Visual particle aggregate detection device and detection sample accommodating device

Abstract

The visible particle aggregate detection device and the detection sample accommodating device are used for testing a target substance in a detection sample, and the detection sample is formed by adding detection particles into a sample; a detection sample is added into an accommodating cavity in the detection sample accommodating device, and a target substance in the detection sample is combined and gathered with the detection particles to form a visible particle aggregate; the supporting assembly is used for placing the detection sample accommodating device; the height of the accommodating cavity is H; the camera module is used for shooting the accommodating cavity to obtain a detection sample image; the AI calculation module comprises visual particle aggregate AI characteristic data; the calculation module is used for calculating to obtain the volume V = S * H of the detection sample, wherein S is the selected area in the detection sample image; the AI calculation module is used for obtaining the number of particles in the area S or the area of a visible particle aggregate; the calculation module is used for calculating the quantity or content T1 of the target substance corresponding to the volume V of the detection sample, and the content T2 of the target substance in unit volume is equal to T1 / V.

Description

Technical Field

[0001] This application belongs to the technical field of analysis based on formed components, and particularly relates to a visual particle aggregate detection device and a detection sample containing device. Background Art

[0002] In vitro diagnostic immunology is a method of diagnosing diseases by detecting specific immune markers in body fluids. These immune markers can be antibodies, antigens, immunoglobulins, etc. Detecting their presence or changes in levels can help doctors diagnose diseases, monitor treatment effects, or predict disease progression.

[0003] The immune response is crucial for the normal function of the immune system because it enables the immune system to recognize and eliminate pathogens, foreign substances, and abnormal cells in the body. Techniques such as immunohistochemistry utilize the affinity reaction between antibodies and antigens to detect specific molecules or cells.

[0004] In the analysis techniques for quantitatively and qualitatively analyzing trace immune markers, there are multiple different technical paths. The mature techniques include enzyme-linked immunosorbent assay, radioimmunoassay, immunoturbidimetry, immunofluorescence analysis, and chemiluminescent immunoassay.

[0005] Chinese Patent Application No. "CN201410197209.1", "A Method for Detecting Biological Macromolecules or Microorganisms", proposes a method for detecting biological macromolecules or microorganisms. The patent with Application No. "CN201410197209.1" integrates immunomagnetic enrichment and visualization detection, has simple operation, requires a short time for the entire detection process, does not require special instrument equipment, and the method of the present invention has low requirements for the purity of antibodies, which can greatly reduce the detection cost. However, this patent only reveals that "the degree of aggregation of the aggregates is positively correlated with the concentration of the biological macromolecules or microorganisms", and uses "determine the concentration of biological macromolecules or microorganisms in the sample to be detected according to the degree of aggregation of the aggregates, specifically: obtain a photo of the aggregates, and determine the concentration of biological macromolecules or microorganisms in the sample to be detected by quantifying the gray value of the photo", rather than accurately calculating the concentration. The method proposed in this patent application can at most give a qualitative conclusion and cannot give a quantitative measurement result, so it cannot be applied to medical detection.

[0006] Because, during the process of taking photos of test samples, for the same type of sample, under different thickness conditions, the grayscale values of the taken photos are different. Therefore, the patent application No. "CN201410197209.1" cannot accurately measure the content of the target substance in the sample. This type of technology is not mature and cannot be practically applied in the industry. Especially in medical application scenarios that require precise measurement, in immunoassay scenarios, it cannot meet the 8% measurement accuracy required for veterinary tests, and when applied to human medical tests, it is even more unable to meet the requirements of human medical measurement accuracy.

[0007] Chinese patent application number "CN202180041737.6" with the application title "Aggregation Induction Assay for Improving Sensitivity". In this application, it is proposed that "a system, device, and method for rapidly and accurately measuring analyte particle-binding-induced reporter particle aggregation are provided. In the presence of analyte particles of interest, reporter particles form aggregates, and the average particle size thereof increases with the increase in analyte concentration. Based on the analysis of the average particle size determined from the sample frames, the presence and / or concentration of the analyte can be determined", and a "calibration curve" is proposed. This "calibration curve" has "horizontal axis = SARS-CoV-2 antibody (mg / dL), vertical axis = aggregation size (pixels)", establishing the relationship between the average aggregation area and the target analyte. After being verified by a large number of experiments, when the content change of the target substance fluctuates by more than 20%, the measurement deviation of this method is huge.

[0008] This patent application is essentially the same as the Chinese patent application number "CN201410197209.1" with the application title "A Method for Detecting Biomacromolecules or Microorganisms", and it does not give how to accurately calculate the content of the target substance.

[0009] Facts have proved that there is no direct correlation between the average aggregation particle size and the content of the target substance. It is affected by various factors such as the length of time for configuring the test sample, the magnitude of the vibration force, and the temperature during configuration. It is not scientific and has no application value to use the average aggregation particle size to measure the content of the target substance.

[0010] For example, the reference range of C-reactive protein is 0 - 10 mg / L, and the reference range of high-sensitivity C-reactive protein is 0 - 3 mg / L, with higher sensitivity. In fact, the detection range of C-reactive protein is wider, but the lower detection limit of high-sensitivity C-reactive protein is lower. In terms of sensitivity, hsCRP can detect concentrations up to 0.005 - 0.1 mg / L relative to CRP. The measurement accuracy requirement for high-sensitivity C-reactive protein is at least 100 times higher than that for C-reactive protein. During the quantitative detection process, if the volume of the test sample cannot be accurately measured, high-precision immunoassays have no scientific basis and cannot be applied. Summary of the Invention

[0011] In this application, through a large number of experiments, repeated inferences, and demonstrations, the applicant found that the concentration of the target detection substance is directly related to the number of aggregated microsomes. Through AI technology, large-volume particles and small-volume aggregated particles can be accurately distinguished. By detecting the area and the height of the detection cavity corresponding to the detection area, the accurate volume of the detection sample can be obtained, and accurate quantitative results can be obtained. By adopting a scale accuracy of the height H of the accommodation cavity higher than 8%, the accurate volume of the detection sample can be obtained, making the visible particulate aggregate detection device and the detection sample accommodation device have medical application value. Based on this design, the visible particulate aggregate detection device and the detection sample accommodation device can be used in the above scenarios.

[0012] The solution of this application to solve the above technical problems is: a visible particulate aggregate detection device for testing the target substance in a detection sample, where the detection sample is formed by adding detection microparticles to the sample; the detection sample is added to the accommodation cavity inside the detection sample accommodation device, and the target substance in the detection sample binds and aggregates with the detection microparticles to form visible particulate aggregates; it includes a control module, a camera module, a support component, and an AI calculation module; the control module is electrically connected to the camera module; the control module includes a calculation module; the calculation module is electrically connected to the AI calculation module; the support component is used to place the detection sample accommodation device; the height of the accommodation cavity is H; the camera module is used to photograph the accommodation cavity to obtain a detection sample image; the AI calculation module includes a storage unit; the storage unit is used to store the AI feature data of visible particulate aggregates; the calculation module is used to calculate the volume V of the detection sample as V = S×H, where S is the selected area in the detection sample image; the AI calculation module is used to obtain the number of microparticles or the area of visible particulate aggregates in the area S; the calculation module is used to calculate the number or content T1 of the target substance corresponding to the volume V of the detection sample; the calculation module is used to calculate the content T2 of the target substance per unit volume as T2 = T1 / V.

[0013] The visible particulate aggregate detection device described above includes any one or more of the following features: TB10: The AI calculation module is within the control module; TB20: The control module includes a network component; the AI calculation module is arranged in a server, and the network component is electrically connected to the AI calculation module through a network; TB30: The calculation module is used to record the height H of the accommodation cavity; TB31: It further includes a code scanning component, which is electrically connected to the control module, and the code scanning component is used to scan the code to obtain the height H of the accommodation cavity, and the height H is recorded on the detection sample accommodation device in the form of a bar code or a QR code; TB32: The density difference between the detection microparticles and the detection sample is greater than 0.01 and less than 0.1; TB40: The scale accuracy of the height H of the accommodation cavity is higher than a set value; the set value is less than 15%.

[0014] The visual particle aggregate detection device described above includes any one of the following features: TC10: The camera module includes a Z-axis slide table assembly and a microscopic camera assembly. The microscopic camera assembly is mechanically connected to the slide table in the Z-axis slide table assembly. The microscopic camera assembly can move in the Z-axis direction. The Z-axis slide table is electrically connected to the control module. It also includes a power module, and the power module is connected to the Z-axis slide table by a cable; TC20: It further includes a driving module; the control module is electrically connected to the driving module; the support assembly includes an X-slide table assembly, and the driving module is electrically connected to the X-slide table assembly. The driving module is used to drive the X-slide table assembly; the detection sample containing device is placed on the slide table of the X-slide table assembly, and the detection sample containing device can move in the X-axis direction.

[0015] In the visual particle aggregate detection device described above, in TC20: the support assembly includes a Y-slide table assembly. The X-slide table assembly is placed on the slide table of the Y-slide table assembly. The driving module is electrically connected to the Y-slide table assembly. The driving module is used to drive the Y-slide table assembly. The detection sample containing device can move in the X-axis or Y direction.

[0016] The visual particle aggregate detection device described above includes any one of the following features: TD10: It further includes circuit board A and circuit board B. The AI computing module is arranged on circuit board A, and the control module is arranged on circuit board B. Circuit board A is connected to circuit board B by a cable; TD20: It further includes circuit board C. The AI computing module and the control module are arranged on circuit board C. Circuit board C is connected to the camera module by a cable, and circuit board C is connected to the support assembly by a cable.

[0017] The visual particle aggregate detection device described above includes any one or more of the following features: TA10: The detection particles are polymer particles or magnetic bead particles; TA20: The detection particles adsorb or couple with antibodies or antigens; TA11: The target includes any one of proteins, carbohydrates, lipids, vitamins, and small molecule hormones; The surface of the detection particles is labeled with an antibody, and the binding and aggregation is an affinity reaction; TA12: The target includes an antibody; The surface of the detection particles includes any one of proteins, carbohydrates, lipids, vitamins, and small molecule hormones, and the binding and aggregation is an affinity reaction; TA21: The surface of the detection particles is labeled with a specific antigen or antibody, and the binding and aggregation is a specific antigen-antibody binding; TA22: The surface of the detection particles is labeled with a specific antibody, and the binding and aggregation is an immune reaction; TA30: The detection sample includes body fluids or excreta; Body fluids include serum, plasma, whole blood, saliva, and local body fluid effusions. Excreta include urine and feces; Feces are diluted feces; TA40: The visual particle aggregate is irradiated with excitation light, and the visual particle aggregate is excited by the excitation light to emit fluorescence, and the number or area or volume or fluorescence intensity of the visual particle aggregate emitting fluorescence is obtained.

[0018] The described visible particle aggregate detection device includes any one or more of the following features: TE1: The support assembly includes a light source assembly, and the light source assembly includes a white light source. The white light emitted by the white light source is used to irradiate the accommodation cavity; TE2: The support assembly includes an excitation light source assembly, and the excitation light source assembly includes a purple light source. The purple light emitted by the purple light source is used to irradiate the accommodation cavity; TE3: The camera module is above or below the support assembly.

[0019] The solution for this application to solve the above technical problems can also be a sample accommodation device for visible particle aggregate detection in a visible particle aggregate detection device. The visible particle aggregate detection device is used for detecting samples. The sample to be detected includes detection particles, and the detection particles are adsorbed or conjugated with antibodies or antigens; the target analyte in the sample to be detected aggregates with the detection particles to form visible particle aggregates; it includes an accommodation cavity A and a sample addition port; the sample addition port is connected to the accommodation cavity A; the sample addition port is used to add the sample to be detected; the height of the accommodation cavity A is equal to the set value H; the height H of the accommodation cavity is used for the visible particle aggregate detection device to calculate the volume of the sample to be detected. The visible particle aggregate detection device is used to calculate the volume of the sample to be detected = the area of the sample corresponding to the image × the height H of the accommodation cavity; the accommodation cavity A is used to accommodate the sample to be detected; the upper and lower parts of the accommodation cavity include transparent windows, and external illumination light can enter the accommodation cavity through the transparent windows; through the transparent windows, an image of the visible particle aggregates is taken.

[0020] The described visible particle aggregate detection device further includes an accommodation cavity B, and the sample addition port is connected to the accommodation cavity B; the accommodation cavity B is used to accommodate the sample to be detected of species B; the height of the accommodation cavity A is higher than the height of the accommodation cavity B.

[0021] The visual particle aggregate detection device described above includes any one or more of the following features: TF10: The accommodation cavities A and B are connected in series for the liquid to be detected to be poured into the accommodation cavities A and B in sequence; TF20: The accommodation cavities A and B are connected in parallel for the liquid to be detected to be poured into the accommodation cavities A and B simultaneously; TF30: The accommodation cavities A and B are not connected in parallel. The sampling port includes sampling port A and sampling port B. The accommodation cavity A is connected to sampling port A, and the accommodation cavity B is connected to sampling port B; TF40: It further includes an exhaust port; the exhaust port is connected to the accommodation cavity A; the exhaust port is connected to the accommodation cavity B; the exhaust port is connected to the external atmosphere; TF50: The height of the accommodation cavity A or B is recorded on the detection sample accommodation device using a bar code or a QR code; TF70: The scale accuracy of the height of the accommodation cavity A or B is higher than a set value; the set value is less than 15%; TF90: The average diameter of the detected particles is H2, and the height of the accommodation cavity A or B is greater than 50 times the height of H2; TG10: The upper parts of the accommodation cavities A and B are made of a transparent material; TG20: The lower parts of the accommodation cavities A and B are made of a transparent material.

[0022] TG30: The bottoms of the accommodation cavities A and B have the same height; TG40: The tops of the accommodation cavities A and B have the same height.

[0023] The visual particle aggregate detection device described above includes any one of the following technical features: TH10: The density difference between the detected particles and the detection sample is greater than 0.01 and less than 0.1; TH20: The detection sample includes body fluid or excrement; the body fluid includes serum, plasma, whole blood, saliva, local body fluid effusion, and the excrement includes urine, feces; the feces are diluted feces.

[0024] The technical effects of the above technical solutions include: a control module, a camera module, a support component, and an AI calculation module. In particular, the calculation module in the control module can accurately perform volume quantification; it can be used to accurately obtain the content of the target substance per unit volume.

[0025] The technical effects of the above technical solutions include: The AI calculation module is within the control module, making the device more efficient and compact.

[0026] The technical effects of the above technical solutions include: The control module includes a network component; the AI calculation module is arranged in a server, and the network component is electrically connected to the AI calculation module through a network, facilitating real-time update of the AI calculation module and being conducive to evolution.

[0027] The technical effects of the above technical solutions include: The calculation module is used to record the height H of the accommodation cavity; it can accurately obtain the height of each accommodation cavity for volume calculation.

[0028] The technical effects of the above technical solution include: the density difference between the detection particles and the detection sample is greater than 0.01 and less than 0.1, which facilitates the floating or sinking of the visible particle aggregates and facilitates the acquisition of clear images.

[0029] The technical effects of the above technical solution include: the dimensional accuracy of the height H of the accommodation cavity is higher than the set value; the set value is less than 15%; the dimensional accuracy of the cavity height H ensures the accuracy of volume calculation.

[0030] The technical effects of the above technical solution include: the scanning component is used to scan the code to obtain the height H of the accommodation cavity, and the height H is recorded on the detection sample accommodation device in the form of a bar code or a QR code, ensuring that the height H of each accommodation cavity is obtained by scanning the code for accurate volume calculation.

[0031] The technical effects of the above technical solution include: the camera component includes a Z-axis slide table component and a microscopic camera component; the microscopic camera component is mechanically connected to the slide table in the Z-axis slide table component, and the microscopic camera component can move in the Z-axis direction. It is convenient for image acquisition, provides a device for accurately adjusting the imaging-related distance, and is convenient for obtaining clear pictures.

[0032] The technical effects of the above technical solution include: the driving module is used to drive the X-slide table component to move in the X-axis direction, driving the detection sample accommodation device to move in the X-axis direction. The driving module is used to drive the Y-slide table component to move in the Y-axis direction, driving the detection sample accommodation device to move in the X or Y direction. The detection sample accommodation device moves in the X or Y direction, which is convenient for obtaining images at different positions and improves the efficiency of image acquisition and analysis.

[0033] The technical effects of the above technical solution include: the control module is arranged on the circuit board A, and the driving module is arranged on the circuit board B, and they are arranged separately, which is beneficial to reducing the maintenance cost.

[0034] The technical effects of the above technical solution include: the driving module and the control module are arranged on the circuit board C, making the device more compact and reducing the comprehensive cost.

[0035] The technical effects of the above technical solution include: detecting particulate polymers or magnetic bead particles, which can be applied to a variety of detection scenarios.

[0036] The technical effects of the above technical solution include: the detection particles adsorb or couple antibodies or antigens and can be used for antigen or antibody detection.

[0037] The technical effects of the above technical solution include: being able to detect proteins, sugars or enzymes based on the binding aggregation as an affinity reaction.

[0038] The technical effects of the above technical solution include: it can be applicable to the detection of various different types of samples, with good adaptability.

[0039] The technical effects of the above technical solution include: the light source assembly includes a white light source, and the white light emitted by the white light source is used to irradiate the accommodation cavity. The strong white light can provide a variety of spectra, which is beneficial to the identification of various target objects.

[0040] The technical effects of the above technical solution include: the purple light emitted by the purple light source is used to irradiate the accommodation cavity; as an excitation light source, it can make the visual particle aggregates be excited by the excitation light to emit fluorescence.

[0041] The technical effects of the above technical solution include: the imaging component is above or below the support component, compatible with the up and down imaging methods, and the way of obtaining pictures is more flexible.

[0042] The technical effects of the above technical solution include: the detection sample accommodation device is provided with two accommodation cavities A and accommodation cavity B, which can further improve the detection efficiency of the target object.

[0043] The technical effects of the above technical solution include: different connection methods and communication methods of the accommodation cavity A and the accommodation cavity B, which are adapted to a variety of different application scenarios and improve efficiency.

[0044] The technical effects of the above technical solution include: the upper part of the accommodation cavity A and the upper part of the accommodation cavity B are made of transparent materials, and the lower part of the accommodation cavity A and the lower part of the accommodation cavity B are made of transparent materials, which is convenient for the application of the up and down imaging method.

[0045] The technical effects of the above technical solution include: the accommodation cavity A and the accommodation cavity B have bottoms or tops with the same height. Even if the cavity height of the accommodation cavity A is different from the cavity height of the accommodation cavity B, it is convenient to perform imaging based on the bottom or top, and there is a common imaging reference plane. Description of the Drawings

[0046] Figure 1 is a schematic diagram of the steps of a method for detecting target substances based on particle aggregation;

[0047] Figure 2 is a schematic diagram of the substance to be detected that is invisible in the sample;

[0048] Figure 3 is a schematic diagram of the structures of traditional monoclonal antibodies, heavy chain antibodies, and nanobodies;

[0049] Figure 4 is a schematic diagram of antibodies or antigens coated on particles such as latex or magnetic beads;

[0050] Figure 5 is a schematic diagram of the coated particles adsorbing and aggregating with each other;

[0051] Figure 6 There is no target substance, and the detected particles show a relatively uniform microscopic magnified image;

[0052] Figure 7 There is a target substance, and the detected particles show an agglomerated microscopic magnified image;

[0053] Figure 8 The agglomerated particles are recognized by AI;

[0054] Figure 9 It is a schematic diagram of the detection area corresponding to an image when taking an array image;

[0055] Figure 10 It is a top view schematic diagram of a detection chip;

[0056] Figure 11 It is a cross-sectional schematic diagram of the detection cavity and the injection channel inside a detection chip;

[0057] Figure 12 It is a cross-sectional schematic diagram of the detection cavity, injection channel, and exhaust channel inside a detection chip;

[0058] Figure 13 It is a calculation method for detecting the content of a target substance based on particle aggregation images;

[0059] Figure 14 It is a schematic diagram for obtaining the number, area, or volume of agglomerated microparticles through AI image recognition;

[0060] Figure 15 It is a schematic diagram for obtaining the number, area, or volume of agglomerated microparticles by binarizing the test image area;

[0061] Figure 16 It is a schematic diagram for obtaining an image by binarizing the test image area;

[0062] Figures 17 to 22 It is a schematic frame of a visible particle aggregate detection device Figures 1 to 6 ;

[0063] Figures 23 to 25 It is a schematic diagram of a detection sample holding device Figures 1 to 3 . Specific implementation mode

[0064] The following further details the content of the present application in conjunction with the accompanying drawings. It should be noted that the following is a description of the preferred embodiments of the present invention and does not constitute any limitation to the present invention. The description of the preferred embodiments of the present invention is only for the illustration of the general principles of the present invention. The numbers such as "first", "second", "A", and "B" involved in the present invention are only for the convenience of description and do not represent the order relationship in time or space. The combinations of letters and numbers such as "TA", "TB", and "H" involved in the present invention are only for the convenience of description, and the specific meanings are determined by the specific words they represent.

[0065] For example Figure 1 , a detection method for detecting a target substance based on particle aggregation includes adding detection particles to a sample; the target substance in the sample binds to the detection particles to form a particle conjugate; the particle conjugates aggregate to form aggregated particulate bodies; taking an image of the sample under a microscope; analyzing the image to obtain the number, area, or volume of the aggregated particulate bodies, and obtaining the number or content of the target substance according to the binding degree between the target substance and the detection particles.

[0066] For example Figure 2 , target substances in the sample, such as proteins, small molecules, amino acids, sugars, enzymes, etc., substances that cannot be observed or are difficult to observe under an optical microscope, cannot be directly observed and detected with an ordinary optical microscope.

[0067] For example Figure 3 , in an antigen-antibody detection system, specific antibodies react with the substance to be detected, but the antibodies and antigens cannot be directly observed and detected with an ordinary optical microscope. Traditional monoclonal antibodies, heavy-chain antibodies, and nanobodies cannot be directly observed under a traditional microscope.

[0068] For example Figure 4 , antibodies or antigens are coated on particles such as latex or magnetic beads. The diameter of the particles is greater than 0.1 μm, and the particles can be directly observed and detected with an ordinary optical microscope.

[0069] For example Figure 5 , the coated particles adsorb or aggregate with each other to form large aggregated particulate bodies. By observing the number, area, or volume of the aggregated particulate bodies under a microscope, the number or content information of the target substance can be obtained.

[0070] For example Figure 6 , for the actually photographed detection particles, when there is no target substance in the sample, the detection particles are relatively evenly distributed, and only a very small number of particles aggregate into about two small clusters. For large-particle-size detection particles (such as 1000-nm magnetic bead detection particles), when there is no target substance or the content is extremely low in the sample, the dispersibility of the detection particles is good.

[0071] For example Figure 7, the actually photographed detection particles, the sample contains the target substance, and some particles aggregate into clusters. As the concentration of the corresponding target substance increases, the individually dispersed detection particles aggregate to form aggregated detection particles, and the aggregated detection particles are clearly identifiable after aggregation.

[0072] Such as Figure 8 , during detection, detection particles with a fixed concentration are added, the number of aggregated detection particles is identified, and the antigen concentration is quantified. By identifying and counting the aggregated particles, and based on the binding degree between the particles and the target substance, the quantity or content of the target substance can be calculated. The binding degree between the particles and the target substance is calculated based on the particle size, the amount of coated antibody, and the degree of aggregation.

[0073] The above detection method; the particles can be polymer particles or magnetic bead particles. The polymer particles can be polystyrene microspheres, i.e., latex particles. Polystyrene microspheres, i.e., latex particles, adsorb proteins. Through adsorption, the invisible particles can expand into visible particles, and by detecting the quantity and size of the visible particles, the amount of protein can be detected.

[0074] Various modifications can be carried out on the surface of polystyrene. For example, hydrophilic modification. The surface modification groups of the polymer particles mainly include functional groups such as polysaccharides, acrylamides, polyvinyl alcohols, and polyamines. After modification, polystyrene can selectively adsorb different target substances. Therefore, the present invention can not only be applied to the detection of antibodies and antigens, but also to the detection of various target substances or non-target substances.

[0075] The above detection method; the detection particles adsorb or conjugate antibodies or antigens. The detection of antibodies and antigens is a very important detection item. The modification methods or coating methods of magnetic bead microspheres in various existing technologies can all be applied to the modification and coating of the particles in this application. The modified or coated particles can selectively aggregate when encountering the target substance to be detected.

[0076] The above detection method; the sample includes body fluids or excreta; the body fluids include serum, plasma, whole blood, saliva, local body fluid effusions, and the excreta include urine, feces; the feces are diluted feces.

[0077] The above detection method; according to the corresponding sample area and sample height of the photographed image, the sample volume is obtained, and the unit volume content of the aggregated particulate matter is calculated based on the number of aggregated particulate matter and the sample volume.

[0078] Such as Figure 9 , during the microscopic imaging process, the field of view is relatively small, and the volume corresponding to each imaging is very small. By selecting the sample area and sample height corresponding to the area of the image, the volume calculated for each imaging can be obtained. By increasing the number of photographed images, a larger sample volume can be obtained, improving the detection accuracy.

[0079] The above detection method; based on the binding degree between the target analyte and the detection particles, and the unit volume content of the aggregated microparticles, calculate the unit volume content of the target analyte.

[0080] Such as Figure 9 , by identifying the aggregated microparticles in the sample volume, the content or quantity per unit volume corresponding to the sample volume can be calculated, and the detection result can be converted into a measurement index in the prior art, such as virus content, the unit volume content of a specific protein, etc.

[0081] The above detection method; irradiate the aggregated microparticles with excitation light, and the aggregated microparticles are excited by the excitation light to emit fluorescence, so as to obtain the number, area, volume or fluorescence intensity of the aggregated microparticles that emit fluorescence.

[0082] Such as Figure 10 , a detection chip for detecting antibody-antigen, including a sample injection channel 1010, a detection cavity 1020, and a sample injection port 1011; the detection cavity is used to accommodate the sample; one end of the sample injection channel is communicated with the detection cavity; the other end of the sample injection channel is communicated with the sample injection port, and the sample injection port is communicated with the external atmosphere; the upper and lower parts of the detection cavity include transparent windows, and external illumination light can enter the detection cavity through the transparent windows; when placed horizontally, the sample injection port is higher than the top of the detection cavity; the sample includes detection particles, and the detection particles adsorb or couple with antibodies or antigens; the target analyte in the sample binds to the detection particles to form particle conjugates; the particle conjugates aggregate to form aggregated microparticles; through the transparent windows, an image of the sample can be taken; the number, area or volume of the aggregated microparticles is obtained.

[0083] Such as Figure 11 , a cross-sectional schematic diagram of the detection cavity and the sample injection channel of the detection chip, the detection cavity 1120 internally accommodates the sample, the sample injection channel 1110 is communicated with the sample injection port 1111, the sample injection port 1111 is higher than the upper surface 1121 of the detection cavity, the sample will not overflow from the sample injection port 1111, and at the same time, due to the internal pressure of the liquid, air will automatically be discharged.

[0084] The upper and lower surfaces of the detection cavity are transparent windows, which can introduce light to obtain an image of the internal aggregated microparticles.

[0085] The above detection chip; the detection particles are polymer particles or magnetic bead particles; such as Figure 12 , it may further include an exhaust channel 1210 and an exhaust port 1211; one end of the exhaust channel is communicated with the detection cavity; the other end of the exhaust channel is communicated with the exhaust port, and the exhaust port is communicated with the external atmosphere; when placed horizontally, the exhaust port is higher than the top of the detection cavity.

[0086] The above detection chip; the polymer particles include polystyrene microspheres, i.e., latex particles.

[0087] The sample volume is obtained based on the corresponding sample area of the captured image and the height of the detection cavity. The height H of the detection cavity is used to calculate the sample volume, and the sample volume = the corresponding sample area of the image × the height H of the detection cavity.

[0088] The above detection chip; based on the binding degree between the target analyte and the microparticles and the unit volume content of the aggregated microparticles, the unit volume content of the target analyte is calculated. The unit volume content of the aggregated microparticles is calculated based on the number of aggregated microparticles and the sample volume. The number of aggregated microparticles is obtained from the image; the unit volume content of the aggregated microparticles = the number of aggregated microparticles ÷ the sample volume; the unit volume content of the target analyte = the unit volume content of the aggregated microparticles × the binding degree between the target analyte and the microparticles.

[0089] Such as Figure 9 , during the process of taking pictures, multiple pictures are taken to increase the sample volume. Among the captured images, all or part are selected, such as Figure 9 , the area of the selected image corresponds to an area inside the chip that is 0.3 mm long, 0.2 mm wide, and the height is 0.4 mm, and the height is determined by the height of the internal cavity of the chip.

[0090] Furthermore, based on the binding degree between the target analyte and the microparticles and the unit volume content of the aggregated microparticles, the unit volume content of the target analyte is calculated.

[0091] Within a certain concentration range, the binding degree between the target analyte and the microparticles is relatively fixed. With the unit volume content of the aggregated microparticles, multiplying by the binding degree gives the unit volume content of the target analyte. The binding degree of the microparticles is obtained through calibration experiments.

[0092] The sample can be serum, and the target analyte can be various viruses, bacteria, antibodies caused by various pathogens, and the microparticles are coated with the corresponding antigens.

[0093] A reagent for antibody-antigen detection, including detection microparticles, and the detection microparticles adsorb or conjugate with antibodies or antigens; during the detection process, the reagent is mixed with the sample; the target analyte in the sample binds to the detection microparticles to form a microparticle conjugate; the microparticle conjugates aggregate to form aggregated microparticles; an image of the aggregated microparticles is obtained, and the amount of antibodies or antigens in the sample is obtained by analyzing the number of aggregated microparticles through the image.

[0094] The detection particles are added to various detection liquids. The concentration of the detection particles can be pre-prepared so that the detection particles are dispersed in the detection liquid. During the test, they are added according to the volume ratio, which facilitates the detection process. There are detection particles in the reagent, which can serve as the target for focusing of the optical microscopy system to assist in focusing. The detection particles can be polymer particles or magnetic bead particles. The polymer particles can be polystyrene microspheres, i.e., latex particles. The diameter of the detection particles can be greater than 0.1 micrometers. The diameter of the detection particles can be 0.3 - 3 micrometers. If the diameter is too small, such as less than 0.1 micrometers, it cannot be seen under a conventional microscope with a magnification of 40 times. If it is greater than 3 micrometers, the antigen-antibody binding force cannot cause them to aggregate, and it is difficult to agglomerate, so detection cannot be carried out.

[0095] Such as Figure 13 , a calculation method for detecting the content of the target substance based on the particle aggregation image, includes selecting one or more microscopic test pictures as the calculation selection pictures; selecting all or part of them as the test image area in the calculation selection pictures; obtaining the test sample volume according to the test image area and the sample height; obtaining the number or area or volume of the aggregated particulate bodies in the test image area; obtaining the number or content of the target substance according to the number or area or volume information of the aggregated particulate bodies; dividing the number or content of the target substance by the test sample volume to obtain the content or number per unit volume of the target substance.

[0096] The method for calculating the sample volume can be to obtain the test image area by multiplying the pixel area of the image sensor by the number of pixel points in the test image area; obtaining the test sample area by dividing the test image area by the microscope magnification; multiplying the test sample area by the test sample height to obtain the test sample volume.

[0097] Such as Figure 14 , obtaining the number or area or volume of the aggregated particulate bodies in the test image area can be to obtain the number or area or volume of the aggregated particulate bodies through AI image recognition.

[0098] Such as Figure 15 , obtaining the number or area or volume of the aggregated particulate bodies in the test image area can be to binarize the test image area, calculate the area of the binarized image, and obtain the area of the large mass.

[0099] Such as Figure 16 , photos of the target substance at 3 concentrations taken by the detection device of "Shenzhen Anlv Medical Technology Co., Ltd." are shown. Picture A corresponds to a very low content of the target analyte in the sample, Picture B contains a small amount of the target analyte, and Picture C contains a high concentration of the target analyte. The pictures are binarized to obtain pictures A1, B1, and C1, and it can be clearly seen that the area of the aggregated particles changes with the content of the target analyte.

[0100] The number, area, or volume of unagglomerated microsomes in the test image region is detected through AI image recognition. The more the number, area, or volume of unagglomerated microsomes recognized, the less the content of the target substance.

[0101] The target substance can be a substance with antigenic activity, and the substance with antigenic activity includes any one of protein, nucleic acid, and polysaccharide.

[0102] The target substance can also be a substance with a cell structure, and the substance with a cell structure includes any one of platelets, target substances, and red blood cells.

[0103] Such as Figure 17 A visible particle aggregate detection device is used to test the target substance in the test sample. The test sample is formed by adding detection particles to the sample. The target substance in the test sample binds and aggregates with the detection particles to form visible particle aggregates. It includes a control module, a camera module, a support component, and an AI calculation module. The control module includes a calculation module. The support component is used to place the test sample containing device. The interior of the test sample containing device includes a containing cavity with a height H, and the containing cavity is used to hold the test sample. The camera module is used to photograph the containing cavity to obtain a test sample image. The AI calculation module includes a storage unit. The storage unit is used to store the AI feature data of the visible particle aggregates. The calculation module selects a test area S according to the test sample image and calculates to obtain the volume V of the test sample = S × H. The AI calculation module analyzes the test sample image to obtain the number of particles in the visible particle aggregates corresponding to the test area S or the area of the visible particle aggregates, and obtains the number or content T1 of the target substance according to the number or area. The content of the target substance per unit volume T2 = T1 / V.

[0104] Such as Figure 17 Or Figure 18 The AI calculation module is within the control module.

[0105] Such as Figure 19 The control module includes a network component. The AI calculation module is arranged in the server, and the network component is electrically connected to the AI calculation module through the network.

[0106] It can be that the height H of the containing cavity is obtained by measurement before leaving the factory.

[0107] It can be that the height H of the containing cavity is obtained by measurement before or during use.

[0108] It can be that the density difference between the detection particles and the test sample is greater than 0.01 and less than 0.1.

[0109] It can be that the scale accuracy of the height H of the containing cavity is higher than the set value. The set value is less than 15%.

[0110] For example Figures 18 to 22 It further includes a driving module; the control module is electrically connected to the driving module; the supporting component includes an X slide table component, and the driving module is electrically connected to the X slide table component, and the driving module is used to drive the X slide table component; the detection sample accommodating device is placed on the slide table of the X slide table component, and the detection sample accommodating device can move in the X-axis direction.

[0111] For example Figure 21 It can be that it further includes a circuit board A and a circuit board B, the AI computing module is arranged on the circuit board A, and the control module is arranged on the circuit board B.

[0112] For example Figure 22 It can be that it further includes a circuit board C, and the AI computing module and the control module are arranged on the circuit board C.

[0113] It can be that the supporting component includes a Y slide table component, the X slide table component is placed on the slide table of the Y slide table component, the driving module is electrically connected to the Y slide table component, the driving module is used to drive the Y slide table component, and the detection sample accommodating device can move in the X-axis or Y direction.

[0114] For example Figures 20 to 22 The imaging module includes a Z-axis slide table component and a microscopic camera component. The microscopic camera component is mechanically connected to the slide table in the Z-axis slide table component, and the microscopic camera component can move in the Z-axis direction.

[0115] It can be that the detected particles are polymer particles or magnetic bead particles.

[0116] It can be that the detected particles adsorb or conjugate with an antibody or an antigen.

[0117] It can be that the target includes any one of proteins, sugars or enzymes; the surface of the detected particles is labeled with avidin, and the binding and aggregation is an affinity reaction.

[0118] It can be that the target includes avidin; the surface of the detected particles includes any one of proteins, sugars or enzymes, and the binding and aggregation is an affinity reaction.

[0119] It can be that the detection sample includes body fluids or excreta; body fluids include serum, plasma, whole blood, saliva, local body fluid accumulation, and excreta include urine, feces; the feces are diluted feces.

[0120] It can be that the visible particle aggregates are irradiated with excitation light, and the visible particle aggregates emit fluorescence when excited by the excitation light, and the number or area or volume or fluorescence intensity of the visible particle aggregates emitting fluorescence is obtained.

[0121] For example Figures 17 to 22, the support component includes a light source component, and the light source component includes a white light source. The white light emitted by the white light source is used to irradiate the accommodation cavity.

[0122] Alternatively, the support component includes an excitation light source component, and the excitation light source component includes a purple light source. The purple light emitted by the purple light source is used to irradiate the accommodation cavity.

[0123] Alternatively, the camera module is above or below the support component.

[0124] Such as Figure 23 , a detection sample accommodation device for visual particle aggregate detection, includes an accommodation cavity A and a sample addition port; the sample addition port is communicated with the accommodation cavity A; the sample addition port is used to add a detection sample; the height H of the accommodation cavity A; the height H of the accommodation cavity is used to calculate the volume of the detection sample, and the volume of the detection sample = the area of the detection sample corresponding to the image × the height H of the accommodation cavity; the accommodation cavity A is used to accommodate the detection sample; the detection sample includes detection particles, and the detection particles are adsorbed or coupled with antibodies or antigens; the target analyte in the detection sample aggregates with the detection particles to form a visual particle aggregate; the upper and lower parts of the accommodation cavity include transparent windows, and external illumination light can enter the accommodation cavity through the transparent windows; through the transparent windows, an image of the visual particle aggregate is taken.

[0125] Such as Figure 23 , further includes an accommodation cavity B, and the sample addition port is communicated with the accommodation cavity B; the accommodation cavity B is used to accommodate the detection sample of species B; the scale accuracy of the height of the accommodation cavity B is higher than a set value; the accommodation cavity A is used to accommodate the detection sample of species A; the height of the accommodation cavity A is higher than the height of the accommodation cavity B.

[0126] Such as Figure 23 , the accommodation cavity A and the accommodation cavity B are connected in series and communicated, and are used for the liquid to be detected to be poured into the accommodation cavity A and the accommodation cavity B in sequence.

[0127] Such as Figure 24 , the accommodation cavity A and the accommodation cavity B are connected in parallel and communicated, and are used for the liquid to be detected to be poured into the accommodation cavity A and the accommodation cavity B simultaneously.

[0128] Such as Figure 25 , the accommodation cavity A and the accommodation cavity B are not connected in parallel. The sample addition port includes a sample addition port A and a sample addition port B. The accommodation cavity A is communicated with the sample addition port A, and the accommodation cavity B is communicated with the sample addition port B.

[0129] Such as Figures 23 to 25 , further includes an exhaust port; the exhaust port is communicated with the accommodation cavity A; the exhaust port is communicated with the accommodation cavity B; the exhaust port is communicated with the external atmosphere.

[0130] It is possible that the height H of the accommodation cavity A or B is measured before leaving the factory. The height H is printed on the surface of the detection sample accommodation device through a QR code or a bar code.

[0131] It is possible that the height H of the accommodation cavity A or B is measured before use or during use.

[0132] It is possible that the density difference between the detection particles and the detection sample is greater than 0.01 and less than 0.1. If the density difference is too large, it is difficult for the detection particles to fully combine with the sample and they will sink to the bottom. If the density difference is too small, the detection particles will float in the sample and it will be impossible to accurately capture images.

[0133] It is possible that the scale accuracy of the height of the accommodation cavity A is higher than the set value; the set value is less than 15%. In the field of veterinary detection, the accuracy can be required to be a little looser. For example, when the accuracy reaches below 8% for detection consistency, good detection consistency can be achieved. In the field of human medical detection, when the accuracy reaches below 5%, the required detection consistency and detection accuracy can be achieved.

[0134] It is possible that the average diameter of the detection particles is H2, and the height of the accommodation cavity A or B is greater than 50 times the height of H2. The aggregation of detection particles has a certain volume. If the height is not enough, the detection particles will block the cavity, resulting in the ineffective flow of the sample and the inability to conduct the test.

[0135] It is possible that the upper parts of the accommodation cavity A and the accommodation cavity B are made of transparent materials.

[0136] It is possible that the lower parts of the accommodation cavity A and the accommodation cavity B are made of transparent materials.

[0137] It is possible that the accommodation cavity A and the accommodation cavity B have bottoms of the same height.

[0138] It is possible that the accommodation cavity A and the accommodation cavity B have tops of the same height.

[0139] It is possible that the detection sample includes body fluids or excreta; body fluids include serum, plasma, whole blood, saliva, local body fluid effusions, and excreta include urine, feces; the feces are diluted feces.

[0140] Although the present invention is described and illustrated according to preferred embodiments and several alternative solutions, the invention is not limited by the specific descriptions in this specification. Other additional alternatives or equivalent components can also be used to practice the present invention.

Claims

1. A visible particle aggregate detection device for testing a target substance in a detection sample, where the detection sample is formed by adding detection particles to a sample; the detection sample is added to a containing cavity inside a detection sample containing device, and the target substance in the detection sample binds and aggregates with the detection particles to form visible particle aggregates; characterized in that, it includes a control module, a camera module, a support component, and an AI calculation module; The control module is electrically connected to the camera module; The control module includes a calculation module; the calculation module is electrically connected to the AI calculation module; The support component is used to place the detection sample containing device; the height H of the containing cavity; The camera module is used to photograph the containing cavity to obtain a detection sample image; The AI calculation module includes a storage unit; the storage unit is used to store visible particle aggregate AI feature data; The calculation module is used to calculate the volume V of the detection sample as V = S×H, where S is the selected area in the detection sample image; The AI calculation module is used to obtain the number of particles or the area of visible particle aggregates in the area S; The calculation module is used to calculate the number or content T1 of the target substance corresponding to the volume V of the detection sample; The calculation module is used to calculate the content T2 of the target substance per unit volume as T2 = T1 / V.

2. The visual particle aggregate detection device according to claim 1, wherein It includes any one or more of the following features: TB10: The AI calculation module is within the control module; TB20: The control module includes a network component; the AI calculation module is arranged in a server, and the network component is electrically connected to the AI calculation module through a network; TB30: The calculation module is used to record the height H of the containing cavity; TB31: It further includes a code scanning component, the code scanning component is electrically connected to the control module, the code scanning component is used to scan the code to obtain the height H of the containing cavity, and the height H is recorded on the detection sample containing device in the form of a bar code or a QR code; TB32: The density difference between the detection particles and the detection sample is greater than 0.01 and less than 0.1; TB40: The scale accuracy of the height H of the containing cavity is higher than a set value; the set value is less than 15%.

