CN111430034A - Human immune system function level detection data model and application thereof in health analysis - Google Patents
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- G—PHYSICS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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Abstract
The invention discloses a human immune system function level detection data model and application thereof in health analysis, wherein the human immune system function level detection data model comprises an immune system basic detection model, an immune system accurate detection model and a data analysis model; the immune system basic detection is carried out by specific markers of immune cells and adaptive immune cells; the immune system is accurately detected by a specific marker of the cell factor; analyzing and quantifying immune cells in the basic detection of the immune system and cytokines in the accurate detection of the immune system, and analyzing the current health condition of the subject through the data analysis model; the immune system function level data model is established, detection and analysis are carried out on different disease background crowds through immune system basic detection and immune system accurate detection, the immune system function level can be evaluated under the same disease background crowds, and the health condition of a patient/a non-patient can be obtained.
Description
Technical Field
The invention relates to the technical field of human health analysis and evaluation, in particular to a human immune system function level detection data model and application thereof in health analysis.
Background
The immune system is a functional system for cleaning foreign pathogens, tumor cells and infected cells of a human body, is a unique system for protecting the human body, can detect the immune function, can obtain the current immune function level of the human body, and is beneficial to health analysis of people with different disease backgrounds. The core of the technology lies in the model analysis of big data, but the current deficiency lies in that the data is insufficient, and a large amount of detection data support of clinical patients and non-clinical patients is needed. In addition, with the development of subjects such as immunology and biotechnology, new detection means and the discovery of specific markers have been developed, and it is necessary to update an analysis model of the large data. Moreover, because the immune system network in the human body is complex and thousands of threads, the relationship between different factors needs to be continuously mined.
It is seen that improvements and enhancements to the prior art are needed.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention aims to provide human immune system function level detection data and applications thereof in health analysis, and aims to establish an immune system function level data model, provide a large amount of immune function detection data as support, and apply the immune function detection data in health analysis of human body.
In order to achieve the purpose, the invention adopts the following technical scheme:
the application of a human immune system function level detection data model in health analysis, wherein the human immune system function level detection data model comprises an immune system basic detection model, an immune system accurate detection model and a data analysis model; the immune system basic detection is carried out by specific markers of immune cells and adaptive immune cells; the immune system is accurately detected by a specific marker of the cell factor; analyzing and quantifying immune cells in the basic detection of the immune system and cytokines in the accurate detection of the immune system, and analyzing the current health condition of the subject through the data analysis model.
In the application of the human immune system function level detection data model in health analysis, the health condition of a subject is divided into the following 4 grades:
grade 1: asymptomatic, without accompanying known immune system-related diseases;
grade 2: mild symptoms, with known immune system related diseases, but the disease is in a stable state, no clinical treatment within 3 months, no disease activity is shown by clinical indicators;
grade 3: moderate symptoms, associated with known immune system related diseases, but the disease is in a stable state after activity, clinical treatment is carried out within 3 months, and clinical indicators do not show disease activity after treatment;
grade 4: severe symptoms, with known immune system related diseases, remain treated for 3 months and fail to return to a stable state.
In the application of the human immune system function level detection data model in health analysis, the immune system basic detection comprises the detection of the proportion of immune cells in human peripheral blood to immune cells in adaptive immunity; the immune system accurate detection comprises the detection of the proportion of cytokines in human peripheral blood.
The application of the human immune system function level detection data model in health analysis further comprises scoring the proportion of immune cells and immune cells in adaptive immunity in human peripheral blood, wherein the relation between the proportion and the score is as follows: comparing the ratio of the immune cells with the medical standard value, 10% -15% deviating from the normal range is scored as 1 point, 15% -20% is scored as 2 points, 25% -30% is scored as 3 points, 30% -35% is scored as 4 points, 40% -50% is scored as 5 points, and more than 50% is scored as 6 points.
In the application of the human immune system function level detection data model in health analysis, immune cells in the immune system basic detection comprise CD3, CD4, CD8, CD19, CD56, CD25 and CD 28.
