcium ions first, and at this time, cells 2, 3 and 4 were in a resting state; then, the calcium ions in cell 1 were gradually recovered, and the calcium ions in cells 2 and 3 began to be released at the same time; further, cell 4 released calcium ions during the recovery of cells 2 and 3. In the four-cell structure, the calcium imaging experimental results are highly consistent with the simulation, revealing the key characteristics of signal propagation in multi-cell networks, i.e., the topological structure of the myocardial cell network presets the functional connection mode between cells, and enables the signal to achieve cascade diffusion through intermediate cells.

[0098] Example 3

[0099] Based on the results of Example 2, to further explore the signal transmission mechanism of the cluster cells in irregular arrangement, in this example, the irregularly distributed myocardial cell network was selected as shown in Figure 4 (a), and the corresponding simulation model was constructed as shown in Figure 4 (b). In this structure, cell 1 and adjacent cells 2-4 are in close coupling, while cell 5 is spatially isolated due to the long distance (30 pixels). In the simulation, a local stimulus is applied to the middle of cell 1, and the excitation signal is transmitted from cell 1 to cell 2, cell 3, and cell 4 in turn, showing clear cascade propagation characteristics; while the distal cell 5 is always not activated and remains in a stable state. Based on the existing technology, a mechanical probe can selectively activate a single myocardial cell without interfering with adjacent cells, and trigger the excitation of adjacent cells through electrical signal transmission. Therefore, in the experiment, a micrometer-scale mechanical probe was used to precisely stimulate cell 1 in the myocardial cell network, while recording the mechanical response signals of each cell. It was observed that the excitation signal followed the spatiotemporal sequence of cell 1→cell 2→cell 3→cell 4, while cell 5 was beyond the effective coupling range and did not show any mechanical response. The mechanical intervention experiment was highly consistent with the simulation, revealing that the signal transmission range of the cluster cells is determined by the coupling strength caused by the spatial arrangement of the cells.

[0100] Examples 2 and 3 constructed regular and irregular myocardial cell network models, and verified through calcium imaging and mechanical intervention experiments that, at the functional level, the network topology structure enables the signal to be transmitted through the relay of intermediate cells to achieve cascade diffusion by pre-setting the functional connection mode between cells; at the physical level, the spatial arrangement of cells determines the propagation range by regulating the coupling strength. The network topology structure, together with the spatial arrangement, forms a structure-guided directional and stable signal transmission channel by pre-setting the functional connection mode between cells. This "topology-space" mechanism shows that myocardial cell signal transmission is a nonlinear process determined by the directional propagation of network topology and the coupling strength regulated by spatial arrangement.

[0101] Example 4

[0102] The synchronization between myocardial cells is a complex process involving multi-scale dynamic coupling. The interaction between excitation waves between cells gradually eliminates the rhythm difference through precise phase coordination, and finally achieves synchronized beating. The core of this phenomenon lies in the unique electro-mechanical physiological characteristics of myocardial cells - each cell can act as an autonomous oscillation unit to generate inherent beating, and can also receive and integrate the synchronization signals of adjacent cells through the electrically coupled network. When heterogeneous pacemakers coexist, the system spontaneously forms an ordered state centered on the dominant rhythm through nonlinear interaction.

[0103] Based on the above core description of cell synchronization, this example is based on the intercellular synchronization interaction process of the cell pair model under the condition of heterogeneous pacemaker. As shown inFigure 5 (a) shows, wherein the cell-to-cell distance is 3 pixels and the cell radius is 50 pixels. The model is set to automatically trigger the next local stimulation when the excitation wave in the cell completely spreads to the cell boundary and decays to the resting state (determined when the x variable concentration in the cell is reduced to below 0.01), to simulate the periodic excitation-resting of the actual cell. As shown in Figure 5 (a) shows, in the simulation, the study of the application of local perturbation stimulation to cell 1 and cell 2 at different time periods, cell 1 receives perturbation stimulation at the initial stage of the simulation, while the perturbation stimulation of cell 2 is delayed to be applied when the iteration number reaches 58000, thereby constructing the initial phase difference of the two cells; as the excitation wave of cell 1 continues to transmit into cell 2, the wave front of the two cells collides in space and time inside cell 2, causing the excitation process of cell 2 to be "interrupted", and this excitation wave reconstruction makes the starting time of the next excitation of cell 2 lag; as shown in Figure 6 (c) shows, after about 8 cycles of iteration adjustment, the phase of cell 2 is gradually adjusted to "match" the beating phase of cell 1, and the two cells are synchronized. As shown in Figure 6 (b) shows, in the cell experiment, the study of loading calcium ion fluorescent probe on in vitro cultured cardiomyocytes, recording the calcium ion release cycle inside two closely adjacent cardiomyocytes to represent the excitation phase state of the cells. As shown in Figure 6 (d) shows, it is observed that from the beginning of recording, the phase of cell 1 always leads cell 2; as the periodic excitation of cell 1, the phase of cell 2 gradually adjusts, and the phase difference between cell 1 and cell 2 becomes smaller and smaller; after a period of adjustment, cell 1 and cell 2 achieve synchronous excitation. The synchronization process of the two cells in the calcium imaging experiment and the simulation shows good dynamic consistency, indicating that the "intervention-coordination-matching" three-stage feature is the key mechanism of the phase synchronization process between cells.

