CN115078277A - Method and device for calculating IgA immune activity index of sample - Google Patents
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Abstract
The invention discloses a method and a device for calculating an IgA immune activity index. In a first aspect of the application, there is provided a method of calculating an IgA immune activity index, the method comprising the steps of: step 1: acquiring a light absorption value; step 2: converting the light absorption value into the detected amount of the IgA compound according to a regression model; and step 3: setting an in-plate anchoring value of the detected quantity on the ELISA plate, and calculating to obtain an in-plate normalized detected quantity of the IgA compound; and 4, step 4: and setting inter-plate anchoring values of the detected amounts among the enzyme label plates, and calculating the normalized detected amounts among the plates. The method obtains the original OD value of each hole on the ELISA plate, firstly performs quality control on the layer surface of the hole, calculates the detection amount of the IgA compound in the hole in a fitting manner, then performs quality control on the layer surface of the plate, normalizes the data on the layer surface of the ELISA plate, and removes the plate-to-plate difference of the ELISA plate, thereby further improving the accuracy of mass detection.
Description
Technical Field
The application relates to the technical field of immunodetection, in particular to a method and a device for calculating an IgA immune activity index of a sample.
Background
In the process of human autoimmune reaction, when human immunoglobulin a (IgA) participates, IgA binds to a pathogen to initiate an immune reaction, and downstream antibody IgG participates in IgM and molecules such as C3 complement of the complement pathway to form IgA-IgG, IgA-IgM, IgA-C3, IgA-IgG-IgM, and the like, which are collectively called IgA complex. During a normal immune response, these pathogen-bound complexes are typically cleared by the immune system, such as by phagocytosis by macrophages and the like. However, when the IgA immune response is abnormal, the IgA complex is not effectively cleared by the immune system, but remains in the blood circulation system and the urinary system for a long time, and causes two diseases, specifically: IgA nephropathy (IgAN) is caused by the deposition and retention of IgA complexes in the kidney; the deposition of IgA complexes in blood vessels will lead to purpura, commonly known as anaphylactoid purpura (Henoch-Schonlein purpura, HSP), or IgA vasculitis (IgAV).
In the conventional methods, diagnosis is generally performed by immunoassay of serological total IgA, which is any of three immunization (IgA, IgM, IgG) or five immunization (three immunization plus complement C3, C4) items that are clinically conventional. However, the factor of increase in total IgA is probably due to other diseases such as multiple myeloma, rheumatoid arthritis, thrombocytopenia, and infectious diseases in addition to IgA nephropathy and purpura, and therefore the specificity of total IgA to IgA nephropathy and purpura is low. For this reason, the applicant tried to directly detect the amount of IgA complex detected as an index of IgA immune activity instead of detecting three or five immune factors, based on the principle that circulating IgA complex in serum is a major factor inducing pathogenesis. However, although this method has better sensitivity and specificity, some problems are still inevitably caused when batch diagnosis of large sample amount is faced due to the operation of experimenters and the problem of inter-plate difference of enzyme label plate itself, and therefore, it is necessary to provide a method for calculating the IgA immune activity index which can further improve the accuracy of large-batch detection.
Disclosure of Invention
The present application is directed to solving at least one of the problems in the prior art. Therefore, the application provides a calculation method of the IgA immune activity index, which can further improve the accuracy of mass detection.
In a first aspect of the application, there is provided a method of calculating an IgA immune activity index for a sample, the method comprising the steps of:
acquiring the light absorption value OD of each hole on the nth ELISA plate;
converting the light absorption value OD into a detected amount mu of the IgA complex according to a regression model;
setting the in-plate anchoring value omega of the detected quantity on the nth ELISA plate n The in-plate normalized detection amount [ mu ] of the IgA complex is calculated according to the following formula n ＝μ-ω n ；
Setting inter-plate anchoring values omega of detected amounts of 1 st to N ELISA plates N The normalized detection quantity mu between the plates of the IgA complex on the nth ELISA plate is calculated according to the following formula F＝ μ n+ ω N And is reported as IgA immune activity index;
wherein N is less than or equal to N and is a positive integer.
In some embodiments of the present application, the sample comprises a test substance and a positive control substance, and the in-plate anchoring value ω is n Is the median of the detected amount of the sample in the nth enzyme label plate or the detected amount of the positive reference substance in the nth enzyme label plate.
In some embodiments of the present application, the inter-plate anchor value ω N In-plate anchoring value omega for N ELISA plates n The median of (3).
In some embodiments of the present application, the regression model is a linear regression model.