The application of the human immune system function level detection data model in health analysis further comprises scoring the proportion of the cell factors in human peripheral blood, and the relation between the proportion and the score is as follows: comparing the proportional value of the cytokine with the medical standard value, 10% -15% deviating from the normal range is scored as 1 point, 15% -20% is scored as 2 points, 25% -30% is scored as 3 points, 30% -35% is scored as 4 points, 40% -50% is scored as 5 points, and more than 50% is scored as 6 points.
The human immune system function level detection data model is applied to health analysis, and cytokines in the accurate detection of the immune system comprise I L-1 β, I L-2, I L-18, TGF- β and IFN-gamma.
The human immune system functional level detection data model is applied to health analysis, and data points of the data analysis model comprise living habits, working properties, drug treatment schemes, familial inheritance, immune system functional level and disease progression; the weights of the data points are as follows: the weight of the working property was 0.8, the weight of the family inheritance was 0.8, the weight of the lifestyle was 1, the weight of the medication regimen was 1, the weight of the immune system functional level was 1.2, and the weight of the disease progression was 1.2.
In the application of the human immune system function level detection data model in health analysis, the corresponding relationship among the score in the immune system basic detection, the score in the immune system accurate detection, the data point weight and the human health is as follows:
the human immune system function level detection data model comprises an immune system basic detection model, an immune system accurate detection model and a data analysis model; the immune system basic detection comprises the specific marker detection of immune cells and adaptive immune cells; the precise detection of the immune system comprises the detection of a specific marker of a cytokine; the data analysis model comprises the analysis and quantification of immune cells in the basic detection of the immune system and cytokines in the accurate detection of the immune system.
Has the advantages that:
the invention provides a human immune system function level detection data model and application thereof in health analysis, establishes the immune system function level data model, carries out detection and analysis on different disease background crowds through immune system basic detection and immune system accurate detection, and can evaluate the immune system function level of the people under the same disease background crowds to obtain the health condition of patients/non-patients. The advantage of the data analysis model is that compared with clinical data, the data analysis model contains more data points, not only considers the basic information analysis of the population, but also analyzes the occupation, the family inheritance, the immune system function level and the disease treatment scheme. Through the data analysis model, the patient or non-patient can be analyzed, the treatment by the past clinician is not performed any more depending on the experience, and the treatment reliability and the visual sense of the patient to the disease outcome are enhanced. The proportion of the immune cell subgroup in peripheral blood is detected by flow cytometry, so that the immune function state in vivo under different conditions can be known, the method can be used for assisting in the diagnosis of clinical diseases, exploring the pathogenesis, course and prognosis of the diseases, monitoring and guiding clinical treatment schemes, prompting people to think and search for factors causing the diseases, and has great significance for the prevention and treatment of the diseases.
Detailed Description
The invention provides a human immune system function level detection data model and application thereof in establishing analysis, and further detailed description is provided below in order to make the purpose, technical scheme and effect of the invention clearer and more clear. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a human immune system function level detection data model and application thereof in health analysis, wherein the human immune system function level detection data model comprises an immune system basic detection model, an immune system accurate detection model and a data analysis model; the immune system basic detection is carried out by specific markers of immune cells and adaptive immune cells; the immune system is accurately detected by a specific marker of the cell factor; analyzing and quantifying immune cells in the basic detection of the immune system and cytokines in the accurate detection of the immune system, and analyzing the current health condition of the subject through the data analysis model.
The immune system function level data model is established, detection and analysis are carried out on different disease background crowds through immune system basic detection and immune system accurate detection, the immune system function level can be evaluated under the same disease background crowds, and the health condition of a patient/a non-patient can be obtained. It can be seen that: 1) normal population: the functional level of the immune system is low or high, and the risk of certain diseases caused by the change of the functional level of the immune system can be predicted by combining the factors of family history, working property and the like; 2) the disease population: the functional level of the immune system of the patient has close relation with the disease development, the drug influence and the disease outcome, and the disease development of the patient can be predicted according to the evaluation of the functional level of the immune system to guide clinical medication; 3) cell therapy: cell therapy, including immune cell therapy and stem cell therapy, has been used clinically, but the effects of cell therapy on the human body, particularly the immune system, have not been much studied. Therefore, in the population using cell therapy, detection of the immune system function level helps to avoid improper use of cell therapy, and even excessive use of cell therapy.
