An interleukin detection kit and a capture microsphere antibody ratio optimization method thereof

Abstract

The present invention provides an interleukin detection kit and a method for optimizing its ratio, which belongs to the field of biological detection technology. The interleukin detection kit includes a capture microsphere antibody, a detection antibody, SA-PE, an experimental buffer and a washing buffer, wherein the capture microsphere antibody includes an IL-2RA capture microsphere antibody, an IL-18 capture microsphere antibody, an IL-33 capture microsphere antibody, an IL-23 capture microsphere antibody, an IL-27 capture microsphere antibody, and an IL-22 capture microsphere antibody; the detection antibody is a biotin-labeled interleukin paired antibody, which can reduce the problem of false negatives in the existing anti-interleukin antibody detection method. The capture microsphere antibody ratio optimization method of the interleukin detection kit optimizes the ratio through a small number of experiments, combined with a neighbor propagation clustering algorithm and a deep learning network, so that the interference between the optimized monoclonal antibodies is reduced, and the detection accuracy of the interleukin detection kit is improved.

Description

Technical Field

[0001] The present invention belongs to the field of biological detection technology, and in particular, relates to an interleukin detection kit and a method for optimizing the ratio of capture microspheres and antibodies thereof. Background Art

[0002] Interleukins are a type of cytokine that plays an important regulatory role in the immune system. Because of their large variety, they are also the most widely used type of cytokines. More than 40 interleukins have been discovered, and different family members play anti-inflammatory or pro-inflammatory roles due to their different cell sources and related signal regulation methods. Their abnormal expression can lead to the occurrence and development of immune diseases such as psoriasis, rheumatoid arthritis, asthma and cancer.

[0003] Existing antibody detection methods for interleukins have the problems of false positives and false negatives. The inventors have found that the root cause of the false negative problem is that after the double antibody sandwich method captures the interleukins in the sample, there is a problem of reduced efficiency in binding with the subsequent detection antibody, resulting in the failure to detect the positive sample, resulting in a false negative; the root cause of the false positive problem is that the large amount of irrelevant antibodies in the sample interfere, resulting in false positives and other detection distortions.

[0004] In addition, since different interleukin detection reagents such as interleukin-2RA / interleukin-18 / interleukin-33 / interleukin-23 / interleukin-27 / interleukin-22 detection reagents are used simultaneously, after the interleukins in the sample are captured using the double antibody sandwich method, there is a problem that multiple different interleukin detection reagents interfere with each other, resulting in reduced detection accuracy. Summary of the invention

[0005] In view of this, the present invention provides an interleukin detection kit, which can effectively reduce the false negative problem of existing interleukin antibody detection methods; and provides a capture microsphere antibody ratio optimization method for an interleukin detection kit, which can effectively solve the problem that after the interleukin in the sample is captured by the double antibody sandwich method, a variety of different interleukin detection reagents interfere with each other, resulting in reduced detection accuracy.

[0006] The present invention is achieved in that:

[0007] The first aspect of the present invention provides an interleukin detection kit, which includes a capture microsphere antibody, a detection antibody, SA-PE, an experimental buffer and a washing buffer, wherein the capture microsphere antibody includes IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, IL-22 capture microsphere antibody; the detection antibody is a biotin-labeled interleukin paired antibody; the SA-PE is phycoerythrin-labeled streptavidin; and the washing buffer is a phosphate buffer containing tween-20.

[0008] Furthermore, it also includes: stabilizer 1 and stabilizer 2, wherein the stabilizer 1 and stabilizer 2 are selected from one or more of disodium ethylenediaminetetraacetic acid, bovine serum albumin, sorbitol, glucose, and trehalose; and the inorganic salt is selected from one or more of sodium chloride, potassium chloride, magnesium chloride, and magnesium sulfate.

[0009] Furthermore, it also includes: a surfactant, wherein the surfactant is selected from one or more of Tween series, Triton series, lauryl alcohol polyoxyethylene ether, fatty alcohol polyoxyethylene ether, and sophorolipid.

