Method and device for calculating IgA immune activity index of sample

Abstract

The present invention discloses a method and device for calculating the IgA immune activity index. In a first aspect of the present application, a method for calculating the IgA immune activity index is provided, the method comprising the following steps: step 1: obtaining an absorbance value; step 2: converting the absorbance value into a detection amount of an IgA complex according to a regression model; step 3: setting an intra-plate anchor value for the detection amount on an enzyme labeling plate, and calculating the intra-plate normalized detection amount of the IgA complex; step 4: setting an inter-plate anchor value for the detection amount between a number of enzyme labeling plates, and calculating the inter-plate normalized detection amount. The method obtains the original OD value of each well on the enzyme labeling plate, first performs quality control at the well level, calculates the detection amount of the IgA complex in the well by fitting, and then performs quality control at the plate level, normalizes the data at the enzyme labeling plate level, and removes the inter-plate difference of the enzyme labeling plate. In this way, the accuracy of large-scale detection can be further improved.

Description

Technical Field

[0001] The present application relates to the field of immune detection technology, and in particular to a method and device for calculating the IgA immune activity index of a sample. Background Art

[0002] During the body's autoimmune response, immunoglobulin A (IgA) binds to pathogens, initiating an immune response. Downstream, antibodies IgG and IgM, complement molecules such as C3, form IgA-IgG, IgA-IgM, IgA-C3, and IgA-IgG-IgM, collectively known as IgA complexes. During a normal immune response, these pathogen-bound complexes are typically cleared by the immune system, for example, by phagocytosis by macrophages. However, when the IgA immune response is abnormal, IgA complexes cannot be effectively cleared by the immune system and instead remain in the circulatory and urinary systems for a long time, leading to two diseases. Specifically, the accumulation and retention of IgA complexes in the kidneys leads to IgA nephropathy (IgAN); the accumulation of IgA complexes in the blood vessels leads to purpura, commonly known as Henoch-Schonlein purpura (HSP) or IgA vasculitis (IgAV).

[0003] In the existing method, diagnosis is usually carried out by immunoassay of serological total IgA, and total IgA detection is any one of the routine immune three items (IgA, IgM, IgG) or immune five items (immune three items+complement C3, C4) items clinically. However, the factors that increase total IgA may also be due to other diseases such as multiple myeloma, rheumatoid arthritis, thrombocytopenia, infectious diseases, etc., in addition to IgA nephropathy and purpura, so the specificity of total IgA to IgA nephropathy and purpura is on the low side. For this reason, the applicant attempts to proceed from its principle, because circulating IgA complex in serum is the main inducing pathogenic factor, so the detection amount of direct detection IgA complex is used as the index of IgA immune activity to replace the detection of immune three items or immune five items. However, although this method has better sensitivity and specificity, it still inevitably brings some problems when facing batch diagnosis of large sample sizes due to problems such as the experimenter's operation and the inter-plate variability of the ELISA plate itself. Therefore, it is necessary to provide a calculation method for the IgA immune activity index that can further improve the accuracy of large-scale detection. Summary of the Invention

[0004] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a method for calculating the IgA immune activity index that can further improve the accuracy of large-scale detection.

[0005] In a first aspect of the present application, a method for calculating the IgA immune activity index of a sample is provided, the method comprising the following steps:

[0006] Obtain the absorbance OD value of each well on the nth ELISA plate;

[0007] The absorbance value OD was converted into the detection amount μ of IgA complex according to the regression model;

[0008] Set the plate anchor value ω of the detection amount on the nth ELISA plate n The normalized detection amount of IgA complex within the plate μ was calculated according to the following formula: n =μ-ω n ;

[0009] Set the inter-plate anchor value ω for the detection amount of the 1st to Nth ELISA plates N The inter-plate normalized detection amount μ of the IgA complex on the nth ELISA plate is calculated according to the following formula: F＝ μ n+ ω N , recorded as IgA immune activity index;

[0010] Wherein, n≤N and are all positive integers.

[0011] In some embodiments of the present application, the sample includes a test substance and a positive control substance, and the plate anchor value ω n It is the median of the detected amount of samples in the nth ELISA plate or the detected amount of the positive control in the nth ELISA plate.

[0012] In some embodiments of the present application, the inter-board anchor value ω N is the intra-plate anchor value ω of N ELISA plates n of the median.

[0013] In some embodiments of the present application, the regression model is a linear regression model.

[0014] In some embodiments of the present application, the absorbance value OD is converted into the detected amount μ of the IgA complex according to the following formula:

[0015] In some embodiments of the present application, each sample is provided with several replicate wells, and the deviation coefficient CV of the detection amount μ of the several replicate wells of each sample is calculated. When the deviation coefficient CV is ≥20%, the sample is determined to be an invalid sample.