In some embodiments of the present application, the absorbance OD is converted to the detected amount of IgA complex μ according to the following formula:
in some embodiments of the present application, each sample is provided with a plurality of duplicate wells, a deviation coefficient CV of the detected amount μ of the plurality of duplicate wells of each sample is calculated, and the sample is determined to be an invalid sample when the deviation coefficient CV is equal to or greater than 20%.
In some embodiments of the present application, the sample comprises different amounts of standard substance and negative control substance, and the microplate meets at least one of the following conditions, and the absorbance OD of each well is obtained again:
a) absorbance of maximum standard<T 0 ；
b) Correlation coefficient of regression model<R 0 ；
c) Deviation of detected amount of standard product from standard amount>P 0 ％；
d) Amount of negative control detected>Δ 0 。
In some embodiments of the present application, T 0 Is 0.6, R 0 Is 0.9, P 0 Is 30, Δ 0 Is 0.1.
In a second aspect of the present application, there is provided a method of determining an IgA immune activity index, the method comprising the steps of:
calculating IgA immune Activity index μ of the subject according to the method described previously F ；
According to IgA immune activity index μ of subject F The following determination is performed:
when mu is F <m +2 sigma, judging the IgA immune activity index of the subject to be in a normal basic range,
when m +2 sigma is less than or equal to mu F <m +3 sigma, high IgA immune activity index of the subject,
when mu is F Judging whether the IgA immune activity index of the subject is higher in an abnormal range when the IgA immune activity index is more than or equal to m +3 sigma;
wherein m is the average value of the IgA immune activity index of the normal human, and sigma is the standard deviation of the IgA immune activity index of the normal human.
In some embodiments of the present application, the method further comprises generating a physical examination report based on the results of determining the IgA immune activity index.
In some embodiments of the present application, the physical examination report includes the IgA immune activity index and the interval criteria for the index and the subject's corresponding IgA immune activity index data.
In some embodiments of the present application, the physical examination report further includes the validity of the quality control result during the examination process.
In some embodiments of the present application, the physical examination report further includes general information of the subject.
In some embodiments of the present application, the physical examination report further includes the general results of clinical trials of the IgA immune activity index for physician and patient reference.
In some embodiments of the present application, the physical examination report further includes statistics, standard curves, etc. of healthy population for reference.
In a third aspect of the present application, a computer-readable storage medium is provided, having stored thereon computer-executable instructions for causing a computer to perform the steps of the aforementioned method of calculating an IgA immune activity index or method of determining an IgA immune activity index.
In a fourth aspect of the present application, there is provided an apparatus comprising a processor and a memory, the memory having stored thereon a computer program operable on the processor, when executing the computer program, implementing the aforementioned method of calculating an IgA immune activity index or method of determining an IgA immune activity index.
In a fifth aspect of the present application, there is provided a system comprising:
the acquisition module is used for acquiring the light absorption value OD of each hole in the ELISA plate;
the detection and analysis module is used for converting the light absorption value OD into a detection quantity mu of the IgA compound according to the regression model;
an in-board normalization detection quantity calculation module for calculating in-board normalization detection quantity mu of IgA compound according to the following formula n ＝μ-ω n Wherein, ω is n An in-board anchor value;
the inter-plate normalized detected quantity calculation module is used for calculating the inter-plate normalized detected quantity mu of the IgA compound according to the following formula F ＝μ n+ ω N Wherein, ω is N An inter-plate anchor value.
In some embodiments of the present application, the system further comprises a pore quality control module for calculating a coefficient of deviation, CV, of the detected quantity, μ, of the number of replicate pores for each sample. When the coefficient of deviation CV is greater than or equal to 20%, the sample is judged as an invalid sample.
In some embodiments of the present application, the system further comprises a plate quality control module for determining the following criteria in the microplate, the microplate being determined to be an invalid microplate when either of the following conditions is met:
a) absorbance of maximum detected standard<T 0 ；
b) Correlation coefficient of regression model<R 0 ；
c) Deviation coefficient between detected amount of positive control and standard amount>P 0 ％；
d) Amount of negative standard>Δ 0 ；
In some embodiments of the present application, T 0 Is 0.6, R 0 Is 0.9, P 0 Is 30, Δ 0 Is 0.1.
In some embodiments of the present application, the system further comprises an IgA immune activity index analysis module for analyzing the IgA immune activity index μ F In relation to the average value m of the IgA immune activity index of normal human,
when mu is F <m +2 σ, the IgA immune activity index of the subject is judged to be in a normal basal range,
when m +2 sigma is less than or equal to mu F <m +3 σ, the subject is judged to have a high IgA immune activity index in the basal range,
when mu is F Judging that the IgA immune activity index of the subject is higher in an abnormal range when the IgA immune activity index is more than or equal to m +3 sigma;
wherein σ is the standard deviation of the normal human IgA immune activity index.
