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WO2024199141A1 - 一种细胞的表征、分型和识别方法和应用 - Google Patents

一种细胞的表征、分型和识别方法和应用 Download PDF

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Publication number
WO2024199141A1
WO2024199141A1 PCT/CN2024/083362 CN2024083362W WO2024199141A1 WO 2024199141 A1 WO2024199141 A1 WO 2024199141A1 CN 2024083362 W CN2024083362 W CN 2024083362W WO 2024199141 A1 WO2024199141 A1 WO 2024199141A1
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Prior art keywords
cell
cells
mechanical force
multicellular
multicellular aggregates
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PCT/CN2024/083362
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English (en)
French (fr)
Inventor
林哲
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医工瑞新(厦门)科技有限公司
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Publication date
Priority claimed from CN202310297791.8A external-priority patent/CN118685266A/zh
Priority claimed from CN202310299308.XA external-priority patent/CN118687808A/zh
Priority claimed from CN202310299309.4A external-priority patent/CN118706717A/zh
Priority claimed from CN202310299290.3A external-priority patent/CN118685253A/zh
Priority claimed from CN202310299292.2A external-priority patent/CN118685254A/zh
Priority claimed from CN202310299296.0A external-priority patent/CN118685255A/zh
Priority claimed from CN202310299306.0A external-priority patent/CN118685270A/zh
Application filed by 医工瑞新(厦门)科技有限公司 filed Critical 医工瑞新(厦门)科技有限公司
Publication of WO2024199141A1 publication Critical patent/WO2024199141A1/zh

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12M—APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
    • C12M1/00—Apparatus for enzymology or microbiology
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12M—APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
    • C12M1/00—Apparatus for enzymology or microbiology
    • C12M1/34—Measuring or testing with condition measuring or sensing means, e.g. colony counters
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12M—APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
    • C12M1/00—Apparatus for enzymology or microbiology
    • C12M1/42—Apparatus for the treatment of microorganisms or enzymes with electrical or wave energy, e.g. magnetism, sonic waves
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/02—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving viable microorganisms
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N11/00—Investigating flow properties of materials, e.g. viscosity, plasticity; Analysing materials by determining flow properties
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/55—Specular reflectivity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/543—Immunoassay; Biospecific binding assay; Materials therefor with an insoluble carrier for immobilising immunochemicals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/69—Microscopic objects, e.g. biological cells or cellular parts

Definitions

  • the present invention relates to the field of biotechnology, and in particular to a method and application for characterizing, typing and identifying cells.
  • Cells are the basic units of life. Their adhesion, migration, differentiation, apoptosis, dynamic changes in different physiological and pathological processes, and interactions with macromolecules are of great significance for understanding and regulating life phenomena. Therefore, characterizing the types, states, and behaviors of cells and cell polymers is an important topic in the fields of bioengineering, cell biology, and physical biology.
  • the present invention provides a method for characterizing cells, which can characterize cells and multicellular aggregates by detecting and obtaining the static or dynamic cell mechanical force and/or hardness of cells/multicellular aggregates at different times or before, during, or after the action of other factors;
  • the present invention also provides a method for cell typing and identification, which can achieve typing and identification of cells and/or multicellular aggregates in any situation through cell mechanical force and/or hardness.
  • the present invention also provides an application of the above method.
  • the main technical solutions adopted by the present invention include:
  • the present invention provides a method for characterizing cells, which characterizes cells and/or multicellular aggregates by acquiring cell physical information of the cells and/or multicellular aggregates.
  • the cell physical information includes cell mechanical force and/or hardness obtained under at least one of the following conditions;
  • the multicellular aggregate is formed by two or more cells agglomerating together to form a cell colony.
  • the present invention also provides a method for cell or/and multicellular aggregate typing and identification, which is carried out by the above Characterization methods are used to type and identify the cells and/or multicellular aggregates;
  • cell or/and multicellular aggregate typing refers to the fact that due to different factors, cells or/and multicellular aggregates may have different characteristics including but not limited to type, state, behavior, spatial omics characteristics, etc., and typing can be performed based on the above differences.
  • the present invention further provides an application of the method described in any one of the schemes, wherein the application comprises at least one of the following:
  • the cell physical information obtained by the present invention can be used to characterize the state before, during and after the interaction between cells and/or multicellular aggregates, and the interaction with external factors, or including continuous states, 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 its accuracy rate is above 98%; it can be applied to different scenarios and conditions to quickly determine the relationship between cells and cells, cells and multicellular aggregates, and multicellular aggregates and multicellular aggregates, and cell samples can be reused; the present invention further limits it to be achieved through a characterization system, which can achieve the above-mentioned effect.
  • the characterization system further defined by the present invention can detect cell mechanical force by reflecting light. Compared with the existing cell mechanical force detection device, it has the characteristics of high throughput and low cost; compared with the existing TFM and ordinary micro-column array, the technical solution of the present invention gets rid of the dependence on microscopes and greatly simplifies the operation process, because there is no need for high-resolution imaging through a microscope, and only the intensity of reflected light needs to be monitored to achieve high-throughput monitoring of cells at a low cost.
  • the cell mechanical force detection device is based on the deformation of the micro-column by the cell mechanical force, and converts the cell mechanical force into an optical signal for detection, which has the characteristics of high accuracy and high sensitivity; the optical intensity is linearly correlated with the size of the cell mechanical force, and the cell mechanical force can be qualitatively and quantitatively analyzed;
  • the characterization system further defined by the present invention optionally adds a magnetic metal reflective layer and a magnetic material to the top of the microcolumn, and by changing the coating composition characteristics, spacing, motion logic and other parameters of the microcolumn, it is possible to switch between measuring cell mechanical force or cell hardness, or measure cell force or cell hardness simultaneously, thereby achieving a more flexible and accurate comprehensive characterization of cell physical characteristics.
  • the characterization system of the present invention has single-cell resolution: high resolution, which can monitor each cell in real time, and can be combined with other single-cell analysis techniques to measure the heterogeneity of cell response to drugs; real-time monitoring: no fluorescence is required, which can avoid the phototoxic effect of laser on cells, so it is suitable for long-term monitoring and can be used to study the long-term response of cells to drugs; high sensitivity: through the reflection signal, the micro-column deformation signal is amplified to increase the sensitivity of deformation monitoring.
  • the detection of micro- and nano-column bending deformation generally relies on optical systems (such as microscopes) for detection, but the smaller the size of the micro-column, the higher the precision and resolution requirements of the optical system.
  • a micro-column with a width of 2 microns and a height of 6 microns requires an objective lens of more than 20 times and a conjugate focus system to be effectively observed.
  • the present invention uses the principle of mirror reflection to detect the attenuation of reflected light, and actually amplifies the signal of micro-column deformation. It has been experimentally verified that the same signal can be observed under a 5-fold objective lens. With a special reading system, the deformation of micro/nano-columns can be effectively detected without relying on a high-magnification optical objective lens, thereby greatly reducing the system cost and effectively improving the throughput.
  • the characterization system of the present invention can simulate the cell microenvironment; it can simulate the components and morphology of the extracellular matrix, and can cope with a richer range of technical demand scenarios.
  • FIG1 is a schematic structural diagram of a cell mechanical force detection device in a first embodiment of the present invention
  • FIG2 is a scanning electron microscope (SEM) image of a microcolumn (real object) of a cell mechanical force detection device in the first embodiment of the present invention; wherein 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;
  • SEM scanning electron microscope
  • FIG3 is a schematic structural diagram of a cell/multicellular aggregate interaction characterization system related to the ninth embodiment of the present invention.
  • FIG4 is a schematic structural diagram of a cell/multicellular aggregate interaction characterization system related to the tenth embodiment of the present invention.
  • FIG5 is a scanning electron microscope image of a microcolumn (polydimethylsiloxane) having a light reflecting layer (gold) at the top;
  • FIG5a is a scanning electron microscope image of the microcolumn;
  • FIG5b is an elemental characterization diagram of the top region of the microcolumn;
  • FIG5c is an elemental characterization diagram of the side region of the microcolumn (excluding the top region);
  • FIG6 is a picture of cells adhering to the top of micro-columns of a substance having a cell adhesion function (fibronectin) according to the seventh embodiment of the present application, wherein 6a is a fluorescence imaging picture of a preset pattern formed by cells adhering to a group of micro-columns with fibronectin on the top, and 6b is a cell force distribution picture calculated from the light reflection signal measured by cells adhering to a group of micro-columns with fibronectin on the top;
  • 6a is a fluorescence imaging picture of a preset pattern formed by cells adhering to a group of micro-columns with fibronectin on the top
  • 6b is a cell force distribution picture calculated from the light reflection signal measured by cells adhering to a group of micro-columns with fibronectin on the top;
  • FIG7 is a picture related to the experiment of cell adhesion in which the substance for cell adhesion is selected as OKT3 antibody (i.e., a substance that interacts with cell surface receptors) or fibronectin (Fibronectin, FN) as a substance for cell adhesion shown in a specific embodiment of the present application, wherein 7a is a schematic diagram of the experiment using OKT3 antibody as a substance with cell adhesion; the two images in the upper part of 7b are fluorescent imaging images of cells adhering to the top of microcolumns with OKT3 antibody and fibronectin on the top respectively; the two images in the lower part of 7b are cell mechanical force magnitude distribution diagrams calculated from the light reflection signal measured on the microcolumns; 7c is a mechanical magnitude comparison diagram measured on the surfaces coated with OKT3 antibody and fibronectin respectively; 7d is a diagram of the dynamic changes in cell mechanics after T cells are implanted on the OKT3 antibody surface (top of microcolumns);
  • FIG8 is a schematic structural diagram a of a cell mechanical force detection device having a cell restriction mechanism
  • FIG9 is a schematic structural diagram b of a cell mechanical force detection device having a cell restriction mechanism
  • FIG10 is a picture of a cell mechanical force detection device using a silicon film as a cell restriction mechanism in a specific embodiment of the present invention, wherein a is a physical picture thereof; b is a fluorescence microscope picture of the cell mechanical force detection device using a silicon film as a cell restriction mechanism under light reflection; and c is an enlarged picture of b;
  • FIG11 is a fluorescence microscope image of the characterization system for monitoring cell mechanical forces according to the eleventh embodiment
  • FIG12 is a schematic diagram of a cell mechanical force detection system and its detection results provided by the twelfth embodiment of the present invention, wherein a is a structural schematic diagram of a characterization system for the interaction between cells or/and multicellular aggregates of the twelfth embodiment; b is an image of a light reflection signal of a cell mechanical force detection device obtained by the light signal detection device of the twelfth embodiment; and c is a visualization effect diagram of the mechanical magnitude and distribution after processing by the light signal analysis device of the twelfth embodiment;
  • FIG13 is a schematic diagram of the relationship between the cell mechanical force and the light reflection signal using the fluid as an external force shown in a specific embodiment of the present invention, wherein a is a schematic diagram of the structure of the cell mechanical force detection device in the microfluidic environment before and after the fluid is turned on; b is a bright field microscope image of the microcolumn before the fluid is turned on, a distribution diagram of the reflected light signal, and a comparison diagram of the superposition effect of the two; wherein the superposition effect diagram refers to a comparison diagram of the bright field microscope image of the microcolumn and the distribution diagram of the reflected light signal, and the superposition effect diagram of the two; wherein the superposition effect diagram refers to a comparison diagram of the bright field microscope image of the microcolumn after the fluid is turned on, a distribution diagram of the reflected light signal, and the superposition effect diagram of the two; wherein the superposition effect diagram refers to a comparison diagram of the bright field microscope image of the microcolumn and the distribution diagram of the
  • FIG14 is a schematic diagram of a cell mechanical force detection method according to a specific embodiment of the present invention, wherein a is a schematic diagram of the structure of a cell mechanical force detection device before and after the microcolumn contacts the cell; b is a distribution diagram of a reflected light signal obtained by an optical signal detection device; c is a monitoring diagram of the cell migration process; and d is a distribution diagram of a reflected light signal during the cell migration process;
  • FIG15 is a diagram showing the cell mechanical force information obtained by the cell mechanical force detection method of the present application in a specific embodiment of the present invention, wherein a is a fluorescence imaging diagram of a mixed system of healthy cells and non-small cell lung cancer cells; b is a distribution diagram of light reflection signals of a cell mechanical force detection device obtained by an optical signal detection device; c is a visualization diagram of mechanical magnitude and distribution after processing by an optical signal analysis device; d is an enlarged diagram of representative single-cell cell force distribution of healthy cells and non-small cell lung cancer cells in c; e is a comparison diagram of cell morphology of healthy cells and non-small cell lung cancer cells; f is a comparison diagram of reflection signal strength of healthy cells, non-small cell lung cancer cells, and mixtures of these two cells in different proportions; g is a cluster analysis diagram obtained by processing c based on structured cell physical information after structured processing;
  • FIG. 16 is a diagram showing a specific embodiment of the present application showing the cell mechanical force obtained by the cell mechanical force detection method of the present application.
  • Figure 1 is a schematic diagram of the cell viability monitoring method using force information, wherein a is a schematic diagram of the operation flow of the cell viability detection method; b is a comparison diagram of the cell viability obtained by the MTT method and the cell viability reflected by the cell mechanical force after A549 cells were treated with different doses of 5FU for 24 hours; c is a comparison diagram of the cell viability obtained by the MTT method and the cell viability reflected by the cell mechanical force after A549 cells were treated with different doses of 5FU for different periods of time;
  • FIG17 is a schematic diagram of scalar processing of displacement information of a certain point in the twenty-ninth embodiment of the present invention.
  • FIG19 is a result diagram B of using the established cell characteristic model for identifying unknown cells or unknown cell phenotypes in the extended implementation manner of the thirtieth embodiment of the present invention.
  • FIG20 is a diagram showing the experimental results of monitoring organoid attachment and drug response using mechanical force characterization in the thirty-fifth embodiment
  • FIG21 is a diagram showing the results of a fluorescence staining experiment using mechanical force to characterize tumor spheroids in the thirty-sixth embodiment
  • FIG22 is a diagram showing the experimental results of using a restrictive structure to constrain the size and shape of a cell spheroid in the thirty-sixth embodiment
  • FIG23 is an imaging and quantitative diagram of fluorescence performance and cell mechanical force of a T cell line after activation by a CD3 antibody coating on a device in the forty-first embodiment of the present invention
  • FIG. 24 is a visualization of the effect of measuring the mechanical force of mouse cardiomyocytes using the cell mechanical force measuring device in the fifty-third embodiment.
  • FIG25 is a diagram showing changes in cell mechanical force during differentiation of NIH3T3-L1 cells into adipocyte-like cells in the fifty-sixth embodiment
  • FIG26 is a diagram showing the fifty-eighth embodiment of printing tropic ECM on a chip and characterizing the induction of cardiac tissue by stem cells;
  • FIG27 is a diagram showing the fifty-ninth embodiment of printing tissue-specific ECM on a chip and performing fluorescence and histochemical staining to characterize cartilage induced by stem cells;
  • FIG28 is a schematic diagram of a double-sided deformable lung tumor chip according to the sixtieth embodiment
  • FIG29 is a cell mechanical force imaging diagram of a tumor tissue block and a normal tissue block in the sixty-third embodiment
  • FIG30 is a cell mechanical force imaging diagram of a tumor tissue block and a normal tissue block after drug treatment in the sixty-third embodiment
  • FIG. 31 shows a sandwich structure according to the thirty-sixth embodiment.
  • 1-cell mechanical force detection device 2-optical signal generating device; 3-optical signal detection device; 4-optical signal analysis device; 5-Spectrum splitter; 11-base; 12-microcolumn; 13-light reflecting layer; 15-recessed space; 16-limiting surface; 101-objective lens; 102-incident and reflected light; 103-deformed microcolumn; 104-cell; 105-antireflection layer; 106-substance with cell adhesion effect; 107-substance with cell adhesion inhibition effect.
  • This embodiment provides a method for characterizing cells or/and multicellular aggregates, which characterizes cells or/and multicellular aggregates by acquiring cell physical information of cells or/and multicellular aggregates; the cell physical information includes cell mechanical force and/or hardness at a certain point in the cell; the cell mechanical force includes at least one of size, direction, and frequency.
  • the cell physical information also includes cell morphology information.
  • the cell physical information includes changes in the cell mechanical force and/or hardness at this point within a certain time interval.
  • the cell mechanical force and/or hardness in the cell physical information is presented in a visual form.
  • the cell physical information is obtained by performing cell restriction operations on cells or/and multicellular aggregates.
  • Restriction enables a fixed number of cell groups to be cultured in an orderly manner in a restricted environment, and enables high-throughput monitoring of changes in their cell mechanical forces. At the same time, it allows each cell group to have the opportunity to contact other cell groups, which is conducive to observing cell-to-cell interactions. Differentiation refers to the identification of known types and unknown types.
  • the cell physical information is obtained based on the following interactions: interaction between cells and multicellular aggregates; interaction between cells and cells; interaction between multicellular aggregates and multicellular aggregates; interaction between cells and multicellular aggregates;
  • the first cell or/and the multicellular aggregate, the second cell or/and the multicellular aggregate are respectively arranged in specific areas, and the physical information of the cells is detected and obtained;
  • the second cell or/and multicellular aggregate After placing the first cell or/and multicellular aggregate in a specific area, the second cell or/and multicellular aggregate interacts with the first cell or/and multicellular aggregate to detect and obtain cell physical information;
  • the first cell or/and multicellular aggregate, and the second cell or/and multicellular aggregate are both more than one cell or/and multicellular aggregate;
  • the cell physical information is used to characterize the interaction between the first cell or/and the multicellular aggregate, and the second cell or/and the multicellular aggregate.
  • the cell/multicellular aggregate characterization system of embodiment 1 may be selected for characterization, and the specific area is located in the cell/multicellular aggregate characterization device characterization system;
  • cells and/or multicellular aggregates may be attached to specific areas, optionally in a restricted manner.
  • the attachment method includes: placing cells or/and multicellular aggregates in a specific area (a specific area of the characterization system in some other specific embodiments), culturing them statically for more than half an hour, and continuing to add culture medium for culturing until the cells or/and multicellular aggregates are completely attached to the specific area (characterization device).
  • external stimulation is added before or during the detection and acquisition of cell physical information.
  • the added external stimulation may be, but is not limited to: biological, chemical, physical stimulation, tropism guidance, dynamic stimulation;
  • Drug stimulation is used to monitor and characterize the effects of drugs on cells and/or multicellular aggregates, as well as the interactions between cells and multicellular aggregates, the interactions between cells and cells, the interactions between multicellular aggregates and multicellular aggregates, and the changes in the interactions between cells and multicellular aggregates under drug stimulation. Furthermore, the pharmacological effects and other characteristics of the drug are detailed.
  • other chemical stimuli can be, but are not limited to: pH value, oxygen content, sugar concentration.
  • Biostimulation can be, but is not limited to: Growth factors are key signaling molecules for cell growth and proliferation. Cells can be stimulated by adding growth factors to promote their proliferation, migration, or differentiation, thereby affecting the mechanical properties and interactions of cells.
  • Extracellular matrix (ECM) composition Changing the composition or structure of the ECM, such as by adjusting the stiffness, fiber arrangement, or chemical composition of the ECM, can directly affect the mechanical response and behavior of cells.
  • Dynamic stimulation can be, but is not limited to: Cyclic strain: Applying cyclic strain stimulation, such as alternating tensile and compressive forces, can simulate the dynamic changes of biological tissues in physiological processes, thereby studying the mechanical response and adaptability of cells.
  • Time-varying chemical environment By changing the chemical environment cyclically or stepwise, such as cyclically changing drug concentrations or the addition and removal of chemicals, the dynamic response and adaptation of cells under physiological or pathological conditions can be simulated.
  • the directional guidance can be, but is not limited to: by forming a biomorphic gradient on the substrate, such as the structure or stiffness gradient of the extracellular matrix, cells can be guided to grow or move in a certain direction. By drawing a line on the substrate in a certain direction, cells can be guided to grow and change in the direction of the line.
  • Physical stimulation can be, but is not limited to: temperature, magnetic induction, electrical stimulation, flow field stimulation;
  • Mechanical force By applying mechanical stimulation such as mechanical stretching, squeezing or compression, the morphology and mechanical response of cells can be directly regulated, including but not limited to changing cell morphology and intracellular mechanical distribution.
  • Fluid mechanics stimulation Applying fluid mechanics stimulation, such as shear force and flow field changes, can simulate the physiological environment of cells in blood or tissue fluids, thereby regulating the physiological activity and mechanical properties of cells.
  • External stimulation can amplify the difference in cell mechanical force information between cells of different types, making them easier to identify and improving the efficiency and accuracy of identification.
  • a characterization device containing microcolumns is used to detect mechanical force and hardness
  • the cell physical information is amplified by changing the hardness of the microcolumns.
  • the attachment of cells or/and multicellular aggregates can be achieved by adding cell culture fluid and continuing the culture to allow them to be stably attached. At the same time, the cells or/and multicellular aggregates can be attached by adhesive substances.
  • the cell physical information of cells/multicellular aggregates is obtained respectively, and the identification of the interaction between cells and/or multicellular aggregates is realized;
  • the cell mechanical force can be monitored and obtained by a micro-force sensor or a micro-rheometer, or a cell mechanical force detection device. These devices can measure the magnitude, direction, and frequency of the force exerted by cells on the matrix or other cells. By measuring the cell mechanical force at a specific time interval, its changes can be understood.
  • the hardness of cells or multicellular aggregates can be measured by nanoindentation, force-distance curve technology, etc. These techniques can quantitatively assess the hardness of cells or aggregates to understand their changes when subjected to external forces.
  • Cell morphology information and spatial distribution can be obtained through imaging techniques such as microscopy, confocal microscopy, atomic force microscopy, etc. These techniques can observe the morphological characteristics of cells, the internal structure of cells, and the spatial distribution of cell aggregates.
  • physical information of cells can be obtained through the characterization system
  • a base and a micro-column array composed of one or more micro-columns disposed on the base and capable of being deformed by mechanical force and/or magnetic force of cells, wherein a light reflecting layer is disposed on the micro-columns;
  • a light reflecting layer is provided at one end of the microcolumn away from the base, the base is provided with a light-transmitting portion, and the body of the microcolumn is provided with a light-transmitting portion; optionally, the surface of the microcolumn and/or the base has an anti-reflection layer.
  • the light emitted by the optical signal emitting device irradiates the light reflecting layer through an incident light path, and the light reflected by the light reflecting layer enters the optical signal detecting device through a reflected light path;
  • the optical intensity acquired by the optical signal detection device is analyzed to obtain cell physical information
  • the optical intensity acquired by the optical signal detection device is linearly correlated with the magnitude of the cell mechanical force, and qualitative and quantitative analysis can be performed to achieve different cell typing.
  • the characterization device may contain a liquid
  • liquid is a cell culture medium, allowing the cells and/or multicellular aggregates to adhere and/or continue to be cultured;
  • the cells and/or multicellular aggregates are adhered to the micro-columns by an adhesive substance disposed on the micro-columns.
  • the multicellular aggregate can be combined with the characterization device in a variety of ways.
  • two specific combination methods are provided:
  • the first combination mode a culture medium is set on the microcolumn of the cell mechanical force detection device, and cells are transplanted into the culture medium on the microcolumn to culture to obtain multi-cell aggregates; in other embodiments, this combination mode can monitor the cell culture process in real time when the cell physical information is output in a visual form, so as to be applied to the influence of chemical, biological and physical external stimuli such as culture medium and drugs on cell growth;
  • the second combination method is to directly adhere the cultured multicellular aggregates to the microcolumns of the cell mechanical force detection device for detection.
  • This embodiment also provides a method for typing and identifying the cell or/and multicellular aggregates by using any of the cell physical cells described above;
  • the typing and identification include: the type, state, behavior, spatial omics characteristics and differentiation direction, and stress response of cells or/and multicellular aggregates;
  • the typing and identification includes: selectively sorting out specific cells or tissues by physical cell analysis of the cells.
  • the cell recognition device uses a cell recognition device for recognition, and the cell recognition device includes an information acquisition unit, a preprocessing unit, a learning unit and a recognition unit;
  • the information acquisition unit is used to acquire cell physical information of cells and/or multicellular aggregates
  • the preprocessing unit is used to preprocess the cell physical information to form structured cell physical information;
  • the structured cell physical information includes the number of cells, the number of cell features and feature information of each cell feature;
  • the learning unit is used to establish a cell feature model using supervised, unsupervised or semi-supervised machine learning with structured cell physical information as input data;
  • the identification unit is used to apply the cell characteristic model to the classification or clustering of cells and/or multicellular aggregates to achieve typing and identification of cells and/or multicellular aggregates.
  • Identification in the present invention refers to the identification of cells of known genotype and unknown genotype and/or multicellular aggregates.
  • the classification in the present invention refers to the differences in characteristics of cells or/and multicellular aggregates, including but not limited to type, state, behavior, spatial omics characteristics, etc. due to different factors. According to the above differences, classification can be performed. The same or similar cell physical information can be clustered and further formed into different types.
  • the present invention can realize rapid and high-throughput identification of differences between cells/multicellular aggregates by acquiring cell physical information, and can be applied to the response of cells/multicellular aggregates to drugs.
  • Cell or/and multicellular aggregate typing refers to the fact that due to different factors, cells or/and multicellular aggregates may have different characteristics, including but not limited to type, state, behavior, spatial omics characteristics, etc., and typing can be performed based on the above differences.
  • This embodiment provides a method for characterizing cells or/and multicellular aggregates, which is different from the first embodiment in that it is based on multicellular aggregates at different growth moments, or/and based on cell physical information obtained from different regions inside the multicellular aggregates;
  • the method for obtaining cell physical information may include, but is not limited to, placing the multicellular aggregate on a specific area, adding cell culture fluid to allow the multicellular aggregate to be stably attached, so as to facilitate the determination of cell physical information.
  • this embodiment can use the characterization system described in Embodiment 1 to obtain the cell physical information.
  • the characterization system can accommodate cell culture fluid; the addition of cell culture fluid can achieve the acquisition of tissue cell mechanical force while the tissue is cultured on the cell mechanical force detection device (characterization device) without removing the tissue from the cell mechanical force device.
  • the liquid level of the cell culture medium is higher than the top of the microcolumn
  • the method for obtaining physical information of tissue cells is: placing the tissue on the characterization system, adding cell culture fluid so that the tissue is in contact with the cell culture fluid for at least half an hour, culturing for more than half an hour, continuing to add cell culture fluid and culturing until the tissue is completely attached to the microcolumns, and then measuring and obtaining the cellular mechanical force of the tissue in real time.
  • external stimulation is added to measure the change in the mechanical force of the cells under the external stimulation.
  • the multicellular aggregates (which may be tissues) are attached to the micro-pillars by adhesive substances disposed on the micro-pillars.
  • the multicellular aggregate refers to tissue, and the tissue can be selected as a tissue slice of 150 to 200 mm;
  • the tissue includes living tissue, organoids, and in vitro organs.
  • the multicellular aggregate is stimulated by external factors before, during and after measuring and acquiring the physical information of the cells.
  • external stimulation is added to measure the change in the mechanical force of the cells under the external stimulation.
  • External stimulation can amplify the differences in cell physical information between different regions of different multicellular aggregates and different types of multicellular aggregates, making them easier to identify and improving the efficiency and accuracy of identification.
  • a cell mechanical force detection device containing microcolumns is used to detect mechanical force and hardness
  • the cell physical information is amplified by changing the hardness of the microcolumns.
  • the specific external stimulation is as described in the first embodiment.
  • Different regions within the multicellular aggregate include, but are not limited to, tumor regions and non-tumor regions in the tissue; after characterization, tumor regions and non-tumor regions in the tissue can be identified.
  • Peripheral zone Located at the outer edge of the multicellular aggregate, in contact with the surrounding environment and may be exposed to the medium or culture medium.
  • Central region The central part of a multicellular aggregate, which is usually more compact due to increased cell density and may have a different cellular organization.
  • Marginal area An area between the peripheral area and the central area, usually showing different characteristics from the peripheral and central areas.
  • Core region The core part of a multicellular aggregate, which may be the area with the highest cell density or may contain certain specific types of cells or cell groups.
  • Surface area The surface area located on the outside of the multicellular aggregate that may be directly exposed to the external medium and in direct contact with the surrounding environment.
  • Functional domain An area within a multicellular aggregate that has a specific function or activity, such as a metabolically active area, a secretory area, or a differentiated area.
  • Gradient regions present within multicellular aggregates may contain gradient-distributed signaling molecules or nutrients.
  • Microenvironmental region The microenvironment within a multicellular aggregate, which may be influenced by cell secretions, cell-cell interactions, or matrix components, has an important impact on cell behavior and function.
  • This implementation can characterize, classify and identify not only the above-mentioned areas but also unknown areas.
  • This embodiment can form structured information of the cell information of the multicellular aggregate (tissue) state, and different types of tissues.
  • Different tissues can be divided into: two or more different tissues, different states of a tissue formed at different times or under external stimuli, and two or more different regions in a tissue;
  • Two or more different tissues can be pathological tissue and normal tissue;
  • the different states of a tissue at different times or under external stimuli can be the different states of the tissue corresponding to different times under dynamic changes after the addition of drugs; or the changing state of the tissue during the culture process after the addition of cell culture medium.
  • Two or more different regions in one tissue there may be a tumor region and a non-tumor region in one tissue.
  • This embodiment can use the cellular mechanical force of the multicellular aggregate (tissue) to cause the micro-column to deform, thereby converting and amplifying the cellular mechanical force into a light reflection signal, and realizing accurate identification of the mechanical force of tissue cells; it can be applied to real-time monitoring of the tissue during the change process. Even if the tissue has only slight changes during the culture process, the changes in its tissue cell mechanical force can be obtained, and the mechanical fingerprint of each changed tissue can be given.
  • the micro-column can also be penetrated into the cell through magnetic force to realize hardness measurement, thereby realizing characteristic, accurate and rapid identification.
  • This embodiment can be used to quickly, directly, non-destructively and in real time measure the cellular mechanical force of the entire living tissue and each cell in the living tissue; the mechanical force of the cells is measured by the contact between the cells in the tissue and the microcolumns.
  • the mechanical distribution of the entire tissue measured using the characterization system can be used to identify different cell blocks in the tissue, such as identifying tumor areas and non-tumor areas; in addition, when measuring the cellular mechanical force of the tissue, drug treatment can be directly added to monitor the changes in the cellular mechanical force of the cells in the tissue in real time to determine whether the drug has achieved the effect, thereby achieving accurate drug screening with an accuracy rate of more than 98%.
  • This embodiment provides a method for quickly, directly, non-destructively, and in real time measuring the mechanical force of living tissue as a whole and of each cell.
  • the mechanical force of the cells can be measured through the contact between the cells and the microcolumns in the tissue.
  • different cell blocks such as tumor and non-tumor areas, can be identified.
  • this method can directly introduce drug treatment when measuring the mechanical force of tissue cells, and monitor the changes in cell mechanical force in real time to evaluate the effect of the drug and achieve precise drug screening with an accuracy rate of more than 98%.
  • this method can also realize real-time monitoring of cell mechanical force during tissue culture and dynamic changes, quickly measure the cell mechanical force of entire living tissues, use the strength of cell mechanical force to identify tumor and non-tumor areas, and monitor the mechanical force changes of tumor cells in real time after drug treatment to determine whether the drug can effectively inhibit tumor cell growth.
  • This method converts the mechanical force information of tissue cells into structural information, and realizes the determination and identification of different tissue states. Accordingly, it also provides a characterization system and an identification system for tissue states, as well as applications in tissue state identification and drug effectiveness evaluation methods for tumors.
  • This embodiment provides a method for characterizing cells and/or multicellular aggregates, which is different from the first embodiment in that:
  • the method for obtaining cell physical information comprises the following steps:
  • the culture medium is added to at least allow the cells or/and multicellular aggregates to contact the cell culture medium, and the cells are cultured for more than half an hour, and the cell culture medium is continued to be added until the cells or/and multicellular aggregates are completely attached to the specific area.
  • the substance that reacts with it is added to continue culturing, and the physical information of the cells is measured and obtained.
  • culturing for more than half an hour is conducive to better fixation of cells/multicellular aggregates and microcolumns.
  • external stimulation is added before or during detection and acquisition of physical information of cells.
  • the substances include biologically active macromolecules, chemical substances, biologically active substances and inactivated biological substances; the biologically active macromolecules include proteins, polypeptides, polysaccharides and fats.
  • This embodiment provides a cell mechanical force detection device or a cell/cell polymer characterization system described in any of the above embodiments or a cell mechanical force detection method described in any of the above schemes to obtain cell mechanical force information of cells/multi-cell polymers; specifically, it includes the following steps: placing cells/multi-cell polymers on a cell mechanical force detection device, adding a cell culture fluid to at least make the cells/multi-cell polymers contact with the cell culture fluid, culturing for more than half an hour, continuing to add a cell culture fluid to culture until the cells/multi-cell polymers are completely attached to the micro-columns, and then measuring and obtaining the cell mechanical force of the cells/multi-cell polymers.
  • external factors are added to detect the dynamic changes of the cell mechanical force of cells/multi-cell polymers under external factors; in some specific embodiments, external factors can be added before or during the detection of cell mechanical force.
  • the substance can be produced by the cells/multi-cell polymers or added from the outside.
  • This embodiment also provides a method for obtaining visualized cell information containing cells and/or multicellular aggregates before, during and after the interaction between a substance and a cell/multicellular aggregate through a cell mechanical force detection device, including visualized information such as the size and distribution of the change in cell mechanical force; the visualized information is used for visual identification of the interaction between the substance to be tested and the cell/multicellular aggregate, and real-time monitoring and characterization of the interaction between the substance and the cell/multicellular aggregate.
  • the cell mechanical force information also includes the direction of the cell mechanical force at that point. In some other embodiments, the cell mechanical force information also includes the change in the magnitude or direction of the cell mechanical force at that point within a certain time interval. In some other embodiments, the cell information also includes cell morphology information. In some other embodiments, the cell mechanical force information is obtained by the method of the eighteenth embodiment. Based on the cell mechanical force detection device of the present invention, not only can it be visually distinguished by the naked eye for qualitative analysis, but also the state of cells/multicellular aggregates can be more intuitively and accurately identified (quantitative and qualitative analysis) based on the measured cell mechanical characteristics, and it has been confirmed that the cell force field can be used as a marker to better distinguish types.
  • the present invention also provides a substance and cell/multicellular aggregate identification system and method, which converts cell information including cell mechanical force information of the substance's effect on cells/multicellular aggregates into structured information, thereby realizing rapid and automatic determination and identification of the interaction between the substance to be tested and the cells/multicellular aggregates.
  • the present invention also provides a cell/multicellular aggregate characterization and identification system and method for use in related methods and products that require characterization of interactions between cells/multicellular aggregates.
  • the cell mechanical force detection device of the present invention can detect the cell mechanical force of multilayer cells, including tumor polymers, so that it can be applied to drug screening, regenerative medicine, gene editing, precision medicine, organ development, and disease modeling where multiple cells are needed.
  • This embodiment provides a method for characterizing cells and/or multicellular aggregates, which is different from the third embodiment in that the cell physical information can also be obtained by stimulating cells and/or multicellular aggregates based on other physical, biological or chemical factors.
  • the method can be:
  • Placing cells and/or multicellular aggregates in a specific area may be placed in the characterization system.
  • the method can monitor subtle changes in cell mechanical force during the culture process or under external factors, and can be used to measure changes in the state of multicellular aggregates or cells during the culture process or under external factors, and characterize the stress response of cells and/or multicellular aggregates.
  • the external stimulus factors include drugs, mechanical force, biochemistry, electric field, tropism guidance, dynamic stimulation, and a combination of one or more stimuli in the flow field acting on the culture.
  • the sample to be tested may be subjected to different
  • the method can be used to perform stimulation of different types and intensities (mechanical stimulation, electrical stimulation, light stimulation, etc.), and to operate samples at specific locations or regions (labeling, solidification, ablation, cutting, extraction, sorting, etc.); it can be combined with other characterization methods (protein staining, histochemical staining, single-cell sequencing, etc.) for comparative analysis.
  • it also includes an action mechanism acting on the characterization system or cells, and the action mechanism is one or a combination of two or more of microfluidics, microneedles, and lasers.
  • the appropriate microcolumn height, the spacing between adjacent microcolumns, and the size of the column surface within the above range can make the cells/multicellular aggregates in a more stable state in the characterization system of substances and cells/multicellular aggregates.
  • the method of this embodiment can be used to characterize cell viability, adhesion, migration, activation, differentiation, and apoptosis;
  • stimulation is used to cause stress to cells or/and multicellular aggregates, including physical stimulation, biochemical stimulation, and stimulation between small molecules and macromolecules on cells or/and multicellular aggregates.
  • the cell physical information obtained includes: the cell mechanical force and dynamic changes of cells and/or multicellular aggregates when the organism is not stressed, and during/after stress.
  • the present invention can first fix attached cells or/and multicellular aggregates at specific locations and then apply stimulation, or continue to add other cells or/and multicellular aggregates to the attached cells or/and multicellular aggregates, and can monitor changes in the physical information of the attached cells or/and multicellular aggregates in real time, and can monitor the interactions between cells or multicellular aggregates, or between cells and multicellular aggregates in real time.
  • the sample to be tested before, during or after using the characterization system for characterization, can be subjected to stimulation of different types and intensities (mechanical stimulation, electrical stimulation, light stimulation, etc.), and samples in specific locations or areas can be operated on (labeling, solidification, ablation, cutting, extraction, sorting, etc.); it can be combined with other characterization methods (protein staining, histochemical staining, single-cell sequencing, etc.) for comparative analysis.
  • stimulation of different types and intensities mechanical stimulation, electrical stimulation, light stimulation, etc.
  • samples in specific locations or areas can be operated on (labeling, solidification, ablation, cutting, extraction, sorting, etc.); it can be combined with other characterization methods (protein staining, histochemical staining, single-cell sequencing, etc.) for comparative analysis.
  • This embodiment provides a method for characterizing cells or/and multicellular aggregates, which is different from the first embodiment in that: it is based on the physical information of cells during the planting and growth of an in vitro organ or/and related cell model; the physical information of cells includes: physical information of cells or/and any region during the planting and culturing of a culture of organ-related cells or/and tissues;
  • the cell physical information is used to characterize cells or cell clusters, organ tissues in any region of the in vitro organ or/and related cell model growth process;
  • a mixture of cells or/and tissues and ECM is seeded
  • the method of planting includes: 3D printing and/or microfluidic method to control cells
  • the distribution and flow of materials are used to achieve planting.
  • cultures of organ-related cells and/or tissues are seeded on characterization devices to prepare in vitro organ and cell models;
  • the specific method includes
  • S1 collects microenvironment parameters under the physiological and pathological conditions of the corresponding tissue, and manufactures the corresponding in vitro organ chip from the characterization device according to the parameters (i.e., the characterization device can be customized into an in vitro organ chip);
  • S2 planting the culture including the organ-related cells and/or tissues on the in vitro organ chip.
  • the planting can be carried out on the in vitro organ chip by 3D printing.
  • S3 optionally adding physical and biochemical stimulation, including one or a combination of two or more stimulations selected from the group consisting of drugs, mechanical force, biochemistry, electric field, and flow field, to act on the culture;
  • step S4 obtaining the changes of the cell mechanical force of each cell and tissue through the in vitro organ chip, and achieving the characterization of each cell and organ tissue.
  • step S4 selectively sorting out specific cells or tissues through the characterization.
  • the recognition unit in the cell recognition device is used to apply the cell characteristic model to the classification or clustering of organs and cells in growth states or under external stimuli, so as to realize the recognition and characterization of organs and cells in corresponding states at each moment.