[0016] In some embodiments of the present application, the sample includes different amounts of a standard substance and a negative control substance, and the absorbance OD value of each well of the ELISA plate is re-obtained when at least one of the following conditions is met:

[0017] a) Absorbance value of the maximum amount of standard <T0;

[0018] b) The correlation coefficient of the regression model < R0;

[0019] c) The deviation of the detected amount of the standard product from the calibrated amount > P0%;

[0020] d) The detected amount of the negative control product > Δ0.

[0021] In some embodiments of the present application, T0 is 0.6, R0 is 0.9, P0 is 30, and Δ0 is 0.1.

[0022] In the second aspect of the present application, a method for judging the IgA immune activity index is provided, and the method includes the following steps:

[0023] Calculate the IgA immune activity index μ of the subject according to the aforementioned method F ;

[0024] According to the IgA immune activity index μ of the subject F Perform the following judgment:

[0025] When μ F < m + 2σ, it is judged that the IgA immune activity index of the subject is within the normal basic range,

[0026] When m + 2σ ≤ μ [[ID=​​​​​​​​​​​​​​​​​​​​​​​In some embodiments of the present application, the physical examination report also includes general results of clinical experiments on the IgA immune activity index for reference by doctors and patients.

[0034] In some embodiments of the present application, the physical examination report also includes statistical characteristics of healthy people, standard curves, etc. for reference.

[0035] In a third aspect of the present application, a computer-readable storage medium is provided, which stores computer-executable instructions for causing a computer to execute the steps in the aforementioned method for calculating the IgA immune activity index or the method for determining the IgA immune activity index.

[0036] In a fourth aspect of the present application, a device is provided, which includes a processor and a memory, wherein the memory stores a computer program that can be run on the processor, and when the processor runs the computer program, it implements the aforementioned method for calculating the IgA immune activity index or the method for determining the IgA immune activity index.

[0037] A fifth aspect of the present application provides a system, the system comprising:

[0038] The acquisition module is used to obtain the absorbance value OD of each well in the ELISA plate;

[0039] The detection amount calculation module and the detection analysis module are used to convert the absorbance value OD into the detection amount μ of the IgA complex according to the regression model;

[0040] The normalized detection amount calculation module is used to calculate the normalized detection amount μ of the IgA complex according to the following formula: n =μ-ω n , where ω n is the anchor value within the board;

[0041] The inter-plate normalized detection amount calculation module is used to calculate the inter-plate normalized detection amount μ of the IgA complex according to the following formula: F =μ n+ ω N , where ω N is the inter-board anchor value.

[0042] In some embodiments of the present application, the system further includes a well quality control module configured to calculate a coefficient of variation (CV) of the detection amount μ of a plurality of replicate wells of each sample. When the coefficient of variation (CV) is ≥ 20%, the sample is deemed invalid.

[0043] In some embodiments of the present application, the system further includes a plate quality control module, which is used to judge the following indicators in the enzyme-labeled plate. When any of the following conditions is met, the enzyme-labeled plate is determined to be an invalid enzyme-labeled plate:

[0044] a) The absorbance value of the maximum detectable standard < T0;

[0045] b) The correlation coefficient of the regression model < R0;

[0046] c) The deviation coefficient of the detected amount of the positive control from the calibrated amount > P0%;

[0047] d) The detected amount of the negative standard > Δ0;

[0048] In some embodiments of the present application, T0 is 0.6, R0 is 0.9, P0 is 30, and Δ0 is 0.1.

[0049] In some embodiments of the present application, the system further includes an IgA immune activity index analysis module, which is used to analyze the relationship between the IgA immune activity index μ F and the average value m of the IgA immune activity index of normal people,

[0050] When μ F < m + 2σ, it is judged that the IgA immune activity index of the subject is within the normal basic range,

[0051] When m + 2σ ≤ μ F < m + 3σ, it is judged that the IgA immune activity index of the subject is on the high side within the basic range,

[0052] When μ F ≥ m + 3σ, it is judged that the IgA immune activity index of the subject is on the high side within the abnormal range;

[0053] where σ is the standard deviation of the IgA immune activity index of normal people.

[0054] In some embodiments of the present application, the system further includes a physical examination report generation module, which is used to judge the IgA immune activity index of the subject according to the relationship between the IgA immune activity index and the average value m of the IgA immune activity index of normal people.

[0055] In some embodiments of the present application, the physical examination report includes the IgA immune activity index, the interval standard of the index, and the IgA immune activity index data corresponding to the subject.

[0056] In some embodiments of the present application, the physical examination report further includes the effectiveness of the quality control result during the detection.

[0057] In some embodiments of the present application, the physical examination report also includes general information of the subject.

[0058] In some embodiments of the present application, the physical examination report also includes general results of clinical experiments on the IgA immune activity index for reference by doctors and patients.

[0059] In some embodiments of the present application, the physical examination report also includes statistical characteristics of healthy people, standard curves, etc. for reference.

