CN116990514A - Lymphoma biomarker and detection system and kit thereof - Google Patents

Lymphoma biomarker and detection system and kit thereof Download PDF

Info

Publication number
CN116990514A
CN116990514A CN202310502919.XA CN202310502919A CN116990514A CN 116990514 A CN116990514 A CN 116990514A CN 202310502919 A CN202310502919 A CN 202310502919A CN 116990514 A CN116990514 A CN 116990514A
Authority
CN
China
Prior art keywords
biomarker
lymphoma
detection
cell expressing
kit
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310502919.XA
Other languages
Chinese (zh)
Inventor
李太生
陆莲凤
陈宇
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Peking Union Medical College Hospital Chinese Academy of Medical Sciences
Original Assignee
Peking Union Medical College Hospital Chinese Academy of Medical Sciences
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Peking Union Medical College Hospital Chinese Academy of Medical Sciences filed Critical Peking Union Medical College Hospital Chinese Academy of Medical Sciences
Priority to CN202310502919.XA priority Critical patent/CN116990514A/en
Publication of CN116990514A publication Critical patent/CN116990514A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407Specifically defined cancers
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57484Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Immunology (AREA)
  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Urology & Nephrology (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Hematology (AREA)
  • Cell Biology (AREA)
  • Microbiology (AREA)
  • Biotechnology (AREA)
  • Oncology (AREA)
  • Hospice & Palliative Care (AREA)
  • Food Science & Technology (AREA)
  • Medicinal Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Pathology (AREA)
  • Investigating Or Analysing Biological Materials (AREA)

Abstract

The application discloses a lymphoma biomarker, a detection system and a kit thereof. The biomarker is any one or more of a cell expressing CD4+CD38+/CD4+ T, a cell expressing CD4+HLA-DR+/CD4+ T, a cell expressing CD4+PD-1+/CD4+ T, a cell expressing CD4+KI-67/CD4+ T, a cell expressing CD8+CD38+/CD8+ T, a cell expressing CD8+HLA-DR+/CD8+ T, a cell expressing CD8+PD-1+/CD4+ T, and a cell expressing CD8+KI-67/CD8+ T. The application also discloses a detection system for detecting the biomarker, which comprises a detection module and an analysis module; the detection module is used for detecting the content of each biomarker in the sample; the analysis module is used for receiving and analyzing the data obtained by the detection module; methods for detecting a sample by the detection module include flow cytometry. The application also discloses a lymphoma detection kit, which comprises detection reagents, wherein the detection reagents comprise reagents for detecting one or more of the biomarkers. The biomarker and the detection system or the detection kit can identify whether an organism has lymphoma.