  • the characterization system of the present invention forms structured information of the cell information of the organ in the corresponding state at each moment, and analyzes the cell information in the unknown state to realize automatic recognition of cells in the unknown state.
  • In vitro organ chips can simulate the structural microenvironment of human organs and accurately approximate the real organ environment. At the same time, they can monitor the behavior of each cell in real time for a long time to achieve organ characterization and can be applied to in vitro organs. The establishment of relevant cell models is applied to the needs of various research topics for relevant models;
  • in vitro organ chips are used in screening therapeutic drugs for the organ, and in studying organ models under physiological and case conditions.
  • the in vitro organ chip in this embodiment can not only simulate the structural microenvironment of the organ in the body, but also can detect the cellular mechanical force of each cell and the cellular mechanical force of the organ tissue in real time to achieve characterization; it can monitor subtle changes in cellular mechanical force during the culture process or under external stimulation, and can be used to measure organ tissue or cell changes during the culture process under external stimulation.
  • the external stimulus includes a combination of one or more stimuli such as drugs, mechanical force, biochemistry, electric field, and flow field, acting on the culture.
  • the characterization method of the present invention is different from the characterization method of traditional life sciences. It is non-invasive and label-free, and can monitor living cells or tissues in real time for a long time, and characterize samples with single-cell resolution. It can be closer to the real environment of the organ;
  • the chip body is provided with micro-columns of corresponding hardness and length according to the organ; micro-columns of different hardness and length can be customized according to different organs, so as to simulate a more realistic environment of the organ.
  • a heart chip it can create a heart microenvironment on a microchip, including mechanical contraction, molecular transmission, electrical activity, biochemical stimulation and other factors, which are customizable. It can simulate the complex structure and function of the heart in a tiny space, including multiple tissue components such as myocardial cells, vascular endothelial cells, and myocardial extracellular matrix, thereby simulating heart function more accurately.
  • the surface of the microcolumn is provided with ECM;
  • a mixture of the organ-related cells or/and tissues and ECM is planted on the microcolumn;
  • the surface of the microcolumn has a tropic ECM layer;
  • the planting method includes: 3D printing; In order to achieve better controllability and repeatability. 3D printing and microfluidics can be used to accurately control the distribution and flow of cells and biomaterials, as well as simulate blood flow in organs (such as the heart); various parameters of the microenvironment can be standardized to improve experimental repeatability and data comparability.
  • the cells include one or a combination of two or more of cardiomyocytes, smooth muscle cells, endothelial cells, fibroblasts, stem cells, and immune cells.
  • it further comprises: an electrode device, the micro-column is made of a conductive material, and the electrode device acts on the micro-column.
  • a mechanical simulation device which is a mechanical stretching device for stretching the chip body; or an inflatable and deformable flexible film arranged at the bottom of the microcolumn; the upper end of the flexible film is connected to the microcolumn, and the lower end is connected to the base, or the base is a flexible film.
  • the implantation area of the in vitro organ is stimulated by external factors.
  • External stimulation can amplify the differences in cell physical information between different regions within the multicellular aggregates, cells of different types, and multicellular aggregates, making them easier to identify and improving the efficiency and accuracy of identification.
  • a cell mechanical force detection device containing microcolumns is used to detect mechanical force and hardness
  • the cell physical information is amplified by changing the hardness of the microcolumns.
  • the specific external stimulation is as described in the first embodiment.
  • the cells include one or a combination of two or more of cardiomyocytes, smooth muscle cells, vascular endothelial cells, fibroblasts, stem cells, and immune cells.
  • the improved in vitro organ chip in this embodiment is used in screening therapeutic drugs for the organ, and in studying organ models under physiological and case conditions.
  • the method and in vitro organ chip in this embodiment have better characterization capabilities by detecting cell mechanical forces, are non-invasive and label-free, and can monitor living cells or tissues in real time for a long time and characterize them with single-cell resolution; in vitro organ chips can be used as an important technical means through cell mechanomics to address the shortcomings of cell and animal models commonly used in existing technologies, thereby promoting the further development and application of research on organs such as the heart.
  • the in vitro organ chip of the present invention is closer to the real organ environment.
  • the heart can create a cardiac microenvironment on a microchip, including mechanical contraction, molecular transmission, electrical activity, biochemical stimulation and other factors, which can be customized. It can simulate the complex structure and function of the heart in a tiny space, including multiple tissue components such as myocardial cells, vascular endothelial cells, and myocardial extracellular matrix, thereby simulating cardiac function more accurately.
  • 3D printing and microfluidics can be used to accurately control the distribution and flow of cells and biomaterials, as well as simulate the blood flow of organs such as the heart; the conditions of the microenvironment can be standardized to improve repeatability and data comparability. It is more economical, efficient, safe and ethical. Compared with animal experiments or clinical trials, it can save time and cost, and is safer and more ethical.
  • the in vitro organ chip of the present invention can characterize the organ or even each cell in each state in a short time, at low cost and with high throughput by monitoring the mechanical force of each cell in real time, thereby realizing accurate identification and continuous long-term monitoring of the effects of external stimuli such as drugs on organs and cells at every moment.
  • external stimuli such as drugs on organs and cells at every moment.
  • accuracy rate is above 98%; for other external stimulus research methods, its recognition accuracy rate is above 98% under different states.
  • This embodiment provides a method for identifying and typing cells and/or multicellular aggregates: the method can also be used for typing and identification through the cell physical information obtained in Embodiments 1 to 5, and includes:
  • the substance comprising one or a combination of two or more of a protein or/and a polypeptide, a semi-solid culture medium, and an antibody or a secondary antibody;
  • this system can monitor the effects of genetic engineering on cells, including: detecting small clone clusters or single cells near large clones;
  • the growth and differentiation of fat cells can be monitored; optionally, it can be used to monitor the conversion process of white fat, beige fat and brown fat in real time.
  • the identification method comprises the following steps: obtaining cell physical information of cells/multicellular aggregates through a cell mechanical force detection device to realize the identification of the interaction between substances and cells/multicellular aggregates; the cell physical information includes cell mechanical force information; the present invention can realize rapid and high-throughput identification of differences in cells/multicellular aggregates by obtaining cell mechanical forces, and can be applied to the response of cells/multicellular aggregates to substances.
  • This embodiment obtains cell physical information before, during and after the action.
  • the cell physical information in this embodiment can be measured in real time, or at a specific time or time interval, and the cell physical information can be continuous or intermittent.
  • This embodiment can characterize cells or/multicellular aggregates at different growth moments and under external stimulation, and can also perform typing and identification of known or unknown types.
  • the present embodiment is not limited to the characterization at different growth moments and under the action of a specific external factor, but can be the characterization of cells or/and multi-cell aggregates under the action of various combinations of factors.
  • This embodiment can be used for clustering and classification of cells or/and multicellular aggregates, especially unknown classification, before, during and at any time after the action of a substance on the cells or/and multicellular aggregates through the characterization.
  • any of the above-mentioned embodiments can use 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 to obtain cell physical information and perform analysis.
  • First embodiment a device for detecting cell mechanical force
  • FIG1 is a schematic diagram a of the structure of a device for detecting cell mechanical force.
  • the device for detecting cell mechanical force shown in the figure includes a light-transmitting base 11 (in some other specific embodiments, the base is provided with a light-transmitting portion, that is, it may not be a fully light-transmitting base, and may be provided with a light-impermeable portion) and a microcolumn 12 disposed on the base 11 and deformable by the cell mechanical force.
  • the top of the microcolumn 12 is coated with a light-reflecting layer 13, and the thickness of the light-reflecting layer 13 is 5 nm (in some other embodiments, the thickness of the light-reflecting layer 13 may be between 5 nm and 20 nm - the thickness of the coating is related to the coating material. Under the premise of using the same coating material, the selection of the coating thickness should be limited to ensuring the light-transmitting effect, the stability of the microcolumn body, and ensuring that the connection with the microcolumn body does not fall off).
  • the body of the microcolumn 12 can transmit light, as shown in FIG1 1 and 14 , the light-impermeable portion of the base is formed by a configuration including but not limited to an anti-reflection layer 105.
  • Figure 2 is a scanning electron microscope (SEM) image of the micro-column 12 (real object) of the cell mechanical force detection device of this embodiment
  • a is a top view of the cell mechanical force detection device
  • b is a side view of the cell mechanical force detection device.
  • the micro-column of the cell mechanical force detection device has a uniform microstructure and controllable size. Compared with the existing cell mechanical force detection device, the mechanical value measured by the cell mechanical force detection device based on this embodiment is more accurate.
  • Figure 3 is a structural schematic diagram of the characterization system of the cell/multi-cell aggregate interaction related to the ninth embodiment of the present invention. Figure 3 can be used to understand this embodiment.
  • the system shown in Figure 3 also involves: an optical signal generating device 2 with a light source and an optical signal detecting device 3 arranged below the base 11, the light emitted by the light source is irradiated from the transparent base 11 of the cell mechanical force detection device 1 to the light reflecting layer of the micro-pillar 12 through the incident light path; the optical signal detecting device 3 is used to detect the light reflected from the light reflecting layer 13 at the top of the micro-pillar, and the light reflected by the light reflecting layer 13 enters the optical signal detecting device 3 after passing through the reflection light path and the action of the spectrometer 5.
  • an optical signal analyzing device 4 can compare and analyze the reflected light before and after the cell mechanical force is applied to the cell mechanical force detection device 1 and the cell to be tested to obtain cell mechanical force information.
  • the micro-pillar 12 When the micro-pillar 12 is not subjected to force, it should remain upright so as to reflect the detection light to the maximum extent; when the micro-pillar 12 contacts the cell, under the action of the cell mechanical force, the micro-pillar 12 deforms (including but not limited to bending and swinging), resulting in a decrease in the light reflection level. Therefore, when the cell mechanical force is greater, the light reflection signal obtained should be smaller, so the size of the cell mechanical force at that point can be easily inferred by observing the intensity of the light reflection signal.
  • the measurement light source in the technical solution of this embodiment can use an infrared laser of a certain intensity.
  • Microcolumn measurement in the traditional technical solution requires taking high-resolution images. If a laser is used in this process, it is easy to cause cell phototoxicity or sample fluorescence quenching. In this technical solution, if only the reflection signal is measured, the effect of infrared laser within a certain light intensity on cells can be basically ignored, so it is suitable for long-term monitoring of cells.
  • Second embodiment a device for detecting cell mechanical force
  • the microcolumn 12 not only has a light reflecting layer 13 on the top end surface, but also has a light reflecting layer 13 on the upper half of the cylindrical surface of the microcolumn 12 (i.e., the curved surface connecting the two end surfaces of the column).
  • the detection effect desired by the present invention can basically be achieved.
  • the light reflecting layer 13 can even be laid at any local position of the upper half of the side cylindrical surface or the local position of the top, and it does not have to cover the entire upper half of the cylindrical surface or the entire top end surface, and the expected purpose can be achieved, although the acquired data and the effect of the subsequent calculation may be different.
  • first and second embodiments of the present invention have definitions of the "cylindrical surface” and "end surface” of the microcolumn, that is, the independent column that we usually understand should have two end surfaces and a curved surface (cylindrical surface) connecting the two end surfaces, while the microcolumn in the present invention has only one end surface, namely the top end surface, due to the presence of the base, and the other end is fixedly connected to the base or integrally formed with the base.
  • the end surface at the top may be a curved surface that is smoothly connected to the cylindrical surface as a whole, and it does not necessarily have an intersection line or a clear boundary as shown in the first or second embodiments.
  • the setting position of the light reflecting layer 13 will also be understood as the upper half of the column, and cannot be limited to the "end surface” or "cylindrical surface”.
  • Third embodiment a device for detecting cell mechanical force
  • FIG4 is a schematic diagram of the structure of a cell/multi-cell aggregate characterization system in the tenth embodiment of the present invention, and is used to illustrate the cell mechanical force detection device 1 in this embodiment.
  • the difference between this embodiment and the first and second embodiments is that the light transmittance of the base 11 and the micro-pillars 12 of the micro-pillar array is not required, that is, it can be light-transmitting or not.
  • the optical signal received by the optical signal detecting device 3 will change relative to the micro-column 12 when it is upright and not deformed.
  • the relative magnitude of the cell mechanical force can also be obtained. After correction with the standard value, the absolute magnitude of the cell mechanical force can be obtained.
  • Fourth embodiment a device for detecting cell mechanical force
  • the difference between this embodiment and the first to third embodiments is that, on the surface of the microcolumn 12, in addition to the area where the light reflecting layer 13 is provided, an anti-reflection layer 105 for light is provided.
  • an anti-reflection layer 105 for light is provided on the surface of the microcolumn 12, in addition to the area where the light reflecting layer 13 is provided.
  • the anti-reflection layer 105 is provided in the base to further enhance the signal-to-noise ratio.
  • the light reflecting layer 13 may be a layer of gold foil. In other embodiments, the light reflecting layer 13 may also be other metal layers or other reflective materials with light reflecting functions. The reflective effects brought by different materials, the difficulty of preparing the reflective layer, and the cost may vary. In actual operation, consideration and selection may be made based on specific conditions.
  • the cross-sectional shape of the microcolumn 12 is circular. In other embodiments, the cross-sectional shape of the microcolumn 12 can also be elliptical or polygonal. In various embodiments of the present invention, different cross-sectional shapes can achieve different purposes. For example, a circular cross-sectional shape has the characteristic of isotropy, that is, the mechanical properties of the microcolumn itself are insensitive to direction.
  • the cross-sectional shape is elliptical, it is anisotropic, that is, the mechanical properties of the microcolumn itself are sensitive to direction, which can control the sensitivity of different directions to the force field, and can regulate the tropism of cells to a certain extent (the geometric morphology of most cells is actually asymmetric.
  • the tropism of cells in the present invention refers to the morphological asymmetry, polarity or directionality exhibited by cells. For example, if an ellipse is used to fit the shape of the cell projection, the major axis of the ellipse can be considered as the direction of the cell).
  • the cross-sectional shape is elliptical, the cross-sectional shape has a major axis and a minor axis, it is much easier to push the microcolumn along the minor axis than along the major axis, and the deformation under relative force conditions is also large.
  • the cross-sectional shape if cells are planted on such micropillars, there is anisotropic mechanical interaction between the cells and the micropillars, which will cause the cells to grow along a certain side. When applied to fluids, it can be used to determine the direction of the fluid.
  • the dimensions of the microcolumn array are: column height 10nm ⁇ 500 ⁇ m, column spacing 10nm ⁇ 50 ⁇ m, column upper surface diameter 50nm ⁇ 50 ⁇ m. Microcolumns within this size range can meet the basic use conditions of microcolumns used as sensors, that is, at least they can be deformed and not fall over.
  • the regulation of different microcolumn array sizes can also achieve the following functions: For example, by regulating the aspect ratio AspectRatio of the microcolumn (which can be understood as the ratio of height to cross-sectional diameter/side length/major diameter at the microcolumn level), a certain microcolumn deformation performance regulation function can be achieved, thereby achieving better simulation of the organ tissue environment in the body (such as bone tissue and nerve tissue of different hardness).
  • AspectRatio of the microcolumn which can be understood as the ratio of height to cross-sectional diameter/side length/major diameter at the microcolumn level
  • a certain microcolumn deformation performance regulation function can be achieved, thereby achieving better simulation of the organ tissue environment in the body (such as bone tissue and nerve tissue of different hardness).
  • the overall size of the array, or the number of micropillars 12 on a certain area of the base 11, will also affect the ligand density, that is, the number of points on the surface that cells can find to adhere to. If the array of micropillars 12 is sparser, the adhesion points that cells can find are smaller, which will have a significant impact on cell behavior.
  • the cross-sectional area of the micro-pillar shape will also affect the cell adhesion behavior, because cells need a certain area to form focal adhesion. If it is a nano-micro-pillar, the cross-sectional area of the micro-pillar is small, which will affect the formation of focal adhesion.
  • micro-pillar array by combining the material's own characteristics and a certain size of micro-pillar array, we can achieve a cell support effect, chip stability, and measurement accuracy that better meets the requirements. By regulating the distribution of the micro-pillar array, we can also regulate and influence the cell attachment state to a certain extent.
  • the material of the micro-pillar 12 is polydimethylsiloxane (PDMS).
  • the material of the micro-pillar 12 can also be other polymer materials, such as silicon-based polymers, photoresistive polymer materials, conductive polymer materials, temperature-sensitive polymer materials, etc.
  • the main embodiment of the present invention mainly adopts polymer materials because the current polymer materials have a deformable property that is more suitable for the application of the present invention, but the present invention
  • the implementation of the invention does not require that the material of the microcolumn be limited to polymer materials, but should and can be extended to all materials with corresponding deformability, and the inventive concept of the present invention can be realized.
  • the material of the microcolumn must meet the conditions of having a certain force deformability, and in some embodiments, it needs to have a certain light transmittance. The latter is not a necessary condition for all embodiments.
  • the inventive concept of the present invention can also be realized.
  • the hardness (deformability) of the microcolumn 12 can be controlled according to actual needs through multiple technical dimensions such as size (mainly Aspect Ratio), selection of material type, control of the degree of cross-linking of polymer materials, chemical or physical surface treatment, etc.
  • 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 area of the microcolumn;
  • Figure 5c is an elemental characterization diagram of the side area of the microcolumn (excluding the top area).
  • the scanning electron microscope image of Figure 5 characterizes the material composition of the microcolumn, and it can be confirmed that the Au element exists at the top of the microcolumn and the Si element exists at the rest of the microcolumn.
  • a substance 106 having a cell adhesion function is provided on the top end surface of some micro-pillars 12 of the micro-pillar array.
  • This embodiment adopts collagen in the extracellular matrix molecule.
  • a combination of one or more of the extracellular matrix molecules including collagen, fibronectin, vitronectin, laminin and tropoelastin can also be used.
  • other types of substances having a cell adhesion function can also be provided on the top end surface of all or part of the micro-pillars of the micro-pillar 12 array, such as a simulated substance of the extracellular matrix, such as a polypeptide containing an RGD adhesion sequence; or a substance 106 having a cell adhesion promoting mechanism, including polylysine; or a substance that interacts with cell surface receptors.
  • Arranging such a substance 106 with cell adhesion on the top end surface of the micro-column 12 can effectively promote the attachment of cells to the micro-column 12, thereby achieving the regulation of cell attachment, proliferation, migration, state, differentiation, etc.
  • a substance with cell adhesion such as Fibronectin and other extracellular matrix proteins
  • these micro-columns can form a certain shape.
  • cells tend to adhere to micro-columns of specific positions and shapes, thereby performing high-throughput mechanical measurements under the condition of controlling cell size, shape and tropism characteristics.
  • the cell adhesion substance is beneficial to the stability of cells/multi-cell aggregates on the micro-columns.
  • Sixth embodiment a device for detecting cell mechanical force
  • the top end surface of some micro-pillars 12 of the micro-pillar array is provided with a substance 106 having a cell adhesion effect
  • the cylindrical surface (end surface or side surface) of the part of the micro-pillars 12 that is not provided with the substance having a cell adhesion effect on the top end surface is also provided with a substance having a cell adhesion inhibition effect, such as F-127.
  • the base is provided with a substance 107 having a cell adhesion inhibition effect.
  • the provision of the substance 107 having a cell adhesion inhibition effect makes cells more inclined to adhere to micro-pillars of a specific position and shape (on the top), thereby performing high-throughput mechanical measurements while controlling the size, shape and tropism characteristics of the cells, so that the cell mechanical force acts on the micro-pillars through the top of the micro-pillars.
  • Seventh embodiment a device for detecting cell mechanical force
  • the top end surface of the microcolumn 12 array is provided with a preset pattern of microcolumns containing substances with cell adhesion effects.
  • a cell adhesion molecule layer with a specific pattern can be printed by micron printing technology to promote the adhesion of cells in these areas.
  • the so-called preset pattern can be a triangle, quadrilateral, polygon, circle, ellipse and other shapes.
  • the functions of the preset pattern include: first, the contact between cells is controlled by the pattern composed of these substances with cell adhesion effects, so as to facilitate the realization of high-throughput data acquisition.
  • the dimensionality reduction effect in data processing can be achieved by unifying the cell shape, thereby reducing the difficulty of analysis.
  • the purpose of controlling the size, shape, tropism, differentiation state, etc. of the cell can be achieved by limiting the cell attachment area, and even by controlling the actin Actinfilament regulates the mechanical state of cells to meet the requirements of certain special technical scenarios.
  • the unprinted portions of the preset pattern may be treated with substances having a cell adhesion inhibitory effect, such as BSA (bovine serum albumin) or F127 (polymer nonionic surfactant), to inhibit cell adhesion in these areas, thereby achieving directional adhesion, control of cell morphology, or simulation of a specific cell microenvironment.
  • BSA bovine serum albumin
  • F127 polymer nonionic surfactant
  • the substance with cell adhesion effect is selected from fibronectin (Fibronectin, FN) as an exemplary illustration, but it is not intended to limit the embodiments of the present invention.
  • fibronectin Fibronectin, FN
  • Polydimethylsiloxane micro-stamps with protruding square and rectangular patterns on the surface are used respectively, and fibronectin is adhered to the surface of the micro-stamp.
  • the fibronectin in the protruding part of the stamp is transferred to the top of the metal reflective layer located at the top of the micro-column by micro-contact printing. Then, the micro-column is immersed in F-127 solution so that the part without fibronectin has the effect of inhibiting cell adhesion.
  • Figure 6 a is a fluorescent imaging image of cells adhering to a preset pattern formed by a group of micro-pillars with fibronectin on the top. It can be seen that the adhesion range of the cells is limited to the area with fibronectin.
  • Figure 6 b is a distribution diagram of the cell mechanical force calculated from the light reflection signal measured on the micro-pillar.
  • the substance with cell adhesion is selected from OKT3 antibody (i.e., a substance that interacts with cell surface receptors) or fibronectin (Fibronectin, FN) as an exemplary illustration, but it is not intended to limit the embodiments of the present invention.
  • OKT3 antibody i.e., a substance that interacts with cell surface receptors
  • fibronectin Fibronectin, FN
  • Figure 7 a is a schematic diagram of an experiment using OKT3 antibody as a substance with cell adhesion
  • the upper image of Figure 7 b is a fluorescent imaging image of cells adhering to the top of micro-columns with OKT3 antibodies and fibronectin on the top
  • the lower image of Figure 7 b is a distribution diagram of light reflection signals (reflecting the size of cell mechanical force) measured on the micro-columns
  • Figure 7 c is a mechanical size comparison diagram measured on the OKT3 antibody and fibronectin coated surfaces respectively
  • Figure 7 d is a diagram of dynamic changes in cell mechanics after T cells are planted on the OKT3 antibody surface (micro-column top).
  • the above experiment can be coated with OKT3 antibodies or fibronectin on the top of some micro-columns of the same or different cell force detection devices, and T cells are planted on the surface of the cell mechanical force detection device with cell adhesion substances.
  • a cell mechanical force detection device coated with a substance that interacts with cell surface receptors (such as OKT3 antibody) or fibronectin (FN) on the surface of the microcolumn can be used to monitor the mechanical force effect and interaction of the substance on the cell in real time.
  • the cell mechanical force detection device also includes a cell restriction mechanism, and the cell restriction mechanism includes one or more restriction surfaces 16, and the restriction surface 16 is a plane or curved surface that is perpendicular to the plane where the base 11 is located, connected to the base 11 or integrally formed with the base 11, and the height of the restriction surface 16 is higher than the microcolumns 12 and surrounds a preset number of microcolumns 12.
  • the function of the cell restriction mechanism provided in this embodiment is to isolate and detect single cells, that is, to avoid contact or adhesion between cells during detection, and to restrict cell morphology, thereby facilitating high-throughput testing.
  • the number of restriction surfaces 16 in the cell position limiting mechanism or the shape of the restriction surface 16 may be different.
  • the restriction surface 16 included in the cell position limiting mechanism may be a cylindrical surface, or three planes connected end to end to form a triangular cross-sectional shape and enclose a certain number of micro-columns, four planes that are perpendicular to each other and connected end to end to form a rectangular shape and enclose a certain number of micro-columns, N planes connected end to end to enclose an N-sided polygon, or a curved surface with a circular cross-section, etc.
  • the cross-sectional shape formed by the restriction surface 16 is a controllable closed shape, and its area (or the number of micro-columns that can be understood as being accommodated in its space) is also controllable.
  • the cell restriction mechanism can also appear in the following forms:
  • FIG. 8 is a schematic diagram of the structure of a cell mechanical force detection device having a cell restriction mechanism, in which the cell restriction mechanism and the base 11 are integrally formed, that is, the material forming the cell restriction mechanism has a certain There are several recessed spaces 15 , the wall of which is the limiting surface 16 , the depth of which is the height of the limiting surface 16 , the bottom of which is the base 11 , and each recessed space 15 has a plurality of micro-pillars 12 .
  • FIG. 9 is a structural schematic diagram b of a cell mechanical force detection device having a cell restriction mechanism.
  • the restriction surface 16 is a structure bonded to the base 11 .
  • the cell confinement mechanism in this embodiment is a silicon film.
  • FIG. 10 a is a physical picture of a cell mechanical force detection device using a silicon film as a cell restriction mechanism.
  • the silicon film is adhered to a base after being punched with a laser, and each hole is provided with a microcolumn, and the silicon film is used to restrict the morphology and migration of cells, while controlling the contact or adhesion between cells;
  • FIG. 10 b is a fluorescence microscope picture of a cell mechanical force detection device using a silicon film as a cell restriction mechanism under light reflection
  • FIG. 10 c is an enlarged picture of FIG. 10 b.
  • the size of each hole in the silicon film can be set to match the size of a single cell, suitable for single cell attachment, thereby limiting cell contact, cell morphology and its migration range.
  • Example 10 A Cell or/and Multicellular Aggregate Characterization System
  • a characterization system for cell/multicellular aggregate interaction comprising a cell mechanical force detection device 1, an optical signal generating device 2 and an optical signal detecting device 3 as described in the first or second embodiment; the optical signal generating device 2 and the optical signal detecting device 3 are both located below the base 11 in the cell mechanical force detection device 1, and the optical signal generating device 2 has a light source, and the light emitted by the light source is irradiated to the light reflecting layer 13 of the microcolumn 12 through an incident light path (successively passing through a light-transmissive base and a light-transmissive microcolumn body), and is reflected, and the reflected light enters the optical signal detecting device 3 through a reflection light path (successively passing through a light-transmissive microcolumn body and a light-transmissive base).
  • the optical signal detecting device 3 can obtain the reflected light signal before and after the microcolumn 12 contacts the cell.
  • the characterization system for cell/multicellular aggregate interaction also includes an optical signal analyzing device 4, which can obtain cell mechanical force information by comparing, analyzing and calculating the reflected light signal before and after the microcolumn 12 contacts the cell, including the size, direction, and changes in a certain time range of the cell mechanical force.
  • Example 11 A Cell or/and Multicellular Aggregate Characterization System
  • Figure 4 is a characterization system for cell/multicellular aggregate interactions related to the eleventh embodiment of the present invention, including the cell mechanical force detection device 1 described in the third embodiment, and also including an optical signal generating device 2 and an optical signal detecting device 3; the optical signal generating device 2 and the optical signal detecting device 3 are both located above the base 11 in the cell mechanical force detection device 1, and the optical signal generating device 2 has a light source.
  • the light emitted by the light source is irradiated to the light reflecting layer 13 through the incident light path and reflected.
  • the optical signal detecting device 3 can obtain the reflected light signal before and after the microcolumn 12 contacts the cell.
  • the optical signal detection device can be a microscope, a charge coupled device CCD, a complementary metal oxide semiconductor CMOS, a photomultiplier tube PMT and a photoelectric converter PT, a film, or other optical signal detection elements with the same function, and the present invention does not make specific restrictions.
  • the cell mechanical force detection device of the present invention when a microscope is used as an optical signal detection device, there is no need to set up an independent optical signal generating device, and the cell mechanical force detection device of the present invention can be directly placed on the stage of the microscope, and the light source of the microscope is used as the optical signal generating device, and the objective lens 101 of the microscope (a 5x objective lens is sufficient, without relying on a high-power optical objective lens) is used as the optical signal detection device; when other optical signal detection devices, such as a charge coupled device CCD, are used, an independent optical signal generating device needs to be set up.
  • the optical signal generating device can be an LED, a halogen lamp, a laser (for example, an infrared laser), or other light sources, or other devices having these light sources, and the present invention does not make specific restrictions.
  • FIG11 a fluorescence microscope image of the cell/multi-cell aggregate interaction characterization system of this embodiment for monitoring cell mechanical force.
  • cells for example, fibroblasts are used in this embodiment
  • the optical signal detection device for example, a microscope in this embodiment
  • the cell mechanical force information into an optical signal and form an image for visual observation, and can provide real-time feedback on the changes in cell mechanical force.
  • Example 12 A Cell or/and Multicellular Aggregate Characterization System
  • FIG. 4 is a characterization system for cell/multi-cell aggregate interaction related to the twelfth embodiment of the present invention, including the cell mechanical force detection device 1 described in the third embodiment, and also including an optical signal generating device 2, an optical signal detecting device 3 and an optical signal analyzing device 4.
  • the optical signal generating device 2 and the optical signal detecting device 3 are both located above the base 11 in the cell mechanical force detection device 1; the optical signal generating device 2 has a light source, and the light emitted by the light source is irradiated to the light reflecting layer 13 through the incident light path, and is reflected; the spectrometer 5 can be a semi-transparent and semi-reflective or other equivalent optical element, the main purpose of which is to simplify the design of the light path; the optical signal detecting device 3 can obtain the reflected light signal before and after the micro-column 12 contacts the cell; the optical signal analyzing device 4 can obtain the cell mechanical force information by comparing, analyzing and calculating the reflected light signal before and after the micro-column 12 contacts the cell, including the size, direction, and changes in a certain time range of the cell mechanical force.
  • the optical signal analysis device can be an optical image analysis software ImageJ, Matlab, Fluoview, Python, or other optical image analysis elements with the same function, or a combination of these analysis software, and the present invention does not impose any specific limitations.
  • Figure 12 a is a structural schematic diagram of the characterization system of cells/multicellular aggregates
  • Figure 12 b is an image of the light reflection signal of the cell mechanical force detection device obtained by the light signal detection device
  • Figure 12 c is a visualization effect diagram of the mechanical size and distribution.
  • a metal reflective layer is provided on the top of each microcolumn and an anti-reflective layer is provided on the side.
  • the optical signal detection device such as a CCD camera.
  • the cell force generated by the cell movement will cause the microcolumn to tilt, thereby reducing the reflected signal.
  • the cell force intensity can be calculated.
  • an optical signal detection device (such as a CCD camera) is used to collect an image of the light reflection signal of the cell mechanical force detection device and an amplified image of the local cell adhesion area (as shown in b in FIG. 12 ).
  • the image in b in FIG. 12 is further processed by an optical signal analysis device to convert it into a more intuitive visualization effect of the mechanical size and distribution (as shown in c in FIG. 12 ).
  • the specific processing process is as follows: first, based on b in Figure 12, a bright field reflection signal image (I, focused on the cells) is obtained; then, the high-frequency signal is filtered out by Fourier transforming the image, and an inverse Fourier transform operation is performed to calculate the microcolumn reflection signal image (I 0 ) in the unbiased state; then, the I and I 0 images are further processed to convert the reflection signal image into a more intuitive cell mechanics image (I 0 signal value minus I signal value) and then standardized to obtain a more intuitive cell mechanical force intensity image j.
  • Embodiments 1 to 9 of the present invention can also measure hardness simultaneously, by rotating the micro-pillars into cells under the action of external force to complete the hardness measurement of cells and/or multi-cell aggregates.
  • Example 13 Method for calculating mechanical force, relationship between mechanical force and light reflection signal
  • This embodiment combines the characterization system for cell/multicellular aggregate interactions described in any one of the tenth to twelfth embodiments or the method for detecting cell mechanical force described in the fourteenth embodiment to illustrate the method for calculating mechanical force in the embodiments of the present invention; and uses fluid as an external force to verify the relationship between mechanical and light reflection signals.
  • Figure 13 is a schematic diagram of the structure of the cell mechanical force detection device in the microfluidic environment before and after the fluid is turned on; b in Figure 13 and c in Figure 13 are comparison diagrams of the bright field microscope image of the microcolumn before and after the fluid is turned on, the distribution diagram of the reflected light signal, and the superposition effect diagram of the two; d in Figure 13 is a diagram of the intensity of the light reflection signal before and after the fluid is turned on; and e in Figure 13 is a diagram of the linear relationship between the light reflection signal and the microcolumn offset.
  • the effect diagram is the superposition of the microscope image and the reflected light signal distribution map.
  • the cell mechanical force detection device is integrated into the microfluidic channel.
  • the microcolumn is displaced and the angle of the reflective layer on the microcolumn surface is changed (a in Figure 13 - c in Figure 13).
  • the light reflection signal changes from strong to weak.
  • the displacement of the microcolumn is changed by the flow rate, and the displacement of the top of the microcolumn relative to the bottom of the microcolumn is photographed using a confocal microscope.
  • the mechanical force on each microcolumn can be calculated using the following formula:
  • F represents the mechanical force that causes the micropillar to deflect by an angle of ⁇
  • E represents Young's modulus
  • k bend represents the ideal spring constant of an isolated nanopillar
  • D represents the diameter of the micropillar
  • L represents the height of the micropillar.
  • the light reflection signal at the top of the microcolumn is recorded, and the light reflection signal and the microcolumn offset are plotted as e in Figure 13 to obtain the linear relationship diagram and linear range of the light reflection signal (reflecting the cell mechanical force) and the microcolumn offset.
  • Example 14 A method for detecting cell mechanical force
  • a method for detecting cell mechanical force comprises the following steps:
  • the light signal generating device 2 in the cell/multicellular aggregate interaction characterization system as described in any one of the tenth to twelfth embodiments emits light.
  • the optical signal detection device 3 in the characterization system of cell/multicellular aggregate interaction as described in any one of the tenth to twelfth embodiments is used to detect the light after being acted upon by the cell mechanical force detection device 1.
  • the optical signal detection device 3 can obtain the reflected light signal before and after the microcolumn 12 in the cell mechanical force detection device 1 comes into contact with the cell.
  • the optical signal analysis device 4 in the characterization system of cell/multicellular aggregate interaction obtains the cell mechanical force information by comparing, analyzing, and calculating the reflected light signal before and after the microcolumn 12 comes into contact with the cell, including the size, direction, and changes in the cell mechanical force within a certain time range, etc.
  • a and b in Figure 14 are schematic diagrams of the structure of the microcolumn of the cell mechanical force detection device before and after the contact with the cell; b in Figure 14 is the reflected light signal obtained by the optical signal detection device (CCD electronic photosensitive element).
  • the optical signal detection device CCD electronic photosensitive element
  • c in Figure 14 is a monitoring diagram of the cell migration process (after staining the cell membrane, using a fluorescent light source to excite, and using a CCD electronic photosensitive element to record the migration process);
  • d in Figure 14 is a distribution diagram of the reflected light signal during the cell migration process (using a CCD electronic photosensitive element to record the changes in the reflected light signal during the migration process). It can be seen from c in Figure 14 and d in Figure 14 that the reflected light signal is significantly attenuated in the part where the cell applies force.
  • D in Figure 14 shows the reflected light signal monitored in real time during the cell migration process, and the mechanical force during the migration process is fed back in real time through the reflected light signal. It can be seen that monitoring the reflected light signal during the cell migration process by the optical signal detection device can provide real-time feedback on the changes in the cell mechanical force during the cell migration process.
  • Example 15 Method for preparing a cell mechanical force detection device
  • a method for preparing a cell mechanical force detection device comprises the following steps: laying a light reflecting layer 13 on the top or upper half of a microcolumn 12 to obtain a microcolumn 12 having a reflecting layer on the top or upper half of a microcolumn 12.
  • Example 16 Method for preparing a cell mechanical force detection device
  • a method for preparing a cell mechanical force detection device comprises the following steps:
  • An anti-reflection layer is uniformly coated on the entire micro-column 12 ; the anti-reflection layer on the top or upper half of the cylinder is removed; and a light reflection layer 13 is laid on the top or upper half of the cylinder of the micro-column 12 .
  • Example 17 A method for preparing a cell mechanical force detection device
  • the present embodiment is different from the fifteenth and sixteenth embodiments in that the step of "laying a light reflecting layer 13 on the top or upper half of the microcolumn 12" is specifically to: uniformly sputtering a layer of reflective metal on the top or upper half of the microcolumn to obtain a microcolumn with a metal light reflecting layer on the top or upper half of the microcolumn.
  • Example 18 A method for cell identification (including visual qualitative identification, and accurate qualitative and quantitative identification)
  • This embodiment specifically provides a method for identifying cells by using the cell mechanical force information obtained by using the characterization system for cell/multicellular aggregate interactions described in any one of the tenth to twelfth embodiments or the cell mechanical force detection method described in the fourteenth embodiment.
  • Figure 15a is a fluorescence imaging image of a mixed system of healthy cells and lung non-small cell cancer cells
  • Figure 15b is a distribution diagram of light reflection signals of a cell mechanical force detection device obtained by an optical signal detection device
  • Figure 15c is a visualization effect diagram of mechanical magnitude and distribution
  • Figure 15d is an enlarged diagram of representative single-cell cell force distribution of healthy cells and lung non-small cell cancer cells in Figure 15c
  • Figure 15e is a comparison diagram of cell morphology of healthy cells and lung non-small cell cancer cells
  • Figure 15f is a comparison diagram of reflection signal strength of healthy cells, lung non-small cell cancer cells and mixtures of these two cells in different proportions
  • Figure 15g is a clustering analysis diagram obtained by processing structured cell information after structured processing of Figure 15c.
  • this embodiment uses healthy cells (Normal) and lung non-small cell cancer cell lines (Cancer) as detection objects, uses two different fluorescent dyes (Dil & DIO) to pre-stain the cell membranes of healthy cells and lung cancer cells, and then mixes them in a certain proportion and adds them to the same cell mechanical force detection device (in other embodiments, they can be added to different independent cell mechanical force detection devices).
  • healthy cells Normal
  • lung non-small cell cancer cell lines Cancer
  • an image of the light reflection signal of the cell mechanical force detection device is collected by an optical signal detection device (a microscope is used in this embodiment) (as shown in b in FIG. 15 ), and the high-resolution force field distribution in the two cells is directly rendered by the optical signal detection device and converted into a readable light intensity attenuation signal (reflecting the cell force intensity) and displayed in the image (as shown in c in FIG. 15 ).
  • the two cells can be intuitively distinguished (qualitative analysis) by naked eye observation.
  • the light reflection signal in c in Figure 15 is further processed by the optical signal analysis device.
  • the obtained cell force field in Figure 15c is collected by the optical signal analysis device (ImageJ and Python analysis software are used in this embodiment, and other image analysis software can also be used in other embodiments), including collecting cell mechanical force magnitude information at multiple points of each cell, thereby obtaining multi-point cell mechanical force magnitude data in multiple cells; pre-processing the obtained cell mechanical force magnitude information to form structured cell information; and obtaining a comparison result diagram of healthy cells and lung non-small cell cancer cells in cell morphology based on the structured cell information analysis (as shown in e in Figure 15).
  • the structured cell information includes the number of cells, the number of cell features and the feature information of each cell feature (such as the cell adhesion area and cell roundness in this embodiment).
  • the structured cell information can be regarded as a two-dimensional matrix of a feature matrix (Feature Matrix), where N is the number of cells and P is the number of cell features.
  • Feature Matrix feature matrix
  • N the number of cells
  • P the number of cell features.