[0104] The synchronization process between cardiomyocytes exhibits precise dynamic regulation characteristics, and this complex physiological phenomenon is systematically described by the constructed cross-scale model and calcium imaging experiment. When periodic stimulation is applied to a pair of closely coupled cells, a typical phase domestication process is revealed and the rhythm of the two cells is eventually synchronized. The calcium imaging experiment provides direct evidence for this mechanism, and the dynamic adjustment process exhibited by the calcium transient is highly consistent with the "trigger-reset-lock" three-stage feature revealed by the simulation, which shows that cardiomyocytes have the inherent ability to achieve rhythm coordination through phase reset.

[0105] Embodiment 5

[0106] Synchronization of clustered cells involves a nonlinear self-organization process of a multi-node coupled network. This embodiment systematically reveals the dynamic mechanism of this cross-scale coordination by constructing a cell matrix model arranged in a regular pattern and combining with optical flow experimental analysis.

[0107] As Figure 6 (a)、 Figure 6 (b) shows that the embodiment constructs a 9*9 square model composed of 81 identical parameter myocardial cells (radius 20 pixels, interval 3 pixels). First, as shown in Figure 7 (a), in the simulation, a local stimulation is applied to the cell at the 3rd row and 5th column of the node, and the excitation signal presents a concentric circle diffusion pattern, showing a stable conduction process of a signal in the cluster cells. Second, as shown in Figure 7 (b), a periodic local stimulation is applied to the cell at the 4th row and 5th column of the node, and the excitation signal spreads among the cells in the form of ring wave and continuously activates the surrounding cells, with the cells farther away from the pacemaker showing more obvious phase delay; as the coupling iteration between the cells continues, the phase difference of all cells in the cell square gradually decreases, showing visual consistency, which gradually evolves from the initial chaotic state to a synchronous field with spatial gradient characteristics centered on the pacemaker. As shown in Figure 7 Figure 7 Figure 7 (c), the light flow method is used to dynamically observe the in vitro cultured myocardial cell group for 5 days, and the color mapping is used to visualize the excitation and beating of the cells, and it is found that the excitation activity of the cultured myocardial cell group is developed around a certain excitation node, and the light flow spreads in the form of ring wave to the surrounding, which is highly consistent with the simulation synchronization mode. This spatial propagation characteristic shows that the myocardial cell cluster has the ability to form global order through local coupling.

[0108] The results of the above embodiments show that the synchronization of myocardial cell clusters is essentially a dynamic self-organization process under network topology constraints. Through the iterative superposition and integration of the "intervention-coordination-matching" mechanism between the two cells in embodiment 4 in space, the microscopic phase adjustment finally emerges as a macro gradient synchronization mode at the cluster level. This self-organization process from local to global ensures the spatiotemporal order of the cardiac conduction system.

[0109] The application innovatively combines the excitation medium kinetics of Belousov-Zhabotinsky (BZ) reaction system with the electrical-mechanical coupling system of myocardial cells, analyzes the cross-scale behaviors of single cell excitation, intercellular signal transmission and cluster cell synchronization by constructing an intercellular signal transmission model. In the signal transmission layer, the research reveals the "topology-space" mechanism: the network topology structure presets the conduction path, and the spatial arrangement controls the propagation range through the coupling strength. In the synchronization mechanism layer, the "intervention-coordination-matching" three-stage process is quantitatively described: the leading cell intervenes in the excitation process of the subordinate cell by using the advanced phase, resets the rhythm through the nonlinear excitation wave, and the subordinate cell adjusts multiple times to finally realize the phase matching and synchronization with the leading cell. In the cluster layer, the two-by-two synchronization at the microscale is integrated through spatial iteration, and finally emerges as a macro gradient synchronization mode centered on the pacemaker. These findings not only fill the scale gap from single cell excitation to tissue conduction, but also provide a universal framework for the multi-scale modeling of complex systems in vivo through the unique excitation medium characteristics of the BZ system.

