WO2013064078A1 - 疟原虫感染的红细胞的识别方法及装置 - Google Patents
疟原虫感染的红细胞的识别方法及装置 Download PDFInfo
- Publication number
- WO2013064078A1 WO2013064078A1 PCT/CN2012/083864 CN2012083864W WO2013064078A1 WO 2013064078 A1 WO2013064078 A1 WO 2013064078A1 CN 2012083864 W CN2012083864 W CN 2012083864W WO 2013064078 A1 WO2013064078 A1 WO 2013064078A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- cells
- plasmodium
- red blood
- scattered light
- scattergram
- Prior art date
Links
- 210000003743 erythrocyte Anatomy 0.000 title claims abstract description 121
- 238000000034 method Methods 0.000 title claims abstract description 72
- 210000004027 cell Anatomy 0.000 claims abstract description 117
- 210000004369 blood Anatomy 0.000 claims description 69
- 239000008280 blood Substances 0.000 claims description 69
- 241000224016 Plasmodium Species 0.000 claims description 59
- 201000004792 malaria Diseases 0.000 claims description 44
- 244000045947 parasite Species 0.000 claims description 20
- 239000003153 chemical reaction reagent Substances 0.000 claims description 17
- 238000001514 detection method Methods 0.000 claims description 15
- 238000012545 processing Methods 0.000 claims description 13
- 238000009534 blood test Methods 0.000 claims description 10
- 102000001554 Hemoglobins Human genes 0.000 claims description 9
- 108010054147 Hemoglobins Proteins 0.000 claims description 9
- 210000000601 blood cell Anatomy 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 8
- 230000002159 abnormal effect Effects 0.000 claims description 5
- 230000005856 abnormality Effects 0.000 claims description 3
- 238000010586 diagram Methods 0.000 abstract description 9
- 125000000217 alkyl group Chemical group 0.000 description 22
- 210000000265 leukocyte Anatomy 0.000 description 14
- 229910052736 halogen Inorganic materials 0.000 description 9
- 125000001797 benzyl group Chemical group [H]C1=C([H])C([H])=C(C([H])=C1[H])C([H])([H])* 0.000 description 8
- 230000006870 function Effects 0.000 description 7
- 150000002367 halogens Chemical class 0.000 description 7
- 125000001495 ethyl group Chemical group [H]C([H])([H])C([H])([H])* 0.000 description 6
- -1 fluorenyl bromide isoquinoline Chemical compound 0.000 description 6
- 238000007689 inspection Methods 0.000 description 6
- 125000002496 methyl group Chemical group [H]C([H])([H])* 0.000 description 6
- 125000001436 propyl group Chemical group [H]C([*])([H])C([H])([H])C([H])([H])[H] 0.000 description 6
- 238000003745 diagnosis Methods 0.000 description 5
- 125000003545 alkoxy group Chemical group 0.000 description 4
- 125000003178 carboxy group Chemical group [H]OC(*)=O 0.000 description 4
- 239000003093 cationic surfactant Substances 0.000 description 4
- 239000003219 hemolytic agent Substances 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 description 3
- 125000004442 acylamino group Chemical group 0.000 description 3
- 125000003342 alkenyl group Chemical group 0.000 description 3
- 125000003282 alkyl amino group Chemical group 0.000 description 3
- 125000003118 aryl group Chemical group 0.000 description 3
- 125000004369 butenyl group Chemical group C(=CCC)* 0.000 description 3
- 125000000484 butyl group Chemical group [H]C([*])([H])C([H])([H])C([H])([H])C([H])([H])[H] 0.000 description 3
- 125000004093 cyano group Chemical group *C#N 0.000 description 3
- 125000001188 haloalkyl group Chemical group 0.000 description 3
- 125000000623 heterocyclic group Chemical group 0.000 description 3
- 229910052739 hydrogen Inorganic materials 0.000 description 3
- 125000000449 nitro group Chemical group [O-][N+](*)=O 0.000 description 3
- 125000001997 phenyl group Chemical group [H]C1=C([H])C([H])=C(*)C([H])=C1[H] 0.000 description 3
- 125000001424 substituent group Chemical group 0.000 description 3
- RTZKZFJDLAIYFH-UHFFFAOYSA-N Diethyl ether Chemical compound CCOCC RTZKZFJDLAIYFH-UHFFFAOYSA-N 0.000 description 2
- 125000003277 amino group Chemical group 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 229910052799 carbon Inorganic materials 0.000 description 2
- 230000005859 cell recognition Effects 0.000 description 2
- 150000001875 compounds Chemical class 0.000 description 2
- 125000002704 decyl group Chemical group [H]C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])* 0.000 description 2
- LQZZUXJYWNFBMV-UHFFFAOYSA-N dodecan-1-ol Chemical compound CCCCCCCCCCCCO LQZZUXJYWNFBMV-UHFFFAOYSA-N 0.000 description 2
- 125000003438 dodecyl group Chemical group [H]C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])* 0.000 description 2
- 239000000975 dye Substances 0.000 description 2
- 210000000267 erythroid cell Anatomy 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 238000000684 flow cytometry Methods 0.000 description 2
- 238000005534 hematocrit Methods 0.000 description 2
- 208000015181 infectious disease Diseases 0.000 description 2
- 210000004698 lymphocyte Anatomy 0.000 description 2
- 210000001616 monocyte Anatomy 0.000 description 2
- 125000001421 myristyl group Chemical group [H]C([*])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])[H] 0.000 description 2
- 125000002347 octyl group Chemical group [H]C([*])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])C([H])([H])[H] 0.000 description 2
- 150000003242 quaternary ammonium salts Chemical class 0.000 description 2
- 229910052711 selenium Inorganic materials 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 229910052717 sulfur Inorganic materials 0.000 description 2
- 239000004094 surface-active agent Substances 0.000 description 2
- 208000024891 symptom Diseases 0.000 description 2
- 206010003399 Arthropod bite Diseases 0.000 description 1
- LSNNMFCWUKXFEE-UHFFFAOYSA-M Bisulfite Chemical compound OS([O-])=O LSNNMFCWUKXFEE-UHFFFAOYSA-M 0.000 description 1
- 208000035473 Communicable disease Diseases 0.000 description 1
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 description 1
- 229920003171 Poly (ethylene oxide) Polymers 0.000 description 1
- 206010037660 Pyrexia Diseases 0.000 description 1
- PVSWUYJJLMMEQX-UHFFFAOYSA-N [O-][N+](c1ccc(CN(C=C2)c(cccc3)c3/C2=C/C=C/C=C/c2[n+](Cc3ccccc3)c3ccccc3[s]2)cc1)=O Chemical compound [O-][N+](c1ccc(CN(C=C2)c(cccc3)c3/C2=C/C=C/C=C/c2[n+](Cc3ccccc3)c3ccccc3[s]2)cc1)=O PVSWUYJJLMMEQX-UHFFFAOYSA-N 0.000 description 1
- 150000008052 alkyl sulfonates Chemical class 0.000 description 1
- 150000001449 anionic compounds Chemical class 0.000 description 1
- 150000001450 anions Chemical class 0.000 description 1
- 239000003146 anticoagulant agent Substances 0.000 description 1
- 229940127219 anticoagulant drug Drugs 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000017531 blood circulation Effects 0.000 description 1
- 238000004820 blood count Methods 0.000 description 1
- 210000000170 cell membrane Anatomy 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- BNIILDVGGAEEIG-UHFFFAOYSA-L disodium hydrogen phosphate Chemical compound [Na+].[Na+].OP([O-])([O-])=O BNIILDVGGAEEIG-UHFFFAOYSA-L 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000001747 exhibiting effect Effects 0.000 description 1
- 238000005206 flow analysis Methods 0.000 description 1
- 125000003983 fluorenyl group Chemical group C1(=CC=CC=2C3=CC=CC=C3CC12)* 0.000 description 1
- 239000007850 fluorescent dye Substances 0.000 description 1
- 238000001215 fluorescent labelling Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 108010080417 hemozoin Proteins 0.000 description 1
- 125000002887 hydroxy group Chemical group [H]O* 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000003834 intracellular effect Effects 0.000 description 1
- 150000002500 ions Chemical class 0.000 description 1
- 239000012528 membrane Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 229910000403 monosodium phosphate Inorganic materials 0.000 description 1
- 235000019799 monosodium phosphate Nutrition 0.000 description 1
- 230000000877 morphologic effect Effects 0.000 description 1
- 239000002736 nonionic surfactant Substances 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 125000002924 primary amino group Chemical group [H]N([H])* 0.000 description 1
- 125000002943 quinolinyl group Chemical class N1=C(C=CC2=CC=CC=C12)* 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- WXMKPNITSTVMEF-UHFFFAOYSA-M sodium benzoate Chemical compound [Na+].[O-]C(=O)C1=CC=CC=C1 WXMKPNITSTVMEF-UHFFFAOYSA-M 0.000 description 1
- 235000010234 sodium benzoate Nutrition 0.000 description 1
- 239000004299 sodium benzoate Substances 0.000 description 1
- AJPJDKMHJJGVTQ-UHFFFAOYSA-M sodium dihydrogen phosphate Chemical compound [Na+].OP(O)([O-])=O AJPJDKMHJJGVTQ-UHFFFAOYSA-M 0.000 description 1
- 125000000542 sulfonic acid group Chemical group 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 239000010409 thin film Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
- G01N21/49—Scattering, i.e. diffuse reflection within a body or fluid
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
- G01N21/49—Scattering, i.e. diffuse reflection within a body or fluid
- G01N21/51—Scattering, i.e. diffuse reflection within a body or fluid inside a container, e.g. in an ampoule
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N21/6486—Measuring fluorescence of biological material, e.g. DNA, RNA, cells
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
- G01N33/5091—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing the pathological state of an organism
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
- G01N33/5094—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for blood cell populations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
- G01N33/56905—Protozoa
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/80—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving blood groups or blood types or red blood cells
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/01—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/01—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells
- G01N2015/011—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells with lysing, e.g. of erythrocytes
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/01—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells
- G01N2015/012—Red blood cells
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/01—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells
- G01N2015/016—White blood cells
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
- G01N2021/4704—Angular selective
- G01N2021/4707—Forward scatter; Low angle scatter
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
- G01N2021/4704—Angular selective
- G01N2021/4711—Multiangle measurement
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
- G01N2021/4704—Angular selective
- G01N2021/4726—Detecting scatter at 90°
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N2021/6491—Measuring fluorescence and transmission; Correcting inner filter effect
- G01N2021/6493—Measuring fluorescence and transmission; Correcting inner filter effect by alternating fluorescence/transmission or fluorescence/reflection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
- G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
- G01N2333/44—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans from protozoa
- G01N2333/445—Plasmodium
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
- Y02A50/30—Against vector-borne diseases, e.g. mosquito-borne, fly-borne, tick-borne or waterborne diseases whose impact is exacerbated by climate change
Definitions
- the present invention relates to the field of medicine, and more particularly to a technique for red blood cell recognition of Plasmodium infection. Background technique
- Plasmodium infection is a common infectious disease in many parts of the world, especially in Africa. Plasmodium enters the human blood circulation system through mosquito bites and multiplies and proliferates in red blood cells. Malaria often causes clinical symptoms such as fever and chills, and treatment may not be timely or may result in death. Malaria is a contagious disease that seriously threatens human health.