  • a supervised machine pre-staining two cell lines with different cell membrane dyes (Dil & DIO) for comparison
  • the structured cell information of a large number of cells is used to train the cell feature model
  • a cluster analysis diagram as shown in g in Figure 15 is obtained, and then the obtained cell feature model is applied to the classification and identification of cells of unknown type or unknown state.
  • an optical signal analysis device (ImageJ and Python analysis software are used in this embodiment, and other cluster analysis software can also be used in other embodiments) can be used to cluster and type normal healthy cells and cancer cells, thereby realizing the identification of unknown cell types.
  • Figure 15e shows that there is no statistically significant difference in the morphology of different cells (including cell adhesion area and cell roundness);
  • Figure 15f shows the obvious difference in the reflection signal intensity (reflecting cell force) between normal cells and tumor cells, and that after normal cells and tumor cells are mixed together in a certain proportion, the reflection signal intensity and the mixing ratio have a certain linear relationship. It can be seen that compared with other cell characteristics (such as cell adhesion area, cell roundness, etc. in Figure 15e), The cell mechanical characteristics measured by the cell mechanical force detection device of the present invention can more intuitively and accurately identify the state and type of cells (quantitative and qualitative analysis).
  • tumor cells show higher mechanical force magnitude than normal cells, and the distribution is more uneven. It can be seen that after the cell mechanical force is visualized in an image manner, the force field characteristics of different cells can be intuitively seen by the naked eye to have obvious differences; and further, after the force field magnitude of each point of different cells is structured by image analysis software, the cell morphology information of e in FIG. 15 , the reflected signal intensity of f in FIG. 15 (reflecting cell force) and the cluster analysis diagram of g in FIG. 15 are obtained by comprehensive analysis.
  • the present invention can perform cluster typing and quantitative analysis on different cells (such as healthy cells and non-small cell lung cancer cells in this embodiment) through comprehensive analysis of the force field structured information of each point of the cell, thereby realizing accurate identification of cell types.
  • the cell mechanical force detection device based on the present invention can not only make intuitive distinctions by the naked eye for qualitative analysis, but also make more intuitive and accurate identification (quantitative and qualitative analysis) of the cell state and type based on the measured cell mechanical characteristics, and it has been confirmed that using the cell force field as a marker can better distinguish cell types.
  • the above-mentioned cell identification method is applicable to various factors, including the typing and identification of cells/multicellular aggregates before, during and after the external factors act on the cells/multicellular aggregates as described in the first embodiment.
  • Example 19 A method for detecting cell viability
  • This embodiment specifically provides cell physical information obtained by the cell/multicellular aggregate characterization system described in any one of the tenth to twelfth embodiments or the cell mechanical force detection method described in the fourteenth embodiment, which is applied to monitoring cell vitality.
  • Figure 16 a is a schematic diagram of the operation flow of the cell viability detection method
  • Figure 16 b is a comparison diagram of the cell viability obtained by the MTT method after A549 cells were treated with different doses of 5FU for 24 hours and the cell mechanical force obtained by the device or system or method of the present invention
  • Figure 16 c is a comparison diagram of the cell viability obtained by the MTT method after A549 cells were treated with different doses of 5FU for different times and the cell mechanical force obtained by the device or system or method of the present invention.
  • non-small cell lung cancer cells A549 were cultured on multiple cell mechanical force detection devices, and different doses of 5-fluorouracil (5-FU), a drug that inhibits cell proliferation, were added for treatment.
  • the cell mechanical force at different time points was monitored by the characterization system for cell/multicellular aggregate interactions described in any one of the tenth to twelfth examples or the cell mechanical force detection method described in the fourteenth example.
  • the cell proliferation and cytotoxicity at different time points were monitored by the CCK-8 kit.
  • the cell viability determined by the MTT assay was used as a control group to obtain the data in Figures 16b and 16c.
  • the cell viability measured by the MTT assay and the cell viability reflected by the cell mechanical force both tend to gradually decrease in a dose-dependent manner, that is, the cell mechanical force is positively correlated with the cell viability.
  • the mechanical force can reflect the reduction of cell viability with a greater reduction, thereby more intuitively evaluating cell viability.
  • the cell viability determined by the MTT method did not change significantly; however, by measuring the mechanical force, the reduction of cell mechanical force can be observed at an earlier time point before the MTT method detects the reduction of cell metabolic activity.
  • the direct detection of cell mechanical force by the cell mechanical force detection device in this embodiment is a highly sensitive and effective method for evaluating the activity of cell response to drugs.
  • Example 20 A characterization method based on the interaction between cells or/and multicellular aggregates
  • This embodiment provides a cell mechanical force detection device or characterization system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes to obtain cell physical information of cells/multi-cell aggregates; specifically, it includes the following steps:
  • Place the cells/multicellular aggregates on a cell mechanical force detection device add cell culture fluid to at least allow the cells/multicellular aggregates to contact the cell culture fluid, and culture them for more than half an hour. Continue to add cell culture fluid and culture until the cells/multicellular aggregates are completely attached to the micro-columns, and then measure and obtain the cell mechanical force of the cells/multicellular aggregates.
  • external stimulation is added to detect the cell/multicellular aggregate cell under external stimulation. Dynamic changes in mechanical forces;
  • external stimulation can be added before or during the detection of cell mechanical force.
  • Different cells/multicellular aggregates can be divided into: two or more different cells/multicellular aggregates, different states of a cell/multicellular aggregate formed at different times or under external stimuli, and two or more different regions in a cell/multicellular aggregate;
  • Two or more different cells/multicellular aggregates can be pathological cells/multicellular aggregates and normal cells/multicellular aggregates.
  • Example 21 A typing and identification method based on the interaction between cells or/and multicellular aggregates
  • This embodiment provides a cell mechanical force detection device or characterization system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes to obtain cell physical information of cells/multicellular aggregates; and to identify cells/multicellular aggregates before, during and after the interaction between cells and/or multicellular aggregates according to the cell physical information;
  • S1 obtains visualized cell information of cells/multicellular aggregates before, during and after the interaction between cells/multicellular aggregates through a cell mechanical force detection device, including visualized information such as the size and distribution of cell mechanical force changes;
  • S2 uses the visualization information for visualization and identification of cells and polymers to be detected.
  • the cell mechanical force detection device also includes a cell restriction mechanism, which includes one or more restriction surfaces, which are planes or curved surfaces that are perpendicular to the plane where the base is located, connected to the base or integrally formed with the base, and the height of the restriction surface is higher than the micro-pillars and surrounds a preset number of micro-pillars.
  • a cell restriction mechanism which includes one or more restriction surfaces, which are planes or curved surfaces that are perpendicular to the plane where the base is located, connected to the base or integrally formed with the base, and the height of the restriction surface is higher than the micro-pillars and surrounds a preset number of micro-pillars.
  • the first cell/multi-cell aggregate and the second cell/multi-cell aggregate that interact with each other can be restricted to a specific area to facilitate observation of the changes in their respective cell mechanical forces, and the first cell/multi-cell aggregate and the second cell/multi-cell aggregate have the opportunity to contact each other, which promotes their interaction, and the contact area is fixed, so that the first cell/multi-cell aggregate and the second cell/multi-cell aggregate can remain as two independent cell groups when interacting with each other, which is conducive to observation and subsequent data analysis and quantification.
  • the cell confinement mechanism is a silicon film, wherein a plurality of holes are provided in the silicon film, wherein micro-pillars are provided in the holes, and each hole accommodates more than one cell or more than one multi-cell aggregate.
  • a fixed number of cell groups can be cultured in the micro-wells in an orderly manner.
  • Example 21 Method for identifying cells or/and multicellular aggregates
  • This embodiment provides a cell mechanical force detection device or characterization system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes to obtain physical information of cells or/and multicellular aggregates, and to perform typing and identification of cells or/and multicellular aggregates according to the cell physical information;
  • the cell physical information is obtained based on at least one of the following circumstances:
  • S1 attaches cells/multicellular aggregates to microcolumns to measure cell physical information
  • S2 adds other cells/multicellular aggregates, substances or applies other actions, and after the action, obtains the cell information of the attached cells/multicellular aggregates, the cell information includes the cell physical information of a certain point in the cells/multicellular aggregates obtained by the cell mechanical force detection device, and the cell physical information includes the size of the cell mechanical force at the point, specifically: using an optical signal detection device (or in conjunction with an optical signal analysis device) to collect cell information of multiple cells on the cell mechanical force detection device, including collecting cell mechanical force size information of multiple points of each cell, thereby obtaining multi-point cell mechanical force size data in multiple cells;
  • the structured cell information includes The number of cells, the number of cell features and the feature information of each cell feature.
  • the structured cell information can be regarded as a two-dimensional feature matrix (Feature matrix), where N is the number of cells and P is the number of cell features.
  • Feature matrix two-dimensional feature matrix
  • N the number of cells
  • P the number of cell features.
  • P 1, that is, the cell feature is the size of the cell mechanical force
  • a cell feature model is established using supervised, unsupervised or semi-supervised machine learning, and the cell feature model is applied to cells and/or multicellular aggregates at different growth moments, as well as the typing and clustering of changing states under other factors, to further identify different typings.
  • the cell physical information also includes the direction of the cell mechanical force at that point. In some other embodiments, the cell physical information also includes the change in the size or direction of the cell mechanical force at that point within a certain time interval. In some other embodiments, the cell information also includes cell morphology information. In some other embodiments, the cell physical information is obtained by the method of the twentieth embodiment. In some other embodiments, the cell mechanical force detection device also includes a cell restriction mechanism, which is an interacting first cell/multi-cell aggregate, and the second cell/multi-cell aggregate remains independent, but can interact with each other.
  • the cell mechanical force detection device of the present invention can not only visually distinguish by naked eye for qualitative analysis, but also can more intuitively and accurately identify the state of cells/multicellular aggregates based on the measured cell mechanical characteristics (quantitative and qualitative analysis), and it has been confirmed that using cell force field as a marker can better distinguish types.
  • Example 23 A method for evaluating the interaction between cells or cell polymers based on cell mechanical forces
  • This embodiment provides a cell mechanical force detection device or characterization system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes to obtain cell or/and multicellular aggregate cell physical information, and to perform typing and identification of the interaction between cells and their multimers according to the cell physical information, wherein the method is:
  • S1 uses polydimethylsiloxane (PDMS) material and uses micromachining technology to make a thin film with a thickness of 5-10 microns, and creates multiple micropores with a diameter of about 200 microns on the film. After these PDMS microporous films are treated with Pluronic F127 solution and dried, they are precisely placed on the microcolumn array of the cell mechanical force detection device.
  • PDMS polydimethylsiloxane
  • S2 evenly distributes lung cancer cells on the above device so that each micropore with a diameter of 200 microns can accommodate about 20 tumor cells, thereby forming cell polymers. After one day of culture, the cells that failed to attach were washed away, and at this time, the cell mechanical force signals of the cell polymers in each micropore were recorded.
  • S3 adds mononuclear sphere THP-1 cells to start real-time monitoring of changes in mechanical force of cell polymers. This process not only promotes the orderly cultivation of a fixed number of cell groups in microwells, but also facilitates high-throughput monitoring of their mechanical force changes.
  • the design of the device of the present invention ensures that each cell polymer has the opportunity to contact another cell, and because the growth of cell polymers in microwells is restricted, the contact area with the chip is fixed, which greatly facilitates subsequent data analysis and quantification.
  • this microporous device is not limited to tumor cells, but is also suitable for the study of cell polymers (spheroids) or organoids, and can effectively observe the effects of various cells on cell polymers or organoids.
  • This method provides an efficient and precise experimental platform for the study of cell mechanical forces.
  • Example 24 A method for evaluating the effect of immune cells on tumor multicellular spheroids by cell mechanical force
  • This embodiment provides a cell mechanical force detection device or characterization system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes to obtain physical information of cells or/and multicellular aggregates, and then identify the interaction between immune cells and tumor multicellular spheroids.
  • the specific operation steps are as follows:
  • S1 uses polydimethylsiloxane (PDMS) material and uses micromachining technology to prepare a microporous structure film with a thickness of 5-10 microns and a diameter of each micropore of about 200 microns.
  • the PDMS microporous film is immersed in Pluronic F127 solution and laid on the microcolumn array of the cell mechanical force detection device after drying.
  • lung cancer tumor cells A549 were evenly distributed on the above device, and each microwell with a diameter of 200 microns contained about 20 tumor cells to form cell polymers. After one day of culture, the unattached cells were removed and the cell mechanical force signals of the cell polymers in each microwell were recorded.
  • S2 adds T cell Jurkat cells to the system and begins to monitor the changes in cellular mechanical force of tumor cell aggregates in real time.
  • This method not only enables a fixed number of cell groups to be cultured in a microwell in an orderly manner, but also facilitates high-throughput monitoring of changes in cell mechanical forces.
  • Through the device of the present invention it is ensured that each cell polymer has the opportunity to contact immune cells, thereby effectively monitoring the response of tumor cells to immune cells.
  • This example through carefully designed experimental steps, can not only orderly culture a fixed number of tumor cell polymers in a microporous structure, but also evaluate the effect of immune cells on tumor multicellular spheroids at the cellular level.
  • this example provides a novel and effective method for evaluating the killing effect of immune cells on tumor cells.
  • Example 25 A method for evaluating the effect of tumor cells on mesothelial cells by cell mechanical force
  • This embodiment provides a cell mechanical force detection device or characterization system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes to obtain physical information of cells or/and multicellular aggregates, which is obtained based on the effect of tumor cells on vascular endothelial cells, and thereby achieves characterization, typing identification and evaluation, and the specific steps are as follows:
  • S1 uses polydimethylsiloxane (PDMS) material with a thickness of 5-10 microns to prepare a structural film with micropores of about 200 microns in diameter.
  • PDMS microporous film is immersed in Pluronic F127 solution, dried and laid on the microcolumn array of the cell mechanical force detection device.
  • S2 evenly distributes the mesothelial cell line Met5A on the cell mechanical force detection device, and each microwell with a diameter of 200 microns accommodates about 20 endothelial cells to form cell polymers. After one day of culture, the unattached cells are removed and the cell mechanical force signals of the mesothelial cell polymers in each microwell are recorded.
  • S3 adds the ovariectomy cell line OVCAR3 to the system and starts to monitor the changes in the cell mechanical force of the mesothelial cells in real time.
  • This embodiment not only cultured a fixed number of mesothelial cells in the microwells in an orderly manner, but also monitored the changes in the cell mechanical force through high throughput to identify the interaction between tumor cells and mesothelial cells.
  • Example 26 A method for evaluating the effect of tumor cells on vascular endothelial cells by cell mechanical force
  • This embodiment provides a cell mechanical force detection device or characterization system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes to obtain physical information of cells or/and multicellular aggregates, which is obtained based on the effect of tumor cells on vascular endothelial cells, and thereby achieves characterization, typing identification and evaluation, and the specific steps are as follows:
  • S1 uses polydimethylsiloxane (PDMS) material with a thickness of 5-10 microns to prepare a structural film with micropores of about 200 microns in diameter.
  • PDMS microporous film is immersed in Pluronic F127 solution, dried and laid on the microcolumn array of the cell mechanical force detection device.
  • S2 evenly distributes HUVECs, a vascular endothelial cell line, on a cell mechanical force detection device, and each microwell with a diameter of 200 microns accommodates about 20 endothelial cells to form a cell polymer. After one day of culture, the unattached cells are removed, and the cell mechanical force signals of the vascular endothelial cell polymer in each microwell are recorded.
  • S3 adds lung cancer cell line A549 to the system and starts to monitor the changes in cell mechanical force of vascular endothelial cells in real time.
  • This embodiment not only cultivates a fixed number of vascular endothelial cells in a microwell in an orderly manner, but also monitors the changes in cell mechanical force through high throughput to identify the interaction between tumor cells and vascular endothelial cells.
  • Example 27 A method for evaluating the effect of sperm cells on egg cells by cell mechanical force
  • This embodiment aims to provide a method based on cell mechanical force detection, which is used to evaluate the effect of sperm cells on egg cells, thereby providing a new technical means in the field of reproductive biology research.
  • This method uses a cell mechanical force detection device or characterization system, as well as a cell mechanical force detection method to obtain cell mechanical force information of cells or multicellular aggregates, and identify the interaction between cells based on this.
  • the specific operation steps of this embodiment are as follows:
  • a structural film with a diameter of about 30 microns and a thickness of 5-10 microns was made of polydimethylsiloxane (PDMS) material.
  • PDMS polydimethylsiloxane
  • the PDMS microporous film was treated with Pluronic F127 solution and dried, and then laid on the cell mechanical force
  • the detection device is on a micropillar array.
  • mouse oocytes were evenly distributed on the above-mentioned cell mechanical force detection device, with each microwell with a diameter of 30 microns accommodating about one oocyte. After culturing these oocytes for two hours, the cells that failed to attach were removed, and then the culture was continued for six hours to one day.
  • mouse sperm cells are added to the system, the fertilization process is implemented, and the changes in the cell mechanical force of the egg cells are monitored in real time.
  • this method can accurately observe and analyze the effects of sperm cells on a single egg cell, thereby providing an effective technical path for studying the mechanical interaction between cells during the fertilization process.
  • the application of this method may also include but is not limited to the optimization of human assisted reproductive technology and the development of new drugs or treatment methods.
  • Example 28 A method for evaluating the interaction between cell polymers and other factors through cell mechanical force (only the size of cell mechanical force, part of the data has labels, and part of the data has no labels), comprising the following steps:
  • This step specifically includes: using the cell mechanical force detection device to collect information on the above-mentioned several types of cells, including collecting cell mechanical force size information at multiple points of each cell, thereby obtaining multi-point cell mechanical force size data in multiple cells;
  • the structured cell information includes the number of cells, the number of cell features and the feature information of each cell feature.
  • the structured cell information can be regarded as a two-dimensional matrix of M N ⁇ P feature matrix, where N is the number of cells and P is the number of cell features.
  • P 1, that is, the cell feature is: cell mechanical force;
  • optimization or improvement can be performed in the following manner: for a single cell, further information processing is performed on the multi-point cell mechanical force information obtained, for example, calculating: the average value of the cell mechanical force per unit area; the distribution of the cell mechanical force within the cell; and other dimensional information, which can be used as a new cell feature and added to the two-dimensional feature matrix described in step S2, that is, the content of P is expanded, and then subsequent machine learning is used to determine which feature can better distinguish cells with different degrees of drug resistance and non-resistant cells.
  • Embodiment 29 A method for evaluating cells or/and cell polymers by cell physical information ((the magnitude and direction of cell mechanical force, without label), comprising the following steps:
  • cell physical information wherein the cell physical information is the size and direction of the cell mechanical force at a certain point in the cell, and the cell hardness, obtained based on the cell mechanical force detection device, specifically comprising: using the cell mechanical force detection device (a nano-microcolumn sensor in this embodiment) to collect cell information from multiple cells, including collecting information on the size and direction of the cell mechanical force at multiple points of each cell, thereby obtaining the size and direction data of the cell mechanical force at multiple points in the multiple cells;
  • the cell mechanical force detection device a nano-microcolumn sensor in this embodiment
  • the structured cell information includes the number of cells, the number of cell features, and feature information of each cell feature.
  • step S2 in this embodiment processes the cell information as follows: Assume that a total of n points of cell mechanical force vector data (magnitude and direction) are obtained in a cell, and these points are: (i, ⁇ ⁇ 1, 2, ... n ⁇ ), corresponding to two two-dimensional coordinates respectively: as well as Where t 0 and t n correspond to the initial and displacement positions of the nanopillars, respectively. That is, the direction of the force at each coordinate point.
  • each coordinate point should also have a scalar information, that is, the magnitude of the force d. In this way, the cell axis direction and the center point coordinates can be estimated based on the existing data, and each cell can be organized into a vector of the same length based on this.
  • the center point can be calculated as:
  • the cell axis is calculated by finding the two points (x 1 , y 1 ) and (x 2 , y 2 ) that are farthest apart, and the cell axis is obtained by the following formula:
  • FIG. 17 is a schematic diagram of the scalar processing of displacement information of a certain point in the fourth embodiment of the present invention.
  • Each point in the figure represents a point, and the color depth of each point from light to dark represents the force from small to large.
  • each point can be further quantized: the angle between the displacement vector of each point and the cell axis is calculated as ⁇ .
  • optimization or improvement can be performed in the following manner: for a single cell, further information processing is performed on the multi-point cell mechanical force magnitude or cell mechanical force direction information obtained, for example, the following dimensional information is calculated: the average value of the cell mechanical force magnitude per unit area; the distribution of the cell mechanical force magnitude in the cell; the distribution of the cell mechanical force vector in the cell; and the like, which can be used as a new cell feature and added to the two-dimensional feature matrix described in step S2, that is, the content of P is expanded, and then the subsequent machine learning is used to calculate the cell mechanical force magnitude per unit area; the distribution of the cell mechanical force magnitude in the cell; the distribution of the cell mechanical force vector in the cell; and the like, which can be used as a new cell feature and added to the two-dimensional feature matrix described in step S2, that is, the content of P is expanded, and then the information is processed by subsequent machine learning. To learn which features can better distinguish cells of different types or states.
  • Embodiment 30 A method for evaluating cells or cell aggregates by cell mechanical force (the magnitude and direction of the cell mechanical force, with labels), comprising the following steps:
  • the structured cell information includes the number of cells, the number of cell features and feature information of each cell feature.
  • this embodiment uses the Random Forest (RF) algorithm to extract significant features and estimate model parameters, and then applies it to new cells to estimate the labels corresponding to the new cells, that is, applying the cell feature model to the classification of cells of unknown type or unknown state.
  • RF Random Forest
  • machine learning algorithms/ideas such as Support Vector Machine (SVM) or deep learning to complete the corresponding model establishment and training learning work.
  • Figures 18 and 19 are respectively Result Graph A and Result Graph B of the fifth embodiment of the present invention, which use the established cell feature model for the identification of unknown cells or unknown cell phenotypes.
  • Different rows in Figure A represent different cell types, and different columns represent different samples.
  • the black dots in the figure are the top 50 significant features extracted by the random forest algorithm, or they can be called significant points.
  • the point here refers to a certain position in a cell, and the cell physical information obtained from different positions is different.
  • Figure B shows the significant distinction effect of the top 50 significant features (significant points) on three different cell types.
  • the significant features learned based on labeled data can visualize the data dimensionality reduction. Subsequently, cells can also be classified and identified based on dimensionality reduction data through a clustering algorithm.
  • optimization or improvement can be performed in the following manner: for a single cell, further information processing is performed on the multi-point cell mechanical force magnitude or cell mechanical force direction information obtained, for example, the following dimensional information is calculated: the average value of the cell mechanical force magnitude per unit area; the distribution of the cell mechanical force magnitude within the cell; the distribution of the cell mechanical force vector within the cell, etc.
  • This can be used as a new cell feature and added to the two-dimensional feature matrix described in step S2, that is, the content of P is expanded, and then subsequent machine learning is used to determine which feature can better distinguish cells of different types or states.
  • Embodiment 31 A method for evaluating cells or cell polymers by cell physical information (cell mechanical force magnitude and direction, part of the data is labeled, part of the data is unlabeled), comprising the following steps:
  • the cell physical information is the size of the cell mechanical force at a certain point in the cell obtained based on the cell mechanical force detection device. Specifically, it includes: using the cell mechanical force detection device to collect information on the above-mentioned several types of cells, including collecting cell mechanical force size information at multiple points of each cell, thereby obtaining multi-point cell mechanical force size data in multiple cells;
  • the structured cell information includes the number of cells, the number of cell features and the feature information of each cell feature.
  • the structured cell information can be regarded as a two-dimensional matrix of M N ⁇ P feature matrix, where N is the number of cells and P is the number of cells.
  • the number of cell characteristics, where P 2, means the cell characteristics are: the size of the cell mechanical force, the direction of the cell mechanical force;
  • optimization or improvement can be performed in the following manner: for a single cell, further information processing is performed on the multi-point cell mechanical force magnitude or cell mechanical force direction information obtained, for example, calculating: the average value of the cell mechanical force magnitude per unit area; the distribution of the cell mechanical force magnitude within the cell; the distribution of the cell mechanical force vector within the cell; and other dimensional information, which can be used as a new cell feature and added to the two-dimensional feature matrix described in step S2, that is, the content of P is expanded, and then subsequent machine learning is used to determine which feature can better distinguish cells of different types or states.
  • Embodiment 32 A method for evaluating the interaction between cells or cell polymers by cell physical information (the instantaneous value of the cell mechanical force vector, the change of the cell mechanical force vector within a certain time interval, without label), comprising the following steps:
  • cell information is the instantaneous value of the cell mechanical force vector at a certain point in the cell acquired by the cell mechanical force detection device and the change of the cell mechanical force vector at the point within a certain time interval; specifically comprising: using the cell mechanical force detection device to collect cell information of multiple cells, including collecting information on the size and direction of the cell mechanical force at multiple points of each cell, thereby obtaining the size and direction data of the cell mechanical force at multiple points in the multiple cells;
  • the structured cell information includes the number of cells, the number of cell features and the feature information of each cell feature.
  • the structured cell information can be regarded as a two-dimensional matrix of M N ⁇ P feature matrix, where N is the number of cells and P is the number of cell features.
  • the mechanical data of a single cell obtained can actually be compared to an image (instantaneous value) or a video (changes in the time dimension).
  • the machine learning algorithms in the field of image and video data processing can be used for reference in subsequent machine learning.
  • the machine learning widely used in image recognition more precisely, the Convolutional Neural Network (CNN) in deep learning can be adopted to model and analyze the data.
  • CNN Convolutional Neural Network
  • Embodiment 33 A method for evaluating the interaction between cells or cell polymers by cell mechanical force (the instantaneous value of the cell mechanical force vector, the change of the cell mechanical force vector within a certain time interval, with labels), comprising the following steps:
  • the structured cell information includes the number of cells, the number of cell features, and feature information of each cell feature.
  • the structured cell information can be regarded as a two-dimensional matrix of M N ⁇ P feature matrix, where N is the number of cells, P is the number of cell characteristics.
  • this embodiment uses the Random Forest (RF) algorithm to extract significant features and estimate model parameters, and then applies it to new cells to estimate the labels corresponding to the new cells, i.e., the cell feature model is applied to the classification of cells of unknown type or unknown state.
  • RF Random Forest
  • machine learning algorithms/ideas such as Support Vector Machine (SVM) or deep learning to complete the corresponding model establishment and training learning work.
  • the mechanical data of a single cell obtained can actually be compared to an image (instantaneous value) or a video (multiple instantaneous values within a certain time dimension).
  • the machine learning algorithms in the field of image and video data processing can be used for reference in subsequent machine learning.
  • the machine learning widely used in image recognition more precisely, the Convolutional Neural Network (CNN) in deep learning can be adopted to model and analyze the data.
  • CNN Convolutional Neural Network
  • Embodiment 34 This embodiment provides a cell physical characterization device and system.
  • this embodiment provides a cell physical characterization device, which utilizes a light reflection layer, a magnetic material, or a magnetic metal light reflection layer to influence the strength of the light reflection signal to achieve measurement of multimodal biophysical information of cells.
  • the top of the microcolumn 12 has a coating of a magnetic metal (such as iron, cobalt, nickel, etc.) (in other embodiments, other magnetic materials can be used instead, and the magnetic material can be set on the side of the microcolumn or inside the column, as long as the microcolumn can generate magnetic force under a magnetic field), and the coating with a magnetic metal can serve as a light reflection layer 105.
  • a magnetic metal light reflection layer is set on the top of the microcolumn 12.
  • coating is used in this embodiment, which only means that the light reflecting layer 13 in this embodiment can be prepared by a coating process, but it does not limit the light reflecting layer 105 to be prepared by a coating process. For example, it can also be prepared by a sputtering or evaporation process.
  • the characterization system is composed of one of the above-mentioned characterization devices, an optical signal emitting device, an optical signal detecting device and a magnetic field emitting device.
  • the optical signal emitting device is used to emit a predetermined light
  • the optical signal detecting device is used to detect the light reflected from the light reflecting layer 13
  • the magnetic field emitting device is used to emit a magnetic field to generate a magnetic force with the magnetic metal.
  • the light emitted by the optical signal emitting device is irradiated to the light reflecting layer 13 through the incident light path, and the light reflected by the light reflecting layer 13 enters the optical signal detecting device through the reflected light path.
  • the "action" in this embodiment may be only the reflection effect of the light reflection layer set at any part of the top or side of the micro-column of the cell physical characterization device on the predetermined light, or it may be the reflection effect of the light reflection layer set at both the top and side of the micro-column on the predetermined light.
  • the magnetic metal light reflection layer set at the top of the micro-column is under the action of the magnetic field of a specific direction and a specific intensity emitted by the magnetic field emission device, and the micro-column tilts in one direction, penetrates into the cell to be characterized, deforms, pulls or swings, and the magnetic metal light reflection layer reflects the light during the deformation process of the micro-column. Therefore, the system of this embodiment can measure the mechanical force of the cell to be characterized alone, or can measure the hardness of the cell to be characterized alone, or can jointly measure the mechanical force and hardness of the cell to be characterized.
  • the two cell physical characterization devices provided in the present application are combined.
  • the pair is set up to form a double-sided structure, with the outer side being the base and the inner side enclosing a three-dimensional containing cavity (sandwich structure) for cells or multi-cell aggregates.
  • the volume or height of the three-dimensional containing cavity can be adjusted according to actual needs. For example, when the cells to be characterized are the two opposite sides of a single cell, the height of the three-dimensional containing cavity can be controlled between 5nm-2mm. When the cells to be characterized are living tissues, the height and volume can be adjusted to be larger accordingly, and the height can even reach 5cm, and the volume can reach 30cm3 .
  • Example 35 Using a Cell Mechanics Chip to Monitor Organoid Attachment and Evaluate Responses to Chemotherapy Drugs and Immune Cell Attacks
  • This embodiment provides an immune organoid chip, which monitors the changes in cell mechanical force of organoids on the chip to evaluate the response of organoids to chemotherapeutic drugs and immune cell attacks.
  • S1. Prepare the chip: Select a cell mechanical chip with a microcolumn structure, and apply a suitable extracellular matrix (ECM) on the top of the microcolumn to promote the attachment and growth of organoids. Use anti-adhesion treatment on the sides of the microcolumns and between the microcolumns.
  • ECM extracellular matrix
  • S2. Plant the organoids: Place the cultured organoids on the mechanical chip. Make sure that the organoids are in contact with the surface of the chip so that the organoids can attach to the chip. You can also add cells and corresponding extracellular matrix materials directly to the chip, directly culture the organoids and monitor the mechanical response and changes during the development of the organoids.
  • Monitor the attachment of organoids Use light reflection signals to monitor the attachment of organoids to the mechanical chip in real time and observe the changes in cell mechanical force.
  • Add chemotherapy drugs Add an appropriate amount of chemotherapy drugs to the organoid culture medium.
  • S5. Monitor the response of organoids to drugs: Continue to use light reflection signals and microcolumn deflection to monitor the changes in cell mechanical force and hardness of organoids under the action of drugs. Observe the reduction of organoid vitality under the action of drugs ( Figure 20) or add immune cells (NK cells or T cells) for co-culture to monitor the changes in organoid vitality.
  • Example 36 Characterizing Heterogeneous Tumor Spheroids and Screening for Drug-Resistant or Immune-Escape Individuals Using Cell Mechanics Chip
  • This embodiment provides an immune-organoid chip, which screens out individuals with drug resistance or immune escape by monitoring changes in cell mechanical forces on heterogeneous tumor spheroids.
  • S1. Prepare the chip: Select a cell mechanical chip with a microcolumn structure, and coat the top of the microcolumn with a suitable extracellular matrix (ECM) to promote the attachment and growth of tumor spheroids. Use anti-adhesion treatment on the sides of the microcolumns and between the microcolumns.
  • ECM extracellular matrix
  • S2. Cultivate heterogeneous tumor spheroids: Cultivate tumor spheroids of different origins or with different drug resistance characteristics in the laboratory, and use restrictive structures to constrain the size and shape of the spheroids ( Figure 22). Tumor spheroids can also be extracted and separated from patients.
  • Plant tumor spheroids Place the cultured heterogeneous tumor spheroids on the mechanical chip.
  • This example demonstrates how to use a cell mechanics chip to characterize heterogeneous tumor spheroids and screen for drug-resistant individuals. By monitoring changes in cell mechanical forces, important information can be provided for drug resistance research and personalized treatment.
  • This embodiment provides an immune-tumor chip, which monitors and studies the relationship between the mechanical properties of tumor cells and the interaction with immune cells, as well as the effect of drug intervention on this relationship.
  • S1. Prepare the chip: Select a cell mechanical chip with a microcolumn structure, and coat the top of the microcolumn with a suitable extracellular matrix (ECM) to promote the attachment and growth of tumor cells and immune cells. Use anti-adhesion treatment on the sides of the microcolumns and between the microcolumns.
  • Plant tumor cells and immune cells Plant tumor cells and immune cells (such as NK cells or T cells) on the mechanical chip separately to allow them to interact with each other.
  • This example demonstrates how to use cell mechanics chips to characterize immune-tumor cell interactions and the effects of drug intervention on this relationship.
  • the positive correlation between cell mechanical force and cell stiffness indicates the importance of characterizing these two properties simultaneously.
  • the cell mechanics chip referred to in the present invention may be the cell mechanical force retrieval device disclosed in the present invention, the cell/multicellular aggregate interaction characterization and identification system, or other cell mechanics chips that can combine light signal reflection through microcolumns.
  • the thirty-eighth embodiment is a method for evaluating the interaction between expressed proteins, polypeptides and cells/cell polymers by cell mechanical force.
  • This embodiment provides a cell mechanical force detection device or a cell/cell polymer characterization system or a cell mechanical force detection method described in any of the above embodiments to obtain cell mechanical force information of cells/multi-cell polymers; the interaction between substances and cells or/and multi-cell polymers is identified according to the cell mechanical force information: the mechanical force information of transfected cells is obtained to predict the transfection status of the transfected cells to be tested. According to the transfection status, optionally, in combination with microfluidics, high-throughput biological screening can be achieved.
  • This embodiment can be used to find that there are obvious differences in cell mechanical force and hardness characteristics between successful and unsuccessful cell transfection. For the first time, it is found that there are obvious differences in cell mechanical force and hardness characteristics between intracellular expression and non-expression of biologically active compounds (including proteins and polypeptides). According to these physical characteristics combined with artificial intelligence training recognition models, it is possible to quickly identify high-yield cells that are successfully transfected and express biologically active compounds without invasive labeling, and combine microfluidics to achieve high-throughput biological screening.
  • non-transfected cells When added to the culture system, non-transfected cells may not be killed because the drug concentration is too low or the cell density is too high. Rapidly dividing cells are more easily killed than slowly proliferating cells. Control cells (non-transfected) may not be killed until 5-7 days after adding antibiotics, and clones of transfected cells (resistant clones) need 10-14 days to form.
  • the purpose of transfection is to change the morphology or function of cells, such as affecting the cytoskeleton, cell adhesion or cell differentiation, etc., then the successfully transfected cells may show mechanical force patterns and sizes different from those of untransfected or untransfected cells12.
  • the purpose of transfection is to change the gene expression or protein level of cells without directly affecting the cell morphology or function, then there may be no obvious difference between successfully and unsuccessfully transfected cells.
  • the method of transfection is to use viral vectors or other physical means instead of chemical reagents such as liposomes, then the transfection process itself may cause a certain degree of damage or stress response to the cells, thereby affecting the mechanical force of the cells.
  • the present invention is the first to discover that the mechanical force of cells that are successfully transfected and those that are not successfully transfected has obvious changes.
  • the system of the present invention has real-time characterization and fast speed, and can monitor the cell status in real time, as well as the potential cytotoxicity during the experiment, so as to optimize the transfection scheme in time.
  • Example 39 A method and application for characterizing, classifying and identifying interactions between expressed fat and cells/cell polymers based on cell mechanical forces
  • This embodiment provides a cell mechanical force detection device or a cell/cell polymer characterization system or a cell mechanical force detection method described in any of the above embodiments to obtain cell physical information of cells/multi-cell polymers; and to identify the interaction between fat and cells or/and multi-cell polymers according to the cell physical information:
  • Adipocytes are the largest connective tissue cells in the human body, and their main function is to store and mobilize lipids. Adipocytes can be divided into two categories: white adipocytes and brown adipocytes, which are very different in morphology, function and source.
  • White adipocytes are single-bubble shaped, that is, a white adipocyte contains a large triglyceride-rich lipid droplet, which occupies 90% of the cell volume, squeezing other components and nuclei to the edge.
  • White adipose tissue is mainly responsible for storing energy and releasing free fatty acids for use by other tissues when needed.
  • White adipose tissue can also secrete a variety of hormones and factors, such as leptin, angiotensin, vascular endothelial growth factor, etc., to regulate physiological processes such as blood pressure, appetite, and glucose metabolism.
  • Brown fat cells are multivesicular, that is, a brown fat cell contains many small triglyceride-rich lipid droplets and highly condensed mitochondria, which make them appear brown.
  • Brown adipose tissue is mainly responsible for generating heat and consumes excess energy when it is cold or overeating.
  • Brown adipose tissue can also secrete some hormones and factors that are different from or opposite to white, such as hepcidin, neuron guidance factors, etc., to regulate physiological processes such as iron metabolism and neurogenesis.
  • hepcidin hepcidin
  • neuron guidance factors etc.
  • For different types of fat cells they each play a normal and important role in a healthy state; but in an unhealthy state, such as overnutrition or malnutrition, they may undergo some abnormal changes or transformations and affect human health. For example, when overnourished, white adipose tissue will increase in number and size, and lead to metabolic disorders, diabetes, cardiovascular diseases, etc.; while brown adipose tissue will reduce
  • the cell mechanical force detection device of the present invention can be used to monitor the cell mechanical force in the process of adipocyte differentiation, and there are obvious dynamic changes, and it can monitor the conversion process of white fat, beige fat and brown fat in real time.
  • White adipocytes and brown adipocytes have obvious differences in morphology and function, which is also reflected in their cell mechanical force. In general, white adipocytes are harder than brown adipocytes, but the mechanical force generated is smaller.
  • Rho/ROCK pathway can regulate the process of fat precursor cells differentiating into white or brown fat.
  • some signal pathways such as Rho/ROCK pathway can regulate the process of fat precursor cells differentiating into white or brown fat.
  • some drugs such as tea polyphenols (epigallocatechin gallate) can inhibit white fat differentiation or promote brown fat differentiation by affecting the Rho/ROCK pathway or other signal pathways, and these effects can also be observed by mechanical force microscopy. This embodiment can effectively study the differences in morphology, function and metabolism of different types of fat cells, and can screen out some drug candidates that are beneficial for preventing and treating obesity and related diseases.
  • Embodiment 40 A method for evaluating the interaction between other substances and cells/cell polymers by cell mechanical force
  • This embodiment provides a cell mechanical force detection device or a cell/cell multimer characterization system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes to obtain cell physical information of cells/multicellular aggregates; and to evaluate the interaction between a substance and a cell or/and multicellular aggregates according to the cell physical information:
  • the structure can be used for machine learning.
  • the effects of genetic engineering (such as transfection) on cells can be monitored, small clones or single cells near large clones can be detected, and the monoclonal separation of target clones can be ensured.
  • the structural and morphological parameters (e.g., spheres and shapes) of the clones can be combined to define and exclude suspicious (e.g., elongated) clones.
  • the system in the application of synthetic biology, can help determine the minimum effective concentration for killing non-resistant cells by monitoring the vitality and state of the cells. At the same time, during the drug screening process, cells are monitored in real time to adjust the experimental scheme in time.