[0060] The method for calculating the IgA immune activity index according to the embodiment of the present application has at least the following beneficial effects:

[0061] This method uses, for example, an enzyme-linked immunosorbent assay (ELISA) to obtain the raw OD values ​​of each well on an ELISA plate. Well-level quality control is first performed. A standard curve is fitted to derive a formula for converting OD values ​​to sample quantification, which is then used to calculate the amount of IgA complex detected in the well. Plate-level quality control is then performed, and the plate-level data is normalized to remove inter-plate variations. Finally, the calculation is repeated for each sample to determine the final quantitative result. This approach can further improve the accuracy of large-scale testing.

[0062] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become obvious from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 This is a flow chart for calculating the IgA immune activity index provided in an embodiment of the present application.

[0064] Figure 2 This is another flow chart for calculating the IgA immune activity index provided in an embodiment of the present application.

[0065] Figure 3 These are the results of constructing linear regression models in different ways in Example 1 of the present application. a is a linear regression model constructed directly using OD values ​​and detection amounts, and b is a linear regression model constructed using the logarithms of OD values ​​and detection amounts.

[0066] Figure 4 This is the distribution of the IgA immune activity index of 33 healthy people in Example 2 of the present application, a is its probability density distribution, the horizontal axis is the value of the IgA immune activity index, and the vertical axis is the proportion of the number of people; b is its QQ graph; c is its cumulative distribution graph; d is its PP graph.

[0067] Figure 5 This is a schematic diagram of the physical examination report provided in Example 3 of the present application. DETAILED DESCRIPTION

[0068] The following will clearly and completely describe the concept and technical effects of this application in conjunction with the embodiments to fully understand the purpose, features and effects of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments of this application, other embodiments obtained by those skilled in the art without creative work are all within the scope of protection of this application.

[0069] The embodiments of the present application are described in detail below. The described embodiments are exemplary and are only used to explain the present application, and should not be understood as limiting the present application.

[0070] In the description of this application, "several" means more than one, "multiple" means more than two, "greater than," "less than," and "exceed" are understood to be exclusive of the number itself, while "above," "below," and "within" are understood to be inclusive of the number itself. The use of "first" and "second" is solely for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of the indicated technical features, or implicitly indicating the order of the indicated technical features. Even if a logical sequence is described in a flowchart, in some cases, the steps described or shown may be performed in a different order than that in the flowchart.

[0071] Throughout the description of this application, reference to terms such as "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of this application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0072] refer to Figure 1 , shows a method for calculating the IgA immune activity index in an embodiment of the present application, the method comprising the following steps:

[0073] S110, obtaining the absorbance value OD of each well on the nth ELISA plate.

[0074] Wherein, ELISA plate refers to an ELISA plate for performing an enzyme-linked immunosorbent assay (ELISA) experiment of an IgA complex, and a number of holes, such as 6 holes, 12 holes, 24 holes, 48 ​​holes, 96 holes, etc., are provided on the ELISA plate. In an embodiment of the present application, the IgA complex is fixed by binding to the probe in the hole, and then color is developed in combination with an enzyme-labeled secondary antibody. Specifically, the probe of the IgA complex is an Fc receptor protein of IgA, such as FCAR / CD89 protein, which can specifically bind to the IgA complex. In the ELISA process, it is usually necessary to set at least one of a standard substance, a reference substance, etc. A standard substance refers to a sample of an IgA complex containing a known detection amount (calibrated content), and a standard curve can be obtained by the gradient of the known detection amount given by it, or by diluting different known detection amounts to obtain a gradient and a corresponding absorbance value OD. The control substance generally includes at least one of a negative control substance and a positive control substance. The negative control substance does not contain IgA complex or its content is lower than the detection limit. The positive control substance contains IgA complex and the interfering substances therein are eliminated by various methods. It is used to evaluate whether the test results are valid and its stability and comparability. Both are quality control products. The absorbance value OD of each well refers to the reaction result of the colored product formed by the enzyme-labeled secondary antibody bound to the IgA complex fixed in the well and catalyzing the enzyme reaction substrate. It is understandable that in the detection process, usually each sample (including standard substances, test substances, control substances, etc.) will be repeated by setting a number of repetitions (for example, two to three).

[0075] S120. Convert the absorbance value OD into the detected amount μ of the IgA complex according to the regression model.

[0076] In this step, the regression model refers to a quantitative model for the statistical relationship between the absorbance value OD and the amount of IgA complex detected μ. Specifically, the regression model usually uses a linear regression model to fit the standard curve, for example, directly fitting the values ​​of the two: OD = κ × μ + δ; or fitting after taking the logarithm of the two: log2 (OD) = κ × log2 (μ) + δ. In some specific embodiments, after comparing the two linear regression models, the correlation coefficient R of the second model is 2 The value of is closer to 1, so the goodness of fit is better. Therefore, according to the second model, we get The specific values ​​of δ and κ are determined based on the calibration amount of the standard and the corresponding absorbance values. Based on this model, the absorbance values ​​(OD) of the remaining wells can be used to calculate the detected amount μ of the IgA complex in the remaining wells. The term "detectable amount" and the maximum amount mentioned below can refer to mass, concentration, or other measurements.