In some embodiments of the present application, the system further comprises a physical examination report generation module for determining the IgA immune activity index for the subject based on the relationship of the IgA immune activity index to the average value m of the normal human IgA immune activity index.
In some embodiments of the present application, the physical examination report includes the IgA immune activity index and the interval criteria for the index and the subject's corresponding IgA immune activity index data.
In some embodiments of the present application, the physical examination report further includes the validity of the quality control result during the examination process.
In some embodiments of the present application, the physical examination report further includes general information about the subject.
In some embodiments of the present application, the physical examination report further includes the general results of clinical trials of the IgA immune activity index for physician and patient reference.
In some embodiments of the present application, the physical examination report further includes statistical properties, standard curves, etc. of healthy population for reference.
The method for calculating the IgA immune activity index according to the embodiment of the application has at least the following beneficial effects:
the method comprises the steps of obtaining an original OD value of each hole on an ELISA plate from enzyme-linked immunosorbent assay, firstly performing quality control on a hole layer, obtaining a calculation formula for converting OD into sample quantification through standard curve fitting, calculating the detection amount of IgA compounds in the holes, then performing quality control on the plate layer, normalizing data on the enzyme-labeled plate layer, removing the plate-to-plate difference of the ELISA plate, and finally performing repeated calculation on the samples to determine the final quantification result of each sample. In this way, the accuracy of mass detection can be further improved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
FIG. 1 is a flow chart for calculating an IgA immune activity index as provided by an embodiment of the present application.
FIG. 2 is another flow chart for calculating an IgA immune activity index provided by an embodiment of the present application.
Fig. 3 shows the results of constructing a linear regression model in different ways in example 1 of the present application, where a is to directly construct a linear regression model from OD values and detected amounts, and b is to construct a linear regression model by taking logarithms of OD values and detected amounts.
FIG. 4 shows the distribution of IgA immune activity indexes among 33 healthy persons in example 2 of the present application, where a is the probability density distribution, the horizontal axis represents the value of the IgA immune activity index, and the vertical axis represents the proportion of persons; b is its Q-Q diagram; c is its cumulative profile; d is its P-P diagram.
Figure 5 is a schematic illustration of a physical examination report provided in example 3 of the present application.
Detailed Description
The conception and the resulting technical effects of the present application will be clearly and completely described below in conjunction with the embodiments to fully understand the objects, features and effects of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all embodiments, and other embodiments obtained by those skilled in the art without inventive efforts based on the embodiments of the present application belong to the protection scope of the present application.
The following detailed description of embodiments of the present application is provided for the purpose of illustration only and is not intended to be construed as a limitation of the application.
In the description of the present application, the meaning of a plurality is one or more, the meaning of a plurality is two or more, and larger, smaller, larger, etc. are understood as excluding the present numbers, and larger, smaller, inner, etc. are understood as including the present numbers. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated. If a logical order is described in the flowcharts, in some cases, the steps described or illustrated may be performed in an order different than the order in the flowcharts.
In the description of the present application, reference to the description of the terms "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example" or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Referring to fig. 1, a method of calculating an IgA immune activity index in an embodiment of the present application is shown, the method comprising the steps of:
s110, obtaining the light absorption value OD of each hole on the nth ELISA plate.
The ELISA plate is used for performing an enzyme-linked immunosorbent assay (ELISA) of the IgA complex, and is provided with a plurality of holes, for example, 6 holes, 12 holes, 24 holes, 48 holes, 96 holes, and the like. In the present example, the IgA complex is immobilized by binding to the probe in the well, followed by color development with an enzyme-labeled secondary antibody. In particular, the probe for the IgA complex is an Fc receptor protein for IgA, such as the FCAR/CD89 protein, which is capable of specifically binding to the IgA complex. In the ELISA process, it is usually necessary to set at least one of a standard, a control, and the like. The standard substance is a sample containing the IgA complex with a known detected amount (a calibrated content), and a standard curve can be obtained through the given gradient of the known detected amount or the relation between the gradient of different known detected amounts and the corresponding absorbance OD obtained by dilution. The control generally comprises at least one of a negative control containing no IgA complex or having a content below a detection limit and a positive control containing IgA complex and having interfering substances removed therefrom by various methods for evaluating whether the detection result is valid and its stability and comparability, both of which are quality control. The absorbance OD of each well is the reaction result of the enzyme-labeled secondary antibody bound to the IgA complex immobilized in the well, catalyzing the colored product formed from the enzyme reaction substrate. It will be appreciated that in the testing process, typically each sample (including standards, test samples, controls, etc.) will pass through several iterations (e.g., two to three).