  • the state and dynamic changes of multicellular aggregates in addition to single cells, the state and dynamic changes of multicellular aggregates (including tumor spheroids, organoids, living tissues, etc.) can also be monitored in real time, with high throughput and low cost.
  • the type, state, behavior and differentiation direction of single or multi-cell aggregates are further judged or predicted according to the mechanical characteristics and change laws of different types combined with artificial intelligence training recognition models.
  • the present invention is applicable to the fields of synthetic biology, diagnosis, drug discovery, early screening of tumors, cell therapy and precision medicine.
  • it is determined whether the measured cells grow into polymers in the culture process as a single or aggregated form; the characterization and identification system and method of the present invention have real-time characterization and fast speed, and can monitor the cell state in real time, as well as the potential cytotoxicity during the experiment, and timely optimize the transfection scheme; in some specific embodiments, it can be used for the establishment of high-yield stable cell lines, which is crucial for the production of large-scale recombinant proteins and antibody drugs.
  • the present invention establishes a dose-response curve (dose-response curve or kill curve) to determine the minimum effective concentration for killing non-resistant cells.
  • dose-response curve dose-response curve or kill curve
  • it can be applied to flow cytometry: fluorescently labeled antibodies or fluorescent probes can be used to mark the expression of the target protein in the cell/cell polymer, and then the cells are analyzed and sorted using a flow cytometer.
  • drug development usually relies on high-throughput cell-based screening of large compound libraries.
  • characterization system, identification system and method of the present invention demonstrate an on-chip platform that combines solution-based compound library synthesis with high-throughput biological screening (chemBIOS).
  • the inventors discovered for the first time that there are significant differences in the mechanical force characteristics of cells that express and do not express biologically active compounds (including proteins and peptides) within cells, and that the screening and separation of high-expressing clones can be achieved through the mechanical force characteristics of cells; in some specific embodiments, in the process of studying the interaction between cells and macromolecules, it was discovered for the first time that the cell force characterization method is more sensitive than the traditional gene or proteomics characterization method, and can detect cell changes faster and more sensitively. In some specific embodiments, in addition to single cells, it can also be used to monitor the state and dynamic changes of multicellular aggregates (including tumor spheroids, organoids, living tissues, etc.) in real time, with high throughput and low cost.
  • multicellular aggregates including tumor spheroids, organoids, living tissues, etc.
  • in synthetic biology applications Refers to the use of genetic engineering or other means to transform or create biological systems with specific functions, such as the efficient synthesis of certain metabolites or drugs.
  • synthetic biology applications it is usually necessary to introduce the target gene into the host cell by transfection, transformation or other methods, and screen out the high-expressing cell strains to improve production efficiency.
  • the principle of using cell mechanical force characterization to identify and sort high-expressing cell strains is that the expression of the target gene may affect the morphology or function of the cell, thereby changing the interaction force between the cell and the matrix.
  • the target gene encodes a protein that can change the cytoskeleton, adhesion or differentiation state
  • cells with high expression of the gene may be significantly different from low-expressing or non-transfected cells in mechanical force patterns and sizes.
  • mechanical force microscopy to identify and sort high expression
  • other methods such as fluorescence detection, enzyme-linked immunosorbent assay, etc. can be combined to verify the results, further improving the accuracy of the obtained cell physical information and the accuracy of the prediction.
  • This embodiment provides a cell mechanical force detection device or a cell/cell polymer characterization system described in any of the above embodiments or a cell mechanical force detection method described in any of the above schemes to obtain cell physical information of cells/multicellular polymers; and to identify the interaction between macromolecules (such as proteins, sugar molecules, lipids) or microorganisms and cells or/and multicellular polymers according to the cell physical information:
  • the effects of different extracellular matrices on cell mechanical force are compared, and the steps are as follows: S1. Different extracellular matrices, such as collagen, fibronectin and laminin, are respectively covered on the top of the microcolumns of the cell mechanical force detection device, or the extracellular matrices are printed on the top of the microcolumns in a special pattern by microcontact printing; and Pluronic F127 is used for anti-adhesion treatment on the sides of the microcolumns and between the microcolumns; S2. Lung cancer A549 cells are cultured separately to detect the cell mechanical force of different extracellular matrix coatings; S3. Cell mechanics are monitored in real time, and the strength and distribution of cell mechanical force of cells on different extracellular matrix coatings are compared.
  • Different extracellular matrices such as collagen, fibronectin and laminin
  • the method for detecting the effect of an antibody on cell mechanical force comprises the following steps:
  • a method for detecting the effect of sugar molecules on cell mechanical force (glycoprotein or glycolipid). S1.
  • the top of the microcolumn of the cell mechanical force detection device is covered with Lipopolysaccharides (LPS); and the sides of the microcolumns and between the microcolumns are treated with Pluronic F127 for anti-adhesion; S2.
  • LPS Lipopolysaccharides
  • Pluronic F127 for anti-adhesion
  • THP1-ASC-GFP cell lines are added, LPS will attract cells to contact the chip, and this monocyte cell line will express green fluorescent protein when activated by LPS; S3. Real-time monitoring of cell mechanical changes and green fluorescent protein expression.
  • a method for detecting the effect of a protein on cellular mechanical forces In some embodiments, a method for detecting the effect of a protein on cellular mechanical forces.
  • the top of the microcolumn of the cell mechanical force detection device is covered with zymosan; while the sides of the microcolumns and between the microcolumns are treated with Pluronic F127 for anti-adhesion; S2. THP1-ASC-GFP cell lines are added, LPS will attract cells to contact the chip, and this monocyte cell line will express green fluorescent protein when activated by LPS; S3. Real-time monitoring of cell mechanical changes and the expression of green fluorescent protein.
  • the top of the microcolumn of the cell mechanical force detection device is covered with bacteria treated with paraformaldehyde; the sides of the microcolumns and between the microcolumns are treated with Pluronic F127 for anti-adhesion; S2. THP1-ASC-GFP cell lines are added, LPS will attract cells to contact the chip, and this monocyte cell line will express green fluorescent protein when activated by LPS; S3. Real-time monitoring of cell mechanical changes and the expression of green fluorescent protein.
  • Example 42 Method for measuring the interaction between immune cells and molecules and the cell activation process by characterizing the mechanical force and hardness of the cells
  • This embodiment provides a method for evaluating the interaction between immune cells and molecules (such as CD3 antibodies) and the cell activation process by measuring the changes in mechanical force and hardness of immune cells (such as T cells).
  • immune cells and molecules such as CD3 antibodies
  • the expression of green fluorescent protein is used as a marker of cell activation and cross-validated with the measurement results of cell mechanical force and hardness.
  • S1 Prepare a cell mechanical force detection device with the top of the microcolumn covered with CD3 antibody; and use Pluronic F127 for anti-adhesion treatment on the sides and between the microcolumns.
  • S2. Add NFAT reporter (eGFP) Jurkat recombinant cell line to the chip. CD3 antibody will attract T cells to contact the chip, and the T cell line will express green fluorescent protein when activated by CD3 antibody.
  • S3. Use the characterization system to monitor the mechanical changes of cells and the expression of green fluorescent protein. By analyzing The changes in the mechanical force of cells at different time points can be used to study the interaction between immune cells and molecules and the cell activation process.
  • S4. Use the characterization system to monitor the mechanical changes of cells and the expression of green fluorescent protein. By analyzing The changes in the mechanical force of cells at different time points can be used to study the interaction between immune cells and molecules and the cell activation process.
  • Example 43 Method for Identifying Activated T Cells and Inactive T Cells by Measuring Cell Mechanical Force and Hardness and Obtaining Their Activation Ratio
  • This embodiment provides a method for identifying activated T cells and unactivated T cells by measuring cell mechanical force and hardness, and obtaining their activation ratio. This method can be used to characterize cell therapy samples and predict the success probability of cell therapy.
  • S1. Culture the T cell line NFAT reporter (eGFP) Jurkat cells on a cell mechanical force detection device, control the amount of culture fluid, make the T cells contact the biological state and stress characterization device, and measure the mechanical force of unactivated cells.
  • S2. Add CD3 antibodies, CD28 antibodies and cytokines to the culture fluid to activate T cells; when T cells are activated by antibodies, they will express green fluorescent protein.
  • S3. Monitor the mechanical force changes and green fluorescent protein expression of each T cell in real time.
  • a pressure transmitter to pierce the microcolumn into the cell, add a magnetic field and characterize the hardness of the cell by detecting the light reflection signal.
  • S5. It is found that when T cells are activated, the cell mechanical force will gradually increase, which is positively correlated with the green fluorescence.
  • S6. Input the cell mechanical force changes and hardness changes of each T cell activation process into the database, and use machine learning methods to establish a model that can use the cell mechanical force and hardness characteristics, spatial distribution and temporal dynamic changes to determine the degree of T cell activation.
  • S7. Use CD4 and CD8 antibodies to separate T cells from the donor's peripheral blood mononuclear cells (PBMC).
  • PBMC peripheral blood mononuclear cells
  • Example 44 Technology for using microfluidics and cell mechanical force detection devices to monitor in vitro culture of CAR-T cell therapy
  • This embodiment provides a technology for using microfluidics and cell mechanical force detection devices to monitor in vitro culture of CAR-T cell therapy, so as to more effectively monitor and evaluate the growth, activation and efficacy of CAR-T cells in an in vitro environment.
  • S1. The top of the microcolumn of the biological state and stress characterization device chip is covered with CD3 and CD28 antibodies; while the sides of the microcolumns and between the microcolumns are treated with Pluronic F127 for anti-adhesion.
  • S2. Lay the chip on the bottom of the microfluidic device.
  • S3. Inject T cells separated from the donor's peripheral blood mononuclear cells (PBMCs) into the microfluidic device and activate the T cells.
  • PBMCs peripheral blood mononuclear cells
  • T cells determine whether all T cells have been fully activated by monitoring cell mechanical force.
  • S4. After the T cells are fully activated, add lentivirus for transduction, so that the T cells express chimeric antigen receptors with antibody-specific sequences (sc-fv) that can recognize cancer cell surface proteins.
  • S5. Take out the transduced T cells (CAR-T) from the microfluidics and continue to culture and amplify.
  • S6. Lay the PDMS microporous film (microwell) on the cell mechanical force detection device, and culture tumor cells, tumor multicellular spheroids or tumor organoids on the cell mechanical force detection device containing microwells, and the cells will grow in the microwells in an orderly manner.
  • CAR-T cells to the cell mechanical force detection device containing tumor cells to monitor the cell mechanical force of tumor cells in real time.
  • CAR-T cells can effectively kill tumor cells, the cell mechanical force of tumor cells will drop significantly.
  • the cell mechanical properties of CAR-T cells in the process of activating, amplifying and killing tumor cells can be more effectively monitored and evaluated in an in vitro environment, thereby providing more accurate data support for CAR-T cell therapy.
  • Example 45 Technology for using microfluidics and cell mechanical force detection devices to monitor in vitro culture of CAR-T cell therapy
  • This embodiment provides a technology for using microfluidics and cell mechanical force detection devices to monitor in vitro culture of CAR-T cell therapy, so as to more effectively monitor and evaluate the growth, activation and efficacy of CAR-T cells in an in vitro environment.
  • S1. The top of the microcolumn of the characterization device is covered with CD3 and CD28 antibodies; and the sides of the microcolumns and between the microcolumns are treated with Pluronic F127 for anti-adhesion.
  • S2. The biological state and stress characterization device are laid on the bottom of the microfluidic device.
  • T cells isolated from the peripheral blood mononuclear cells (PBMCs) of the donor are injected into the microfluidic device and the T cells are activated.
  • PBMCs peripheral blood mononuclear cells
  • the cell mechanical force is monitored to determine whether all T cells have been fully activated.
  • S4 the T cell receptors (TCR) of the T cells are transformed to be able to express and recognize cancer cell antigens using CRISPR-Cas9 technology.
  • S5. The modified TCR-T cells are removed from the microfluidics and continue to be cultured and amplified.
  • S6 Lay the PDMS microporous film (microwell) on the cell mechanical force detection device, and culture tumor cells, tumor multicellular spheroids or tumor organoids on the cell mechanical force detection device containing microwells. The cells will grow in the microwells in an orderly manner.
  • S7 the T cell receptors of the T cells are transformed to be able to express and recognize cancer cell antigens using CRISPR-Cas9 technology.
  • TCR-T cells to the cell mechanical force detection device containing tumor cells to monitor the cell mechanical force of tumor cells in real time.
  • TCR-T cells can effectively kill tumor cells.
  • the cell mechanical properties of TCR-T cells in the process of activating, amplifying and killing tumor cells can be more effectively monitored and evaluated in an in vitro environment, thereby providing more accurate data support for TCR-T cell therapy.
  • the forty-sixth embodiment uses a characterization system to monitor changes in cell mechanical force to determine the effect of an antibody-drug conjugate in treating suspended cancer.
  • This embodiment provides a method for using a characterization system to monitor changes in cell mechanical force to determine the effect of an antibody-drug conjugate in treating suspended cancer.
  • S1. The antibody-drug conjugate is covered on the top of the microcolumn of the characterization system, and Pluronic F127 is used for anti-adhesion treatment on the sides and between the microcolumns.
  • S2. Blood cancer cells are cultured on this device, and the antibody coating can attract blood cancer to the device and contact the device.
  • the cell mechanical force of blood cancer cells is monitored in real time by detecting the strength of the light reflection signal; when the antibody-drug conjugate can effectively inhibit cell growth or allow cells to enter apoptosis, the cell mechanical force will be greatly reduced.
  • a characterization system to monitor changes in cell mechanical force, the therapeutic effect of the antibody-drug conjugate on suspended cancer can be better understood.
  • Real-time monitoring of cell mechanical force helps to better evaluate the efficacy of the antibody-drug conjugate, thereby optimizing drug design and treatment plans.
  • the forty-seventh embodiment uses a characterization system to monitor changes in cell mechanical force and hardness to determine the effect of an antibody-drug complex in treating adherent cancer.
  • This embodiment provides a method for evaluating the therapeutic effect of an antibody-drug complex on adherent cancer by monitoring changes in cell mechanical force and hardness.
  • S1. Cover the top of the microcolumn of the characterization system with an extracellular matrix, and use Pluronic F127 to treat the sides, spaces between microcolumns, and bases of the microcolumns for anti-adhesion treatment.
  • S2. Culture lung cancer cells on the characterization system, and after one day of culture, allow the cells to completely adhere to the device.
  • S3. Add the antibody-drug complex to the culture medium.
  • Example 48 Using monitoring of cell mechanical force changes in living tissue to determine the therapeutic effect of antibody-drug complexes
  • This embodiment aims to provide a method for evaluating the therapeutic effect of antibody-drug complexes on tumor cells by monitoring the changes in mechanical force of living tissue cells.
  • S1. The top of the microcolumn of the characterization system is covered with extracellular matrix, and the sides and between the microcolumns are treated with Pluronic F127 for anti-adhesion.
  • S2. Fresh tumor tissue is cut into slices with a thickness of 200 microns using a tissue slicer.
  • the living tissue slices are laid on the cell mechanical force detection device, and after one day of culture, the tissue is completely attached to the chip. It is known that the cell mechanical force of the tumor cell block is stronger than that of the non-tumor block.
  • S4. The antibody-drug complex is added to the culture medium.
  • the cell mechanical force of the tumor cell block and the non-tumor cell block is monitored in real time.
  • the antibody-drug complex effectively inhibits cell growth or causes cells to enter apoptosis, the cell mechanical force will be significantly reduced. S6.
  • the antibody-drug complex can specifically kill tumor cells. And evaluate the impact on normal cells. This example provides an important basis for evaluating the therapeutic effect of antibody-drug complexes on tumor cells by monitoring the changes in cell mechanical force of living tissues.
  • Example 49 Using monitoring of cell mechanics changes in multicellular spheroids to determine the therapeutic effect of antibody-drug complexes
  • This embodiment aims to provide a method for determining the therapeutic effect of an antibody-drug complex by monitoring the cell mechanical changes of a multicellular spheroid.
  • S1. Prepare a characterization system, wherein the top of the microcolumn has an extracellular matrix, and the sides of the microcolumns and between the microcolumns are treated with Pluronic F127 for anti-adhesion.
  • S2. Tumor cells are formed into multicellular spheroids and cultured on this chip. After one day of culture, the multicellular spheroids are completely attached to the chip. Add an antibody-drug complex to the culture medium.
  • S3. Use a method to detect the strength of the light reflection signal to monitor the cell mechanical changes of the multicellular spheroid in real time. When the antibody-drug complex can effectively inhibit cell growth or cause cells to enter apoptosis, the cell mechanical force of the multicellular spheroid will be greatly reduced.
  • Example 50 Determining the targeting of antibody drug complexes by comparing changes in cell mechanical forces of tumor cells and non-tumor cells simultaneously
  • This embodiment aims to provide a method for determining the targeting of an antibody-drug complex by monitoring cell mechanical force.
  • the top of the microcolumn of the cell mechanical force detection device has an extracellular matrix, and the sides and between the microcolumns are treated with Pluronic F127 for anti-adhesion.
  • S2. Tumor cells with red fluorescence and non-tumor cells with green fluorescence are mixed in equal proportions and cultured on this cell mechanical force detection device. After one day of culture, the cells are completely attached to the chip. Add the antibody-drug complex to the culture medium.
  • This embodiment provides an in vitro organ chip, which includes providing the cell mechanical force detection device or detection system described in any of the above embodiments, and also includes: an electrode device, the micro-column is made of conductive material, and the electrode device acts on the micro-column to achieve electrical stimulation of the organ or cell.
  • organ-related cells and tissues can be planted on the micro-column, and the cell mechanical force of the cells and tissues can cause the micro-column to deform and convert it into an optical signal; wherein the micro-column is set with corresponding hardness and length according to the organ, so that the microenvironment of the chip is suitable for the real structural environment of the organ.
  • the hardness of the microcolumn is controlled by adjusting the length of the microcolumn and the cross-linking ratio to simulate the hardness of the corresponding tissue or simulate the microenvironment under pathological conditions (such as cardiac fibrosis); in some specific embodiments, in order to simulate the microenvironment more realistically, the microcolumn surface is provided with ECM; in some specific embodiments, in order to simulate the microenvironment more realistically, the mixture of the organ-related cells or/and tissues and ECM is planted on the microcolumn; in some specific embodiments, in order to simulate the microenvironment more realistically, the microcolumn surface has a directional ECM layer, for example, it can simulate the cardiac ECM microstructure and guide the tropism of myocardial cells; in some specific embodiments, the planting method includes: 3D printing; in some specific embodiments, if the organ is the heart, the cells include one or more combinations of myocardial cells, smooth muscle cells, vascular endothelial cells, fibroblasts, stem cells, and immune
  • the top of the microcolumn can be coated with de-heart-related cell ECM, artificially recombined cardiac ECM, or the cells can be coated in a gel containing cardiac ECM to simulate the extracellular matrix components of the heart.
  • a mechanical simulation device which is a mechanical stretching device for stretching the chip body; or an inflatable and deformable flexible film arranged at the bottom of the microcolumn; the upper end of the flexible film is connected to the microcolumn, and the lower end is connected to the base, or the base is a flexible film.
  • it also includes a microfluidic device, which applies flow field stimulation to the organ-related cells and organ tissues.
  • drugs, mechanical force, biochemistry, electric field and flow field stimulation, or a combination of more than one stimulation can be applied to the recognition of the state of each cell and organ in the external stimulation.
  • Embodiment 52 A method for establishing an in vitro organ and cell model with an in vitro organ chip, and characterizing cells and organ tissues: S1: collecting microenvironmental parameters of the corresponding organ tissues including physiological and pathological states, and making the corresponding in vitro organ chip according to the parameters; S2: planting a culture including the organ-related cells and/or tissues on the in vitro organ chip; S3: optionally adding a combination of one or more stimuli including drugs, mechanical force, biochemistry, electric field, and flow field to act on the culture; S4: obtaining each cell through the in vitro organ chip, and the change of the cell mechanical force of the tissue, to achieve the characterization of each cell and organ tissue.
  • specific cells or tissues can be sorted out by characterization.
  • the application of in vitro organ chips in screening the organ therapeutic drugs and in the study of organ models under physiological and case states.
  • Example 53 A method for detecting myocardial cell contraction and relaxation using an in vitro organ chip
  • This embodiment provides a cell mechanical force detection device or detection system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes, and an in vitro organ chip to obtain cell physical information; specifically comprising: S1 cutting the mouse heart perfused with a high concentration of EDTA solution into pieces, and then decomposing it into single cells with collagenase; S2 after the cell-containing suspension is allowed to stand for 20 minutes, the cardiomyocytes will settle at the bottom of the tube; S3 directly culturing the obtained cardiomyocytes on an in vitro organ chip; S4 after several days of cultivation, the cardiomyocytes will show regular contraction; S5 using high-speed photography to take 100 photos per second to observe the mechanical changes of the cardiomyocytes during each contraction-relaxation cycle, and after continuously recording multiple contraction-relaxation cycles, the contraction frequency of the cardiomyocytes can be converted, please refer to Figure 24.
  • Example 54 A method for detecting the effect of drugs on the contraction-relaxation frequency of cardiomyocytes using an in vitro organ chip
  • This embodiment provides a cell mechanical force detection device or detection system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes, and an in vitro organ chip to obtain cell physical information;
  • S1 cuts the mouse heart perfused with a high concentration of EDTA solution into pieces, and then decomposes it into single cells with collagenase;
  • S2 after the cell-containing suspension is allowed to stand for 20 minutes, the cardiomyocytes will settle at the bottom of the tube;
  • S3 directly culture the obtained cardiomyocytes on an in vitro organ chip;
  • S4 after several days of culture, the cardiomyocytes will contract regularly;
  • S5 takes 100 photos per second by high-speed photography to observe the mechanical changes of the cardiomyocytes during each contraction-relaxation cycle, and continuously records multiple contraction and relaxation cycles.
  • the contraction frequency of myocardial cells can be calculated;
  • S6 then adds the calcium ion blocker Nifedipine to continuously record the mechanical changes of myocardial cells
  • Example 55 A method for printing extracellular matrix patterns on an in vitro organ chip for cardiomyocyte arrangement and measurement of cardiomyocyte contraction-relaxation frequency
  • This embodiment provides a cell mechanical force detection device or detection system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes, and an in vitro organ chip to obtain cell physical information;
  • S1 uses microcontact printing to print the extracellular matrix onto a mechanical chip in a special pattern;
  • S2 culture mouse cardiomyocytes on this mechanical chip, and the cells will adhere and grow in the area with extracellular matrix, forming a special pattern and regular arrangement;
  • S3 After several days of culture, the cardiomyocytes will show regular contraction;
  • S4 uses high-speed photography to take 100 photos per second to observe the mechanical changes of the cardiomyocytes during each contraction-relaxation cycle. After continuously recording multiple contraction and relaxation cycles, the contraction frequency of the cardiomyocytes can be converted.
  • Example 56 A method for measuring changes in mechanical force of cells during differentiation of fibroblasts into adipocytes in vitro
  • This embodiment provides a cell mechanical force detection device or detection system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes, and an in vitro organ chip to obtain cell physical information;
  • S1 culture the mouse fibroblast cell line NIH3T3-L1 on a mechanical chip and start recording the cell mechanical force;
  • S2 replace the culture medium with a culture medium containing methylisobutylxanthine, dexamethasone and insulin;
  • S3 on the third day of culture replace the culture medium with a culture medium containing insulin;
  • S4 on the sixth day of culture replace the culture medium with a normal DMEM culture medium;
  • S5 around the tenth day NIH3T3-L1 can differentiate into adipocytes, and Oil Red O staining can be used to monitor lipid accumulation to know the cells that have differentiated into adipocytes, and Calcein AM staining can be used to exclude dead cells.
  • S6 records the changes in cell mechanical force
  • This embodiment provides a cell mechanical force detection device or detection system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above schemes, and an in vitro organ chip to obtain cell physical information;
  • S1 brown adipose tissue and white adipose tissue are respectively taken out from newborn mice, cut into small pieces, and digested and decomposed into single cells using collagenase, and then filtered and centrifuged to obtain preadipocytes;
  • S2 the preadipocytes obtained from brown adipose tissue and white adipose tissue are cultured and enlarged in culture dishes respectively;
  • S3 after several days of culture, the two types of preadipocytes are transferred to a mechanical chip for culture, and the cell mechanical force is recorded at the same time;
  • S4 a culture medium containing methylisobutylxanthine, dexamethasone and insulin is added to the preadipocytes separated from the white adipose tissue to differentiate them into white a
  • Example 58 A stem cell-induced heart organ model and characterization method thereof
  • This embodiment specifically provides a stem cell induced heart model, in which a tropic ECM is printed on a cell mechanical force detection device by microcontact printing, and stem cells are planted on it to induce the direction of myocardial differentiation. During the induction process, light reflection signals and magnetic field-induced microcolumn deflection are used to monitor changes in cell mechanical force and hardness.
  • S1. Use microcontact printing technology to prepare a tropic extracellular matrix (ECM) on the top of the microcolumn of the mechanical chip.
  • ECM extracellular matrix
  • S2. Use anti-adhesion treatment on the sides of the microcolumns and between the microcolumns, such as Pluronic F127.
  • Example 59 A stem cell-induced tissue-specific cartilage model and characterization method thereof
  • This embodiment specifically provides a stem cell induced cartilage model, in which cartilage-specific ECM extracted from cartilage tissue is coated on the chip, adult stem cells (MSC) are planted on top and cartilage differentiation is induced.
  • MSC adult stem cells
  • MSC adult stem cells
  • S1. Cartilage-specific extracellular matrix (ECM) extracted from cartilage tissue is coated on the top of the microcolumn of the mechanical chip.
  • ECM extracellular matrix
  • Anti-adhesion treatment is applied to the sides and between the microcolumns, such as Pluronic F127.
  • MSC adult stem cells
  • S4 Appropriate induction factors are added to guide adult stem cells to differentiate into chondrocytes.
  • light reflection signals are used to monitor the interaction between cells and microcolumns, so as to detect changes in cell mechanical force in real time.
  • S6 The microcolumn deflection is induced by magnetic field, and the force applied by cells to the microcolumns is measured to further evaluate changes in cell hardness.
  • S7 During the differentiation induction process, fluorescence staining and histochemical staining were performed to evaluate the expression of cartilage differentiation-related markers.
  • the light reflection signal and magnetic field-induced microcolumn deflection data were analyzed and compared with the fluorescence staining results and histochemical staining results to evaluate the changes in cell mechanical force and hardness during cartilage differentiation, providing a strong basis for chondrocyte differentiation research (Figure 27).
  • Example 60 A lung tumor model and characterization method thereof
  • This embodiment specifically provides a lung tumor model and characterization method, in which normal and tumor lung extracted cells are planted on a double-sided sandwich structure chip.
  • the chip base is a flexible material that can be inflated and deflated to simulate the breathing action of the lungs.
  • light reflection signals and magnetic field-induced micro-column deflection are used to monitor the changes in cell mechanical force and hardness to measure the tumor killing and the impact on normal cells to evaluate the targeting of the drug.
  • S1. Prepare a double-sided sandwich structure mechanical chip.
  • the chip base is a flexible material.
  • the top of the micro-column is coated with extracellular matrix (ECM).
  • ECM extracellular matrix
  • the side of the micro-column and between the micro-columns are treated with anti-adhesion, such as PluronicF127.
  • S2. Plant normal lung cells on one side of the chip and lung tumor cells on the other side, so that the cells are completely attached to the chip. It can also be mixed in different areas on the same side.
  • S3. Place the double-sided chip in a device that can be inflated and deflated to simulate the breathing action of the lungs ( Figure 28).
  • S4. Add chemotherapy drugs to stimulate normal lung cells and lung tumor cells.
  • the force exerted by cells on microcolumns is measured using magnetic field-induced microcolumn deflection to further evaluate changes in cell hardness.
  • S7 Analyze light reflection signals and magnetic field-induced microcolumn deflection data, 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 of chemotherapy drugs based on experimental results to provide a basis for drug screening and research.
  • Example 61 A method for determining tumor areas and non-tumor areas in tissue
  • This embodiment provides a cell mechanical force detection device or characterization system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above solutions to obtain cell physical information of different tissues; it includes the following steps:
  • tumor-containing tissues such as the pancreas and liver, were removed from the mice and cut into pieces about 0.5 cm in length and width. The tissues were fixed on a tissue embedding tray using glue, and then cut into thin slices about 150-200 mm thick using a tissue slicer.
  • S2 Place the tissue slice on the microcolumn of the cell detection device, add cell culture fluid until it just covers the top of the tissue slice, let it stand for half an hour, then add more cell culture fluid to completely immerse the tissue. After one hour, the cell mechanical force and its changes in the tissue can be monitored;
  • step S3 detects the cell mechanical force and finds that the block is divided into areas with strong cell mechanical force and weak cell mechanical force.
  • the pancreatic cancer cell line in step S1 is a cell that expresses EGFP fluorescent protein; at the same time, in step S3, the EGFP signal of the tissue and the strength of cell mechanical force are compared, and it is found that the area containing cancer cells in the tissue (EGFP expression area) has a stronger cell mechanical force.
  • the area with strong cell mechanical force is the area containing cancer cells, thereby achieving the identification of different areas in the tissue, as shown in Figure 31.
  • This embodiment provides a cell mechanical force detection device or characterization system as described in any of the above embodiments or a cell mechanical force detection method as described in any of the above solutions to obtain cell physical information of different tissues; it includes the following steps:
  • pancreatic cancer cell lines expressing EGFP fluorescent protein into the pancreas of mice
  • tumor-containing tissues such as the pancreas and liver, were removed from the mice.
  • the tissue will be completely attached to the chip and drugs can be added for drug testing, such as Gemcitabine and 5-FU, which are commonly used to treat pancreatic cancer.
  • drugs can be added for drug testing, such as Gemcitabine and 5-FU, which are commonly used to treat pancreatic cancer.
  • This embodiment specifically provides a tissue biophysical characterization system, which can distinguish tumor and normal tissue areas and evaluate the effect of drug treatment by monitoring the spatial omics of mechanical properties of living tissue slices.
  • S1 Prepare biopsy sections: Obtain biopsy samples (including tumors and normal tissues) and prepare them into thin sections.
  • Drug treatment Add anti-tumor drugs to biopsy sections and treat them for a certain period of time. Immune cell suspension can also be added to measure tumor-immune interactions.