In one embodiment, the immune system technology detects the ratio of immune cells to adaptive immune cells in human peripheral blood by flow cytometry; the immune system accurately detects the proportion of cytokines in human peripheral blood by flow cytometry. Flow cytometry carries out multiparameter and rapid quantitative analysis on single cells or other biological particles through monoclonal antibodies on the cellular molecular level, integrates computer technology, laser technology, hydrodynamics, cytochemistry and cellular immunology into a whole, and is a technology for carrying out multiparameter and rapid quantitative analysis and sorting on cells, biological particles or macromolecular substances in liquid in a rapid linear motion state; the method has the advantages of rapidness, simplicity, convenience, high sensitivity, high efficiency, safety and biological condition approaching, and the whole blood detection better reserves the cell and biochemical microenvironment and can more accurately reflect the condition in the human body.
Specifically, the operation method of the lost cell technology comprises the steps of collecting 3-5 m l peripheral blood, adding a separation solution and normal saline into the blood, and performing centrifugal separation to obtain mononuclear cells; culturing the single cell in a serum-containing culture medium, blowing, beating and cleaning to obtain a single cell suspension; direct or indirect immunofluorescence staining can be adopted to mark a sample to be detected, and direct immunofluorescence staining which is simple to operate and saves time is preferred in the embodiment; according to different cell parts, the method is divided into cell surface and intracellular antigen staining, and the cell surface antigen marking method comprises the steps of adding corresponding antibodies into peripheral blood, incubating in a dark place, adding a hemolytic agent, washing by PBS, and performing on-machine analysis; the method for labeling the cytoplasm or nuclear antigen comprises the steps of collecting single cell suspension, adding a fixing agent, fixing the cell after in vitro stimulation, and fixing the cell factor in the cell through crosslinking and denaturation of protein on one hand and avoiding loss of the cell surface antigen on the other hand; washing off the fixing solution, adding the membrane breaking agent and the corresponding antibody, washing with PBS, and performing computer analysis. The membrane breaking agent is used for perforating a cell membrane, and is beneficial to the fluorescent labeled antibody to enter cells and be combined with corresponding cytokines. The fixing agent is 0.1-2.0% paraformaldehyde or formaldehyde buffer solution, is used for inactivating infected samples before analysis, and can inactivate 3-5 log-rank viral loads of viruses such as HIV and the like; the film breaking agent is one of 0.05% of saporin, 0.1% of triton and 70% of ethanol.
Further, peripheral blood is a natural single cell that can be directly labeled and then hemolyzed. In the case of a sample from a patient with chronic liver disease or hyperlipidemia, in which the fragility of erythrocytes is reduced due to abnormal lipid metabolism, hemolysin often cannot completely lyse erythrocytes, and a density gradient centrifugation method is required, it should be noted that the more the sample is processed, the more the number of centrifugation, the more cells are lost, and the unequal ratio of such loss in leukocyte classification, and therefore, in the case of a whole blood sample, there is no need to wash after hemolysis, and the number of sample processing steps can be minimized.