And S120, converting the light absorption value OD into the detected quantity mu of the IgA complex according to the regression model.
In this step, the regression model is a quantitative model of a statistical relationship between the absorbance OD and the amount μ of IgA complex detected. Specifically, the regression model usually uses a linear regression model to fit a standard curve, for example, directly fit the two values: OD ═ κ × μ + δ; or fitting the two after taking logarithm: log (log) 2 (OD)＝κ×log 2 (μ) + δ. In some embodiments, the correlation coefficient R of the second linear regression model is compared to the correlation coefficient R of the first linear regression model 2 Is closer to 1 and thus better fits. Thus, according to the second model
Wherein, the specific values of delta and kappa can be obtained according to the standard quantity of the standard substance and the corresponding light absorption value. According to this model, the absorbance values OD of the remaining wells can be used to calculate the detected amount μ of IgA complex in the remaining wells. The amount detected and hereinafter the maximum amount may refer to mass, concentration or other measure.
S130, setting the in-plate anchoring value omega of the detected quantity on the nth ELISA plate n The in-plate normalized detection quantity mu of the IgA complex is calculated according to the following formula n ＝μ-ω n 。
In this step, the in-plate anchor value ω is passed n The detected amount of IgA complex in different wells in the same plate is normalized and changed into the in-plate anchoring value omega n The difference in (b) facilitates alignment of different microplate plates to the same level in subsequent S140. Among these, the in-board anchoring value ω n Optionally, a relatively stable value between different plates can be selected, for example, the detected amount of the positive control can be used as the in-plate anchoring value omega n Or using the intermediate value of the detected quantity of each object to be tested in the effective gradient of the standard curve as the in-board anchoring value omega n 。
S140, setting inter-plate anchoring values omega of detected amounts of 1 st to N ELISA plates N The normalized detection quantity mu between the plates of the IgA compound on the nth ELISA plate is calculated according to the following formula F＝ μ n+ ω N And is reported as IgA immune activity index.
In this step, the plate-to-plate anchoring value ω is set by the 1 st to N th microplate N The detection quantity which becomes the difference value after normalization is adjusted to the actual level again by the application of the method (N is less than or equal to N and is a positive integer). To achieve this, the inter-plate anchor value ω N Preferably, the in-plate anchoring value omega corresponding to each of N enzyme label plates can be adopted n Median of (e.g. for ω) 1 、ω 2 ……ω k Taking the median of k intra-board anchor values as an inter-board anchor value omega N . It can be understood that ω is N Other values according to this concept can also be used as the inter-plate anchor value ω N The preparation is used. Although the actual detected amount of the to-be-detected product detected in different enzyme label plates has certain difference, which causes certain difficulty in normalization treatment, the median of the to-be-detected product between different plates is gradually stabilized along with the increase of the number of the to-be-detected product in the plate, and similarly, the positive reference product also has relatively stable IgA compound content, so that the in-plate anchoring value omega is passed through n And an inter-plate anchor value omega N And (3) setting a stable anchor point, aligning different enzyme label plates to the same level, performing data normalization, and eliminating the difference between the plates. That is, the detected amount of the microplate is first normalized to a level close to 0, and then the anchor point normalized to close to 0 is raised to an actual level in order to approach the actual detected amount.
Referring to FIG. 2, in order to ensure the detection accuracy of the sample, a step of discrimination may be added before the normalization process of S130 and S140, and the detection result may be rejected as invalid because of the quality problem of a part of wells on the microplate or a part of the microplate or the step error in the detection process. Subsequent re-testing is required.
For this purpose, quality control is carried out from two aspects, including the quality control at the well level in the microplate and the quality control at the microplate level. Referring to fig. 2, the quality control of the wells in the microplate is performed in step S121, and since each sample has a plurality of wells to be repeated, the detected amounts of different wells in the same sample are analyzed, and the deviation coefficient CV is calculated, and when the deviation coefficient is higher than 20%, the error between the different wells in the sample is too large, and the sample is determined to be an invalid sample, and the next step is performed after all the invalid samples are removed. Specifically, the calculation formula CV of the deviation coefficient CV is standard deviation/average × 100%, and therefore, the deviation coefficient of the detected amount of IgA complex for each sample is calculated from this formula and the result of the detected amount μ of all the replicate wells for each sample, and when the deviation coefficient is higher than 20%, it is determined as an invalid sample. It is understood that the threshold values for the deviation factor may vary by 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 8%, 5%, 3%, etc. for greater experimental accuracy. Wherein, the sample for carrying out the quality control of the pore layer surface can comprise a standard substance and a positive control substance. Of course, it is understood that the detected amount of the sample can be controlled in this way.