- the object of the present invention is to provide a method for identifying red blood cells infected by Plasmodium, which aims to solve the problem that the prior art scheme has poor recognition accuracy and low efficiency in red blood cell infection of Plasmodium infection.
- An aspect of the present invention provides a method for identifying a red blood cell infected by a Plasmodium, the method comprising: acquiring a forward scattered light signal and a side scattered light signal of a cell in a sample, and an optional fluorescent signal; Scattering the light signal and the side scattered light signal to obtain a first two-dimensional scattergram, or obtaining a three-dimensional scattergram based on the forward scattered light signal, the side scattered light signal, and the fluorescent signal;
- the present invention provides an apparatus for identifying a red blood cell infected with a Plasmodium, the apparatus comprising:
- a signal acquisition unit that acquires forward scattered light and side scattered light signals of the cells in the sample, and an optional fluorescent signal
- a graphics generating unit obtaining a first two-dimensional scattergram according to the forward scattered light signal and the side scatter light signal, or obtaining a three-dimensional scattergram according to the forward scattered light signal, the side scatter light signal, and the fluorescence signal;
- the recognition unit is configured to recognize, in the first two-dimensional scattergram or the three-dimensional scattergram, a fine monthly bag that is identified as a Plasmodium infection in a preset area.
- the present invention also provides a method for identifying a red blood cell infected by a Plasmodium, the method comprising:
- the present invention provides an apparatus for identifying a red blood cell infected by a Plasmodium, the apparatus comprising:
- a blood processing unit that processes the blood sample to obtain a processed blood sample
- a detecting unit detecting a scattered light signal of the cells in the processed blood sample
- the data processing unit obtains a scattergram according to the scattered light signal, and recognizes cells represented in the preset region in the scattergram as red blood cells infected by the malaria parasite.
- the sample is detected by flow analysis technology to obtain a scattergram, and then the malaria parasite is identified according to the region in which the cells in the scattergram are expressed.
- the program can be completed by automated instruments, and at the same time reduce the influence of human factors on the recognition accuracy, so it has the advantages of fast inspection and high recognition accuracy.
- the program analyzes and processes the cells of the whole blood sample, and detects The number of cells is large, and no missed diagnosis occurs because the number of red blood cells in the field of view is small, so that the recognition accuracy is further improved.
- FIG. 1 is a scatter diagram of a forward scattered light signal and a side scattered light signal of a normal blood sample provided by an embodiment of the present invention
- FIG. 2 is a scattergram of a forward scattered light signal and a side scattered light signal of a Plasmodium-infected blood sample provided by an embodiment of the present invention
- FIG. 3 is a flow chart of a method for identifying red blood cells infected by Plasmodium according to a specific embodiment of the present invention
- FIG. 4 is a structural diagram of an apparatus for identifying a red blood cell infected with Plasmodium according to a specific embodiment of the present invention
- FIG. 5 is a flow chart of a method for identifying red blood cells infected by Plasmodium according to another embodiment of the present invention.
- FIG. 6 is a structural diagram of an apparatus for identifying a red blood cell infected with Plasmodium according to another embodiment of the present invention.
- FIG. 7 is a structural diagram of a flow cytometer according to Embodiment 1 of the present invention.
- FIG. 8 is a three-dimensional scattergram of a blood sample of a Plasmodium infection according to a first embodiment of the present invention
- FIG. 9 is a three-dimensional scattergram of a normal blood sample according to Embodiment 1 of the present invention.
- FIG. 10 is a two-dimensional scatter combination diagram according to Embodiment 1 of the present invention.
- FIG. 1 For convenience of explanation, we provide a scatter plot of the forward scattered light signal and the side scattered light signal of a normal blood sample (Fig. 1); the forward scattered light signal and the side scattered light signal of the blood sample of Plasmodium infection The scatter plot is shown in Figure 2. In contrast to Figures 1 and 2, a population of red blood cells infected with Plasmodium occurs in a specific area.
- the average fluorescence intensity of Plasmodium-infected red blood cells is slightly smaller than that of normal red blood cells, in the three-dimensional white blood cell classification scatter plot (X-axis is the side-scattered light intensity, Y-axis is the forward scattered light intensity, Z-axis)
- the treatment of the underlying performance of the normal white blood cell population for fluorescence intensity After the experiment, the cell population clearly appeared in a specific region of the three-dimensional scattergram of the white blood cell classification, and it was verified that the cell population was red blood cells infected by the malaria parasite. Comparing Fig. 8 and Fig. 9, it can be seen that a red blood cell population infected with Plasmodium occurs in a specific region.
- the invention provides a method for identifying erythrocytes infected by Plasmodium, the method is completed by a flow analyzer, and the method is as shown in FIG. 3, comprising:
- 532 Detecting forward scattered light intensity and side scattered light intensity of the cells of the blood sample, and optionally fluorescence intensity; 533. Obtain a first scattergram of the blood sample, where the first scattergram is a two-dimensional scatterplot or a three-dimensional scatterplot;
- the sample is processed by flow cytometry to obtain a scattergram, and then the red blood cells infected by the malaria parasite are identified according to the region in which the cells in the scattergram are expressed.
- the automatic instrument is completed, so the method reduces the influence of human factors and improves the recognition precision, so it has the advantages of quick inspection and high recognition precision.
- the method analyzes and processes the cells of the whole blood sample, and the detection range is wide. , no missed diagnosis due to the number of red blood cells in the field of view, so it further improves the recognition accuracy.
- the reagent in the above S31 may be a hemolytic agent, and the present invention does not limit the specific component of the hemolytic agent, and the reagent only needs to dissolve normal red blood cells.
- the reagent comprises fluorescent labeling the cells.
- the dye, and a surfactant which partially breaks the leukocyte membrane is preferably a cationic surfactant, particularly a quaternary ammonium salt type surfactant.
- the ratio of the above hemolytic agent to the blood sample is not particularly limited.
- the volume ratio may be: 1:50; of course, other ratios such as 1:45 may be used, and the present invention is not limited to the specific range of the ratio.
- the optional fluorescence intensity in the method for implementing S32 indicates that the fluorescence intensity can be increased by the user according to the actual situation.
- the user can also choose not to increase the fluorescence intensity.
- the processed blood sample is subjected to irradiation analysis using a forward-scattering light signal, a side-scattered light signal, and a fluorescence signal of the flow analyzer to obtain a three-dimensional scattergram of the blood sample.
- the three-dimensional scattergram obtained by three kinds of signal irradiation analysis has a scattergram (two-dimensional) obtained by the forward scattered light intensity signal and the side scattered light intensity signal in S32, which can further improve the recognition accuracy of the red blood cells infected by the malaria parasite.
- the foregoing method may further include, after S34,: counting the Plasmodium infection in the scattergram The number of cells in the red blood cells, when the number of cells is greater than the first threshold, an alarm signal is issued.
- the above alarm conditions can also be other combined conditions, and an alarm signal is issued. Since the Plasmodium infection causes the blood test parameters of multiple red blood cell lines to be out of the normal range, it can be combined with the cell count result to increase the sensitivity of the alarm, and an alarm is issued at a lower cell number, that is, the second threshold. signal.
- the blood cell routine detection parameter is selected from: total number of red blood cells or hemoglobin concentration, ie, total number of red blood cells (Red Blood Cell count) , RBC) or Hemoglobin Concentration (HGB) or Mean Corpuscular Hemoglobin (MCH) or Mean Corpuscular Hemoglobin Concentration (MCHC) or Mean Corpuscular (Mean Corpuscular) Volume, MCV) or hematocrit (HCT).
- the threshold may be a specific value, and may be a ratio, for example, the ratio of the number of cells to the total number of cells.