[0077] S130, setting the plate anchor value ω of the detection amount on the nth enzyme labeling plate nThe normalized detection amount of IgA complex within the plate μ was calculated according to the following formula: n =μ-ω n .

[0078] In this step, the anchor value ω is used n The detection amount of IgA complex in different wells of the same plate was normalized to the plate anchor value ω n The difference between the two makes it easier to align different ELISA plates to the same level in S140. n An arbitrary value that is relatively stable across different plates can be selected, for example, the detection amount of the positive control substance is used as the intra-plate anchor value ω n , or the median value of the detection amount of each test product within the effective gradient of the standard curve is used as the anchor value within the plate n .

[0079] S140, setting the inter-plate anchor value ω of the detection amount of the 1st to Nth ELISA plates N The inter-plate normalized detection amount μ of the IgA complex on the nth ELISA plate is calculated according to the following formula: F＝ μ n+ ω N , recorded as IgA immune activity index.

[0080] In this step, the inter-plate anchor value ω of the 1st to Nth ELISA plates is used. N The application of will normalize the detection amount that becomes the difference to the actual level (n≤N and are all positive integers). In order to achieve this goal, the anchor value ω between plates N Preferably, the anchor value ω corresponding to each of the N ELISA plates can be used. n The median of, for example, for ω1, ω2, ... ω k The median of the k intra-board anchor values ​​is taken as the inter-board anchor value ω N It is understandable that ω N Other values ​​that are consistent with this concept can also be used as the inter-plate anchor value ω N Although there are certain differences in the actual detection amount of the test sample in different ELISA plates, which leads to certain difficulties in normalization, the median of the test sample between different plates will gradually stabilize as the number of test samples in the plate increases. Similarly, the positive control also has a relatively stable IgA complex content. Therefore, through the plate anchor value ω n and the inter-board anchor value ω NBy making a selection, stable anchor points are set, different enzyme-labeled plates are aligned to the same level, data normalization is performed, and inter-plate differences are eliminated. That is, first, the detected amounts of the enzyme-labeled plates are normalized to a level close to 0, and then, to approach the actual detected amounts, the anchor points normalized to close to 0 are adjusted up to the actual level.

[0081] Reference Figure 2 , to ensure the detection accuracy of the samples, before performing the normalization of S130 and S140, a discrimination step can be added. Due to quality problems in some wells of the enzyme-labeled plates or mistakes in the steps during the detection process, the detected results are unusable and are considered invalid and excluded. Retesting needs to be carried out subsequently.

[0082] For this reason, quality control is carried out from two aspects, including quality control at the well level within the enzyme-labeled plate and quality control at the enzyme-labeled plate level. Reference Figure 2 , quality control at the well level within the enzyme-labeled plate is achieved through step S121. Since several wells are repeated for each sample, the detected amounts of different repeated wells for the same sample are analyzed, and their coefficient of variation CV is calculated. When the coefficient of variation is higher than 20%, the error between different repeated wells of this sample is too large, and it is considered an invalid sample. After excluding all invalid samples, the next step is carried out. Specifically, the calculation formula for the coefficient of variation CV is CV = standard deviation / average × 100%. Therefore, according to this formula and the results of the detected amounts μ of all repeated wells of each sample, the coefficient of variation of the IgA complex detected amount of each sample is calculated. When the coefficient of variation is higher than 20%, it is considered an invalid sample. It can be understood that, in order to pursue better experimental accuracy, the threshold of the coefficient of variation can be values such as 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 8%, 5%, 3%, etc. Among them, the samples for which quality control is carried out at the well level can include standard products and positive control products. Of course, it can be understood that the detected amounts of the test samples can also be quality-controlled in this way.

[0083] After completing the quality control at the well level within the enzyme-labeled plate, further quality control at the enzyme-labeled plate level is required. Quality control at the enzyme-labeled plate level can be carried out in the following ways, including making the following determinations: a) the absorbance value of the maximum detected standard product < T0; b) the correlation coefficient of the regression model < R0; c) the detected amount of the standard product deviates from the calibrated amount > P0%; d) the detected amount of the negative control product > Δ0. When any of the above conditions is met, the enzyme-labeled plate will be considered an invalid enzyme-labeled plate. Specifically, for example, T0 is

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[0084] The embodiments of the present application also provide a method for judging the IgA immune activity index, and the method includes the following steps:

[0085] Calculate the IgA immune activity index μ of the subject according to the aforementioned method for calculating the IgA immune activity index F ;

[0086] According to the IgA immune activity index μ of the subject F Perform the following judgment:

[0087] When μ F < m + 2σ, it is judged that the IgA immune activity index of the subject is within the normal basic range,

[0088] When m + 2σ ≤ μ F < m + 3σ, it is judged that the IgA immune activity index of the subject is on the high side within the basic range,

[0089] When μ F ≥ m + 3σ, it is judged that the IgA immune activity index of the subject is on the high side within the abnormal range;

[0090] Among them, m is the average value of the IgA immune activity index of normal people, and σ is the standard deviation of the IgA immune activity index of normal people.