After the quality control of the pore layer surface in the ELISA plate is completed, the quality control needs to be further performed on the surface of the ELISA plate. The quality control of the microplate level can be carried out in the following ways, including the following determinations: a) absorbance of maximum detected standard<T 0 (ii) a b) Correlation coefficient of regression model<R 0 (ii) a c) Deviation of detected amount of standard product from standard amount>P 0 Percent; d) amount of negative control detected>Δ 0 . When either of the above conditions is satisfied, the microplate will be identified as a null microplate. In particular, e.g. T 0 Is 0.6, R 0 Is 0.9, P 0 Is 30, Δ 0 Is 0.1 ng.
The embodiment of the application also provides a method for judging the IgA immune activity index, which comprises the following steps:
calculating IgA immune activity index μ of the subject according to the aforementioned method of calculating IgA immune activity index F ；
IgA immunization according to subjectActivity index mu F The following determination is performed:
when mu is F <m +2 sigma, judging the IgA immune activity index of the subject to be in a normal basic range,
when m +2 sigma is less than or equal to mu F <m +3 sigma, the IgA immune 7 activity index of the subject is judged to be higher in the basic range,
when mu is F Judging whether the IgA immune activity index of the subject is higher in an abnormal range when the IgA immune activity index is more than or equal to m +3 sigma;
wherein m is the average value of the IgA immune activity index of the normal human, and sigma is the standard deviation of the IgA immune activity index of the normal human.
Obtaining IgA immune Activity index μ for each specific subject sample F The subject's IgA immune activity index can then be predicted to fall within the range by comparison with normal values. Further, whether or not the subject suffers from IgA nephropathy or purpura can be known based on the range of the IgA immune activity index, directly or in combination with other indicators. In the above determination process, m and σ can be obtained by detecting a certain number of normal people. The number of normal population can be more than 20, 30, 50, 100 and 200, and the normal population specifically refers to the population which is determined not to have IgA nephropathy and purpura or other diseases possibly influencing the index detection through various standard detections, or is a healthy population. It will be appreciated that to enhance the representation of m and σ, the normal population preferably includes people of all ages from children to the elderly, preferably half as many males and females as or close to 1: 1. the m and σ values can be derived from the IgA immune activity index for each individual in the normal population by any method known in the art, such as by direct mathematical calculations, or by fitting a normal distribution. Of course, the standards of 2 σ and 3 σ in the above division interval are not unique, and may be adjusted appropriately according to actual conditions.
After the judgment result is obtained, a corresponding physical examination report may be generated for each subject, and the physical examination report may include the relevant results of other detection items in addition to the relevant information of the IgA immune activity index, which is not described herein again. For the portion of the IgA immune activity index, the physical examination report may provide the IgA immune activity index, the criteria for each segment corresponding to the index, and the classification corresponding to the segment in which the subject's index falls, which falls within the normal basal range, or higher abnormality, etc. It can be understood that the physical examination report also contains the result of quality control in the detection process, and the result of validity of the quality control is given to prove that the detection is valid. Of course, general information of the subject, such as name, etc., is also included. In addition, the general results of clinical trials of IgA immune activity indices, or the statistical properties of normal populations, standard curves, etc. can be provided in physical examination reports for reference.
Embodiments of the present application also provide a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the steps of the aforementioned method for calculating an IgA immune activity index or the method for determining an IgA immune activity index.
The embodiment of the application also provides equipment, which comprises a processor and a memory, wherein the memory is stored with a computer program capable of running on the processor, and the processor realizes the method for calculating the IgA immune activity index or the method for judging the IgA immune activity index when running the computer program.
The memory, as a non-transitory computer readable storage medium, may be used to store a non-transitory software program and a non-transitory computer executable program, such as the process of determining the IgA immune activity index as described in the embodiments of the present application. The processor implements the determination of the subject's IgA immune activity index by executing the non-transitory software program 8 stored in memory and instructions.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store a computer program for executing the above. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device.
In some embodiments of the present application, the memory optionally includes memory located remotely from the processor, and these remote memories may be connected to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Non-transitory software programs and instructions needed to implement the above-described determinations are stored in memory and, when executed by one or more processors, perform the above-described determinations.