- the foregoing method may further include:
- the second scattergram may specifically be: a second scattergram obtained from the side scattered light intensity and the fluorescence intensity of the cells, wherein the abnormality is an abnormal condition associated with the erythrocytes infected by the Plasmodium.
- the above abnormal situation may specifically be: counting the cell population in the high fluorescence region of the second scattergram.
- the counting of the high fluorescence region to the cell population means that in the signal processing, the signal intensity which can be recognized as a cell population appears in the high fluorescence region.
- the second scattergram appears as a high-fluorescence cell population above the monocyte region and the lymphocyte region.
- the invention also provides a device for identifying red blood cells infected by Plasmodium, which device can be specifically: a flow analyzer, and of course, the device can also be installed on other inspection devices, as shown in FIG. 4, including :
- a blood processing unit 41 processing the blood sample to obtain a processed blood sample
- the detecting unit 42 acquires a scattered light signal of the cells in the processed blood sample;
- the data processing unit 43 obtains a scattergram according to the scattered light signal, and recognizes the cells represented in the preset region in the scattergram as red blood cells infected by the malaria parasite.
- the apparatus performs the reagent treatment on the blood sample, and then processes the sample by flow cytometry to obtain a scattergram, and then recognizes the erythroid cells infected by the malaria parasite according to the region in which the cells in the scattergram are displayed, and the device is It is completed by an automated instrument, so the method reduces the influence of human factors and improves the recognition accuracy, so it has the advantages of quick inspection and high recognition precision.
- the device analyzes and processes the cells of the entire blood sample, and the scope of the test Wide, no missed diagnosis due to the number of red blood cells in the field of view, so it further improves the recognition accuracy.
- the detecting unit 42 also acquires a fluorescent signal of the blood sample cell.
- the foregoing apparatus may further include:
- Statistical alarm unit 44 counting the number of cells of the red blood cells infected by the malaria parasite
- the first alarm unit 45 when the number of cells is greater than the first threshold, sends an alarm signal.
- the foregoing apparatus further includes:
- Statistical alarm unit 44 counting the number of cells infected with erythrocytes by Plasmodium
- the data processing unit 43 further obtains a routine detection parameter of the red blood cell blood associated with the Plasmodium infection of the blood sample;
- the second alarm unit 46 sends an alarm signal when the number of cells is greater than a second threshold and the red blood cell blood routine detection parameter is not in the normal range.
- a second threshold is expressed in the same manner as the method embodiment.
- the blood detecting parameters of the above red blood cell system are specifically: total red blood cells or hemoglobin concentration.
- the foregoing apparatus may further include:
- Statistical alarm unit 44 counting the number of cells of the red blood cells infected by the malaria parasite
- the third alarm unit 47 obtains a second scattergram of the blood sample when the number of cells is greater than the second threshold; the second scattergram is: a region obtained by the side scattered light intensity and the fluorescence intensity of the blood sample cells The second scattergram is an alarm signal when the high fluorescing region of the second scattergram counts to the cell population.
- the invention further provides a method for identifying red blood cells infected by Plasmodium in a sample, which is shown in FIG. 5, and includes:
- the method provided by the present invention acquires a forward scattered light signal and a side scattered light signal of a sample, and an optional fluorescence signal to obtain a first two-dimensional scattergram or a three-dimensional scattergram, and then according to the cells in the scattergram.
- the region recognizes red blood cells infected by Plasmodium, and the method is completed by an automated instrument. Therefore, the method reduces the influence of human factors and improves the recognition accuracy, so it has the advantages of quick inspection and high recognition accuracy.
- the foregoing method may further include: after S53:
- the number of cells of the erythrocytes infected by the Plasmodium is counted, and an alarm signal is issued when the number of cells is greater than a first threshold.
- the foregoing method may further include: after S53:
- the blood test parameters of the above red blood cell system may specifically be: total number of red blood cells or hemoglobin concentration.
- the foregoing method may further include: after S53:
- the invention also provides an apparatus for identifying red blood cells infected by Plasmodium in a sample, which is shown in FIG. 6 and includes:
- a signal acquisition unit 61 which acquires forward scattered light and side scattered light signals of cells in the sample, and an optional fluorescent signal;
- the graphic generating unit 62 obtains a first two-dimensional scattering map according to the forward scattered light signal and the side scattered light signal, or obtains a three-dimensional scattering map according to the forward scattered light signal, the side scattered light signal, and the fluorescent signal;
- the identification unit 63 is configured to recognize the fine monthly bag in the first two-dimensional scattergram or the three-dimensional scattergram as a red moon bag infected by the malaria parasite in the preset area.
- the apparatus provided by the present invention acquires a forward scattered light signal and a side scattered light signal of a sample, and an optional fluorescent signal to obtain a first two-dimensional scattergram or a three-dimensional scattergram, and then according to the cells in the scattergram
- the region recognizes red blood cells infected by Plasmodium, and the device is completed by an automated instrument. Therefore, the device reduces the influence of human factors and improves the recognition accuracy, so it has the advantages of quick inspection and high recognition accuracy.
- the foregoing apparatus may further include:
- the statistical alarm unit 64 counts the number of cells of the red blood cells infected by the Plasmodium, and issues an alarm signal when the number of the cells is greater than the first threshold.
- the statistical alarm unit 64 is configured to count the number of cells of the red blood cell infected by the Plasmodium, and obtain a blood test routine parameter of the red blood cell line associated with the Plasmodium infection, wherein the number of the cells is greater than a second threshold. And when the blood cell routine detection parameter of the red blood cell system is not within the range of the normal value, an alarm signal is issued.
- the statistical alarm unit 64 is configured to count the number of cells in the preset area, and obtain a second two-dimensional scattergram according to the side scattered light signal and the fluorescence signal of the blood sample cell, where the second two-dimensional scatter The dot pattern shows a high fluorescent cell population, and an alarm signal is issued when the number of cells is greater than a second threshold.
- the preset area described herein may be a blood sample obtained by comparing a normal human blood sample with a Plasmodium infected patient, and after statistical analysis, a specific region in the scattergram is obtained. Input the parameters of the specific area into the recognition unit Get the preset area.
- the cells present in the predetermined region are recognized as red blood cells infected by the malaria parasite.
- a relative positional relationship function between the regions of the red blood cells infected with the Plasmodium and the normal white blood cell regions is obtained, and the function is input into the recognition unit.
- the preset area is determined based on the normal white blood cell area and the relative positional relationship function.
- the first threshold and the second threshold may be the number of red blood cells infected by the Plasmodium, or may be the percentage of the red blood cells infected by the Plasmodium compared to the normal red blood cells.
- the threshold may be preset or may be set by the user through a human-machine interaction interface.
- the present embodiment provides a method for identifying red blood cells infected by Plasmodium.
- the technical scenario implemented in this embodiment may be: The method provided in this embodiment is completed by a flow cytometer, and the analyzer may specifically use Shenzhen Mindray Biotechnology.
- the BC series flow cytometer produced by Medical Electronics Co., Ltd., the specific structure of the analyzer is shown in Figure 7.
- the formulation of the hemolytic agent can be: Reagent A, the reagent A can specifically include: Dye A (0.5ppm) , fluorenyl bromide isoquinoline (0.4g/L), dodecyl alcohol polyoxyethylene (23) ether (1.3g/L), sodium benzoate (2.0g/L), methanol (50g/L) , sodium dihydrogen phosphate (3 / L) and disodium hydrogen phosphate (4.8g / L).
- Dye A 0.5ppm
- fluorenyl bromide isoquinoline 0.4g/L
- dodecyl alcohol polyoxyethylene (23) ether 1.3g/L
- sodium benzoate 2.0g/L
- methanol 50g/L
- sodium dihydrogen phosphate 3 / L
- disodium hydrogen phosphate 4.8g / L
- the structural formula of dye A is as follows:
- the volume of the above reagent may be 1 ml, and the blood sample may be kept at a temperature of 25 ° C with fresh anticoagulant 20 ⁇ M.
- the method provided in this embodiment includes the following steps:
- the measurement angle was 90.
- the fluorescence intensity information of the blood sample cells after the lateral fluorescence measurement was measured, and the side scattered light intensity information of the blood sample cells after the treatment was measured by the side scattered light having a measurement angle of 90°, and the measurement angle 2 was used.
- the forward scattered light is used to measure the forward scattered light intensity information of the treated blood sample cells to obtain a three-dimensional scattergram (as shown in FIG. 8).
- Figure 8 is a three-dimensional scatter plot of a normal blood sample; the scatter in the red blood cell region of the Plasmodium infection in the three-dimensional scatter plot is identified as red blood cells infected by Plasmodium, when the number of infected red blood cells exceeds the alarm (ie When the first threshold is used, an alarm is generated; of course, the condition of the alarm may be other conditions, for example, when the infected red blood cells do not exceed the number of alarms, but the number is still large (ie, exceeds the second threshold) and the value of HGB or RBC is biased. An alarm is also generated when low (ie, below normal).
- the principle that white blood cells infected with blood samples by Plasmodium phagocytose malaria pigment can comprehensively recognize the red blood cells infected by Plasmodium, and comprehensively recognize the red blood cells infected by Plasmodium by multi-information, which is beneficial to improve the accuracy of Plasmodium identification.
- the white blood cell differential counting reagent disclosed in Chinese Application No. 200910177186.7 is also applicable to the method of the present invention, and can also recognize red blood cells infected by Plasmodium.
- the reagents include:
- a flower-cationic compound selected from the group consisting of the following formulae I and II:
- X is C(CH 3 ) 2 , 0, S or Se;
- R 4 is CMS alkyl, -Cw alkyl-OR 5 , benzyl or halogen, wherein the benzyl group is optionally substituted by a substituent selected from the group consisting of halogen, hydroxy, decyl, cyano, nitro, alkyl, aromatic , alkoxy, heterocyclic, haloalkyl, amino, alkylamino, acylamino, carboxy;
- R 5 is H or C 1-18 alkyl
- Y is an anion
- X is C(CH 3 ) 2 , 0, S or Se;
- R 2 ' and R 2 ' are each independently selected from H, OH, C 1-18 alkyl, C 1-6 alkyl OR 5 ', C 1-18 alkyl sulfonate, phenyl or halogen;
- R 3 ', R 4 ' are each independently selected from C 1-18 alkyl COOR 6 ', C 1-18 alkyl OR 6 ', benzyl, wherein the benzyl group is optionally substituted with a substituent selected from the group consisting of: halogen, a hydroxy group, a fluorenyl group, a cyano group, a nitro group, an alkyl group, an aryl group, an alkoxy group, a heterocyclic group, a halogenated alkyl group, an amino group, an alkylamino group, an acylamino group, a carboxyl group, under the condition that 'and R 4 are not a benzyl group, And 'when benzyl is R 4 ' is not C 1-18 alkyl OR 6 ';
- R 5 ' is C 1-18 alkyl or H
- R 6 ' is C M8 alkyl, H or phenyl, wherein phenyl is optionally substituted by a substituent selected from the group consisting of halogen, hydroxy, decyl, cyano, nitro, alkyl, aryl, alkoxy, Heterocyclic group, haloalkyl group, amino group, alkylamino group, acylamino group, carboxyl group;
- Y- is a negative ion
- a cationic surfactant which is a quinoline salt type cationic surfactant of the formula: and/or IV:
- R 3 to R 16 are each independently selected from the group consisting of H, OH, d- 4 alkyl, C M alkoxy, and sulfonic acid;
- a ( 14 alkyl or Cw 4 alkenyl group preferably a linear alkyl group of a self group, an octyl group, a decyl group, a lauryl group or a tetradecyl group, particularly preferably selected from an octyl group, a decyl group, a lauryl group or a linear alkyl group of tetradecyl;
- R 3 is ( ⁇ 4 alkyl or C 24 alkenyl, preferably methyl, ethyl, propyl, butyl or butenyl, particularly preferably methyl, ethyl or propyl;
- R 4 is d 4 alkyl or C 2 4 alkenyl or benzyl, preferably methyl, ethyl, propyl, butyl, butenyl or benzyl, particularly preferably methyl, ethyl or propyl;
- the reagent may also contain at least one anionic compound selected from the group consisting of one or more carboxyl groups or sulfonic acid groups.
- a compound having the structure of formula II is selected from
- the disclosed apparatus and method can be Implemented in other ways.
- the device embodiments described above are merely illustrative.
- the division of the unit is only a logical function division.
- there may be another division manner for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not executed.
- the components displayed by the unit may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
- each functional unit in the embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
- the functions, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium.
- the technical solution of the present invention which is essential or contributes to the prior art, or a part of the technical solution, may be embodied in the form of a software product, which is stored in a storage medium, including
- the instructions are used to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention.
- the foregoing storage medium includes: a U disk, a removable hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and the like, which can store program codes. .
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Immunology (AREA)
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Hematology (AREA)
- Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Pathology (AREA)
- Molecular Biology (AREA)
- Biomedical Technology (AREA)
- Urology & Nephrology (AREA)
- Cell Biology (AREA)
- Microbiology (AREA)
- Biotechnology (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Tropical Medicine & Parasitology (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Virology (AREA)
- Physiology (AREA)
- Ecology (AREA)
- Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
一种疟原虫感染的红细胞的识别方法，其包括：获取样本中细胞的前向散射光信号和侧向散射光信号，和任选的荧光信号；根据前向散射光信号和侧向散射光信号得到第一二维散点图，或基于前向散射光信号、侧向散射光信号和荧光信号得到三维散点图；将第一二维散点图或三维散点图中表现在预设区域内细胞识别为疟原虫感染的红细胞。还提供了一种疟原虫感染的红细胞的识别装置。上述方法和装置具有识别精度高的优点。
Description
发明名称： 疟原虫感染的红细胞的识别方法及装置 技术领域 本发明属于医疗领域， 尤其涉及疟原虫感染的红细胞识别的技术。 背景技术
疟原虫感染是全球许多地区特别是非洲地区的一种常见传染性疾病。 疟原 虫通过蚊虫叮咬进入人体血液循环系统， 在红细胞内进行繁殖和增生。 疟疾常 会导致发热、 畏寒等临床症状， 治疗不及时甚至可能导致死亡。 疟疾是严重威 胁人类健康的传染性疾病。
当前诊断疟疾需要综合病史、 旅行史、 临床症状和镜检结果， 而疟原虫感 染的红细胞的识别对疟疾的识别起到关键的作用， 现有的疟原虫的识别方法通 过对病人作细胞形态学检查来确定疟原虫感染的红细胞， 但是现有的血细胞形 态学检查釆用的薄膜涂片方式， 单个视野内红细胞数目较少， 容易漏诊， 导致 疟原虫感染的红细胞识别准确度差， 并且人为检测由于人员水平的不同也会出 现准确度差， 效率低的问题。 发明内容
本发明实施例的目的在于提供一种疟原虫感染的红细胞的识别方法， 旨在 解决现有的技术方案在疟原虫感染的红细胞识别精度差， 效率低的问题。
本发明一方面提供一种疟原虫感染的红细胞的识别方法， 所述方法包括： 获取样本中细胞的前向散射光信号和侧向散射光信号， 和任选的荧光信号； 根据所述前向散射光信号和侧向散射光信号得到第一二维散点图， 或基于 所述前向散射光信号、 侧向散射光信号和荧光信号得到三维散点图；
将所述第一二维散点图或三维散点图中表现在预设区域内细胞识别为疟原
虫感染的红细胞。
另一方面， 本发明还提供一种疟原虫感染的红细胞的识别装置， 所述装置 包括：
信号获取单元， 获取样本中细胞的前向散射光和侧向散射光信号， 和任选 的荧光信号；
图形生成单元， 根据所述前向散射光信号和侧向散射光信号得到第一二维 散射图， 或根据所述前向散射光信号、 侧向散射光信号和荧光信号得到三维散 射图；
识别单元， 将在所述第一二维散点图或三维散点图中表现在预设区域内细 月包识别为疟原虫感染的红细月包。
下一方面， 本发明还提供一种疟原虫感染的红细胞的识别方法， 所述方法 包括：
使用试剂处理血液样本；
控制处理后的所述血液样本通过流式细胞仪的检测区；
检测获得所述血液样本的细胞的前向散射光强度和侧向散射光强度， 和任 选的荧光强度；
得到所述血液样本的第一散点图， 所述第一散点图为二维散点图或三维散 点图；
将所述第一散点图中表现在预设区域的细胞识别成疟原虫感染的红细胞。 又一方面， 本发明还提供一种疟原虫感染的红细胞的识别装置， 所述装置 包括：
血液处理单元， 对血液样本进行处理， 得到处理后的血样；
检测单元， 检测获得处理后的血样中细胞的散射光信号；
数据处理单元， 根据所述散射光信号得到散点图， 将所述散点图中表现在 预设区域的细胞识别成疟原虫感染的红细胞。
上述技术方案通过对该血液样本进行试剂处理后， 釆用流式分析技术对该 样本进行检测， 得到散点图， 然后根据散点图中细胞表现在的区域识别疟原虫
感染的红细胞， 该方案可以有自动化仪器完成， 同时减少了人为因素对识别精 度的影响， 所以具有检验快， 识别精度高的优点， 另外， 该方案对整个血液样 本的细胞进行分析处理， 检测的细胞数量多， 不会因为视野内红细胞数目较少 而发生漏诊， 所以其进一步提高了识别精度。 附图说明
图 1 是本发明具体实施方式提供的正常血液样本的前向散射光信号和侧向 散射光信号的散点图；
图 2是本发明具体实施方式提供的疟原虫感染血液样本的前向散射光信号 和侧向散射光信号的散点图；
图 3 是本发明具体实施方式提供的一种疟原虫感染的红细胞的识别方法的 流程图；
图 4是本发明具体实施方式提供的一种疟原虫感染的红细胞的识别装置的 结构图；
图 5 为本发明另一个具体实施方式提供的一种疟原虫感染的红细胞的识别 方法的流程图；
图 6为本发明另一个具体实施方式提供的一种疟原虫感染的红细胞的识别 装置的结构图；
图 7是本发明实施例一提供的流式细胞分析仪的结构图；
图 8是本发明实施例一提供的疟原虫感染血液样本的三维散点图； 图 9是本发明实施例一提供的正常血液样本的三维散点图；
图 10是本发明实施例一提供的二维散点组合图。
需要额外说明的是， 上述图 1、 图 2、 图 8、 图 9、 图 10中的一个黑点表示 一个细胞， 椭圆表现一个细胞种类的区域。 具体实施方式
为了使本发明的目的、 技术方案及优点更加清楚明白， 以下结合附图及实
施例， 对本发明进行进一步详细说明。 应当理解， 此处所描述的具体实施例仅 仅用以解释本发明， 并不用于限定本发明。
为了能够快速准确地筛选出疟原虫感染的血液样本， 需要一种新的自动化 的方法实现疟原虫感染的红细胞的识另 'J。
我们经过研究发现， 疟原虫感染病人的血液样本中的感染红细胞在细胞膜 性质和内部形态性质方面， 与正常的红细胞不同， 而与正常的白细胞有某些性 质上的类似， 有可能在白细胞分类的同时把疟原虫感染的红细胞识别出来。 由 于疟原虫感染的红细胞相比正常白细胞平均体积略小， 相比正常白细胞平均的 细胞内复杂程度略大， 有可能在白细胞分类散点图 （X轴为侧向散射光强度， Y 轴为前向散射光强度） 的正常白细胞群的右下方表现出来。 经过反复的实验， 通过对其血液样本的散射光信号进行处理和分析， 我们发现在根据前向散射光 信号和侧向散射光信号得到的散点图中， 特定区域稳定地出现细胞群， 经过研 究确认该细胞群为疟原虫感染的红细胞。
为了方便说明， 我们提供了正常血液样本的前向散射光信号和侧向散射光 信号的散点图 （如图 1 )； 疟原虫感染血液样本的前向散射光信号和侧向散射光 信号的散点图如图 2所示， 对比图 1和图 2, 在特定的区域出现疟原虫感染的红 细胞群。
此外， 我们还发现， 疟原虫感染的红细胞比正常红细胞的平均荧光强度略 小， 在三维的白细胞分类散点图 （X轴为侧向散射光强度， Y轴为前向散射光 强度， Z轴为荧光强度）的正常白细胞群的下方表现处理。 经过试验， 在白细胞 分类的三维散点图的特定区域清晰地出现细胞群， 经过验证该细胞群为疟原虫 感染的红细胞。对比图 8和图 9,可见在特定的区域出现疟原虫感染的红细胞群。
本发明提供的一种疟原虫感染的红细胞的识别方法， 该方法由流式分析仪 完成， 该方法如图 3所示， 包括：
531、 使用试剂处理血液样本；
532、 检测所述血液样本的细胞的前向散射光强度和侧向散射光强度， 和任 选的荧光强度；
533、 得到所述血液样本的第一散点图， 所述第一散点图为二维散点图或三 维散点图；
534、 将所述第一散点图中表现在预设区域的细胞识别成疟原虫感染的红细 胞。
本发明提供的方法对该血液样本进行处理后， 采用流式细胞技术对该样本 进行处理得到散点图， 然后根据散点图中细胞表现在的区域识别疟原虫感染的 红细胞， 该方法均由自动化仪器完成， 所以该方法减少了人为因素的影响， 提 高了识别精度， 所以其具有检验快， 识别精度高的优点， 另外， 该方法对整个 血液样本的细胞进行分析处理， 其检验的范围广， 不会因为视野内红细胞数目 而发生漏诊， 所以其进一步提高了识别精度。
需要说明的是， 上述 S31 中的试剂可以为溶血剂， 本发明并不限定该溶血 剂的具体组分， 只需该试剂能够溶解正常的红细胞即可， 优选， 试剂包含对细 胞进行标记的荧光染料， 和使白细胞膜发生部分破损的表面活性剂， 该表面活 性剂优选阳离子表面活性剂， 特别是季铵盐型的表面活性剂。 另外， 上述溶血 剂与血液样本的比例也无特殊要求， 例如体积比可以为： 1 :50; 当然也可以为其 他的比例， 例如 1 :45等， 本发明并不限制该比例的具体范围。
可选的， 实现 S32 的方法中的任选的荧光强度表示该荧光强度可以由用户 根据实际情况自行增加， 当然在实际情况中， 用户也可以选择不增加荧光强度。 另外， 当用户选择增加荧光强度时， 使用流式分析仪的前向散射光信号、 侧向 散射光信号和荧光信号对处理后的血液样本进行照射分析得到该血液样本的三 维散点图。 采用三种信号照射分析得到的三维散点图比 S32 中的前向散射光强 度信号和侧向散射光强度信号得到的散点图 （二维） 能进一步提高疟原虫感染 的红细胞的识别精度。
统计所述疟原虫感染的红细胞的细胞数量， 获取所述血液样本的与疟原虫 感染相关的红细胞系血常规检测参数， 在所述细胞数量大于第二阈值且所述红 细胞系血常规检测参数不在正常范围时， 发出报警信号。
可选的， 上述方法在 S34之后还可以包括： 统计上述散点图中疟原虫感染
的红细胞的细胞数量， 在细胞数量大于第一阈值时， 发出报警信号。 当然上述 报警的条件还可以为其他组合条件， 发出报警信号。 由于疟原虫感染会导致多 个红细胞系血常规检测参数不在正常值的范围之内， 可以利用其结合细胞计数 结果， 提高报警的灵敏度， 在较低细胞数量， 也就是第二个阈值时发出报警信 号。 例如， 在细胞数量大于第二阈值且该红细胞系血常规检测参数不在正常范 围时， 发出报警信号； 该红细胞系血常规检测参数选自： 红细胞总数或血红蛋 白浓度， 即红细胞总数（Red Blood Cell count , RBC ) 或血红蛋白浓度 ( Hemoglobin Concentration , HGB ) 或平均红细月包血红蛋白含量 ( Mean Corpuscular Hemoglobin , MCH )或平均红细月包血红蛋白浓度 (Mean Corpuscular Hemoglobin Concentration, MCHC)或平均红细胞体积 ( Mean Corpuscular Volume , MCV )或红细胞压积 （Hematocrit , HCT ) 。 需要说明是， 上述阈值具 体可以为一个确定的数值， 当然也可以为一个比值， 例如上述细胞数量与细胞 总数量的比值数。
可选的， 上述方法在 S34之后， 还可以包括：
统计疟原虫感染的红细胞的细胞数量， 在细胞数量大于第二阈值时， 获取 血液样本的第二散点图， 在第二散点图出现异常情况时， 发起报警信号；
上述第二散点图具体可以为： 由细胞的侧向散射光强度和荧光强度得到的 第二散点图， 上述异常情况为与疟原虫感染的红细胞相关的异常情况。
上述异常情况具体可以为： 在第二散点图的高荧光区域计数到细胞群。 该 高荧光区域计数到细胞群是指在信号处理中， 在高荧光区域出现可以识别为细 胞群的信号强度。 实际情况例如第二散点图出现单核细胞区域和淋巴细胞区域 的上方出现高荧细胞群。
本发明还提供的一种疟原虫感染的红细胞的识别装置， 该装置具体可以为： 流式分析仪完成， 当然该装置也可以安装在其他的检验设备上， 该装置如图 4 所示， 包括：
血液处理单元 41 , 对血液样本进行处理， 得到处理后的血样；
检测单元 42 , 获取处理后的血样中细胞的散射光信号；
数据处理单元 43 , 根据所述散射光信号得到散点图， 将所述散点图中表现 在预设区域的细胞识别成疟原虫感染的红细胞。
本发明提供的装置对该血液样本进行试剂处理后， 采用流式细胞技术对该 样本进行处理得到散点图， 然后根据散点图中细胞表现在的区域识别疟原虫感 染的红细胞， 该装置均由自动化仪器完成， 所以该方法减少了人为因素的影响， 提高了识别精度， 所以其具有检验快， 识别精度高的优点， 另外， 该装置对整 个血液样本的细胞进行分析处理， 其检验的范围广， 不会因为视野内红细胞数 目而发生漏诊， 所以其进一步提高了识别精度。
可选的， 检测单元 42还获取该血液样本细胞的荧光信号。
可选的， 上述装置还可以包括：
统计报警单元 44, 统计疟原虫感染的红细胞的细胞数量；
第一报警单元 45 , 在所述细胞数量大于第一阈值时， 发出报警信号。
可选的， 上述装置还包括：
统计报警单元 44, 统计疟原虫感染红细胞的细胞数量；
数据处理单元 43 , 还得到所述血液样本与疟原虫感染相关的红细胞系血常 规检测参数；
第二报警单元 46, 在所述细胞数量大于第二阈值且所述红细胞系血常规检 测参数不在正常范围时， 发出报警信号。 另外， 需要说明的是， 上述阈值的表 现形式与方法实施例相同。
可选的， 上述红细胞系血常规检测参数具体为： 红细胞总数或血红蛋白浓 度。
可选的， 上述装置还可以包括：
统计报警单元 44, 统计疟原虫感染的红细胞的细胞数量，
第三报警单元 47, 在所述细胞数量大于第二阈值时， 获取血液样本的第二 散点图； 第二散点图为： 由血液样本细胞的侧向散射光强度和荧光强度得到的 所述第二散点图， 在第二散点图高荧光区域计数到细胞群时， 发出报警信号。
上述试剂的说明可以参见方法实施例的说明， 这里不在赘述。
本发明又提供一种样本中疟原虫感染的红细胞的识别方法， 该方法如图 5 所示， 包括：
551、 获取样本中细胞的前向散射光信号和侧向散射光信号， 和任选的荧光 信号；
552、 根据所述前向散射光信号和侧向散射光信号得到第一二维散射图， 或 基于所述前向散射光信号、 侧向散射光信号和荧光信号得到三维散射图；
553、 将所述第一二维散点图或三维散点图中表现在预设区域内细胞识别为 疟原虫感染的红细胞。
本发明提供的方法获取样本的前向散射光信号和侧向散射光信号， 和任选 的荧光信号得到第一二维散点图或三维散点图， 然后根据散点图中细胞表现在 的区域识别疟原虫感染的红细胞， 该方法均由自动化仪器完成， 所以该方法减 少了人为因素的影响， 提高了识别精度， 所以其具有检验快， 识别精度高的优 点。
可选的， 上述方法在 S53之后还可以包括：
统计所述疟原虫感染的红细胞的细胞数量， 在所述细胞数量大于第一阈值 时， 发出报警信号。
可选的， 上述方法在 S53之后还可以包括：
统计所述疟原虫感染的红细胞的细胞数量， 获取所述样本的与疟原虫感染 相关的红细胞系血常规检测参数， 在所述细胞数量大于第二阈值， 且所述红细 胞系血常规检测参数不在正常范围内时， 发出报警信号。
需要说明的是， 上述红细胞系血常规检测参数具体可以为： 红细胞总数或 血红蛋白浓度。
可选的， 上述方法在 S53之后还可以包括：
统计所述疟原虫感染的红细胞的细胞数量， 根据侧向散射光信号和荧光信 号得到第二二维散点图， 在所述第二二维散点图出现高荧光细胞群， 且在所述 细胞个数大于第二阈值时， 发出报警信号。
需要说明的是， 上述阈值的具体表现形式可以参见方法实施例的表述， 另
外， 上述高荧光细胞群的定义也可以参见方法实施例的表述。
本发明还提供一种样本中疟原虫感染的红细胞的识别装置， 该装置如图 6 所示， 包括：
信号获取单元 61 , 获取样本中细胞的前向散射光和侧向散射光信号， 和任 选的荧光信号；
图形生成单元 62, 根据所述前向散射光信号和侧向散射光信号得到第一二 维散射图， 或根据所述前向散射光信号、 侧向散射光信号和荧光信号得到三维 散射图；
识别单元 63 , 将在所述第一二维散点图或三维散点图中表现在预设区域内 细月包识别为疟原虫感染的红细月包。
本发明提供的装置获取样本的前向散射光信号和侧向散射光信号， 和任选 的荧光信号得到第一二维散点图或三维散点图， 然后根据散点图中细胞表现在 的区域识别疟原虫感染的红细胞， 该装置均由自动化仪器完成， 所以该装置减 少了人为因素的影响， 提高了识别精度， 所以其具有检验快， 识别精度高的优 点。
可选的， 上述装置还可以包括：
统计报警单元 64, 统计所述疟原虫感染的红细胞的细胞数量， 在所述细胞 数量大于第一阈值时， 发出报警信号。
可选的， 上述统计报警单元 64, 统计所述疟原虫感染的红细胞的细胞数量， 还获取该血液样本的与疟原虫感染相关的红细胞系血常规检测参数， 在所述细 胞数量大于第二阈值， 且所述红细胞系血常规检测参数不在正常值的范围内时， 发出报警信号。
可选的， 上述统计报警单元 64, 统计预设区域内的细胞数量， 还根据血液 样本细胞的侧向散射光信号和荧光信号得到第二二维散点图， 在所述第二二维 散点图出现高荧光细胞群， 且在所述细胞数量大于第二阈值时， 发出报警信号。
本文所述预设区域， 可以是经过对比正常人血样和疟原虫感染病人的血样， 统计分析后， 得到在散点图中的特定区域。 将该特定区域的参数输入识别单元
得到预设区域。 在未知血样散点图中， 表现在该预设区域中的细胞识别为疟原 虫感染的红细胞。 或者， 是经过对比正常人血样和疟原虫感染病人的血样， 统 计分析后， 得到疟原虫感染的红细胞的区域与正常白细胞区域的相对位置关系 函数， 将该函数输入识别单元。 在未知血样散点图中， 根据正常白细胞区域， 以及该相对位置关系函数， 确定预设区域。
本文中， 第一阈值和第二阈值可以是疟原虫感染的红细胞的个数， 也可以 是疟原虫感染红细胞相比正常红细胞的百分比。 该阈值可以是预先设定好的， 也可以由用户通过人机互动界面设定。
实施例一
本实施例提供一种疟原虫感染的红细胞的识别方法， 本实施例实现的技术 场景具体可以为： 本实施例提供的方法由流式细胞分析仪完成， 该分析仪具体 可以釆用深圳迈瑞生物医疗电子股份有限公司生产的 BC系列流式细胞分析仪， 该分析仪的具体结构如图 7所示， 该溶血剂的配方可以为： 试剂 A, 该试剂 A具 体可以包括： 染料 A ( 0.5ppm ) 、 癸基溴化异喹啉 ( 0.4g/L ) 、 十二烷基醇聚氧 乙烯（23 ) 醚（ 1.3g/L ) 、 苯甲酸钠 （2.0g/L ) 、 甲醇 （ 50g/L ) 、 磷酸二氢钠 ( 3 /L )和磷酸氢二钠 （4.8g/L ) 。 其中染料 A的结构式如下所示：
另外， 上述试剂的体积可以为 lml, 上述血液样本釆用新鲜抗凝血 20 μ ΐ, 温 度可以保持在 25 °C。 本实施例提供的方法包括下述步骤：
对血液样本进行试剂 A处理后，釆用测定角度为 90。 的侧向荧光测定处理后 的血液样本细胞的荧光强度信息， 釆用测定角度为 90° 的侧向散射光测定处理 后的血液样本细胞的侧向散射光强度信息， 釆用测定角度 2。 —5。 的前向散射 光测定处理后的血液样本细胞的前向散射光强度信息得到三维散点图 （如图 8所
示） ， 图 8为正常血液样本的三维散点图； 在三维散点图中出现在疟原虫感染的 红细胞区域的散点识别为疟原虫感染的红细胞， 当感染红细胞超过报警的个数 (即第一阈值时） ， 产生报警； 当然报警的条件还可以为其他条件， 例如当感 染红细胞未超过报警的个数， 但是个数还是较多 （即超过第二阈值）且 HGB或 RBC的值偏低（即低于正常水平时） 时， 也产生报警。 当然在实际情况中还可 以为其他方式， 例如， 在前向散射光和侧向散射光的二维散点图 （如图 10所示） 中疟原虫感染的红细胞个数较多 （即大于第二阈值）且侧向散射光和荧光的二 维散点图 （如图 10所示） 的单核细胞区域和淋巴细胞区域的上方出现高荧细胞 群时， 也产生报警。 此种情况是利用疟原虫感染血液样本的白细胞会吞噬疟色 素的原理来综合识别疟原虫感染的红细胞， 通过多信息的综合识别疟原虫感染 的红细胞， 有利于提高疟原虫识别的精度。
中国申请 200910177186.7中公开的白细胞分类计数试剂，也适用本发明的方 法， 也可以识别疟原虫感染的红细胞。 所述试剂包括：
(1) 选自如下通式 I和 II的花 类阳离子化合物：
其中
11为 1、 2或 3;
X为 C(CH3)2、 0、 S或 Se;
和 各自独立选自 H、 C1-18烷基、 -C1-6烷基 -OR5或卤素；
为11、 1-18烷基、 OR5、 -C1-6烷基 -OR5、 COOR5、 N02、 CN或卤素;
R4为 CMS烷基、 -Cw烷基 -OR5、 苄基或卤素， 其中苄基由选自以下的取代基 任选取代： 卤素、 羟基、 巯基、 氰基、 硝基、 烷基、 芳基、 烷氧基、 杂环基、 卤代烷基、 氨基、 烷基氨基、 酰氨基、 羧基；
R5为 H或 C1-18烷基；
Y—为负离子；
或者
II
其中
11为 1、 2或 3 ;
X为 C(CH3)2、 0、 S或 Se;
'和 R2'各自独立选自 H、 OH、 C1-18烷基、 C1-6烷基 OR5'、 C1-18烷基磺酸基、 苯基或卤素；
R3'、 R4'各自独立选自 C1-18烷基 COOR6'、 C1-18烷基 OR6'、 苄基， 其中苄基由 选自以下的取代基任选取代： 卤素、 羟基、 巯基、 氰基、 硝基、 烷基、 芳基、 烷氧基、 杂环基、 卤代烷基、 氨基、 烷基氨基、 酰氨基、 羧基， 条件是 '和 R4 不同时为苄基， 且 '为苄基时 R4'不为 C1-18烷基 OR6';
R5'为 C1-18烷基或者 H;
R6'为 CM8烷基、 H或者苯基，其中苯基由选自以下的取代基任选取代： 卤素、 羟基、 巯基、 氰基、 硝基、 烷基、 芳基、 烷氧基、 杂环基、 卤代烷基、 氨基、 烷基氨基、 酰氨基、 羧基；
Y-为负离子；
(2) 阳离子表面活性剂， 所述阳离子表面活性剂为通式 ΠΙ和 /或 IV的喹啉 盐型阳离子表面活性剂：
m
IV 和 分别独立选自 C6 - 18烷基和 C6 - 18卤代烷基；
R3 ~ R16分别独立选自 H、 OH、 d -4烷基、 CM烷氧基和磺酸基；
Z—为卤素离子；
和 /或
通式 V的季铵盐型阳离子表面活性剂，
, I \
( Ri― N+― R4 ) Z-
I
R3 v
其中
为(^14烷基或 Cw4链烯基， 优选选自己基、 辛基、 癸基、 月桂基或十四烷基的 直链烷基， 特别优选选自辛基、 癸基、 月桂基或十四烷基的直链烷基；
为(^4烷基或 C24链烯基， 优选甲基、 乙基、 丙基、 丁基或丁烯基， 特别优选 甲基、 乙基或丙基；
R3为 (^4烷基或 C24链烯基， 优选甲基、 乙基、 丙基、 丁基或丁烯基， 特别优选 甲基、 乙基或丙基；
R4为 d_4烷基或 C2_4链烯基或苄基， 优选甲基、 乙基、 丙基、 丁基、 丁烯基或苄 基， 特别优选甲基、 乙基或丙基；
Z—为卤素离子；
(3) 至少一种非离子表面活性剂。
试剂还可以含有至少一种选自带有一个或多个羧基或磺酸基的阴离子化合 物。
具有通式 I结构的化合物选 ：
具有通式 II结构的化合物选自
该申请的内容援引加入本发明， 具体试剂的成分和配制方法参见该申请内 容， 本文不作赘述。 本领域普通技术人员可以意识到， 结合本文中所公开的实施例描述的各示 例的单元及算法步骤， 能够以电子硬件、 或者计算机软件和电子硬件的结合来 实现。 这些功能究竟以硬件还是软件方式来执行， 取决于技术方案的特定应用 和设计约束条件。 专业技术人员可以对每个特定的应用来使用不同方法来实现 所描述的功能， 但是这种实现不应认为超出本发明的范围。
所属领域的技术人员可以清楚地了解到， 为描述的方便和筒洁， 上述描述 的系统、 装置和单元的具体工作过程， 可以参考前述方法实施例中的对应过程, 在此不再赘述。
在本申请所提供的实施例中， 应该理解到， 所揭露的装置和方法， 可以通
过其它的方式实现。 例如， 以上所描述的装置实施例仅仅是示意性的， 例如， 所述单元的划分， 仅仅为一种逻辑功能划分， 实际实现时可以有另外的划分方 式， 例如多个单元或组件可以结合或者可以集成到另一个系统， 或一些特征可 以忽略， 或不执行。 单元显示的部件可以是或者也可以不是物理单元， 即可以位于一个地方， 或者 也可以分布到多个网络单元上。 可以根据实际的需要选择其中的部分或者全部 单元来实现本实施例方案的目的。
另外， 在本发明实施例中的各功能单元可以集成在一个处理单元中， 也可 以是各个单元单独物理存在， 也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用 时， 可以存储在一个计算机可读取存储介质中。 基于这样的理解， 本发明的技 术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以 软件产品的形式体现出来， 该计算机软件产品存储在一个存储介质中， 包括若 干指令用以使得一台计算机设备（可以是个人计算机， 服务器， 或者网络设备 等）执行本发明各个实施例所述方法的全部或部分步骤。 而前述的存储介质包 括： U盘、 移动硬盘、 只读存储器 （ROM, Read-Only Memory ) 、 随机存取存 储器（RAM, Random Access Memory ) 、 磁碟或者光盘等各种可以存储程序代 码的介质。
以上所述仅为本发明的较佳实施例而已， 并不用以限制本发明， 凡在本发 明的原则之内所作的任何修改、 等同替换和改进等， 均应包含在本发明的保护 范围之内。
Claims
1、 一种疟原虫感染的红细胞的识别方法， 其特征在于， 所述方法包括： 获取样本中细胞的前向散射光信号和侧向散射光信号， 和任选的荧光信号； 根据所述前向散射光信号和侧向散射光信号得到第一二维散点图， 或基于 所述前向散射光信号、 侧向散射光信号和荧光信号得到三维散点图；
将所述第一二维散点图或三维散点图中表现在预设区域内细胞识别为疟原 虫感染的红细胞。
2、 根据权利要求 1所述的方法， 其特征在于， 所述方法还包括：
统计所述疟原虫感染的红细胞的细胞数量， 在所述细胞数量大于第一阈值 时， 发出报警信号。
3、 根据权利要求 1所述的方法， 其特征在于， 所述方法还包括：
统计所述疟原虫感染的红细胞的细胞数量， 获取所述样本的与疟原虫感染 相关的红细胞系血常规检测参数， 在所述细胞数量大于第二阈值， 且所述红细 胞系血常规检测参数不在正常范围内， 发出报警信号。
4、 根据权利要求 3所述的方法， 其特征在于， 所述红细胞系血常规检测参 数选自红细胞总数或血红蛋白浓度或平均红细胞血红蛋白含量或平均红细胞血 红蛋白浓度或平均红细 体积或红细 压积。
5、 根据权利要求 1所述的方法， 其特征在于， 所述方法还包括：
统计所述疟原虫感染的红细胞的细胞数量；
根据侧向散射光信号和荧光信号得到第二二维散点图， 在所述第二二维散 点图出现高荧光细胞群， 且在所述细胞数量大于第二阈值时， 发出报警信号。
6、 一种疟原虫感染的红细胞的识别装置， 其特征在于， 所述装置包括： 信号获取单元， 获取样本中细胞的前向散射光和侧向散射光信号， 和任选 的荧光信号；
图形生成单元， 根据所述前向散射光信号和侧向散射光信号得到第一二维 散射图， 或根据所述前向散射光信号、 侧向散射光信号和荧光信号得到三维散
射图；
识别单元， 将在所述第一二维散点图或三维散点图中表现在预设区域内细 月包识别为疟原虫感染的红细月包。
7、 根据权利要求 6所述的装置， 其特征在于， 所述装置还包括： 统计报警单元， 统计所述疟原虫感染的红细胞的细胞数量， 在所述细胞数 量大于第一阈值时， 发出报警信号。
8、 根据权利要求 6所述的装置， 其特征在于， 所述装置还包括： 统计报警单元， 统计所述疟原虫感染的红细胞的细胞数量， 获取该血液样 本的与疟原虫感染相关的红细胞系血常规检测参数， 在所述细胞数量大于第二 阈值， 且所述红细胞系血常规检测参数不在正常范围时， 发出报警信号。
9、 根据权利要求 6所述的装置， 其特征在于， 所述装置还包括： 统计报警单元， 统计预设区域内的细胞数量；
根据血液样本细胞的侧向散射光信号和荧光信号得到第二二维散点图， 在 所述第二二维散点图出现高荧光细胞群， 且在所述细胞个数大于第二阈值时， 发出报警信号。
10、 一种疟原虫感染的红细胞的识别方法， 其特征在于， 所述方法包括： 使用试剂处理血液样本；
控制处理后的所述血液样本通过流式细胞仪的检测区；
检测获得所述血液样本的细胞的前向散射光强度和侧向散射光强度， 和任 选的荧光强度；
得到所述血液样本的第一散点图， 所述第一散点图为二维散点图或三维散 点图；
将所述第一散点图中表现在预设区域的细胞识别成疟原虫感染的红细胞。
11、 根据权利要求 10所述的方法， 其特征在于， 所述方法还包括： 统计所述疟原虫感染的红细胞的细胞数量， 在所述细胞数量大于第一阈值 时， 发出报警信号。
12、 根据权利要求 10所述的方法， 其特征在于， 所述方法还包括：
统计所述疟原虫感染的红细胞的细胞数量；
获取所述血液样本的与疟原虫感染相关的红细胞系血常规检测参数， 在所 述细胞数量大于第二阈值且所述红细胞系血常规检测参数不在正常范围时， 发 出报警信号， 其中所述第二阈值小于所述第一阈值。
13、 根据权利要求 10所述的方法， 其特征在于， 所述方法还包括： 统计疟原虫感染的红细胞的细胞数量；
获取所述血液样本的第二散点图， 在所述细胞数量大于第二阈值且所述第 二散点图出现异常情况时， 发出报警信号；
所述第二散点图具体为： 由细胞的侧向散射光强度和荧光强度得到的所述 第二散点图， 所述异常情况为与疟原虫感染的红细胞相关的异常情况。
14、 根据权利要求 13所述的方法， 其特征在于， 所述异常情况具体为： 在所述第二散点图的高荧光区域计数到细胞群。
15、 一种疟原虫感染的红细胞的识别装置， 其特征在于， 所述装置包括： 血液处理单元， 对血液样本进行处理， 得到处理后的血样；
检测单元， 检测获得处理后的血样中细胞的散射光信号；
数据处理单元， 根据所述散射光信号得到散点图， 将所述散点图中表现在 预设区域的细胞识别成疟原虫感染的红细胞。
16、 根据权利要求 15所述的装置， 其特征在于， 所述检测单元还获取所述 血液样本细胞的荧光信号。
17、 根据权利要求 15所述的装置， 其特征在于， 所述装置还包括： 统计报警单元， 统计疟原虫感染的红细胞的细胞数量；
第一报警单元， 在所述细胞数量大于第一阈值时， 发出报警信号。
18、 根据权利要求 15所述的装置， 其特征在于， 所述装置还包括： 统计报警单元， 统计疟原虫感染红细胞的细胞数量；
所述数据处理单元还得到所述血液样本与疟原虫感染相关的红细胞系血常 规检测参数；
第二报警单元， 在所述细胞数量大于第二阈值且所述红细胞系血常规检测
数不在正常范围时， 发出报警信号。
19、 根据权利要求 15所述的装置， 其特征在于， 所述装置还包括： 统计报警单元， 统计疟原虫感染的红细胞的细胞数量；
所述数据处理单元还根据侧向散射光信号和荧光信号得到所述血液样本的 二散点图；
三报警单元， 在所述细胞数量大于第二阈值且所述第二散点图高荧光区域计 数到细胞群时， 发出报警信号。
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US14/355,544 US10656143B2 (en) | 2011-10-31 | 2012-10-31 | Methods and apparatuses for identifying red blood cells infected by plasmodium |
| US16/814,846 US20200209224A1 (en) | 2011-10-31 | 2020-03-10 | Methods and apparatuses for identifying red blood cells infected by plasmodium |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110337707.8A CN103091286B (zh) | 2011-10-31 | 2011-10-31 | 疟原虫感染的红细胞的识别方法及装置 |
| CN201110337707.8 | 2011-10-31 |
Related Child Applications (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| US14/355,544 A-371-Of-International US10656143B2 (en) | 2011-10-31 | 2012-10-31 | Methods and apparatuses for identifying red blood cells infected by plasmodium |
| US16/814,846 Division US20200209224A1 (en) | 2011-10-31 | 2020-03-10 | Methods and apparatuses for identifying red blood cells infected by plasmodium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2013064078A1 true WO2013064078A1 (zh) | 2013-05-10 |
Family
ID=48191343
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/CN2012/083864 WO2013064078A1 (zh) | 2011-10-31 | 2012-10-31 | 疟原虫感染的红细胞的识别方法及装置 |
Country Status (3)
| Country | Link |
|---|---|
| US (2) | US10656143B2 (zh) |
| CN (1) | CN103091286B (zh) |
| WO (1) | WO2013064078A1 (zh) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10241048B2 (en) | 2014-08-08 | 2019-03-26 | Sysmex Corporation | Blood analyzing method and blood analyzer |
Families Citing this family (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104297135B (zh) * | 2013-07-16 | 2017-02-15 | 成都深迈瑞医疗电子技术研究院有限公司 | 血液样本中粒子的识别方法、系统及血液细胞分析仪 |
| JP6225085B2 (ja) * | 2013-08-30 | 2017-11-01 | シスメックス株式会社 | 検体分析方法および検体分析装置 |
| CN104515723B (zh) * | 2013-09-30 | 2017-12-05 | 深圳迈瑞生物医疗电子股份有限公司 | 细胞分析仪及其红细胞凝集报警方法和系统 |
| CN106662572B (zh) * | 2015-02-12 | 2019-07-05 | 深圳迈瑞生物医疗电子股份有限公司 | 细胞分析仪、粒子分类方法及装置 |
| JP6635720B2 (ja) * | 2015-08-31 | 2020-01-29 | シスメックス株式会社 | 血液分析装置及び血液分析方法 |
| DE102016004051B3 (de) * | 2016-04-04 | 2017-07-27 | Technische Universität Dresden | Verfahren und Vorrichtung zur optischen in-ovo Geschlechtsbestimmung von befruchteten und bebrüteten Vogeleiern |
| CN107655865B (zh) * | 2016-07-25 | 2021-10-19 | 希森美康株式会社 | 血液分析装置及血液分析方法 |
| CN108226127B (zh) * | 2017-12-26 | 2021-04-06 | 深圳国际旅行卫生保健中心 | 测定疟原虫含量的方法和检测疟原虫含量的系统 |
| CN109580550A (zh) * | 2018-12-03 | 2019-04-05 | 迪瑞医疗科技股份有限公司 | 一种白细胞的分类处理方法及其装置 |
| CN113348366A (zh) * | 2019-12-31 | 2021-09-03 | 深圳迈瑞生物医疗电子股份有限公司 | 一种细胞图像分析装置和样本分析方法 |
| CN111781168B (zh) * | 2020-06-17 | 2023-06-13 | 迈克医疗电子有限公司 | 红细胞碎片识别区域的调整方法、装置、设备和介质 |
| CN116569041A (zh) * | 2020-12-01 | 2023-08-08 | 深圳迈瑞生物医疗电子股份有限公司 | 样本分析方法、样本分析仪及计算机可读存储介质 |
| WO2023125939A1 (zh) * | 2021-12-31 | 2023-07-06 | 深圳迈瑞生物医疗电子股份有限公司 | 血液细胞分析仪、提示感染状态的方法以及感染标志参数的用途 |
| CN115711866B (zh) * | 2022-10-31 | 2024-07-09 | 西安电子科技大学 | 基于环形扫描照明的定量相衬层析显微装置和方法 |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060223137A1 (en) * | 2005-03-29 | 2006-10-05 | Sysmex Corporation | Reagent for partially lysing a cell membrane of a red blood cell, a reagent for detecting malaria infected red blood cells, and a sample analyzing method for detecting malaria infected red blood cells |
| EP1746407A2 (en) * | 2005-07-21 | 2007-01-24 | Sysmex Corporation | Blood analyzing method and blood analyzer |
| CN101389947A (zh) * | 2005-12-29 | 2009-03-18 | 霍尼韦尔国际公司 | 微流格式的测定工具 |
| CN102016577A (zh) * | 2008-05-09 | 2011-04-13 | 希森美康株式会社 | 血液分析装置，血液分析方法及溶血剂 |
| CN102016573A (zh) * | 2008-05-09 | 2011-04-13 | 希森美康株式会社 | 血液分析装置，血液分析方法，溶血剂及染色剂 |
| CN102109430A (zh) * | 2009-12-25 | 2011-06-29 | 深圳迈瑞生物医疗电子股份有限公司 | 有核红细胞模拟粒子，血液质控物及其制备方法和用途 |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8842900B2 (en) * | 2008-10-28 | 2014-09-23 | Sysmex Corporation | Specimen processing system and blood cell image classifying apparatus |
-
2011
- 2011-10-31 CN CN201110337707.8A patent/CN103091286B/zh active Active
-
2012
- 2012-10-31 US US14/355,544 patent/US10656143B2/en active Active
- 2012-10-31 WO PCT/CN2012/083864 patent/WO2013064078A1/zh active Application Filing
-
2020
- 2020-03-10 US US16/814,846 patent/US20200209224A1/en not_active Abandoned
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060223137A1 (en) * | 2005-03-29 | 2006-10-05 | Sysmex Corporation | Reagent for partially lysing a cell membrane of a red blood cell, a reagent for detecting malaria infected red blood cells, and a sample analyzing method for detecting malaria infected red blood cells |
| EP1746407A2 (en) * | 2005-07-21 | 2007-01-24 | Sysmex Corporation | Blood analyzing method and blood analyzer |
| CN101389947A (zh) * | 2005-12-29 | 2009-03-18 | 霍尼韦尔国际公司 | 微流格式的测定工具 |
| CN102016577A (zh) * | 2008-05-09 | 2011-04-13 | 希森美康株式会社 | 血液分析装置，血液分析方法及溶血剂 |
| CN102016573A (zh) * | 2008-05-09 | 2011-04-13 | 希森美康株式会社 | 血液分析装置，血液分析方法，溶血剂及染色剂 |
| CN102109430A (zh) * | 2009-12-25 | 2011-06-29 | 深圳迈瑞生物医疗电子股份有限公司 | 有核红细胞模拟粒子，血液质控物及其制备方法和用途 |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10241048B2 (en) | 2014-08-08 | 2019-03-26 | Sysmex Corporation | Blood analyzing method and blood analyzer |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103091286A (zh) | 2013-05-08 |
| US10656143B2 (en) | 2020-05-19 |
| US20140308697A1 (en) | 2014-10-16 |
| CN103091286B (zh) | 2016-08-17 |
| US20200209224A1 (en) | 2020-07-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2013064078A1 (zh) | 疟原虫感染的红细胞的识别方法及装置 | |
| US11105742B2 (en) | Nucleated red blood cell warning method and device, and flow cytometer using the same | |
| JP2565844B2 (ja) | 細胞溶解処理条件下で異種細胞集団を正確に計数し，感受性に関する格付けを行う方法 | |
| JP4911601B2 (ja) | 有核赤血球細胞の計測方法 | |
| CA1309328C (en) | Method of classifying leukocytes by flow cytometry and reagents used in the method | |
| US20210041361A1 (en) | Alarm method, system and storage medium for abnormalities of sample analyzer | |
| KR101847225B1 (ko) | 혈액 샘플 분석 방법 및 분석 시스템 | |
| US10107754B2 (en) | Blood analyzer and blood analyzing method | |
| US11874212B2 (en) | Blood analysis method, blood analysis system and storage medium | |
| JPH10282094A (ja) | 全血中の網状赤血球、赤血球及び血小板を迅速に同定及び特徴付けるための完全に自動化された方法及びそれらのための試薬組成物 | |
| CN103460041B (zh) | 白细胞的分类计数方法、白细胞分类试剂盒及白细胞分类试剂 | |
| WO2021077327A1 (zh) | 分析血液样本中红细胞方法及血液分析系统 | |
| CN110383037A (zh) | 一种血小板聚集识别的方法、装置和细胞分析仪 | |
| CN111684263A (zh) | 血液分析系统、血液分析仪、血液分析方法及存储介质 | |
| US20200025778A1 (en) | Blood analyzer and blood analyzing method | |
| Dumas et al. | Automated Plasmodium detection by the Sysmex XN hematology analyzer | |
| WO2022115982A1 (zh) | 样本分析方法、样本分析仪及计算机可读存储介质 | |
| US12135287B2 (en) | Alarm method, system and storage medium for abnormalities of sample analyzer | |
| Jorgensen | Automated Point-of-Care Image Processing Methodology for the Diagnosis of Malaria |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 12846546 Country of ref document: EP Kind code of ref document: A1 |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| WWE | Wipo information: entry into national phase |
Ref document number: 14355544 Country of ref document: US |
|
| 32PN | Ep: public notification in the ep bulletin as address of the adressee cannot be established |
Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 24/09/2014) |
|
| 122 | Ep: pct application non-entry in european phase |
Ref document number: 12846546 Country of ref document: EP Kind code of ref document: A1 |