[0010] Furthermore, it also includes: a coagulant, wherein the coagulant is selected from one or more of polyethylene glycol 6000, polyethylene glycol 8000, and polyethylene glycol 20000.

[0011] Furthermore, it also includes: a preservative, wherein the preservative is selected from one or more of sodium azide, proclin 300, sodium thimerosal, phenol, and ethyl paraben.

[0012] Furthermore, it also includes: an antioxidant, wherein the antioxidant is selected from one or more of L-ascorbic acid, dilauryl thiodipropionate, 2,6-di-tert-butyl-p-cresol, butylated hydroxyanisole, butylated hydroxytoluene, and tert-butylhydroquinone.

[0013] On the basis of the above technical solution, the interleukin detection kit of the present invention can also be improved as follows:

[0014] Among the capture microsphere antibodies, the concentrations of IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody are all 0.1 to 5 μg / mL.

[0015] Wherein, the experimental buffer is selected from one or more of tris(hydroxymethylaminomethane)-hydrochloric acid buffer, 3-morpholinepropanesulfonic acid buffer, 4-hydroxyethylpiperazineethanesulfonic acid buffer, piperazine-1,4-diethanesulfonic acid buffer, 2-(N-morpholino)ethanesulfonic acid buffer, 3-(cyclohexylamino)2-hydroxy-1-propanesulfonic acid buffer, glycine buffer, citric acid buffer, sodium barbital buffer, boric acid buffer, and phosphate buffer.

[0016] Furthermore, the experimental buffer also includes bovine serum albumin.

[0017] Wherein, the experimental buffer is a phosphate buffer containing bovine serum albumin.

[0018] Further, preferably, among the capture microsphere antibodies, the concentrations of IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody are all 1 to 5 μg / mL.

[0019] A second aspect of the present invention provides a method for optimizing the ratio of capture microsphere antibodies of an interleukin detection kit, wherein the method is used to optimize the ratio of the concentrations of IL-2RA capture microsphere antibodies, IL-18 capture microsphere antibodies, IL-33 capture microsphere antibodies, IL-23 capture microsphere antibodies, IL-27 capture microsphere antibodies, and IL-22 capture microsphere antibodies in the capture microsphere antibodies of the above-mentioned interleukin detection kit, and the method comprises the following steps:

[0020] S10: for each mAb of the capture microsphere antibody, prepare a serial concentration of mAb;

[0021] S20: respectively detecting the prepared monoclonal antibody and the human test sample by microsphere flow immunofluorescence luminescence method, and obtaining the concentration of each of the IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody, which is recorded as the first concentration set;

[0022] S30: combining the prepared monoclonal antibodies of the sequence concentrations in pairs to form a mixed solution, and using a microsphere flow immunofluorescence luminescence method to detect each group of mixed solutions and the human test sample to be tested, to obtain the concentration of each of the IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody, which is recorded as the second concentration set;

[0023] S40: for each antibody, screening the concentration in the second concentration set that has the smallest difference from the first concentration set as the third concentration set;

[0024] S50: taking the mixed solution ratio corresponding to the third concentration set as the basic ratio;

[0025] S60: using the neighbor propagation clustering algorithm to cluster the obtained basic ratios into one category, and calculating the cluster center of the changed category as the concentration ratio of each type of monoclonal antibody in the capture microsphere antibody;

[0026] S70: preparing capture microsphere antibodies according to the obtained concentration ratio of each type of monoclonal antibody.

[0027] On the basis of the above technical solution, the method for optimizing the ratio of capture microspheres and antibodies in an interleukin detection kit of the present invention can also be improved as follows:

[0028] Furthermore, the concentration value interval of the sequence concentration is no greater than 1 μg / mL.

[0029] Furthermore, the concentration value interval is 0.25 μg / mL.

