Cell characterization, typing and identification methods and their applications

Abstract

The present invention relates to the field of biotechnology, and more particularly to methods for characterizing, typing, and identifying cells and their applications. The physical information of cells includes the mechanical force and / or stiffness of cells obtained in at least one of the following cases: interactions between cells and / or multicellular aggregates, cells and / or multicellular aggregates at different growth stages, different regions within multicellular aggregates, the effects of substances on cells and / or multicellular aggregates, and the effects of other physical, biological, or chemical factors on cells and / or multicellular aggregates. The present invention performs typing and identification of cells and / or multicellular aggregates by the above-described characterization method. The present invention can characterize the real-time and continuous state of cells and / or multicellular aggregates by the physical information of cells, and can identify each type and state of cells and / or multicellular aggregates in a short time, at low cost, and with high throughput, with an accuracy of 98% or more. The present invention is further limited to being realized by a characterization system, and the above effects can be achieved.

Description

Technical Field

[0001] The present invention relates to the field of biotechnology, and particularly to cell characterization, typing and identification methods and their applications.

Background Art

[0002] In the field of biology, when using cells or multicellular aggregates in the drug development process, the selection of cell models is very important. This is because an effective cell model can more accurately predict drug reactions in vivo. Conventional two-dimensional (2D) cell culture models are easy to operate and observe, but since they do not mimic the in vivo microenvironment, their prediction results often have a large difference from the actual in vivo situation. In order to better mimic the in vivo microenvironment, in recent years, tumor spheroids and organoids have attracted attention as multicellular aggregate culture models. In particular, cell-cell interactions and other characterizations are very important.

[0003] Cells are the basic units of life, and their adhesion, migration, differentiation, apoptosis processes, dynamic changes in various physiological and pathological processes, and interactions with macromolecules have important significance in understanding and controlling life phenomena. Therefore, characterizing the types, states, behaviors, etc. of cells and cell aggregates is an important issue in fields such as biotechnology, cell biology, and physical biology.

[0004] Currently, there are several main methods for characterizing cells and cell multimers: Physical methods: Instruments are used to measure the mechanical or electrical properties of cells, such as mechanical force, adhesive force, elastic modulus, and impedance. These methods can reflect the morphology, function, and metabolic state of cells, but existing technologies usually require expensive equipment and data processing techniques. Examples include atomic force microscopes, mechanical force microscopes, and impedance spectrometers. These methods are complex to operate, have low flow rates, and are expensive. Furthermore, limitations such as flow rate and phototoxicity make it difficult to monitor cells over long periods and in real time. Biochemical methods: Reagents or labeled substances are used to measure cells. These methods can detect the state of cells and their binding to macromolecules with high sensitivity, but they may also affect the properties and functions of the cells themselves. Examples include fluorescence resonance energy transfer, biotin-avidin systems, and enzyme-linked immunosorbent assays. Chemical methods can detect the binding between cells and macromolecules with high sensitivity, but they usually require labeling or modification of the target substance, which may interfere with its normal function. [Overview of the project] [Problems that the invention aims to solve]

[0005] In view of the aforementioned shortcomings and deficiencies of existing technologies, the present invention provides a method for characterizing cells and multicellular aggregates by detecting and acquiring static or dynamic cellular mechanical forces and / or stiffness at different times and before and during the action of other factors on the cells / multicellular aggregates.

[0006] Accordingly, the present invention also provides a method for typing and identifying cells, which can achieve typing and identification of cells and / or multicellular aggregates in any case by cellular mechanical force and / or stiffness.

[0007] Accordingly, the present invention also provides applications of the above method. [Means for solving the problem]

[0008] To achieve the above objectives, the main technical means employed by the present invention include the following: In a first embodiment, the present invention provides a method for characterizing cells, thereby characterizing cells and / or multicellular aggregates by obtaining physical information about the cells of the cells and / or multicellular aggregates.

[0009] Optionally, the physical information of the cell is: (1) Interactions between cells and multicellular aggregates, (2) Intercellular interactions, (3) Interactions between multicellular aggregates, (4) Cells or / or multicellular aggregates at different growth times, (5) Different regions within a multicellular aggregate, (6) The effects of a substance on cells or / and on multicellular aggregates, (7) Including cellular mechanical force or / and stiffness obtained in the case of at least one of the effects of other physical, biological or chemical factors on cells or / and multicellular aggregates, The aforementioned multicellular aggregate is a group of cells formed by the aggregation of two or more cells.

[0010] In a second embodiment, the present invention also provides a cell typing and identification method which types and identifies the cell and / or multicellular aggregate by the physical information of the cell as described in any one of claims 1 to 11.

[0011] Optionally, the typing and identification include the type, state, behavior, spatial omics features and differentiation direction of cells and / or multicellular aggregates, stress response, Optionally, the typing and identification may include selectively separating specific cells or tissues based on the physical information of the cells.

[0012] In a third embodiment, the present invention also provides an application of the method to any of the embodiments, the application of which Applications in the construction of in vitro organs and cell models, Screening of organ-specific therapeutic agents, applications in research on the physiological and pathological states of organ models, Methods for evaluating the efficacy of drugs against tumors and their application in related evaluation products. This includes at least one of the following: cell therapy, synthetic biology, adipose research, research on the interaction between cells / multicellular aggregates and macromolecules, research methods for multicellular aggregates, and applications in related products. [Effects of the Invention]

[0013] The beneficial effects of this invention are as follows: First, the present invention can characterize the interactions between cells and / or multicellular aggregates, the state before and after the action of external factors, the state during the action process, or a continuous state based on the physical information of acquired cells, and the state can be observed in real time. It can identify each state in a short time, at low cost, and with high throughput, and has an accuracy rate of 98% or more. Relationships between cells, between cells and multicellular aggregates, and between multicellular aggregates can be rapidly determined under different scenes and conditions, and cell samples can be reused. The present invention can achieve the above effects by further limiting its implementation to a characterization system.

[0014] Next, the characterization system further defined by the present invention can detect cellular mechanical forces using reflected light and features high throughput and low cost compared to existing cellular mechanical force detection devices. Compared to existing TFMs and general micropillar arrays, the technical solution of the present invention eliminates reliance on microscopes and significantly simplifies the operational flow. This is because it does not require the acquisition of high-resolution images, and cells can be monitored at high throughput and low cost simply by monitoring the intensity of reflected light. The cellular mechanical force detection device has high accuracy and sensitivity because it detects cellular mechanical forces by converting them into optical signals based on the deformation of micropillars caused by cellular mechanical forces. There is a linear correlation between optical intensity and the magnitude of cellular mechanical force, and different cell typing can be achieved through qualitative and quantitative analysis.

[0015] Furthermore, the characterization system further defined by the present invention optionally includes the addition of a magnetic metal reflective layer and magnetic material to the top of the micropillars, and by changing parameters such as the coating composition characteristics, spacing, and motion logic of the micropillars, it is possible to switch between measuring cellular mechanical force or cellular stiffness, or measure them simultaneously, thereby achieving a more flexible and accurate comprehensive characterization of cellular physical features.

[0016] Furthermore, the characterization system of the present invention possesses single-cell resolution. Its high resolution allows for real-time monitoring of each cell and enables measurement of heterogeneity in the drug response of cells in combination with other single-cell analysis techniques. Real-time monitoring: It does not require fluorescence and avoids phototoxicity to cells, making it suitable for long-term monitoring and usable in studies of long-term drug responses of cells. High sensitivity: The deformation signal of the micropillar is amplified by the reflected signal, improving the sensitivity of deformation monitoring. Detection of bending deformation of micro- and nanopillars generally relies on optical systems (e.g., microscopes), but the smaller the micropillar size, the higher the demands on the accuracy and resolution of the optical system. For example, a micropillar with a width of 2 μm and a height of 6 μm requires an objective lens of 20x or more and a confocal system. The present invention utilizes the principle of specular reflection and, by detecting the attenuation of reflected light, actually amplifies the deformation signal of the micropillar. Experimental verification has shown that the same signal can be observed with a 5x objective lens. By incorporating a special reading system, the deformation of micro / nanopillars can be effectively detected without relying on high-magnification optical objective lenses, significantly reducing system costs and effectively improving throughput.

[0017] Furthermore, the characterization system of the present invention can mimic the cellular microenvironment. It can mimic the components and morphology of the extracellular matrix, thereby addressing a wider range of technological needs. [Brief explanation of the drawing]

[0018] [Figure 1]It is a structural schematic diagram of a cell mechanical force detection device in the first embodiment of the present invention. [Figure 2] It is a scanning electron microscope (SEM) image of a micropillar (real object) of the cell mechanical force detection device in the first embodiment of the present invention. Here, a is a plan view of the cell mechanical force detection device, and b is a side view of the cell mechanical force detection device. [Figure 3] It is a structural schematic diagram of a characterization system for cell / multicellular aggregate interaction related to the ninth embodiment of the present invention. [Figure 4] It is a structural schematic diagram of a characterization system for cell / multicellular aggregate interaction related to the tenth embodiment of the present invention. [Figure 5] It is a scanning electron microscope image of a micropillar (polydimethylsiloxane) provided with a light reflection layer (gold) at the top position. Here, FIG. 5a is a scanning electron microscope image of the micropillar. FIG. 5b is an elemental characterization diagram of the top region of the micropillar. FIG. 5c is an elemental characterization diagram of the side region (excluding the top region) of the micropillar. [Figure 6] It is a photograph of cells in the seventh embodiment of the present application adhering to a micropillar provided with a substance (fibronectin) having a cell adhesion effect at the top of the micropillar. Here, 6a is a fluorescence imaging diagram of cells adhering to a preset pattern composed of a group of micropillars provided with fibronectin at the top. 6b is a cell force distribution diagram calculated from the light reflection signals measured on a group of micropillars provided with fibronectin at the top. [Figure 7]The figures shown in the specific embodiments of this application are experimental related photos in which the OKT3 antibody (a substance that interacts with cell surface receptors) or fibronectin (Fibronectin, FN) is selected as the substance having cell adhesion effect. Here, 7a is a schematic diagram of an experiment in which the OKT3 antibody is adopted as the substance having cell adhesion effect. The upper two images in 7b are fluorescence imaging diagrams of cells adhered to the top of micro-pillars provided with the OKT3 antibody and fibronectin at the top respectively. The lower two images in 7b are diagrams of the cell mechanical force magnitude distribution resolved from the optical reflection signals measured on the micro-pillars. 7c is a comparison diagram of the mechanical magnitudes measured on the surfaces coated with the OKT3 antibody and fibronectin respectively. 7d is a diagram of the dynamic change of cell mechanics after seeding T cells on the OKT3 antibody surface (the top of the micro-pillar). [Figure 8] It is a schematic structural diagram a of a cell mechanical force detection device having a cell restriction mechanism. [Figure 9] It is a schematic structural diagram b of a cell mechanical force detection device having a cell restriction mechanism. [Figure 10] It is a related photo of a cell mechanical force detection device that adopts a silicon thin film as a cell restriction mechanism in the specific embodiments of the present invention. Here, a is a physical diagram thereof. b is a fluorescence microscope diagram of a cell mechanical force detection device that adopts a silicon thin film as a cell restriction mechanism under light reflection. c is an enlarged view of b. [Figure 11] The characterization system of the eleventh embodiment is a fluorescence microscope image for monitoring cell mechanical force. [Figure 12] It is a schematic diagram of a cell mechanical force detection system and its detection result provided in the twelfth embodiment of the present invention. Here, a is a schematic structural diagram of the characterization system of the cell or / and multi-cell aggregate interaction in the twelfth embodiment. b is an image of the cell mechanical force detection device optical reflection signal obtained by the optical signal detection device in the twelfth embodiment. c is a visualization effect diagram of the mechanical magnitude and distribution processed by the optical signal analysis device in the twelfth embodiment. [Figure 13]This diagram illustrates the interrelationship between mechanics and light reflection signals when a fluid is used as an external force, as shown in a specific embodiment of the present invention. 'a' is a schematic diagram of the structure of a cell mechanical force detection device in a microfluidic environment before fluid switching. 'b' and 'c' are comparative diagrams of bright-field microscope images, reflected light signal distribution diagrams, and their superposition effect diagrams of the micropillar before and after fluid switching. 'd' is a diagram of the light reflection signal intensity before and after fluid switching. 'e' is a linear relationship diagram between the light reflection signal and the micropillar offset. Here, the superposition effect diagram is an effect diagram formed by superimposing the bright-field microscope image and the reflected light signal distribution diagram of the micropillar. [Figure 14] This is a schematic diagram of a method for detecting cellular mechanical force as shown in a specific embodiment of the present invention. a is a schematic diagram of the structure of the cellular mechanical force detection device before and after contact between the micropillar and the cell. b is a reflected light signal distribution diagram acquired by the optical signal detection device. c is a monitoring diagram of the cell migration process. d is a reflected light signal distribution diagram during the cell migration process. [Figure 15] The cell mechanical force information obtained by the cell mechanical force detection method of this application, as shown in the specific embodiments of the present invention, is shown below. a is a fluorescence imaging diagram of a mixed system of healthy cells and non-small cell lung cancer cells. b is a cell mechanical force detection device light reflection signal distribution diagram obtained by an optical signal detection device. c is a visualization effect diagram of the magnitude and distribution of mechanics processed by an optical signal analyzer. d is a magnified view of representative single-cell force distributions of healthy cells and non-small cell lung cancer cells in c. e is a comparison diagram of the cell morphology of healthy cells and non-small cell lung cancer cells. f is a comparison diagram of the reflection signal strength after mixing healthy cells, non-small cell lung cancer cells and these two types of cells in different proportions. g is a clustering analysis diagram obtained by processing c based on the physical information of structured cells after structuring. [Figure 16] This diagram shows a schematic representation of monitoring cell vitality using cell mechanical force information obtained by the cell mechanical force detection method of this application, as shown in the specific examples of this application. Here, a is a schematic diagram of the operation flow of the cell vitality detection method. b is a comparison diagram of cell vitality measured by the MTT method and cell vitality reflecting cell mechanical force after treating A549 cells with different doses of 5FU for 24 hours. c is a comparison diagram of cell vitality measured by the MTT method and cell vitality reflecting cell mechanical force after treating A549 cells with different doses of 5FU for different times. [Figure 17] This is a schematic diagram of the standardization process for displacement information at a certain point in the 29th embodiment of the present invention. [Figure 18] Figure A shows the results of using the cell feature model established in the extended embodiment of the 30th embodiment of the present invention to identify unknown cells or unknown cell characterization types. [Figure 19] Figure B shows the result of using the cell feature model established in the extended embodiment of the 30th embodiment of the present invention to identify unknown cells or unknown cell characterization types. [Figure 20] The 35th example is a diagram showing experimental results of monitoring organoid adhesion and drug reaction using mechanical force characterization. [Figure 21] This figure shows the results of a fluorescence staining experiment of tumor spheroids using mechanical characterization in the 36th example. [Figure 22] This figure shows the experimental results of using a restricting structure to constrain the size and shape of cell spheroids in the 36th example. [Figure 23] These are fluorescence characterization, cell mechanistic imaging, and quantification diagrams of T cell lines activated by CD3 antibody coating on an instrument in the 41st embodiment of the present invention. [Figure 24] This is a visualization diagram showing the effect of measuring the mechanical force of mouse cardiomyocytes using a cell mechanical force measuring device in the 53rd embodiment. [Figure 25] This is a diagram illustrating the changes in cellular mechanical forces during the differentiation of NIH3T3-L1 into adipoid cells in the 56th example. [Figure 26] This is a characterization diagram of the 58th embodiment, in which tropic ECM is printed on a chip and stem cells are guided into cardiac tissue. [Figure 27] This is a characterization diagram of fluorescence and histochemical staining in which tissue-specific ECM is printed on a chip in the 59th example, and stem cells are induced into cartilage. [Figure 28] This is a schematic diagram of the sixtieth embodiment of a bilateral variable lung tumor chip. [Figure 29] This is a cellular mechanical force imaging diagram of the tumor tissue region and normal tissue region in the 63rd embodiment. [Figure 30] This is a cellular mechanical force imaging diagram of the tumor tissue area and normal tissue area after drug treatment in the 63rd example. [Figure 31] This is the sandwich structure described in the 36th embodiment. [Modes for carrying out the invention]

[0019] To better illustrate the present invention, exemplary embodiments of the invention will be described in more detail below with reference to the accompanying drawings. Although the drawings show exemplary embodiments of the invention, the invention can be carried out in various forms and should not be construed as being limited to the embodiments described herein. Rather, these embodiments are provided to give a more complete understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0020] Implementation Method 1 Embodiment 1

[0021] This embodiment provides a method for characterizing cells and / or multicellular aggregates by acquiring physical information about the cells of the cells and / or multicellular aggregates. The physical information about the cells includes cellular mechanical forces and / or stiffness at specific points within the cells. The cellular mechanical forces include at least one of magnitude, direction, and frequency. The physical information about the cells further includes cellular morphological information. The physical information about the cells includes changes in cellular mechanical forces and / or stiffness at specific points over a certain time interval. Optionally, the cellular mechanical forces and / or stiffness in the physical information about the cells are presented in a visualization format.

[0022] Optionally, cellular physical information is obtained under cell restriction operations on cells and / or multicellular aggregates. Restriction allows for the orderly cultivation of a fixed number of cell populations in a restricted environment, enabling high-throughput monitoring of changes in their cellular mechanical forces, while simultaneously providing opportunities for each cell population to come into contact with other cell populations, facilitating the observation of intercellular interactions.

[0023] "Identification" refers to the identification of known and unknown types.

[0024] In this embodiment, the physical information of cells is obtained based on the following interactions: interactions between cells and multicellular aggregates, interactions between cells, interactions between multicellular aggregates, and interactions between cells and multicellular aggregates.

[0025] Specifically, this includes the following steps: The first cell and / or multicellular aggregate and the second cell and / or multicellular aggregate are each placed in specific regions, and the physical information of the cells is detected and acquired. or After placing a first cell and / or multicellular aggregate in a specific region, a second cell and / or multicellular aggregate is made to interact with the first cell and / or multicellular aggregate to detect and acquire the physical information of the cells.

[0026] The first cell and / or multicellular aggregate and the second cell and / or multicellular aggregate each refer to one or more cells and / or multicellular aggregates. The interactions between the first cell and / or multicellular aggregate and the second cell and / or multicellular aggregate are characterized through the physical information of the cells.

[0027] Optionally, the cell / multicellular aggregate characterization system of Embodiment 1 can be selected for characterization, and specific regions are located within the cell / multicellular aggregate characterization system. Optionally, cells and / or multicellular aggregates can adhere to specific regions, optionally via restricted adhesion.

[0028] The attachment method includes placing cells and / or multicellular aggregates in a specific region (in other specific embodiments, a specific region of the characterization system), then allowing them to culture statically for 30 minutes or more, and continuing to add culture medium until the cells and / or multicellular aggregates are completely attached to the specific region (characterization device).

[0029] Optionally, external stimuli may be applied before or during the detection and acquisition of cellular physical information. Optionally, additional external stimuli may include, but are not limited to, biological, chemical, physical, tropic induction, and dynamic stimuli.

[0030] Drug stimulation is used to monitor and characterize the effects of drugs on cells and / or multicellular aggregates, as well as changes in interactions between cells and multicellular aggregates, between cells, between multicellular aggregates, and between cells and multicellular aggregates under drug stimulation. Furthermore, it clarifies the pharmacological effects and other properties of the drug. Other chemical stimuli, besides drugs, include, but are not limited to, pH levels, oxygen content, and sugar concentrations.

[0031] Biological stimuli include, but are not limited to, growth factors. Growth factors are important signaling molecules for cell growth and proliferation. By adding growth factors, cells can be stimulated to promote their proliferation, migration, or differentiation, and influence the mechanical properties and interactions of cells. Extracellular matrix (ECM) components: By adjusting the stiffness, fiber arrangement, or chemical composition of the extracellular matrix, the composition or structure of the extracellular matrix can be altered, directly influencing the mechanical response and behavior of cells.

[0032] Dynamic stimuli include, but are not limited to, periodic strains. By applying periodic strain stimuli, for example by alternately applying tensile and compressive forces, it is possible to mimic the dynamic changes in biological tissues during physiological processes and study the mechanical responses and adaptability of cells. Time-varying chemical environments: By periodically or stepwise changing the chemical environment, by periodically changing drug concentrations or adding and removing chemicals, it is possible to mimic the dynamic responses and adaptations of cells under physiological or pathological conditions.

[0033] Directional induction includes, but is not limited to, inducing directional growth or movement of cells by forming biological morphological gradients on a substrate, such as the structure or stiffness gradient of the extracellular matrix. Drawing lines on a substrate in a specific direction induces cells to change growth in the direction of the lines.

[0034] Physical stimuli include, but are not limited to, temperature, magnetic stress, electrical stimulation, and flow field stimulation. Mechanical forces: By applying mechanical stimuli such as mechanical tension and compression, cell morphology and mechanical response can be directly regulated, including, but not limited to, changes in cell morphology and intracellular force distribution. Hydrodynamic stimuli: By applying hydrodynamic stimuli such as shear force and changes in the flow field, the physiological environment of cells in blood or tissue fluid can be mimicked, and the physiological activity and mechanical properties of cells can be regulated.

[0035] External stimuli can amplify the differences in cellular mechanical force information between different types of cells, facilitating identification and improving identification efficiency and accuracy. When detecting mechanical force and stiffness using a characterization device that includes a microcolumn, the physical information of the cells can be amplified by changing the stiffness of the microcolumn.

[0036] The adhesion of cells and / or multicellular aggregates can be stabilized by adding cell culture medium and continuing the culture, and / or by using adhesion materials to attach cells and / or multicellular aggregates.

[0037] In this embodiment, physical information of cells in a cell / multicellular aggregate is acquired to enable the identification of interactions between cells and / or multicellular aggregates. By acquiring physical information of cells, this embodiment enables rapid and high-throughput identification of differences between cells / multicellular aggregates and is applicable to drug responses of cells / multicellular aggregates.

[0038] In this embodiment, cellular mechanical forces can be monitored and acquired using a microforce sensor, microrheometer, or cellular mechanical force detection device. These devices can measure the magnitude, direction, and frequency of the force exerted by a cell on a substrate or other cells. By taking measurements at specific time intervals, changes in cellular mechanical forces can be tracked.

[0039] Hardness Monitoring: The hardness of cells or multicellular aggregates can be measured using techniques such as nanoindentation and force-distance curve analysis. These techniques allow for quantitative evaluation of the hardness of cells or aggregates and understanding how it changes under external forces.

[0040] Cell morphology and spatial distribution monitoring: Cell morphology and spatial distribution can be acquired using imaging techniques such as microscopy, confocal microscopy, and atomic force microscopy. These techniques allow observation of cellular morphological features, internal structure, and the spatial distribution of cell aggregates.

[0041] In this embodiment, the physical information of cells can be obtained via a characterization system, which includes the following: Base; and A microcolumn array comprising one or more microcolumns arranged on a base and capable of being deformed under the action of cellular mechanical forces and / or magnetic forces, wherein the microcolumns have a light-reflecting layer.