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Abstract

一种细胞的表征、分型和识别方法和应用。细胞物理信息包括是在以下至少一种情况下获取的细胞机械力或/和硬度；细胞或/和多细胞聚体之间相互作用、不同生长时刻下的细胞或/和多细胞聚体、多细胞聚体内部的不同区域、物质对细胞或/和多细胞聚体之间的作用、其它物理、生物或化学因素对细胞或/和多细胞聚体作用；通过上述表征方法对细胞或/和多细胞聚体进行分型和识别；通过细胞物理信息表征细胞或/和多细胞聚体实时和连续的状态，可以在短时间内、低成本、高通量的识别到细胞或/和多细胞聚体各个类型和状态，其准确率在98％以上；通过表征系统可实现上述的效果。

Description

一种细胞的表征、分型和识别方法和应用 技术领域
本发明涉及生物技术领域，尤其涉及一种细胞的表征、分型和识别方法和应用。
背景技术
在生物领域中对于细胞或和多细胞聚体在药物开发过程中，细胞模型的选择至关重要，因为有效的细胞模型可以更准确地预测药物在体内的反应。传统的二维(2D)细胞培养模型虽然易于操作和观察，但由于缺乏体内微环境的模拟，其预测结果往往与体内实际情况存在较大差距。为了更好地模拟体内微环境，近年来，肿瘤球体及类器官作为多细胞聚体培养模型受到了广泛关注。特别是对细胞-细胞相互作用，以及其它的表征尤为重要。
细胞是生命的基本单位，其黏附，迁移，分化，凋亡的过程及在不同生理和病理过程中的动态变化，及与大分子之间的相互作用，对于理解和调控生命现象具有重要意义。因此，表征细胞及细胞多聚体的类型、状态、行为等，是生物工程、细胞生物学、物理生物学等领域的重要课题。
目前，表征细胞及细胞多聚体的方法主要有以下几种：如物理方法：利用仪器来测量细胞的力学或电学特性，如机械力、黏附力、弹性模量、电阻抗等。这些方法可以反映细胞的形态、功能和代谢状态，但现有技术通常需要昂贵的设备和数据处理技术。例如，原子力显微镜、机械力显微镜、电阻抗谱仪等。操作复杂，通量低成本高。也因为通量或光毒性等限制，难以对细胞进行长期且实时的监测。生化方法：利用试剂或标记物来测量细胞。这些方法可以灵敏地检测细胞状态及和大分子的结合情况，但也可能影响其本身的特性或功能。例如，荧光共振能量转移、生物素-亲和素系统、酶联免疫吸附试验等。化学方法虽然可以灵敏地检测到细胞与大分子之间地结合情况，但通常需要对目标进行标记或修饰，并且可能干扰其正常地功能。
发明内容
(一)要解决的技术问题
鉴于现有技术的上述缺点、不足，本发明提供一种细胞的表征方法，其可以通过检测和获取细胞/多细胞聚体在不同时刻或在其它因素作用之前后、作用过程中的静态或动态的细胞机械力或/和硬度，表征细胞和多细胞聚体；
相应地，本发明还提供一种细胞的分型和识别方法，其通过细胞机械力或/和硬度可以实现对任何情况下的细胞或/和多细胞聚体的分型和识别。
相应地，本发明还提供一种上述方法的应用。
(二)技术方案
为了达到上述目的，本发明采用的主要技术方案包括：
第一方面，本发明提供一种细胞的表征方法，通过获取细胞或/和多细胞聚体的细胞物理信息表征细胞或/和多细胞聚体。
可选地，所述细胞物理信息包括是在以下至少一种情况下获取的细胞机械力或/和硬度；
(1)细胞和多细胞聚体之间相互作用、
(2)细胞与细胞之间的相互作用、
(3)多细胞聚体与多细胞聚体之间的相互作用、
(4)不同生长时刻下的细胞或/和多细胞聚体、
(5)多细胞聚体内部的不同区域、
(6)物质对细胞或/和多细胞聚体之间的作用、
(7)其它物理、生物或化学因素对细胞或/和多细胞聚体作用；
所述多细胞聚体为两个以上细胞团聚一起形成细胞群体。
第二方面，本发明还提供一种细胞或/和多细胞聚体分型和识别方法，其通过上述 表征方法对所述细胞或/和多细胞聚体进行分型和识别；
其中，细胞或/和多细胞聚体分型是指由于不同因素下可使细胞或/和多细胞聚体的包括不仅限于类型、状态、行为、空间组学特征等特性的不同，根据上述的不同，可进行分型。
第三方面，本发明还提供任一方案中所述方法的应用，所述应用包括以下的至少一种：
在建立体外器官和细胞模型中的应用；
在筛选器官治疗药物中、在器官模型在生理和病例状态下研究中的应用；
在药物对肿瘤有效性评估方法和相关评估产品中的应用；
在细胞疗法、合成生物学、脂肪研究、细胞/多细胞聚体与大分子相互作用研究、多细胞聚体研究方法及其以上相关产品中的应用。
(三)有益效果
本发明的有益效果是：
首先：本发明通过获取的细胞物理信息可用于表征细胞或/和多细胞聚体相互作用、与外界因素相互作用之前、之中和之后的状态，或者包括连续的状态，可实时观察状态，其可以在短时间内、低成本、高通量的识别到各个状态，其准确率在98％以上；可适用于不同场景和条件下，快速的确定细胞和细胞之间，细胞和多细胞聚体，以及多细胞聚体和多细胞聚体之间的关系，对于细胞样品可重复利用；本发明进一步限定通过表征系统来实现，其可实现上述的效果。
其次：本发明进一步限定的表征系统，其通过反射光线就可实现细胞机械力的检测，其相对于现有细胞机械力检测装置，其具有高通量低成本的特点；与现有TFM及普通微柱阵列相比，本发明的技术方案摆脱了对显微镜的依赖，极大地简化了操作流程，因为无需通过显微镜高分辨率成像，只需通过对反射光的强度进行监测，即可实现高通量对细胞进行监测，且成本低廉。细胞机械力检测装置基于细胞机械力使微柱形变，将细胞机械力转化为光学信号进行检测，具有精确率高、灵敏度高的特点；光学强度与细胞机械力的大小具有线性相关，可进行定性和定量的分析细胞机械力；
再次：本发明进一步限定的表征系统，可选地，在微柱的顶端上增加了磁性金属反射层和磁性材料，并通过改变微柱的涂层组成特性、间距、运动逻辑等参数，可以在测量细胞机械力或细胞硬度之间切换，或同时测量细胞力或细胞硬度，实现更灵活、更精确的细胞物理特征的全面表征。
再次：本发明的表征系统，单细胞分辨率：分辨率高，可对每只细胞进行实时监测，可结合其他单细胞分析技术测量细胞对药物反应的异质性；实时监测：无需荧光，可避免激光对细胞的光毒性作用，因此适合长期监测，可用于研究细胞对药物的长期反应；高灵敏度：通过反射讯号，将微柱形变信号放大，增加对形变监测的灵敏度。检测微、纳米柱弯曲形变一般依赖光学系统(如显微镜)进行检测，但微柱尺寸越小，对光学系统的精密度和解析度要求越高。例如2微米宽，6微米高的微米柱，需要20倍以上的物镜搭配共轭焦系统才可有效观测。而本发明利用镜面反射原理通过探测反射光的衰减，实际使微柱形变的信号得以放大，经实验验证，同样的讯号在5倍物镜下即可观测。搭配特殊的读取系统，不需依赖高倍数的光学物镜即可有效检测微/纳米柱形变，从而极大降低系统成本，并有效提升通量。
再次：本发明的表征系统，可模拟细胞微环境；可模拟细胞外基质的组分和形态，可应付更丰富的技术需求场景。
附图说明
图1为本发明第一实施例中一种细胞机械力的检测装置的结构示意图；
图2为本发明第一实施例中一种细胞机械力的检测装置的微柱(实物)的扫描电子显微镜(SEM)图像；其中，a为细胞机械力检测装置的俯视图，b为细胞机械力检测装置的侧视图；
图3为本发明第九实施例相关的一种细胞/多细胞聚体相互作用的表征系统的结构示意图；
图4为本发明第十实施例相关的一种细胞/多细胞聚体相互作用的表征系统的结构示意图；
图5为在顶部位置设有光线反射层(金)的微柱(聚二甲基硅氧烷)的扫描电子显微镜图像；其中，图5a为微柱的扫描电子显微镜图像；图5b为微柱顶部区域的元素表征图；图5c为微柱侧面区域(除顶部区域外)的元素表征图；
图6为本申请第七实施例示出的细胞粘附在具有细胞黏附作用的物质的微柱顶端(纤维粘连蛋白)的图片，其中，6a为细胞粘附于顶部设有纤连蛋白的微柱群构成的预设图案的荧光成像图，6b为细胞粘附于顶部设有纤连蛋白的微柱群上测得的光反射信号解算出来的细胞力分布图；
图7为本申请具体实施例示出的细胞粘附在细胞黏附作用的物质选用OKT3抗体(即与细胞表面受体具有相互作用的物质)或纤连蛋白(Fibronectin，FN)的试验相关图片，其中，7a为采用OKT3抗体作为具有细胞黏附作用的物质的试验示意图；7b的上部分两个图像为细胞分别粘附于顶部设有OKT3抗体、纤连蛋白的微柱顶部的荧光成像图；7b的下部分两个图像为在微柱上测得的光反射信号解算出的细胞机械力大小分布图；7c为分别在OKT3抗体、纤连蛋白涂敷表面测得的力学大小对比图；7d为将T细胞种植于OKT3抗体表面(微柱顶部)后发生的细胞力学动态变化图；
图8为具有细胞限制机构的细胞机械力的检测装置的结构示意图a；
图9为具有细胞限制机构的细胞机械力的检测装置的结构示意图b；
图10为本发明具体实施例中采用硅薄膜作为细胞限制机构的细胞机械力的检测装置相关图片，其中a为其实物图；b为在光反射下采用硅薄膜作为细胞限制机构的细胞机械力的检测装置的荧光显微镜图；c为b的放大图；
图11第十一实施例的表征系统监测细胞机械力的荧光显微镜图像；
图12为本发明第十二实施例提供的细胞机械力检测系统及其检测结果示意图，其中a为第十二实施例的细胞或/和多细胞聚体相互作用的表征系统的结构示意图；b为第十二实施例的光信号检测装置获取得到的细胞机械力检测装置光反射讯号的图像；c为第十二实施例的光信号分析装置处理后的力学大小及分布的可视化效果图；
图13本发明具体实施例示出的利用流体当作外加力，细胞机械力与光反射信号的相互关系示意图，a为流体开启前后微流体环境中细胞机械力检测装置的结构示意图；b为流体开启前微柱的明视场显微镜图、反射光信号分布图以及二者叠合效果的对比图；其中，叠合效果图是指将微柱的明视场显微镜图和反射光信号分布图叠合而成的效果图；c为流体开启后微柱的明视场显微镜图、反射光信号分布图以及二者叠合效果图的对比图；其中，叠合效果图是指将微柱的明视场显微镜图和反射光信号分布图叠合而成的效果图；d为流体开启前后光反射信号的强度值；e为光反射信号衰减和微柱顶部平移的线性区间；
图14为本发明具体实施例示出的细胞机械力的检测方法示意图，a为细胞机械力的检测装置的微柱与细胞发生接触前后的结构示意图；b为光信号检测装置获取的反射光信号分布图；c为细胞迁移过程的监测图；d为细胞迁移过程中的反射光信号分布图；
图15为本发明具体实施例示出的用本申请细胞机械力的检测方法获取得到的细胞机械力信息，a为健康细胞和肺非小细胞癌细胞混合体系的荧光成像图；b为光信号检测装置获取得到的细胞机械力检测装置光反射讯号分布图；c为光信号分析装置处理后的力学大小及分布的可视化效果图；d为c中的健康细胞和肺非小细胞癌细胞的代表性单细胞细胞力分布的放大图；e为健康细胞和肺非小细胞癌细胞在细胞形态上的对比图；f为健康细胞、肺非小细胞癌细胞以及这两种细胞以不同比例混合后的反射信号强弱的对比图；g为将c经过结构化处理后，基于结构化细胞物理信息处理得到的聚类分析图；
图16为本申请具体实施例示出的用本申请细胞机械力的检测方法获取得到的细胞机械 力信息，用于监测细胞活力的示意图，其中，a为细胞活力检测方法的操作流程示意图；b为A549细胞在不同剂量的5FU处理24h后，MTT法测定得到的细胞活力以及细胞机械力所反映的细胞活力的对比图；c为A549细胞在不同剂量的5FU处理不同时间后，MTT法测定得到的细胞活力以及细胞机械力所反映的细胞活力的对比图；
图17为本发明第二十九实施例中对某点位位移信息标量化处理的示意图；
图18为本发明第三十实施例扩展实施方式中所述将建立的细胞特征模型用于未知细胞或未知细胞表现型的识别的结果图A；
图19为本发明三十实施例扩展实施方式中所述将建立的细胞特征模型用于未知细胞或未知细胞表现型的识别的结果图B；
图20为第三十五实施例使用机械力表征监控类器官贴附及对药物反应的实验结果图；
图21为第三十六实施例中使用机械力表征肿瘤球体的荧光染色实验结果图；
图22为第三十六实施例中限制性结构来约束细胞球体的大小和形状实验结果图；
图23为为本发明第四十一实施例中T细胞株经装置上CD3抗体涂层激活后，其荧光表现与细胞机械力成像图与量化图；
图24为第五十三实施例中以细胞机械力测量装置量测小鼠心肌细胞机械力的可视化效果。
图25为第五十六实施例中NIH3T3-L1分化成类脂肪细胞过程的细胞机械力变化图；
图26为第五十八实施例在芯片上印制向性ECM,并表征干细胞诱导心脏组织的表征图；
图27为第五十九实施例在芯片上印制组织特异性ECM,并对干细胞诱导软骨进行荧光及组化染色表征图；
图28为第六十实施例双面可形变肺肿瘤芯片的原理图；
图29为第六十三实施例肿瘤组织区块与正常组织区块的细胞机械力成像图；
图30为第六十三实施例中经药物处理后，肿瘤组织区块与正常组织区块的细胞机械力成像图；
图31为第三十六实施例中所述的三明治结构。
附图标记说明：
1-细胞机械力的检测装置；2-光信号发生装置；3-光信号检测装置；4-光信号分析装置；
5-分光器；
11-基座；12-微柱；13-光线反射层；15-凹陷空间；16-限制面；
101-物镜；102-入射及反射光线；103-形变的微柱；104-细胞；105-抗反射层；106-具有
细胞黏附作用的物质；107-具有细胞黏附抑制作用的物质。
具体实施方式
为了更好的解释本发明，以便于理解，下面将更详细地描述本发明的示例性实施例。虽然以下显示了本发明的示例性实施例，然而应当理解，可以以各种形式实现本发明而不应被这里阐述的实施例所限制。相反，提供这些实施例是为了能够更清楚、透彻地理解本发明，并且能够将本发明的范围完整的传达给本领域的技术人员。
实施方式一
本实施方式提供一种细胞或/和多细胞聚体的表征方法，通过获取细胞或/和多细胞聚体的细胞物理信息表征细胞或/和多细胞聚体；所述细胞物理信息包括细胞中某点的细胞机械力或/和硬度；所述细胞机械力包括大小、方向、频率中的至少一种。所述细胞物理信息还包括细胞形貌信息。所述细胞物理信息包括该点细胞机械力或/和硬度在一定时间间隔内的变化。可选地，所述细胞物理信息中的细胞机械力或/和硬度通过可视化的形式呈现。
所述细胞物理信息可选地，是在对细胞或/和多细胞聚体进行细胞限定操作下获取的。限定使得固定数量的细胞群能够有序地培养在限制环境中，并能够高通量监测其细胞机械力变化，同时能够让每个细胞群有接触到其他细胞群的机会，有利于观察细胞间相互作用。识 别是指对已知分型和未知分型进行识别。
本实施方式通过细胞物理信息是基于以下作用获取的，细胞和多细胞聚体之间相互作用；细胞与细胞之间的相互作用；多细胞聚体与多细胞聚体之间的相互作用；细胞和多细胞聚体之间相互作用；
具体地，其包括以下步骤：
将第一细胞或/和多细胞聚体、第二细胞或/和多细胞聚体分别设置在特定区域，检测并且获取细胞物理信息；
或
将第一细胞或/和多细胞聚体于特定区域后，第二细胞或/和多细胞聚体与所述第一细胞或/和多细胞聚体相互作用，检测并且获取细胞物理信息；
所述第一细胞或/和多细胞聚体，以及第二细胞或/和多细胞聚体均为一个以上的细胞或/和多细胞聚体；
通过所述细胞物理信息表征第一细胞或/和多细胞聚体、以及第二细胞或/和多细胞聚体之间的相互作用。
可选地，可选择实施方式一的细胞/多细胞聚体表征系统进行表征，所述特定区域位于细胞/多细胞聚体表征装置表征系统；
可选地，细胞或/和多细胞聚体可以贴附在特定区域，可选为限位贴附。
贴附的方法包括：细胞或/和多细胞聚体置于特定区域(在其它一些具体实施方式中为表征系统的特定区域)后，静置培养养半小时以上，继续加入培养液培养直至细胞或/和多细胞聚体完全与特定区域(表征装置)贴附。
可选地，在检测和获取细胞物理信息之前、之中加入外界刺激。可选地，加入的外界刺激可以但不仅限于：生物、化学、物理刺激，向性引导、动态刺激；
药物的刺激，用于监测和表征药物对于细胞或/和多细胞聚体的作用，以及在药物的刺激下，细胞和多细胞聚体之间相互作用；细胞与细胞之间的相互作用；多细胞聚体与多细胞聚体之间的相互作用；细胞和多细胞聚体之间相互作用的变化。进一步，明细药物的药理作用和其它特性。除了药物之后，其它的化学刺激，可以但不仅限于：pH值、含氧量、糖浓度。
生物刺激可以但不仅限于：生长因子是细胞生长和增殖的关键信号分子。可以通过添加生长因子来刺激细胞，促进其增殖、迁移或分化，从而影响细胞的机械特性和相互作用。细胞外基质(ECM)成分：改变细胞外基质的组成或结构，例如通过调整细胞外基质的刚度、纤维排列或化学成分，可以直接影响细胞的机械响应和行为。
动态刺激可以但不仅限于：周期性应变：应用周期性的应变刺激，例如交替施加拉伸和压缩力，可以模拟生物组织在生理过程中的动态变化，从而研究细胞的机械响应和适应性。时间变化的化学环境：通过周期性或阶梯性地改变化学环境，可以是周期性变化的药物浓度或化学物质的添加和清除，可以模拟细胞在生理或病理条件下的动态响应和适应。
向性引导可以但不仅限于：通过在基板上形成生物形态梯度，例如细胞外基质的结构或刚度梯度，可以引导细胞定向生长或运动。通过对基质在某个方向的划线，引导细胞在划线的方向上生长变化；
物理刺激可以但不仅限于：温度、磁感应力、电刺激、流场刺激；机械力：通过应用机械拉伸、挤压或压缩等力学刺激，可以直接调控细胞的形态和机械响应，包括但不仅限于改变细胞形态、细胞内力学分布。流体力学刺激：应用流体力学刺激，例如剪切力、流场变化等，可以模拟细胞在血液或组织流体中的生理环境，从而调节细胞的生理活性和机械特性。
外界刺激可放大不同分型细胞之间细胞机械力信息的差异，更易识别，提高识别的效率和准确率。当使用含有微柱的表征装置检测机械力和硬度时，通过改变微柱的硬度来放大细胞物理信息。
细胞或/和多细胞聚体的贴附可以是细胞培养液的加入继续培养可以使其稳定贴附，同时，通过胶黏物质将细胞或/和多细胞聚体贴附。
通过本实施方式中，分别获得细胞/多细胞聚体的细胞物理信息，实现细胞或/和多细胞聚体相互作用的识别；
本实施方式中通过获取细胞物理信息可实现快速、高通量的识别细胞/多细胞聚体 的不同，可应用于细胞/多细胞聚体对于药物的反应。
本实施方式中，细胞机械力可通过微力传感器或微流变仪、细胞机械力检测装置进行监测和获取。这些装置可以测量细胞施加到基质或其他细胞上的力量的大小、方向和频率。通过在特定时间间隔内对细胞机械力的测量，可以了解其变化情况。
硬度的监测：细胞或多细胞聚合体的硬度可以通过纳米压痕仪、力-距离曲线技术等方法来测量。这些技术可以定量地评估细胞或聚合体的硬度，从而了解其受到外部力量时的变化。
细胞形貌信息和空间分布的监测：细胞形貌信息和空间分布可以通过显微镜、共聚焦显微镜、原子力显微镜等成像技术来获取。这些技术可以观察细胞的形态特征、细胞内部结构以及细胞聚合体的空间分布情况。
本实施方式中，细胞物理信息可通过表征系统获取；
所述表征系统包括：
基座，以及设置于基座上的，可受细胞机械力作用和/或磁力作用而产生形变的一个以上的微柱构成的微柱阵列，所述微柱上设有光线反射层；
可选地，所述微柱远离基座的一端设置有光线反射层，所述基座设置有可透光部分，所述微柱的柱体设置有可透光部分；可选地，所述微柱的表面或/和基座具有抗反射层。
可选地，其还通过光信号发射装置和光信号检测装置获取，所述光信号发射装置发出的光线通过入射光路照射到所述光线反射层，所述光线反射层反射的光线经过反射光路进入光信号检测装置；
可选地，所述光信号检测装置获取的光学强度，分析获得细胞物理信息；
可选地，所述光信号检测装置获取的光学强度与细胞机械力的大小具有线性相关，可进行定性和定量的分析实现不同的细胞分型。
可选地，所述表征装置可容置液体；
若所述液体为细胞培养液，使所述细胞或/和多细胞聚体贴附或/和继续培养；
可选地，所述细胞或/和多细胞聚体通过设置在微柱上的胶黏物质粘附于微柱上。
通过表征装置获取细胞物理信息的方法中，多细胞聚合体可以以多种方式结合在表征装置上，在其它一些具体实施方式中，提供其中的两种具体结合方式：
第一种结合方式：在细胞机械力检测装置的微柱上设置培养基，将细胞移植到微柱上的培养基中培养得到多细胞聚合体；在另一些实施方式中，这种结合方式，在细胞物理信息以可视化形式输出下，可以实时监控细胞的培养过程，以应用于如培养基、药物等化学、生物和物理外界刺激对细胞生长的影响；
第二种结合方式：直接将培养好的多细胞聚合体粘附于细胞机械力检测装置的微柱上，进行检测。
本实施方式还提供通过上述任一项所述细胞物理细胞，对所述细胞或/和多细胞聚体进行分型和识别的方法；
所述分型和识别包括：细胞或/和多细胞聚体的类型、状态、行为、空间组学特征及分化方向、应激反应；
可选地，所述分型和识别包括：通过所述细胞物理细胞可选择地分选出特定的细胞或组织。
可选地，其使用细胞识别装置进行识别，细胞识别装置包括信息获取单元、预处理单元、学习单元和识别单元；
所述信息获取单元用于获取细胞或/和多细胞聚体的细胞物理信息；
所述预处理单元用于对细胞物理信息做预处理，形成结构化细胞物理信息；所述结构化细胞物理信息包括细胞数目、细胞特征数目和各细胞特征的特征信息；
所述学习单元用于以结构化细胞物理信息作为输入数据，利用有监督、无监督或半监督的机器学习建立细胞特征模型；
所述识别单元用于将所述细胞特征模型应用于细胞或/和多细胞聚体的分类或聚类，实现细胞或/和多细胞聚体的分型和识别。
本发明中的识别是指对已知分型和未知分型细胞或/和多细胞聚体进行识别。
本发明中的分型是指由于不同因素下可使细胞或/和多细胞聚体的包括不仅限于类型、状态、行为、空间组学特征等特性的不同，根据上述的不同，可进行分型。对相 同或相近的细胞物理信息进行聚类分型，进一步可形成不同的类型。
本发明通过获取细胞物理信息可实现快速、高通量的识别细胞/多细胞聚体的不同，可应用于细胞/多细胞聚体对于药物的反应。
细胞或/和多细胞聚体分型是指由于不同因素下可使细胞或/和多细胞聚体的包括不仅限于类型、状态、行为、空间组学特征等特性的不同，根据上述的不同，可进行分型。
实施方式二
本实施方式提供一种细胞或/和多细胞聚体的表征方法，其与实施方式一不同点在于，其是基于不同生长时刻的多细胞聚体，或/和基于多细胞聚体内部不同的区域获得的细胞物理信息；
细胞物理信息的获取方法可以但是不仅限于：将多细胞聚体放在特定区域上，加入细胞培养液使多细胞聚体使其稳定贴附，便于测定细胞物理信息。
在其它一些具体实施方式中，本实施方式可使用如实施方式一中所述的表征系统获取所述细胞物理信息，
在其它一些具体实施方式中，表征系统可容置细胞培养液；细胞培养液的加入可实现组织在细胞机械力检测装置(表征装置)上培养的同时获取组织细胞机械力，无需将组织从细胞机械力装置中取出。
在其它一些具体实施方式中，细胞培养液的液面高于微柱顶部；
在其它一些具体实施方式中，组织细胞物理信息获取的方法为：将组织放在表征系统上，加入细胞培养液至少使组织与细胞培养液接触，静置培养半小时以上，继续加入细胞培养液培养直至组织完全与微柱贴附之后，实时测定并且获取组织的细胞机械力。
其中，培养半小时以上有利于组织与微柱更好的固定。
可选地，组织与细胞机械力完全贴附之后，通过加入外界刺激，测定组织在外界刺激下细胞机械力的变化。
在其它一些具体实施方式中，多细胞聚体(可以组织)通过设置在微柱上的胶黏物质粘附于微柱上。
在其它一些具体实施方式中，多细胞聚体指的是组织，组织可选为150～200mm的组织切片；
通过本实施方式的方法，
可选地，组织包括活性组织、类器官、体外器官。
可选地，在测定和获取细胞物理信息之前、之中和之后，对所述多细胞聚体进行外界因素刺激。
可选地，组织与细胞机械力完全贴附之后，通过加入外界刺激，测定组织在外界刺激下细胞机械力的变化。
外界因素刺激可放大不同多细胞聚体内部不同的区域，不同分型多细胞聚体之间细胞物理信息的差异，更易识别，提高识别的效率和准确率。当使用含有微柱的细胞机械力检测装置检测机械力和硬度时，通过改变微柱的硬度来放大细胞物理信息。具体的外界刺激，如实施方式一所述。
多细胞聚体内部不同的区域，包括但不仅限于：组织中肿瘤区域和非肿瘤区域；通过表征之后，可以对组织中肿瘤区域和非肿瘤区域识别。
还包括但不仅限于：
外围区域：位于多细胞聚集体的外部边缘，与周围环境接触，可能暴露于介质或培养基中。
中心区域：多细胞聚集体的中心部分，通常由于细胞密度增加而更为致密，可能具有不同的细胞组织结构。
边缘区域：介于外围区域和中心区域之间的区域，通常表现出与外围和中心区域不同的特征。
核心区域：多细胞聚集体的核心部分，可能是细胞密度最高的区域，也可能包含某些特定类型的细胞或细胞群。
表面区域：位于多细胞聚集体外部的表面区域，可能直接暴露于外部介质中，与周围环境直接接触。
功能区域：在多细胞聚集体内具有特定功能或活动的区域，例如代谢活跃区域、分泌区域或分化区域。
梯度区域：存在于多细胞聚集体内的梯度区域，可能包含梯度分布的信号分子或营养物质。
微环境区域：多细胞聚集体内部的微环境，可能受到细胞分泌物、细胞-细胞相互作用或基质组分的影响，对细胞行为和功能具有重要影响。
这些不同的区域可能在细胞增殖、分化、信号传导、代谢和细胞相互作用等方面表现出差异，对细胞聚集体的整体行为和功能具有重要影响。
本实施方式可以对不仅限于上述区域，未知区域进行表征、分型和识别。
本实施方式可将多细胞聚体(组织)状态的细胞信息形成结构化信息，不同类型组织。不同组织可分为：两个以上不同的组织、一个组织在不同时间下或外界刺激下形成的不同状态、一个组织中中两个以上不同的区域；
两个以上不同的组织：可以是病态组织和正常组织；
一个组织在不同时间下或外界刺激下形成的不同状态：可以是加入药物之后，动态变化下不同时间对应的不同状态的组织；或加入细胞培养液培养过程中组织的变化状态。
一个组织中中两个以上不同的区域：可以是一个组织中具有肿瘤区域和非肿瘤区域。
本实施方式可通过多细胞聚体(组织)的细胞机械力使微柱产生形变从而将细胞机械力转化放大为光反射信号，实现组织细胞机械力的精确识别；使其可应用于组织在变化过程的实时监测，即便组织在培养过程中仅有细微的变化，也能获取到其组织细胞机械力的变化，赋予每个变化后组织的力学指纹，还可以通过磁力，将微柱刺入细胞，实现硬度的测定，实现特征性、准确、快速的识别。
本实施方式其可用于快速、直接、非破坏且实时地测量整个活组织以及活组织中每个细胞的细胞机械力；通过组织中的细胞与微柱的接触来测量细胞的机械力。此外，因每种细胞种类具有不同的细胞力学强度，所以使用表征系统测量出整片组织之力学分布可以用来辨识出组织中不同细胞的区块，例如辨识肿瘤区域和非肿瘤区域；除此之外，在测量组织的细胞机械力时，可直接加入药物处理，实时监测组织中细胞的细胞机械力变化，来判断药物是否达到效果，从而实现精准药物的筛选，其准确率在98％以上。
本实施方式除上述不同之外，其它同实施方式一，在此不再赘述。
本实施方式提供了一种用于快速、直接、非破坏、实时地测量活组织整体及每个细胞机械力的方法。通过组织中细胞与微柱的接触，可以测量细胞的机械力。此外，利用表征系统测量整片组织的力学分布，可以辨识出不同细胞的区块，如肿瘤和非肿瘤区域。同时，该方法可在测量组织细胞机械力时，直接引入药物处理，并实时监测细胞机械力变化，以评估药物效果，实现精准药物筛选，准确率高达98％以上。
此外，该方法还能实现组织在培养和动态变化过程中细胞机械力的实时监测，快速测量整片活组织的细胞机械力，利用细胞机械力强弱来辨识肿瘤和非肿瘤区域，并在药物处理后实时监测肿瘤细胞的机械力变化，以判断药物是否能有效抑制肿瘤细胞生长。
此方法将组织细胞机械力信息转化为结构化信息，实现对组织不同状态的判定和识别。相应地，还提供了组织状态的表征系统和识别系统，以及在组织状态识别和药物对肿瘤有效性评估方法中的应用。
实施方式三
本实施方式提供一种细胞或/和多细胞聚体的表征方法，其与实施方式一不同点在于：
其是基于物质对细胞或/和多细胞聚体之间的作用获得的细胞物理信息；
其细胞物理信息获取的方法包括以下步骤：
将多细胞聚体物质与所述细胞或/和多细胞聚体相互作用；检测并且获取细胞或/和多细胞聚体的细胞物理信息。
可选地，加入培养液至少使细胞或/和多细胞聚体于细胞培养液接触，静置培养养半小时以上，继续加入细胞培养液培养直至细胞或/和多细胞聚体完全贴附于特定区域 后，加入与其作用的物质继续培养，并且测定和获取细胞物理信息。其中，培养半小时以上有利于细胞/多细胞聚体与微柱更好的固定。
可选地，在检测和获取细胞物理信息之前、之中加入外界刺激。
本实施方式除上述不同之外，其它同实施方式一，在此不再赘述。
其中，物质包括生物活性大分子、化学物质、生物活性物质和灭活生物物质；所述生物活性大分子包括：蛋白、多肽、多糖、脂肪。
本实施例提供上述任一项实施例中所述细胞机械力检测装置或细胞/细胞多聚体表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞/多细胞聚体的细胞机械力信息；具体地，其包括以下步骤：将细胞/多细胞聚体放在细胞机械力检测装置上，加入细胞培养液至少使细胞/多细胞聚体与细胞培养液接触，静置培养半小时以上，继续加入细胞培养液培养直至细胞/多细胞聚体完全与微柱贴附之后，测定获取细胞/多细胞聚体的细胞机械力。在一些具体实施例中，加入外界因素，以检测在外界因素下细胞/多细胞聚体细胞机械力的动态变化；在一些具体实施例中，外界因素可以在检测细胞机械力之前、之中加入。在一些具体实施例中，物质可以是细胞/多细胞聚体产生，也可以是外界加入。
本实施方式中还提供一种通过细胞机械力检测装置获取物质和细胞/多细胞聚体之间相互作用之前、之中和之后的包含细胞或/和多细胞聚体的可视化细胞信息，包括细胞机械力变化大小、分布等可视化信息；将所述可视化信息用于对待测物质和细胞/多细胞聚体之间相互作用的可视化识别，实时监控和表征物质和细胞/多细胞聚体之间相互作用。
在其它一些实施例中，所述细胞机械力信息还包括该点细胞机械力的方向。在其它一些实施例中，所述细胞机械力信息还包括该点细胞机械力的大小或方向在一定时间间隔内的变化。在其它一些实施例中，所述细胞信息还包括细胞形貌信息。在其它一些实施例中，通过第十八实施例的方法获取细胞机械力信息。基于本发明的细胞机械力检测装置，不仅可以通过肉眼直观区分以进行定性分析，还可以基于测得的细胞力学特征对细胞/多细胞聚体的状态进行更直观精确的识别(定量和定性分析)，并且证实了以细胞力场作为标志物能够更好地对类型进行区分。
本发明还提供一种物质和细胞/多细胞聚体识别系统和方法，其将物质对细胞/多细胞聚体作用的包括细胞机械力信息的细胞信息转化为结构化信息，实现对待测物质和细胞/多细胞聚体之间相互作用的快速、自动判定识别。
相应地，本发明还提供一种细胞/多细胞聚体表征和识别系统、方法在在需要表征细胞/多细胞聚体之间相互作用的相关方法和产品中的应用。
可适用于不同场景和条件下，快速的确定物质和细胞/多细胞具体之间的作用机理，使其可应用于监测细胞对物质的影响，监测细胞内外物质的变化，或者监测物质对细胞的影响，监测细胞的变化状态，对于细胞样品可重复利用；
再次：本发明的细胞机械力检测装置，可以对多层细胞，包括肿瘤多聚体等细胞机械力进行检测，使其可以应用于药物筛选、再生医学、基因编辑、精准医疗、器官发育、疾病建模中的需要对多细胞。
实施方式四
本实施方式提供一种细胞或/和多细胞聚体的表征方法，其与实施方式三不同点在于：还可以通过基于其它物理、生物或化学因素刺激对细胞或/和多细胞聚体作用下获得的细胞物理信息。
其方法可以为：
将细胞或/和多细胞聚体置于特定区域(在其它一些实施方式中，可以置于所述表征系统中)
可以在培养过程中，或者外界因素下，监测到细胞机械力的细微变化，可以应用于培养过程中，外界因素下，测定多细胞聚体或细胞的状态变化，并表征细胞或/和多细胞聚体的应激反应。
可选地，外界刺激因素包括药物、机械力、生化、电场、向性引导、动态刺激。流场中一种或两种以上刺激的组合，作用于所述培养物上。
可选地方案中，在使用表征系统之前、之中或之后，还可以对待测样品进行不同 类型和强度的刺激(机械刺激、电刺激、光刺激等)，以及对特定位置或区域的样品进行操作(标记、固化、烧蚀、切割、提取、分选等)；可以与其他表征方法(蛋白染色、组化染色、单细胞测序等)结合进行比较分析。可选地，其还包括作用于表征系统或细胞的作用机构，所述作用机构为微流控、微针、激光中的一种或两种以上的组合。合适的微柱的高度、相邻微柱的间距以及柱表面的大小在上述范围内的限定可以使细胞/多细胞聚体在物质和细胞/多细胞聚体的表征系统中处于更为稳定的状态。
本实施方式的方法，可用于表征细胞活力、黏附、迁移、激活、分化、凋亡；
在其它一些具体实施方式中，使用刺激使细胞或/和多细胞聚体产生应激，包含物理刺激，生化刺激，小分子及大分子之间对细胞或/和多细胞聚体产生刺激。
所获得的细胞物理信息包括：生物未受应激时，以及应激中/后细胞或/和多细胞聚体的细胞机械力及动态变化。
细胞通过不同的机制感知和回应外界刺激，包括基质硬度、剪应力和机械张力，本发明可以先固定贴附细胞或/和多细胞聚体在特定位置后，施加刺激，或再继续加入其它细胞或/和多细胞聚体置于所贴附的细胞或/和多细胞聚体上，可实时监测所贴附的细胞或/和多细胞聚体细胞物理信息的变化，可实时监测细胞或，多细胞聚体之间，或细胞和多细胞聚体之间的相互作用。
可选地方案中，在使用该表征系统进行表征之前、之中或之后，还可以对待测样品进行不同类型和强度的刺激(机械刺激、电刺激、光刺激等)，以及对特定位置或区域的样品进行操作(标记、固化、烧蚀、切割、提取、分选等)；可以与其他表征方法(蛋白染色、组化染色、单细胞测序等)结合进行比较分析。
本实施方式除上述不同之外，其它内容同实施方式一，在此不再赘述。
实施方式五
本实施方式提供一种细胞或/和多细胞聚体的表征方法，其与实施方式一不同点在于：其是基于体外器官或/和相关细胞模型种植成长过程中的细胞物理信息；所述细胞物理信息包括：器官相关细胞或/和组织的培养物种植和培养培养过程中的细胞或/和任何一个区域的细胞物理信息；
在其它一些具体实施方式中，通过所述细胞物理信息表征体外器官或/和相关细胞模型生长过程的任何区域的细胞或细胞团、器官组织；
在其它一些具体实施方式中，将细胞或/和组织与ECM的混合物种植；
在其它一些具体实施方式中，种植的方法包括：3D打印或/和微流控方法控制细胞
和生物材
料的分布和流动实现种植。
在其它一些具体实施方式中，将器官相关细胞或/和组织的培养物种植于表征装置上制成体外器官和细胞模型；
在其它一些具体实施方式中，其具体方法包括
S1采集相应组织生理及病理状态下的微环境参数，并根据所述参数将所述表征装置制得相应的体外器官芯片(即：表征装置可定制成体外器官芯片)；
S2将包括所述器官相关细胞或/和组织的培养物种植于所述体外器官芯片上。其中，种植可以以3D打印的方式种植于体外器官芯片上。
S3可选择地添加物理及生化刺激，包括药物、机械力、生化、电场、流场中一种或两种以上刺激的组合，作用于所述培养物上；
S4通过所述体外器官芯片获取每一个细胞，以及组织的细胞机械力的变化，实现每一个细胞和器官组织的表征。可选地，其还包括步骤S4，通过所述表征可选择地分选出特定的细胞或组织。
细胞识别装置中的识别单元用于将所述细胞特征模型应用于器官、细胞生长状态或在外界刺激下的分类或聚类，实现每个时刻相应状态下的器官和细胞的识别表征。
本发明的表征系统，将每个时刻相应状态下的器官的细胞信息形成结构化信息，分析未知状态下的细胞信息可实现自动对未知未知状态下的细胞识别。
体外器官芯片，其可以模拟人体器官的结构微环境，准确的贴近真实器官环境；同时，可以实时长时间监测每一只细胞的行为，实现器官的表征，可应用于体外器官 和相关细胞模型的建立，应用于各种研究课题对相关模型的需求；
在其它一些具体实施方式中，体外器官芯片在筛选所述器官治疗药物中、以及在器官模型在生理和病例状态下研究中的应用。
本实施方式中的体外器官芯片不仅可以模拟体内器官的结构微环境，而且可以实时通过检测每一只细胞的细胞机械力，以及器官组织的细胞机械力，实现表征；可以在培养过程中，或者外界刺激下，监测到细胞机械力的细微变化，可以应用于培养过程中，外界刺激下，测定器官组织或细胞变化。其中，外界刺激包括药物、机械力、生化、电场、流场中一种或两种以上刺激的组合，作用于所述培养物上。本发明的表征方法和传统生命科学的表征方法不同，无创无标记，而且能对活体细胞或组织长期实时的监测，并以单细胞分辨率对样品进行表征。可以更贴近器官的真实环境；
可选地，所述芯片主体根据所述器官，设置相应软硬度和长度的微柱；可以根据不同的器官，定制不同软硬度和长度的微柱，能够模拟器官更真实的环境。比如，其作为心脏芯片，可以在微型芯片上制造出一个心脏微环境，包括机械收缩、分子传输、电活动和生化刺激等多种因素，可定制性。它可以在微小的空间内模拟心脏的复杂结构和功能，包括心肌细胞、血管内皮细胞、心肌细胞外基质等多种组织成分，从而更加准确地模拟心脏功能。
可选地，所述微柱表面设置有ECM；可选地，将所述器官相关细胞或/和组织与ECM的混合物种植微柱上；可选地，所述微柱表面带有向性的ECM图层；可选地，所述种植的方法包括：3D打印；为了实现更好的可控性和可重复性。可以通过3D打印及微流控技术来精确控制细胞和生物材料的分布和流动，以及模拟器官(如：心脏)血液流动；微环境的各参数可以进行标准化，提高实验可重复性和数据的可比性。可选地，若所述器官为心脏，所述细胞包括心肌细胞、平滑肌细胞、血管内皮细胞、成纤维细胞、干细胞、免疫细胞中的一种或两种以上的组合。
可选地，其还包括：电级装置，所述微柱为导电材料制成，所述电极装置作用于所述微柱。
可选地，其还包括机械模拟装置，所述机械模拟装置为对所述芯片主体进行拉伸的机械拉伸装置；或为设置在微柱底部的可充气变形的柔性薄膜；所述柔性薄膜上端连接于微柱，下端连接于所述基座，或所述基座为柔性薄膜。
在测定和获取细胞物理信息之前、之中和之后，对所述体外器官的种植区域进行外界因素刺激。
外界因素刺激可放大多细胞聚体内部不同的区域，不同分型细胞、多细胞聚体之间细胞物理信息的差异，更易识别，提高识别的效率和准确率。当使用含有微柱的细胞机械力检测装置检测机械力和硬度时，通过改变微柱的硬度来放大细胞物理信息。具体的外界刺激，如实施方式一所述。
可选地，若所述器官为心脏，所述细胞包括心肌细胞、平滑肌细胞、血管内皮细胞、成纤维细胞、干细胞、免疫细胞中的一种或两种以上的组合。
本实施方式中提高的体外器官芯片在筛选所述器官治疗药物中、以及在器官模型在生理和病例状态下研究中的应用。