An embodiment of the present application further provides a system, including:
the acquisition module is used for acquiring the light absorption value OD of each hole in the ELISA plate;
the detection and analysis module is used for converting the light absorption value OD into a detection quantity mu of the IgA compound according to the regression model;
an in-board normalization detection quantity calculation module for calculating in-board normalization detection quantity mu of IgA compound according to the following formula n ＝μ-ω n Wherein, ω is n An in-board anchor value;
the inter-plate normalized detected quantity calculation module is used for calculating the inter-plate normalized detected quantity mu of the IgA compound according to the following formula F ＝μ n+ ω N Wherein, ω is N An inter-plate anchor value.
The system implementation described above is merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
It will be understood that all or some of the steps, systems disclosed above may be implemented as software, firmware, hardware, or suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). It should be understood that computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is 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 tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer.
In addition, 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 includes any information delivery media.
The method provided by the present application is described below with reference to specific examples.
Example 1
The following calculations and physical examination report generation were implemented in the open source development environment, RStudio Version 1.4.1717, whose operating system environment was macOS Big Sur Version 11.6.
Detection of IgA Complex
Relates to a kit for detecting IgA compounds, which comprises molecular probe freeze-dried powder, coating buffer solution, an enzyme label plate, a standard substance, an enzyme-labeled secondary antibody, developing solution, stop solution, washing solution, diluent and confining solution.
Wherein the molecular probe freeze-dried powder is recombinant FCAR protein freeze-dried powder;
carbonate buffer with coating buffer 0.05M (pH 9.6);
the ELISA plate is a 96-hole plate;
the standard substance is commercial human serum IgA containing IgA compound;
the negative control is human serum without IgA complex;
the positive reference substance is human serum containing IgA compound, and 25ng of commercial human serum IgA is selected;
the enzyme-labeled secondary antibody is mouse anti-human IgA marked by Horse Radish Peroxidase (HRP);
the color developing solution comprises color developing solution A-3, 3 ', 5, 5' -tetramethyl benzidine (TMB) and color developing solution B-hydrogen peroxide solution;
the stop solution is 10% sulfuric acid;
the washing solution is 0.15M phosphate buffer solution containing 0.05% Tween-20;
the diluent is washing solution plus 1 ‰ BSA;
the blocking solution was washing solution + 5% BSA.
The detection method of the kit is as follows, and the specific flow is shown in figure 1:
(1) dissolving the molecular probe freeze-dried powder in a coating buffer solution to obtain a molecular probe solution;
(2) adding the molecular probe solution into each hole of a 96-hole enzyme label plate, covering a sealing film, and standing overnight at 4 ℃; throwing off the solution in the holes, washing the ELISA plate for multiple times by using a washing solution, adding a sealing solution into the ELISA plate, covering a sealing film, standing overnight in an environment at 4 ℃, washing the ELISA plate for 1 time by using the washing solution, and drying to obtain the ELISA plate coated with the molecular probe;
(3) diluting the sample with diluent to obtain sample diluent and standard product gradient diluent (the detection amounts are 50, 25, 12.5, 6.75, 3.375 and 1.5625ng in sequence), and diluting the positive control and the negative control without diluent; then respectively adding the sample diluent, the standard product gradient diluent, the negative control solution and the positive control solution into the ELISA plate coated with the molecular probe HQP001, covering a sealing film for incubation, and washing the ELISA plate for 3 times by using a washing solution after the incubation is finished; adding a secondary antibody marked by HRP into an ELISA plate for incubation, and washing the ELISA plate for 3 times after the incubation is finished; mixing a developing solution A and a developing solution B according to the ratio of 1: 1, performing room-temperature dark color development, adding a stop solution after the color development is finished, placing the ELISA plate in an ELISA reader after slight oscillation to detect a light absorption value (OD value), wherein the first wavelength is 450nm, and the second wavelength is 630 nm.
Tables 1 and 2 are respectively a sample mapping matrix of the ELISA plate and a part of an OD value matrix obtained according to the sample mapping matrix and a detection result of the ELISA plate.
TABLE 1 sample mapping matrix locality
| 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 |
TABLE 2 OD value matrix local
| 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 |
As shown in Table 1, STD 1-6 represents the standard samples with different detection quantity gradients after dilution, nCtrl is a negative control sample, B000001-5 is a sample to be detected, and the tail end F represents whether the plasma sample is Frozen (F: Frozen, which is a Frozen sample) or not, and is used for comparing the difference of the samples under different storage conditions; q2, Q4, Q7 and Q8 are control samples of healthy people. According to the above table, two replicates per sample were set up for the assay.