[0042] Optionally, a light-reflecting layer is placed at the end of the microcolumn away from the base; the base has a light-transmitting portion; the column of the microcolumn has a light-transmitting portion; optionally, the surface and / or base of the microcolumn has an anti-reflective layer.

[0043] The signal is optionally further acquired via an optical signal generator and an optical signal detector. Light emitted from the optical signal generator is directed to the optical reflection layer via the incident light path, and the light reflected by the optical reflection layer is directed to the optical signal detector via the reflected light path.

[0044] Optionally, the light intensity acquired by an optical signal detector is analyzed to obtain physical information about the cells. Optionally, the light intensity acquired by the optical signal detector has a linear correlation with the magnitude of the cell's mechanical force, and different cell types can be realized through qualitative and quantitative analysis.

[0045] Optionally, the characterization apparatus can contain a liquid; if the liquid is a cell culture medium, cells and / or multicellular aggregates are attached and / or cultured. Optionally, cells and / or multicellular aggregates are attached to the microcolumn by an adhesion material placed on the microcolumn.

[0046] In a method for obtaining physical information of cells via a characterization device, multicellular aggregates can be bound to the characterization device in multiple ways. In another specific embodiment, two specific binding methods are provided: 1. First coupling method: A culture medium is placed on a microcolumn of a cell mechanical force detection device, and cells are transplanted into the medium on the microcolumn and cultured to obtain a multicellular aggregate. In other embodiments, this coupling method allows for real-time monitoring of the cell culture process when the physical information of the cells is output in a visualized format, and can be applied to the effects of chemical, biological, and physical external stimuli such as culture medium and drugs on cell growth.

[0047] 2. Second binding method: The cultured multicellular aggregate is directly attached to the microcolumn of the cell mechanical force detection device for detection.

[0048] This embodiment further provides a method for typing and identifying cells and / or multicellular aggregates using the physical information of cells as described above. Typing and identification include the type, state, behavior, spatial omics features and differentiation direction, and stress response of cells and / or multicellular aggregates. Optionally, typing and identification may include selectively separating specific cells or tissues via the physical information of cells.

[0049] Optionally, identification is performed using a cell identification device, which includes an information acquisition unit, a preprocessing unit, a learning unit, and an identification unit: - The information acquisition unit is used to acquire physical information about cells and / or cells in multicellular aggregates. - The preprocessing unit is used to preprocess the physical information of cells to form the physical information of structured cells, which includes the number of cells, the number of cell features, and the characteristic information of each cell feature. - The learning unit uses the physical information of structured cells as input data and is used to establish cell feature models using supervised, unsupervised, or semi-supervised machine learning. - The identification unit is used to apply a cellular feature model to the typing or clustering of cells and / or multicellular aggregates to achieve typing and identification of cells and / or multicellular aggregates.

[0050] In this invention, "identification" refers to identifying known and unknown types of cells and / or multicellular aggregates. In this invention, "typing" refers to typing cells and / or multicellular aggregates based on differences in characteristics, including but not limited to type, state, behavior, and spatial omics features of cells and / or multicellular aggregates, caused by different factors. Cells having the same or similar physical information can be typed to form further different categories.

[0051] The present invention enables rapid and high-throughput identification of differences between cells / multicellular aggregates by acquiring physical information of cells, and is applicable to drug responses of cells / multicellular aggregates. Typing of cells and / or multicellular aggregates refers to typing cells and / or multicellular aggregates based on differences in characteristics, including but not limited to type, state, behavior, and spatial omics features of cells and / or multicellular aggregates caused by different factors.

[0052] Embodiment 2

[0053] This embodiment provides a method for characterizing cells and / or multicellular aggregates, and differs from Embodiment 1 in that it obtains physical information about cells based on different regions within the multicellular aggregate and / or multicellular aggregate at different stages of growth.

[0054] Methods for obtaining physical information about cells include, but are not limited to, placing multicellular aggregates in a specific region, adding cell culture medium to stabilize the attachment of the multicellular aggregates, and facilitating the measurement of the physical information of the cells.

[0055] In other specific embodiments, the characterization system described in Embodiment 1 can be used to obtain physical information about cells. In other specific embodiments, the characterization system can contain cell culture medium; by adding cell culture medium, tissue cell mechanical forces can be obtained while culturing the tissue on the cell mechanical force detection device (characterization device), without the need to remove the tissue from the cell mechanical force device.

[0056] In other specific embodiments, the liquid level of the cell culture medium is higher than the top of the microcolumn. In other specific embodiments, the method for obtaining physical information of tissue cells includes placing the tissue on a characterization system, adding cell culture medium so that the tissue is at least in contact with the cell culture medium, allowing the tissue to stand for 30 minutes or more, continuing to add cell culture medium until the tissue is fully attached to the microcolumn, and then measuring and obtaining the cellular mechanical force of the tissue in real time. Cultivating for 30 minutes or more helps to better fix the tissue and microcolumn.

[0057] Optionally, after the tissue has fully adhered to the cellular mechanical forces, an external stimulus is applied and the change in the cellular mechanical forces of the tissue under the external stimulus is measured. In other specific embodiments, a multicellular aggregate (which may be a tissue) is adhered to a microcolumn by an adhesion material placed on the microcolumn. In other specific embodiments, the multicellular aggregate refers to a tissue, which may be a tissue section of 150-200 μm.

[0058] According to the method of this embodiment: Optionally, tissues may include active tissues, organoids, and extracorporeal organs.

[0059] Optionally, external stimuli are applied to multicellular aggregates before, during, and after the measurement and acquisition of physical information about cells.

[0060] Optionally, after the tissue has fully attached to the cellular mechanical forces, an external stimulus is applied, and the change in the cellular mechanical forces of the tissue under the external stimulus is measured.

[0061] External stimuli can amplify the differences in physical information between cells in different regions of different multicellular aggregates and between multicellular aggregates with different typings, facilitating identification and improving identification efficiency and accuracy. When detecting mechanical force and stiffness using a cell mechanical force detection device including a microcolumn, the physical information of the cells is amplified by changing the stiffness of the microcolumn. Specific external stimuli are described in Embodiment 1.

[0062] Different regions within a multicellular aggregate include, but are not limited to, tumorous and non-tumorous regions within the tissue; after characterization, tumorous and non-tumorous regions within the tissue can be distinguished. These also include, but are not limited to: - Peripheral region: Located on the outer edge of the multicellular aggregate, it is in contact with the surrounding environment and may be exposed to culture medium or culture culture medium. - Central region: This is the central part of a multicellular aggregate, which is usually more densely populated due to increased cell density and may have a different cellular tissue structure. - Peripheral region: This is the region between the peripheral region and the central region, and usually exhibits characteristics different from those of the peripheral and central regions. - Core region: This is the core part of a multicellular aggregate, potentially the region with the highest cell density, and may contain a specific cell type or population. - Surface region: This is the outer surface region of a multicellular aggregate, which may be directly exposed to the external culture medium and is in direct contact with the surrounding environment. - Functional region: A region within a multicellular aggregate that has a specific function or activity, such as a metabolic activity region, a secretory region, or a differentiation region. -Gradient region: A gradient region within a multicellular aggregate that may contain the gradient distribution of signaling molecules or nutrients. - Microenvironment: This is the microenvironment within a multicellular aggregate, which can be affected by cellular secretions, intercellular interactions, or matrix components, and has a significant impact on cellular behavior and function.

[0063] These distinct regions may exhibit differences in cell proliferation, differentiation, signaling, metabolism, and cell interactions, significantly impacting the overall behavior and function of the cell aggregate. This embodiment can characterize, type, and identify not only the regions mentioned above, but also unknown regions.

[0064] This embodiment can form structured information from cellular information in different states of multicellular aggregates (tissues). Different tissues can be divided into two or more different tissues, different states of a single tissue formed at different times or under different external stimuli, or two or more different regions within a single tissue.

[0065] Two or more different tissues: These may be pathological tissue and normal tissue.

[0066] Different states of a single tissue formed at different times or under different external stimuli: These may be different states of tissue corresponding to different times under dynamic changes after drug addition, or changes in tissue during the culture process due to the addition of cell culture medium.

[0067] Two or more different regions within a single tissue: This may include tissue containing both tumor and non-tumor regions.

[0068] This embodiment enables accurate identification of tissue cellular mechanical forces by deforming a microcolumn using the cellular mechanical forces of a multicellular aggregate (tissue), and converting and amplifying these cellular mechanical forces into light reflection signals. It can be applied to real-time monitoring of tissue change processes, and even slight changes in the tissue during the culture process can be acquired, thereby assigning a mechanical fingerprint to each post-change tissue. Hardness can also be measured by inserting the microcolumn into cells using magnetic force, achieving characteristic, accurate, and rapid identification.

[0069] This embodiment can be used to rapidly, directly, non-destructively, and in real time measure the cellular mechanical force of the entire biological tissue and individual cells within that tissue; the cellular mechanical force is measured by contact between cells in the tissue and a microcolumn. Furthermore, since each cell type has a different cellular mechanical strength, different cellular blocks in the tissue, such as tumor and non-tumor areas, can be identified by measuring the mechanical distribution of the entire tissue using a characterization system. In addition, when measuring the cellular mechanical force of the tissue, accurate drug screening can be achieved by directly adding and treating the tissue with a drug, and monitoring the changes in the cellular mechanical force of cells in the tissue in real time to determine whether the drug is effective, with an accuracy rate of over 98%.

[0070] This embodiment is the same as Embodiment 1 except for the differences described above, and will not be repeated here.

[0071] This embodiment provides a method for rapidly, directly, non-destructively, and in real time measuring the mechanical forces of entire biological tissues and individual cells. The mechanical forces of cells can be measured by contact between cells in the tissue and a microcolumn. Furthermore, by measuring the mechanical distribution of the entire tissue using a characterization system, different cellular blocks, such as tumors and non-tumor areas, can be identified. Simultaneously, this method allows for the direct introduction and processing of drugs during the measurement of tissue cellular mechanical forces, enabling real-time monitoring of changes in cellular mechanical forces to evaluate drug effects and achieve accurate drug screening with an accuracy rate of over 98%.

[0072] Furthermore, this method enables real-time monitoring of cellular mechanical forces in tissues during culture and dynamic change processes, allowing for rapid measurement of cellular mechanical forces throughout the entire biological tissue. It also enables the identification of tumor and non-tumor areas using the strength of cellular mechanical forces, and allows for real-time monitoring of changes in tumor cell mechanical forces after drug treatment to determine whether the drug can effectively suppress tumor cell growth.

[0073] This method converts tissue cell mechanical force information into structured information, enabling the determination and identification of different tissue states. Accordingly, it also provides tissue state characterization and identification systems, as well as applications to tissue state identification and drug efficacy evaluation methods.

[0074] Embodiment 3

[0075] This embodiment provides a method for characterizing cells and / or multicellular aggregates, the difference from Embodiment 1 being that it is based on the physical information of cells obtained by the action of a substance on the cells and / or multicellular aggregates.

[0076] The method for obtaining physical information about cells includes the following steps: The multicellular aggregate material is made to interact with the cells and / or the multicellular aggregate; and the physical information of the cells of the cells and / or the multicellular aggregate is detected and acquired.

[0077] Optionally, culture medium is added to bring at least the cells and / or multicellular aggregates into contact with the cell culture medium, and the cells are cultured statically for at least 30 minutes. The addition of cell culture medium is continued until the cells and / or multicellular aggregates are completely attached to a specific area, after which the substance of action is added and the culture is continued, and the physical information of the cells is measured and obtained. Here, culturing for at least 30 minutes helps to better fix the cells / multicellular aggregates to the microcolumn.

[0078] Optionally, external stimuli are added before or during the detection and acquisition of physical information from cells.

[0079] This embodiment is the same as Embodiment 1 in all respects except for the differences described above, and will not be repeated here.

[0080] Here, the term "substance" includes bioactive polymers, chemical substances, bioactive materials, and inactivated biomaterials. The bioactive polymers include proteins, peptides, polysaccharides, and lipids.

[0081] This embodiment acquires cellular mechanical force information of a cell / multicellular aggregate using a cellular mechanical force detection device or cell / cell aggregate characterization system described in any of the above embodiments, or a cellular mechanical force detection method described in any of the above schemes. Specifically, the steps include: placing the cell / multicellular aggregate on the cellular mechanical force detection device, adding cell culture medium to bring the cell / multicellular aggregate into contact with the cell culture medium at least 30 minutes, allowing it to culture statically, continuing to add cell culture medium until the cell / multicellular aggregate is completely attached to the microcolumn, and then measuring and acquiring the cellular mechanical force of the cell / multicellular aggregate. In some specific embodiments, an external factor is added to detect the dynamic change in the cellular mechanical force of the cell / multicellular aggregate under the external factor. In some specific embodiments, the external factor may be added before or during the detection of cellular mechanical force. In some specific embodiments, the substance may be generated by the cell / multicellular aggregate or added from the outside.

[0082] This embodiment also provides a method for acquiring visualized cellular information, including cells and / or multicellular aggregates, before, during, and after interaction between a substance and cells / multicellular aggregates using a cellular mechanical force detection device, and includes visualized information such as the amount of change and distribution of cellular mechanical force. The visualized information is used for the visualization, identification, real-time monitoring, and characterization of interactions between the test substance and cells / multicellular aggregates.

[0083] In other embodiments, the cellular mechanical force information further includes the direction of the cellular mechanical force at the point. In other embodiments, the cellular mechanical force information further includes the change in magnitude or direction of the cellular mechanical force at the point over a certain time interval. In other embodiments, the cellular information further includes cellular morphology information. In other embodiments, the cellular mechanical force information is obtained by the method of the eighteenth embodiment.

[0084] Based on the cell mechanical force detection device of the present invention, it is possible to achieve not only qualitative analysis by visual distinction with the naked eye, but also more intuitive and accurate identification (quantitative and qualitative analysis) of the state of cells / multicellular aggregates based on measured cell mechanical characteristics, and it has been demonstrated that types can be better distinguished by using the cell force field as a marker.

[0085] The present invention also provides a system and method for identifying substances and cells / multicellular aggregates, which converts cellular information, including cellular mechanical force information resulting from the interaction of a substance with cells / multicellular aggregates, into structured information, thereby enabling rapid and automated determination and identification of interactions between a test substance and cells / multicellular aggregates.

[0086] Accordingly, the present invention also provides applications of cell / multicellular aggregate characterization and identification systems and methods in related methods and products where it is necessary to characterize interactions between cell / multicellular aggregates.

[0087] It is applicable in different scenarios and conditions, rapidly determines the mechanism of action between a substance and cells / multicellular aggregates, enables monitoring of the effects of a substance on cells, changes in intracellular and extracellular substances, or the effects of a substance on cells and the state of cellular changes, and allows for the reuse of cell samples.

[0088] Furthermore, the cellular mechanical force detection device of the present invention can detect cellular mechanical forces in multilayer cells, including tumor aggregates, and is applicable to drug screening, regenerative medicine, gene editing, precision medicine, organogenesis, and disease modeling that require multicellular analysis.

[0089] Embodiment 4

[0090] This embodiment provides a method for characterizing cells and / or multicellular aggregates, and differs from Embodiment 3 in that it allows for the acquisition of cellular physical information by having other physical, biological, or chemical stimuli act upon the cells and / or multicellular aggregates.

[0091] The method is: Cells and / or multicellular aggregates can be placed in a specific region (which may be placed in a characterization system in other embodiments), allowing for the monitoring of subtle changes in cellular mechanical forces during culture or under external factors, and enabling the measurement of changes in the state of multicellular aggregates or cells during culture or under external factors to characterize the stress response of cells and / or multicellular aggregates.

[0092] Optionally, external stimuli include drugs, mechanical forces, biochemical factors, electric fields, tropic induction, and dynamic stimuli. One or more combinations of stimuli in a flow field are applied to the culture.

[0093] In optional configurations, different types and intensities of stimuli (mechanical, electrical, or optical) can be applied to the test sample before, during, or after using the characterization system, and manipulations (labeling, solidification, ablation, cutting, extraction, separation, etc.) can be performed on samples at specific locations or regions. Comparative analysis can be performed in combination with other characterization methods (protein staining, histochemical staining, single-cell sequencing, etc.). Optionally, the system may further include a mechanism of action that acts on the characterization system or cells, the mechanism of action being one or more of microfluidics, microneedles, or lasers. By limiting the appropriate microcolumn height, spacing between adjacent microcolumns, and column surface size within the above ranges, cells / multicellular aggregates can be made more stable within the characterization system for materials and cells / multicellular aggregates.

[0094] The method of this embodiment can be used to characterize cell vitality, adhesion, migration, activation, differentiation, and apoptosis.

[0095] In other specific embodiments, stimuli are used to induce stress on cells or / or multicellular aggregates, and include physical stimuli, biochemical stimuli, and stimuli between small molecules and macromolecules on cells or / or multicellular aggregates.

[0096] The physical information of cells obtained includes: cellular mechanical forces and dynamic changes of cells or / or multicellular aggregates when the organism is not under stress, and during / after stress.

[0097] Cells respond to external stimuli, including matrix hardness, shear stress, and mechanical tension, through different mechanisms. The present invention allows for the real-time monitoring of changes in the physical information of cells in the attached cells or multicellular aggregates, as well as real-time monitoring of interactions between cells or multicellular aggregates, or between cells and multicellular aggregates, after fixing and attaching cells or / or multicellular aggregates to a specific location, by applying stimuli or by placing other cells or / or multicellular aggregates on top of the attached cells or / or multicellular aggregates.

[0098] In optional configurations, different types and intensities of stimuli (mechanical, electrical, or optical) can be applied to the test sample before, during, or after characterization using the characterization system, and manipulations (labeling, solidification, ablation, cutting, extraction, separation, etc.) can be performed on samples at specific locations or regions. Comparative analysis can be performed in combination with other characterization methods (protein staining, histochemical staining, single-cell sequencing, etc.).

[0099] Except for the differences described above, this embodiment is otherwise identical to Embodiment 1 and will not be repeated here.

[0100] Embodiment 5

[0101] This embodiment provides a method for characterizing cells or / and multicellular aggregates, the difference from Embodiment 1 being that it is based on the physical information of cells during the culture growth process of an in vitro organ or / and associated cell model. The physical information of cells includes: the physical information of cells or / and cells in any region during the culture process of an organ-associated cell or / and tissue culture.

[0102] In other specific embodiments, the physical information of the cells is used to characterize cells or cell groups, organ tissues, in any region of the growth process of an extracorporeal organ or / and related cell model.

[0103] In other specific embodiments, a mixture of cells and / or tissues with the ECM is cultured.

[0104] In other specific embodiments, the culture method includes achieving culture by controlling the distribution and flow of cells and biomaterials by 3D printing and / or microfluidic methods.

[0105] In other specific embodiments, organ-associated cell and / or tissue cultures are cultured on a characterization device to produce in vitro organ and cell models.

[0106] In other specific embodiments, the specific method includes the following steps: S1, collect microenvironmental parameters in the physiological and pathological state of the corresponding tissue, and fabricate the characterization device on the corresponding extracorporeal organ chip based on the parameters (i.e., the characterization device can be customized on the extracorporeal organ chip). S2. Cultures of the organ-related cells and / or tissues are cultured on the in vitro organ chip. Here, the cultures can be cultured on the in vitro organ chip by 3D printing. S3, optionally, physical and biochemical stimuli are added, including a combination of one or more stimuli in the form of drugs, mechanical forces, biochemical factors, electric fields, and flow fields, and act upon the culture. S4. The external organ chip is used to acquire changes in the cellular mechanical forces of each cell and tissue, thereby enabling the characterization of each cell and organ tissue.

[0107] Optionally, step S4 further includes selectively isolating specific cells or tissues by the characterization.

[0108] The identification unit in the cell identification device applies the cell feature model to organs, cell growth states, or typing or clustering under external stimuli, thereby realizing the identification and characterization of organs and cells in the corresponding states at each time point.

[0109] The characterization system of the present invention forms structured information of organ cells in corresponding states at each time point, analyzes cell information in unknown states to achieve automatic identification of cells in unknown states.

[0110] The in vitro organ chip can mimic the structural microenvironment of human organs, accurately replicating the real organ environment. Simultaneously, it allows for long-term, real-time monitoring of individual cell behavior, enabling organ characterization. This makes it applicable to the establishment of in vitro organ and related cell models, meeting the demand for related models in various research topics.

[0111] In other specific embodiments, the in vitro organ chip is applied to screening for organ-therapeutic agents and to studies of the physiological and pathological states of organ models.

[0112] The in vitro organ chip of this embodiment not only mimics the structural microenvironment of an in vivo organ, but can also be characterized by detecting the cellular mechanical forces of each cell and organ tissue in real time. It can monitor subtle changes in cellular mechanical forces during the culture process or under external stimuli, and measure changes in organ tissue or cells during the culture process or under external stimuli. Here, external stimuli include one or more combinations of stimuli in the form of drugs, mechanical forces, biochemical factors, electric fields, and flow fields, acting on the culture. Unlike conventional life science characterization methods, the characterization method of the present invention is non-invasive, label-free, allows for long-term real-time monitoring of living cells or tissues, and can characterize samples with single-cell resolution. It can more closely approximate the actual environment of an organ.

[0113] Optionally, the chip body is fitted with microcolumns of corresponding softness, hardness, and length according to the organ. Microcolumns of different softness, hardness, and length can be customized according to different organs, allowing for a more realistic simulation of the organ's environment. For example, as a cardiac chip, a cardiac microenvironment can be created on the microchip, including various factors such as mechanical contraction, molecular transport, electrical activity, and biochemical stimulation, offering high customizability. The complex structure and function of the heart can be simulated in a minute space, including various tissue components such as cardiomyocytes, vascular endothelial cells, and extracellular matrix of cardiomyocytes, allowing for a more accurate simulation of cardiac function.

[0114] Optionally, ECM is placed on the surface of the microcolumn. Optionally, a mixture of organ-associated cells and / or tissues and ECM is cultured on the microcolumn. Optionally, the surface of the microcolumn has a tropic ECM coating. Optionally, the culture method includes 3D printing. To achieve better controllability and reproducibility, 3D printing and microfluidic technology can be used to precisely control the distribution and flow of cells and biomaterials, mimicking blood flow in an organ (e.g., the heart). Each parameter of the microenvironment can be standardized, improving experimental reproducibility and data comparableity. Optionally, if the organ is the heart, the cells include one or more combinations of cardiomyocytes, smooth muscle cells, vascular endothelial cells, fibroblasts, stem cells, and immune cells.

[0115] Optionally, the system further includes an electrode device, the microcolumn being made of a conductive material, and the electrode device acting on the microcolumn.

[0116] Optionally, the invention further includes a mechanical imitation device, which is either a mechanical tensioning device for pulling the chip body or a flexible, air-deformable thin film placed at the bottom of a microcolumn. The upper end of the flexible thin film is connected to the microcolumn and the lower end is connected to the base, or the base is the flexible thin film.

[0117] External stimuli are applied to the culture area of ​​the extracorporeal organ before, during, and after the measurement and acquisition of the physical information of the cells.