本实施方式中的方法以及体外器官芯片，其通过检测细胞机械力具有更好的表征能力，无创无标记，而且能对活体细胞或组织长期实时的监测，并以单细胞分辨率进行表征；体外器官芯片通过细胞力组学可以作为一种重要的技术手段，解决现有技术常用的细胞及动物模型存在的不足，从而促进心脏等器官研究的进一步发展和应用。
与传统生命科学的表征方法不同，本发明的体外器官芯片，更贴近真实的器官环境。心脏可以在微型芯片上制造出一个心脏微环境，包括机械收缩、分子传输、电活动和生化刺激等多种因素，可定制性搞。它可以在微小的空间内模拟心脏的复杂结构和功能，包括心肌细胞、血管内皮细胞、心肌细胞外基质等多种组织成分，从而更加准确地模拟心脏功能。
其中，为了实现更好的可控性和可重复性。可以通过3D打印及微流控技术来精确控制细胞和生物材料的分布和流动，以及模拟心脏等器官的血液流动；微环境的条件可以进行标准化，提高可重复性和数据的可比性。更加经济、高效、安全和伦理。相比于动物实验或临床试验，可以节省时间和成本，并且更加安全和伦理。
本发明的体外器官芯片，通过实时监测每一只细胞机械力，其可以在短时间内、低成本、高通量的对器官甚至每一只细胞在每个状态下的表征，从而实现精准的识别持续长时间监控到药物等外界刺激对器官和细胞的每个时刻的影响，对于药物筛选其准确率在98％以上；对于其它外界刺激研究的方法中，其在不同的状态下识别的准确率在98％以上。
本实施方式除上述不同之外，其它同实施方式一，在此不再赘述。
实施方式六
本实施方式提供一种细胞或/和多细胞聚体的识别和分型方法：其还可以通过实施方式一至实施方式五中获取的细胞物理信息进行分型和识别，其包括：
通过物质与细胞或多细胞聚体的相互作用的表征，确定是否细胞或多细胞聚体是否转染成功，所述包括蛋白或/和多肽、半固态培养基及抗体或二抗中的一种或两种以上的组合；
通过生物活性物质与细胞或多细胞聚体的相互作用的表征，确定并筛选得到生物活性物质的高产细胞或多细胞聚体；
通过获取细胞/多细胞聚体的细胞机械力，可监测该系统可监测基因工程对细胞的影响，包括：检测大克隆附近的小克隆团或单个细胞；
通过监测细胞的活力及状态，帮助需要建立最优的剂量反应曲线(dose-response curve or kill curve)确定杀死无抗性细胞的最低有效浓度，可选地，在药物筛选过程中对细胞进行实时监测以及时调整实验方案。
通过获取脂肪细胞包括生长、分化过程的细胞机械力信息，监测脂肪细胞的生长、分化；可选地，用于实时监测白色脂肪、米色脂肪及棕色脂肪的转换过程。
所述识别的方法包括以下步骤：通过细胞机械力检测装置获得细胞/多细胞聚体的细胞物理信息，实现物质对细胞/多细胞聚体相互作用的识别；所述细胞物理信息包括细胞机械力信息；本发明通过获取细胞机械力可实现快速、高通量的识别细胞/多细胞聚体的不同，可应用于细胞/多细胞聚体对于物质的反应。
本实施方式除上述不同之外，其它同实施方式一，在此不再赘述。
上述任一实施方式中应该注意的是：
本实施方式在作用之前，过程中和之后获取细胞物理信息。
本实施方式中的细胞物理信息可以实时测定，也可以特定时间或特定时间间隔进行测定，细胞物理信息可以是连续的，也可以是间断的。
本实施方式可以表征不同生长时刻下，以及外界刺激作用的细胞或/多细胞聚体，并且也由此进行已知或未知的类型的分型和识别。
本实施方式不仅限于不同生长时刻下，以及某一特定外界因素作用下的表征，可以是各种因素作用各种的组合作用下的细胞或/多细胞聚体的表征。
本实施方式通过所述表征可以用于物质对细胞或/和多细胞聚体作用前、作用过程以及作用后任一时刻中细胞或/和多细胞聚体的聚类和分类，特别是未知分类。
上述任一实施方式均可以以下面任一实施例中的细胞机械力的检测装置和表征系统，作为细胞物理信息表征装置或表征系统获取细胞物理信息，以及进行分析。
第一实施例一种细胞机械力的检测装置
请参照图1，为一种细胞机械力的检测装置的结构示意图a，图中展示的细胞机械力的检测装置包括透光的基座11(在其它一些具体实施例中，基座设置有透光部分，即：可以不是全透光基座，可以设置有不透光部分)以及设置在该基座11上的、可受细胞机械力作用而产生形变的微柱12，微柱12的顶部涂覆有光线反射层13，光线反射层13的厚度为5nm(在其他一些实施方式中，光线反射层13的厚度可以在5nm-20nm之间——涂层的厚度和涂层材料有关，在应用同种涂层材料的前提下，涂层厚度的选择应以保证透光效果、微柱柱体稳定性、保证与微柱柱体的连接不脱落为限)。微柱12的柱体可以透射光线，如图1所 示的入射及反射光线102，其中入射光线用实线箭头表示，反射光线用虚线箭头表示。图中方向相反的箭头簇表示入射光线和反射光线。(注意：本实施例中用了“涂层”一词，仅表示本实施例中的光线反射层13可以是涂覆工艺制备的，并不限定光线反射层13一定是涂覆工艺制备的)在其它一些具体实施例中，如图1、14所示，基座的不透光部分由包括但不限于抗反射层105的设置所形成。
请参照图2，为本实施例的细胞机械力检测装置的微柱12(实物)的扫描电子显微镜(SEM)图像，为细胞机械力检测装置的俯视图，b为细胞机械力检测装置的侧视图。由2可以看出，该细胞机械力检测装置的微柱的微结构整齐均一，尺寸可控，相比现有的细胞机械力检测装置，基于本实施例的细胞机械力检测装置测量得到的力学值更为精准。
当本实施方式所述的细胞机械力的检测装置1在投入使用时，微柱12的数量将不止一个。请参阅图3，为本发明第九实施例相关的细胞/多细胞聚体相互作用的表征系统的结构示意图；图3可用于对本实施例的理解。图3展示的系统除了涉及本实施例阐述的细胞机械力的检测装置1之外，还涉及：在基座11的下方设置的具有光源的光信号发生装置2以及光信号检测装置3，所述光源发出的光线通过入射光路从细胞机械力的检测装置1的透光的基座11照射到微柱12的光线反射层；所述光信号检测装置3用于检测从微柱顶部的光线反射层13反射后的光线，所述光线反射层13反射的光线经过反射光路并经过分光器5作用之后进入光信号检测装置3。在获得反射光信号之后，可以由一个光信号分析装置4对所述细胞机械力的检测装置1与待测细胞发生细胞机械力作用前后的反射光线进行对比分析，获取细胞机械力信息。当微柱12未受力的情况下微柱理应保持直立状态，从而能最大限度地反射探测光；而当微柱12与细胞相接触时，在细胞机械力的作用下，微柱12发生形变(为但不仅于弯曲、摆动)，导致光反射水平降低。所以，当细胞机械力越大时，所得到的光反射信号就应越小，这样藉由对光反射信号强度的观测即可轻易反推该点细胞机械力的大小。
此外，本实施例的技术方案中的测量光源可以采用一定强度的红外激光。传统技术方案中的微柱测量需要拍高解析度图像，在该过程中若使用激光容易造成细胞光毒性或是样品荧光光淬灭。而本技术方案中若只要测反射信号，因而一定光强度以内的红外激光对细胞影响基本可以忽略不计，因此适合对细胞进行长期监测。
第二实施例一种细胞机械力的检测装置
与第一实施例不同之处在于，所述微柱12不仅顶部端面具有光线反射层13，在微柱12的柱面(即连接柱体两个端面的曲面)的上半部分也设有光线反射层13。实际上，在其他实施方式中，除了在微柱12的侧柱面的下半部分设置光线反射层13的方案因实际效果较差而不予采用之外，只要将光线反射层13设置于微柱12的侧面的上半部分，基本都能够实现本发明所想达到的检测效果。也就是说，在某些其他实施方式中，光线反射层13甚至可以铺设在上半侧柱面的任一局部位置或顶部的局部位置而并不一定要铺满整个上半柱面或整个顶部端面，都能达到预期目的，虽然获取的数据和后期运算的效果上可能有所差别。
此外，本发明的第一实施例和第二实施例出现了对微柱“柱面”和“端面”的定义，也就是说，通常我们理解的独立柱体，应有两个端面以及将两个端面连接的曲面(柱面)，而本发明中的微柱由于基座的存在而只具有一个端面即顶端面，另一端则固定连接于基座或与基座一体成型。然而，在另外一些实施方式中，顶部的端面可能与柱面为一个整体光滑连接的曲面，并不必然如第一实施例或第二实施例所示的这样有交线或明显分界。在这种情况下，光线反射层13的设置位置也将理解为柱体的上半部分，而并不可被限定为“端面”或“柱面”。
第三实施例一种细胞机械力的检测装置
请参阅图4，图4为本发明第十实施例中一种细胞/多细胞聚体的表征系统的结构示意图，用于说明本实施例中的细胞机械力的检测装置1。本实施例与第一、第二实施例不同之处在于，对所述基座11和所述微柱阵列的微柱12柱体的透光性能不作要求，即既可透光也可不 透光也可半透光。此时，只需要改变光信号发生装置2和光信号检测装置3的位置，将二者设置于基座11的上方，这样每次当微柱发生弯曲或摆动的时候，光信号检测装置3所接收到的光信号都将相对于微柱12直立不形变时发生变化，通过对前后光信号的变化情况进行分析同样也可以得到细胞机械力的相对大小情况，在与标准值经过校正之后可以得到细胞机械力的绝对大小数值。
第四实施例一种细胞机械力的检测装置
如图1、14所示，本实施例与第一至第三实施例不同之处在于，在微柱12表面，除设有光线反射层13区域之外的区域，设置有对光线的抗反射层105。这样的设计可以减少柱体表层可能带来的反射光信号的干扰，增强信噪比，使检测结果更加精确。在其它一些具体实施例中，基座中设有抗反射层105，进一步强信噪比。
在某些实施例中，所述光线反射层13可以是一层金箔。在其他实施例中，光线反射层13还可以是其他具有光线反射功能的金属层或其他反光材料。不同材料带来的反光效果、反射层制备难易程度以及成本等可能存在差异，在实际操作中可以根据具体条件进行考量和抉择。
在第一至第四实施例中，所述微柱12的横截面形状为圆形。在其他实施方式中，所述微柱12的横截面形状还可以是椭圆形或多边形。在本发明的各种不同具体情况的实施方式中，横截面的不同可以达到不同的目的，例如圆形横截面具有各向同性的特点，即微柱本身的力学特性对方向不敏感。而如截面为椭圆形的情形则为各项异性，即微柱本身的力学特性对方向敏感，可以此控制不同方向对力场的敏感度，并且能在一定程度上调控细胞的向性(大部分细胞的几何形态其实都是不对称的，本发明中细胞的向性指的是细胞表现出的形态上的不对称性、极性或方向性。例如，假若用一个椭圆来拟合细胞投影的形状，椭圆的长轴可以认为是细胞具有的方向)。因为如截面是椭圆形的话，截面具有长轴和短轴，则沿着短轴比长轴要推动微柱要容易得多，则相对受力条件下形变也大。在一些延伸实施方式中，如果把细胞种在这种微柱上，细胞和微柱存在各向异性的力学交互，将会导致细胞沿着某一侧生长。而应用在流体上，则可用来测定流体的方向。
在第一至第四实施例中，所述微柱阵列的尺寸为：柱高10nm～500μm，柱间距10nm～50μm，柱上表面直径50nm～50μm。该尺寸范围内的微柱可以满足作为传感器使用的微柱的基本使用条件，即至少可形变且不倒伏。在此基础上，不同微柱阵列尺寸的调控还可以实现如下功能：例如，通过调控微柱的纵横比AspectRatio(在微柱的层面可以理解为高度和横截面直径/边长/长径之比)可以实现一定的微柱形变性能调控功能，从而对体内器官组织环境(例如不同硬度的骨组织和神经组织)实现更好的模拟。
此外，阵列的整体规格或者说一定面积基座11上的微柱12数量也会影响配体密度LigandDensity，即细胞在表面能找到可粘附的点的数量。如果微柱12阵列越稀疏，则细胞能找到的粘附点越小，对细胞行为会产生不小的影响。
微柱的形状中的截面积大小也将影响细胞黏附行为，因为细胞黏附形成黏附斑FocalAdhesion是需要一定面积的。如果是纳米微柱，则微柱截面面积小，对FocalAdhesion的形成会产生影响。
总而言之，结合材料本身特性和一定的微柱阵列尺寸，能够达到更符合需求的细胞支撑效果、芯片稳定性、测量精度。通过调控微柱阵列的分布还可以在一定程度上对细胞附着状态进行调控和影响。
在第一至第四实施例中，所述微柱12的材质为聚二甲基硅氧烷(PDMS)。在其他一些本发明的主要实施方式中，微柱12的材质还可以是其他一些高分子材料，例如硅基高分子聚合物、光阻高分子材料、导电高分子材料、温敏高分子材料等。本发明主要实施方式主要采用高分子材料的原因是当前高分子材料具有比较合适于本发明应用的可形变性能，但本 发明的实施并不需要把微柱材质限定为高分子材料，而完全应当和可以扩展至所有具有相应可形变性的材料，均可实现本发明的发明构思。简言之，微柱的材质必须满足的条件是具有一定的受力可形变性，以及在一些实施方式中，需要有一定的透光性，后者并非所有实施方式的必要条件，在选用透光性能受限的材料制备微柱的情形下，只要适当设置光信号发生装置和光信号检测装置的位置，同样也能够实现本发明的发明构思。
总体而言，微柱12的硬度(可形变性)可根据实际需求，通过尺寸(AspectRatio为主)、材料类型的选择以及高分子材料交联程度的控制、化学或物理表面处理等多重技术维度来进行调控。
请参照图5，图5为在顶部位置设有光线反射层(金)的微柱(聚二甲基硅氧烷)的扫描电子显微镜图像；其中，图5a为微柱的扫描电子显微镜图像；图5b为微柱顶部区域的元素表征图；图5c为微柱侧面区域(除顶部区域外)的元素表征图。通过图5的扫描电镜图像表征微柱的物质成分构成，可以确认微柱的顶部位置存在有Au元素，微柱的其余位置存在有Si元素。
第五实施例一种细胞机械力的检测装置
本实施例与第一至第四实施例的不同之处在于，微柱阵列的部分微柱12的顶部端面上设有具有细胞黏附作用的物质106，本实施方式采用的是细胞外基质分子中的胶原蛋白，在其他实施方式中还可以采用包括胶原蛋白在内、以及纤粘连蛋白、玻璃粘连蛋白、层粘连蛋白以及弹性蛋白原这些细胞外基质分子中的一种或若干种的结合。在另外一些实施方式中，还可以在微柱12阵列的全部或部分微柱的顶部端面上设其他类别的具有细胞黏附作用的物质，例如细胞外基质的模拟物质，如含有RGD粘附序列的多肽；或具有细胞黏附促进机制的物质106，包括聚赖氨酸；又或者是与细胞表面受体具有相互作用的物质。
在微柱12顶部端面上设置这样的具有细胞黏附作用的物质106可以有效促进细胞对微柱12的贴附，从而实现对细胞贴附、增殖、迁移、状态、分化等的调控。此外，如在微柱阵列的预设区域的部分微柱的顶部端面上设有具有细胞黏附作用的物质，例如Fibronectin等细胞外基质蛋白，则这些微柱可组成一定的形状。从而细胞倾向于粘附在特定位置和形状的微柱上，从而在控制细胞大小，形状及向性特征的情况下进行高通量力学测量。
本实施例细胞机械力的检测装置，细胞黏附物质有利于细胞/多细胞聚体在微柱上的稳定。
第六实施例一种细胞机械力的检测装置
本实施例与第五实施例不同之处在于，如第五实施例所述，微柱阵列的部分微柱12的顶部端面上设有具有细胞黏附作用的物质106，而本实施例中，所述顶部端面未设有具有细胞黏附作用的物质的那部分微柱12的柱面(端面或侧面)还设有具有细胞黏附抑制作用的物质，例如F-127。在其它一些具体实施例中，所述基座设置有具有细胞黏附抑制作用的物质107。具有细胞黏附抑制作用的物质107的设置使细胞更倾向于粘附在特定位置和形状(顶端上)的微柱上，从而在控制细胞大小，形状及向性特征的情况下进行高通量力学测量，使细胞机械力通过微柱顶部作用于微柱。
第七实施例一种细胞机械力的检测装置
本实施例与第一至第四实施例的不同之处在于，微柱12阵列的顶部端面上设有具有细胞黏附作用的物质的微柱构成预设的图案。具体而言，可通过微米印刷技术来印刷特定图案的细胞粘附分子层促进细胞在这些区域的贴附。所谓的预设图案可以是三角形、四边形、多边形、圆形，椭圆形等形状，预设图案的作用包括：首先，通过这些具有细胞黏附作用的物质构成的图案来控制细胞和细胞间接触，以方便实现高通量数据获取的诉求。其次，可通过使细胞形状统一达到数据处理中的降维效果，从而降低分析难度。再次，通过限制细胞贴附区域来达到控制细胞的大小，形状、向性、分化状态等的目的，甚至还可以通过控制肌动蛋 白丝Actinfilament调控细胞力学状态，从而达到某些特殊技术要求场景的要求。
在与本实施例大致相似的另一实施例中，未印刷的所述预设图案的部分可用具有细胞贴附抑制作用的物质如BSA(牛血清白蛋白)或F127(高分子非离子型表面活性剂)来抑制细胞在这些区域的贴附，从而实现定向贴附、对细胞形态的控制或模拟特定的细胞微环境。
在其它一些实施例中，具有细胞黏附作用的物质选用纤维粘连蛋白(Fibronectin，FN)作为示例性说明，但不用以限制本发明的实施方式。分别使用表面带有凸出正方形及长方形图案的聚二甲基矽氧烷微印章，并在微印章表面黏附纤连蛋白，采用微接触印刷的方式，将印章凸出部分的纤连蛋白转移到位于微柱的顶端金属反射层上方。接着，将微柱浸入F-127溶液，使得未设有纤连蛋白的部分具备抑制细胞黏附的效果。最后，将微柱用生理盐水彻底清洗后，将带有细胞膜染色成纤维细胞种植于微柱表面，再对细胞进行荧光成像(如图6中的a所示)，同时对细胞内的力场进行高分辨率的测量(如图6中的b所示)。请参照图6中的a和图6中的b，图6中的a为细胞粘附于顶部设有纤连蛋白的微柱群构成的预设图案的荧光成像图，可以看出细胞的黏附范围被限制于有纤连蛋白的区域；基于此，可以通过预设的图案来限制细胞贴附区域，进而对细胞的大小，形状、向性、分化状态等进行控制的情况下对细胞进行力学监测，图6中的b为在微柱上测得的光反射信号解算出来的细胞机械力大小分布图。
在其它一些实施例中，具有细胞黏附作用的物质选用OKT3抗体(即与细胞表面受体具有相互作用的物质)或纤连蛋白(Fibronectin，FN)作为示例性说明，但不用以限制本发明的实施方式。请参阅图7中的a-图7中的d，图7中的a为采用OKT3抗体作为具有细胞黏附作用的物质的试验示意图；图7中的b的上部分图像为细胞分别粘附于顶部设有OKT3抗体、纤连蛋白的微柱顶部的荧光成像图；图7中的b的下部分图像为在微柱上测得的光反射信号(反映细胞机械力大小)分布图；图7中的c为分别在OKT3抗体、纤连蛋白涂敷表面测得的力学大小对比图；图7中的d为将T细胞种植于OKT3抗体表面(微柱顶部)后发生的细胞力学动态变化图。具体的，上述试验可以在同一或不同细胞力检测装置的部分微柱顶端涂敷OKT3抗体或纤连蛋白，并将T细胞种植于细胞机械力检测装置的具有细胞黏附作用物质的表面。由图7中的a-图7中的d可知，在微柱表面涂敷与细胞表面受体有相互作用的物质(例如OKT3抗体)或纤连蛋白(Fibronectin，FN)的细胞机械力检测装置，可用于实时监测该物质对细胞的机械力影响及相互作用。
第八实施例一种细胞机械力的检测装置
本实施例与第一至第七实施例的不同之处在于，所述的细胞机械力的检测装置还包括细胞限制机构，所述细胞限制机构包括一个或若干个限制面16，所述限制面16为与基座11所在平面垂直、连接于所述基座11或与所述基座11一体成型的平面或曲面，且所述限制面16的高度高于微柱12并将预设数量的微柱12包绕在内。
本实施例设置的细胞限制机构的作用是单细胞隔离检测，即避免检测时细胞与细胞之间存在接触或黏连，以及限制细胞形态，从而方便高通量测试。根据不同的需求，细胞位置限定机构中的限制面16的数量或者围成的形状可以是不同的。例如，细胞位置限定机构包括的限制面16可以是一个圆柱面，也可以是首尾相接形成三角形截面形状并将一定数量微柱包围在内的3个平面、彼此垂直并首尾相接形成矩形形状将一定数量微柱包围在内的4个平面，首尾相接包围形成N边形的N个平面、或者横截面为类圆形的一个曲面等。也就是说，限制面16构成的横截面形状是可控的封闭形状，且其面积(或可理解为其空间内可容纳的微柱数量)也是可控的。
在实际的实施方式中，根据制程工艺的不同，细胞限制机构还可以通过以下的形式出现：
A，请参照图8，图8为具有细胞限制机构的细胞机械力的检测装置的结构示意图a，图中，所述细胞限制机构与基座11是一体成型的，即：在形成细胞限制机构的物质具有若 干个凹陷空间15，其凹陷空间15的壁面即为限制面16，凹陷空间15的深度即为限制面16的高度，凹陷空间15的底部即为基座11，每个凹陷空间15中有若干个微柱12。
B，请参照图9，图9为具有细胞限制机构的细胞机械力的检测装置的结构示意图b，图中，限制面16是粘结在基座11上的结构。
第九实施例一种细胞机械力的检测装置
本实施例与第八实施例的不同之处在于，本实施例中的细胞限制机构为硅薄膜。
具体的，请参照图10中的a-图10中的c，图10中的a为采用硅薄膜作为细胞限制机构的细胞机械力的检测装置的实物图，图10中的a中，硅薄膜在使用激光打孔后，黏附在基座上，每个孔中均设有微柱，通过硅薄膜限制细胞的形态和迁移，同时控制细胞与细胞之间存在接触或黏连；图10中的b为在光反射下采用硅薄膜作为细胞限制机构的细胞机械力的检测装置的荧光显微镜图，图10中的c为图10中的b的放大图。在一些实施例中，硅薄膜的每个孔的大小可以设置为与单细胞大小相适配，适合单一细胞贴附，从而限制细胞接触、细胞形态及其迁移范围。
第十实施例一种细胞或/和多细胞聚体表征系统
一种细胞/多细胞聚体相互作用的表征系统，包括第一或第二实施例所述的细胞机械力的检测装置1、光信号发生装置2和光信号检测装置3；所述光信号发生装置2和光信号检测装置3均位于所述细胞机械力的检测装置1中的基座11的下方，所述光信号发生装置2具有光源，所述光源发出的光线通过入射光路(相继穿过可透光的基座和可透光的微柱柱体)照射到微柱12的光线反射层13，发生反射，反射光经过反射光路(相继通过可透光的微柱柱体以及可透光的基座)进入光信号检测装置3。光信号检测装置3能够获取到微柱12与细胞发生接触前后的反射光信号。在另外一些实施方式中，这种细胞/多细胞聚体相互作用的表征系统还包括光信号分析装置4，可通过对比、分析、计算微柱12与细胞发生接触前后的反射光信号得到细胞机械力信息，包括细胞机械力的大小、方向、在一定时间范围内的变化情况等。
第十一实施例一种细胞或/和多细胞聚体表征系统
请参阅图4，图4为本发明第十一实施例相关的一种细胞/多细胞聚体相互作用的表征系统，包括第三实施例所述的细胞机械力的检测装置1，还包括光信号发生装置2和光信号检测装置3；所述光信号发生装置2和光信号检测装置3均位于所述细胞机械力的检测装置1中的基座11的上方，所述光信号发生装置2具有光源，所述光源发出的光线通过入射光路照射到光线反射层13，发生反射，光信号检测装置3能够获取到微柱12与细胞发生接触前后的反射光信号。
在本发明的实施例中，光信号检测装置可以是显微镜，电荷耦合元件CCD，互补金属氧化物半导体CMOS，光电倍增管PMT及光电转换器PT，胶片，或者其它具有相同功能的光信号检测元件，本发明不作具体限制。需要说明的是，在本发明的一些实施例中，当采用显微镜作为光信号检测装置时，则无需设置独立的光信号发生装置，可以直接将本发明的细胞机械力检测装置放置在显微镜的载物台上，以显微镜的光源作为光信号发生装置，以显微镜的物镜101(5倍物镜即可，不需依赖高倍数的光学物镜)作为光信号检测装置；当采用其它光信号检测装置，例如电荷耦合元件CCD时，则需要设置独立的光信号发生装置。在本发明的实施例中，光信号发生装置可以是LED，卤素灯，激光(例如，红外激光)，或其他光源，或其他具有这些光源的装置，本发明不作具体限制。
下面对本实施例相关的一种细胞/多细胞聚体相互作用的表征系统用于细胞机械力监测的可视化过程作具体介绍。
请参阅图11为采用本实施例的细胞/多细胞聚体相互作用的表征系统监测细胞机械力的荧光显微镜图像。具体的，将细胞(例如，本实施例采用成纤维细胞Fibroblast)放置于细 胞机械力检测装置的微柱上，光信号检测装置(例如，本实施例采用显微镜)可以将细胞机械力信息转化为光学信号并形成图像，以供可视化观测，并且能够实时反馈细胞机械力的变化。
第十二实施例一种细胞或/和多细胞聚体表征系统
请参阅图4，图4为本发明第十二实施例相关的一种细胞/多细胞聚体相互作用的表征系统，包括第三实施例所述的细胞机械力的检测装置1，还包括光信号发生装置2、光信号检测装置3和光信号分析装置4。所述光信号发生装置2和光信号检测装置3均位于所述细胞机械力的检测装置1中的基座11的上方；所述光信号发生装置2具有光源，所述光源发出的光线通过入射光路照射到光线反射层13，发生反射；分光器5可以为半透半反或其它等效的光学元件，主要目的是简化光路的设计；光信号检测装置3能够获取到微柱12与细胞发生接触前后的反射光信号；光信号分析装置4可通过对比、分析、计算微柱12与细胞发生接触前后的反射光信号得到细胞机械力信息，包括细胞机械力的大小、方向、在一定时间范围内的变化情况等。
在本发明的实施例中，光信号分析装置可以是光学图像分析软件ImageJ，Matlab，Fluoview，Python，或者其它具有相同功能的光学图像分析元件，或者这些分析软件的联合使用，本发明不作具体限制。
下面对本实施例相关的一种细胞/多细胞聚体相互作用的表征系统的检测、分析过程作具体介绍。
请参阅图12中的a-图12中的c，图12中的a为细胞/多细胞聚体的表征系统的结构示意图；图12中的b为光信号检测装置获取得到的细胞机械力检测装置光反射讯号的图像；图12中的c为力学大小及分布的可视化效果图。
如图12中的a所示，在细胞机械力检测装置上，每根微柱的顶部均设有金属反射层，侧面则设有抗反射层；在无细胞时，光线由下方照射微柱，会完全反射而被光信号检测装置(例如CCD相机)完全接收；但当细胞贴附在微柱上时，细胞移动产生的细胞力会使得微柱发生倾斜，从而降低了反射讯号，经过光反射讯号分析后，即可计算出细胞力强度。
进一步地，通过光信号检测装置(例如CCD相机)采集细胞机械力检测装置光反射信号的图像以及局部细胞黏附区域放大图像(如图12中的b所示)。接着，通过光信号分析装置对图12中的b的图像进行进一步的处理，使其转化为更为直观的力学大小及分布的可视化效果图12中的c。
具体处理过程如下：首先，基于图12中的b，获得明视野反射信号图(I，对焦于细胞上)；接着，通过对图像进行傅立叶变换后过滤高频信号，并进行逆傅立叶变换操作，从而计算获得到未偏移情况下的微柱反射讯号图像(I0)；接着，将I和I0图像进一步处理，以将反射讯号图转为更为直观的细胞力学图(I0讯号值减去I讯号值)后标准化获得更为直观的细胞机械力强度图j。
本发明实施例一到九也可以同时测定硬度，通过外力的作用下，使微柱转动刺入细胞完成细胞或/和多细胞聚体的硬度测定。
第十三实施例机械力的计算方法，力学与光反射信号的相互关系
本实施例结合第十至第十二实施例中任意一个所述的细胞/多细胞聚体相互作用的表征系统或第十四实施例所述的细胞机械力的检测方法，说明本发明实施例中机械力的计算方法；并利用流体当作外加力，以验证力学与光反射信号的相互关系。
请参阅图13，其中，图13中的a为流体开启前后微流体环境中细胞机械力检测装置的结构示意图；图13中的b和13中的c为流体开启前后微柱的明视场显微镜图、反射光信号分布图以及二者叠合效果图的对比图；图13中的d为流体开启前后光反射信号强度图；图13中的e为光反射信号与微柱偏移的线性关系图。其中，叠合效果图是指将微柱的明视场 显微镜图和反射光信号分布图叠合而成的效果图。
首先，如图13所示，将细胞机械力检测装置整合于微流体通道中，当外加流速增加，微柱产生位移，同时改变微柱表面反射层的角度(图13中的a-图13中的c)，由图13中的d可以看出，在流体开启前后，光反射信号由强转弱。具体的，利用流速强弱来改变微米柱的偏移量，使用共聚焦显微镜拍摄微柱顶部相对于微柱底部的位移，通过以下公式即可计算出每个微柱所受的机械力：
式中，F代表引起微柱偏转δ角度的机械力，E代表杨氏模量，kbend代表孤立纳米柱的理想弹簧常数，D代表微柱的直径，L代表微柱的高度。
同时，纪录微柱顶部的光反射信号，将光反射信号与微柱偏移量做图13中的e，即可得到光反射信号(反映细胞机械力)与微柱偏移的线性关系图及线性范围。
第十四实施例一种细胞机械力的检测方法
一种细胞机械力的检测方法，包括如下步骤：
使用如第十至第十二实施例中任意一个所述的细胞/多细胞聚体相互作用的表征系统中的光信号发生装置2发出光线。
使用如第十至第十二实施例中任意一个所述的细胞/多细胞聚体相互作用的表征系统中的光信号检测装置3检测经所述细胞机械力的检测装置1作用后的光线。所述光信号检测装置3能够获取到细胞机械力的检测装置1中的微柱12与细胞发生接触前后的反射光信号。在另外一些实施方式中，细胞/多细胞聚体相互作用的表征系统中的光信号分析装置4通过对比、分析、计算微柱12与细胞发生接触前后的反射光信号得到细胞机械力信息，包括细胞机械力的大小、方向、在一定时间范围内的变化情况等。
请参照图14中的a-图14中的d，图14中的a和图14中的b为细胞机械力的检测装置的微柱与细胞发生接触前以及发生接触后的结构示意图；图14中的b为光信号检测装置(CCD电子感光元件)获取的反射光信号，在细胞周边力场较大区域可以看到明显的反射讯号衰减；图14中的c为细胞迁移过程的监测图(对细胞膜染色之后，使用荧光光源激发，用CCD电子感光元件记录其迁移的过程)；图14中的d为细胞迁移过程中的反射光信号分布图(用CCD电子感光元件记录其迁移过程中的反射光信号变化)。由图14中的c和图14中的d可以看出，在细胞施力的部分反射光信号明显衰减。图14中的d示出了在细胞迁移过程中实时监测的反射光信号，并通过反射光信号实时反馈迁移过程中的机械力，可见通过光信号检测装置对细胞迁移过程中的反射光信号进行监测能够实时反馈细胞迁移过程中的细胞机械力的变化。
第十五实施例一种细胞机械力检测装置的制备方法
一种细胞机械力检测装置的制备方法，包括如下步骤：在微柱12的顶部或上半柱面铺设一层光线反射层13，获得顶部或上半柱面具有反射层的微柱12。
第十六实施例一种细胞机械力检测装置的制备方法
一种细胞机械力检测装置的制备方法，包括如下步骤：
在微柱12整体均匀镀一层抗反射层；将顶部或上半柱面的抗反射层去除；在微柱12的顶部或上半柱面铺设一层光线反射层13。
第十七实施例一种细胞机械力检测装置的制备方法
本实施例与第十五、十六实施例不同之处在于，所述步骤“在微柱12的顶部或上半柱面铺设一层光线反射层13”具体到：在微柱的顶部或上半柱面均匀溅射一层反射金属，获得顶部或上半柱面具有金属光线反射层的微柱。
第十八实施例一种细胞识别的方法(包括可视化定性识别，以及精确的定性、定量识别)
本实施例具体提供第十至第十二实施例中任意一个所述的细胞/多细胞聚体相互作用的表征系统或第十四实施例所述的细胞机械力的检测方法获取得到的细胞机械力信息，应用于识别细胞的方法。
请参照图15中的a至图15中的g，图15中的a为健康细胞和肺非小细胞癌细胞混合体系的荧光成像图；图15中的b为光信号检测装置获取得到的细胞机械力检测装置光反射讯号分布图；图15中的c为力学大小及分布的可视化效果图；图15中的d为图15中的c中的健康细胞和肺非小细胞癌细胞的代表性单细胞细胞力分布的放大图；图15中的e为健康细胞和肺非小细胞癌细胞在细胞形态上的对比图；图15中的f为健康细胞、肺非小细胞癌细胞以及这两种细胞以不同比例混合后的反射信号强弱的对比图；图15中的g为将图15中的c经过结构化处理后，基于结构化细胞信息处理得到的聚类分析图。
具体的，本实施例以健康细胞(Normal)和肺非小细胞癌细胞系(Cancer)作为检测对象，使用两种不同荧光染料(Dil&DIO)对健康细胞和肺癌细胞的细胞膜预染色，并以一定比例混合后添加到同一个细胞机械力检测装置(在另一些实施方式中，可以是添加到不同的独立的细胞机械力检测装置)上。
进一步地，通过光信号检测装置(本实施例使用显微镜)采集了细胞机械力检测装置光反射讯号的图像(如图15中的b所示)，而两种细胞内高分辨率的力场分布被光信号检测装置直接渲染即可转化成可读取的光强度衰减信号(反映细胞力强度)并显示在图片内(如图15中的c所示)。根据图15中的c图片显示的两种细胞的光衰减程度的不同，可以通过肉眼观察对两种细胞进行直观的区分(定性分析)。
进一步地，通过光信号分析装置对图15中的c中的光反射讯号进行进一步处理。具体地，本实施例通过光信号分析装置(本实施例使用ImageJ及Python分析软件，在其它实施例中还可以使用其他图像分析软件)对所获得的细胞力场的图15c进行信息采集，其中包括对各个细胞的多点进行细胞机械力大小信息采集，从而获取多个细胞中的多点细胞机械力大小数据；对获取的细胞机械力大小信息做预处理，形成结构化细胞信息；并根据结构化细胞信息分析得到健康细胞和肺非小细胞癌细胞在细胞形态上的对比结果图(如图15中的e所示)。
所述结构化细胞信息包括细胞数目、细胞特征数目和各细胞特征的特征信息(例如本实施例中的细胞黏附面积及细胞圆度)，此时结构化细胞信息可以视为一个特征矩阵(Feature Matrix)的二维矩阵，其中N为细胞数目，P为细胞特征数目，此处P＝2，即细胞特征为：细胞机械力大小、细胞机械力在细胞内的分布。
进一步地，以上述的结构化细胞信息作为输入数据，利用有监督机器(与不同的细胞膜染料(Dil&DIO)对两种细胞系进行预染色进行对比)学习建立细胞特征模型，并利用大量细胞的结构化细胞信息对所述细胞特征模型进行训练，得到如图15中的g所示的聚类分析图，然后将所获得的细胞特征模型应用于未知类型或未知状态的细胞的分类识别。由此可知，根据结构化的细胞特征数据(细胞机械力大小、细胞机械力在细胞内的分布)作为输入数据，可以利用光信号分析装置(本实施例使用ImageJ及Python分析软件，在其它实施例中还可以使用其他聚类分析软件)对正常的健康细胞及癌症细胞进行聚类分型，从而实现对未知细胞种类的识别。
图15中的e示出了不同细胞在形态(包括细胞黏附面积及细胞圆度)上没有统计学意义上的明显区别；图15中的f示出了正常细胞及肿瘤细胞反射讯号强度(反映细胞力)的明显差异，以及把正常细胞及肿瘤细胞按一定比例混合在一起后反射讯号强度和混合比例呈一定线性关系。由此可知，相比于细胞的其它特征(例如图15中的e中的细胞黏附面积、 细胞圆度等形态信息)，基于本发明的细胞机械力检测装置测得的细胞力学特征可对细胞的状态及类型进行更直观精确的识别(定量和定性分析)。
此外，从图15中的d和图15中的f的数据得出，肿瘤细胞比正常细胞显示出更高的机械力大小，并且分布更不均匀。可见，细胞机械力以图像方式可视化后，即可通过肉眼直观地看出不同细胞的力场特征具有明显区别；并且进一步地，通过图像分析软件对不同细胞各点的力场大小进行结构化处理后，综合分析得到图15中的e的细胞形态信息，图15中的f的反射讯号强度(反映细胞力)以及图15中的g的聚类分析图。本发明通过细胞各点的力场结构化信息的综合分析可以对不同细胞(例如本实施例中健康细胞以及非小细胞肺癌细胞)进行聚类分型及定量分析，从而实现对细胞种类的精确识别。
综上可知，基于本发明的细胞机械力检测装置，不仅可以通过肉眼直观区分以进行定性分析，还可以基于测得的细胞力学特征对细胞的状态及类型进行更直观精确的识别(定量和定性分析)，并且证实了以细胞力场作为标志物能够更好地对细胞类型进行区分。
上述的细胞识别方法，适用于各种因素，包括如实施方式一中所述外界因素对细胞/多细胞聚体作用之前、作用之中、作用之后的细胞/多细胞聚体的分型和识别。
第十九实施例一种细胞活力的检测方法
本实施例具体提供第十至第十二实施例中任意一个所述的细胞/多细胞聚体的表征系统或第十四实施例所述的细胞机械力的检测方法获取得到的细胞物理信息，应用于监测细胞的活力。
请参阅图16中的a-图16中的c，图16中的a为细胞活力检测方法的操作流程示意图；图16中的b为A549细胞在不同剂量的5FU处理24h后，MTT法测定得到的细胞活力以及本发明装置或系统或方法测定得到的细胞机械力的对比图；图16中的c为A549细胞在不同剂量的5FU处理不同时间后，MTT法测定得到的细胞活力以及本发明装置或系统或方法测定得到的细胞机械力的对比图。
具体地，本实施例将非小细胞肺癌细胞A549培养在多个细胞机械力检测装置上，分别加入不同剂量的抑制细胞增殖的药物5-氟尿嘧啶(5-FU)进行处理，并通过第十至第十二实施例中任意一个所述的细胞/多细胞聚体相互作用的表征系统或第十四实施例所述的细胞机械力的检测方法监测不同时间点的细胞机械力，通过CCK-8试剂盒监测不同时间点的细胞增殖和细胞毒性，同时以MTT测定法测定的细胞活力作为对照组，得到图16b和图16c的数据。
从图16中的b和图16中的c显示，通过传统MTT测定法和本发明所述装置或系统或方法进行测定后，MTT测定法测定的细胞活力以及细胞机械力所反映的细胞活力都是以剂量依赖性呈逐渐降低的趋势，即细胞机械力与细胞活力呈正相关。
此外，如图16中的b所示，在用不同剂量的5FU处理24h后，与对照组DMSO相比，通过机械力可以以更大的降低幅度反映细胞活力的降低，从而更加直观地对细胞活力进行评估。如图16中的c所示，在用5FU处理12h内，MTT法测定的细胞活力变化不明显；而通过测定机械力，可以在MTT法检测到细胞代谢活性降低之前的更早时间点即观测到细胞机械力的降低，具体的在0.5μM处理剂量下即可在6h时出现明显的降低趋势，在1μM处理剂量下即可在3h时出现明显的降低趋势，从而可以更加灵敏地表征细胞活力的降低。
综上可知，本实施例通过细胞机械力检测装置直接检测细胞机械力是评估细胞对药物反应活力的一种高度敏感且有效的方法。
第二十实施例一种基于细胞或/和多细胞聚体之间相互作用的表征方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞/多细胞聚体的细胞物理信息；具体地，其包括以下步骤：
将细胞/多细胞聚体放在细胞机械力检测装置上，加入细胞培养液至少使细胞/多细胞聚体与细胞培养液接触，静置培养半小时以上，继续加入细胞培养液培养直至细胞/多细胞聚体完全与微柱贴附之后，测定获取细胞/多细胞聚体的细胞机械力。
在一些具体实施例中，加入外界刺激，以检测在外界刺激下细胞/多细胞聚体细胞 机械力的动态变化；
其中，外界刺激可以在检测细胞机械力之前、之中加入。
不同细胞/多细胞聚体可分为：两个以上不同的细胞/多细胞聚体、一个细胞/多细胞聚体在不同时间下或外界刺激下形成的不同状态、一个细胞/多细胞聚体中中两个以上不同的区域；
两个以上不同的细胞/多细胞聚体：可以是病态细胞/多细胞聚体和正常细胞/多细胞聚体。