Normal reference value for T lymphocyte subpopulation, CD3 +: 50-84%; CD3+/CD4 +: 27 to 51 percent; 15-44% of CD3+/CD8 +; 1.4-2.5% of CD4/CD 8. CD45 is expressed in all leukocytes; CD3 is expressed on T lymphocytes; CD4 is expressed on T helper/inducer lymphocytes (CD4+ T cells) and monocytes; CD8 is expressed on cytotoxic T cells (CD8+ T) and NK cells; CD19 or CD20 is expressed on B lymphocytes; CD16 is expressed in NK cells, monocytes, macrophages, granulocytes, dendritic cells, and the like; CD56 is expressed on NK cells and cytotoxic T cells; CD14 is expressed on monocytes. The total number of CD3+, CD4+ and CD8+ is reduced, indicating that the cellular immune function is low; a decrease in CD4+ (CD4+/CD8+) or an increase in CD8+ (CD8+/CD4+) is indicative of diseases such as hereditary immunodeficiency, systemic lupus erythematosus, chronic active hepatitis, infectious mononucleosis, AIDS, viral infection, malignant tumor (recurrence or metastasis), aplastic anemia, etc.; an increase in CD4+ (CD4+/CD8+) or a decrease in CD8+ (CD8+/CD4+) is indicative of autoimmune diseases, multiple sclerosis, autoimmune hemolytic anemia, rheumatoid arthritis, diabetes, etc.; CD3+, CD4+, CD8+ T cell depletion, indicative of immunoglobulin deficiency, thymic dysplasia, severe immunodeficiency disease; the activity of NK + [ CD (16+56) + ] is low, which indicates diseases such as tumor, leukemia, autoimmune disease, immunodeficiency disease and the like; increased NK + [ CD (16+56) + ] activity, and indication of multiple myeloma, bone marrow transplantation infection, infectious diseases (B virus, herpes virus, pulmonary TB), habitual abortion, etc.; CD19+ B cell depletion, predictive of humoral immunosuppression; increased CD19+ B cells are indicative of B cell malignant proliferative diseases (leukemia) and the like. The differentiation antigen not only participates in recognizing the antigen, capturing the antigen, promoting the interaction between immune cells and the antigen or immune molecules, but also mediates the adhesion between the immune cells and a matrix, plays an important role in immune response, activation and effect stages, analyzes the proportion of each immune cell in peripheral blood of a human body in innate immune cells and adaptive immunity and compares and scores the proportion with a medical standard value, and the analysis can obtain the immune function level of basic detection of a subject.
Further, the detection method of the cell factor comprises the steps of collecting 3-5 ml of human peripheral blood, adding stimulin and an inhibitor into whole blood or single cell suspension, wherein the stimulin can stimulate secretion of the cell factor, adding an intracellular protein secretion inhibitor with a certain concentration, enabling the synthesized cell factor to be accumulated in cells, preventing the cell factor from being secreted outside the cells to influence the detection accuracy, adding a cell surface antibody, incubating for 20-30 min, washing with PBS, adding a fixing agent and a membrane breaking agent and corresponding antibodies, incubating, washing with PBS, and performing on-machine analysis.
Specifically, the anticoagulant is used for preventing the performance of a blood sample from changing and prolonging the storage time of the sample, the anticoagulant is one of ethylenediamine tetraacetate, heparin sodium anticoagulant and sodium citrate anticoagulant, the EDTA salt anticoagulant sample is stably stored for 12-24 hours at room temperature, granulocytes in the EDTA salt anticoagulant sample exceeding 30 hours are likely to be reduced, the heparin sodium or ACD anticoagulant sample can be stably stored for 48 hours, preferably, the sample is subjected to cell counting and classification by a blood cell analyzer at the same time, and EDTA salt is selected as the anticoagulant; and a vacuum tube is adopted for collecting samples.
The blood non-activated leucocyte has no or only a very small amount of cell factors, when the blood non-activated leucocyte is activated by various activators, the synthesis of the cell factors in the cell is increased and is continuously secreted out of the cell to participate in immune regulation, and the cell factors generally combine with corresponding receptors to regulate the growth, differentiation and effect of the cell, regulate immune response, and have multiple functions of regulating innate immunity and adaptive immunity, hematopoiesis, cell growth, APSC multipotential cells, damaged tissue repair and the like. Detecting the proportion of the cell factors in the peripheral blood, analyzing and scoring the cell factors, and improving the accuracy and reliability of the model; moreover, the analysis is used as a supplement to the basic detection of the immune system, and different strategy schemes are used in different disease background populations, thereby improving the applicability of the model.
Different data points have different weights, the data points are quantized and analyzed in combination with the weights, so that the level and the health condition of the immune system of the subject are known, the risk of the subject suffering from diseases can be known according to the results, the medication is guided, the blind treatment is avoided, and the method has great significance for the outcome of the diseases.