[0118] External stimuli can amplify the differences in physical information between cells in different regions of a multicellular aggregate, cells of different types, and cells within the multicellular aggregate, thereby facilitating identification and improving identification efficiency and accuracy. When detecting mechanical force and stiffness using a cell mechanical force detection device including a microcolumn, the physical information of the cells can be amplified by changing the stiffness of the microcolumn. Specific external stimuli are as described in Embodiment 1.

[0119] If the organ is optionally the heart, the cells include one or more combinations of cardiomyocytes, smooth muscle cells, vascular endothelial cells, fibroblasts, stem cells, and immune cells.

[0120] The in vitro organ chip of this embodiment is applicable to screening for organ-therapeutic drugs and to research on the physiological and pathological states of organ models.

[0121] The method and in vitro organ chip of this embodiment have better characterization capabilities by detecting cellular mechanical forces, are non-invasive and label-free, enable long-term real-time monitoring of living cells or tissues, and can characterize with single-cell resolution. Through cellular force omics, the in vitro organ chip can promote further development and application of organ research, such as the heart, as an important technological means to overcome the shortcomings of conventional cell and animal models.

[0122] Unlike conventional methods of characterizing life sciences, the external organ chip of this invention more closely resembles the actual organ environment. The heart can create a cardiac microenvironment on the microchip, incorporating various factors such as mechanical contraction, molecular transport, electrical activity, and biochemical stimulation, and is highly customizable. It can mimic the complex structure and function of the heart in a small space, including various tissue components such as cardiomyocytes, vascular endothelial cells, and extracellular matrix of cardiomyocytes, thus more accurately mimicking cardiac function.

[0123] To achieve better controllability and reproducibility, 3D printing and microfluidic technology allow for precise control of the distribution and flow of cells and biological materials, mimicking blood flow in organs such as the heart. Standardization of each parameter in the microenvironment improves experimental reproducibility and data comparability. It is more economical, efficient, safer, and ethical compared to animal experiments and clinical trials. It saves time and costs, and is safer and more ethical.

[0124] The in vitro organ chip of the present invention can characterize the state of organs and individual cells in a short time, at low cost, and with high throughput by monitoring the mechanical forces of each cell in real time. It can also precisely identify and monitor the effects of external stimuli, such as drugs, on organs and cells at each time point over a long period. The accuracy rate for drug screening is over 98%, and the accuracy rate for identifying different states in other external stimulus research methods is also over 98%.

[0125] This embodiment is the same as Embodiment 1 in all respects except for the differences described above, and will not be repeated here.

[0126] Embodiment 6

[0127] This embodiment provides a method for identifying and typing cells and / or multicellular aggregates: Typing and identification can also be performed using the physical information of cells obtained in Embodiments 1 to 5, which includes: The success or failure of transfection of cells or multicellular aggregates is determined by characterizing the interaction between a substance and cells or multicellular aggregates, and the substance includes one or more combinations of proteins and / or peptides, semi-solid media, antibodies or two antibodies; By characterizing the interactions between bioactive substances and cells or multicellular aggregates, high-productivity cells or multicellular aggregates of bioactive substances can be identified and selected. By acquiring the cellular mechanical forces of cells / multicellular aggregates, the system can monitor the effects of genetic engineering on cells, including the detection of small clonal clusters or single cells near large clones; By monitoring cell vitality and condition, it is possible to establish the optimal dose-response curve (or kill curve), determine the minimum effective concentration to kill resistant cells, and optionally, monitor cells in real time during the drug screening process to adjust experimental strategies in a timely manner.

[0128] By acquiring cellular mechanical information, including the growth and differentiation processes of adipocytes, this system monitors the growth and differentiation of adipocytes; optionally, it can be used to monitor the conversion processes of white, beige, and brown adipose tissue in real time.

[0129] The aforementioned identification method includes the following steps: obtaining physical information of cells / multicellular aggregates using a cell-mechanical force detection device to identify the interactions that a substance has with cells / multicellular aggregates; the physical information of the cells includes cell-mechanical force information; the present invention enables rapid and high-throughput identification of differences between cells / multicellular aggregates by obtaining cell-mechanical force, and can be applied to the reactions of cells / multicellular aggregates with substances.

[0130] This embodiment is the same as Embodiment 1 in all respects except for the differences described above, and will not be repeated here.

[0131] Points to note in any of the above embodiments: This embodiment acquires physical information of cells before, during, and after the action.

[0132] The physical information of the cells in this embodiment can be measured in real time, at a specific time, or at a specific time interval, and the physical information of the cells may be continuous or intermittent.

[0133] This embodiment can characterize cells or / or multicellular aggregates at different stages of development and exposed to external stimuli, thereby enabling typing and identification of known or unknown types.

[0134] This embodiment is not limited to characterizing cells at different growth stages or when specific external factors are at play, but can also be used to characterize cells and / or multicellular aggregates when various factors are combined and act upon them.

[0135] With the above-described characteristics, this embodiment can be used for clustering and typing of cells and / or multicellular aggregates, particularly for unknown typing, at any point before, during, or after the substance acts on the cells and / or multicellular aggregates.

[0136] Any of the above embodiments can acquire and analyze the physical information of cells by using the cell mechanical force detection device and characterization system in any of the following embodiments as a cell physical information characterization device or characterization system.

[0137] First embodiment: Cell mechanical force detection device Referring to Figure 1, which is a schematic diagram of the structure of a cell mechanical force detection device, the cell mechanical force detection device shown in the figure includes a translucent base 11 (in other specific embodiments, the base may have a translucent portion, i.e., it does not need to be a fully translucent base, and an opaque portion may be provided) and micropillars 12 that are deformable under the action of cell mechanical forces and are placed on the base 11. The top of the micropillars 12 is coated with a light-reflecting layer 13, and the thickness of the light-reflecting layer 13 is 5 nm (in other embodiments, the thickness of the light-reflecting layer 13 may be between 5 nm and 20 nm -- the thickness of the coating depends on the coating material, and assuming the same coating material is applied, the selection of the coating thickness is limited to ensuring the light-transmitting effect, the stability of the micropillar, and the non-detachment of the connection with the micropillar). The columns of the micropillars 12 can transmit light, and as shown in Figure 1, the incident light is indicated by a solid arrow and the reflected light is indicated by a dashed arrow. The cluster of arrows pointing in opposite directions in the figure represents incident and reflected light rays. (Note: Although the term "coating" is used in this embodiment, it only indicates that the light-reflecting layer 13 in this embodiment is manufactured by a coating method, and does not necessarily limit the manufacturing of the light-reflecting layer 13 to a coating method.) In other specific embodiments, as shown in Figures 1 and 14, the opaque portion of the base is formed by the installation of an anti-reflective layer 105, but is not limited to this.

[0138] Referring to Figure 2, which shows a scanning electron microscope (SEM) image of the micropillar 12 (actual object) of the cell mechanical force detection device of this embodiment, a is a top view of the cell mechanical force detection device and b is a side view of the cell mechanical force detection device. As can be seen from Figure 2, the microstructure of the micropillar of the cell mechanical force detection device is orderly and uniform, its dimensions are controllable, and the mechanical values ​​measured by the cell mechanical force detection device of this embodiment are more precise than those measured by existing cell mechanical force detection devices.

[0139] When using the cell mechanistic force detection device 1 according to this embodiment, the number of micropillars 12 will be one or more. Referring to Figure 3, which is a schematic diagram of the structure of a cell / multicellular aggregate interaction characterization system related to the ninth embodiment of the present invention, is provided for understanding this embodiment. The system shown in Figure 3 includes, in addition to the cell mechanistic force detection device 1 described in this embodiment, an optical signal generator 2 and an optical signal detection device 3 having a light source installed below the base 11. Light rays emitted from the light source are irradiated from the translucent base 11 of the cell mechanistic force detection device 1 to the light reflection layer of the micropillars 12 via the incident light path. The optical signal detection device 3 is used to detect light rays reflected from the light reflection layer 13 at the top of the micropillars. The light rays reflected from the light reflection layer 13 pass through the reflection light path, are subjected to the action of the spectrometer 5, and then enter the optical signal detection device 3. After acquiring the reflected light signal, the optical signal analyzer 4 can compare and analyze the reflected light rays before and after the cell mechanistic force action is generated by the cell mechanistic force detection device 1 and the test cell, and cell mechanistic force information can be acquired. When the microcolumn 12 is not subjected to any force, it maintains an upright position and can reflect the exploration light to the maximum extent. When the microcolumn 12 comes into contact with a cell, the cellular mechanical force causes the microcolumn 12 to deform (including, but not limited to, bending and oscillating), and the level of light reflection decreases. Therefore, the greater the cellular mechanical force, the smaller the resulting light reflection signal, and the magnitude of the cellular mechanical force at that point can be easily inversely estimated by observing the intensity of the light reflection signal.

[0140] Furthermore, the measurement light source in the technical solution of this embodiment can be an infrared laser of a constant intensity. In conventional technical solutions, micro-column measurement requires the acquisition of high-resolution images, and using a laser in this process tends to cause cell phototoxicity or sample fluorescence decolorization. In this technical solution, only the reflected signal needs to be measured, so the effect of an infrared laser within a certain light intensity is negligible on cells, and therefore it is suitable for long-term monitoring of cells.

[0141] Second embodiment: Cell mechanical force detection device The difference from the first embodiment is that the light-reflecting layer 13 is provided not only on the top end face of the micro-column 12, but also on the upper half of the column face of the micro-column 12 (i.e., the curved surface connecting both end faces of the column). In fact, in other embodiments, except that the method of installing the light-reflecting layer 13 on the lower half of the side column face of the micro-column 12 is not adopted because the actual effect is poor, the detection effect that the present invention aims to achieve can be basically realized by installing the light-reflecting layer 13 on the upper half of the side of the micro-column 12. That is, in some other embodiments, the light-reflecting layer 13 is laid at any local position on the upper half side column face or at a local position on the top, and it is not necessarily required to lay it on the entire upper half column face or the entire top end face, and in either case the expected purpose can be achieved, but there may be differences in the data acquired and the effect of post-calculation.

[0142] Furthermore, the definitions of "columnar face" and "end face" of the micro-column appeared in the first and second embodiments of the present invention. That is, while an independent column as we normally understand it should have two end faces and a curved surface (columnar face) connecting the two end faces, the micro-column of the present invention has only a top end face due to the presence of a base, and the other end is fixedly connected to the base or integrally molded with the base. However, in other embodiments, the top end face may be a curved surface that is smoothly connected integrally with the column face, and there is not necessarily an intersection line or clear boundary as shown in the first or second embodiment. In this case, the installation position of the light-reflecting layer 13 is also understood to be the upper half of the column and is not limited to the "end face" or "columnar face".

[0143] Third embodiment: Cell mechanical force detection device Referring to Figure 4, which is a schematic diagram of the structure of a cell / multicellular aggregate characterization system in the tenth embodiment of the present invention, it is used to explain the cell mechanical force detection device 1 of this embodiment. The difference between this embodiment and the first and second embodiments is that there is no requirement for the light transmission performance of the base 11 and the micro-pillars 12 of the micro-pillar array; that is, they may be light-transmitting, opaque, or semi-transmitting. In this case, it is only necessary to change the positions of the optical signal generator 2 and the optical signal detection device 3 and install both above the base 11. In this way, each time the micro-pillar bends or oscillates, the optical signal received by the optical signal detection device 3 changes compared to when the micro-pillar 12 is upright and undeformed, and by analyzing the changes in the optical signal before and after, the relative magnitude of the cell mechanical force can be obtained in the same way, and by calibrating with a standard value, the absolute magnitude of the cell mechanical force can be obtained.

[0144] Fourth embodiment: Cell mechanical force detection device As shown in Figures 1 and 14, this embodiment differs from the first to third embodiments in that an anti-reflective layer 105 is provided in areas other than the region on the surface of the microcolumn 12 where the light-reflecting layer 13 is provided. This design reduces interference of the reflected light signal by the columnar surface layer, improves the signal-to-noise ratio, and enhances the accuracy of the detection results. In other specific embodiments, an anti-reflective layer 105 is provided on the base to further improve the signal-to-noise ratio.

[0145] In some embodiments, the light-reflecting layer 13 may be a gold foil layer. In other embodiments, the light-reflecting layer 13 may be a metal layer or other reflective material having other light-reflecting properties. Different materials may differ in reflective effect, difficulty of manufacturing the reflective layer, and cost, and in actual operation, they can be considered and selected according to specific conditions.

[0146] In the first to fourth embodiments, the cross-sectional shape of the microcolumn 12 is circular. In other embodiments, the cross-sectional shape of the microcolumn 12 may be elliptical or polygonal. In various specific embodiments of the present invention, different cross-sections can achieve different objectives. For example, a circular cross-section has isotropic characteristics, meaning that the mechanical properties of the microcolumn itself are not sensitive to direction. On the other hand, an elliptical cross-section is anisotropic, meaning that the mechanical properties of the microcolumn itself are sensitive to direction, thereby allowing control of sensitivity to force fields in different directions and to some extent adjusting the cellular orientation (the geometric form of most cells is asymmetrical, and in this invention, cellular orientation refers to the morphological asymmetry, polarity, or directionality exhibited by the cell. For example, when fitting the shape of a cell projection with an ellipse, the major axis of the ellipse can be considered the direction the cell has). This is because, when the cross-section is elliptical, the cross-section has a major axis and a minor axis, and it is easier to push the microcolumn along the minor axis than along the major axis, and the deformation under relative force conditions is also greater. In some stretched embodiments, when cells are seeded on such a microcolumn, anisotropic mechanical interaction exists between the cells and the microcolumn, causing the cells to grow along a certain side. When applied to fluids, the direction of the fluid can be measured.

[0147] In the first to fourth embodiments, the dimensions of the microcolumn array are: column height 10 nm to 500 μm, column spacing 10 nm to 50 μm, and column surface diameter 50 nm to 50 μm. Microcolumns within this dimensional range can satisfy the basic operating conditions for microcolumns used as sensors, namely, that they are at least deformable and do not collapse. On this basis, the following functions can be realized by adjusting the different microcolumn array dimensions. For example, by adjusting the aspect ratio of the microcolumn (which can be understood as the ratio of height to cross-sectional diameter / side length / major axis in the layer plane of the microcolumn), a certain microcolumn deformation performance adjustment function can be realized, which can better mimic the internal organ tissue environment (e.g., bone tissue and nerve tissue of different hardnesses).

[0148] In addition, the overall dimensions of the array or the number of microcolumns 12 on a given area of ​​base 11 also affect the ligand density (the number of points on the surface where cells can adhere). The sparser the microcolumn 12 array, the fewer adhesion points cells can find, which has a significant impact on cell behavior.

[0149] The size of the cross-sectional area of ​​a microcolumn also affects cell adhesion behavior. This is because a certain area is necessary for the formation of focal adhesion plaques through cell adhesion. In the case of nano-microcolumns, the small cross-sectional area affects the formation of focal adhesion.

[0150] In short, by combining the inherent properties of the material with specific microcolumn array dimensions, it is possible to achieve cell support effects, chip stability, and measurement accuracy that better meet the requirements. By adjusting the distribution of the microcolumn array, it is possible to control and influence the cell adhesion state to some extent.

[0151] In the first to fourth embodiments, the material of the microcolumn 12 is polydimethylsiloxane (PDMS). In other main embodiments of the present invention, the material of the microcolumn 12 may be other polymer materials, such as silicon-based polymers, photoresist polymer materials, conductive polymer materials, temperature-sensitive polymer materials, etc. The reason that the main embodiments of the present invention mainly employ polymer materials is that current polymer materials have deformation properties that are relatively suitable for the application of the present invention. However, the implementation of the present invention is not limited to polymer materials for the microcolumn material and can be extended to all materials with corresponding deformability, and any of them can realize the inventive concept of the present invention. Simply put, the condition that the material of the microcolumn must satisfy is that it has a certain force-receiving deformability, and in some embodiments a certain light transmittance is required, but the latter is not a requirement in all embodiments. When manufacturing a microcolumn with a material with limited light transmittance, the inventive concept of the present invention can be realized in the same way by simply appropriately setting the positions of the optical signal generator and optical signal detector.

[0152] Overall, the hardness (deformability) of the microcolumn 12 can be adjusted according to actual requirements through multiple technical dimensions such as dimensions (mainly aspect ratio), selection of material type, control of the degree of crosslinking of polymer materials, and chemical or physical surface treatment.

[0153] Referring to Figure 5, Figure 5 is a scanning electron microscope image of a microcolumn (polydimethylsiloxane) with a light-reflecting layer (gold) at the top. Figure 5a is a scanning electron microscope image of the microcolumn. Figure 5b is an elemental characterization diagram of the top region of the microcolumn. Figure 5c is an elemental characterization diagram of the side region of the microcolumn (excluding the top region). The scanning electron microscope images in Figure 5 allow us to characterize the material composition of the microcolumn, and we can confirm that the element Au is present at the top of the microcolumn and the element Si is present at other positions on the microcolumn.

[0154] Fifth embodiment: Cell mechanical force detection device The difference between this embodiment and the first to fourth embodiments is that a substance 106 having cell adhesion properties is provided on the apical end faces of some of the microcolumns 12 in the microcolumn array. In this embodiment, collagen from extracellular matrix molecules is used, while in other embodiments, collagen may be included, and one or more combinations of extracellular matrix molecules such as fibronectin, vitronectin, laminin, and elastinogen may also be used. In some other embodiments, other types of substances having cell adhesion properties may be provided on the apical end faces of all or some of the microcolumns in the microcolumn array 12, such as extracellular matrix mimics (e.g., peptides containing RGD adhesion sequences), substances 106 having a cell adhesion promoting mechanism (e.g., polylysine), or substances that interact with cell surface receptors.

[0155] By providing a substance 106 with such cell adhesion properties on the apical end face of the microcolumn 12, the adhesion of cells to the microcolumn 12 can be effectively promoted, enabling the regulation of cell adhesion, proliferation, migration, state, and differentiation. Furthermore, by providing a substance with cell adhesion properties, such as an extracellular matrix protein like fibronectin, on the apical end face of some of the microcolumns in a pre-set region of the microcolumn array, these microcolumns can be configured to form a specific shape. As a result, cells tend to adhere to microcolumns of a specific position and shape, enabling high-throughput mechanical measurements while controlling the size, shape, and tropism of the cells.

[0156] In the cell mechanical force detection device of this embodiment, the cell adhesion substance contributes to the stability of the cell / multicellular aggregate on the microcolumn.

[0157] Sixth embodiment: Cell mechanical force detection device The difference between this embodiment and the fifth embodiment is that, as in the fifth embodiment, a substance 106 having cell adhesion properties is provided on the apical end face of some of the microcolumns 12 in the microcolumn array, whereas in this embodiment, a substance having cell adhesion inhibitory properties (e.g., F-127) is provided on the columnar face (end face or side face) of the portion of the microcolumn 12 where the substance having cell adhesion properties is not provided on the apical end face. In other specific embodiments, a substance 107 having cell adhesion inhibitory properties is provided on the base. By installing the substance 107 having cell adhesion inhibitory properties, cells tend to adhere to the microcolumn at a specific position and shape (on the apex), allowing for high-throughput mechanical measurements while controlling the size, shape, and tropism of the cells, and ensuring that the cellular mechanical force acts on the microcolumn through the apex.

[0158] Seventh embodiment: Cell mechanical force detection device The difference between this embodiment and the first to fourth embodiments is that the microcolumns, each having a cell adhesion substance on its apical end face, form a pre-set pattern. Specifically, a cell adhesion molecular layer of a particular pattern can be printed using microprinting technology to promote cell adhesion in these areas. The so-called pre-set pattern may be in the shape of a triangle, quadrilateral, polygon, circle, or ellipse. The effects of the pre-set pattern include: firstly, controlling intercellular contact by forming a pattern composed of a cell adhesion substance, thereby meeting the requirements for high-throughput data acquisition; secondly, achieving dimensionality reduction in data processing by unifying cell shapes, thereby reducing the difficulty of analysis; and finally, limiting the cell adhesion area to achieve the objective of controlling cell size, shape, tropism, differentiation state, etc., and further controlling actin filaments to adjust the cell dynamics, thereby meeting the requirements of certain specific technical requirements.

[0159] In other embodiments substantially similar to this embodiment, the unprinted areas of a pre-set pattern can be treated with substances that inhibit cell adhesion, such as BSA (bovine serum albumin) or F127 (high molecular weight nonionic surfactant), to suppress cell adhesion in these areas, thereby achieving directional adhesion, control of cell morphology, or mimicry of a specific cellular microenvironment.

[0160] In some other embodiments, fibronectin (FN) is described as an example of a substance having cell adhesion properties, but this does not limit the embodiments of the present invention. Polydimethylsiloxane microstamps having square and rectangular convex patterns on their surfaces are used, and fibronectin is adhered to the surface of the microstamp. By microcontact printing, the fibronectin on the convex portion of the stamp is transferred to the upper metal reflective layer of the microcolumn. After adhesion, the microcolumn is immersed in F-127 solution to inhibit cell adhesion in the areas where fibronectin is not present. Finally, after thoroughly washing the microcolumn with physiological saline, cell membrane-stained fibroblasts are seeded on the surface of the microcolumn, and fluorescence imaging of the cells is performed (shown in Figure 6a). Simultaneously, high-resolution measurement of the intracellular force field is performed (shown in Figure 6b). Referring to Figures 6a and 6b, Figure 6a is a fluorescence imaging image of cells adhered to a pre-set pattern composed of a group of microcolumns with fibronectin at the top, showing that the cell adhesion area is limited to the region with fibronectin. Based on this, the cell adhesion area can be limited by a pre-set pattern, and the mechanical monitoring of cells can be performed while controlling the cell size, shape, tropism, and differentiation state. Figure 6b is a magnitude distribution map of the cell mechanical force resolved from the light reflection signal measured on the microcolumn.

[0161] In some other embodiments, OKT3 antibody (a substance that interacts with cell surface receptors) or fibronectin (FN) are described as examples of substances having cell adhesion properties, but this does not limit the embodiments of the present invention. Refer to Figures 7a to 7d. Figure 7a is a schematic diagram of a test in which OKT3 antibody was used as a substance having cell adhesion properties. The upper part of Figure 7b is a fluorescence imaging diagram of cells adhering to the top of a microcolumn where OKT3 antibody and fibronectin are provided, respectively. The lower part of Figure 7b is a distribution diagram of light reflection signals (reflecting the magnitude of cellular mechanical force) measured on the microcolumn. Figure 7c is a comparison diagram of the mechanical magnitudes measured on the OKT3 antibody and fibronectin coated surfaces, respectively. Figure 7d is a diagram of the cellular mechanical changes after T cells were seeded on the OKT3 antibody surface (top of the microcolumn). Specifically, the above-described test involves coating the top of the microcolumn of the same or different parts of the cell mechanical force detector with OKT3 antibody or fibronectin, and seeding T cells onto the surface of the cell mechanical force detector that has a cell adhesion substance. As can be seen from Figures 7a to 7d, a cell mechanical force detector coated with a substance that interacts with cell surface receptors (e.g., OKT3 antibody) or fibronectin (FN) on the microcolumn surface can be used to monitor the effects and interactions of mechanical force on cells in real time.