第二十一实施例一种基于细胞或/和多细胞聚体之间相互作用的分型和识别方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞/多细胞聚体的细胞物理信息；根据所述细胞物理信息识别细胞或/和多细胞聚体相互作用之前、之中和之后的细胞/多细胞聚体；
具体包括：
S1通过细胞机械力检测装置获取细胞/多细胞聚体之间相互作用之前、之中和之后的包含细胞/多细胞聚体的可视化细胞信息，包括细胞机械力变化大小、分布等可视化信息；
S2将所述可视化信息用于对待测细胞、多聚体的可视化识别。
在一些具体实施例中，
细胞机械力的检测装置还包括细胞限制机构，所述细胞限制机构包括一个或若干个限制面，所述限制面为与基座所在平面垂直、连接于所述基座或与所述基座一体成型的平面或曲面，且所述限制面的高度高于微柱并将预设数量的微柱包绕在内。可使相互作用的第一细胞/多细胞聚体，和第二细胞/多细胞聚体的限制在特定区域内以便于观察各自的细胞机械力变化，并且第一细胞/多细胞聚体，和第二细胞/多细胞聚体有接触到的机会，促使其相互作用，并且接触的面积是固定的，便于第一细胞/多细胞聚体，和第二细胞/多细胞聚体在相互作用时，依然保持是两个独立的细胞群，利于观察利于进行后续数据分析和定量。
可选地，细胞限制机构为硅薄膜，所述硅薄膜中设有若干个孔，所述孔中设有微柱，每个孔容置一个以上细胞或一个以上多细胞聚体。固定数量的细胞群能够有序地培养在微孔中。
第二十一实施例一种细胞或/和多细胞聚体的识别方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞或/和多细胞聚体细胞物理信息，根据所述细胞物理信息对细胞或/和多细胞进行分型和识别；
所述细胞物理信息是基于以下至少一种情况下获取的，
(1)细胞和多细胞聚体之间相互作用；
(2)细胞与细胞之间的相互作用；
(3)多细胞聚体与多细胞聚体之间的相互作用；
(4)不同生长时刻下的细胞或/和多细胞聚体；
(5)多细胞聚体内部的不同区域；
(6)物质对细胞或/和多细胞聚体之间的作用；
(7)其它物理、生物或化学因素对细胞或/和多细胞聚体作用；
具体包括：
S1将细胞/多细胞聚体贴附在微柱上，测定细胞物理信息；
S2加入其它细胞/多细胞聚体、物质或施加其它的作用过程中，作用之后，获取已贴附的细胞/多细胞聚体的细胞信息，所述细胞信息包括基于细胞机械力的检测装置获取的细胞/多细胞聚体中某点的细胞物理信息，所述细胞物理信息包括该点细胞机械力的大小，具体为：使用光信号检测装置(或者和光信号分析装置一起联用)对细胞机械力的检测装置上的多个细胞进行细胞信息采集，其中包括对各个细胞的多点进行细胞机械力大小信息采集，从而获取多个细胞中的多点细胞机械力大小数据；
S2、对所获取的细胞信息做预处理，形成结构化细胞信息；所述结构化细胞信息包括 细胞数目、细胞特征数目和各细胞特征的特征信息，此时结构化细胞信息可以视为一个的二维特征矩阵(Feature matrix)，其中N为细胞数目，P为细胞特征数目，此处P＝1，即细胞特征为细胞机械力大小；
S3、以结构化细胞信息作为输入数据，利用有监督、无监督或半监督的机器学习建立细胞特征模型，并将所述细胞特征模型应用于不同成长时刻的细胞或/和多细胞聚体，以及在其它因素下变化状态的分型和聚类，进一步对不同分型进行识别。
在其它一些实施例中，所述细胞物理信息还包括该点细胞机械力的方向。在其它一些实施例中，所述细胞物理信息还包括该点细胞机械力的大小或方向在一定时间间隔内的变化。在其它一些实施例中，所述细胞信息还包括细胞形貌信息。在其它一些实施例中，通过第二十施例的方法获取细胞物理信息。在其它一些实施例中，细胞机械力的检测装置还包括细胞限制机构，是相互作用的第一细胞/多细胞聚体，和第二细胞/多细胞聚体保持独立，但是又能互相作用。
本发明的细胞机械力检测装置，不仅可以通过肉眼直观区分以进行定性分析，还可以基于测得的细胞力学特征对细胞/多细胞聚体的状态进行更直观精确的识别(定量和定性分析)，并且证实了以细胞力场作为标志物能够更好地对类型进行区分。
第二十三实施例：一种通过细胞机械力基于细胞或细胞多聚体之间相互作用评估的方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞或/和多细胞聚体细胞物理信息，根据所述细胞物理信息对细胞及其多聚体之间的相互作用下的分型和识别，其方法为：
S1采用聚二甲基硅氧烷(PDMS)材料，通过微加工技术制成厚度为5-10微米的薄膜，并在薄膜上创建直径约为200微米的多个微孔。这些PDMS微孔薄膜经过Pluronic F127溶液处理并干燥后，被精确放置于细胞机械力检测装置的微柱阵列上。
S2将肺癌肿瘤细胞均匀分布于上述装置上，使得每个直径为200微米的微孔能容纳约20个肿瘤细胞，从而形成细胞多聚体。一天培养后，未能贴附的细胞被冲洗掉，此时，记录下每个微孔内细胞多聚体的细胞机械力信号。
S3加入单核球细胞THP-1，启动对细胞多聚体机械力变化的实时监控。这一过程不仅促进了固定数量细胞群在微孔中有序地培养，而且便于高通量地监测其机械力变化。本发明装置的设计确保每个细胞多聚体均有机会与另一种细胞接触，且由于细胞多聚体在微孔中的生长被限制，其与芯片的接触面积固定，大大有利于后续的数据分析和定量。
此外，这种微孔装置的应用不限于肿瘤细胞，同样适用于细胞多聚体(spheroid)或类器官(organoid)的研究，能够有效观察各种细胞对细胞多聚体或类器官的影响。这种方法为细胞机械力的研究提供了一个高效、精确的实验平台。
第二十四实施例一种通过细胞机械力评估免疫细胞对肿瘤多细胞球体作用的方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞或/和多细胞聚体细胞物理信息，进而识别免疫细胞与肿瘤多细胞球体之间的相互作用。具体操作步骤如下：
S1采用聚二甲基硅氧烷(PDMS)材料，通过微加工技术制备出厚度为5-10微米，每个微孔直径约200微米的微孔结构薄膜。将该PDMS微孔薄膜浸泡于Pluronic F127溶液中，干燥后铺设在细胞机械力检测装置的微柱阵列上。
随后，均匀分布肺癌肿瘤细胞A549于上述装置上，每个直径200微米的微孔中容纳约20个肿瘤细胞，形成细胞多聚体。一天培养后，移除未贴附的细胞，并记录下每个微孔内细胞多聚体的细胞机械力信号。
S2向系统中加入T细胞Jurkat细胞，并开始实时监控肿瘤细胞多聚体的细胞机械力变化。 此方法不仅使得固定数量的细胞群能够有序地在微孔中培养，而且有助于高通量监控其细胞机械力变化。通过本发明装置，确保每个细胞多聚体都有机会接触到免疫细胞，从而有效监测肿瘤细胞对免疫细胞的响应。
本实施例通过精细设计的实验步骤，不仅能够在微孔结构中有序培养固定数量的肿瘤细胞多聚体，还能够在细胞级别上评估免疫细胞对肿瘤多细胞球体的作用效果。通过实时监控细胞机械力的变化，本实施例为评估免疫细胞对肿瘤细胞杀伤效果提供了一种新颖且有效的方法。
第二十五实施例：一种通过细胞机械力评估肿瘤细胞对间皮细胞作用的方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞或/和多细胞聚体细胞物理信息，其是基于肿瘤细胞对血管内皮细胞的作用获取，并由此实现表征、分型识别和评估，具体步骤如下：
S1采用厚度为5-10微米的聚二甲基硅氧烷(PDMS)材料制备含有直径约200微米微孔的结构薄膜。将该PDMS微孔薄膜浸泡于Pluronic F127溶液中，干燥处理后铺放至细胞机械力检测装置的微柱阵列之上。
S2将间皮细胞系Met5A均匀分布于细胞机械力检测装置上，每个200微米直径的微孔中容纳约20个内皮细胞，形成细胞多聚体。一天培养后，去除未贴附的细胞，并记录下每个微孔内间皮细胞多聚体的细胞机械力信号。
S3向系统中添加卵癌细胞系OVCAR3，并开始实时监控间皮细胞的细胞机械力变化。本实施例不仅有序地在微孔中培养固定数量的间皮细胞，而且还能够通过高通量监控细胞机械力的变化，以识别肿瘤细胞与间皮细胞之间的相互作用。
通过本实施例，能够有效地监测并分析肿瘤细胞对间皮细胞的影响，为研究肿瘤的血管生成过程及其对间皮细胞的作用机制提供了一种新的实验方法和技术手段。
第二十六实施例：一种通过细胞机械力评估肿瘤细胞对血管内皮细胞作用的方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞或/和多细胞聚体细胞物理信息，其是基于肿瘤细胞对血管内皮细胞的作用获取，并由此实现表征、分型识别和评估，具体步骤如下：
S1采用厚度为5-10微米的聚二甲基硅氧烷(PDMS)材料制备含有直径约200微米微孔的结构薄膜。将该PDMS微孔薄膜浸泡于Pluronic F127溶液中，干燥处理后铺放至细胞机械力检测装置的微柱阵列之上。
S2将血管内皮细胞系HUVECs均匀分布于细胞机械力检测装置上，每个200微米直径的微孔中容纳约20个内皮细胞，形成细胞多聚体。一天培养后，去除未贴附的细胞，并记录下每个微孔内血管内皮细胞多聚体的细胞机械力信号。
S3向系统中添加肺癌细胞系A549，并开始实时监控血管内皮细胞的细胞机械力变化。本实施例不仅有序地在微孔中培养固定数量的血管内皮细胞，而且还能够通过高通量监控细胞机械力的变化，以识别肿瘤细胞与血管内皮细胞之间的相互作用。
通过本实施例，能够有效地监测并分析肿瘤细胞对血管内皮细胞的影响，为研究肿瘤的血管生成过程及其对血管内皮细胞的作用机制提供了一种新的实验方法和技术手段。
第二十七实施例：一种通过细胞机械力评估精细胞对卵子细胞作用的方法
本实施例旨在提供一种基于细胞机械力检测的方法，用于评估精细胞对卵子细胞的作用，从而在生殖生物学研究领域提供新的技术手段。该方法利用细胞机械力检测装置或表征系统，以及细胞机械力的检测方法来获取细胞或多细胞聚体的细胞机械力信息，并据此识别细胞间的相互作用。本实施例的具体操作步骤如下：
首先，采用聚二甲基硅氧烷(PDMS)材料制作含有直径约30微米微孔的结构薄膜，厚度为5-10微米。该PDMS微孔薄膜经Pluronic F127溶液处理后干燥，随后铺设于细胞机械力 检测装置的微柱阵列上。
随后，将鼠卵子细胞均匀分布至上述细胞机械力检测装置上，每个30微米直径的微孔中约容纳1个卵子细胞。这些卵子细胞在培养两小时后，去除未能贴附的细胞，然后继续培养六小时至一天。
之后，向该系统中加入鼠精细胞，实施受精过程，并开始实时监测卵子细胞的细胞机械力变化。通过精确控制每个微孔中只容纳一个卵子细胞，本方法能够精准观察和分析精细胞对单个卵子细胞的作用，从而为研究受精过程中细胞间的机械力学交互提供了有效的技术路径。通过本实施例，能够实现对精细胞与卵子细胞间相互作用的精细监测，为深入理解受精机制及早期胚胎发展提供了重要的实验基础。此外，该方法的应用可能还包括但不限于人类辅助生殖技术的优化和新药物或治疗方法的开发。
第二十八实施例一种通过细胞机械力评估细胞多聚体与其他因素作用结果的方法(仅细胞机械力大小，部分数据有标签、部分数据无标签)，包括如下步骤：
S1、获取已知不同细胞或/和多细胞聚体的多个细胞的细胞信息，其中部分细胞为若干种已知细胞类型或已知细胞状态的细胞，其余细胞为未知细胞类型或未知细胞状态的细胞；所述细胞信息为基于细胞机械力检测装置获取的细胞中某点的细胞机械力的大小。本步骤具体包括：使用细胞机械力检测装置对上述若干种细胞进行信息采集，其中包括对各个细胞的多点进行细胞机械力大小信息采集，从而获取多个细胞中的多点细胞机械力大小数据；
S2、对获取的细胞机械力大小信息做预处理，形成结构化细胞信息；所述结构化细胞信息包括细胞数目、细胞特征数目和各细胞特征的特征信息，此时结构化细胞信息可以视为一个MN×P特征矩阵(Feature matrix)的二维矩阵，其中N为细胞数目，P为细胞特征数目，此处P＝1，即细胞特征为：细胞机械力大小；
S3、以上述的结构化细胞信息作为输入数据，利用半监督机器学习建立细胞特征模型并利用大量细胞的结构化细胞信息(同时包括有标签和无标签的细胞)对所述细胞特征模型进行训练，然后将所述细胞特征模型应用于未知类型或未知状态的细胞的分类/聚类。
在另外一些与本实施例类似的实施方式里，可以以如下的方式进行优化或改进：对单个细胞而言，对其获取的多点细胞机械力大小信息做进一步的信息处理，例如计算出：单位面积细胞机械力大小的平均值；细胞机械力大小在细胞内的分布情况；等维度的信息，可以此作为新的细胞特征，添加入步骤S2中所述的二维特征矩阵，即扩充P的内容，然后经由后续的机器学习来获知哪种特征能够更好的将不同耐药程度细胞、非耐药细胞的分型细胞区别开来。
第二十九实施例一种通过细胞物理信息评估细胞或/和细胞多聚体的方法((细胞机械力的大小和方向，无标签)，包括如下步骤：
S1、获取细胞物理信息，所述细胞物理信息为基于细胞机械力检测装置获取的细胞中某点的细胞机械力的大小和方向，细胞硬度，具体包括：使用细胞机械力检测装置(本实施例中为纳米微柱传感器)对多个细胞进行细胞信息采集，其中包括对各个细胞的多点进行细胞机械力大小和方向的信息采集，从而获取多个细胞中的多点细胞机械力大小及方向数据；
S2、对获取的细胞机械力大小和方向的信息做预处理，形成结构化细胞信息；所述结构化细胞信息包括细胞数目、细胞特征数目和各细胞特征的特征信息，此时结构化细胞信息可以视为一个MN×P特征矩阵(Feature matrix)的二维矩阵，其中N为细胞数目， P为细胞特征数目，此处P＝2，即细胞特征为：细胞机械力大小、细胞机械力方向；
S3、以上述的结构化细胞信息作为输入数据，利用无监督机器学习建立细胞特征模型，并将所述细胞特征模型应用于未知类型或未知状态的细胞的聚类。
具体地，本实施例中的S2步骤对细胞信息做大致如下的处理：假设在一个细胞内共取到n个点的细胞机械力向量数据(大小和方向)，这些点位为：(i，∈{1，2，...n})，分别对应两个二维坐标：以及其中t0和tn分别对应纳米微柱初始以及位移后的点位。这样一来，即为每个坐标点上力的方向。此外，每个坐标点位上还应有一个标量信息，即力的大小d。如此即可通过已有数据估计出细胞轴方向以及中心点坐标、并以此为基准将每个细胞整理为一个长度相同的向量。例如，基于每个细胞中的各点位，中心点可以被计算为：细胞轴的计算方式为寻找距离最远的两点(x1，y1)以及(x2，y2)，通过如下公式来得到细胞轴：
请参见图17，图17为本发明第四实施例中对某点位位移信息标量化处理的示意图，图中每个点代表一个点位，各点位颜色深度由浅至深表示力由小到大。在获得每个细胞的细胞轴之后，可进一步对每个点位量化处理：计算每个点的位移矢量与细胞轴夹角为θ。每个点位可以继而与力的大小(标量)相结合，如将力的大小d视为权重，从而将各点位处理为一个标量si＝θi*di。如此一来，每个细胞的细胞信息都可以被整理为一个向量z＝(s1，...sn)。
在另外一些与本实施例类似的实施方式里，可以以如下的方式进行优化或改进：对单个细胞而言，对其获取的多点细胞机械力大小或细胞机械力方向信息做进一步的信息处理，例如计算出：单位面积细胞机械力大小的平均值；细胞机械力大小在细胞内的分布情况；细胞机械力向量在细胞内的分布情况；等维度的信息，可以此作为新的细胞特征，添加入步骤S2中所述的二维特征矩阵，即扩充P的内容，然后经由后续的机器学 习来获知哪种特征能够更好的将不同类型或状态的细胞区别开来。
第三十实施例一种通过细胞机械力评估细胞或细胞多聚体的方法(细胞机械力的大小和方向，有标签)，包括如下步骤：
S1、获取不同细胞/多细胞聚体的细胞物理信息，所述细胞信息为基于细胞机械力检测装置获取的细胞中某点的细胞机械力的大小和方向，以及细胞硬度，具体包括：使用细胞机械力检测装置对上述若干种细胞进行信息采集，其中包括对各个细胞的多点进行细胞机械力大小信息采集，从而获取多个细胞中的多点细胞机械力大小数据；
S2、对获取的细胞机械力大小，以及细胞硬度信息做预处理，形成结构化细胞信息；所述结构化细胞信息包括细胞数目、细胞特征数目和各细胞特征的特征信息，此时结构化细胞信息可以视为一个MN×P特征矩阵(Feature matrix)的二维矩阵，其中N为细胞数目，P为细胞特征数目，此处P＝2，即细胞特征为：细胞机械力大小、细胞机械力方向；
S3、以上述的结构化细胞信息作为输入数据，利用有监督机器学习建立细胞特征模型并利用大量细胞的结构化细胞信息对所述细胞特征模型进行训练，然后将所述细胞特征模型应用于未知类型或未知状态的细胞的分类。例如，本实施例采用随机森林(Random Forest，RF)算法进行显著特征的提取以及估计模型参数，然后应用于新的细胞，估计新细胞对应的标签，即将所述细胞特征模型应用于未知类型或未知状态的细胞的分类。而其他实施方式中，还可能采取支持向量机(Support Vector Machine，SVM)或深度学习等机器学习的算法/思路完成相应的模型建立和训练学习工作。
请参见图18和图19，图18和图19分别为本发明第五实施例扩展实施方式中所述将建立的细胞特征模型用于未知细胞或未知细胞表现型的识别的结果图A以及结果图B，图A中不同行代表不同细胞类型，不同列代表不同样本，图中黑点为采用随机森林所算法提取的前50个显著特征，或者可以称为显著点位，此处的点位是指一个细胞中的某个位置，从不同的位置获取的细胞物理信息不同。而图B则展示了利用前50显著特征(显著点位)对三种不同的细胞类型的显著区分效果。基于有标签数据学习到的显著特征可对数据降维可视化。后续亦可经由聚类算法，基于降维数据，对细胞进行分类和识别。
在另外一些与本实施例类似的实施方式里，可以以如下的方式进行优化或改进：对单个细胞而言，对其获取的多点细胞机械力大小或细胞机械力方向信息做进一步的信息处理，例如计算出：单位面积细胞机械力大小的平均值；细胞机械力大小在细胞内的分布情况；细胞机械力向量在细胞内的分布情况等维度的信息，可以此作为新的细胞特征，添加入步骤S2中所述的二维特征矩阵，即扩充P的内容，然后经由后续的机器学习来获知哪种特征能够更好的将不同类型或状态的细胞区别开来。
第三十一实施例一种通过细胞物理信息评估细胞或细胞多聚体的方法(细胞机械力大小和方向，部分数据有标签、部分数据无标签)，包括如下步骤：
S1、获取多个细胞的细胞物理信息，其中部分细胞为若干种已知细胞类型或已知细胞状态的细胞，其余细胞为未知细胞类型或未知细胞状态的细胞；所述细胞物理信息为基于细胞机械力检测装置获取的细胞中某点的细胞机械力的大小。具体包括：使用细胞机械力检测装置对上述若干种细胞进行信息采集，其中包括对各个细胞的多点进行细胞机械力大小信息采集，从而获取多个细胞中的多点细胞机械力大小数据；
S2、对获取的细胞机械力大小信息做预处理，形成结构化细胞信息；所述结构化细胞信息包括细胞数目、细胞特征数目和各细胞特征的特征信息，此时结构化细胞信息可以视为一个MN×P特征矩阵(Feature matrix)的二维矩阵，其中N为细胞数目，P为细 胞特征数目，此处P＝2，即细胞特征为：细胞机械力大小、细胞机械力方向；
S3、以上述的结构化细胞信息作为输入数据，利用半监督机器学习建立细胞特征模型并利用大量细胞的结构化细胞信息对所述细胞特征模型进行训练，然后将所述细胞特征模型应用于未知类型或未知状态的细胞的分类。
在另外一些与本实施例类似的实施方式里，可以以如下的方式进行优化或改进：对单个细胞而言，对其获取的多点细胞机械力大小或细胞机械力方向信息做进一步的信息处理，例如计算出：单位面积细胞机械力大小的平均值；细胞机械力大小在细胞内的分布情况；细胞机械力向量在细胞内的分布情况；等维度的信息，可以此作为新的细胞特征，添加入步骤S2中所述的二维特征矩阵，即扩充P的内容，然后经由后续的机器学习来获知哪种特征能够更好的将不同类型或状态的细胞区别开来。
第三十二实施例一种通过细胞物理信息评估细胞或细胞多聚体之间相互作用的方法(细胞机械力向量的瞬间值、细胞机械力向量在一定时间间隔内的变化情况，无标签)，包括如下步骤：
S1、获取细胞信息，所述细胞信息为基于细胞机械力检测装置获取的细胞中某点的细胞机械力的向量的瞬时值和该点细胞机械力向量在一定时间间隔内的变化情况；具体包括：使用细胞机械力检测装置对多个细胞进行细胞信息采集，其中包括对各个细胞的多点进行细胞机械力大小和方向的信息采集，从而获取多个细胞中的多点细胞机械力大小及方向数据；
S2、对获取的细胞机械力大小和方向的信息做预处理，形成结构化细胞信息；所述结构化细胞信息包括细胞数目、细胞特征数目和各细胞特征的特征信息，此时结构化细胞信息可以视为一个MN×P特征矩阵(Feature matrix)的二维矩阵，其中N为细胞数目，P为细胞特征数目。
S3、以上述的结构化细胞信息作为输入数据，利用无监督机器学习建立细胞特征模型，并将所述细胞特征模型应用于未知类型或未知状态的细胞的聚类。
本实施方式中，由于获取的不仅是细胞内某个点位的细胞机械力向量的瞬时值，还包括了其在一定时间间隔内的间隔情况，因此所获取的单个细胞的力学数据实际上可以类比为图像(瞬时值)或者视频(时间维度内的变化情况)，如此一来，如果将当前细胞覆盖下的点阵类比为图像中的像素点，而将各点位所记录的信息(力的大小、方向等多个细胞特征)可以类比为像素点所对应的色彩，就可以在后续机器学习中借鉴图像和视频数据处理领域的机器学习算法，例如的采取广泛应用在图像识别当中的机器学习，更确切点说，深度学习(deep learning)中的卷积神经网络(Convolutional Neural Network，CNN)来对数据建模分析。
第三十三实施例一种通过细胞机械力评估细胞或细胞多聚体之间相互作用的方法(细胞机械力向量的瞬间值、细胞机械力向量在一定时间间隔内的变化情况，有标签)，包括如下步骤：
S1、获取不同细胞类型或细胞状态(可以是已知或者未知)的细胞的细胞物理信息，所述细胞信息为基于细胞机械力检测装置获取的细胞中某点的细胞机械力的向量的瞬时值和该点细胞机械力向量在一定时间间隔内的变化情况；具体包括：使用细胞机械力检测装置对多个细胞进行细胞信息采集，其中包括对各个细胞的多点进行细胞机械力大小和方向的信息采集，从而获取多个细胞中的多点细胞机械力大小及方向数据；
S2、对获取的细胞机械力大小和方向的信息做预处理，形成结构化细胞信息；所述结构化细胞信息包括细胞数目、细胞特征数目和各细胞特征的特征信息，此时结构化细胞信息可以视为一个MN×P特征矩阵(Feature matrix)的二维矩阵，其中N为细胞数目， P为细胞特征数目。
S3、以上述的结构化细胞信息作为输入数据，利用有监督机器学习建立细胞特征模型并利用大量细胞的结构化细胞信息对所述细胞特征模型进行训练，然后将所述细胞特征模型应用于未知类型或未知状态的细胞的分类(即识别，本发明所述的“识别”应理解为广义的识别，既包括“分类”，即判定细胞的类型或细胞的状态；也包括“聚类”，即虽然不知具体的细胞状态或类型，但将可能具有相同或相似性质的、可能为相同或相似类型或状态的细胞进行聚类)。例如，本实施例采用随机森林(Random Forest，RF)算法进行显著特征的提取以及估计模型参数，然后应用于新的细胞，估计新细胞对应的标签，即将所述细胞特征模型应用于未知类型或未知状态的细胞的分类。而其他实施方式中，还可能采取支持向量机(Support Vector Machine，SVM)或深度学习等机器学习的算法/思路完成相应的模型建立和训练学习工作。
本实施方式中，由于获取的不仅是细胞内某个点位的细胞机械力向量的瞬时值，还包括了其在一定时间间隔内的间隔情况，因此所获取的单个细胞的力学数据实际上可以类比为图像(瞬时值)或者视频(一定时间维度内的多个瞬时值)，如此一来，如果将当前细胞覆盖下的点阵类比为图像中的像素点，而将各点位所记录的信息(力的大小、方向等多种细胞特征)可以类比为像素点所对应的色彩，就可以在后续机器学习中借鉴图像和视频数据处理领域的机器学习算法，例如的采取广泛应用在图像识别当中的机器学习，更确切点说，深度学习(deep learning)中的卷积神经网络(Convolutional Neural Network，CNN)来对数据建模分析。
第三十四实施例本实施例提供一种细胞物理表征装置、系统
如图1所示，本实施例提供了一种细胞物理表征装置，利用光线反射层、磁性材料中的一种或具有磁性的金属光线反射层来影响光反射信号强弱从而实现对细胞多模态生物物理信息的测量。
微柱12的顶端具有磁性金属(如铁、钴、镍等)的涂层(其他实施例中，还可以用其他磁性材料替代，并且磁性材料所设置的位置可以是微柱侧面或柱体内，只要使微柱能够在磁场下产生磁力作用即可)，该具有磁性金属的涂层可作为光线反射层105。在优选的实施方式中，微柱12的顶端设置的是磁性金属光线反射层。
需要提醒的是，本实施例中用了“涂层”一词，仅表示本实施例中的光线反射层13可以是涂覆工艺制备的，但并不因此限定光线反射层105一定是涂覆工艺制备的，例如也可以是溅射或蒸镀工艺制备的。
表征系统，由1个上述表征装置、光信号发射装置、光信号检测装置和磁场发射装置构成。其中，光信号发射装置用于发出预定的光线，光信号检测装置用于检测从光线反射层13反射的光线，磁场发射装置用于发射磁场与磁性金属产生磁力作用。光信号发射装置发出的光线通过入射光路照射到光线反射层13，光线反射层13反射的光线经过反射光路进入光信号检测装置。
当用上述细胞物理表征系统测量细胞多模态生物物理特征时，具体操作步骤为：
S1、将待测(表征)细胞培养在图1所示的细胞物理表征装置上，经过一至两天的培养，待测(表征)细胞完全贴附生长于物理表征装置上；
S2、用光信号发射装置发出预定光线；
S3、用光信号检测装置检测经细胞物理表征装置作用后的光线。本实施例中的“作用”可能仅为细胞物理表征装置微柱的顶端、侧面中的任意一个部位设置的光线反射层对预定光线产生的反射作用，也可能是微柱顶端和侧面都设置的光线反射层对预定光线产生的反射作用，优选地，还可能是微柱顶端设置的磁性金属光线反射层在磁场发射装置发射的特定方向和特定强度的磁场磁力作用下，微柱往一个方向倾斜、刺入待表征细胞、形变、牵拉或摆动，同时磁性金属光线反射层在微柱形变过程对光线产生反射作用。因此，采用本实施例系统可单独测量待表征细胞机械力，或可单独测量待表征细胞硬度，也可联合测量待表征细胞机械力和硬度。
如图31所示，在其它一些具体实施方式中，将本申请提供的2个细胞物理表征装置相 对设置构成双面结构，外侧为基座，内侧围合成细胞或多细胞聚体的三维容置腔(三明治结构)。三维容置腔的容积或高度可以根据实际需要进行调控。例如当待表征细胞为单细胞的相对两面，可以控制三维容置腔的高度在5nm-2mm之间，当待表征细胞为活体组织时，高度和容积大小都可以相应调整的更大一些，高度甚至可以达到5cm，容积可以达到30cm3。
第三十五实施例使用细胞力学芯片监测类器官贴附并评估化疗药物及免疫细胞攻击的反应
本实施例提供了一种-免疫-类器官芯片。通过监测类器官在芯片上的细胞机械力变化，评估类器官对化疗药物及免疫细胞攻击的反应。
S1.准备芯片：选择具有微柱结构的细胞力学芯片，微柱顶部涂敷适宜的细胞外基质(ECM)，以促进类器官的贴附和生长。在微柱侧面及微柱之间使用抗粘附处理。S2.种植类器官：将培养好的类器官置于力学芯片上。确保类器官与芯片表面接触，以便类器官贴附在芯片上。也可以直接在芯片上加入细胞和相应的细胞外基质物质，直接培养类器官并监测类器官发育过程中力学的反应和变化。S3.监控类器官贴附：利用光反射信号实时监测类器官在力学芯片上的贴附情况，观察细胞机械力的变化。S4.加入化疗药物：向类器官培养液中加入适量的化疗药物。S5.监测类器官对药物的反应：继续利用光反射信号和微柱偏转来监控类器官在药物作用下的细胞机械力及硬度的变化。观察类器官活力在药物作用下的减小情况(图20)或者加入免疫细胞(nk细胞或T细胞)共培养，监测类器官活力的变化。
第三十六实施例利用细胞力学芯片表征异质性肿瘤球体并筛选耐药或免疫逃逸个体
本实施例提供了一种-免疫-类器官芯片。通过监测异质性肿瘤球体上的细胞机械力变化，筛选出具有耐药或免疫逃逸的个体。
S1.准备芯片：选择具有微柱结构的细胞力学芯片，微柱顶部涂敷适宜的细胞外基质(ECM)，以促进肿瘤球体的贴附和生长。在微柱侧面及微柱之间使用抗粘附处理。S2.培养异质性肿瘤球体：在实验室中分别培养不同来源或具有不同耐药特性的肿瘤球体，可用限制性结构来约束球体的大小和形状(图22)。肿瘤球体亦可从患者提取分离。S3.种植肿瘤球体：将培养好的异质性肿瘤球体置于力学芯片上。确保肿瘤球体与芯片表面接触，以便肿瘤球体贴附在芯片上。S4.监测肿瘤球体贴附：利用光反射信号实时监测肿瘤球体在力学芯片上的贴附情况，观察细胞机械力的变化。S5.加入化疗药物：向肿瘤球体培养液中加入适量的化疗药物。或加入免疫细胞共培养。S6.监测肿瘤球体对药物的反应：继续利用光反射信号和微柱偏转来监控肿瘤球体在药物作用下的细胞机械力及硬度的变化。观察不同肿瘤球体在药物作用下的生长抑制情况，以筛选出具有耐药特性的个体(图21)。亦可获取免疫细胞对肿瘤球体的杀伤以及免疫细胞受药物影响的情况，以评估药物的靶向性。
总结：本实施例展示了如何利用细胞力学芯片表征异质性肿瘤球体并筛选耐药个体。通过监测细胞机械力的变化，可以为耐药性研究及个体化治疗提供重要信息。
第三十七实施例利用细胞力学芯片表征免疫-肿瘤细胞相互作用并评估药物干预效果
本实施例提供了一种-免疫-肿瘤芯片。通过监测研究肿瘤细胞力学特性与免疫细胞相互作用的关系，以及药物干预对这一关系的影响。
S1.准备芯片：选择具有微柱结构的细胞力学芯片，微柱顶部涂敷适宜的细胞外基质(ECM)，以促进肿瘤细胞和免疫细胞的贴附和生长。在微柱侧面及微柱之间使用抗粘附处理。S2.种植肿瘤细胞和免疫细胞：在力学芯片上分别种植肿瘤细胞和免疫细胞(如NK细胞或T细胞)，使它们相互作用。S3.监测肿瘤细胞的力学特性：利用光反射信号和微柱偏转实时监测肿瘤细胞在与免疫细胞相互作用过程中的细胞机械力及硬度变化。同时通过磁场引导微柱偏转，对细胞硬度进行测量。S4.观察免疫细胞对肿瘤细胞的杀伤作用：发现肿瘤细胞的力学大小与硬度正相关，较软的肿瘤细胞(较小的细胞机械力)难以被免疫细胞识别和杀伤。S5.药物干预：向培养液中加入使肿瘤细胞变硬的药物，观察肿瘤细胞的细胞机械力和硬度变化。S6.评估药物干预效果：在药物作用下，肿瘤细胞变硬，细胞机械力增大。 观察发现，免疫细胞对肿瘤细胞的杀伤作用随之增强。
总结：本实施例展示了如何利用细胞力学芯片表征免疫-肿瘤细胞的相互作用，以及药物干预对这一关系的影响。特别是细胞机械力和细胞硬度的正相关，表明同时表征这两个属性的重要性。通过研究肿瘤细胞的力学特性，可以为免疫治疗策略的优化提供。
本发明中所指的细胞力学芯片，可以是本发明所披露的细胞机械力检索装置，细胞/多细胞聚体相互作用表征和识别系统。或者其它可以通过微柱结合光信号反射的细胞力学芯片。
第三十八实施例一种通过细胞机械力评估表达蛋白、多肽和细胞/细胞多聚体之间相互作用的方法，本实施例提供上述任一项实施例中所述细胞机械力检测装置或细胞/细胞多聚体表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞/多细胞聚体的细胞机械力信息；根据所述细胞机械力信息识别物质与细胞或/和多细胞聚体之间的相互作用：通过获取转染后细胞的机械力信息，用于预测待测转染细胞的转染情况。根据转染情况，可选地，结合微流体微流控，可实现高通量生物筛选。本实施例，可应用于发现细胞转染成功及未转染成功，细胞机械力及硬度特征存在明显差异，首次发现胞内表达与不表达生物活性化合物(包含蛋白，多肽)的细胞机械力及硬度特征存在明显差异，根据这些物理特征结合人工智能训练识别模型，可以无创无标记快速辨别转染成功及表达生物活性化合物的高产细胞，结合微流体微流控，实现高通量生物筛选。
经过试验验证：加入培养体系中，未转染的细胞有可能不会被杀死，原因在于药物浓度过低，或者细胞密度过高。快速分裂的细胞相对于缓慢增殖细胞，更容易被杀死。对照细胞(未转染)可能在添加抗生素5-7天后才能被杀死，转染细胞(抗性克隆子)的克隆需要10-14天形成。
在一些具体实施例中，转染的目的是改变细胞的形态或功能，例如影响细胞骨架、细胞粘附或细胞分化等，那么转染成功的细胞可能会表现出不同于未转染或转染失败的细胞的机械力模式和大小12。在一些具体实施例中，转染的目的是改变细胞的基因表达或蛋白质水平，而不直接影响细胞形态或功能，那么转染成功和未成功的细胞可能没有明显区别。在一些具体实施例中，转染的方法是利用病毒载体或其他物理手段，而不是利用脂质体等化学试剂，那么转染过程本身可能会对细胞造成一定程度的损伤或应激反应，从而影响细胞机械力。本发明首次发现细胞转染成功及未转染成功的细胞机械力具有明显的变化。本发明的系统，具有实时表征，速度快，可以实时监测细胞状态，以及实验过程中潜在的细胞毒性，以及时优化转染方案。
第三十九实施例一种通过细胞机械力基于表达脂肪和细胞/细胞多聚体之间相互作用的表征、分类和识别方法和应用
本实施例提供上述任一项实施例中所述细胞机械力检测装置或细胞/细胞多聚体表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞/多细胞聚体的细胞物理信息；根据所述细胞物理信息识别脂肪与细胞或/和多细胞聚体之间的相互作用：脂肪细胞(adipocyte)是人体内最大的结缔组织细胞，主要功能是储存和动员脂类。脂肪细胞可分为白色脂肪细胞(white adipocyte)和棕色脂肪细胞(brown adipocyte)两大类，两者在形态、功能和来源方面都有很大差异。白色脂肪细胞呈单泡形，即一个白色脂肪细胞内含有一个大的富含三酰甘油的脂滴，占据了90％的细胞体积，将其他成分及核挤到边缘。白色脂肪组织主要负责储存能量，并在需要时释放游离脂肪酸供其他组织利用。白色脂肪组织还能分泌多种激素和因子，如瘦素、血管紧张素、血管内皮生长因子等，调节血压、食欲、糖代谢等生理过程。棕色脂肪细胞呈多泡形，即一个棕色脂肪细胞内含有许多小的富含三酰甘油的脂滴，并且含有高度团缩的线粒体，使得它们呈现棕色。棕色脂肪组织主要负责产生热量，并在寒冷或过度进食时消耗多余的能量。棕色脂肪组织还能分泌一些与白色不同或相反作用的激素和因子，如铁调素、神经元导向因子等，调节铁代谢、神经发生等生理过程。对于不同类型的脂肪细胞，在健康状态下它们各自发挥着正常而重要的作用；但在不健康状态下，如过度营养或营养不良时，它们可能会发生一些异常变化或转化，并影响人体健康。例如，在过度营养时，白色脂肪组织会增加数量和大小，并导致代谢紊乱、糖尿病、心血管疾病等；而棕色脂肪组织则会减少活性或转化为白色样特征，并降低能量消耗率。
发明人发现，细胞机械力在脂肪细胞分化的过程中存在明显动态变化，更能依次来实时监测白色脂肪，米色脂肪及棕色脂肪的转换过程。并为相关药物测试提供高通量的测试平台。 本发明的细胞机械力检测装置可用于监测细胞机械力在脂肪细胞分化的过程中存在明显动态变化，更能依次来实时监测白色脂肪，米色脂肪及棕色脂肪的转换过程。白色脂肪细胞和棕色脂肪细胞在形态和功能上有明显差异，这也反映在它们的细胞机械力上。一般来说，白色脂肪细胞比棕色脂肪细胞更硬，但产生的机械力更小。细胞机械力与细胞分化有密切关系，一些信号通路如Rho/ROCK通路可以调节脂肪前体细胞向白色或棕色脂肪分化的过程。在一些具体实施例中，通过改变培养基质的刚度或施加周期性拉伸等方法，可以影响脂肪前体细胞的分化方向和速率，并且可以检测到不同类型的脂肪分化后的特征标记物。在一些具体实施例中，一些药物如茶多酚类物质(epigallocatechin gallate)可以通过影响Rho/ROCK通路或其他信号通路来抑制白色脂肪分化或促进棕色脂肪分化，并且这些效果也可以通过机械力显微镜来观察。本实施例可以有效地研究不同类型的脂肪细胞在形态、功能和代谢方面的差异，并且可以筛选出一些有利于防治肥胖和相关疾病的药物候选物。
第四十实施例一种通过细胞机械力评估其它物质和细胞/细胞多聚体之间相互作用的方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或细胞/细胞多聚体表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞/多细胞聚体的细胞物理信息；根据所述细胞物理信息评估物质与细胞或/和多细胞聚体之间的相互作用：