Description

Lymphoma biomarker and detection system and kit thereof
Technical Field
The application relates to the technical field of biology, in particular to a lymphoma biomarker, a detection system and a kit thereof.
Background
The immune system is an important component of the human body defense system and plays a key role in eliminating external pathogens, purifying aging cells and monitoring autoimmune. Numerical detection of relative percentages and absolute counts of lymphocyte subpopulations is abnormal when immune function is impaired. Therefore, measurement and evaluation of the immune status of the human body by some markers has an important role in delaying aging, preventing diseases or treating diseases.
Although the pathogenesis of most immune diseases is unknown, in recent years, immune-related problems have emerged in the study of various diseases. The immune system is a defense system for an organism to execute immune response and immune function, and consists of three parts of immune organs, immune cells and immune molecules, and can recognize abnormal cells, clear non-abnormal cells and maintain stable internal environment of the organism. However, immune homeostasis is often disrupted by foreign pathogens, internal cancer cells, autoantibodies, etc., which may lead to reduced immune function in the body, and thus immune disorders are susceptible to infection and tumor development.
Mechanistically, immune disorders involve multiple cell, multiple molecule, multiple channel functional changes. The most obvious manifestation of immune disorders is a change in immune cell number and function, an increase or decrease in T cell number with the disappearance of TCR diversity, memory B cell increase, NK cell number but decreased killing ability in the face of the occurrence of different diseases. A large amount of soluble factors are secreted, the formation of inflammatory microenvironment is promoted, and inflammatory factor storm is generated when the inflammatory microenvironment is excessively activated.
Currently available methods for determining immune disorders are not few, but most of the detection methods either choose a single measurement index or focus more on the determination of cytokines, while less attention is paid to the change of cell surface molecules, giving results that are mostly lacking in generalizability and simplicity and operability.
Lymphomas are a group of malignant tumors originating in lymph nodes or other lymphoid tissues, and can be divided into two major categories, hodgkin's Disease (HD) and non-hodgkin's lymphoma (NHL), and are currently one of the most common ten malignant tumors. Histologically, neoplastic hyperplasia of lymphocytes and/or histiocytes is mainly manifested clinically by painless, progressive lymphadenectasis.
In the current method for detecting lymphoma fusion genes by molecular biology widely used at home and abroad, the Fluorescence In Situ Hybridization (FISH) technology can only perform qualitative detection and has complex operation; the fluorescent quantitative PCR has the limitation of detection flux, so that the requirements of clinical diagnosis and detection cannot be met truly. The conventional solid-phase Biochip (Biochip) technology has the prominent weaknesses of poor repeatability, insufficient sensitivity and complicated operation. There is therefore a need for a lymphoma biomarker with clinical accessibility to aid in the diagnosis of early stage lymphoma.
Disclosure of Invention
Aiming at the defects in the prior art, the application provides a lymphoma biomarker, a detection system and a kit thereof. Human immune homeostasis is assessed from the perspective of immune cell subpopulations, allowing for a more comprehensive and careful monitoring of lymphomas.
For the purpose of the application, immune markers related to lymphomas were screened after measuring immune cell subsets of 101 healthy people.
The present application provides a lymphoma biomarker which is any one or more of a cell expressing CD4+CD38+/CD4+ T, a cell expressing CD4+HLA-DR+/CD4+ T, a cell expressing CD4+PD-1+/CD4+ T, a cell expressing CD4+KI-67/CD4+ T, a cell expressing CD8+CD38+/CD8+ T, a cell expressing CD8+HLA-DR+/CD8+ T, a cell expressing CD8+PD-1+/CD4+ T, and a cell expressing CD8+KI-67/CD8+ T.
Further, the biomarker is used for detection of lymphoma.
Further, the number of one or more of the biomarkers is drastically reduced in lymphoma afflicted individuals.
The application also provides a detection system of the lymphoma biomarker, which comprises a detection module and an analysis module; the detection module is used for detecting the content of each biomarker in a sample; the analysis module is used for receiving and analyzing the data obtained by the detection module. The method comprises the following specific steps:
(1) Setting a disease group and a healthy control group, and obtaining samples of the immune related disease group and the healthy control group; (2) Detecting immune subgroup cell markers of the two groups of samples by adopting a detection module to obtain immune cell marker detection data; (3) Inputting the detection data obtained in the step (2) into an analysis module for analysis; the analysis comprises comparing and analyzing the detection data of the markers of the same kind in the related disease group and the healthy control group, and performing correlation analysis on the detection data of the markers of different kinds in the immune related disease group.