[0162] Eighth embodiment: Cell mechanical force detection device The difference between this embodiment and the first to seventh embodiments is that the cell mechanical force detection device further includes a cell restriction mechanism, the cell restriction mechanism includes one or more restriction surfaces 16, the restriction surface 16 is perpendicular to the plane in which the base 11 is located, connected to the base 11 or integrally molded with the base 11, and the height of the restriction surface 16 is greater than the microcolumn 12, surrounding a preset number of microcolumns 12.

[0163] The function of the cell restriction mechanism provided in this embodiment is single-cell isolation detection, that is, to avoid cell-to-cell contact or adhesion during detection, to restrict cell morphology, and to facilitate high-throughput testing. Depending on different requirements, the number of restricting surfaces 16 or the enclosed shape in the cell position restriction mechanism may vary. For example, the restricting surface 16 included in the cell position restriction mechanism may be a single cylindrical surface, three planes forming a triangular cross-sectional shape that are contiguous and enclose a certain number of microcolumns, four planes perpendicular to each other and contiguous, forming a rectangular shape that encloses a certain number of microcolumns, N planes contiguous, forming an N-sided shape that encloses, or a single curved surface with a nearly circular cross-section. In other words, the cross-sectional shape composed of the restricting surface 16 is a controllable closed shape, and its area (or the number of microcolumns that can be accommodated in that space) is also controllable.

[0164] In actual embodiments, depending on the manufacturing process, the cell restriction mechanism may also manifest in the following forms: A. Refer to Figure 8, which is a schematic diagram a of the structure of a cell mechanistic force detection device having a cell restriction mechanism. In the figure, the cell restriction mechanism and the base 11 are integrally molded, that is, the material forming the cell restriction mechanism has a plurality of concave spaces 15, the walls of the concave spaces 15 are restriction surfaces 16, the depth of the concave spaces 15 is the height of the restriction surfaces 16, the bottom of the concave spaces 15 is the base 11, and there are a plurality of microcolumns 12 in each concave space 15.

[0165] B. Refer to Figure 9, which is a schematic diagram b of the structure of a cell mechanical force detection device having a cell restriction mechanism. In the figure, the restriction surface 16 is a structure bonded to the base 11.

[0166] Ninth embodiment: Cell mechanical force detection device The difference between this embodiment and the eighth embodiment is that the cell restriction mechanism in this embodiment is a silicon thin film.

[0167] Specifically, refer to Figures 10a to 10c. Figure 10a is a diagram of a cell mechanistic force detection device employing a silicon thin film as a cell restriction mechanism. In Figure 10a, the silicon thin film is adhered to a base after laser perforation, and microcolumns are provided in each pore. The silicon thin film restricts cell morphology and migration, while simultaneously controlling intercellular contact or adhesion. Figure 10b is a fluorescence micrograph of the cell mechanistic force detection device employing a silicon thin film as a cell restriction mechanism under light reflection. Figure 10c is a magnified view of Figure 10b. In some embodiments, the size of each pore in the silicon thin film can be set to match the size of a single cell, making it suitable for single-cell adhesion and allowing for restriction of cell contact, cell morphology, and their migration range.

[0168] Tenth Example: Cell and / or Multicellular Aggregate Characterization System A characterization system for cell / multicellular aggregate interactions includes a cell mechanical force detection device 1, an optical signal generator 2, and an optical signal detection device 3 as described in the first or second embodiment. Both the optical signal generator 2 and the optical signal detection device 3 are located below the base 11 of the cell mechanical force detection device 1. The optical signal generator 2 has a light source, and the light emitted from the light source irradiates the light reflection layer 13 of the microcolumn 12 via the incident light path (sequentially passing through a translucent base and a translucent microcolumn column), causing reflection, and the reflected light enters the optical signal detection device 3 via the reflection light path (sequentially passing through a translucent microcolumn column and a translucent base). The optical signal detection device 3 can acquire reflected light signals before and after contact between the microcolumn 12 and cells. In some other embodiments, such a characterization system for cell / multicellular aggregate interactions further includes an optical signal analyzer 4, which can obtain cell mechanical force information, including the magnitude, direction, and changes within a certain time range, by comparing, analyzing, and calculating the reflected light signals before and after contact between the microcolumn 12 and cells.

[0169] Eleventh Example: Cell and / or Multicellular Aggregate Characterization System Referring to Figure 4, Figure 4 is a characterization system for cell / multicellular aggregate interactions related to an eleventh embodiment of the present invention, which includes a cell-mechanical force detection device 1 as described in the third embodiment, and further includes an optical signal generator 2 and an optical signal detection device 3. Both the optical signal generator 2 and the optical signal detection device 3 are located above the base 11 of the cell-mechanical force detection device 1, the optical signal generator 2 has a light source, and the light rays emitted from the light source are irradiated onto the light reflection layer 13 via the incident light path and reflected, and the optical signal detection device 3 can acquire reflected light signals before and after contact between the microcolumn 12 and cells.

[0170] In embodiments of the present invention, the optical signal detection device may be a microscope, a charge-coupled element CCD, a complementary metal-oxide-semiconductor CMOS, a photomultiplier tube PMT and a photoelectric converter PT, a film, or other optical signal detection element having equivalent functionality, and the present invention is not specifically limited. In some embodiments of the present invention, when a microscope is used as the optical signal detection device, it is not necessary to provide an independent optical signal generator. The cell mechanical force detection device of the present invention can be directly placed on the microscope stage, the light source of the microscope can be used as the optical signal generator, and the objective lens 101 of the microscope (a 5x objective lens is sufficient, and it is not necessary to rely on a high-magnification optical objective lens) can be used as the optical signal detection device. When other optical signal detection devices (e.g., a charge-coupled element CCD) are used, it is necessary to provide an independent optical signal generator. In embodiments of the present invention, the optical signal generator may be an LED, a halogen lamp, a laser (e.g., an infrared laser), or another light source, or another device having these light sources, and the present invention is not specifically limited.

[0171] The following describes in detail the visualization process for using the cell / multicellular aggregate interaction characterization system related to this embodiment for monitoring cellular mechanical forces.

[0172] Referring to Figure 11, Figure 11 is a fluorescence microscope image monitoring cellular mechanical forces using the cell / multicellular aggregate interaction characterization system of this embodiment. Specifically, cells (for example, fibroblasts are used in this embodiment) are placed on a microcolumn of the cellular mechanical force detection device, and an optical signal detection device (for example, a microscope is used in this embodiment) converts the cellular mechanical force information into an optical signal to form an image, which can be used for visualization observation, and changes in cellular mechanical forces can be fed back in real time.

[0173] Twelfth Example: Cell and / or Multicellular Aggregate Characterization System Referring to Figure 4, which shows a cell / multicellular aggregate interaction characterization system related to the twelfth embodiment of the present invention, comprising the cell mechanical force detection device 1 described in the third embodiment, and further comprising an optical signal generator 2, an optical signal detection device 3, and an optical signal analyzer 4. Both the optical signal generator 2 and the optical signal detection device 3 are located above the base 11 of the cell mechanical force detection device 1. The optical signal generator 2 has a light source, and the light rays emitted from the light source are irradiated onto the optical reflection layer 13 via the incident optical path and reflected. The spectrometer 5 is a semitransparent semi-reflective or other equivalent optical element, the main purpose of which is to simplify the optical path design. The optical signal detection device 3 can acquire reflected light signals before and after contact between the microcolumn 12 and the cells. The optical signal analyzer 4 can obtain cell mechanical force information, including the magnitude, direction, and changes within a certain time range, by comparing, analyzing, and calculating the reflected light signals before and after contact between the microcolumn 12 and the cells.

[0174] In embodiments of the present invention, the optical signal analyzer may be an optical image analysis software such as ImageJ, Matlab, Fluoview, Python, or other optical image analysis elements with equivalent functionality, or a combination of these analysis software, and the present invention is not specifically limited.

[0175] The following describes in detail the detection and analysis process of the cell / multicellular aggregate interaction characterization system related to this embodiment.

[0176] Refer to Figures 12a to 12c. Figure 12a is a schematic diagram of the cell / multicellular aggregate characterization system. Figure 12b is an image of the light reflection signal of the cell mechanical force detector acquired by the optical signal detector. Figure 12c is a visualization effect diagram of the mechanical magnitude and distribution.

[0177] As shown in Figure 12a, on the cell mechanical force detection device, a metal reflective layer is provided at the top of each microcolumn, and an anti-reflective layer is provided on the sides. When no cells are present, light rays are shone onto the microcolumn from below, and are completely reflected and fully received by the optical signal detection device (e.g., a CCD camera). However, when cells adhere to the microcolumn, the microcolumn tilts due to the cellular force generated by the movement of the cells, and the reflected signal decreases. After analyzing the optical reflected signal, the cellular force intensity can be calculated.

[0178] Furthermore, an optical signal detection device (e.g., a CCD camera) is used to collect images of the light reflection signals from the cell mechanical force detection device and magnified images of the local cell adhesion region (shown in Figure 12b). Next, an optical signal analyzer is used to further process the images in Figure 12b and convert them into Figure 12c, which visualizes the mechanical magnitude and distribution in a more intuitive way.

[0179] The specific processing steps are as follows: First, based on Figure 12b, a bright-field reflection signal diagram (I, focused on cells) is obtained. Next, a Fourier transform is performed on the image, the high-frequency signals are filtered, and an inverse Fourier transform is performed to calculate and obtain a microcolumn reflection signal image (I0) without shift. Then, the I and I0 images are further processed to convert the reflection signal diagram into a more intuitive cell mechanics diagram (subtracting the I signal value from the I0 signal value), which is then standardized to obtain a more intuitive cell mechanical force intensity diagram j.

[0180] Examples 1 to 9 of the present invention can also measure hardness simultaneously. By applying an external force, the microcolumn is rotated and inserted into the cells, completing the measurement of the hardness of the cells and / or multicellular aggregates.

[0181] Thirteenth Embodiment: Method for Calculating Mechanical Force, Interrelationship between Mechanics and Light Reflection Signals This embodiment combines a cell / multicellular aggregate interaction characterization system described in any of the 10th to 12th embodiments or a cell-mechanical force detection method described in the 14th embodiment to illustrate a method for calculating mechanical forces in embodiments of the present invention. Furthermore, a fluid is used as an external force to verify the interrelationship between mechanics and light reflection signals.

[0182] Referring to Figure 13, Figure 13a is a schematic diagram of the structure of the cell mechanical force detection device in the microfluidic environment before fluid switching. Figures 13b and 13c are comparative diagrams of the bright-field microscope image of the microcolumn, the reflected light signal distribution diagram, and the superposition effect diagram of the two before fluid switching. Figure 13d is the light reflected signal intensity diagram before fluid switching. Figure 13e is a linear relationship diagram between the light reflected signal and the microcolumn displacement. Here, the superposition effect diagram refers to the effect diagram formed by superimposing the bright-field microscope image and the reflected light signal distribution diagram of the microcolumn.

[0183] First, as shown in Figure 13, the cell mechanical force detection device is integrated into the microfluidic channel. When the external force velocity increases, the microcolumn is displaced, and simultaneously, the angle of the microcolumn surface reflective layer changes (Figures 13a to 13c). As can be seen from Figure 13d, the light reflection signal changes from strong to weak before and after fluid opening and closing. Specifically, the amount of microcolumn displacement is changed by utilizing the strength of the flow velocity, and the displacement of the top of the microcolumn relative to the bottom of the microcolumn is captured using a confocal microscope. The mechanical force acting on each microcolumn can then be calculated using the following formula.

[0184]

number

[0185] In the equation, F represents the mechanical force that displaces the microcolumn by an angle δ, E represents Young's modulus, kbend represents the ideal spring constant of the isolated nanocolumn, D represents the diameter of the microcolumn, and L represents the height of the microcolumn.

[0186] Simultaneously, by recording the light reflection signal at the top of the microcolumn and plotting the light reflection signal and the amount of microcolumn displacement as shown in Figure 13e, a linear relationship diagram and linear range between the light reflection signal (reflecting cellular mechanical force) and the microcolumn displacement can be obtained.

[0187] Fourteenth Example: Method for Detecting Cellular Mechanism A method for detecting cellular mechanical forces, comprising the following steps: A light beam is emitted using the optical signal generator 2 in the cell / multicellular aggregate interaction characterization system described in any of the 10th to 12th embodiments. The optical signal detection device 3 in the cell / multicellular aggregate interaction characterization system described in any of the 10th to 12th embodiments is used to detect light rays after they have acted upon the cell mechanical force detection device 1. The optical signal detection device 3 can acquire reflected light signals before and after contact between the microcolumn 12 and the cells in the cell mechanical force detection device 1. In some other embodiments, the optical signal analyzer 4 in the cell / multicellular aggregate interaction characterization system can obtain cell mechanical force information, including the magnitude, direction, and changes within a certain time range of the cell mechanical force, by comparing, analyzing, and calculating the reflected light signals before and after contact between the microcolumn 12 and the cells.

[0188] Referring to Figures 14a to 14d, Figures 14a and 14b are schematic diagrams of the structure of the microcolumn of the cell mechanical force detection device before and after contact with cells. Figure 14b is the reflected light signal acquired by the optical signal detection device (CCD photosensitive element), and a clear attenuation of the reflected signal is observed in the region where the force field around the cell is large. Figure 14c is a monitoring diagram of the cell migration process (the cell membrane was stained, excited with a fluorescent light source, and the migration process was recorded with a CCD photosensitive element). Figure 14d is a reflected light signal distribution diagram during the cell migration process (the change in the reflected light signal during the migration process was recorded with a CCD photosensitive element). As can be seen from Figures 14c and 14d, the reflected light signal is clearly attenuated in the area where the cell applies force. Figure 14d shows real-time monitoring of the reflected light signal during the cell migration process, and the mechanical force during the migration process is fed back in real time using the reflected light signal. By monitoring reflected light signals during cell migration using an optical signal detection device, it is possible to provide real-time feedback on changes in cellular mechanical forces during cell migration.

[0189] Fifteenth Example: Method for Manufacturing a Cell Mechanical Force Detection Device A method for manufacturing a cell mechanical force detection device, comprising the following steps: laying a light-reflecting layer 13 on the top or upper half-columnar surface of a microcolumn 12 to obtain a microcolumn 12 having a reflective layer on the top or upper half-columnar surface.

[0190] Sixteenth Example: Method for Manufacturing a Cell Mechanical Force Detection Device A method for manufacturing a cell mechanical force detection device, comprising the following steps: A uniform anti-reflective layer is plated over the entire microcolumn 12; the anti-reflective layer is removed from the top or upper half of the columnar surface; and a light-reflecting layer 13 is laid on the top or upper half of the microcolumn 12.

[0191] Seventeenth Example: Method for Manufacturing a Cell Mechanical Force Detection Device The difference between this embodiment and the fifteenth and sixteenth embodiments is that the step "laying a light-reflecting layer 13 on the top or upper half-columnar surface of the microcolumn 12" specifically involves uniformly sputtering a reflective metal onto the top or upper half-columnar surface of the microcolumn to obtain a microcolumn having a metallic light-reflecting layer on the top or upper half-columnar surface.

[0192] Eighteenth Example: Cell Identification Method (including Visual Qualitative Identification and Accurate Qualitative and Quantitative Identification) This embodiment specifically provides cell-mechanical force information obtained by a cell / multicellular aggregate interaction characterization system described in any of the tenth to twelfth embodiments or a cell-mechanical force detection method described in the fourteenth embodiment, and applies it to a cell identification method.

[0193] Refer to Figures 15a to 15g. Figure 15a is a fluorescence imaging diagram of a mixed system of healthy cells and non-small cell lung cancer cells. Figure 15b is a light reflection signal distribution diagram of a cell mechanical force detector acquired by an optical signal detector. Figure 15c is a visualization effect diagram of mechanical magnitude and distribution. Figure 15d is a magnified view of a typical single-cell force distribution of healthy cells and non-small cell lung cancer cells in Figure 15c. Figure 15e is a morphological comparison diagram of healthy cells and non-small cell lung cancer cells. Figure 15f is a comparison diagram of reflection signal intensity after mixing healthy cells, non-small cell lung cancer cells, and these cells in different proportions. Figure 15g is a clustering analysis diagram obtained by structuring Figure 15c and then processing it based on structured cell information.

[0194] Specifically, this embodiment targets healthy cells (Normal) and lung non-small cell cancer cells (Cancer). The cell membranes of healthy cells and lung cancer cells are pre-stained using two different fluorescent dyes (Dil & DIO), mixed in a certain ratio, and then added to the same cell mechanical force detector (in other embodiments, it may be added to different, independent cell mechanical force detectors).

[0195] Furthermore, an optical signal detection device (a microscope is used in this embodiment) is used to collect an image of the light reflection signal from the cell mechanical force detection device (shown in Figure 15b). The high-resolution force field distributions within the two types of cells are directly rendered by the optical signal detection device, converted into a readable light intensity attenuation signal (reflecting the cell force intensity), and displayed in the image (shown in Figure 15c). Based on the difference in the degree of light attenuation of the two types of cells shown in the image in Figure 15c, the two types of cells can be intuitively distinguished by observation with the naked eye (qualitative analysis).

[0196] Furthermore, the light reflection signal in Figure 15c is further processed using an optical signal analyzer. Specifically, in this embodiment, information is collected from the cell force field in Figure 15c obtained using an optical signal analyzer (in this embodiment, ImageJ and Python analysis software are used; in other embodiments, other image analysis software can be used), and information on the magnitude of cell mechanical forces is collected for multiple points in each cell, thereby obtaining multipoint cell mechanical force magnitude data in multiple cells. Preprocessing is performed on the acquired cell mechanical force magnitude information to form structured cell information, and analysis is performed based on the structured cell information to obtain a cell morphology comparison diagram of healthy cells and lung non-small cell cancer cells (shown in Figure 15e).

[0197] The structured cell information includes the number of cells, the number of cell features, and characteristic information for each cell feature (for example, cell adhesion area and cell roundness in this embodiment). In this case, the structured cell information can be considered as a two-dimensional feature matrix, where N is the number of cells and P is the number of cell features, where P=2, meaning the cell features are: magnitude of cell mechanical force and distribution of cell mechanical force within the cell.

[0198] Furthermore, using the above-mentioned structured cell information as input data, a cell feature model is established using supervised learning (pre-staining and contrasting two types of cell lines using different cell membrane dyes (Dil & DIO)). This cell feature model is then trained using structured cell information from a large number of cells, and after obtaining the clustering analysis diagram shown in Figure 15g, the acquired cell feature model is applied to the typing and identification of unknown types or states of cells. This makes it possible to perform clustering typing on normal healthy cells and cancer cells using structured cell feature data (magnitude of cell mechanical force, distribution of cell mechanical force within cells) as input data, and to identify unknown cell types using an optical signal analyzer (in this embodiment, ImageJ and Python analysis software are used; in other embodiments, other clustering analysis software can be used).

[0199] Figure 15e shows that there are no statistically significant clear differences in morphology (including cell adhesion area and cell roundness) between different cells. Figure 15f shows a clear difference in the reflected signal intensity (reflecting cellular force) between normal cells and tumor cells, and that the reflected signal intensity and mixing ratio exhibit a constant linear relationship after mixing normal cells and tumor cells in a certain proportion. This allows for more intuitive and accurate identification of the state and type of cells by cellular mechanical characteristics measured by the cellular mechanical force detection device of the present invention, compared with other cell characteristics (e.g., morphological information such as cell adhesion area and cell roundness in Figure 15e) (quantitative and qualitative analysis).

[0200] Furthermore, data from Figures 15d and 15f show that tumor cells exhibit higher mechanical force magnitudes and more non-uniform distributions than normal cells. By visualizing cellular mechanical force using image technology, it is possible to intuitively observe clear differences in the force field characteristics of different cells with the naked eye. In addition, after structuring the force field magnitudes at each point of different cells using image analysis software, a comprehensive analysis is performed to obtain cell morphology information in Figure 15e, reflection signal intensity (reflecting cellular force) in Figure 15f, and clustering analysis diagram in Figure 15g. The present invention enables accurate identification of cell types by performing clustering typing and quantitative analysis on different cells (for example, healthy cells and non-small cell lung cancer cells in this embodiment) through a comprehensive analysis of force field structure information at each point of a cell.

[0201] From the above, it has been demonstrated that, based on the cell mechanical force detection device of the present invention, not only can qualitative analysis be performed by intuitively distinguishing cells with the naked eye, but the state and type of cells can be identified more intuitively and accurately based on the measured cellular mechanical characteristics (quantitative and qualitative analysis), and that cell types can be better distinguished by using the cellular force field as a marker.

[0202] The cell identification method described above is applicable to various factors, including typing and identification of cells / multicellular aggregates before, during, and after the external factors described in Embodiment 1 act on the cells / multicellular aggregates.

[0203] Nineteenth Example: Method for Detecting Cell Vitality This embodiment specifically provides cellular physical information obtained by a cell / multicellular aggregate characterization system described in any of the tenth to twelfth embodiments or a cellular mechanical force detection method described in the fourteenth embodiment, and applies it to monitoring cellular vitality.

[0204] Refer to Figures 16a to 16c, where Figure 16a is a schematic diagram of the operation flow of the cell vitality detection method. Figure 16b is a comparison diagram of cell vitality measured by the MTT method and cell mechanical force measured by the apparatus, system, or method of the present invention after treating A549 cells with different doses of 5FU for 24 hours. Figure 16c is a comparison diagram of cell vitality measured by the MTT method and cell mechanical force measured by the apparatus, system, or method of the present invention after treating A549 cells with different doses of 5FU for different durations.

[0205] Specifically, in this example, non-small cell lung cancer cells A549 were cultured on multiple cell mechanism detection devices, treated with 5-fluorouracil (5-FU), a cell proliferation inhibitor, at different doses, and cell mechanisms at different time points were monitored using the cell / multicellular aggregate interaction characterization system described in any of Examples 10 to 12 or the cell mechanism detection method described in Example 14. Cell proliferation and cytotoxicity at different time points were monitored using the CCK-8 kit, and cell vitality measured by the MTT method was used as a control group to obtain the data in Figures 16b and 16c.

[0206] As shown in Figures 16b and 16c, after measurement using the conventional MTT measurement method and the apparatus, system, or method of the present invention, both the cell vitality measured by the MTT measurement method and the cell vitality reflected by cell mechanical force tend to decrease gradually in a dose-dependent manner, meaning that cell mechanical force and cell vitality are positively correlated.

[0207] Furthermore, as shown in Figure 16b, after treatment with different doses of 5FU for 24 hours, the decrease in cell vitality can be reflected with a greater magnitude by mechanical force compared to the control group DMSO, thereby allowing for a more intuitive assessment of cell vitality. As shown in Figure 16c, when treated with 5FU for 12 hours, the change in cell vitality measured by the MTT method is not clear. On the other hand, by measuring mechanical force, the decrease in cell mechanical force can be observed at an earlier time point than when the decrease in cellular metabolic activity is detected by the MTT method. Specifically, a clear downward trend appears at 6 hours with a treatment dose of 0.5 μM, and a clear downward trend appears at 3 hours with a treatment dose of 1 μM, thereby allowing for a more sensitive characterization of the decrease in cell vitality.

[0208] Based on the above, this embodiment is a highly sensitive and effective method for evaluating the drug response activity of cells by directly detecting cellular mechanical forces using a cellular mechanical force detection device.

[0209] Twentieth Example: Characterization Method Based on Interactions Between Cells and / or Multicellular Aggregates This embodiment acquires cellular physical information of a cell / multicellular aggregate using a cell mechanical force detection device or characterization system described in any of the embodiments described above, or a cell mechanical force detection method described in any of the schemes described above. Specifically, it includes the following steps: The cell / multicellular aggregate is placed on a cell mechanical force detection device, cell culture medium is added to ensure the cell / multicellular aggregate is in contact with the cell culture medium at least for 30 minutes, and cell culture medium is continued to be added until the cell / multicellular aggregate is completely attached to the microcolumn. Then, the cell mechanical force of the cell / multicellular aggregate is measured and obtained.

[0210] In some specific examples, an external stimulus is applied, and the dynamic changes in the cellular mechanical forces of cells / multicellular aggregates under the external stimulus are detected.

[0211] Here, external stimuli can be added before or during the detection of cellular mechanical forces.

[0212] Different cell / multicellular aggregates can be divided into: two or more different cell / multicellular aggregates, one cell / multicellular aggregate in different states formed at different times or under different external stimuli, and two or more different regions within one cell / multicellular aggregate.

[0213] Two or more different cell / multicellular aggregates: these may include a pathological cell / multicellular aggregate and a normal cell / multicellular aggregate.

[0214] 21st Example: Typing and Identification Method Based on Interactions Between Cells and / or Multicellular Aggregates This embodiment acquires cellular physical information of cells / multicellular aggregates using a cellular mechanical force detection device or characterization system described in any of the embodiments described above, or a cellular mechanical force detection method described in any of the schemes described above. Based on the cellular physical information, cells / multicellular aggregates are identified before, during, and after interaction between cells and / or multicellular aggregates.

[0215] Specifically, this includes: S1, a cell mechanical force detection device acquires visualized cell information, including cell / multicellular aggregates before, during, and after interactions between cells / multicellular aggregates, and includes visualized information such as the magnitude and distribution of changes in cell mechanical force. S2. The visualization information is used for the visualization and identification of the test cells and multicellular aggregates.

[0216] In some specific embodiments, the cell mechanistic force detection device further includes a cell restriction mechanism, the cell restriction mechanism including one or more restriction surfaces, the restriction surfaces being planes or curved surfaces perpendicular to the plane of the base location, connected to or integrally molded with the base, and the height of the restriction surfaces being greater than the microcolumns and surrounding a predetermined number of microcolumns. Interacting first cell / multicellular aggregates and second cell / multicellular aggregates can be restricted to a specific region, making it easier to observe changes in their respective cell mechanistic forces, and the first cell / multicellular aggregates and second cell / multicellular aggregates have opportunities to come into contact, promoting their interaction, and the contact area is fixed, so that the first cell / multicellular aggregates and second cell / multicellular aggregates remain two independent cell groups when interacting, facilitating observation and subsequent data analysis and quantification.

[0217] Optionally, the cell restriction mechanism is a silicon thin film, with multiple pores provided within the silicon thin film, and microcolumns provided within the pores, each pore accommodating one or more cells or one or more multicellular aggregates. A fixed number of cells can be cultured in an orderly manner within the micropores.

[0218] Example 21: Method for identifying cells or / or multicellular aggregates This embodiment acquires physical information of cells and / or multicellular aggregates by means of a cell mechanical force detection device or characterization system described in any of the embodiments described above, or a cell mechanical force detection method described in any of the plans described above, and types and identifies cells and / or multicellular aggregates based on the physical information of the cells.

[0219] The physical information of the aforementioned cells is obtained based on at least one of the following cases: (1) Interactions between cells and multicellular aggregates; (2) Intercellular interactions; (3) Interactions between multicellular aggregates; (4) Cells or / or multicellular aggregates at different stages of development; (5) Different regions within a multicellular aggregate; (6) The substance acting on cells and / or multicellular aggregates; (7) Other physical, biological, or chemical factors acting on cells and / or multicellular aggregates.

[0220] Specifically, this includes: S1. Attach cells / multicellular aggregates to a microcolumn and measure the physical information of the cells; S2, during and after the process of adding a substance or performing other actions on other cells / multicellular aggregates, cellular information of the attached cells / multicellular aggregates is acquired. The cellular information includes physical information of a cell at a certain point in the cell / multicellular aggregate acquired based on a cell mechanical force detection device, and the physical information of the cell includes the magnitude of the cell mechanical force at that point. Specifically: Cell information is collected for multiple cells on the cell mechanical force detection device using an optical signal detection device (or in combination with an optical signal analyzer), cell mechanical force magnitude information is collected for multiple points on each cell, and multipoint cell mechanical force magnitude data is acquired among the multiple cells; S2, 3. Preprocessing is performed on the acquired cell information to form structured cell information. The structured cell information includes the number of cells, the number of cell features, and the characteristic information of each cell feature. At this time, the structured cell information can be considered as a two-dimensional feature matrix, where N is the number of cells and P is the number of cell features, and where P=1, i.e., the cell feature is the magnitude of the cell's mechanical force; S3, 4. Using structured cell information as input data, a cell feature model is established by supervised, unsupervised, or semi-supervised machine learning. This cell feature model is then applied to cells and / or multicellular aggregates at different growth stages, as well as to typing and clustering whose state has changed due to other factors, and further distinguishes different typings.

[0221] In some other embodiments, the physical information of the cell further includes the direction of the cellular mechanical force at that point. In some other embodiments, the physical information of the cell further includes the change in the magnitude or direction of the cellular mechanical force at that point over a period of time. In some other embodiments, the cell information further includes cell morphological information. In some other embodiments, the physical information of the cell is obtained by the method of the 20th embodiment. In some other embodiments, the cellular mechanical force detection device further includes a cell restriction mechanism that allows the interacting first cell / multicellular aggregate and second cell / multicellular aggregate to interact while being independently held.

[0222] Based on the cell mechanical force detection device of the present invention, it is possible to achieve not only qualitative analysis through intuitive distinction by the naked eye, but also more intuitive and accurate identification (quantitative and qualitative analysis) of the state of cells / multicellular aggregates based on measured cell mechanical characteristics, and it has been demonstrated that types can be better distinguished by using the cell force field as a marker.

[0223] Example 23: Evaluation method based on cellular mechanical forces derived from interactions between cells or cell aggregates This embodiment acquires physical information of cells and / or multicellular aggregates by means of a cell-mechanical force detection device or characterization system described in any of the embodiments described above, or a cell-mechanical force detection method described in any of the methods described above, and performs typing and identification of cells and their aggregates under the interaction conditions based on the physical information of the cells. The method is as follows: S1, using polydimethylsiloxane (PDMS) material, a thin film with a thickness of 5-10 μm is fabricated using microfabrication technology, and multiple micropores with a diameter of approximately 200 μm are created in the thin film. These PDMS microporous thin films are treated with Pluronic F127 solution, dried, and then precisely positioned on a microcolumn array of a cell mechanical force detection device. S2. Lung cancer tumor cells are uniformly distributed on the above apparatus, with approximately 20 tumor cells occupying each 200 μm diameter micropore to form cell aggregates. After 1 day of culture, cells that did not adhere are washed away, and at this time, the cellular mechanical force signals of the cell aggregates in each micropore are recorded. S3 is added, and real-time monitoring of the mechanical force changes of the cell aggregate is initiated. This process not only ensures that a fixed number of cells are cultured in an orderly manner within the micropores, but also helps to monitor their mechanical force changes at high throughput. The design of the apparatus of the present invention ensures that each cell aggregate has the opportunity to come into contact with other cells, and the contact area of ​​the cell aggregate with the chip is fixed, which is very advantageous for subsequent data analysis and quantification.

[0224] Furthermore, the application of this microporous device is not limited to tumor cells; it can also be applied to the study of cell aggregates (spheroids) or organoids, allowing for effective observation of the effects of various cells on cell aggregates or organoids. This method provides an efficient and accurate experimental platform for cell-mechanical dynamics research.

[0225] Twenty-fourth example: A method for evaluating the effect of immune cells on tumor multicellular spheres using cytomechanisms. This embodiment acquires physical information of cells and / or multicellular aggregates by means of a cell-mechanical force detection device or characterization system described in any of the embodiments described above, or a cell-mechanical force detection method described in any of the schemes described above, and identifies interactions between immune cells and tumor multicellular spheres. The specific operating steps are as follows: Using polydimethylsiloxane (PDMS) material, a microporous thin film with a thickness of 5-10 μm and a pore diameter of approximately 200 μm is fabricated using microfabrication technology. This PDMS microporous thin film is immersed in Pluronic F127 solution, dried, and then laid on a microcolumn array of a cell mechanical force detection device. Next, lung cancer tumor cells A549 are uniformly distributed on the apparatus described above, and approximately 20 tumor cells are contained in each 200 μm diameter micropore, forming cell aggregates. After 1 day of culture, cells that did not adhere are removed, and the cellular mechanical force signals of the cell aggregates in each micropore are recorded. S2, T cell Jurkat cells are added to the system, and real-time monitoring of cellular mechanical changes in tumor cell aggregates is initiated. This method not only allows for the orderly culture of a fixed number of cell populations in micropores, but also helps in monitoring their cellular mechanical changes at high throughput. The apparatus of the present invention ensures that each cell aggregate has an opportunity to come into contact with immune cells, and the response of tumor cells to immune cells can be effectively monitored.

[0226] This embodiment, through precisely designed experimental steps, not only allows for the orderly cultivation of a fixed number of tumor cell aggregates in a microporous structure, but also enables the evaluation of the effects of immune cells on tumor multicellular spheres at the cellular level. By monitoring changes in cellular mechanical forces in real time, this embodiment provides a novel and effective method for evaluating the tumor cell-killing effect of immune cells.

[0227] Example 25: A method for evaluating the effects of tumor cells on mesothelial cells using cellular mechanics. This embodiment acquires physical information of cells and / or cells in multicellular aggregates by a cell-mechanical force detection device or characterization system described in any of the embodiments described above, or by a cell-mechanical force detection method described in any of the schemes described above, which is acquired based on the effect that tumor cells have on vascular endothelial cells, thereby enabling characterization, typing identification, and evaluation. The specific steps are as follows: S1. A polydimethylsiloxane (PDMS) material with a thickness of 5-10 μm is used to fabricate a structural thin film containing micropores with a diameter of approximately 200 μm. This PDMS microporous thin film is immersed in Pluronic F127 solution, dried, and then laid on a microcolumn array of a cell mechanical force detection device. In S2, the Met5A mesenteric cell system is uniformly distributed on a cell mechanical force detection device, and approximately 20 endothelial cells are contained in each 200 μm diameter micropore to form cell aggregates. After 1 day of culture, cells that did not adhere are removed, and the cell mechanical force signals of the mesenteric cell aggregates in each micropore are recorded. In step S3, the ovarian cancer cell line OVCAR3 is added to the system, and real-time monitoring of changes in mesothelial cell mechanisms is initiated. This example not only allows for the orderly culture of a fixed number of mesothelial cells in micropores, but also enables the identification of interactions between tumor cells and mesothelial cells through high-throughput monitoring of changes in mechanisms.

[0228] This embodiment allows for effective monitoring and analysis of the effects of tumor cells on mesothelial cells, providing novel experimental methods and technical means for studying the angiogenesis process of tumors and the mechanisms of action on mesothelial cells.

[0229] Example 26: A method for evaluating the effects of tumor cells on vascular endothelial cells using cytomechanisms. This embodiment acquires physical information of cells and / or cells in multicellular aggregates by a cell-mechanical force detection device or characterization system described in any of the embodiments described above, or by a cell-mechanical force detection method described in any of the schemes described above, which is acquired based on the effect that tumor cells have on vascular endothelial cells, thereby enabling characterization, typing identification, and evaluation. The specific steps are as follows: S1. A polydimethylsiloxane (PDMS) material with a thickness of 5-10 μm is used to fabricate a structural thin film containing micropores with a diameter of approximately 200 μm. This PDMS microporous thin film is immersed in Pluronic F127 solution, dried, and then laid on a microcolumn array of a cell mechanical force detection device. S2, vascular endothelial cell systems (HUVECs) are uniformly distributed on a cell mechanistic detection device, accommodating approximately 20 endothelial cells in each 200 μm diameter pore to form cell aggregates. After 1 day of culture, cells that did not adhere are removed, and the cell mechanistic signals of the vascular endothelial cell aggregates in each pore are recorded. In step S3, lung cancer cell line A549 is added to the system, and real-time monitoring of changes in cellular mechanical forces of vascular endothelial cells is initiated. This example not only allows for the orderly culture of a fixed number of vascular endothelial cells in micropores, but also enables the identification of interactions between tumor cells and vascular endothelial cells through high-throughput monitoring of changes in cellular mechanical forces.

[0230] This embodiment allows for effective monitoring and analysis of the effects of tumor cells on vascular endothelial cells, providing novel experimental methods and technical means for studying the angiogenesis process of tumors and their mechanisms of action on vascular endothelial cells.

[0231] Example 27: A method for evaluating the effect of sperm cells on egg cells using cellular mechanics. This embodiment provides a method based on cellular mechanical force detection to evaluate the effects of spermatids on egg cells and to provide a novel technological tool to the field of reproductive biology research. The method utilizes a cellular mechanical force detection device or characterization system and a method for detecting cellular mechanical forces to acquire cellular mechanical force information of cells or multicellular aggregates, and based on this, identifies intercellular interactions. The specific operating steps of this embodiment are as follows: First, a structural thin film containing micropores with a diameter of approximately 30 μm is fabricated using polydimethylsiloxane (PDMS) material, with a thickness of 5-10 μm. This PDMS microporous thin film is treated with Pluronic F127 solution, dried, and then laid on a microcolumn array of a cell mechanical force detection device.

[0232] Next, mouse oocytes are uniformly distributed on the cell mechanical force detection device described above, with approximately one oocyte contained in each 30 μm diameter micropore. After culturing these oocytes for 2 hours, cells that did not adhere are removed, and the cells are cultured for another 6 hours to 1 day.

[0233] Subsequently, mouse spermatogonial cells are added to the system, the fertilization process is carried out, and real-time monitoring of changes in the cellular mechanical forces of the oocyte is initiated. By precisely controlling the placement of only one oocyte in each micropore, this method allows for precise observation and analysis of the effects of spermatogonial cells on a single oocyte, providing an effective technological pathway for studying the mechanodynamic interactions between cells during the fertilization process.

[0234] This embodiment enables precise monitoring of interactions between sperm and egg cells, providing an important experimental basis for a deeper understanding of fertilization mechanisms and early embryonic development. Furthermore, applications of this method include, but are not limited to, the optimization of assisted reproductive technologies for humans and the development of new drugs or therapeutic methods.

[0235] Example 28: Method for evaluating the interaction between cell aggregates and other factors using cellular mechanical forces (magnitude of cellular mechanical forces only, some data labeled, some data unlabeled) The following steps are included: S1, obtain cellular information of multiple cells of known different cells or / or a multicellular aggregate. Here, some cells are of multiple known cell types or known cellular states, and the remaining cells are of unknown cell types or unknown cellular states. The cellular information is the magnitude of the cellular mechanical force at a certain point in the cell, obtained based on a cellular mechanical force detection device. This step specifically includes: collecting information on the above multiple types of cells using a cellular mechanical force detection device, collecting cellular mechanical force magnitude information for multiple points in each cell, and obtaining multipoint cellular mechanical force magnitude data in multiple cells; S2. Preprocessing is performed on the acquired cell mechanical force magnitude information to form structured cell information. The structured cell information includes the number of cells, the number of cell features, and the characteristic information of each cell feature. At this time, the structured cell information can be considered as a two-dimensional feature matrix, where N is the number of cells and P is the number of cell features, and where P=1, i.e., the cell feature is: the magnitude of the cell mechanical force; S3. Using the above structured cell information as input data, a cell feature model is established using semi-supervised machine learning. The cell feature model is then trained using a large amount of structured cell information (including both labeled and unlabeled cells). Subsequently, the cell feature model is applied to typing / clustering cells of unknown types or states.

[0236] In other embodiments similar to this embodiment, optimization or improvement can be carried out in the following manner: For a single cell, further information processing is performed on the obtained magnitude information of the cell mechanical force at multiple points, for example, calculating the following: the average value of the magnitude of the cell mechanical force per unit area; the distribution of the magnitude of the cell mechanical force within the cell; and other information of the same dimension. These can be added to the two-dimensional feature matrix described in step S2 as new cell features, that is, the content of P is expanded, and it can be known through subsequent machine learning which features can better distinguish cells with different degrees of drug resistance and typing cells of non-resistant cells.

[0237] Twenty-ninth Embodiment: A method for evaluating a cell or / and a cell aggregate based on physical information of the cell (the magnitude and direction of the cell mechanical force, without labels) Including the following steps: S1. Obtain the physical information of the cell. The physical information of the cell is the magnitude and direction of the cell mechanical force at a certain point in the cell and the cell hardness obtained based on a cell mechanical force detection device. Specifically: A cell mechanical force detection device (a nano-microcolumn sensor in this embodiment) is used to collect cell information for a plurality of cells. Here, information on the magnitude and direction of the cell mechanical force is collected for multiple points of each cell, and magnitude and direction data of the cell mechanical force at multiple points in the plurality of cells are obtained; S2. Perform preprocessing on the obtained information on the magnitude and direction of the cell mechanical force to form structured cell information. The structured cell information includes the number of cells, the number of cell features, and the feature information of each cell feature. At this time, the structured cell information can be regarded as a two-dimensional matrix of a feature matrix (Feature matrix). Here, N is the number of cells, and P is the number of cell features. Here, P = 2, that is, the cell features are: the magnitude of the cell mechanical force and the direction of the cell mechanical force; S3. Using the above structured cell information as input data, utilize unsupervised machine learning to establish a cell feature model, and apply the cell feature model to the clustering of cells of unknown types or unknown states. Specifically, the S2 step in this embodiment processes cell information as follows: Assume that a total of n cell mechanical force vector data (size and direction) are obtained within a certain cell, and these point positions are:(

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[0238] For example, based on each point position in each cell, the center point can be calculated as follows:

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[0239] Please refer to FIG. 17. FIG. 17 is a schematic diagram for scalarizing the displacement information of a certain point position in the fourth embodiment of the present invention. Each point in the figure represents a point position, and the depth of the color of each point position indicates that the force is small to large from light to dark. After obtaining the cell axis of each cell, each point position can be further quantized: calculate the included angle θ between the displacement vector of each point and the cell axis. Each point position can be combined with the magnitude of the force (scalar). For example, consider the magnitude d of the force as the weight, and each point position as a single scalar

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[0240] In other embodiments similar to this embodiment, it can be optimized or improved in the following manner: For a single cell, further information processing is performed on the magnitude of the cell mechanical force or the direction information of the cell mechanical force obtained at multiple points, for example, calculate the following: the average value of the magnitude of the cell mechanical force per unit area; the distribution of the magnitude of the cell mechanical force inside the cell; the distribution of the cell mechanical force vector inside the cell; and other information of the same dimension, and these can be added to the two-dimensional feature matrix described in step S2 as new cell features, that is, expand the content of P, and then it can be known through subsequent machine learning which features can better distinguish different types or states of cells.

[0241] Thirtieth Embodiment: A Method for Evaluating Cells or Cell Aggregates by Cell Mechanical Force (Magnitude and Direction of Cell Mechanical Force, with Labels) Including the following steps: S1. Physical information of cells from different cell / multicellular aggregates is obtained. The cell information includes the magnitude and direction of the cellular mechanical force at a certain point in the cell, as well as the cell stiffness, obtained based on a cellular mechanical force detection device. Specifically: Information is collected from the above multiple types of cells using a cellular mechanical force detection device, and here, magnitude information of the cellular mechanical force is collected for multiple points in each cell, thereby obtaining multipoint cellular mechanical force magnitude data from multiple cells; S2. Preprocessing is performed on the acquired information regarding the magnitude of the cell mechanical force and cell stiffness to form structured cell information. This structured cell information includes the number of cells, the number of cell features, and the characteristic information of each cell feature. In this case, the structured cell information can be considered as a two-dimensional feature matrix, where N is the number of cells and P is the number of cell features, where P=2, i.e., the cell features are: the magnitude of the cell mechanical force and the direction of the cell mechanical force; S3. Using the above structured cell information as input data, a cell feature model is established using supervised machine learning, the cell feature model is trained using structured cell information from a large number of cells, and then the cell feature model is applied to typing cells of an unknown type or unknown state. For example, this embodiment employs the Random Forest (RF) algorithm to extract significant features and estimate model parameters, then applies it to new cells to estimate labels corresponding to the new cells, i.e., applies the cell feature model to typing cells of an unknown type or unknown state. In other embodiments, it is also possible to employ machine learning algorithms / ideas such as Support Vector Machine (SVM) or deep learning to complete the appropriate model establishment and training learning work.

[0242] Referring to Figures 18 and 19, Figures 18 and 19 are result figures A and B, respectively, of using a cell feature model established in an extended embodiment of the fifth embodiment of the present invention to identify unknown cells or unknown cell characterization types. In Figure A, different rows represent different cell types, and different columns represent different samples. The black dots in the figure are the top 50 significant features (or significant vertices, which can be called significant vertices, where a vertices refer to a location within a cell, and the physical information of cells obtained from different locations is different) extracted by a random forest algorithm. Figure B shows the significant distinction effect of three different cell types using the top 50 significant features (significant vertices). Significant features learned based on labeled data can be used for dimensionality reduction visualization of the data. Subsequently, cell typing and identification can also be performed based on dimensionality reduction data via a clustering algorithm.

[0243] In other embodiments similar to this embodiment, optimization or improvement can be achieved in the following manner: For a single cell, further information processing is performed on the acquired multi-point cell mechanical force magnitude or cell mechanical force direction information to calculate, for example, the following: the average value of the cell mechanical force magnitude per unit area; the distribution of cell mechanical force magnitude within the cell; and the distribution of cell mechanical force vectors within the cell. This information is of multiple dimensions and can be added as new cell features to the two-dimensional feature matrix described in step S2, that is, the contents of P are expanded, and subsequent machine learning can determine which features better distinguish cells of different types or states.

[0244] 31st Example: Method for evaluating cells or cell aggregates based on cellular physical information (magnitude and direction of cellular mechanical forces, some data labeled, some data unlabeled) The following steps are included: S1. Physical information of multiple cells is obtained. Here, some cells are of multiple known cell types or known cellular states, and the remaining cells are of unknown cell types or unknown cellular states. The physical information of the cells is the magnitude of the cellular mechanical force at a certain point in the cell, obtained based on a cellular mechanical force detection device. Specifically: Information is collected for the above multiple types of cells using a cellular mechanical force detection device, and here, information on the magnitude of the cellular mechanical force is collected for multiple points in each cell, thereby obtaining multipoint cellular mechanical force magnitude data in multiple cells; S2, the acquired information on the magnitude of the cellular mechanical force is preprocessed to form structured cell information. This structured cell information includes the number of cells, the number of cell features, and the characteristic information of each cell feature. In this case, the structured cell information can be considered as a two-dimensional feature matrix, where N is the number of cells and P is the number of cell features, where P=2, i.e., the cell features are: the magnitude of the cellular mechanical force and the direction of the cellular mechanical force. S3. Using the above structured cell information as input data, a cell feature model is established using semi-supervised machine learning, the cell feature model is trained using structured cell information from a large number of cells, and then the cell feature model is applied to typing cells of an unknown type or state.

[0245] In other embodiments similar to this embodiment, optimization or improvement can be achieved in the following way: For a single cell, further information processing is performed on the acquired multi-point cell mechanical force magnitude or cell mechanical force direction information to calculate, for example, the following: the average value of the cell mechanical force magnitude per unit area; the distribution of cell mechanical force magnitude within the cell; the distribution of cell mechanical force vectors within the cell; and these are equal-dimensional information which can be added as new cell features to the two-dimensional feature matrix described in step S2, that is, the contents of P can be expanded, and subsequent machine learning can determine which features can better distinguish cells of different types or states.

[0246] Thirty-second example: Method for evaluating interactions between cells or cell aggregates using physical information of cells (instantaneous value of cellular mechanical force vector, change in cellular mechanical force vector within a certain time interval, unlabeled) The following steps are included: S1. Cell information is acquired. The cell information is the instantaneous value of the cell mechanical force vector at a certain point in the cell, acquired based on a cell mechanical force detection device, and the change in the cell mechanical force vector at that point within a certain time interval. Specifically: Cell information is collected for multiple cells using a cell mechanical force detection device, and information on the magnitude and direction of the cell mechanical force is collected for multiple points in each cell, thereby acquiring multipoint cell mechanical force magnitude and direction data in multiple cells; S2. Preprocessing is performed on the acquired information regarding the magnitude and direction of cellular mechanical forces to form structured cell information. This structured cell information includes the number of cells, the number of cell features, and the characteristic information of each cell feature. At this time, the structured cell information can be considered as a two-dimensional feature matrix, where N is the number of cells and P is the number of cell features; S3. Using the above structured cell information as input data, a cell feature model is established using unsupervised machine learning, and this cell feature model is applied to clustering cells of an unknown type or state.

[0247] In this embodiment, the acquired data includes not only the instantaneous value of the cellular mechanical force vector at a specific point within the cell, but also its changes over a certain time interval. Therefore, the acquired single-cell mechanical data can be analogous to an image (instantaneous value) or a video (changes over time). In this way, if the current grid of cells can be analogous to pixel points in an image, and the information recorded at each point (multiple cellular features such as force magnitude and direction) can be analogous to the color corresponding to the pixel point, then subsequent machine learning can refer to machine learning algorithms in the fields of image and video data processing. For example, machine learning widely applied to image recognition, or more precisely, a convolutional neural network (CNN) in deep learning, can be used to model and analyze the data.

[0248] 33rd Example: Method for evaluating interactions between cells or cell aggregates using cellular mechanical forces (instantaneous value of cellular mechanical force vector, change in cellular mechanical force vector within a certain time interval, with labels) The following steps are included: S1. Physical information of cells of different cell types or cellular states (which may be known or unknown) is obtained. The cellular information consists of the instantaneous value of the cellular mechanical force vector at a certain point in the cell and the change in the cellular mechanical force vector at that point within a certain time interval, obtained based on a cellular mechanical force detection device. Specifically: Cellular information is collected for multiple cells using a cellular mechanical force detection device, and information on the magnitude and direction of the cellular mechanical force is collected for multiple points in each cell, thereby obtaining multipoint cellular mechanical force magnitude and direction data in multiple cells; S2. Preprocessing is performed on the acquired information regarding the magnitude and direction of cellular mechanical forces to form structured cell information. This structured cell information includes the number of cells, the number of cell features, and the characteristic information of each cell feature. At this time, the structured cell information can be considered as a two-dimensional feature matrix, where N is the number of cells and P is the number of cell features; S3. Using the above structured cell information as input data, a cell feature model is established using supervised machine learning, the cell feature model is trained using structured cell information from a large number of cells, and then the cell feature model is applied to typing (i.e., identifying) cells of unknown types or states. In this invention, "identification" should be understood as identification in a broad sense, and includes both "typing" (including determining the type or state of a cell) and "clustering" (including clustering cells that may be of the same or similar type or state, but whose specific cell state or type is unknown, but which may have the same or similar properties). For example, this embodiment employs the Random Forest (RF) algorithm to extract significant features and estimate model parameters, then applies it to new cells to estimate labels corresponding to the new cells, i.e., applies the cell feature model to typing cells of unknown types or states. In other embodiments, it is also possible to employ machine learning algorithms / ideas such as Support Vector Machines (SVM) or deep learning to complete the corresponding model establishment and training work.

[0249] In this embodiment, the acquired data includes not only the instantaneous value of the cellular mechanical force vector at a specific point within the cell, but also its changes within a certain time interval. Therefore, the acquired single-cell mechanical data can be analogous to an image (instantaneous value) or a video (multiple instantaneous values ​​within a certain time dimension). In this way, if the current grid of cells can be analogous to pixel points in an image, and the information recorded at each point (multiple cellular features such as force magnitude and direction) can be analogous to the color corresponding to the pixel point, then subsequent machine learning can refer to machine learning algorithms in the fields of image and video data processing. For example, machine learning widely applied to image recognition, or more precisely, a convolutional neural network (CNN) in deep learning, can be used to model and analyze the data.

[0250] Thirty-fourth embodiment: This embodiment provides a cell physical characterization apparatus and system. As shown in Figure 1, this embodiment provides a cell physical characterization device that utilizes a light reflection layer, a type of magnetic material, or a magnetic metal light reflection layer to influence the intensity of the light reflection signal, thereby enabling the measurement of multimodal biophysical information of cells.

[0251] The top of the microcolumn 12 has a coating of a magnetic metal (e.g., iron, cobalt, nickel, etc.) (in other embodiments, this can be replaced with other magnetic materials, and the magnetic material may be installed on the side of the microcolumn or inside the column, as long as the microcolumn can generate a magnetic force under a magnetic field). This coating having a magnetic metal can function as a light-reflecting layer 105. In a preferred embodiment, the layer installed at the top of the microcolumn 12 is a magnetic metal light-reflecting layer.

[0252] It should be noted that although the term "coating" is used in this embodiment, it only indicates that the light-reflecting layer 13 is manufactured by a coating method, and does not necessarily limit the manufacturing of the light-reflecting layer 105 to a coating method. For example, it can also be manufactured by sputtering or vapor deposition.

[0253] The characterization system consists of one characterization device, an optical signal emitter, an optical signal detection device, and a magnetic field emitter. Here, the optical signal emitter is used to emit a predetermined light ray, the optical signal detection device is used to detect the light ray reflected from the optical reflection layer 13, and the magnetic field emitter is used to emit a magnetic field and generate a magnetic force with the magnetic metal. The light ray emitted from the optical signal emitter is irradiated onto the optical reflection layer 13 via the incident optical path, and the light ray reflected by the optical reflection layer 13 enters the optical signal detection device via the reflected optical path.

[0254] When measuring the multimodal biophysical characteristics of a cell using the above cell physical characterization system, the specific operating steps are: S1. The test (characterization) cells are cultured on the cell physical characterization apparatus shown in Figure 1, and after culturing for 1-2 days, the test (characterization) cells are allowed to fully adhere to and grow on the physical characterization apparatus; S2, the optical signal emitter emits a predetermined ray; S3. The optical signal detection device detects the light rays after they have acted on the cell physical characterization device. In this embodiment, "act" may refer only to the reflection of a predetermined light ray by a light-reflecting layer installed at either the apex or side of the microcolumn of the cell physical characterization device, or it may refer to the reflection of a predetermined light ray by light-reflecting layers installed at both the apex and side of the microcolumn. Preferably, the magnetic metallic light-reflecting layer installed at the apex of the microcolumn may tilt in one direction under the magnetic force of a magnetic field of a specific direction and intensity emitted by a magnetic field emitter, piercing, deforming, pulling, or oscillating the cells to be characterized, and simultaneously generating a reflection of light rays during the deformation process of the microcolumn. Therefore, by employing the system of this embodiment, it is possible to measure the mechanical force of the cells to be characterized individually, or the hardness of the cells to be characterized individually, or to measure the mechanical force and hardness of the cells to be characterized simultaneously.

[0255] As shown in Figure 31, in some other specific embodiments, two cell physical characterization devices provided in this application are placed opposite each other to form a double-sided structure, where the outer side is the base and the inner side surrounds a three-dimensional encapsulation cavity (sandwich structure) of cells or multicellular aggregates. The volume or height of the three-dimensional encapsulation cavity can be adjusted according to actual needs. For example, if the cells to be characterized are opposite sides of a single cell, the height of the three-dimensional encapsulation cavity can be controlled between 5 nm and 2 mm. If the cells to be characterized are biological tissues, the height and volume can be adjusted to be correspondingly larger, with the height even reaching 5 cm and the volume 30 cm³. 3 It is possible to reach this point.

[0256] Example 35: Using a cell mechanics chip to monitor organoid adhesion and evaluate responses to chemotherapy drugs and immune cell attacks. This embodiment provides an immuno-organoid chip. The response of organoids to chemotherapeutic agents and immune cell attacks is evaluated by monitoring changes in the cellular mechanistic forces of organoids on the chip.

[0257] S1. Tip preparation: Select a cell mechanics tip with a microcolumn structure, and coat the top of the microcolumn with an appropriate extracellular matrix (ECM) to promote organoid attachment and growth. Apply an anti-adhesion treatment to the sides of the microcolumn and between the microcolumns. S2. Organoid Culture: Place the cultured organoids on a mechanical chip. Ensure that the organoids are in contact with the chip surface and that they adhere to the chip. It is also possible to directly add cells and corresponding extracellular matrix material to the chip and culture the organoids directly, monitoring the mechanical responses and changes during the organoid development process. S3. Monitoring of organoid attachment: Light reflection signals are used to monitor the attachment status of organoids on the mechanical chip in real time and observe changes in cellular mechanical forces. S4. Addition of chemotherapy drug: Add an appropriate amount of chemotherapy drug to the organoid culture medium. S5. Monitoring organoid response to drugs: Continuously monitor changes in organoid cellular mechanical force and stiffness under drug action using light reflection signals and microcolumn displacement. Observe the decrease in organoid vitality under drug action (Figure 20), or add immune cells (NK cells or T cells) and co-culture to monitor changes in organoid vitality.

[0258] Example 36: Characterization of heterogeneous tumor spheroids and screening of drug-resistant or immune-evading individuals using a cell mechanics chip. This embodiment provides an immuno-organoid chip. By monitoring changes in cellular mechanical forces on heterogeneous tumor spheroids, individuals with drug resistance or immune evasion capabilities are screened.

[0259] S1. Tip preparation: Select a cell mechanics tip with a microcolumn structure, coat the top of the microcolumn with an appropriate extracellular matrix (ECM) to promote tumor spheroid adhesion and growth. Apply an anti-adhesion treatment to the sides and between the microcolumns. S2. Culture of heterogeneous tumor spheroids: Tumor spheroids of different origins or with different drug resistance characteristics can be cultured in the laboratory, and their size and shape can be restricted using restrictive structures (Figure 22). Tumor spheroids may also be isolated from patients. S3. Tumor spheroid dissemination: Cultured heterogeneous tumor spheroids are placed on a mechanical chip. Ensure that the tumor spheroids are in contact with the chip surface and adhere to the chip. S4. Monitoring of tumor spheroid adhesion: Light reflection signals are used to monitor the adhesion status of tumor spheroids on the mechanical chip in real time and observe changes in cellular mechanical force. S5. Addition of chemotherapeutic agents: Add an appropriate amount of chemotherapeutic agent to the culture medium of tumor spheroids. Alternatively, add immune cells and co-culture them. S6. Monitoring of tumor spheroid drug response: Continuously monitor changes in cellular mechanical force and stiffness of tumor spheroids under drug action using light reflection signals and microcolumn displacement. Observe the growth inhibition status of different tumor spheroids under drug action to screen for individuals with drug resistance (Figure 21). The killing effect of immune cells on tumor spheroids and the drug effects of immune cells can also be obtained to evaluate the targeting of drugs.

[0260] Abstract: This embodiment demonstrates a method for characterizing heterogeneous tumor spheroids and screening drug-resistant individuals using a cellular mechanics chip. Monitoring changes in cellular mechanics can provide important information for drug resistance research and personalized therapy.

[0261] Example 37: Characterization of immune-tumor cell interactions and evaluation of drug intervention effects using a cell mechanics chip. This embodiment provides an immune-tumor chip. It monitors the relationship between the mechanical properties of tumor cells and their interaction with immune cells, and the impact of drug intervention on this relationship.

[0262] S1. Tip preparation: Select a cell mechanics tip with a microcolumn structure, coat the top of the microcolumn with an appropriate extracellular matrix (ECM) to promote the adhesion and growth of tumor cells and immune cells. Apply an anti-adhesion treatment to the sides and between the microcolumns. S2. Seeding of tumor cells and immune cells: Tumor cells and immune cells (NK cells or T cells, etc.) are seeded on a mechanical chip and allowed to interact with each other. S3. Monitoring the mechanical properties of tumor cells: Real-time monitoring of the cellular mechanical force and stiffness changes of tumor cells during their interaction with immune cells is performed using light reflection signals and microcolumn displacement. Simultaneously, microcolumn displacement is induced by a magnetic field to measure cell stiffness. S4, Observation of the killing effect of immune cells on tumor cells: We found that there is a positive correlation between the mechanical size and hardness of tumor cells, and that softer tumor cells (lower cellular mechanical force) are more difficult to recognize and kill by immune cells. S5. Drug intervention: Add a drug that scleroses tumor cells to the culture medium and observe changes in the cellular mechanical force and stiffness of the tumor cells. S6. Evaluation of the effect of drug intervention: Under drug action, tumor cells hardened and their cellular mechanical strength increased. We observed that the killing effect of immune cells on tumor cells was consequently enhanced.

[0263] Abstract: This embodiment demonstrates a method for characterizing immune-tumor cell interactions using a cell mechanics chip and evaluating the impact of drug intervention on this relationship. In particular, the positive correlation between cell mechanical force and cell stiffness highlights the importance of characterizing these two attributes simultaneously. Studying the mechanical properties of tumor cells can provide insights for optimizing immunotherapy strategies.

[0264] The cell mechanics chip in the present invention may be a cell mechanical force detection device, a cell / multicellular aggregate interaction characterization and identification system disclosed in the present invention, or other cell mechanics chips combining a microcolumn and optical signal reflection.

[0265] Example 38: A method for evaluating interactions between proteins, peptides, and cells / cell aggregates mediated by cellular mechanical forces. This embodiment acquires cellular mechanical force information of cells / multicellular aggregates using a cellular mechanical force detection device or cell / cell aggregate characterization system described in any of the embodiments above, or a cellular mechanical force detection method described in any of the above-mentioned schemes. Based on the cellular mechanical force information, interactions between substances and cells and / or multicellular aggregates are identified: mechanical force information of cells after transfection is acquired and used to predict the transfection status of the transfected cells. High-throughput biological screening can be achieved by combining microfluidics as needed based on the transfection status. This embodiment discovered that there are clear differences in the success and failure of cell transfection, as well as in cellular mechanical force and stiffness characteristics, and for the first time discovered that there are clear differences in the mechanical force and stiffness characteristics of cells that express bioactive compounds (including proteins and peptides) and cells that do not. By combining these physical characteristics with an artificial intelligence trained identification model, it is possible to rapidly identify cells that have successfully transfected and high-productivity cells that express bioactive compounds non-invasively and without labeling, and high-throughput biological screening can be achieved by combining microfluidics.

[0266] Tests have confirmed that: when added to a culture system, untransfected cells may not be killed due to drug concentrations being too low or cell densities too high. Rapidly dividing cells are more susceptible to killing than slow-growing cells. Control cells (untransfected) may be killed within 5-7 days after antibiotic addition, while cloning of transfected cells (resistant clones) takes 10-14 days.

[0267] In some specific examples, the purpose of transfection is to alter the morphology or function of cells by affecting the cytoskeleton, cell adhesion, or cell differentiation, and successfully transfected cells may exhibit different mechanical force patterns and sizes from untransfected or untransfected cells.12 In some specific examples, the purpose of transfection is to alter the gene expression or protein levels of cells, and if there is no direct impact on morphology or function, there may be no clear difference between successfully transfected and unsuccessful cells. In some specific examples, if the transfection method utilizes viral vectors or other physical means and does not use chemical reagents such as liposomes, the transfection process itself may cause certain damage or stress responses to cells, affecting cellular mechanical forces. This invention is the first to discover a clear difference in cellular mechanical properties between successful and unsuccessful cell transfection. The system of this invention allows for real-time characterization, is fast, and enables real-time monitoring of cell status and potential cytotoxicity during experiments, enabling timely optimization of transfection protocols.

[0268] 39th Example: Method and Application for Characterizing, Typing, and Identifying Fat-Cell / Cell Aggregate Interactions Based on Cellular Mechanisms This embodiment acquires the physical information of cells / multicellular aggregates by a cell-mechanical force detection device or cell / cell aggregate characterization system described in any of the embodiments described above, or by a cell-mechanical force detection method described in any of the methods described above. Based on the physical information of the cells, interactions between lipids and cells or / or multicellular aggregates are identified: Adipocytes are the largest connective tissue cells in the human body, and their main function is the storage and recruitment of lipids. Adipocytes can be divided into two major classes: white adipocytes and brown adipocytes, which differ significantly in morphology, function, and origin. White adipocytes are monocellular and contain a large lipid droplet rich in triacylglycerol within each white adipocyte, which accounts for 90% of the cell volume, pushing other components and the nucleus to the periphery. White adipose tissue mainly stores energy and releases free fatty acids as needed for use by other tissues. White adipose tissue also secretes various hormones and factors such as leptin, angiotensin, and vascular endothelial growth factor, regulating physiological processes such as blood pressure, appetite, and glucose metabolism. Brown adipose cells are multifocal and contain numerous small lipid droplets rich in triacylglycerol within each cell, as well as highly aggregated mitochondria, which gives them their brown color. Brown adipose tissue mainly generates heat and consumes excess energy during cold or overeating. Brown adipose tissue also secretes some hormones and factors (e.g., hepcidin, neuronal cell-inducing factor, etc.) that have different or opposite effects to those of white adipose tissue, regulating physiological processes such as iron metabolism and neurogenesis. Different types of adipose cells each play normal and important roles in a healthy state, but in unhealthy conditions, such as overnutrition or malnutrition, abnormal changes or transformations can occur, which can affect human health. For example, overnutrition increases the number and size of white adipose tissue, leading to metabolic disorders, diabetes, and cardiovascular disease. On the other hand, brown adipose tissue becomes less active or is converted to white adipose tissue, resulting in a decrease in energy consumption.

[0269] The inventors discovered that there are clear dynamic changes in cellular mechanical forces during adipocyte differentiation, enabling real-time monitoring of the conversion process between white, beige, and brown fat. Furthermore, the invention provides a high-throughput testing platform for related drug testing. The cellular mechanical force detection device of the present invention can be used to monitor clear dynamic changes in cellular mechanical forces during adipocyte differentiation, thereby enabling real-time monitoring of the conversion process between white, beige, and brown fat. White and brown adipocytes have clear morphological and functional differences, which are reflected in their cellular mechanical forces. Generally, white adipocytes are stiffer than brown adipocytes but generate less mechanical force. Cellular mechanical forces are closely related to cell differentiation, and certain signaling pathways, such as the Rho / ROCK pathway, can regulate the differentiation process of adipocyte progenitor cells into white or brown fat. In some specific embodiments, the differentiation direction and rate of adipocyte progenitor cells can be influenced by methods such as changing the stiffness of the culture substrate or applying periodic stretching, allowing for the detection of characteristic markers after different types of adipogenesis. In some specific embodiments, polyphenolic substances such as epigallocatechin gallate can suppress white adipose differentiation or promote brown adipose differentiation by affecting the Rho / ROCK pathway or other signaling pathways, and these effects can be observed by mechanical force microscopy.

[0270] This embodiment can effectively study the differences in morphology, function, and metabolism between different types of adipocytes, and can screen for drug candidates that may be useful in the prevention and treatment of obesity and related diseases.

[0271] Fortieth Example: A method for evaluating the interaction between other substances and cells / cell aggregates due to cellular mechanical forces. This embodiment acquires physical information of cells in a cell / multicellular aggregate using a cell-mechanical force detection device or cell / cell aggregate characterization system described in any of the embodiments described above, or a cell-mechanical force detection method described in any of the schemes described above. Based on the physical information of the cells, the interaction between a substance and cells or / or multicellular aggregates is evaluated: In some specific embodiments, the system can monitor cellular mechanical forces in real time and with high throughput, effectively verifying transfection success or high-productivity cell lines by combining semi-solid media and antibodies or secondary antibodies in synthetic biology applications. The structure can be used for machine learning. In some specific embodiments, the system can monitor the effects of genetic engineering (e.g., transfection) on cells in synthetic biology applications, detecting small clonal clusters or single cells near large clones to ensure single-clonal isolation of the target clone. By analyzing the structural and morphological parameters of clones (e.g., sphere and shape), suspicious (e.g., stretched) clones can be defined and eliminated. In some specific embodiments, the system helps establish optimal dose-response curves (or kill curves) and determine the minimum effective concentration to kill resistant cells by monitoring cell vitality and state. Simultaneously, it monitors cells in real time during the drug screening process, allowing for timely adjustment of experimental schemes. In some specific embodiments, in addition to single cells, the system can monitor the state and dynamic changes of multicellular aggregates (including tumor spheroids, organoids, biological tissues, etc.) in real time, with high throughput and low cost. In some specific embodiments, artificial intelligence-trained identification models are combined based on different types of mechanical features and change disciplines to further determine or predict the type, state, behavior, and differentiation direction of single or multicellular aggregates. In some specific embodiments, the present invention is applicable to fields such as synthetic biology, diagnostics, drug discovery, early tumor screening, cell therapy, and precision medicine. In some specific embodiments, it is determined whether measured cells are single or aggregated to form multicellular aggregates during the culture process. The characterization and identification system and method of the present invention enable real-time characterization, is fast, allows real-time monitoring of cell state and potential cytotoxicity during the experimental process, and enables timely optimization of transfection schemes. In some specific embodiments, it can be used to establish highly productive and stable cell lines, which are crucial for the large-scale production of recombinant proteins and antibody drugs.By establishing multiple subtype cell banks for currently widely used CHO cells, it is possible to efficiently develop stable and high-productivity expression cell lines and improve the development speed. In some specific examples, microscopic images (before and after capture) and real-time images during capture can be used for quality control. The production of protein drugs using mammalian cells has made great progress, and with the rapid development of biotechnology and synthetic biology, many genetically engineered drugs and recombinant drugs have been synthesized, many new drugs have been discovered, enriching the types of protein drugs and improving disease cure rates. However, 70% of current protein drugs are produced using Chinese hamster ovary cells (CHO), and the growth cycle of protein drugs expressed within the cells is long, resulting in a slow screening process. This invention establishes a dose-response curve (or kill curve) and determines the minimum effective concentration that kills resistant cells.

[0272] In some specific examples, this can be applied to flow cytometry: the expression status of the target protein in the cells / cell aggregates can be labeled using fluorescently labeled antibodies or fluorescent probes, and the cells can be analyzed and typed using a flow cytometer. In some specific examples, drug development typically relies on high-throughput cell screening based on large compound libraries. However, due to the lack of chemical miniaturization and parallelization methods, as well as the difficulty in separating and synthesizing bioactive compounds from biological screening, this method is costly and inefficient.

[0273] The present invention provides an on-chip platform combining solution-based compound library synthesis and high-throughput biological screening (chemBIOS). In some specific embodiments, the inventors have for the first time discovered that there are clear differences in the mechanical properties of cells that express and do not express bioactive compounds (including proteins and peptides), enabling the screening and isolation of high-expression clones based on cellular mechanical properties. In some specific embodiments, in the process of studying cell-macromolecular interactions, the inventors have for the first time discovered that cellular mechanical characterization methods are more sensitive and can detect cellular changes more rapidly and sensitively than conventional gene or protein synthesis characterization methods. In some specific embodiments, the state and dynamic changes of multicellular aggregates (including tumor spheroids, organoids, and biological tissues) can be monitored in real time, in addition to single cells, with high throughput and low cost. In some specific embodiments, synthetic biology applications refer to modifying or creating biological systems with specific functions using genetic engineering or other means, for example, efficiently synthesizing a certain metabolite or pharmaceutical. In some specific examples, in synthetic biology applications, transfection, transformation, or other methods are typically used to introduce target genes into host cells, and it is necessary to screen for high-expression cell lines to improve production efficiency.

[0274] The principle of identifying and typing high-expression cell lines using cellular mechanical characterization is as follows: the expression of a target gene can affect the morphology or function of a cell, potentially altering its cytoskeleton, adhesion, or differentiation state. Therefore, high-expression cells may exhibit clear differences in mechanical pattern and size compared to low-expression or untransfected cells. When identifying and typing high-expression cells using mechanical force microscopy, the results can be validated by combining them with other methods such as fluorescence detection and enzyme-linked immunosorbent assays to further improve the accuracy of the physical information obtained from the cells and the accuracy of predictions.

[0275] Forty-first embodiment This embodiment acquires physical information of cells in a cell / multicellular aggregate by a cell-mechanical force detection device or cell / cell-multimer characterization system described in any of the embodiments described above, or by a cell-mechanical force detection method described in any of the schemes described above; and identifies interactions between macromolecules (e.g., proteins, sugar molecules, lipids) or microorganisms and cells or / or multicellular aggregates based on the physical information of the cells: In some specific examples, the effects of different extracellular matrix materials on cellular mechanical forces are compared, and the steps are as follows: S1. Different extracellular matrix components (e.g., collagen, fibronectin, laminin) are applied to the top of the microcolumn of the cell mechanical force detection device, or the extracellular matrix components are printed on the top of the microcolumn in a specific pattern by microcontact printing; the sides of the microcolumn and the spaces between the microcolumns are treated with anti-adhesion treatment using Pluronic F127. S2. Lung cancer cells A549 are cultured on cell mechanical force detection devices with different extracellular matrix coatings. S3. Monitor cell mechanics in real time and compare the strength and distribution of cellular mechanical forces in different extracellular matrix coatings.

[0276] In some specific embodiments, there is a method for detecting the effect of antibodies on cellular mechanisms, the steps being: S1. Cover the top of the microcolumn of the cell mechanical force detection device with CD3 antibody; apply anti-adhesion treatment to the sides and spaces between microcolumns using Pluronic F127. The S2.NFAT reporter (eGFP) Jurkat recombinant cell line was added, and the CD3 antibody aspirated T cells and brought them into contact with the tip. When this T cell line is activated by the CD3 antibody, it expresses green fluorescent protein. S3. Monitor cellular dynamics changes and green fluorescent protein expression in real time (see Figure 23).

[0277] In some specific embodiments, a method for detecting the effect of sugar molecules (glycoproteins or glycolipids) on cellular mechanical forces. S1. Cover the top of the microcolumn of the cell mechanical force detection device with lipopolysaccharide (LPS); apply anti-adhesion treatment to the sides and spaces between the microcolumns using Pluronic F127. The S2.THP1-ASC-GFP cell line was added, and LPS was applied to aspirate the cells and bring them into contact with the tip. This monocyte cell line expresses green fluorescent protein when activated by LPS. S3. Monitor cell dynamics changes and green fluorescent protein expression in real time.

[0278] In some specific embodiments, a method for detecting the effect of proteins on cellular mechanical forces. S1. Cover the top of the microcolumn of the cell mechanical force detection device with yeast zymosan; apply an anti-adhesion treatment to the sides and spaces between microcolumns using Pluronic F127. The S2.THP1-ASC-GFP cell line was added, and yeast sucrose was used to aspirate the cells and bring them into contact with the chip. When this monocyte cell line is activated by yeast sucrose, it expresses green fluorescent protein. S3. Monitor cell dynamics changes and green fluorescent protein expression in real time.

[0279] In some specific embodiments, a method for detecting the effect of microorganisms on cellular mechanisms. S1. Cover the top of the microcolumn of the cell mechanical force detection device with formaldehyde-treated bacteria; apply an anti-adhesion treatment to the sides and spaces between microcolumns using Pluronic F127. The S2.THP1-ASC-GFP cell line was added, and bacteria aspirated the cells and brought them into contact with the tip. This monocyte cell line expresses green fluorescent protein when activated by the bacteria. S3. Monitor cell dynamics changes and green fluorescent protein expression in real time.

[0280] Forty-second example: Method for measuring the interaction between immune cells and molecules and the cell activation process by characterizing cellular mechanical force and hardness. This embodiment provides a method for evaluating the interaction between immune cells (e.g., T cells) and molecules (e.g., CD3 antibodies) and the cell activation process by measuring changes in the mechanical force and stiffness of immune cells (e.g., T cells). The expression of green fluorescent protein is used as a marker of cell activation and is cross-validated with the measurement results of cell mechanical force and stiffness.

[0281] S1. Prepare a cell mechanical force detection device with CD3 antibody covering the top of the microcolumn; apply anti-adhesion treatment to the sides and spaces between microcolumns using Pluronic F127. S2. The NFAT reporter (eGFP) Jurkat recombinant cell line is added to the chip; the CD3 antibody aspirates T cells and brings them into contact with the chip. When this T cell line is activated by the CD3 antibody, it expresses green fluorescent protein. S3. Monitor cellular dynamics changes and green fluorescent protein expression in real time. By analyzing cellular dynamics changes at different time points, study the interactions between immune cells and molecules and the cell activation process. S4. Using a pressure transmission device, a microcolumn is inserted into the cells, a magnetic field is applied, and the light reflection signal is detected to characterize the cell stiffness. S5. Analyze experimental data and monitor changes in cellular mechanical force and stiffness during the interaction between immune cells and molecules, as well as during the activation process. Simultaneously, observe the expression of green fluorescent protein and cross-validate it with the mechanical measurement results to evaluate cellular activity under different activation conditions.

[0282] Forty-third example: A method for identifying activated and inactivated T cells by measuring cellular mechanical force and hardness, and for determining their activation ratio. This embodiment provides a method for identifying activated and inactivated T cells by measuring cellular mechanical force and stiffness, and for determining their activation ratio. This method can be used to characterize cell therapy samples and predict the success rate of cell therapy.

[0283] S1. T cell line NFAT reporter (eGFP) Jurkat cells are cultured on a cell mechanical force detection device; the amount of culture medium is controlled to ensure that the T cells are in contact with the device, and the mechanical force of inactivated cells is measured. S2.CD3 antibody, CD28 antibody, and cell factors are added to the culture medium to activate T cells; when T cells are activated by the antibodies, they express green fluorescent protein. S3. Monitor the changes in the mechanical force of each T cell and the expression of green fluorescent protein in real time. S4. Using a pressure transmission device, a microcolumn is inserted into the cells, a magnetic field is applied, and the light reflection signal is detected to characterize the cell stiffness. We discovered that when S5 T cells are activated, their cellular mechanical properties gradually increase, and this correlates positively with green fluorescence. S6. Input the changes in cellular mechanical force and stiffness during each T cell activation process into a database, and use machine learning methods to establish a model that determines the degree of T cell activation based on the characteristics, spatial distribution, and temporal dynamic changes of cellular mechanical force and stiffness. S7. T cells are isolated from donor peripheral blood mononuclear cells (PBMCs) using CD4 and CD8 antibodies. S8. Culture the isolated T cell pool on a cell mechanical force detection device; control the amount of culture medium so that all T cells are in contact with the cell mechanical force detection device. S9. Record the mechanical force distribution of all T cells and perform computational analysis using the previously established model to determine the ratio of activated to inactivated T cells in the donor body. This value can be used to predict the success rate of cell therapy.

[0284] Forty-fourth example: A technology applying microfluidics and a cell mechanical force detection device to in vitro culture monitoring of CAR-T cell therapy. This embodiment provides a technology for applying microfluidics and a cellular mechanical force detection device to the in vitro culture monitoring of CAR-T cell therapy, enabling more effective monitoring and evaluation of CAR-T cell growth, activation, and therapeutic effects in an in vitro environment.

[0285] S1. Cover the top of the microcolumn of the biostate and stress characterization instrument chip with CD3 and CD28 antibodies; apply anti-adhesion treatment to the sides and spaces between microcolumns using Pluronic F127. S2. Lay the chip at the bottom of the microfluidic device. S3. T cells isolated from donor peripheral blood mononuclear cells (PBMCs) are injected into a microfluidic device to activate them. Simultaneously, the cellular mechanical force is monitored to determine whether all T cells have been fully activated. S4. After the T cells are fully activated, a lentivirus is added to induce transduction, causing the T cells to express a chimeric antigen receptor with an antibody-specific sequence (sc-fv) that recognizes cancer cell surface proteins. S5. Transduced T cells (CAR-T) are extracted from the microfluidic fluid and cultured to further increase their size. S6. A PDMS microwell thin film is laid on a cell mechanical force detection device, and tumor cells, tumor multicellular spheres, or tumor organoids are cultured on the cell mechanical force detection device containing microwells, allowing the cells to grow in an orderly manner within the microwells. S7. CAR-T cells are added to a cellular mechanism detection device containing tumor cells, and the cellular mechanism of the tumor cells is monitored in real time. When CAR-T cells effectively kill tumor cells, the cellular mechanism of the tumor cells decreases significantly.

[0286] This embodiment allows for more effective monitoring and evaluation of the cytodynamic properties of CAR-T cells during activation, amplification, and tumor cell killing processes in an in vitro environment, providing accurate data support for CAR-T cell therapy.

[0287] Forty-fifth example: A technology applying microfluidics and a cell mechanical force detection device to in vitro culture monitoring of TCR-T cell therapy. This embodiment provides a technology that applies microfluidics and a cellular mechanical force detection device to the in vitro culture monitoring of TCR-T cell therapy, enabling more effective monitoring and evaluation of TCR-T cell growth, activation, and therapeutic effects in an in vitro environment.

[0288] S1. Cover the top of the microcolumn of the characterization apparatus with CD3 and CD28 antibodies; apply anti-adhesion treatment to the sides and spaces between the microcolumns using Pluronic F127. S2. The biological state and stress characterization device is laid at the bottom of the microfluidic device. S3. T cells isolated from donor peripheral blood mononuclear cells (PBMCs) are injected into a microfluidic device to activate them. Simultaneously, the cellular mechanical force is monitored to determine whether all T cells have been fully activated. After S4 T cells are fully activated, CRISPR-Cas9 technology is used to modify the T cell receptor (TCR) of the T cells and express a sequence that recognizes cancer cell antigens. S5. The modified TCR-T cells are extracted from the microfluidic fluid and cultured and amplified. S6. A PDMS microwell thin film is laid on a cell mechanical force detection device, and tumor cells, tumor multicellular spheres, or tumor organoids are cultured on the cell mechanical force detection device containing microwells, allowing the cells to grow in an orderly manner within the microwells. S7. TCR-T cells are added to a cellular mechanism detection device containing tumor cells, and the cellular mechanism of the tumor cells is monitored in real time. When TCR-T cells effectively kill tumor cells, the cellular mechanism of the tumor cells decreases significantly.

[0289] This embodiment allows for more effective monitoring and evaluation of the cytodynamic properties of TCR-T cells during activation, amplification, and tumor cell killing processes in an in vitro environment, providing accurate data support for TCR-T cell therapy.

[0290] Forty-sixth example: Monitoring changes in cellular mechanical forces using a characterization system to determine the therapeutic effect of antibody-drug conjugates on floating cancers. This embodiment provides a method for monitoring changes in cellular mechanical forces using a characterization system and determining the efficacy of antibody-drug conjugates in treating floating cancers.

[0291] S1. The top of the microcolumn of the characterization system is covered with an antibody-drug conjugate, and the sides and spaces between the microcolumns are treated with Pluronic F127 to prevent adhesion. S2. Hematopoietic cancer cells are cultured on this device, and the antibody coating is applied by aspirating the hematopoietic cancer cells into the device. S3. The cellular mechanical strength of hematopoietic cancer cells is monitored in real time by detecting the intensity of the light reflection signal. When the antibody-drug conjugate effectively suppresses cell growth or induces apoptosis in cells, the cellular mechanical strength decreases significantly.

[0292] By monitoring changes in cellular mechanisms using characterization systems, we can better understand the therapeutic effects of antibody-drug conjugates on parasitic cancers. Real-time monitoring of cellular mechanisms helps to better evaluate the therapeutic effects of antibody-drug conjugates, thereby optimizing drug design and treatment strategies.

[0293] Forty-seventh example: Using a characterization system to monitor changes in cell mechanical force and stiffness, and to determine the adhesion-based cancer therapeutic effect of antibody-drug conjugates. This embodiment provides a method for evaluating the therapeutic effect of antibody-drug conjugates on adhesive cancers by monitoring changes in cellular mechanical force and stiffness.

[0294] S1. The top of the microcolumn of the characterization system is covered with extracellular matrix, and the sides, intercolumns, and base of the microcolumn are treated with anti-adhesion treatment using Pluronic F127. S2. Lung cancer cells are cultured on the characterization system, and after 1 day of culture, the cells are allowed to fully adhere to the device. S3. Add the antibody-drug conjugate to the culture medium. S4. By detecting the intensity of light reflection signals, the cellular mechanical strength and stiffness of lung cancer cells are monitored in real time. When the antibody-drug conjugate effectively suppresses cell growth or induces apoptosis in cells, the cellular mechanical strength and stiffness decrease significantly.

[0295] Monitoring changes in cellular mechanical forces and stiffness using characterization systems can provide important evidence for evaluating the therapeutic effects of antibody-drug conjugates on adhesive cancers.

[0296] Forty-eighth example: Monitoring changes in cellular mechanical forces in biological tissues to determine the therapeutic effect of antibody-drug conjugates. This embodiment aims to provide a method for evaluating the therapeutic effect of antibody-drug conjugates on tumor cells by monitoring changes in cellular mechanical forces in biological tissues.

[0297] S1. The top of the microcolumn of the characterization system is covered with extracellular matrix, and the sides of the microcolumn and the spaces between microcolumns are treated with Pluronic F127 to prevent adhesion. S2. Use a tissue sectioning machine to cut fresh tumor tissue into 200-micrometer thick sections. S3. A thin section of biological tissue is placed on a cellular mechanical force detection device and cultured for one day, after which the tissue is completely attached to a chip. It is known that the cellular mechanical force in tumor cell compartments is stronger than that in non-tumor compartments. S4. Add the antibody-drug conjugate to the culture medium. S5. By detecting the intensity of the light reflection signal, the cellular mechanical force of the tumor cell compartment and the non-tumor cell compartment is monitored in real time. When the antibody-drug conjugate effectively suppresses cell growth or induces apoptosis in cells, the cellular mechanical force decreases significantly. S6. In addition, by comparing the changes in cellular mechanical forces between tumor cell compartments and non-tumor cell compartments, it is possible to understand whether the antibody-drug conjugate can specifically kill tumor cells. Furthermore, the effects on normal cells can be evaluated.

[0298] This embodiment provides important evidence for evaluating the therapeutic effect of antibody-drug conjugates on tumor cells by monitoring changes in cellular mechanical forces in biological tissues.

[0299] Forty-nineth example: Monitoring cellular dynamics changes in multicellular spheroids to determine the therapeutic effect of antibody-drug conjugates. This embodiment aims to provide a method for determining the therapeutic effect of an antibody-drug conjugate by monitoring changes in the cellular dynamics of multicellular spheroids.

[0300] S1. Prepare a characterization system, with the microcolumn apex containing extracellular matrix, and the microcolumn sides and inter-microcolumn spaces treated with Pluronic F127 to prevent adhesion. S2. Tumor cells are cultured as multicellular spheroids on this chip. After culturing for 1 day, the multicellular spheroids are allowed to completely adhere to the chip. Antibody-drug conjugates are added to the culture medium. S3. Cellular dynamics changes in multicellular spheroids are monitored in real time by detecting the intensity of light reflection signals. When antibody-drug conjugates effectively suppress cell growth or induce apoptosis in cells, the cellular dynamics of multicellular spheroids are significantly reduced.

[0301] Example 50: Simultaneous comparison of cellular mechanical changes in tumor cells and non-tumor cells to determine the targeting potential of antibody-drug conjugates. This embodiment aims to provide a method for determining the targeting of an antibody-drug conjugate by monitoring cellular mechanical forces.

[0302] S1. The top of the microcolumn of the cell mechanical force detection device has an extracellular matrix, and the sides of the microcolumn and the spaces between microcolumns are treated with Pluronic F127 to prevent adhesion. S2. After mixing tumor cells with red fluorescence and non-tumor cells with green fluorescence in equal proportions, the cells are cultured on this cell mechanical force detection device for one day, and then the cells are allowed to completely adhere to the chip. The antibody-drug conjugate is added to the culture medium. S3. The cellular mechanical properties of two types of cells are simultaneously monitored by detecting the intensity of the light reflection signal. When the antibody-drug conjugate specifically suppresses tumor cell growth, the decrease in cellular mechanical properties of tumor cells is greater than that of non-tumor cells, or the cellular mechanical properties of non-tumor cells are not affected by the antibody-drug conjugate.

[0303] Example 51: Extracorporeal organ chip This embodiment provides an in vitro organ chip which includes a cellular mechanical force detection device or detection system as described in any of the embodiments described above, and further includes an electrode device. The microcolumn is made of a conductive material, and the electrode device acts on the microcolumn to realize electrical stimulation to the organ or cells. Organ-related cells and tissues can be cultured on the microcolumn, and the cellular mechanical forces of the cells and tissues deform the microcolumn, which is converted into an optical signal. The microcolumn is set to a corresponding softness and length according to the organ, so that the microenvironment of the chip matches the actual structural environment of the organ. The softness and hardness can be controlled by adjusting the length and crosslinking ratio of the microcolumn to mimic the softness and hardness of the corresponding tissue or the microenvironment under pathological conditions (e.g., cardiac fibrosis).

[0304] In some specific embodiments, an extracellular matrix (ECM) is provided on the surface of the micropillar to mimic a more realistic microenvironment; in some specific embodiments, a mixture of organ-associated cells and / or tissues and the extracellular matrix (ECM) is seeded onto the micropillar to mimic a more realistic microenvironment; in some specific embodiments, a directional ECM layer is provided on the surface of the micropillar to mimic a more realistic microenvironment, for example, to mimic the microstructure of cardiac ECM and induce the orientation of cardiomyocytes; in some specific embodiments, the seeding method includes 3D printing; in some specific embodiments, if the organ is the heart, the cells include one or more combinations of cardiomyocytes, smooth muscle cells, vascular endothelial cells, fibroblasts, stem cells, and immune cells. The apex of the micropillar can be coated with cardiac-associated cell-derived ECM, artificially recombinant cardiac ECM, or cells can be embedded in a gel containing cardiac ECM to mimic the extracellular matrix components of the heart.

[0305] In some specific embodiments, to mimic a mechanical microenvironment: Includes mechanical imitation devices: mechanical tensioning devices for pulling the chip body; or a flexible, air-deformable thin film at the bottom of a microcolumn (the upper end connected to the microcolumn, the lower end connected to the base, or the base itself being a flexible thin film).

[0306] Some specific embodiments include microfluidic devices that impart flow field stimuli to organ-associated cells / tissues. Stimuli such as drugs, mechanical forces, biochemical factors, electric fields, flow fields, etc. (or combinations thereof) are applied to identify the state of each cell and organ under external stimuli.

[0307] 52nd Example: A method for constructing organ and cell models in vitro using an in vitro organ chip and characterizing cells and organ tissues, S1. Collect microenvironmental parameters of corresponding organ tissues under physiological and pathological conditions, and create corresponding in vitro organ chips based on these parameters; S2. Cultures containing organ-related cells and / or tissues are cultured on an in vitro organ chip; S3. Add stimuli (or combinations thereof) such as drugs, mechanical forces, biochemical factors, electric fields, or flow fields as needed, and allow them to act on the culture. S4. By acquiring changes in the cellular mechanical forces of each cell and tissue using an in vitro organ chip, we can characterize each cell and organ tissue.

[0308] In this embodiment, specific cells or tissues can be isolated by characterization. Application areas include screening for organ-specific therapeutic agents and studying organ models in physiological and pathological conditions.

[0309] 53rd Example: Method for detecting cardiomyocyte contraction-relaxation using an extracorporeal organ chip This embodiment acquires physical information of cells using a cell mechanical force detection device / system, detection method, or in vitro organ chip described in any of the embodiments described above: S1. Mouse hearts are perfused with a high-concentration EDTA solution, then shredded and broken down into single cells with collagenase; S2. After the cell suspension has stood for 20 minutes, cardiomyocytes will settle at the bottom of the tube; S3. The acquired cardiomyocytes are directly cultured on an in vitro organ chip; S4. After several days of culture, cardiomyocytes contract regularly; S5. High-speed imaging captures 100 images per second, and the mechanical changes during each contraction-relaxation cycle are observed. After continuously recording multiple contraction-relaxation cycles, the contraction frequency of cardiomyocytes is calculated (see Figure 24).