[0091] After obtaining the IgA immune activity index μ of each specific subject sample F It is possible to estimate the range in which the IgA immune activity index of the subject is located by comparing with the values of normal people. Further, according to the range in which the IgA immune activity index is located, directly or in combination with other indicators, it is possible to know whether the subject has IgA nephropathy or purpura. In the above judgment process, m and σ can be obtained after detecting a certain number of normal populations. The number of normal populations can be 20, 30, 50, 100, more than 200 people. The normal population specifically refers to people who have been determined not to have IgA nephropathy and purpura through various standard detections, or other diseases that may affect the detection of this index, or healthy people. It can be understood that in order to enhance the representativeness of m and σ, the normal population preferably includes people of all ages from children to the elderly, and preferably half of them are male and half are female or close to 1:1. m and σ can be obtained by any method known in the art according to the IgA immune activity index of each individual in the normal population, such as by direct mathematical calculation, or by fitting through normal distribution. Of course, in the above division intervals, the standards of 2σ and 3σ are not the only ones and can be appropriately adjusted according to the actual situation.

[0092] After the judgment result is obtained, a corresponding physical examination report can be generated for each subject. In addition to the relevant information of the IgA immune activity index, the physical examination report can also contain the relevant results of other test items, which will not be repeated here. For the IgA immune activity index, the physical examination report can provide the IgA immune activity index, the standards of each interval corresponding to the index, and the classification corresponding to the interval in which the subject's index falls, such as belonging to the normal basic range, or the basic range is higher, or abnormally higher. It is understandable that the physical examination report also contains the results of the quality control during the detection process, and provides the effectiveness results of the quality control to prove that the detection is effective. Of course, it also includes the subject's general information, such as name, etc. In addition, the physical examination report can also provide the general results of the clinical experiment of the IgA immune activity index, or the statistical characteristics of the normal population, standard curve, etc. for reference.

[0093] An embodiment of the present application also provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the steps in the aforementioned method for calculating the IgA immune activity index or the method for determining the IgA immune activity index.

[0094] An embodiment of the present application also provides a device comprising a processor and a memory, wherein the memory stores a computer program that can be run on the processor, and when the processor runs the computer program, it implements the aforementioned method for calculating the IgA immune activity index or the method for determining the IgA immune activity index.

[0095] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs, such as the process for determining the IgA immune activity index described in the embodiments of this application. The processor determines the subject's IgA immune activity index by executing the non-transitory software programs and instructions stored in the memory.

[0096] The memory may include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function, while the data storage area may store and execute the aforementioned computer programs. Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0097] In some embodiments of the present application, the memory may optionally include a memory remotely located relative to the processor, and the remote memory may be connected to the processor via a network. Examples of the aforementioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0098] The non-transitory software programs and instructions required to implement the above judgment are stored in the memory, and when executed by one or more processors, the above judgment is performed.

[0099] The present application also provides a system, which includes:

[0100] The acquisition module is used to obtain the absorbance value OD of each well in the ELISA plate;

[0101] The detection amount calculation module and the detection analysis module are used to convert the absorbance value OD into the detection amount μ of the IgA complex according to the regression model;

[0102] The normalized detection amount calculation module is used to calculate the normalized detection amount μ of the IgA complex according to the following formula: n =μ-ω n , where ω n is the anchor value within the board;

[0103] The inter-plate normalized detection amount calculation module is used to calculate the inter-plate normalized detection amount μ of the IgA complex according to the following formula: F =μ n+ ω N , where ω N is the inter-board anchor value.

[0104] The system implementation described above is merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0105] It is understood that all or some of the steps and systems disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include computer storage media (or non-transitory media) and communication media (or temporary media). It is understood that computer storage media include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory, or other memory technology, CD-ROM, digital versatile disks (DVD), or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage, or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer.

[0106] Additionally, it will be appreciated that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0107] The method provided in this application is described below with reference to specific embodiments.

[0108] Example 1

[0109] The following calculations and report generation were performed using the open-source development environment RStudio Version 1.4.1717, running macOS Big Sur Version 11.6.

[0110] 1. Detection of IgA complexes

[0111] The invention relates to a kit for detecting IgA complexes, which comprises molecular probe freeze-dried powder, coating buffer, enzyme-labeled plate, standard substance, enzyme-labeled secondary antibody, color developing solution, stop solution, washing solution, diluent and blocking solution.

[0112] Among them, the molecular probe lyophilized powder is the recombinant FCAR protein lyophilized powder;

[0113] The coating buffer was 0.05 M carbonate buffer (pH = 9.6);

[0114] The ELISA plate is a 96-well plate;

[0115] The standard substance is commercial human serum IgA containing IgA complex;

[0116] The negative control was human serum without IgA complexes;

[0117] The positive control was human serum containing IgA complex, and 25 ng of commercial human serum IgA was selected;

[0118] The enzyme-labeled secondary antibody was horseradish peroxidase (HRP)-labeled mouse anti-human IgA;

[0119] The color developing solution includes color developing solution A—3,3',5,5'-tetramethylbenzidine (TMB) and color developing solution B—hydrogen peroxide solution;

[0120] The stop solution is 10% sulfuric acid;

[0121] The washing solution was 0.15 M phosphate buffer containing 0.05% Tween-20;

[0122] The diluent was washing solution + 1‰ BSA;

[0123] The blocking solution was washing solution + 5% BSA.

[0124] The detection method of the above kit is as follows. Please refer to Figure 1 :

[0125] (1) dissolving the molecular probe lyophilized powder in a coating buffer to obtain a molecular probe solution;

[0126] (2) Add the molecular probe solution to each well of a 96-well ELISA plate, cover with a sealing film, and place in a 4°C environment overnight; shake off the solution in the wells, wash the ELISA plate several times with a washing solution, add the blocking solution to the ELISA plate, cover with a sealing film, and place in a 4°C environment overnight, wash the ELISA plate once with a washing solution, and dry to obtain the ELISA plate coated with the molecular probe;

[0127] (3) Dilute the sample to be tested with diluent to obtain sample dilution solution and standard gradient dilution solution (the detection amount is 50, 25, 12.5, 6.75, 3.375, and 1.5625 ng, respectively). The positive control and negative control are not diluted with diluent; then add the sample dilution solution, standard gradient dilution solution, negative control solution, and positive control solution to the ELISA plate coated with the molecular probe HQP001, cover with a sealing film and incubate. After the incubation, wash the ELISA plate 3 times with washing solution; add HRP-labeled secondary antibody to the ELISA plate and incubate. After the incubation, wash the ELISA plate 3 times; mix the color development solution A and the color development solution B in a ratio of 1:1 and add them to the ELISA plate. Color development is carried out at room temperature in the dark. After the color development is completed, add the stop solution, shake gently, and place the ELISA plate in an ELISA reader to detect the absorbance value (OD value). The first wavelength is 450nm and the second wavelength is 630nm.

[0128] Table 1 and Table 2 are respectively the sample mapping matrix of the ELISA plate and a portion of the OD value matrix obtained according to the sample mapping matrix of the ELISA plate and the test results.

[0129] Table 1. Sample mapping matrix local

[0130] STD1 STD1 B000001 B000001 B000001F B000001F STD2 STD2 B000002 B000002 B000002F B000002F STD3 STD3 B000003 B000003 B000003F B000003F STD4 STD4 B000004 B000004 B000004F B000004F STD5 STD5 B000005 B000005 B000005F B000005F STD6 STD6 Q2 Q2 Q7 Q7 nCtrl nCtrl Q4 Q4 Q8 Q8

[0131] Table 2. Partial OD value matrix

[0132] 1.863 2.123 0.626 0.709 0.691 0.601 1.44 1.767 1.05 1.081 1.015 0.849 0.989 0.946 1.272 1.319 1.229 1.132 0.563 0.61 0.988 1.035 1.006 0.992 0.331 0.346 0.991 0.954 1.009 0.861 0.173 0.16 0.84 0.891 0.499 0.521 0.020 0.011 0.448 0.531 0.626 0.653

[0133] As shown in Table 1, STD1-6 represent dilution standards with varying detection limits, nCtrl represents the negative control, B000001-5 represent the samples to be tested, and the tail "F" indicates whether the plasma sample was frozen (F: Frozen), used to compare samples stored under different conditions. Q2, Q4, Q7, and Q8 represent healthy control samples. Based on the table above, two replicates were set for each sample.

[0134] 2. Calculation of IgA Immune Activity Index

[0135] The linear regression was performed based on the OD value matrix of the standard, control, and test product obtained by the kit test to calculate the model parameters. The original OD value and the logarithmic OD value were used to perform linear regression to establish the model. The results are as follows: Figure 3 As shown, a is the regression model of the original OD value (OD = 0.0373 × μ + 0.331, rsq = 0.8908), and b is the regression model of the OD value after taking the logarithm (log2 (OD) = 0.7237 × log2 (μ) -2.826, rsq = 0.9759). The result shows that the logarithmic OD value model in b is more accurate. Therefore, the logarithmic OD value regression model in b is used to calculate the sample detection amount. The parameters in the logarithmic linear model are δ = -2.826 and κ = 0.7237, so the sample detection amount calculation formula is The detection amount of the samples calculated according to this formula is shown in Table 3.

[0136] Table 3. Partial detection matrix

[0137] 35.39 42.39 7.84 9.31 8.99 7.41 24.79 32.9 16.02 16.68 15.29 11.95 14.75 13.87 20.89 21.96 19.92 17.78 6.77 7.57 14.73 15.71 15.1 14.81 3.25 3.46 14.79 14.04 15.17 12.18 1.33 1.19 11.77 12.77 5.73 6.08 0.07 0.03 4.94 6.25 7.84 8.31

[0138] The sample deviations were obtained by performing statistics on the repeated measurements of the standard and the test samples in the above samples. The results are shown in Table 4.

[0139] Table 4. Deviation coefficients of standards

[0140]

[0141]

[0142] As can be seen from the results in Table 4, the coefficients of deviation for the standard, reference, and test sample were all less than 20%, meeting quality control requirements at the well level and being effective. Similarly, testing of the other wells of this ELISA plate and the other 17 ELISA plates all met quality control requirements at the plate well level. Furthermore, the absorbance value of the maximum detectable amount standard, STD1, was greater than 0.6, the coefficient of the regression model was greater than 0.9, the detectable amount of the standard sample deviated from its calibrated amount by no more than 30% of the calibrated amount, and the detectable amount of the negative control was less than 0.1, thus meeting quality control requirements at the ELISA plate level.

[0143] The plate anchor value of the ELISA plate is the middle value ω of the standard curve detection value (excluding the first two gradients above 20ng) n =(6.77+3.46) / 2=5.11. There are 18 ELISA plates in the test experiment. The intra-plate anchor values ​​obtained by the same method for these ELISA plates are 4.93, 5.28, 3, 3.34, 5.07, 5.11, 4.66, 6.21, 4.23, 4.94, 5.07, 5.14, 5.23, 5.3, 3.85, 4.85, 4.97, and 4.74, respectively. Therefore, the inter-plate anchor value ω of the ELISA plate is N The median value of the 18 anchor values ​​in the board is 4.96. n和 ω N The results and μ F =μ-ω n+ ω N The final IgA immune activity index of each sample was calculated, as shown in Table 5.

[0144] Table 5. IgA immune activity index of each sample

[0145] sample IgA immune activity index B000001 8.42 B000001F 8.04 B000002 16.19 B000002F 13.46 B000003 21.26 B000003F 18.69 B000004 15.06 B000004F 14.80 B000005 14.25 B000005F 13.51 Q2 12.11 Q4 5.43 Q7 5.75 Q8 7.92

[0146] The results of Q2 to Q4 are the IgA immune activity index of the corresponding subjects.

[0147] Example 2: Definition of IgA Immune Activity Index Risk Interval Threshold

[0148] Referring to Example 1, one of the other 18 ELISA plates contained samples from 20 healthy children and 13 healthy adults. After calculating the IgA immune activity index of each of these healthy people, the mean and standard deviation of these 33 values ​​were calculated again, with the mean m = 9.0 and the standard deviation σ = 3.09.

[0149] Therefore, the interval of the IgA immune activity index detection value μ is defined as follows:

[0150] Normal base range μ < m + 2σ, that is, μ < 15.18;

[0151] Higher base range m + 2σ ≤ μ < m + 3σ, that is, 15.18 ≤ μ < 18.27;

[0152] Abnormally high μ F ≥ m + 3σ, that is, μ F ≥ 18.27.

[0153] Reference Figure 4 , The IgA immune activity index of 33 normal people conforms to the normal distribution. The characteristics of the normal distribution are that 97.72% of people satisfy μ < m + 2σ, and 99.87% of people satisfy μ < 14 m + 2σ.

[0154] Example 3: Physical examination report of IgA immune activity index

[0155] This example provides a system, which includes:

[0156] Acquisition module, which is used to obtain the absorbance OD of each well in the enzyme-labeled plate;

[0157] Detection quantity calculation module, the detection and analysis module is used to convert the absorbance OD into the detection quantity μ of the IgA complex according to the regression model;

[0158] Intra-plate normalized detection quantity calculation module, the intra-plate normalized detection quantity calculation module is used to calculate the intra-plate normalized detection quantity μ of the IgA complex according to the following formula n = μ - ω n , where ω n is the intra-plate anchor value;

[0159] Inter-plate normalized detection quantity calculation module, the inter-plate normalized detection quantity calculation module is used to calculate the inter-plate normalized detection quantity μ of the IgA complex according to the following formula <舍入错误,原公式不完整,请检查并补充完整后再翻译>μ <舍入错误,原公式不完整,请检查并补充完整后再翻译>ω <舍入错误,原公式不完整,请检查并补充完整后再翻译>, where ω N is the inter-plate anchor value;

[0160] Physical examination report generation module, the physical examination report generation module is used to provide the IgA immune activity index of the subject, the standards of each interval corresponding to the index, and the classification corresponding to the interval in which the subject's index falls.

[0161] The physical examination report contains three parts. The first part is for reference Figure 5, the patient's IgA immune activity index value detected in the report is 26.661 (solid circle in the figure), which is greater than 18.27, so it is "abnormally high". At the same time, the values ​​of the IgA immune activity index of other different sample types are listed as background references (dashed circles in the figure), and different color marks are given according to the risk classification of the index: red represents abnormally high, brown represents "high basal range", and green represents "normal basal range". And the two thresholds for dividing risk groups are marked, 15.18 and 18.27. The second part gives the relevant clinical evidence and references of the IgA immune activity index so far. The third part gives Figure 2 The standard curve shown and Figure 3 The results of the normal distribution fit for healthy people are shown in .

[0162] The present application has been described in detail above with reference to the embodiments. However, the present application is not limited to the above embodiments. Various modifications can be made within the scope of knowledge possessed by a person of ordinary skill in the art without departing from the purpose of the present application. In addition, the embodiments of the present application and the features of the embodiments can be combined with each other unless there is a conflict.

Claims

1. A method for calculating the IgA immune activity index of a sample, characterized in that: The following steps are involved: Get the absorbance value OD of the nth well on the enzyme-labeled plate; The absorbance value OD is converted into the detection amount μ of the IgA complex according to the regression model; Set the plate anchor value ω of the detection amount on the nth ELISA plate n The normalized detection amount of IgA complex within the plate μ was calculated according to the following formula: n =μ-ω n ; Set the inter-plate anchor value ω for the detection amount of the 1st to Nth ELISA plates N The inter-plate normalized detection amount μ of the IgA complex on the nth ELISA plate is calculated according to the following formula: F =μ n +ω N , recorded as IgA immune activity index; Wherein, n≤N and are all positive integers; The in-board anchor value ω n The median value of the detection amount of each test product in the effective gradient of the standard curve in the nth ELISA plate or the detection amount of the positive control in the nth ELISA plate; the inter-plate anchor value ω N is the intra-plate anchor value ω of N ELISA plates n of the median.

2. The method according to claim 1, characterized in that The regression model is a linear regression model.

3. The method according to claim 2, characterized in that The absorbance value OD was converted into the detected amount μ of the IgA complex according to the following formula: .

4. The method according to any one of claims 1 to 3, characterized in that Each sample is provided with several replicate wells, and the deviation coefficient CV of the detection amount μ of the several replicate wells of each sample is calculated. When the deviation coefficient CV is ≥ 20%, the sample is determined to be an invalid sample.

5. The method according to any one of claims 1 to 3, characterized in that The samples include different amounts of standard substances and negative controls. When the ELISA plate meets any of the following conditions, the absorbance OD value of each well is re-obtained: a) Absorbance value of the maximum amount of standard <T0; b) Correlation coefficient of regression model <R0; c) The detected amount of the standard substance deviates from the calibrated amount by >P0%; d) The detected amount of negative control is > Δ0; Among them, T0 is 0.6, R0 is 0.9, P0 is 30, and Δ0 is 0.

1.

6. A method for determining the IgA immune activity index, characterized in that: The following steps are involved: Calculating the IgA immune activity index μ of a subject according to the method according to any one of claims 1 to 5 F ; According to the subject's IgA immune activity index μ F Perform the following judgment: When μ F <m + 2σ, it is determined that the IgA immune activity index of the subject is within the normal baseline range. When m + 2σ ≤ μ F <m + 3σ, it is determined that the IgA immune activity index of the subject is on the high side within the basic range When μ F When ≥m+3σ, the IgA immune activity index of the subject is judged to be high within the abnormal range; Where m is the average value of the IgA immune activity index of normal people, and σ is the standard deviation of the IgA immune activity index of normal people.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the steps of the method according to any one of claims 1 to 6.

8. The device, characterized in that The method comprises a processor and a memory, wherein the memory stores a computer program that can be run on the processor, and the processor implements the method according to any one of claims 1 to 6 when running the computer program.

9. A system for calculating the IgA immune activity index of a sample, characterized in that include: An acquisition module is used to obtain the absorbance value OD of each well in the ELISA plate; A detection amount calculation module, the detection amount calculation module is used to convert the absorbance value OD into the detection amount μ of the IgA complex according to a regression model; The normalized detection amount calculation module is used to calculate the normalized detection amount μ of the IgA complex according to the following formula: n =μ-ω n , where the anchor value ω is n The median value of the detected amount of each test product within the effective gradient of the standard curve in the nth ELISA plate or the detected amount of the positive control in the nth ELISA plate; The inter-plate normalized detection amount calculation module is used to calculate the inter-plate normalized detection amount μ of the IgA complex according to the following formula: F =μ n+ ω N , recorded as the IgA immune activity index; among them, the inter-plate anchor value ω N is the intra-plate anchor value ω of N ELISA plates n the median; Wherein, n≤N and are all positive integers.

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