Second, calculation of IgA immune Activity index
And performing linear regression according to the OD value matrix containing the standard substance, the reference substance and the to-be-detected substance obtained by detection according to the kit to calculate the model parameters. The original OD values and the logarithmic OD values were used to perform linear regression modeling, and the results are shown in fig. 3, where a is the regression model of the original OD values (OD 0.0373 × μ +0.331, rsq 0.8908), and b is the regression model of the logarithmic OD values (log) 2 (OD)＝0.7237×log 2 (μ) -2.826, rsq ═ 0.9759), which indicates that the log OD value model in b is more accurate, and therefore, the log OD value regression model in b is used belowThe model calculates the amount of sample detection. The parameters delta-2.826 and kappa-0.7237 in the logarithmic linear model are calculated according to the formula of the detected sample quantity
The detected amount of the sample calculated according to this formula is shown in table 3.
TABLE 3 examined quantity matrix local
| 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 |
And (4) repeatedly counting the standard substance and the to-be-detected substance in the sample to obtain sample deviation, wherein the result is shown in a table 4.
TABLE 4 deviation factor of standards
It can be seen from the results in table 4 that the deviation coefficients of the standard, reference and test samples are all less than 20%, and are all valid in accordance with the quality control requirements on the pore level. In the same way, the detection of other holes of the ELISA plate and other 17 ELISA plates all meet the quality control requirement of the layer surface of the inner hole of the ELISA plate. In addition, the light absorption value of the standard product STD1 with the largest detection amount is more than 0.6, the coefficient of the regression model is more than 0.9, the value of the detection amount of the standard product deviating from the standard amount is not more than 30% of the standard amount, and the detection amount of the negative control product is less than 0.1, so the quality control requirement of the enzyme label plate layer is met.
The in-plate anchoring value of the enzyme label plate is the middle value omega of a standard curve detection value (removing the first two gradients higher than 20 ng) n (6.77+ 3.46)/2-5.11. The total number of the ELISA plates in the detection experiment is 18, and the in-plate anchoring values of the ELISA plates obtained by the same method are respectively 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, so that the inter-plate anchoring value omega of the ELISA plates is N The median of the 18 in-plate anchors was 4.96. According to omega n and ω N result of (2) and μ F ＝μ-ω n+ ω N The final IgA immune activity index for each sample was calculated as shown in table 5.
TABLE 5 IgA immune Activity index for individual samples
| Sample (I) | 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 |
The results of Q2-Q4 are the IgA immune activity indices for the corresponding subjects.
Example 2: IgA immune activity index Risk Interval threshold definition
Referring to example 1, after calculating IgA immune activity indexes of 20 healthy children and 13 healthy adults among 18 other enzyme-labeled plates, the average and standard deviation of the 33 values were calculated again, where m is 9.0 and σ is 3.09.
Therefore, the interval for the detection value μ for the IgA immune activity index is defined as follows:
normal basal range μ < m +2 σ, i.e., μ < 15.18;
the basic range is higher than or equal to m +2 sigma and less than or equal to mu and less than m +3 sigma, namely, the basic range is higher than or equal to 15.18 and less than or equal to mu and less than 18.27;
abnormally high μ F Not less than m +3 σ, i.e. μ F ≥18.27。
Referring to FIG. 4, the IgA immune activity indices for 33 normal persons fit into a normal distribution. Normal distribution is characterized by 97.72% of the people satisfying μ<m +2 σ, 99.87% of people meet μ< 14 m+2σ。
Example 3: IgA immune activity index physical examination report
The present embodiments provide a system, comprising:
the acquisition module is used for acquiring the light absorption value OD of each hole in the ELISA plate;
the detection and analysis module is used for converting the light absorption value OD into a detection quantity mu of the IgA compound according to the regression model;
an in-board normalization detection quantity calculation module for calculating in-board normalization detection quantity mu of IgA compound according to the following formula n ＝μ-ω n Wherein, ω is n An in-board anchor value;
the inter-plate normalized detected quantity calculation module is used for calculating the inter-plate normalized detected quantity mu of the IgA compound according to the following formula F＝ μ n+ ω N Wherein, ω is N An inter-plate anchor value;
and the physical examination report generation module is used for providing the IgA immune activity index of the subject, the standard of each interval corresponding to the index and the classification corresponding to the interval in which the index of the subject falls.