Example 1
The different disease background populations were graded by a specific quantitative index (H/DI), with the final grade being 4: 1) grade 1: asymptomatic people without genetic diseases, infectious diseases, rheumatic immune diseases, organ involvement, benign and malignant tumors, mental diseases and other known diseases related to the immune system; 2) grade 2: mild symptomatic populations with known immune system related disease, but the disease is in a stable state, no clinical treatment is available within 3 months, and no disease activity is shown by clinical indicators; 3) grade 3: a moderately symptomatic population with known immune system related disease, but with the disease in a stable post-active state, with clinical treatment within 3 months and no disease activity indicated by post-treatment clinical signs; 4) severely symptomatic people, with known immune system related diseases, were still treated for 3 months and failed to recover to a stable state.
Example 2
The immune system basic detection comprises the steps of collecting 3-5 ml of human peripheral blood, carrying out separation, precipitation, washing, staining and the like on mononuclear cells of the peripheral blood, carrying out detection on specific markers of the innate immune cells and the adaptive immune cells through flow cytometry, such as CD3, CD4, CD8, CD19, CD56, CD25, CD28 and the like, analyzing the proportion of various immune cells in the peripheral blood of the human body in the innate immune cells and the adaptive immune cells, comparing the proportion value of various immune cells with the value used in medicine, wherein 10% -15% of the immune cells deviated from the normal range is 1 score, 15% -20% of the immune cells is 2 score, 25% -30% of the immune cells is 3 score, 30% -35% of the immune cells is 4 score, 40% -50% of the immune cells is 5 score, more than 50% of the immune cells is 6 score, the analysis is used as the basic detection of the immune function level, if necessary, cytokines, such as I L-2, I5-15, I L-21 and the like are subjected to the detection by adding Enzyme linked Immunosorbent Assay (Enzyme-linked Immunosorbent Assay) for detecting the peripheral blood collection, ISA 25, and carrying out the detection on the absorption Assay (human peripheral blood).
Example 3
The immune system accurate detection comprises the steps of combining the existing clinical research and basic research results, carrying out deep immune function detection aiming at different disease background populations, for example, collecting 3-5 ml of human peripheral blood, carrying out precipitation, washing, dyeing and the like, carrying out specific marking on the cell factors of the peripheral blood by an E L ISA technology, carrying out detection on the cell factors of the peripheral blood, such as factors I L-1 β, I L-2, I L-18, TGF- β, IFN-gamma and the like, analyzing the proportion of the cell factors in the human peripheral blood, comparing the proportion value of the cell factors with the medically used value, wherein 10% -15% of the cell factors deviated from a normal range is scored as 1, 15% -20% of the cell factors is scored as 2, 25% -30% of the cell is scored as 3, 30% -35% of the cell is scored as 4, 40% -50% of the cell factors is scored as 5, and more than 50% of the cell factors is scored as 6, the analysis is used as a supplement for the basic detection, and different strategies are used in different disease background populations.
Example 4
The scores of all the immune cells and cytokines are quantified by combining the results of basic detection of the immune system and accurate detection of the immune system with living habits, working properties, drug treatment protocols, familial inheritance, immune system function levels, disease progression and the like, and the immune system function levels of the subjects at that time are analyzed by an analysis model in combination with weight analysis (the weight of the working properties is 0.8, the weight of the family inheritance is 0.8, the weight of the living habits is 1, the weight of the drug treatment protocols is 1, the weight of the immune system function levels is 1.2, and the weight of the disease progression is 1.2). The data analysis can learn the influence of life habits and treatment means on the immune system and the disease outcome in a certain disease background.
Example 5
The corresponding relationship among the score in the immune system basic detection, the score in the immune system accurate detection, the data point weight and the human health is as follows:
in summary, the invention provides a data model for detecting the functional level of the human immune system and the application thereof in health analysis, wherein the data model is established by the functional level of the immune system, and the detection and analysis are performed on different disease background populations by the basic detection and the accurate detection of the immune system, so that the functional level of the immune system can be evaluated under the same disease background population to obtain the health condition of patients/non-patients. The advantage of the data analysis model is that compared with clinical data, the data analysis model contains more data points, not only considers the basic information analysis of the population, but also analyzes the occupation, the family inheritance, the immune system function level and the disease treatment scheme. Through the data analysis model, the patient/non-patient can be analyzed, the treatment by the past clinician is not performed any more depending on the experience, and the treatment reliability and the instant vision sense of the patient to the disease outcome are enhanced.