Further, the detection module uses a flow cytometer.
Further, the sample includes, but is not limited to, blood.
Further, the analysis module is used for analyzing the content change of each biomarker.
The application also provides a detection kit for the lymphoma biomarkers, wherein the kit comprises detection reagents, and the detection reagents comprise reagents for detecting the biomarkers.
The application also provides the use of said biomarker or said detection system or said kit in any of the following:
(1) Preparing a lymphoma detection product;
(2) Study of lymphoma pathogenesis.
In conclusion, compared with the prior art, the application achieves the following technical effects:
(1) The application provides a system and a kit for evaluating immune homeostasis of healthy people and disease states, which comprehensively and integrally reflect the possibility of suffering from lymphoma through the change of surface markers of a plurality of immune cells. In addition, the whole process is simple and efficient, low in cost and convenient to popularize.
(2) The kit provided by the application is used for detecting the relative proportion of KI-67+, PD-1+, CD38+ and HLA-DR+ expressed on the surface of CD8 and CD4 cells in a sample to be detected so as to comprehensively characterize the immune level of a patient, thereby helping to judge whether the current immune state of a subject is disordered or not, helping a clinician to identify whether the subject is likely to suffer from lymphoma or not and establishing an individualized treatment strategy.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a diagram showing an exemplary multi-parameter flow cytometer for evaluating immune cell subsets in an immune status according to an embodiment of the present application; (a) lymphocytes; (B) cd3+ T cells; (C) cd4+ T cells; (D) cd8+ T cells; (E) B cells (CD 3-cd19+); (F) NK cells (CD 3-cd56+); (G) cd4+cd38+ T cells (cd3+cd4+cd38+); (H) cd4+hla-dr+ T cells (cd3+cd4+hla-dr+); (I) cd4+pd-1+t cells (cd3+cd4+pd-1+); (J) cd4+ki-67+ t cells (cd3+cd4+ki-67+); (K) cd8+cd38+ T cells (cd3+cd8+cd38+); (L) cd8+ HLA-dr+ T cells (cd3+cd8+ HLA-dr+); (M) cd8+pd-1+t cells (cd3+cd8+pd-1+); (N) CD8+KI-67+ T cells (CD3+CD8+KI-67+).
FIG. 2 is a graph showing the trend and correlation analysis of each cell subset with age, wherein FIG. 2A shows that CD4+CD38+% is positively correlated with age, FIG. 2B shows that CD4+HLA-DR% is negatively correlated with age, FIG. 2E shows that CD8+HLA-DR% is positively correlated with age, and FIG. 2C shows that CD4+PD-1% is positively correlated with age.
FIG. 3 is an example of a flow chart of results for a final diagnosis of lymphoma patient numbered 2;
FIG. 4 is an example of a flow chart of results for healthy controls numbered 8;
FIG. 5 is a plot of the proportion of CD4+CD38+/CD4+ T cells, CD4+HLA-DR+/CD4+ T cells, CD4+PD-1+/CD4+ T cells, CD4+KI-67/CD4+ T cells, CD8+CD38+/CD8+ T cells, CD8+HLA-DR+/CD8+ T cells, CD8+PD-1+/CD4+ T cells, CD8+KI-67/CD8+ T cells versus healthy controls for patients with fever with unknown origin.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, shall fall within the scope of the application.
Example 1
1. Study population
This example groups 51 healthy men and 50 healthy women (subjects) into three groups according to age: 18-35 years old, 36-59 years old, >60 years old. Subjects with severe disease, tumor, acute infection, autoimmune disease, genetic disease, congenital disease, radiation therapy or biological agent treatment are excluded. Table 1 counts the main characteristics of the study population, including the proportion of individuals at each age, the average age, and the white blood cell and lymphocyte counts of the subjects.
TABLE 1 clinical data
2. Research method
(1) Research reagent
The application provides a flow cytometry detection kit for evaluating human lymphoma, which comprises a reagent A: reagent A includes fluorescent microsphere labeled CD85 monoclonal antibody, CD3 monoclonal antibody, CD8 monoclonal antibody, CD16 monoclonal antibody, CD56 monoclonal antibody, CD19 monoclonal antibody, PD-1 monoclonal antibody, CD38 monoclonal antibody, HLA-DR monoclonal antibody, ki-67 monoclonal antibody, which are stained with different color dyes. The concentration ratio of each antibody was 1:1:1:1:1, which are 0.05-0.1mg/mL. The detection kit also comprises a reagent B, wherein the reagent B is erythrocyte lysate.
The collocation of each antibody model sequence and the flow cytometer dye detection signal can be as follows: CD45 antibody (2D 1/IgG1, V500-C channel), CD3 antibody (UCHT 1/IgG1, PE-Cy7 channel), CD8 antibody (SK 3/IgG1, AF700 channel), CD8 antibody (53-6.7/IgG 2a, APC-Cy7 channel), CD38 antibody (UCHT 1/IgG1, PE-Cy7 channel), HLA-DR antibody (L243/IgG 2a, percp-Cy5.5 channel), PD-1 antibody (J43/IgG 2, BV605 channel), ki-67 antibody (35/IgG 1, FITC channel).
(2) 2ml of whole blood was used as an examination initiator, comprising the steps of:
step one: respectively sucking EDTA-K2 anticoagulated whole blood to the bottom of the flow tube by using a reverse pipetting technology, so as to prevent the blood from touching the upper part of the tube wall;
step two: adding a reagent A into the tube, wherein the volume ratio of the reagent A to the whole blood is 1:10, and uniformly mixing by a vortex instrument; incubating at room temperature in a dark place; adding a split red liquid into the tube, wherein the volume ratio of the reagent B to the whole blood is 20:1; mixing evenly by a vortex instrument; light-shielding reaction;
step three: centrifuging at 20deg.C, removing supernatant, adding 2ml PBS solution, centrifuging at 20deg.C, removing supernatant, adding 350 μl PBS solution again to form cell suspension, and detecting by upflow cytometry;
step four: multiparameter flow cytometry was performed using BD LSRFortessa X20 and the results were analyzed using FlowJo V10 software (Tree Star) software. Each subpopulation analyzed included: screening cells positive for CD85 antibody and having SSC value in the range of 0-50K, and determining the cells as lymphocytes; the following cell subsets were isolated from lymphocyte subsets:
(A) A lymphocyte; (B) cd3+ T cells; (C) cd4+ T cells; (D) cd8+ T cells; (E) B cells (CD 3-cd19+); (F) NK cells (cd3-cd16+cd56+); (G) cd8+cd38+ T cells (cd3+cd8+cd38+); (H) cd8+ HLA-dr+ T cells (cd3+ cd8+ HLA-dr+); (I) cd8+pd-1+t cells (cd3+cd8+pd-1+); (J) CD8+KI-67+ T cells (CD3+CD8+KI-67+).
3. Statistical analysis
(1) Statistical analysis was performed using SPSS statistical software version 22.0 and GraphPadPrism version 8.0. All data were evaluated for distribution normalization using the Shapiro Wilk test. Quantitative data are expressed as mean ± standard deviation, and classification values are expressed as numbers (n) and percent (%). For data of the skewed distribution, the data are expressed as median and extremum (minimum and maximum). The comparison of the classified variables adopts chi-square test, the continuous variables conforming to normal distribution evaluate the difference between two or more groups by t test or ANOVA, and the continuous variables not conforming to normal distribution evaluate the difference between two or more groups by rank sum test.
(2) In the present application, the "reference value range" is a reference value range with respect to the "median", for example, after all the observed values are sorted from small to large, the 5 th percentile and the 95 th percentile are calculated, respectively, where the 5 th percentile is the lower limit of the reference value range and the 95 th percentile is the upper limit of the reference value range. Correspondingly, the median is the 50% percentile. The pearson correlation coefficient is used to evaluate the relationship between age and subpopulations that do not fit a normal distribution, and the spearman correlation coefficient is used to evaluate the relationship between age and subpopulations that do not fit a normal distribution.
4. Results
TABLE 2 differential distribution of cell subsets over age
FIG. 2 is a trend graph and correlation analysis of age-related cell subsets of significance provided by examples of the present application
Table 3 establishes the normal reference ranges for each cell subpopulation in healthy humans
Example 2
The application also provides a flow cytometer detection kit of the immune status phenotype, which comprises a reagent C: reagent C includes fluorescent microsphere-labeled CD85 monoclonal antibody, CD3 monoclonal antibody, CD8 monoclonal antibody, CD19 monoclonal antibody, CD56CD16 monoclonal antibody, CD38 monoclonal antibody, HLA-DR monoclonal antibody, KI-67 monoclonal antibody and PD-1 monoclonal antibody stained with different color dyes.
A total of 6 patients with fever with unknown causes and confirmed lymphomas are selected, and 10 healthy people are selected as a control group.
TABLE 4 clinical trial cases
FIG. 3 is an example of a flow chart of results for a final diagnosis of lymphoma patient numbered 2;
FIG. 4 is an example of a flow chart of results for healthy controls numbered 8;
FIG. 5 shows the significant differences in CD4, CD8 expression of CD4+HLA-DR+/CD4+ T cell ratio, CD4+PD-1+/CD4+ T cell ratio, CD4+KI-67/CD4+ T cell ratio, CD8+CD38+/CD8+ T cell ratio, CD8+HLA-DR+/CD8+ T cell ratio, CD8+PD-1+/CD4+ T cell ratio, CD8+KI-67/CD8+ T cell ratio versus healthy group control, CD38, HLA-DR, PD-1, KI-67 for CD4, CD8 (p <0.05, p <0.01, p <0.001, p < 0.0001). The statistical method comprises the following steps: the comparison was performed using a separate sample t-test.
Under different types of diseases and human immune disorder states, the surface expression of CD38+, HLA-DR, PD-1 and KI-67 on CD4 and CD8 can be increased or decreased to different degrees, and the surface expression is obviously different from that of a healthy control group. In conclusion, the immune homeostasis assessment kit can be used for assessing healthy people and comprehensively assessing lymphomas by combining a flow cytometer, and is convenient to use, safe to human bodies and easy to operate.
The foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the application are intended to be included within the scope of the application.