The physical examination report comprises three parts, the first of which is shown in FIG. 5, where the patient detected an IgA immune activity index value of 26.661 (filled circles in the figure), which is greater than 18.27 and thus "abnormally high". Also, values for IgA immune activity index for other different sample types are listed as background references (dashed circles in the figure) and given different color labels according to the risk classification of the index: red represents abnormally high, brown represents "basal range high", and green represents "normal basal range". And two thresholds, 15.18 and 18.27, are marked to segment the risk group. The second section presents relevant clinical evidence and references of the IgA immune activity index to date. The third part gives the fitting results of the standard curve shown in fig. 2 and the normal distribution of healthy people shown in fig. 3.
The present application has been described in detail with reference to the embodiments, but the present application is not limited to the embodiments described above, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present application. Furthermore, the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
Claims (10)
1. A method of calculating an IgA immune activity index for a sample comprising the steps of:
acquiring a light absorption value OD of a hole on the nth ELISA plate;
converting the light absorption value OD into a detected quantity mu of the IgA compound according to a regression model;
setting the in-plate anchoring value omega of the detected quantity on the nth ELISA plate n The in-plate normalized detection amount [ mu ] of the IgA complex is calculated according to the following formula n ＝μ-ω n ；
Setting inter-plate anchoring values omega of detected amounts of 1 st to N ELISA plates N The normalized detection quantity mu between the plates of the IgA compound on the nth ELISA plate is calculated according to the following formula F＝ μ n+ ω N And is reported as IgA immune activity index;
wherein N is less than or equal to N and is a positive integer.
2. The method of claim 1, wherein the sample comprises a test substance and a positive control substance, and the in-plate anchoring value ω is an in-plate anchoring value n Is the median of the detected amount of the to-be-detected product in the nth ELISA plate or the detected amount of the positive reference product in the nth ELISA plate.
3. The method of claim 2, wherein the inter-plate anchor value ω is N In-plate anchoring value omega for N ELISA plates n The median of (3).
4. The method of claim 1, wherein the regression model is a linear regression model;
preferably, the absorbance value OD is converted to the detected amount μ of IgA complex according to the following formula:
5. the method according to any one of claims 1 to 4, wherein each sample is provided with a plurality of repeating holes, a coefficient of deviation CV of the detected amount μ of the plurality of repeating holes of each sample is calculated, and when the coefficient of deviation CV is not less than 20%, the sample is judged as an invalid sample.
6. The method according to any one of claims 1 to 4, wherein the sample comprises different amounts of standard substance and negative control substance, and the absorbance OD of each well is obtained again when the microplate meets any one of the following conditions:
a) absorbance of maximum standard<T 0 ；
b) Correlation coefficient of regression model<R 0 ；
c) Deviation of detected amount of standard product from standard amount>P 0 ％；
d) Amount of negative control detected>Δ 0 ；
Preferably, T 0 Is 0.6, R 0 Is 0.9, P 0 Is 30, Δ 0 Is 0.1.
7. A method for determining an IgA immune activity index, comprising the steps of:
calculating IgA immune activity index μ for a subject according to the method of any one of claims 1 to 6 F ；
According to IgA immune activity index μ of subject F The following determination is performed:
when mu is F <m +2 σ, determining the subject's IgA immune activity index as a normal basal range,
when m +2 sigma is less than or equal to mu F <m +3 σ, the subject is judged to have a high IgA immune activity index in the basal range,
when mu is F Judging that the IgA immune activity index of the subject is higher in an abnormal range when the IgA immune activity index is more than or equal to m +3 sigma;
wherein m is the average value of the IgA immune activity index of the normal person, and sigma is the standard deviation of the IgA immune activity index of the normal person.
8. Computer-readable storage medium, characterized in that it stores computer-executable instructions for causing a computer to perform the steps in the method of any one of claims 1 to 7.
9. Apparatus comprising a processor and a memory, the memory having stored thereon a computer program executable on the processor, the processor implementing the method of any one of claims 1 to 7 when executing the computer program.
10. A system, characterized in that it comprises:
the collection module is used for acquiring the light absorption value OD of each hole in the ELISA plate;
a detected quantity calculation module, wherein the detection analysis module is used for converting the light absorption value OD into a detected quantity mu of the IgA compound according to a regression model;
an in-plate normalized detected quantity calculation module for calculating an in-plate normalized detected quantity mu of the IgA composite according to the following formula n ＝μ-ω n Wherein, ω is n An in-board anchor value;
an inter-plate normalized detected quantity calculation module for calculating an inter-plate normalized detected quantity mu of the IgA composite according to the following formula F＝ μ n+ ω N Wherein, ω is N An inter-plate anchor value.
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| CN105987996A (en) * | 2015-02-09 | 2016-10-05 | 东莞博捷生物科技有限公司 | Enzyme linked immunosorbent assay kit for detecting human anti-saccharomyces cerevisiae IgA antibody |
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