[0110] The application is described in detail through the embodiments, but the content described is only exemplary embodiments of the application and cannot be considered to limit the implementation scope of the application; the protection scope of the application is defined by the claims, and any similar technical solution that utilizes the technical solutions described in the application or is inspired by the technical solutions of the application within the substantial and protection scope of the application, achieves the above technical effects, or makes equivalent changes and improvements to the application scope, should still belong to the patent coverage and protection scope of the application.

Claims

1. A method of cross-scale cardiomyocyte signal transmission based on Belousov-Zhabotinsky reaction, characterized in that: The method comprises the following steps: S1: constructing a two-dimensional geometric model of a single cell based on the actual geometric dispersion characteristics of in-vitro myocardial cells; S2: apply the RZ equation of the excitation system about the substance HBrO2 and Fe(phen)3 3+ to the two-dimensional geometric model, and construct a single-cell cardiomyocyte model. S3: applying local stimulation to the edge region of the myocardial cell model to induce a propagating excitation wave that spreads from the stimulated edge region to the interior of the cell; S4: using fluorescence imaging technology to monitor intracellular calcium transients in real time by loading calcium ion fluorescent probe Fluo-4 to observe calcium ion signal diffusion behavior; S5: based on the myocardial cell model, constructing a cell pair model, applying stimulation to one of the cells, observing the transmission of excitation signals, and studying in-vitro adjacent cell pairs by loading calcium ion fluorescent probe Fluo-4.

2. The method of claim 1, wherein the Belousov-Zhabotinsky reaction is used to transmit signals across scales in cardiac myocytes. In S1, a single myocardial cell is discretized into a circular active region with a radius of 50 pixels, the active region can be excited, and the extracellular medium is modeled as a passive diffusion field to simulate gap junctions and intercellular gaps.

3. The method of claim 1, wherein the Belousov-Zhabotinsky reaction is used to transmit signals across scales in cardiac myocytes. In S2, the RZ equation includes an active region dynamics equation applied to the cardiomyocyte body and a passive region dynamics equation applied to the extracellular medium, which maps the HBrO2 concentration x to the degree of cellular excitation and serves as a proxy variable for the "electro-chemical excitation wave", Fe(phen)3 3+ The concentration z corresponds to the degree of recovery of cellular excitation.

4. The method of claim 3, wherein the Belousov-Zhabotinsky reaction is a cross-scale cardiac cell signal transmission method. The active region dynamics equation is: In formula (1) and formula (2), the concentration variable x represents the intensity of the intracellular excitation wave, and the spatiotemporal evolution directly corresponds to the propagation dynamics of action potentials / calcium waves; The passive region dynamics equation is: z＝0 (4) In formula (3) and formula (4), the concentration variable x represents the intensity of the intercellular excitation wave, and the spatiotemporal evolution directly corresponds to the intercellular signal propagation dynamics.

5. The method of claim 1, wherein the Belousov-Zhabotinsky reaction is used to transmit signals across scales in cardiac myocytes. In S4, the calcium ion signal diffusion behavior specifically manifests as: part of the myocardial cell edge releases calcium ions first, and then the calcium ion signal conducts to the central region of the cell in the form of a progressive wave front, which is consistent with the excitation wave diffusion behavior in S3.

6. The method of claim 1, wherein the Belousov-Zhabotinsky reaction is based on the reaction of bromate and malonic acid in the presence of ferroin. In S5, the cell pair model includes cell one and cell two, the distance between cell one and cell two is 3 pixels, and the radius of cell one and cell two is 50 pixels. When local stimulation is applied to the center of cell one, the excitation wave completes the rise, diffusion and attenuation of the excitation signal in cell one, propagates to cell two through the passive diffusion region, and the interior of cell two further propagates after receiving the signal at the edge region of cell two.

7. The method of claim 6, wherein the Belousov-Zhabotinsky reaction is a cross-scale cardiomyocyte signal transmission method. In S5, by loading calcium ion fluorescent probe Fluo-4 to study in-vitro adjacent cell pairs, the calcium transients in the two cells are monitored. The calcium ions in cell one are released first, and at this time, cell two is in a resting state. Then, the calcium ions in cell one are gradually recovered, and at this time, the calcium ions in cell two begin to be released. The order and intensity of calcium ion release in the two cells are consistent with the transmission of the excitation wave.

8. The method of claim 1, wherein the Belousov-Zhabotinsky reaction is used to transmit signals across scales in cardiac myocytes. In S5, based on the myocardial cell model, the transmission of excitation signals is observed by constructing a plurality of cell pair symmetrical structure models, irregularly distributed myocardial cell network models, and myocardial cell cluster matrix models, and verified by loading calcium ion fluorescent probe Fluo-4, mechanical intervention experiments, and optical flow method.

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