[0030] Furthermore, the specific steps of step S50 include:

[0031] S51: establishing a deep learning network model, taking the sequence concentration of each monoclonal antibody as an input layer and the third concentration set as an output layer, training the deep learning network model to obtain a concentration optimization model;

[0032] S52: reducing the concentration value interval of the sequence concentration to obtain a new sequence concentration, and calculating the new sequence concentration using the obtained concentration optimization model to obtain a fourth concentration set;

[0033] S53: repeat step S52 until convergence;

[0034] S54: taking the mixed liquid ratio corresponding to the fourth concentration set obtained after convergence as the basic ratio.

[0035] Furthermore, the convergence condition of step S53 is that the difference between the fourth concentration set obtained last and the fourth concentration set obtained last time is less than a specified value.

[0036] The specified value shown can be determined based on experience; preferably, the specified value is 3%.

[0037] Compared with the prior art, the interleukin detection kit provided by the present invention has the following beneficial effects: the fluorescent microsphere-coupled IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, IL-22 capture microsphere antibody and biotin-labeled interleukin paired antibody are respectively combined with the interleukins in the sample or calibrator to form a "sandwich" complex, and then react with the added phycoerythrin-labeled streptavidin (SA-PE), which effectively avoids the existence of the binding effect with the subsequent detection antibody element after the anti-interleukin antibody in the sample is captured. On the other hand, the present invention solves the problem of reduced detection rate and effectively reduces the problem of false negatives in existing anti-interleukin antibody detection methods; on the other hand, the beneficial effect of the method for optimizing the capture microsphere antibody ratio of an interleukin detection kit provided by the present invention is that through a small amount of experiments combined with computer model calculations, an optimized capture microsphere antibody ratio is obtained, so that the interference between the IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody in the capture microsphere antibody is reduced, thereby improving the detection accuracy of the interleukin detection kit. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0039] Figure 1 A flow chart of a method for optimizing the ratio of capture microspheres and antibodies in an interleukin detection kit provided by the present invention;

[0040] Figure 2 A specific flow chart of step S50 in a method for optimizing the ratio of capture microspheres and antibodies in an interleukin detection kit provided by the present invention;

[0041] Figure 3 It is the block diagram of the Affinity Propagation Clustering (AP) algorithm. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0045] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0046] The first aspect of the present invention provides an interleukin detection kit, comprising a capture microsphere antibody, a detection antibody, SA-PE, an experimental buffer and a washing buffer, wherein the capture microsphere antibody comprises polystyrene, IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, IL-22 capture microsphere antibody; the detection antibody is a biotin-labeled interleukin paired antibody; SA-PE is phycoerythrin-labeled streptavidin; and the washing buffer is a phosphate buffer containing tween-20.

[0047] Wherein, the microspheres are fluorescent microspheres;

[0048] Furthermore, it also includes: stabilizer 1 and stabilizer 2, wherein stabilizer 1 and stabilizer 2 are selected from one or more of disodium ethylenediaminetetraacetic acid, bovine serum albumin, sorbitol, glucose, and trehalose; and the inorganic salt is selected from one or more of sodium chloride, potassium chloride, magnesium chloride, and magnesium sulfate.

[0049] Furthermore, it also includes: a surfactant, wherein the surfactant is selected from one or more of the group consisting of Tween series, Triton series, lauryl alcohol polyoxyethylene ether, fatty alcohol polyoxyethylene ether, and sophorolipids.

[0050] Furthermore, it also includes: a coagulant, wherein the coagulant is selected from one or more of polyethylene glycol 6000, polyethylene glycol 8000, and polyethylene glycol 20000.

[0051] Furthermore, it also includes: a preservative, wherein the preservative is selected from one or more of sodium azide, proclin 300, sodium thimerosal, phenol, and ethyl paraben.

[0052] Furthermore, it also includes: an antioxidant, wherein the antioxidant is selected from one or more of L-ascorbic acid, dilauryl thiodipropionate, 2,6-di-tert-butyl-p-cresol, butylated hydroxyanisole, butylated hydroxytoluene, and tert-butylhydroquinone.

[0053] The fluorescent microspheres are prepared by the following steps:

[0054] (1) Under nitrogen protection, polyvinyl pyrrolidone K30 and an initiator are dissolved in a mixed solution of deionized water and anhydrous ethanol, and the mixture is stirred to obtain a mixed solution, styrene is added to the mixed solution, and then reacted at 45° C. for 25-35 minutes, and then the temperature is increased to 70° C. and reacted for 8-12 hours to obtain an emulsion;

[0055] (2) centrifuging the emulsion obtained in step (1), washing with ethanol, water, and ethanol in sequence to obtain microspheres, dispersing the obtained microspheres in an ethanol solution, and obtaining polystyrene microspheres after sedimentation separation and drying;

[0056] (3) dissolving the polystyrene microspheres obtained in step (2) in a sodium dodecyl sulfate aqueous solution to obtain a polystyrene microsphere solution, dissolving allophycocyanin (APC) in a phosphate buffered saline solution to obtain a dye solution after ultrasonic dispersion, adding the dye solution to the polystyrene microsphere solution, stirring and ultrasonicating for 4-5 hours, washing with deionized water and anhydrous ethanol for multiple times until no fluorescence is detected in the supernatant, and drying to obtain the fluorescent microspheres; the mass fraction of sodium dodecyl sulfate in the sodium dodecyl sulfate aqueous solution is 20%.

[0057] Among them, in the above technical scheme, among the capture microsphere antibodies, the concentrations of IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody are all 0.1 to 5 μg / mL.

[0058] Among them, in the above technical scheme, the experimental buffer is selected from one or more of tris(hydroxymethylaminomethane)-hydrochloric acid buffer, 3-morpholinepropanesulfonic acid buffer, 4-hydroxyethylpiperazineethanesulfonic acid buffer, piperazine-1,4-diethanesulfonic acid buffer, 2-(N-morpholino)ethanesulfonic acid buffer, 3-(cyclohexylamino)2-hydroxy-1-propanesulfonic acid buffer, glycine buffer, citric acid buffer, sodium barbital buffer, boric acid buffer, and phosphate buffer.

[0059] Furthermore, the experimental buffer also includes bovine serum albumin.

[0060] Wherein, in the above technical solution, the experimental buffer is a phosphate buffer containing bovine serum albumin.

[0061] Furthermore, in the above technical solution, preferably, among the capture microsphere antibodies, the concentrations of IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody are all 1 to 5 μg / mL.

[0062] like Figure 1 As shown, it is a flow chart of a specific embodiment of a method for optimizing the ratio of capture microsphere antibodies of an interleukin detection kit according to the second aspect of the present invention. In this embodiment, the method is used to optimize the ratio of the concentrations of IL-2RA capture microsphere antibodies, IL-18 capture microsphere antibodies, IL-33 capture microsphere antibodies, IL-23 capture microsphere antibodies, IL-27 capture microsphere antibodies, and IL-22 capture microsphere antibodies in the capture microsphere antibodies of the above-mentioned interleukin detection kit, and the method comprises the following steps:

[0063] S10: for each mAb of the capture microsphere antibody, prepare a serial concentration of mAb;

[0064] S20: respectively detecting the prepared monoclonal antibody and the human test sample by microsphere flow immunofluorescence luminescence method, and obtaining the concentration of each of the IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody, which is recorded as the first concentration set;

[0065] S30: combining the prepared monoclonal antibodies of sequential concentrations in pairs to form a mixed solution, and using each group of mixed solutions and the human test sample to be tested to detect using microsphere flow immunofluorescence luminescence method to obtain the concentration of each antibody among IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody, which is recorded as the second concentration set;

[0066] S40: for each antibody, screening the concentration in the second concentration set that has the smallest difference from the first concentration set as the third concentration set;

[0067] S50: taking the mixed solution ratio corresponding to the third concentration set as the basic ratio;

[0068] S60: using the neighbor propagation clustering algorithm to cluster the obtained basic ratios into one category, and calculating the cluster center of the changed category as the concentration ratio of each type of monoclonal antibody in the capture microsphere antibody;

[0069] S70: preparing capture microsphere antibodies according to the obtained concentration ratio of each type of monoclonal antibody.

[0070] Among them, the proximity propagation clustering algorithm (AP) is a clustering algorithm based on graph theory. Its basic idea is to regard all samples to be clustered as nodes in the network and as potential clustering centers. The samples to be clustered are connected through similarity lines to form a network (similarity matrix S), and then the clustering center of the sample set to be clustered is calculated by transmitting the messages (responsibility and availability) of each edge in the network. The block diagram of the proximity propagation clustering algorithm is shown in the attached figure. Figure 3 shown.

[0071] The similarity matrix S(j,h) is calculated based on the sample set to be clustered after data standardization preprocessing. S(j,h) represents the ability of the concentration h of the monoclonal antibody in the basic ratio to be suitable as the cluster center of the data point j. Generally, the negative Euclidean distance is used:

[0072] S(j,h)=-‖x j -x h ‖ 2

[0073] For all samples to be clustered in the network, we can calculate the attraction matrix R(j,h) and the attribution matrix A(j,h) with the help of the idea of ​​adjacency matrix in graph theory. R(j,h) represents the degree of attraction of each candidate cluster center h to cluster sample j relative to other candidate cluster centers h′, and A(j,h) represents the attribution of each sample to be clustered j to the candidate cluster center h:

[0074]

[0075]

[0076] A t+1 (j,h)=∑ j′≠h max{0,R t+1 (j′,h)}

[0077] In the formula, t represents the number of iterations. In order to avoid oscillation of R(j,h) and A(j,h) during the iterative calculation process, the attenuation factor λ is introduced:

[0078] R t+1 (j,h)=(1-λ)R t+1 (j,h)+λR t (j,h)

[0079] A t+1 (j,h)=(1-λ)A t+1 (j,h)+λA t (j,h)

[0080] The value range of the attenuation factor λ is (0,1).

[0081] The AP algorithm achieves clustering effect by iteratively updating the values ​​of the attraction matrix R(j,h) and the attribution matrix A(j,h). When R(j,h) and A(j,h) reach stability or the maximum number of iterations is reached, the algorithm iteration ends, and the sample to be clustered with the largest R(j,h)+A(j,h) is selected as the clustering center c, and c is used as the concentration ratio of each type of monoclonal antibody in the capture microsphere antibody.

[0082] Furthermore, in the above technical solution, the concentration value interval of the sequence concentration is no more than 1 μg / mL.

[0083] Furthermore, in the above technical solution, the concentration value interval is 0.25 μg / mL.

[0084] Furthermore, in the above technical solution, the specific steps of step S50 include:

[0085] S51: establishing a deep learning network model, taking the sequence concentration of each monoclonal antibody as the input layer and the third concentration set as the output layer, training the deep learning network model to obtain a concentration optimization model; wherein the convolutional neural network of the deep learning network model includes 1 input layer, 3 convolutional layers, 3 Relu nonlinear activation layers, 3 pooling layers, 1 fully connected layer and 1 output layer;

[0086] S52: reducing the concentration value interval of the sequence concentration to obtain a new sequence concentration, and calculating the new sequence concentration using the obtained concentration optimization model to obtain a fourth concentration set;

[0087] S53: repeat step S52 until convergence;

[0088] S54: taking the mixed liquid ratio corresponding to the fourth concentration set obtained after convergence as the basic ratio.

[0089] Further, in the above technical solution, the convergence condition of step S53 is that the difference between the fourth concentration set obtained last and the fourth concentration set obtained last time is less than a specified value; wherein the specified value can be determined based on experience; preferably, the specified value is 3%. The difference here adopts the average value of the difference of each monoclonal antibody concentration.

[0090] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for optimizing the ratio of capture microspheres and antibodies in an interleukin detection kit, characterized in that: The method is used to optimize the concentration ratio of IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody in the capture microsphere antibody of the interleukin detection kit, and the method comprises the following steps: S10: for each mAb of the capture microsphere antibody, prepare a serial concentration of mAb; S20: respectively detecting the prepared monoclonal antibody and the human test sample by microsphere flow immunofluorescence luminescence method, and obtaining the concentration of each of the IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody, which is recorded as the first concentration set; S30: combining the prepared monoclonal antibodies of the sequence concentrations in pairs to form a mixed solution, and using a microsphere flow immunofluorescence luminescence method to detect each group of mixed solutions and the human test sample to be tested, to obtain the concentration of each of the IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody, which is recorded as the second concentration set; S40: for each antibody, screening the concentration in the second concentration set that has the smallest difference from the first concentration set as the third concentration set; S50: taking the mixed solution ratio corresponding to the third concentration set as the basic ratio; S60: using the neighbor propagation clustering algorithm to cluster the obtained basic ratios into one category, and calculating the cluster center of the category as the concentration ratio of each type of monoclonal antibody in the capture microsphere antibody; S70: preparing capture microsphere antibodies according to the obtained concentration ratio of each type of monoclonal antibody.

2. The method for optimizing the ratio of capture microspheres and antibodies in an interleukin detection kit according to claim 1, characterized in that: The concentration value interval of the sequence concentration is no greater than 1 μg / mL.

3. The method for optimizing the ratio of capture microspheres and antibodies in an interleukin detection kit according to claim 2, characterized in that: The concentration value interval is 0.25 μg / mL.

4. The method for optimizing the ratio of capture microspheres and antibodies in an interleukin detection kit according to claim 3, characterized in that: The specific steps of step S50 include: S51: establishing a deep learning network model, taking the sequence concentration of each monoclonal antibody as an input layer and the third concentration set as an output layer, training the deep learning network model to obtain a concentration optimization model; S52: reducing the concentration value interval of the sequence concentration to obtain a new sequence concentration, and calculating the new sequence concentration using the obtained concentration optimization model to obtain a fourth concentration set; S53: repeat step S52 until convergence; S54: taking the mixed liquid ratio corresponding to the fourth concentration set obtained after convergence as the basic ratio.

5. The method for optimizing the ratio of capture microspheres and antibodies in an interleukin detection kit according to claim 4, characterized in that: The convergence condition of step S53 is that the difference between the fourth concentration set obtained last and the fourth concentration set obtained last time is less than a specified value.

6. An interleukin detection kit, characterized in that: It includes capture microsphere antibody, detection antibody, SA-PE, experimental buffer and washing buffer, wherein the capture microsphere antibody includes IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, IL-22 capture microsphere antibody; the detection antibody is a biotin-labeled interleukin paired antibody; the SA-PE is phycoerythrin-labeled streptavidin; the washing buffer is a phosphate buffer containing tween-20; Among the capture microsphere antibodies, the concentrations of IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody are all 0.1 to 5 μg / mL, and the concentration ratio of the above capture microsphere antibodies is obtained by the capture microsphere antibody ratio optimization method of the interleukin detection kit according to claim 1.

7. An interleukin detection kit according to claim 6, characterized in that: The experimental buffer is selected from one or more of tris(hydroxymethylaminomethane)-hydrochloric acid buffer, 3-morpholinepropanesulfonic acid buffer, 4-hydroxyethylpiperazineethanesulfonic acid buffer, piperazine-1,4-diethanesulfonic acid buffer, 2-(N-morpholino)ethanesulfonic acid buffer, 3-(cyclohexylamino)2-hydroxy-1-propanesulfonic acid buffer, glycine buffer, citric acid buffer, sodium barbital buffer, boric acid buffer, and phosphate buffer; the experimental buffer also includes bovine serum albumin.

8. An interleukin detection kit according to claim 7, characterized in that: The experimental buffer is a phosphate buffer containing bovine serum albumin.

9. An interleukin detection kit according to claim 8, characterized in that: Among the capture microsphere antibodies, the concentrations of IL-2RA capture microsphere antibody, IL-18 capture microsphere antibody, IL-33 capture microsphere antibody, IL-23 capture microsphere antibody, IL-27 capture microsphere antibody, and IL-22 capture microsphere antibody are all 1 to 5 μg / mL.

Images