3. The visible particle aggregate detection device according to claim 1, characterized in that, It includes any one of the following features: TC10: The camera module includes a Z-axis slide table component and a microscopic camera component. The microscopic camera component is mechanically connected to the slide table in the Z-axis slide table component. The microscopic camera component can move in the Z-axis direction. The Z-axis slide table is electrically connected to the control module, and it further includes a power module, and the power module is connected to the Z-axis slide table by a cable; TC20: It further includes a driving module; the control module is electrically connected to the driving module; the support component includes an X-slide table component, and the driving module is electrically connected to the X-slide table component. The driving module is used to drive the X-slide table component; the detection sample containing device is placed on the slide table of the X-slide table component, and the detection sample containing device can move in the X-axis direction.

4. The visible particle aggregate detection device according to claim 3, characterized in that, In TC20, the support assembly includes a Y slide assembly. The X slide assembly is placed on the slide of the Y slide assembly. The drive module is electrically connected to the Y slide assembly and is used to drive the Y slide assembly. The detection sample holding device can move in the X-axis or Y direction.

5. The visible particle aggregate detection device according to claim 1, characterized in that it includes any one of the following features: TD10: It further includes a circuit board A and a circuit board B. The AI calculation module is arranged on the circuit board A, and the control module is arranged on the circuit board B. The circuit board A and the circuit board B are connected by a cable. TD20: It further includes a circuit board C. The AI calculation module and the control module are arranged on the circuit board C. The circuit board C is connected to the camera module by a cable, and the circuit board C is connected to the support assembly by a cable.

6. The visual particle aggregate detection device according to claim 1, characterized in that, it includes any one or more of the following features: TA10: The detection particles are polymer particles or magnetic bead particles. TA20: The detection particles adsorb or conjugate with antibodies or antigens. TA11: The target includes any one of proteins, carbohydrates, lipids, vitamins, and small molecule hormones. Antibodies are labeled on the surface of the detection particles, and the binding and aggregation are affinity reactions. TA12: The target includes antibodies. Any one of proteins, carbohydrates, lipids, vitamins, and small molecule hormones is included on the surface of the detection particles, and the binding and aggregation are affinity reactions. TA21: Specific antigens or antibodies are labeled on the surface of the detection particles, and the binding and aggregation are specific antigen-antibody bindings. TA22: Specific antibodies are labeled on the surface of the detection particles, and the binding and aggregation are immune reactions. TA30: The detection sample includes body fluids or excreta. Body fluids include serum, plasma, whole blood, saliva, and local body fluid effusions. Excreta include urine and feces. The feces are diluted feces. TA40: The visible particle aggregate is irradiated with excitation light. The visible particle aggregate is excited by the excitation light to emit fluorescence, and the number, area, volume, or fluorescence intensity of the visible particle aggregate emitting fluorescence is obtained.

7. The visible particle aggregate detection device according to claim 1, characterized in that it includes any one or more of the following features: TE1: The support assembly includes a light source assembly. The light source assembly includes a white light source, and the white light emitted by the white light source is used to irradiate the accommodation cavity. TE2: The support assembly includes an excitation light source assembly. The excitation light source assembly includes a purple light source, and the purple light emitted by the purple light source is used to irradiate the accommodation cavity. TE3: The camera module is above or below the support assembly.

8. A detection sample holding device is used for detecting visible particle aggregates in a visible particle aggregate detection device. The visible particle aggregate detection device is used for detecting samples. The detection sample includes detection particles, and the detection particles adsorb or conjugate with antibodies or antigens. The target detection substance in the detection sample aggregates with the detection particles to form visible particle aggregates. It is characterized in that it includes an accommodation cavity A and a sample addition port. The sample addition port is communicated with the accommodation cavity A. The sample addition port is used to add the detection sample. The height of the accommodation cavity A is equal to the set value H. The height H of the accommodation cavity is used for the visible particle aggregate detection device to calculate the volume of the detection sample. The visible particle aggregate detection device is used to calculate the volume of the detection sample = the area of the detection sample corresponding to the image × the height H of the accommodation cavity; The accommodation cavity A is used to accommodate the detection sample; The upper and lower parts of the accommodation cavity include transparent windows, and external illumination light can enter the accommodation cavity through the transparent windows; through the transparent windows, images of visible particle aggregates are taken.

9. The visible particle aggregate detection device according to claim 8, wherein It further includes an accommodation cavity B, a sampling port communicating with the accommodation cavity B; the accommodation cavity B is used to accommodate the detection sample of species B; the height of the accommodation cavity A is higher than the height of the accommodation cavity B.

10. The visual particle aggregate detection device according to claim 9, characterized in that, It includes any one or more of the following features: TF10: The accommodation cavity A and the accommodation cavity B are connected in series, and are used for pouring the liquid to be detected into the accommodation cavity A and the accommodation cavity B in sequence; TF20: The accommodation cavity A and the accommodation cavity B are connected in parallel, and are used for pouring the liquid to be detected into the accommodation cavity A and the accommodation cavity B simultaneously; TF30: The accommodation cavity A and the accommodation cavity B are not connected in parallel. The sampling port includes a sampling port A and a sampling port B. The accommodation cavity A is connected to the sampling port A, and the accommodation cavity B is connected to the sampling port B; TF40: It further includes an exhaust port; the exhaust port is connected to the accommodation cavity A; the exhaust port is connected to the accommodation cavity B; the exhaust port is connected to the external atmosphere; TF50: The height of the accommodation cavity A or B is recorded on the detection sample accommodation device with a barcode or a QR code; TF70: The scale accuracy of the height of the accommodation cavity A or the accommodation cavity B is higher than the set value; the set value is less than 15%; TF90: The average diameter of the detected particles is H2, and the height of the accommodation cavity A or B is greater than 50 times the height of H2; TG10: The upper parts of the accommodation cavity A and the accommodation cavity B are made of transparent materials; TG20: The lower parts of the accommodation cavity A and the accommodation cavity B are made of transparent materials; TG30: The accommodation cavity A and the accommodation cavity B have bottoms with the same height; TG40: The accommodation cavity A and the accommodation cavity B have tops with the same height.

11. The visible particle aggregate detection device according to claim 8, wherein It includes any one of the following technical features: TH10: The density difference between the detected particles and the detection sample is greater than 0.01 and less than 0.1; TH20: The detection sample includes body fluids or excreta; body fluids include serum, plasma, whole blood, saliva, local body fluid effusions, and excreta include urine, feces; the feces are diluted feces.

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