[0310] Example 54: Method for detecting the effect of drugs on myocardial cell contraction-relaxation frequency using an extracorporeal organ chip This embodiment acquires physical information of cells using a cell mechanical force detection device / system, detection method, or in vitro organ chip described in any of the embodiments described above: S1. Mouse hearts are perfused with a high-concentration EDTA solution, then shredded and broken down into single cells with collagenase; S2. After the cell suspension has stood for 20 minutes, cardiomyocytes will settle at the bottom of the tube; S3. The acquired cardiomyocytes are directly cultured on an in vitro organ chip; S4. After several days of culture, cardiomyocytes contract regularly; S5. High-speed imaging captures 100 images per second, observing the mechanical changes during each contraction-relaxation cycle. After continuously recording multiple contraction-relaxation cycles, the contraction frequency of cardiomyocytes is calculated. S6. Add the calcium channel blocker nifedipine and continuously record the mechanical changes of cardiomyocytes to observe a decrease in contraction frequency.

[0311] Example 55: Method for printing an extracellular matrix pattern onto an in vitro organ chip and measuring cardiomyocyte arrangement and contraction-relaxation frequency. This embodiment acquires physical information of cells using a cell mechanical force detection device / system, detection method, or in vitro organ chip described in any of the embodiments described above: S1. Microcontact printing is used to print extracellular matrix onto a mechanical chip in a specific pattern; S2. Rat cardiomyocytes are cultured on the mechanical chip, and the cells attach to a region of the extracellular matrix and grow, arranging regularly in a specific pattern; S3. After several days of culture, cardiomyocytes contract regularly; S4. High-speed imaging captures 100 images per second, observing the mechanical changes during each contraction-relaxation cycle. After continuously recording multiple contraction-relaxation cycles, the contraction frequency of cardiomyocytes is calculated.

[0312] Example 56: Method for measuring changes in cellular mechanical forces during the differentiation process from fibroblasts to adipocytes using an extracorporeal organ chip. This embodiment acquires physical information of cells using a cell mechanical force detection device / system, detection method, or in vitro organ chip described in any of the embodiments described above: S1. Culture mouse fibroblast cell line NIH3T3-L1 on a mechanical chip and begin recording cellular mechanical forces; S2. Replace the culture medium with a culture medium containing methylisobutylxanthine, dexamethasone, and insulin; S3. On day 3, replace the culture medium with an insulin-containing culture medium; S4. On day 6, replace the culture medium with normal DMEM culture medium; S5. Around day 10, NIH3T3-L1 cells differentiate into adipocytes. Differentiated adipocytes are identified by monitoring lipid accumulation with Oil Red O staining, and dead cells are excluded with Calcein AM staining. S6. Record the changes in cellular mechanical forces throughout the differentiation process (see Figure 25).

[0313] Example 57: A method for comparing the cellular mechanical forces of brown adipose tissue and white adipose tissue. This embodiment acquires physical information of cells using a cell-mechanical force detection device or detection system described in any of the embodiments above, or a cell-mechanical force detection method described in any of the plans above, or an in vitro organ chip: S1. Brown adipose tissue and white adipose tissue are extracted from newborn mice, finely chopped, digested into single cells using collagenase, filtered, and centrifuged to obtain preadipocytes; S2. Preadipocytes obtained from brown adipose tissue and white adipose tissue are cultured and expanded in culture dishes, respectively. S3. After several days of culture, transfer the two types of pre-adipocytes to a mechanical chip and culture them, simultaneously starting the recording of cellular mechanical forces; S4. Preadipocytes isolated from white adipose tissue are differentiated into white adipocytes by adding a culture medium containing methylisobutylxanthine, dexamethasone, and insulin. Preadipocytes isolated from brown adipose tissue are differentiated into brown adipocytes by adding a culture medium containing methylisobutylxanthine, dexamethasone, insulin, and triiodothyronine. S5. After 2 days of culture, replace the culture medium with an insulin-containing culture medium, and add triiodothyronine if you want to differentiate into brown adipose tissue; S6. Monitor lipid accumulation using Oil Red O staining to identify cells differentiated into adipocytes, and exclude dead cells using Calcein AM staining; S7. Record the changes in cellular mechanical forces throughout the differentiation process and compare the cellular mechanical forces of brown adipocytes and white adipocytes.

[0314] Example 58: Stem cell-induced cardiac organ model and method for characterizing the same This embodiment provides a cardiac model in which a directional extracellular matrix (ECM) is printed by microcontact printing on a cell mechanical force detection device, and stem cells are cultured to induce myocardial differentiation. Changes in cell mechanical force and stiffness are monitored during the induction process using light reflection signals and magnetic field-induced microcolumn displacement.

[0315] S1. A tropic extracellular matrix (ECM) is fabricated on the top of the microcolumn of a mechanical chip using microcontact printing technology; S2. Apply an anti-adhesion treatment (e.g., Pluronic F127) to the sides and between the microcolumns; S3. Seed stem cells onto a mechanical chip with tropic ECM and allow the cells to fully adhere; S4. Induce differentiation of stem cells into cardiomyocytes by adding appropriate inductive factors; S5. During the induction process, light reflection signals are used to monitor the interaction between cells and microcolumns, and real-time changes in cellular mechanical forces are detected. S6. Utilize magnetic field-induced microcolumn displacement to measure the force exerted by cells on the microcolumn and further evaluate changes in cell stiffness; S7. Analyze light reflection signals and magnetic field-induced microcolumn displacement data to evaluate changes in cellular mechanical force and stiffness during cardiomyocyte differentiation; S8. Fluorescent staining is performed on cells, extracellular matrix, and corresponding control groups to determine the tropic characteristics of cells and the extracellular matrix (ECM) (Figure 26).

[0316] This stem cell-inducing cardiac chip provides a strong basis for research into cardiomyocyte differentiation.

[0317] 59th Example: Stem cell-induced tissue-specific cartilage model and method for characterizing the same This embodiment provides a cartilage model in which cartilage-specific ECM extracted from cartilage tissue is coated onto a chip, and adult stem cells (MSCs) are cultured on it and induced to differentiate into cartilage. During the induction process, changes in cellular mechanical force and stiffness are monitored using light reflection signals and magnetic field-induced microcolumn displacement, and compared with the results of fluorescence staining and histochemical staining.

[0318] S1. Apply cartilage-specific extracellular matrix (ECM) extracted from cartilage tissue to the top of the microcolumn of the mechanical tip; S2. Apply an anti-adhesion treatment (e.g., Pluronic F127) to the sides and between the microcolumns; S3. Seed adult stem cells (MSCs) onto a mechanical chip coated with cartilage-specific ECM and allow the cells to fully adhere; S4. Induce differentiation of adult stem cells into chondrocytes by adding appropriate inducing factors; S5. During the induction process, light reflection signals are used to monitor the interaction between cells and microcolumns, and real-time changes in cellular mechanical forces are detected. S6. Utilize magnetic field-induced microcolumn displacement to measure the force exerted by cells on the microcolumn and further evaluate changes in cell stiffness; S7. Fluorescent and histochemical staining are performed during the differentiation induction process to evaluate the expression of chondrogenic differentiation-related markers. S8. By analyzing light reflection signals and magnetic field-induced microcolumn displacement data and comparing them with fluorescence staining and histochemical staining results, we evaluate changes in cellular mechanical force and stiffness during the cartilage differentiation process, providing strong evidence for chondrocyte differentiation research (Figure 27).

[0319] Sixtieth Example: Lung Tumor Model and Method for Characterizing the Same This embodiment provides a lung tumor model and characterization method for culturing normal and tumor lung extract cells on a double-sided sandwich structure chip. The chip base is made of a flexible material that deforms through filling and releasing air to mimic the respiratory motion of the lung, and changes in cellular mechanical force and stiffness are monitored using light reflection signals and magnetic field-induced microcolumn displacement during the chemotherapy drug stimulation process, and the targeting of the drug is evaluated by measuring the tumor-killing effect and the impact on normal cells.

[0320] S1. A double-sided sandwich structure mechanical chip is fabricated, the chip base is made of a flexible material, the extracellular matrix (ECM) is coated on the top of the microcolumn, and an anti-adhesion treatment (e.g., Pluronic F127) is applied to the sides of the microcolumn, between microcolumns, and the base; S2. Culture normal lung cells on one side of the chip and lung tumor cells on the other side, ensuring complete adhesion of the cells. Mixed culture in different areas of the same side is also possible; S3. Place the double-sided chip in the filling / deflating device to mimic the breathing motion of the lungs (Figure 28); S4. Add chemotherapeutic agents to stimulate normal lung cells and lung tumor cells; S5. During the stimulation process, light reflection signals are used to monitor the interaction between cells and microcolumns, and real-time changes in cellular mechanical forces are detected; S6. Utilize magnetic field-induced microcolumn displacement to measure the force exerted by cells on the microcolumn and further evaluate changes in cell stiffness; S7. Analyze light reflection signals and magnetic field-induced microcolumn displacement data to compare the effects of chemotherapy drugs on normal lung cells and lung tumor cells, and measure the tumor-killing effect and the effect on normal cells; S8. Evaluate the targeting potential of chemotherapy drugs based on experimental results, and provide evidence for drug screening and research.

[0321] 61st Example: Method for determining tumor and non-tumor areas in tissue This embodiment obtains physical information of cells from different tissues using a cell mechanical force detection device or characterization system described in any of the embodiments described above, or a cell mechanical force detection method described in any of the schemes described above, and includes the following steps: S1. Pancreatic cancer cell lines are injected into the pancreas of mice, and after several weeks, tumors are formed in the cancer cells. Then, the tumor-containing tissue (e.g., pancreas and liver) is removed from the mice, and the tissue is cut into pieces approximately 0.5 cm in length and width; the tissue is fixed to a tissue embedding plate using adhesive, and then cut into tissue sections approximately 150-200 μm thick using a tissue sectioning machine; S2. Place the tissue strip on the microcolumn of the cell detection device, add cell culture medium until it just covers the top of the tissue strip, let it stand for 30 minutes, then add more cell culture medium to completely immerse the tissue, and after 1 hour, begin monitoring the cellular mechanical strength of the tissue and any changes thereto. S3. By detecting cellular mechanical forces, we discover that tissues are divided into regions with strong and weak cellular mechanical forces.

[0322] In the control validation method, the pancreatic cancer cell line in step S1 expressed the EGFP fluorescent protein; simultaneously, in step S3, the strength of the EGFP signal and cellular mechanics in the tissue were compared, and it was found that the region containing cancer cells in the tissue (EGFP-expressing region) had strong cellular mechanics.

[0323] Through this verification, we were able to identify regions with strong cellular mechanical forces as regions containing cancer cells, enabling the identification of different regions within the tissue (as shown in Figure 31).

[0324] Example 62: Method for monitoring the tissue response of a drug using cellular mechanical forces. This embodiment obtains physical information of cells from different tissues using a cell mechanical force detection device or characterization system described in any of the embodiments described above, or a cell mechanical force detection method described in any of the schemes described above, and includes the following steps: Inject a pancreatic cancer cell line expressing S1.EGFP fluorescent protein into the pancreas of a mouse; S2. After allowing several weeks to pass to allow cancer cells to form tumors, remove tumor-containing tissues (e.g., pancreas and liver) from the mice; S3. Cut the tissue into pieces approximately 0.5 cm in length and width. S4. Secure the tissue to a tissue embedding plate using adhesive, and cut it into thin sections approximately 150-200 micrometers thick using a tissue sectioning machine; S5. Place the tissue strips on a mechanical chip and add cell culture medium until it just covers the top of the tissue strips; S6. After standing for 30 minutes, add more cell culture medium to completely immerse the tissue, and begin recording and monitoring the mechanical changes of the tissue after 1 hour; S7. After approximately 6 hours, the tissue will be completely attached to the chip, and drug testing can be performed by adding drugs (e.g., gemcitabine and 5-FU, which are commonly used treatments for pancreatic cancer); S8. Continuously monitor changes in cellular mechanisms throughout the tissue. When cells enter apoptosis or death, cellular mechanisms decrease significantly or disappear. Therefore, by observing whether or not cellular mechanisms decrease in the tumor area and the extent of this decrease, the effectiveness of a drug in treating tumors can be predicted.

[0325] 63rd Example: Spatial Omics Monitoring of Mechanical Properties of Tissue Sections for Differentiation of Tumors and Normal Tissue and Evaluation of Drug Treatment Effects This embodiment provides a tissue biophysical characterization system that distinguishes between tumor and normal tissue regions and evaluates the effects of drug treatment by monitoring the mechanical properties and spatial omics of biological tissue sections.

[0326] S1. Preparation of tissue sections: Obtain a tissue sample (including tumor and normal tissue) and prepare thin sections; S2. Measurement of mechanical properties of tissue sections: Mechanical force is monitored by the light reflection signal of a mechanical tip, and hardness is measured by activating the displacement of a microcolumn inserted into the tissue using a magnetic field, and verified with an atomic force microscope (AFM) or similar technique; S3. Distinguishing between tumor and normal tissue: Tumor and normal tissue regions were distinguished by analyzing the mechanical properties and spatial omics data of tissue sections (Figure 29). Tumor regions were found to have high mechanical force and high hardness; S4. Drug treatment: Antitumor drugs are added to biological tissue sections and treated for a set period of time. An immune cell suspension can also be added to measure tumor-immune interactions. S5. Evaluation of drug treatment effect: After drug treatment, changes in mechanical force and hardness at the tumor site were measured. A clear decrease in mechanical force in the tumor area was observed (Figure 30), while hardness did not decrease significantly, indicating that the response speed of mechanical force was faster than that of hardness.

[0327] Finally, it should be noted that the above embodiments are merely for illustrating the technical solutions of the present invention and do not limit them. Although the present invention has been described in detail with reference to the above embodiments, it will be understood by those skilled in the art that it is still possible to modify the technical solutions described in the above embodiments or to make equivalent substitutions to some or all of their technical features. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention. [Explanation of symbols]

[0328] 1. Cellular mechanical force detection device; 2. Optical signal generator; 3. Optical signal detection device; 4. Optical signal analyzer; 5-spectroscope; 11-Base; 12-Micropillar; 13-Light-reflecting layer; 15-Recessed space; 16-Restricting surface; 101-Objective lens; 102-Incident and reflected light rays; 103-Deformed micropillar; 104-Cell; 105-Anti-reflective layer; 106-Substance having cell adhesion properties; 107-Substance having cell adhesion inhibitory properties.

Claims

1. A method for characterizing cells, characterized in that the cell or / and the multicellular aggregate are characterized by obtaining physical information of the cells or the multicellular aggregate.

2. The physical information of the aforementioned cells is, (1) Interactions between cells and multicellular aggregates, (2) Intercellular interactions, (3) Interactions between multicellular aggregates, (4) Cells or / or multicellular aggregates at different stages of development, (5) Different regions within a multicellular aggregate, (6) The effects that substances have on cells or / or on multicellular aggregates (7) The mechanical force or / or stiffness of a cell obtained in the case of at least one of the effects of other physical, biological or chemical factors on a cell or / or multicellular aggregate, The method for characterizing cells according to claim 1, characterized in that the multicellular aggregate is a group of cells formed by the aggregation of two or more cells.

3. The mechanical force of the cell includes one or more combinations of magnitude, direction, frequency, and distribution. Optionally, the hardness includes the hardness of cells or / and multicellular aggregates or / and their distribution. The cell characterization method according to claim 2, characterized in that, optionally, the mechanical force and / or hardness of the cell includes the mechanical force and / or hardness of the cell at a certain point.

4. The method for characterizing cells according to claim 2, characterized in that the physical information of the cells includes changes in the mechanical force and / or hardness of the cells over a certain time interval.

5. The cell characterization method according to claim 2, characterized in that the physical information of the cell further includes morphological information of the cell.

6. The cell characterization method according to claim 2, characterized in that the physical information of the cells is obtained while cell-specific operations are performed on the cells and / or multicellular aggregates.

7. Interactions between cells and multicellular aggregates include interactions between cells and the extracellular matrix, direct cell interactions mediated by intercellular binding substances, and cell interactions mediated by intercellular signaling molecules. Intercellular interactions include intercellular signaling and intercellular mutual recognition. Interactions between multicellular aggregates include interactions between different tissues and interactions between different organs. Cells or / or multicellular aggregates at different developmental stages include interactions between embryonic cells at different developmental stages, tissue regeneration, and repair. Different regions within a multicellular aggregate include the formation and maintenance of cell polarity in multicellular tissue, which includes the regulation of the distribution of polarity proteins within cells and the sites of intercellular interactions. The effects of a substance on cells or / or multicellular aggregates include drug-cell interactions and toxin-cell interactions. The cell characterization method according to claim 2, characterized in that the effects of other physical, biological, or chemical factors on cells and / or multicellular aggregates include the effects of temperature and pressure on cells and the effects of light on plant cells.

8. Based on the physical information of cells obtained through interactions between cells and multicellular aggregates, intercellular interactions, or interactions between multicellular aggregates, the following: A step of placing a first cell or / and multicellular aggregate, a second cell or / and multicellular aggregate in a specific region, and detecting and obtaining the physical information of the cells. or The process includes the steps of arranging a first cell or / and multicellular aggregate in a specific region, then causing a second cell or / and multicellular aggregate to interact with the first cell or / and multicellular aggregate, and detecting and obtaining physical information of the cells. The method for characterizing cells according to claim 2, characterized in that the first cell or / and multicellular aggregate, and the second cell or / and multicellular aggregate, are each one or more cells or / and multicellular aggregates.

9. The method for characterizing cells according to claim 2, characterized in that the substance comprises one or more combinations of bioactive polymers, chemical substances, bioactive materials, and inactivated biomaterials, and the bioactive polymer comprises one or more combinations of proteins, peptides, polysaccharides, and lipids.

10. It is based on the physical information of cells during the implantation and growth process of an in vitro organ or / and associated cell model, and the physical information of cells includes the physical information of cells or / and cells in any region during the implantation and culture process of an organ-associated cell or / and tissue culture. Optionally, the physical information of the cells is used to characterize cells or cell groups, organ tissues, in any region of the growth process of an extracorporeal organ or / and related cell model. Optionally, a mixture of cells and / or tissues with ECM is implanted. Optionally, the implantation method includes controlling the distribution and flow of cells and biological materials by 3D printing and / or microfluidics to achieve implantation. Optionally, cultures of organ-associated cells and / or tissues are implanted onto a characterization device. The cell characterization method according to claim 2, characterized in that an ECM-directed coating is optionally installed on the detection device.

11. The cell characterization method according to claim 10, characterized in that the detection device is customized based on microenvironmental parameters in the physiological and pathological state of the corresponding tissue.

12. it is, The steps include: placing cells or / or multicellular aggregates in a specific region, and then applying a combination of at least one type of stimuli from among physical, biological, and chemical stimuli to the cells or / or multicellular aggregates; The steps include detecting and obtaining physical information about cells or / or cells in a multicellular aggregate, A method for characterizing cells according to any one of claims 1 to 11, characterized in that, optionally, the physical stimulus, biological stimulus, or chemical stimulus includes one or a combination of two or more stimuli from among drugs, mechanical force, hardness, biochemical factors, electric fields, flow fields, directional induction, and radiation.

13. The method for characterizing cells according to any one of claims 1 to 11, characterized in that the physical information of the cells is obtained before, during, and / or after the action, or at different growth stages of the cells and / or multicellular aggregates.

14. The method for characterizing cells according to any one of claims 1 to 11, characterized in that the physical information of the cells is obtained by real-time monitoring.

15. The physical information of the aforementioned cells is obtained by a characterization system. The characterization system includes a characterization device, and the characterization device is Base and, A micropillar array comprising one or more micropillars mounted on a base and deformable by the action of mechanical and / or magnetic forces of cells, wherein a light-reflecting layer is provided on the micropillars, A method for characterizing cells according to any one of claims 1 to 11, characterized in that, optionally, a light-reflecting layer is provided at one end of the micropillar away from the base, a light-transmitting portion is provided on the base, a light-transmitting portion is provided on the column of the micropillar, and optionally, an anti-reflective layer is provided on the surface of the micropillar and / or the base.

16. The characterization system further includes an optical signal emitter and an optical signal detector, wherein a light ray emitted from the optical signal emitter is irradiated onto the optical reflection layer through an incident optical path, and the light ray reflected by the optical reflection layer is incident on the optical signal detector through a reflected optical path. Optionally, the optical intensity obtained by the optical signal detection device is analyzed to obtain physical information about the cell. The cell characterization method according to claim 15, characterized in that, optionally, there is a linear correlation between the optical intensity obtained by the optical signal detection device and the magnitude of the mechanical force of the cell, and different cell typing can be achieved by performing qualitative and quantitative analysis.

17. The characterization device is capable of containing liquid, If the liquid is a cell culture medium, the cells and / or multicellular aggregates are attached to it and / or cultured. The cell characterization method according to claim 15, characterized in that, optionally, the cells and / or multicellular aggregates are adhered to the micropillar by an adhesive substance placed on the micropillar.

18. The physical information of the cells according to any one of claims 1 to 11 is used to type and identify the cells and / or multicellular aggregates. Optionally, the typing and identification include the type, state, behavior, spatial omics characteristics and differentiation direction of cells or / or multicellular aggregates, stress response, A cell typing and identification method characterized in that, optionally, the typing and identification includes selectively separating specific cells or tissues based on the physical information of the cells.

19. Identification is performed using a cell identification device, which includes an information acquisition unit, a preprocessing unit, a learning unit, and an identification unit. The aforementioned information acquisition unit is used to acquire physical information of cells or / or cells in a multicellular aggregate. The aforementioned preprocessing unit is used to preprocess the physical information of cells and form the physical information of structured cells, and the physical information of structured cells includes the number of cells, the number of cell features, and characteristic information of each cell feature. The aforementioned learning unit is used to construct a cell feature model using supervised, unsupervised, or semi-supervised machine learning, with the physical information of structured cells as input data. The cell typing and identification method according to claim 18, characterized in that the identification unit is used to apply the cell feature model to typing or clustering cells or / and multicellular aggregates, and to achieve typing and identification of cells or / and multicellular aggregates.

20. The typing and identification described above include at least one of the following combinations: Typing and identification of tumor and non-tumor areas in tissue. Typing and identification of cells or / or multicellular aggregates with different degrees of transfection and untransfected cells or / or multicellular aggregates. Typing and identification of cells or / or multicellular aggregates with different production levels of bioactive substances. Monitoring the effects of genetic engineering on cells, including identification of small clonal groups or single cells within large clonal groups. Determining the minimum effective concentration of drug to kill resistant cells, Real-time monitoring and timely adjustment of cells during the drug screening process. Monitoring of adipocyte growth and differentiation, The cell typing and identification method according to claim 19, characterized in that it is used to monitor, optionally, the conversion process of white fat, beige fat, and brown fat in real time.

21. An application of the method according to any one of claims 1 to 11, wherein the application is Applications in the construction of in vitro organs and cell models, Screening of organ-specific therapeutic agents, applications in research on the physiological and pathological states of organ models, Methods for evaluating the efficacy of drugs against tumors and their application in related evaluation products. Applications including at least one of the following: cell therapy, synthetic biology, adipose research, research on the interaction between cells / multicellular aggregates and macromolecules, multicellular aggregate research methods and related products.

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