It should be understood that equivalents and modifications of the technical solution and inventive concept thereof may occur to those skilled in the art, and all such modifications and alterations should fall within the scope of the appended claims.
Claims (10)
1. The application of the human immune system function level detection data model in health analysis is characterized in that the human immune system function level detection data model comprises an immune system basic detection model, an immune system accurate detection model and a data analysis model; the immune system basic detection is carried out by specific markers of immune cells and adaptive immune cells; the immune system is accurately detected by a specific marker of the cell factor; analyzing and quantifying immune cells in the basic detection of the immune system and cytokines in the accurate detection of the immune system, and analyzing the current health condition of the subject through the data analysis model.
2. The use of the data model for detecting the functional level of the human immune system according to claim 1 in health analysis, wherein the health status of the subject is classified into the following 4 grades:
grade 1: asymptomatic, without accompanying known immune system-related diseases;
grade 2: mild symptoms, with known immune system related diseases, but the disease is in a stable state, no clinical treatment within 3 months, no disease activity is shown by clinical indicators;
grade 3: moderate symptoms, associated with known immune system related diseases, but the disease is in a stable state after activity, clinical treatment is carried out within 3 months, and clinical indicators do not show disease activity after treatment;
grade 4: severe symptoms, with known immune system related diseases, remain treated for 3 months and fail to return to a stable state.
3. The use of the model of data for testing the functional level of the human immune system as claimed in claim 1, wherein the basic test of the immune system comprises testing the ratio of immune cells to immune cells in adaptive immunity in the peripheral blood of human body; the immune system accurate detection comprises the detection of the proportion of cytokines in human peripheral blood.
4. The use of the model for testing the functional level of the human immune system of claim 3 in health analysis, further comprising scoring the ratio of immune cells to adaptive immune cells in peripheral blood of human, wherein the ratio and the score are related as follows: comparing the ratio of the immune cells with the medical standard value, 10% -15% deviating from the normal range is scored as 1 point, 15% -20% is scored as 2 points, 25% -30% is scored as 3 points, 30% -35% is scored as 4 points, 40% -50% is scored as 5 points, and more than 50% is scored as 6 points.
5. The use of the data model for testing the functional level of the human immune system as claimed in claim 3, wherein the immune cells in the basic test of the immune system include CD3, CD4, CD8, CD19, CD56, CD25, CD 28.
6. The use of the model for testing the functional level of the human immune system in health analysis according to claim 3, further comprising scoring the ratio of cytokines in the peripheral blood of the human, wherein the relationship between the ratio and the score is as follows: comparing the proportional value of the cytokine with the medical standard value, 10% -15% deviating from the normal range is scored as 1 point, 15% -20% is scored as 2 points, 25% -30% is scored as 3 points, 30% -35% is scored as 4 points, 40% -50% is scored as 5 points, and more than 50% is scored as 6 points.
7. The use of the data model for testing the functional level of human immune system as claimed in claim 3, wherein the cytokines in the precise test of immune system include I L-1 β, I L-2, I L-18, TGF- β, IFN- γ.
8. The use of the human immune system functional level detection data model of claim 1 in health analysis, wherein the data points of the data analysis model include lifestyle habits, performance characteristics, drug treatment regimens, family inheritance, immune system functional level, disease progression; the weights of the data points are as follows: the weight of the working property was 0.8, the weight of the family inheritance was 0.8, the weight of the lifestyle was 1, the weight of the medication regimen was 1, the weight of the immune system functional level was 1.2, and the weight of the disease progression was 1.2.
9. The use of the data model for detecting the functional level of the human immune system according to any one of claims 1 to 8 in health analysis, wherein the corresponding relationship between the score in the basic detection of the immune system, the score in the precise detection of the immune system, the weight of the data point and the health condition of the human body is as follows:
10. the human immune system function level detection data model is characterized by comprising an immune system basic detection model, an immune system accurate detection model and a data analysis model; the immune system basic detection comprises the specific marker detection of immune cells and adaptive immune cells; the precise detection of the immune system comprises the detection of a specific marker of a cytokine; the data analysis model comprises the analysis and quantification of immune cells in the basic detection of the immune system and cytokines in the accurate detection of the immune system.
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