在一些具体实施例中，在实时高通量监测细胞机械力，在合成生物学的应用中，结合半固态培养基及抗体或二抗，来有效验证转染成功或高产的细胞株。结构可用作机器学习。在一些具体实施例中，在合成生物学的应用中，可监测基因工程(如转染)对细胞的影响，检测大克隆附近的小克隆团或单个细胞，确保目标克隆的单克隆分离。可以结合分析克隆的结构和形态参数(例如,球体和形状)可以定义并排除可疑的(例如拉长)的克隆。在一些具体实施例中，在合成生物学的应用中，该系统可通过监测细胞的活力及状态，帮助需要建立最优的剂量反应曲线(dose-response curve or kill curve)确定杀死无抗性细胞的最低有效浓度。同时在药物筛选过程中对细胞进行实时监测以及时调整实验方案。在一些具体实施例中，除了单细胞外，还能实时监测多细胞聚体(包含肿瘤球体，类器官，活体组织等)的状态及动态变化，通量高，成本低。在一些具体实施例中，根据不同类型地力学特征和变化规律结合人工智能训练识别模型，进一步判断或预测单个或者多细胞聚体的类型、状态、行为及分化方向等。在一些具体实施例中，本发明适用于合成生物学，诊断、药物发现、肿瘤早筛、细胞疗法和精准医疗等领域。在一些具体实施例中，判断出所测量地细胞在培养过程中，是单个还是聚合生长成了多聚体；本发明的表征和识别系统以及方法，具有实时表征，速度快，可以实时监测细胞状态，以及实验过程中潜在的细胞毒性，以及时优化转染方案；在一些具体实施例中，可用于高产稳定细胞株的建立，对于大规模重组蛋白、抗体药的生产至关重要。针对目前广泛使用的CHO细胞，建立了多个亚型细胞库，可以高效的开发稳定高产表达的细胞株，提升开发速度。在一些具体实施例中，可用于质量控制的显微图像(捕获前后)和捕获期间的实时图像。利用哺乳动物细胞制备蛋白质药物取得了很大进展，并且随着生物技术与合成生物学的快速发展，许多基因工程药物和重组药物被合成，许多新药被发现，丰富了蛋白质药物的种类并提高了疾病治愈的几率。但是目前蛋白质药物70％都是由中国仓鼠卵巢细胞CHO生产，细胞内表达的蛋白质药物生长周期长导致筛选过程慢；本发明建立剂量反应曲线(dose-response curve or kill curve)确定杀死无抗性细胞的最低有效浓度。在一些具体实施例中，可应用于流式细胞术：可以使用荧光标记的抗体或荧光探针来标记目标蛋白质在所述细胞/细胞多聚体的表达情况，然后使用流式细胞仪对细胞进行分析和排序。在一些具体实施例中，药物开发通常依赖于大型化合物库的基于高通量细胞的筛选。然而，由于缺乏化学上的小型化和平行化方法，以及从其生物学筛选中严格分离和不合成生物活性化合物的合成，使得该方法昂贵且效率低下。本发明的表征系统、识别系统及方法展示了一个片上平台，基于解决方案的化合物库合成与高通量生物筛选(chemBIOS)相结合。在一些具体实施例中，发明人首次发现胞内表达与不表达生物活性化合物(包含蛋白，多肽)的细胞机械力特征存在明显差异，可以通过细胞机械力特征实现高表达克隆的筛选与分离；在一些具体实施例中，在研究细胞与大分子的相互作用的过程中，首次发现通过细胞力表征方法比传统基因或蛋白组学的表征方式更敏感，能更快，更灵敏探测到细胞的变化。在一些具体实施例中，除了单细胞外，还可应用于还能实时监测多细胞聚体(包含肿瘤球体，类器官，活体组织等)的状态及动态变化，通量高，成本低。在一些具体实施例中，在合成生物学应用 是指利用基因工程或其他手段来改造或创造具有特定功能的生物系统，例如高效地合成某种代谢产物或药。在一些具体实施例中，在在合成生物学应用中，通常需要通过转染、转化或其他方法将目标基因导入宿主细胞，并筛选出高表达的细胞株以提高生产效率。在利用细胞机械力表征来辨识和分选高表达细胞株的原理是：目标基因的表达可能会影响细胞的形态或功能，从而改变细胞与基质之间的相互作用力。例如，如果目标基因编码一个能够改变细胞骨架、粘附或分化状态的蛋白质，那么高表达该基因的细胞可能会与低表达或未转染的细胞在机械力模式和大小上有明显区别。在使用机械力显微镜来辨识和分选高表达时，可以结合其他方法如荧光检测、酶联免疫吸附试验等来验证结果，进一步提高所获取的细胞物理信息的准确率，以及预测的准确率。
第四十一实施例
本实施例提供上述任一项实施例中所述细胞机械力检测装置或细胞/细胞多聚体表征系统或上述任意一项方案中所述细胞机械力的检测方法获取细胞/多细胞聚体的细胞物理信息；根据所述细胞物理信息识别大分子(如蛋白.糖分子.脂质)或微生物与细胞或/和多细胞聚体之间的相互作用：
在一些具体实施例中，比较不同细胞外基质对细胞机械力的影响，其步骤为：S1.将不同的细胞外基质，如collagen、fibronectin和laminin，分别覆盖在细胞机械力检测装置微柱顶部，或是以微接触印刷，将细胞外基质印以特别图样的方式打印在微柱顶；而微柱侧边及微柱之间则使用Pluronic F127做抗粘附处理；S2.分别培养肺癌细胞A549至不同细胞外基质涂层的细胞机械力的检测上；S3.实时监控细胞力学，并比较细胞在不同细胞外基质涂层的细胞机械力强弱及分布。
在一些具体实施例中，检测抗体对细胞机械力的影响的方法，其步骤为：
S1.细胞机械力检测装置微柱顶端覆盖CD3抗体；而微柱侧边及微柱之间则使用Pluronic F127做抗粘附处理；S2.加入NFAT reporter(eGFP)Jurkat recombinant cell line，CD3抗体会吸引T细胞来与芯片接触，且此T细胞株被CD3抗体激活时会表达出绿色荧光蛋白；S3.实时监控细胞力学变化和绿色荧光蛋白的表现如图23。
在一些具体实施例中，检测糖分子对细胞机械力的影响的方法(糖蛋白或糖脂质)。S1.细胞机械力检测装置微柱顶端覆盖Lipopolysaccharides(LPS)；而微柱侧边及微柱之间则使用Pluronic F127做抗粘附处理；S2.加入THP1-ASC-GFP cell lines，LPS会吸引细胞来与芯片接触，且此monocyte细胞株被LPS激活时会表达出绿色荧光蛋白；S3.实时监控细胞力学变化和绿色荧光蛋白的表现。
在一些具体实施例中，检测蛋白对细胞机械力的影响的方法。
S1.细胞机械力检测装置微柱顶端覆盖zymosan；而微柱侧边及微柱之间则使用Pluronic F127做抗粘附处理；S2.加入THP1-ASC-GFP cell lines，LPS会吸引细胞来与芯片接触，且此monocyte细胞株被LPS激活时会表达出绿色荧光蛋白；S3.实时监控细胞力学变化和绿色荧光蛋白的表现。
在一些具体实施例中，检测微生物对细胞机械力的影响的方法
S1.细胞机械力检测装置微柱顶端覆盖已经多聚甲醛处理过的细菌；而微柱侧边及微柱之间则使用Pluronic F127做抗粘附处理；S2.加入THP1-ASC-GFP cell lines，LPS会吸引细胞来与芯片接触，且此monocyte细胞株被LPS激活时会表达出绿色荧光蛋白；S3.实时监控细胞力学变化和绿色荧光蛋白的表现。
第四十二实施例测量免疫细胞与分子相互作用及细胞激活过程的方法，通过对细胞机械力及硬度的表征
本实施例提供一种通过测量免疫细胞(如T细胞)机械力及硬度的变化，评估免疫细胞与分子(如CD3抗体)相互作用及细胞激活过程的方法。使用绿色荧光蛋白的表达作为细胞激活的标志，与细胞机械力和硬度的测量结果进行交叉验证。
S1、准备细胞机械力检测装置，其微柱顶端覆盖CD3抗体；而微柱侧面及微柱之间则使用Pluronic F127进行抗粘附处理。S2、向芯片中加入NFAT reporter(eGFP)Jurkat重组细胞株，CD3抗体会吸引T细胞与芯片接触，且该T细胞株在被CD3抗体激活时会表达绿色荧光蛋白。S3、使用表征系统，监控细胞的机械力学变化、绿色荧光蛋白的表达。通过分析 细胞在不同时间点的机械力变化，可以研究免疫细胞与分子相互作用及细胞激活过程。S4、使用压力变送装置，将微柱刺入细胞，添加磁场并通过检测光反射信号来表征细胞的硬度。S5、分析实验数据，监控免疫细胞与分子相互作用及细胞激活过程中，细胞机械力和硬度的变化。同时，观察绿色荧光蛋白的表达，与细胞机械力和硬度的测量结果进行交叉验证，以评估细胞在不同激活条件下的活性。
第四十三实施例通过测量细胞机械力和硬度辨识激活T细胞与未激活T细胞，并得知其激活比例的方法
本实施例提供一种通过测量细胞机械力和硬度辨识激活T细胞与未激活T细胞，并得知其激活比例的方法。此方法可用于对细胞疗法样品的表征并预测细胞疗法的成功概率。S1、将T细胞株NFAT reporter(eGFP)Jurkat cells培养在细胞机械力检测装置上，控制培养液的多寡，使T细胞与生物状态及应激表征装置接触，并测量未激活细胞的机械力大小。S2、向培养液中加入含有CD3抗体、CD28抗体及细胞激素，以激活T细胞；当T细胞被抗体激活时，会表达绿色荧光蛋白。S3、实时监控每个T细胞的机械力变化和绿色荧光蛋白表达。S4、使用压力变送装置，将微柱刺入细胞，添加磁场并通过检测光反射信号来表征细胞的硬度。S5、发现T细胞被激活时，细胞机械力会逐渐增强，与绿色荧光成正向关系。S6、将每个T细胞激活过程的细胞机械力变化与硬度变化输入数据库，利用机器学习方法，建立一个可利用细胞机械力及硬度特征，空间分布和时间动态变化，来判断T细胞激活程度的模型。S7、从捐赠者的外周血单个核细胞(PBMC)中，使用CD4及CD8抗体分离出T细胞。S8、将分离出的T细胞pool培养在细胞机械力检测装置上，控制培养液的多寡，使所有T细胞与细胞机械力检测装置接触。S9、记录所有T细胞的机械力大小分布，使用之前建立的模型进行运算分析，得知捐赠者体内激活和非激活T细胞的比例。该数值可用于预测细胞疗法的成功几率。
第四十四实施例应用微流控与细胞机械力检测装置于CAR-T细胞疗法体外培养监控的技术
本实施例提供一种应用微流控与细胞机械力检测装置于CAR-T细胞疗法体外培养监控的技术，以便在体外环境中更有效地监控和评估CAR-T细胞的生长、激活和疗效。S1、生物状态及应激表征装置芯片微柱顶端覆盖CD3及CD28抗体；而微柱侧面及微柱之间则使用Pluronic F127进行抗粘附处理。S2、将芯片铺设在微流控设备的底部。S3、向微流控设备中注入从捐赠者的外周血单个核细胞(PBMCs)中分离出的T细胞，并激活T细胞。同时，通过监测细胞机械力判断是否所有T细胞已完全激活。S4、在T细胞完全激活后，加入lentivirus进行转导(transduction)，使T细胞表达能辨识癌细胞表面蛋白的抗体特异性序列(sc-fv)的嵌合抗原受体。S5、将转导后的T细胞(CAR-T)从微流控中取出，继续培养放大。S6、将PDMS微孔薄膜(microwell)铺放在细胞机械力检测装置上，并将肿瘤细胞、肿瘤多细胞球体或肿瘤类器官培养在含有微孔细胞机械力检测装置上，细胞将有序地生长在微孔中。S7、向含有肿瘤细胞的细胞机械力检测装置中加入CAR-T细胞，实时监测肿瘤细胞的细胞机械力。当CAR-T细胞能有效杀死肿瘤细胞时，肿瘤细胞的细胞机械力会大幅下降。通过本实施例，可以在体外环境中更有效地监控和评估CAR-T细胞在激活、扩增和杀死肿瘤细胞过程中的细胞力学特性，从而为CAR-T细胞疗法提供更准确的数据支持。
第四十五实施例应用微流控与细胞机械力检测装置于CAR-T细胞疗法体外培养监控的技术
本实施例提供一种应用微流控与细胞机械力检测装置于CAR-T细胞疗法体外培养监控的技术，以便在体外环境中更有效地监控和评估CAR-T细胞的生长、激活和疗效。S1、表征装置微柱顶端覆盖CD3及CD28抗体；而微柱侧面及微柱之间则使用Pluronic F127进行抗粘附处理。S2、将生物状态及应激表征装置铺设在微流控设备的底部。S3、向微流控设备中注入从捐赠者的外周血单个核细胞(PBMCs)中分离出的T细胞，并激活T细胞。同时，通过监测细胞机械力判断是否所有T细胞已完全激活。S4、在T细胞完全激活后，利用CRISPR-Cas9技术，让T细胞的T cell receptors(TCR)改造成能够表达辨识癌细胞抗原。S5、将改造后的TCR-T细胞从微流控中取出，继续培养放大。S6、将PDMS微孔薄膜(microwell)铺放在细胞机械力检测装置上，并将肿瘤细胞、肿瘤多细胞球体或肿瘤类器官培养在含有微孔细胞机械力检测装置上，细胞将有序地生长在微孔中。S7、向含有肿瘤细胞的细胞机械力检测装置中加入TCR-T细胞，实时监测肿瘤细胞的细胞机械力。当TCR-T细胞能有效杀死肿 瘤细胞时，肿瘤细胞的细胞机械力会大幅下降。通过本实施例，可以在体外环境中更有效地监控和评估TCR-T细胞在激活、扩增和杀死肿瘤细胞过程中的细胞力学特性，从而为TCR-T细胞疗法提供更准确的数据支持。
第四十六实施例利用表征系统监控细胞机械力变化来判断抗体药物复合物(antibody-drug conjugate)在治疗悬浮性癌症的效果，本实施例提供一种利用表征系统监控细胞机械力变化来判断抗体药物复合物(antibody-drug conjugate)在治疗悬浮性癌症的效果的方法。S1、在表征系统的微柱顶端覆盖抗体药物复合物，微柱侧边及微柱之间则使用Pluronic F127做抗粘附处理。S2、将血癌细胞培养于此装置上，抗体涂层能吸引血癌到装置上并与装置接触。S3、通过检测光反射信号强弱来实时监控血癌细胞的细胞机械力；当抗体药物复合物能有效抑制细胞生长或能让细胞进入凋亡时，细胞机械力会大幅度地降低。通过使用表征系统监测细胞机械力的变化可以更好地了解抗体药物复合物对悬浮性癌症的治疗效果。实时监控细胞机械力有助于更好地评估抗体药物复合物的疗效，从而优化药物设计和治疗方案。
第四十七实施例利用表征系统监控细胞机械力和硬度变化来判断抗体药物复合物在治疗贴壁性癌症的效果，本实施例提供一种通过监测细胞机械力及硬度的变化，评估抗体药物复合物对贴壁性癌症治疗效果的方法。S1、将表征系统的微柱顶端覆盖细胞外基质，微柱侧面，微柱间及基座使用Pluronic F127进行抗粘附处理。S2、在表征系统上培养肺癌细胞，经过一天培养，使细胞完全贴附在装置上。S3、将抗体药物复合物加入培养液中。S4、通过检测光反射信号强弱，实时监控肺癌细胞的细胞机械力和硬度。当抗体药物复合物有效抑制细胞生长或使细胞进入凋亡时，细胞机械力和硬度会显著降低。通过表征系统监测细胞机械力和硬度的变化，可为评估抗体药物复合物对贴壁性癌症治疗效果提供重要依据。
第四十八实施例利用监控活组织的细胞机械力变化来判断抗体药物复合物的治疗效果
本实施例旨在提供一种通过监测活组织细胞机械力变化，评估抗体药物复合物对肿瘤细胞治疗效果的方法。S1、表征系统的微柱顶端覆盖细胞外基质，微柱侧面及微柱间使用Pluronic F127进行抗粘附处理。S2、使用组织切片机将新鲜的肿瘤组织切成厚度为200微米的薄片。S3、将活组织薄片铺设在细胞机械力检测装置上，经过一天培养，使组织完全贴附在芯片上。已知肿瘤细胞区块的细胞机械力比非肿瘤区块强。S4、将抗体药物复合物加入培养液中。S5、通过检测光反射信号强弱，实时监控肿瘤细胞区块和非肿瘤细胞区块的细胞机械力。当抗体药物复合物有效抑制细胞生长或使细胞进入凋亡时，细胞机械力会显著降低。S6、此外，通过比较肿瘤细胞区块和非肿瘤细胞区块的细胞机械力变化，可了解抗体药物复合物是否能专一杀死肿瘤细胞。并评估对正常细胞的影响。本实施例通过监测活组织的细胞机械力变化，为评估抗体药物复合物对肿瘤细胞治疗效果提供重要依据。
第四十九实施例利用监控多细胞球体之细胞力学变化来判断抗体药物复合物治疗效果
本实施例旨在提供一种利用监控多细胞球体之细胞力学变化来判断抗体药物复合物治疗效果的方法。S1、制备表征系统，微柱顶端部具有细胞外基质，微柱侧边及微柱之间则使用Pluronic F127做抗粘附处理。S2、将腫瘤細胞形成多细胞球体培养于此芯片上，经过一天培养，让多细胞球体完全贴附于芯片上。在培养液中加入抗体药物复合物。S3、利用检测光反射信号强弱的方法来实时监控多细胞球体的细胞力学变化。当抗体药物复合物能有效抑制细胞生长或能让细胞进入凋亡时，多细胞球体的细胞力学力会大幅度地降低。
第五十实施例利用同时比较肿瘤细胞与非肿瘤细胞之细胞机械力变化来判断抗体药物复合体的靶向性
本实施例旨在提供一种利用监控细胞机械力判断抗体药物复合体的靶向性的方法。
S1、细胞机械力检测装置微柱顶端部具有细胞外基质，微柱侧边及微柱之间则使用Pluronic F127做抗粘附处理。S2、将带有红色荧光的肿瘤细胞以及带有绿色荧光的非肿瘤细胞等比例混合后，培养在此细胞机械力检测装置上，经过一天培养，让细胞完全贴附于芯片上。加入抗体药物复合体到培养液中。S3、检测光反射信号强弱来同时监控两种细胞的细胞机械力。当抗体药物复合体能专一抑制肿瘤细胞生长，肿瘤细胞的细胞机械力降低幅度会大于非肿瘤细胞，或非肿瘤细胞的细胞机械力不受抗体药物复合体影响。
第五十一实施例一种体外器官芯片
本实施例提供一种体外器官芯片，其包括提供上述任一项实施例中所述细胞机械力检测装置或检测系统，其还包括：电级装置，微柱为导电材料制成，电极装置作用于所述微柱，实现对器官或细胞的电刺激。其中，器官相关细胞和组织可种植于微柱上，细胞和组织的细胞机械力可使微柱发生形变，将其转化为光学信号；其中，微柱根据所述器官，设置相应软硬度和长度，以使芯片的微环境适合于器官的真实的结构环境。通过调节微柱长度及交联比例控制微柱的软硬度，以模拟相应组织的软硬度或模拟病理条件下的微环境(如心脏纤维化)；在一些具体实施例中，为了更真实的模拟微环境，微柱表面设置有ECM；在一些具体实施例中，为了更真实的模拟微环境，将所述器官相关细胞或/和组织与ECM的混合物种植微柱上；在一些具体实施例中，为了更真实的模拟微环境，微柱表面带有向性的ECM图层，比如可以来模拟心脏ECM微结构并引导心肌细胞向性；在一些具体实施例中，种植的方法包括：3D打印；在一些具体实施例中，若所述器官为心脏，所述细胞包括心肌细胞、平滑肌细胞、血管内皮细胞、成纤维细胞、干细胞、免疫细胞中的一种或两种以上的组合。微柱顶端可涂敷脱心脏相关的细胞ECM，人工重组心脏ECM，或将细胞包被在包含心脏ECM的凝胶中以模拟心脏的细胞外基质组分。在一些具体实施例中，为了模拟微环境的机械运动芯片，其还包括机械模拟装置，所述机械模拟装置为对所述芯片主体进行拉伸的机械拉伸装置；或为设置在微柱底部的可充气变形的柔性薄膜；所述柔性薄膜上端连接于微柱，下端连接于所述基座，或所述基座为柔性薄膜。在一些具体实施例中，其还包括微流控装置，所述微流控装置对所述器官相关细胞、器官组织施加流场刺激。在一些具体实施例中，可施加药物，机械力，生化，电场及流场等刺激，或是一种以上刺激的组合，以应用于在外界刺激中每个细胞和器官状态的识别。
第五十二实施例一种体外器官芯片建立体外器官和细胞模型，并且对细胞和器官组织进行表征的方法：S1采集相应器官组织包括生理及病理状态下的微环境参数，并根据所述参数制得相应的所述体外器官芯片；S2将包括所述器官相关细胞或/和组织的培养物种植于所述体外器官芯片上；S3可选择地添加包括药物、机械力、生化、电场、流场中一种或两种以上刺激的组合，作用于所述培养物上；S4通过所述体外器官芯片获取每一个细胞，以及组织的细胞机械力的变化，实现每一个细胞和器官组织的表征。本实施例中，通过表征可分选出特定的细胞或组织。本实施例中，体外器官芯片在筛选所述器官治疗药物中、以及在器官模型在生理和病例状态下研究中的应用。
第五十三实施例一种体外器官芯片来检测心肌细胞收缩-舒张的方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或检测系统或上述任意一项方案中所述细胞机械力的检测方法、体外器官芯片获取细胞物理信息；具体包括：S1将以高浓度EDTA溶液灌注过的小鼠心脏切成碎后，以collagenase将其分解单一细胞；S2含细胞的悬浮液静置20分后，心肌细胞会沉淀于管底；S3将取得的心肌细胞直接培养在体外器官芯片上；S4经数天培养，心肌细胞会出现规律收缩；S5以高速摄影的方式，每一秒拍摄100张照片，观察心肌细胞每次收缩-舒张周期时的力学变化，连续记录下多次收缩舒张周期后，即可换算出心肌细胞收缩频率，请参阅图24。
第五十四实施例一种体外器官芯片来检测来检测药物对心肌细胞收缩-舒张频率的方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或检测系统或上述任意一项方案中所述细胞机械力的检测方法、体外器官芯片获取细胞物理信息；S1将以高浓度EDTA溶液灌注过的小鼠心脏切成碎后，以collagenase将其分解单一细胞；S2含细胞的悬浮液静置20分后，心肌细胞会沉淀于管底；S3将取得的心肌细胞直接培养在体外器官芯片上；S4经数天培养，心肌细胞会出现规律收缩；S5以高速摄影的方式，每一秒拍摄100张照片，观察心肌细胞每次收缩-舒张周期时的力学变化，连续记录下多次收缩舒张周期后， 即可换算出心肌细胞收缩频率；S6接着加入钙离子阻断剂Nifedipine药物，持续纪录心肌细胞力学变化，可观察到心肌细胞收缩频率变慢。
第五十五实施例一种体外器官芯片打印细胞外基质图样应用于心肌细胞排列及量测心肌细胞收缩-舒张频率的方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或检测系统或上述任意一项方案中所述细胞机械力的检测方法、体外器官芯片获取细胞物理信息；S1使用微接触印刷(microcontactprinting)，将细胞外基质以特别图样的方式印至到力学芯片上；S2培养老鼠心肌细胞于此力学芯片上，细胞会贴附生长于有细胞外基质的区域，形成特别的图样规律地排列；S3经数天培养，心肌细胞会出现规律收缩；S4以高速摄影的方式，每一秒拍摄100张照片，观察心肌细胞每次收缩-舒张周期时的力学变化，连续记录下多次收缩舒张周期后，即可换算出心肌细胞收缩频率。
第五十六实施例一种体外器官芯片测量纤维细胞分化成脂肪细胞之细胞机械力变化的方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或检测系统或上述任意一项方案中所述细胞机械力的检测方法、体外器官芯片获取细胞物理信息；S1将老鼠纤维细胞株NIH3T3-L1培养于力学芯片上，并开始记录细胞机械力；S2将培养液置换成含有methylisobutylxanthine,dexamethasone和insulin的培养液；S3培养至第三天时，将培养液置换成含有insulin的培养液；S4培养至第六天时，将培养液置换成正常的DMEM培养液；S5约第十天左右，NIH3T3-L1可分化成脂肪细胞，可利用Oil Red O染色来监测脂质积累而得知已分化成脂肪细胞的细胞，并以CalceinAM染色来排除死亡细胞。S6纪录整个分化过程之细胞机械力变化，请参阅图25。
第五十七实施例一种比较棕色脂肪细胞以及白色脂肪细胞的细胞机械力
本实施例提供上述任一项实施例中所述细胞机械力检测装置或检测系统或上述任意一项方案中所述细胞机械力的检测方法、体外器官芯片获取细胞物理信息；S1从刚出生的小鼠中，分别取出棕色脂肪组织以及白色脂肪组织，切成小块后，使用collagenase将其消化分解成单一细胞，经过滤离心后，得到前脂肪细胞(preadipocytes)；S2将从棕色脂肪组织和白色脂肪组织取得的前脂肪细胞分别培养放大于培养盘；S3经数天培养后，将两种前脂肪细胞移至力学芯片上培养，同时开始记录细胞机械力；S4加入含有methylisobutylxanthine,dexamethasone和insulin的培养液到从白色脂肪组织分离出的前脂肪细胞，将其分化成白色脂肪细胞。加入含有methylisobutylxanthine,dexamethasone,insulin和triiodothyronine的培养液到从棕色脂肪组织分离出的前脂肪细胞，将其分化成棕色脂肪细胞；S5经过两天培养后，将培养液置换成含有insulin的培养液，如需分化成棕色脂肪细胞，则需再加入triiodothyronine；S6可利用Oil Red O染色来监测脂质积累而得知已分化成脂肪细胞的细胞，并以CalceinAM染色来排除死亡细胞；S7纪录整个分化过程之细胞机械力变化，并比较色脂肪细胞以及白色脂肪细胞的细胞机械力。
第五十八实施例一种干细胞诱导的心脏器官模型及其表征方法
本实施例具体提供了一种干细胞诱导心脏模型，在细胞机械力检测装置上用微接触印刷的方式印制带有向性的ECM，在上面种植干细胞并诱导心肌分化方向。在诱导的过程中使用光反射讯号和磁场诱导微柱偏转来监控细胞机械力及硬度的变化。S1、在力学芯片微柱顶端部利用微接触印刷技术制备带有向性的细胞外基质(ECM)。S2、将微柱侧边及微柱之间使用抗粘附处理，例如Pluronic F127。S3、将干细胞接种于带有向性ECM的力学芯片上，让细胞完全贴附于芯片上。S4、添加适当的诱导因子，以引导干细胞向心肌细胞分化。S5、在诱导过程中，利用光反射信号监控细胞与微柱之间的相互作用，从而实时检测细胞机械力的变化。S6、利用磁场诱导微柱偏转，测量细胞对微柱施加的力，进一步评估细胞硬度的变化。S7、分析光反射信号和磁场诱导微柱偏转数据，以评估心肌细胞分化过程中细胞机 械力及硬度的变化，S8、对细胞及细胞外基质以及相应的对照组进行荧光染色，确定细胞及ECM向性特征(图26)。该干细胞诱导心脏芯片为心肌细胞分化研究提供有力依据。
第五十九实施例一种干细胞诱导的组织特异性软骨模型及其表征方法
本实施例具体提供了一种干细胞诱导软骨模型，在芯片上涂敷软骨组织提取的软骨特异性ECM，在上方种植成体干细胞(MSC)并诱导软骨方向分化，在诱导的过程中使用光反射讯号和磁场诱导微柱偏转来监控细胞机械力及硬度的变化。并与荧光染色结果及组化染色结果作比较。S1、在力学芯片微柱顶端部涂敷软骨组织提取的软骨特异性细胞外基质(ECM)。S2、将微柱侧边及微柱之间使用抗粘附处理，例如Pluronic F127。S3、将成体干细胞(MSC)接种于涂敷软骨特异性ECM的力学芯片上，让细胞完全贴附于芯片上。S4、添加适当的诱导因子，以引导成体干细胞向软骨细胞分化。S5、在诱导过程中，利用光反射信号监控细胞与微柱之间的相互作用，从而实时检测细胞机械力的变化。S6、利用磁场诱导微柱偏转，测量细胞对微柱施加的力，进一步评估细胞硬度的变化。S7、在诱导分化的过程中，进行荧光染色及组化染色，以评估软骨分化相关标志物的表达情况。S8、分析光反射信号和磁场诱导微柱偏转数据，与荧光染色结果及组化染色结果进行比较，评估软骨分化过程中细胞机械力及硬度的变化，为软骨细胞分化研究提供有力依据(图27)。
第六十实施例一种肺肿瘤模型及其表征方法
本实施例具体提供了一种肺肿瘤模型及表征方法，在双面三明治结构芯片上种植正常和肿瘤肺提取细胞，芯片基座为柔性材料，可充放气形变来模拟肺部的呼吸动作，增加化疗药物刺激的过程中使用光反射讯号和磁场诱导微柱偏转来监控细胞机械力及硬度的变化，来测量对肿瘤杀伤以及对正常细胞的影响，以评估药物的靶向性。S1、制备双面三明治结构力学芯片，芯片基座为柔性材料，微柱顶端部涂敷细胞外基质(ECM)，微柱侧边及微柱之间使用抗粘附处理，例如PluronicF127。S2、在芯片一侧种植正常肺细胞，另一侧种植肺肿瘤细胞，让细胞完全贴附于芯片上。也可在同一面不同区域混合种植S3、将双面芯片置于可充放气形变的装置中，以模拟肺部的呼吸动作(图28)。S4、添加化疗药物，对正常肺细胞和肺肿瘤细胞进行刺激。S5、在刺激过程中，利用光反射信号监控细胞与微柱之间的相互作用，从而实时检测细胞机械力的变化。S6、利用磁场诱导微柱偏转，测量细胞对微柱施加的力，进一步评估细胞硬度的变化。S7、分析光反射信号和磁场诱导微柱偏转数据，比较化疗药物对正常肺细胞和肺肿瘤细胞的影响，测量对肿瘤杀伤效果以及对正常细胞的影响。S8、根据实验结果评估化疗药物的靶向性，为药物筛选和研究提供依据。
第六十一实施例一种组织中判断肿瘤区域和非肿瘤区域的方法
本实施例提供上述任一项实施例中所述细胞机械力检测装置或表征系统或上述任意一项方案中所述细胞机械力的检测方法获取不同组织的细胞物理信息；其包括以下步骤：
S1将胰脏癌细胞株注射到老鼠之胰脏内，经过数周让癌症细胞成功形成肿瘤后，从老鼠的体内取下含肿瘤之组织，如胰脏和肝脏，将组织切小至约长宽各0.5公分的大小；使用黏胶把组织固定在组织包埋盘上，再以组织切片机将组织切成厚度约150-200mm的组织薄片；
S2将组织薄片铺放在细胞检测装置的微柱上，加入细胞培养液至刚好盖过组织薄片上方，静置半小时使后加入更多细胞培养液让组织完全浸泡其中，一小时后即可开始监测其组织的细胞机械力及其变化；
S3通过检测细胞机械力发现阻止中分为细胞机械力强和细胞机械力弱的区域。在对照验证方法中，步骤S1的胰脏癌细胞株为带有表现EGFP荧光蛋白；同时，步骤S3中比对组织的EGFP讯号以及细胞力学强弱，发现组织中含有癌细胞的区域(EGFP表现区域)具有较强的细胞力机械力。
由此，通过验证，细胞机械力强的区域其为含有癌细胞区域，实现组织中不同区域的识别，如图31所示。
第六十二实施例一种通过细胞机械力监测药物对组织的反应
本实施例提供上述任一项实施例中所述细胞机械力检测装置或表征系统或上述任意一项方案中所述细胞机械力的检测方法获取不同组织的细胞物理信息；其包括以下步骤：
1.将带有表现EGFP荧光蛋白胰脏癌细胞株注射到老鼠之胰脏内
2.经过数周让癌症细胞成功形成肿瘤后，从老鼠的体内取下含肿瘤之组织，如胰脏和肝脏
3.将组织切小至约长宽各0.5公分的大小
4.使用黏胶把组织固定在组织包埋盘上，再以组织切片机将组织切成厚度约150-200micrometer的薄片
5.将组织薄片铺放在力学芯片上，加入入细胞培养液至刚好盖过组织薄片上方
6.静置半小时使后加入更多细胞培养液让组织完全浸泡其中，一小时后即可开始记录及监控其组织之力学变化
7.约六小时后，组织会完全贴附在于芯片上，并可以加入药物进行药物测试，如胰腺癌常用治疗药物Gemcitabine与5-FU
8.持续监测整片组织的细胞机械力变化。因细胞进入凋亡或死亡时，细胞机械力学会大幅降低或消失。故观察肿瘤区域的细胞机械力是否降低及降低幅度，可预测药物对其肿瘤治疗效果。
第六十三实施例活体组织切片的机械特性空间组学监测用于区分肿瘤和正常组织以及评估药物处理效果
本实施例具体提供组织生物物理表征系统，通过监测活体组织切片的机械特性空间组学，区分肿瘤和正常组织区域，并评估药物处理效果。
S1.制备活体组织切片：取得活体组织样本(包含肿瘤和正常组织)，制备成薄切片。S2.测量组织切片的机械特性：通过力学芯片的光反射讯号监测机械力，并通过磁场激活刺入组织的微柱偏转来测量硬度，并用原子力显微镜(AFM)或类似技术验证。S3.区分肿瘤和正常组织：通过分析组织切片的机械特性空间组学数据，区分肿瘤和正常组织区域(图29)。发现肿瘤区域的机械力较大，硬度也较高。S4.药物处理：在活体组织切片上加入抗肿瘤药物，并进行一定时间的处理。也可增加免疫细胞悬液，测量肿瘤-免疫交互作用。S5.评估药物处理效果：药物处理后，测量肿瘤位置的机械力和硬度变化。观察到肿瘤区域的机械力明显降低(图30)，而硬度没有明显下降，说明机械力的响应速度比硬度更早。
最后应说明的是：以上各实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述各实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims (21)

  1. 一种细胞的表征方法，其特征在于，通过获取细胞或/和多细胞聚体的细胞物理信息表征细胞或/和多细胞聚体。
  2. 如权利要求1所述细胞的表征方法，其特征在于：所述细胞物理信息包括是在以下至少一种情况下获取的细胞机械力或/和硬度；
    (1)细胞和多细胞聚体之间相互作用、
    (2)细胞与细胞之间的相互作用、
    (3)多细胞聚体与多细胞聚体之间的相互作用、
    (4)不同生长时刻下的细胞或/和多细胞聚体、
    (5)多细胞聚体内部的不同区域、
    (6)物质对细胞或/和多细胞聚体之间的作用、
    (7)其它物理、生物或化学因素对细胞或/和多细胞聚体作用；
    所述多细胞聚体为两个以上细胞团聚一起形成的细胞群体。
  3. 如权利要求2所述细胞的表征方法，其特征在于：
    所述细胞机械力包括大小、方向、频率、分布中的一种或两种以上的组合；
    可选地，所述硬度包括细胞或/和多细胞聚体的硬度或/和分布；
    可选地，所述细胞机械力或/和硬度包括某点的细胞机械力或/和硬度。
  4. 如权利要求2所述细胞的表征方法，其特征在于：所述细胞物理信息包括细胞机械力或/和硬度在一定时间间隔内的变化。
  5. 如权利要求2所述细胞的表征方法，其特征在于：所述细胞物理信息还包括细胞形貌信息。
  6. 如权利要求2所述细胞的表征方法，其特征在于：所述细胞物理信息是在对细胞或/和多细胞聚体进行细胞限定操作下获取的。
  7. 如权利要求2所述细胞的表征方法，其特征在于：
    细胞和多细胞聚体之间相互作用包括：细胞和细胞外基质相互作用、细胞通过细胞间连接物质直接相互作用和通过细胞间信号分子相互作用；
    细胞与细胞之间的相互作用：细胞间信号传导和细胞间相互识别；
    多细胞聚体与多细胞聚体之间的相互作用包括：不同组织间相互作用、不同器官之间的相互作用；
    不同生长时刻下的细胞或/和多细胞聚体包括：不同发育阶段的胚胎细胞之间的相互作用、组织再生和修复；
    多细胞聚体内部的不同区域包括：多细胞组织中细胞极性的形成与维持，包括极性蛋白在细胞内部分布的调控、细胞-细胞相互作用的地点；
    物质对细胞或/和多细胞聚体之间的作用包括：药物与细胞相互作用、毒物与细胞相互作用；
    其他物理、生物或化学因素对细胞或/和多细胞聚体作用包括：温度和压力对细胞的影响：光照对植物细胞的影响。
  8. 如权利要求2所述细胞的表征方法，其特征在于：其是基于
    细胞和多细胞聚体之间相互作用、细胞与细胞之间的相互作用或多细胞聚体与多细胞聚体之间的相互作用下获取的细胞物理信息，包括以下步骤：
    将第一细胞或/和多细胞聚体、第二细胞或/和多细胞聚体置于特定区域，检测并且获取细胞物理信息；
    或
    将第一细胞或/和多细胞聚体置于特定区域后，再将第二细胞或/和多细胞聚体与所述第一细胞或/和多细胞聚体相互作用，检测并且获取细胞物理信息；
    所述第一细胞或/和多细胞聚体，以及第二细胞或/和多细胞聚体均为一个以上的细胞或/和多细胞聚体。
  9. 如权利要求2所述细胞的表征方法，其特征在于：所述物质包括生物活性大分子、化学物质、生物活性物质、灭活生物物质中的一种或两种物质以上的组合；所述生物活性大分子包括：蛋白、多肽、多糖、脂肪中的一种或两种以上物质的组合。
  10. 如权利要求2所述细胞的表征方法，其特征在于：其是基于体外器官或/和相关细胞模型种植成长过程中的细胞物理信息；所述细胞物理信息包括：器官相关细胞或/和组织的培养物 种植和培养过程中的细胞或/和任何一个区域的细胞物理信息；
    可选地，通过所述细胞物理信息表征体外器官或/和相关细胞模型生长过程的任何区域的细胞或细胞团、器官组织；
    可选地，将细胞或/和组织与ECM的混合物种植；
    可选地，种植的方法包括：3D打印或/和微流控方法控制细胞和生物材料的分布和流动实现种植；
    可选地，器官相关细胞或/和组织的培养物种植于表征装置上；
    可选地，所述检测装置上设置有ECM向性涂层。
  11. 如权利要求10所述细胞的表征方法，其特征在于：检测装置根据相应组织生理及病理状态下的微环境参数定制。
  12. 如权利要求1-11任一项所述细胞的表征方法，其特征在于，其包括以下步骤：
    将细胞或/和多细胞聚体设置于特定区域后，对所述细胞或/和多细胞聚体施加物理刺激、生物刺激、化学刺激中的至少一种刺激作用的组合；
    检测并且获取细胞或/和多细胞聚体的细胞物理信息；
    可选地，物理刺激、生物刺激、化学刺激包括：药物、机械力、硬度、生化、电场、流场、向性引导、辐射中一种或两种以上刺激的组合。
  13. 如权利要求1-11任一项所述细胞的表征方法，其特征在于，所述细胞物理信息在所述作用之前、作用过程中或/和作用之后获取；或者在所述细胞或/和多细胞聚体的不同生长时刻获取。
  14. 如权利要求1-11任一项所述细胞的表征方法，其特征在于：所述细胞物理信息为实时监测获取。
  15. 如权利要求1-11任一项所述细胞的表征方法，其特征在于：所述细胞物理信息通过表征系统获取；
    所述表征系统包括表征装置，所述表征装置包括：
    基座，以及
    设置于基座上的，可受细胞机械力作用和/或磁力作用而产生形变的一个以上的微柱构成的微柱阵列，所述微柱上设有光线反射层；
    可选地，所述微柱远离基座的一端设置有光线反射层，所述基座设置有可透光部分，所述微柱的柱体设置有可透光部分；可选地，所述微柱的表面或/和基座具有抗反射层。
  16. 如权利要求15所述细胞的表征方法，其特征在于：
    所述表征系统还包括光信号发射装置和光信号检测装置，所述光信号发射装置发出的光线通过入射光路照射到所述光线反射层，所述光线反射层反射的光线经过反射光路进入光信号检测装置；
    可选地，所述光信号检测装置获取的光学强度，分析获得细胞物理信息；
    可选地，所述光信号检测装置获取的光学强度与细胞机械力的大小具有线性相关，可进行定性和定量的分析实现不同的细胞分型。
  17. 如权利要求15所述细胞的表征方法，其特征在于：所述表征装置可容置液体；
    若所述液体为细胞培养液，使所述细胞或/和多细胞聚体贴附或/和继续培养；
    可选地，所述细胞或/和多细胞聚体通过设置在微柱上的胶黏物质粘附于微柱上。
  18. 一种细胞分型和识别方法，其特征在于，其通过权利要求1-11任一项所述细胞物理细胞，对所述细胞或/和多细胞聚体进行分型和识别；
    可选地，所述分型和识别包括：细胞或/和多细胞聚体的类型、状态、行为、空间组学特征及分化方向、应激反应；
    可选地，所述分型和识别包括：通过所述细胞物理细胞可选择地分选出特定的细胞或组织。
  19. 如权利要求18所述细胞分型和识别方法，其特征在于，其使用细胞识别装置进行识别，细胞识别装置包括信息获取单元、预处理单元、学习单元和识别单元；
    所述信息获取单元用于获取细胞或/和多细胞聚体的细胞物理信息；
    所述预处理单元用于对细胞物理信息做预处理，形成结构化细胞物理信息；所述结构化细胞物理信息包括细胞数目、细胞特征数目和各细胞特征的特征信息；
    所述学习单元用于以结构化细胞物理信息作为输入数据，利用有监督、无监督或半监督的机器学习建立细胞特征模型；
    所述识别单元用于将所述细胞特征模型应用于细胞或/和多细胞聚体的分类或聚类，实现细胞或/和多细胞聚体的分型和识别。
  20. 如权利要求19所述细胞分型和识别方法，其特征在于：
    所述分型和识别包括以下的至少一种的组合：
    组织中肿瘤区域和非肿瘤区域的分型和识别；
    不同转染程度和非转染细胞或/和多细胞聚体的分型和识别；
    生物活性物质不同产量细胞或/和多细胞聚体的分型和识别；
    监测基因工程对细胞的影响，包括：从大克隆团内，对小克隆团或单个细胞的识别；
    杀死无抗性细胞的最低有效浓度药物的确定；
    在药物筛选过程中对细胞进行实时监测以及时调整；
    监测脂肪细胞的生长、分化；
    可选地，用于实时监测白色脂肪、米色脂肪及棕色脂肪的转换过程。
  21. 一种如权利要求1-11、18-20任一项所述方法的应用，其特征在于，所述应用包括以下的至少一种：
    在建立体外器官和细胞模型中的应用；
    在筛选器官治疗药物中、在器官模型在生理和病例状态下研究中的应用；
    在药物对肿瘤有效性评估方法和相关评估产品中的应用；
    在细胞疗法、合成生物学、脂肪研究、细胞/多细胞聚体与大分子相互作用研究、多细胞聚体研究方法及其以上相关产品中的应用。
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