Claims (9)

1. A lymphoma biomarker, wherein the biomarker is any one or more of a cell expressing cd4+cd38+/cd4+ T, a cell expressing cd4+hla-dr+/cd4+ T, a cell expressing cd4+pd-1+/cd4+ T, a cell expressing cd4+ki-67/cd4+ T, a cell expressing cd8+cd38+/cd8+ T, a cell expressing cd8+hla-dr+/cd8+ T, a cell expressing cd8+pd-1+/cd4+ T, a cell expressing cd8+ki-67/cd8+ T.
2. The lymphoma biomarker according to claim 1, wherein the biomarker is used for detection of lymphoma.
3. The lymphoma biomarker according to claim 1 or 2, wherein the number of one or more of the biomarkers is drastically reduced in lymphoma afflicted individuals.
4. A lymphoma biomarker detection system, comprising a detection module and an analysis module; the detection module is used for detecting the content of each biomarker in a sample; the analysis module is used for receiving and analyzing the data obtained by the detection module.
5. The detection system of claim 4, wherein the detection module uses a flow cytometer.
6. The detection system of claim 4, wherein the sample includes, but is not limited to, blood.
7. The detection system of claim 4, wherein the analysis module is configured to analyze the change in the content of each biomarker.
8. A kit for detecting a biomarker for lymphoma, said kit comprising a detection reagent comprising a reagent for detecting each biomarker of claim 1.
9. Use of a biomarker according to any of claims 1 to 3 or a detection system according to any of claims 4 to 7 or a kit according to claim 8 in any of the following: (1) preparing a lymphoma assay product; (2) study of the pathogenesis of lymphoma.
CN202310502919.XA 2023-05-06 2023-05-06 Lymphoma biomarker and detection system and kit thereof Pending CN116990514A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310502919.XA CN116990514A (en) 2023-05-06 2023-05-06 Lymphoma biomarker and detection system and kit thereof

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310502919.XA CN116990514A (en) 2023-05-06 2023-05-06 Lymphoma biomarker and detection system and kit thereof

Publications (1)

Publication Number Publication Date
CN116990514A true CN116990514A (en) 2023-11-03

Family

ID=88532840

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310502919.XA Pending CN116990514A (en) 2023-05-06 2023-05-06 Lymphoma biomarker and detection system and kit thereof

Country Status (1)

Country Link
CN (1) CN116990514A (en)

Similar Documents

Publication Publication Date Title
Al-Mawali et al. Incidence, sensitivity, and specificity of leukemia-associated phenotypes in acute myeloid leukemia using specific five-color multiparameter flow cytometry
CA2516795C (en) Circulating tumor cells (ctc&#39;s): early assessment of time to progression,_survival and response to therapy in metastatic cancer patients
EP2491395B1 (en) Method of using non-rare cells to detect rare cells
de Tute Flow cytometry and its use in the diagnosis and management of mature lymphoid malignancies
Urrechaga et al. Role of leucocytes cell population data in the early detection of sepsis
Horna et al. Flow cytometric evaluation of peripheral blood for suspected Sézary syndrome or mycosis fungoides: international guidelines for assay characteristics
Boer et al. Evaluation of the XE-5000 for the automated analysis of blood cells in cerebrospinal fluid
El Hawary et al. Role of flow cytometry in the diagnosis of chronic granulomatous disease: the Egyptian experience
Zouiouich et al. Automated bedside flow cytometer for mHLA-DR expression measurement: a comparison study with reference protocol
AU2012267489A1 (en) System and method of cytomic vascular health profiling
Tarrant The role of flow cytometry in companion animal diagnostic medicine
van der Pan et al. Performance of spectral flow cytometry and mass cytometry for the study of innate myeloid cell populations
Nogimori et al. OMIP 078: A 31‐parameter panel for comprehensive immunophenotyping of multiple immune cells in human peripheral blood mononuclear cells
Oyaert et al. Improving clinical performance of urine sediment analysis by implementation of intelligent verification criteria
Soh et al. Development of a 27‐color panel for the detection of measurable residual disease in patients diagnosed with acute myeloid leukemia
Houyhongthong et al. Automated nucleated red blood cell count using the Mindray BC‐6800 hematology analyzer
Kasten-Jolly et al. Differential blood leukocyte populations based on individual variances and age
Gustafson et al. Strategies for improving the reporting of human immunophenotypes by flow cytometry
CN116990514A (en) Lymphoma biomarker and detection system and kit thereof
Szmulik et al. A novel approach to screening and managing the urinary tract infections suspected sample in the general human population
Kim et al. Neutrophils with toxic granulation show high fluorescence with bis (Zn2+-dipicolylamine) complex
AU2011215826B2 (en) Compositions and methods for predicting cardiovascular events
Magierowicz et al. Reference values for WBC differential by hematoflow analysis
Woolfson et al. The application of CD antigen proteomics to pharmacogenomics
RU2815709C1 (en) Method of detection of cell-free dna in whole peripheral blood using flow cytometry

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination