CN111521547A - Particle analyzing and sorting device and method - Google Patents
Particle analyzing and sorting device and method Download PDFInfo
- Publication number
- CN111521547A CN111521547A CN202010405704.2A CN202010405704A CN111521547A CN 111521547 A CN111521547 A CN 111521547A CN 202010405704 A CN202010405704 A CN 202010405704A CN 111521547 A CN111521547 A CN 111521547A
- Authority
- CN
- China
- Prior art keywords
- particle
- droplet
- fluorescence
- droplets
- particles
- 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
Links
- 239000002245 particle Substances 0.000 title claims abstract description 278
- 238000000034 method Methods 0.000 title claims abstract description 25
- 239000007788 liquid Substances 0.000 claims abstract description 85
- 238000001514 detection method Methods 0.000 claims abstract description 83
- 238000012876 topography Methods 0.000 claims abstract description 60
- 230000003287 optical effect Effects 0.000 claims description 43
- 238000003384 imaging method Methods 0.000 claims description 25
- 239000000203 mixture Substances 0.000 claims description 19
- 238000004458 analytical method Methods 0.000 claims description 14
- 238000000799 fluorescence microscopy Methods 0.000 claims description 13
- 238000001917 fluorescence detection Methods 0.000 claims description 11
- 239000012530 fluid Substances 0.000 claims description 7
- 238000005286 illumination Methods 0.000 claims description 7
- 210000004027 cell Anatomy 0.000 description 43
- CIWBSHSKHKDKBQ-JLAZNSOCSA-N Ascorbic acid Chemical compound OC[C@H](O)[C@H]1OC(=O)C(O)=C1O CIWBSHSKHKDKBQ-JLAZNSOCSA-N 0.000 description 7
- 239000002699 waste material Substances 0.000 description 7
- 230000010354 integration Effects 0.000 description 5
- 241000894006 Bacteria Species 0.000 description 3
- 238000001914 filtration Methods 0.000 description 3
- 238000000684 flow cytometry Methods 0.000 description 3
- 238000007493 shaping process Methods 0.000 description 3
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N Silicium dioxide Chemical compound O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- GNBHRKFJIUUOQI-UHFFFAOYSA-N fluorescein Chemical compound O1C(=O)C2=CC=CC=C2C21C1=CC=C(O)C=C1OC1=CC(O)=CC=C21 GNBHRKFJIUUOQI-UHFFFAOYSA-N 0.000 description 2
- 238000012806 monitoring device Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 239000013307 optical fiber Substances 0.000 description 2
- 230000004083 survival effect Effects 0.000 description 2
- 241000588724 Escherichia coli Species 0.000 description 1
- 241000233866 Fungi Species 0.000 description 1
- 108091005461 Nucleic proteins Proteins 0.000 description 1
- 239000004793 Polystyrene Substances 0.000 description 1
- 240000004808 Saccharomyces cerevisiae Species 0.000 description 1
- 241000723873 Tobacco mosaic virus Species 0.000 description 1
- 241000700605 Viruses Species 0.000 description 1
- -1 and the like Substances 0.000 description 1
- 239000000427 antigen Substances 0.000 description 1
- 102000036639 antigens Human genes 0.000 description 1
- 108091007433 antigens Proteins 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004113 cell culture Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 210000000349 chromosome Anatomy 0.000 description 1
- 238000010367 cloning Methods 0.000 description 1
- 239000000084 colloidal system Substances 0.000 description 1
- 238000012258 culturing Methods 0.000 description 1
- 210000000805 cytoplasm Anatomy 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000007863 gel particle Substances 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 229910010272 inorganic material Inorganic materials 0.000 description 1
- 239000011147 inorganic material Substances 0.000 description 1
- 239000004816 latex Substances 0.000 description 1
- 229920000126 latex Polymers 0.000 description 1
- 239000000696 magnetic material Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 239000007769 metal material Substances 0.000 description 1
- 244000005700 microbiome Species 0.000 description 1
- 210000003470 mitochondria Anatomy 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 102000039446 nucleic acids Human genes 0.000 description 1
- 108020004707 nucleic acids Proteins 0.000 description 1
- 150000007523 nucleic acids Chemical class 0.000 description 1
- 210000003463 organelle Anatomy 0.000 description 1
- 239000011236 particulate material Substances 0.000 description 1
- 239000013618 particulate matter Substances 0.000 description 1
- 229920000642 polymer Polymers 0.000 description 1
- 229920002223 polystyrene Polymers 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 102000004169 proteins and genes Human genes 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 230000001846 repelling effect Effects 0.000 description 1
- 210000003705 ribosome Anatomy 0.000 description 1
- 239000000377 silicon dioxide Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- 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
- G01N15/10—Investigating individual particles
- G01N15/14—Optical investigation techniques, e.g. flow cytometry
- G01N15/1434—Optical arrangements
- G01N15/1436—Optical arrangements the optical arrangement forming an integrated apparatus with the sample container, e.g. a flow cell
-
- 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
- G01N15/10—Investigating individual particles
- G01N15/14—Optical investigation techniques, e.g. flow cytometry
- G01N15/149—Optical investigation techniques, e.g. flow cytometry specially adapted for sorting particles, e.g. by their size or optical properties
-
- 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
- G01N15/10—Investigating individual particles
- G01N15/14—Optical investigation techniques, e.g. flow cytometry
- G01N2015/1477—Multiparameters
- G01N2015/1479—Using diffuse illumination or excitation
-
- 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
- G01N15/10—Investigating individual particles
- G01N15/14—Optical investigation techniques, e.g. flow cytometry
- G01N2015/1481—Optical analysis of particles within droplets
-
- 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
- G01N15/10—Investigating individual particles
- G01N15/14—Optical investigation techniques, e.g. flow cytometry
- G01N2015/1493—Particle size
Landscapes
- Chemical & Material Sciences (AREA)
- Dispersion Chemistry (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
Abstract
The embodiment of the application provides a particle analyzing and sorting device and a method, wherein the device comprises a sample loading module, a detection module, a control module and a sorting module; the loading module is used for placing a sample liquid containing particles into a loading device; the detection module is used for acquiring one or more of the following characteristics of the liquid drop: a droplet topography image of the droplet, a size of the droplet, fluorescence signature information of the droplet, a signature of the particle within the droplet; the control module is used for obtaining the sorting classification of the liquid drops by utilizing the characteristics of the liquid drops; the sorting module is used for placing the liquid drops into a specified position by utilizing the sorting classification of the liquid drops. The particle analyzing and sorting device and the particle analyzing and sorting method can improve the efficiency and accuracy of particle analyzing and sorting.
Description
Technical Field
The application relates to the field of optical detection, in particular to a particle analyzing and sorting device and a particle analyzing and sorting method.
Background
A current general flow of flow cytometry sorting is to feed stained particles (e.g., cells, bacteria, etc.) into sample tubes, divide the sample tubes into at least two portions, analyze the composition of the particles in one of the portions of the sample tubes using a flow cytometry sorting apparatus, and identify the classification of the particles in the sample tubes; manually, semi-automatically, or fully automatically feeding the one or more additional sample tubes into a flow cytometric analysis and sorting facility for analyzing and sorting the particles in the one or more additional sample tubes based on the identified classification of the particles in the previous sample tube; feeding the sorted particles into a fluorescence microscope for observation one by one, counting the sorting accuracy of the particles, and resetting sorting classification or continuing sorting according to the sorting accuracy; manually, semi-automatically or fully automatically sorting the sorted particles onto a sample tube or a culture dish; the sample is used for subsequent culturing, enrichment, cloning or production. The existing apparatus and method for analyzing and sorting particles take a long time to perform the analyzing and sorting, the analyzing and sorting efficiency is low, and the survival rate of cells becomes low during the analyzing and sorting.
Disclosure of Invention
The application provides a particle analyzing and sorting device and method, which can effectively improve the efficiency and accuracy of analyzing and sorting particles by combining a fluorescence microscopic imaging technology and a fluorescence energy detection technology.
The application provides a particle analyzing and sorting device, which comprises a sample loading module, a detection module, a control module and a sorting module;
the loading module is used for placing a sample liquid containing particles into a loading device; the sample fluid enwraps the particles to form droplets, each of the droplets containing one or more of the particles;
the detection module is used for acquiring one or more of the following characteristics of the liquid drop: a droplet topography image of the droplet, a size of the droplet, fluorescence signature information of the droplet, a signature of the particle within the droplet; the characteristics of the particles within the droplets include one or more of the following characteristics: the size of the particle, the fluorescence characteristic information of the particle, the internal composition of the particle, the structure of the particle, the complexity of the particle, the fluorescence topography image of the particle, the overall topography image of the particle;
the control module is used for obtaining the sorting classification of the liquid drops by utilizing the characteristics of the liquid drops;
the sorting module is used for placing the liquid drops into a specified position by utilizing the sorting classification of the liquid drops.
Preferably, the detection module comprises an emitter, a flow chamber and one or more of the following: a forward scatter detection device, a side scatter detection device, a fluorescence energy detection device, a fluorescence imaging device, a cell imaging device, a droplet imaging device;
the emitter is used for emitting at least one laser which irradiates on the liquid drop containing the particles in the liquid flow chamber;
the liquid flow chamber is used for limiting the flow of the liquid drop, so that the liquid drop containing the particles is sequentially irradiated by the laser to generate an optical signal, and the optical signal comprises a fluorescence signal and a scattered light signal;
the forward scatter detection device is used for analyzing the scattered light signals; the forward scatter detection device comprises a first detector for detecting a first portion of the optical signal, acquiring the size of the particle and/or the size of the droplet; the direction of the first portion of the optical signal is parallel to the direction of the laser light;
alternatively, the side scatter detection device comprises a third lens and a second detector; the third lens is used for dividing the second part of the optical signal into a scattered light detection part and a fluorescence detection part; the second detector is used for detecting the scattered light detection part and acquiring one or more of the following characteristics: the internal composition of the particle, the structure of the particle, the complexity of the particle; the direction of the scattered light detection part is vertical to the direction of the laser;
or, the fluorescence energy detection device comprises a third detector for detecting the fluorescence detection part and acquiring the fluorescence characteristic information of the particles and/or the fluorescence characteristic information of the liquid drops;
or the fluorescence imaging device comprises a fourth detector, and the fourth detector is used for detecting a third part of the optical signal and acquiring a fluorescence topography image of the particle;
or, the cell imaging device comprises a fifth detector for acquiring an overall morphology image of the particle;
alternatively, the droplet imaging apparatus includes a sixth detector for acquiring a droplet topography image of the droplet.
Preferably, the detection module comprises at least one illumination device for illuminating the flow chamber.
Preferably, the detection module is used for acquiring one or more of the following characteristics when the flow speed of the liquid drop is less than or equal to 1 m/s: the internal composition of the particle, the structure of the particle, the complexity of the particle, the fluorescence topography image of the particle, the global topography image of the particle, the droplet topography image of the droplet;
alternatively, the detection module is configured to obtain one or more of the following characteristics when the flow velocity of the droplet is greater than 1 m/s: fluorescence characteristic information of the particle, size of the droplet, fluorescence characteristic information of the droplet.
Preferably, the control module is further configured to output an analysis sorting report, the analysis sorting report including one or more of: a characteristic of each of the droplets, a sort classification of each of the droplets, whether each of the droplets falls into a specified location, the number of the particles or the droplets falling into the respective specified location.
The present application also provides a method of particle analysis sorting, the method comprising:
placing a sample liquid containing particles into a loading device; the sample fluid enwraps the particles to form droplets, each of the droplets containing one or more of the particles;
acquiring one or more of the following characteristics of the droplet with a detection module: a droplet topography image of the droplet, a size of the droplet, fluorescence signature information of the droplet, a signature of the particle within the droplet; the characteristics of the particles within the droplets include one or more of the following characteristics: the size of the particle, the fluorescence characteristic information of the particle, the internal composition of the particle, the structure of the particle, the complexity of the particle, the fluorescence topography image of the particle, the overall topography image of the particle;
obtaining a sorting classification of the droplets using the characteristics of the droplets;
and placing the liquid drops into a designated position by utilizing the sorting classification of the liquid drops.
Preferably, the acquiring, by the detection module, the characteristics of the liquid droplet specifically includes:
controlling the emitter to emit at least one laser, wherein the laser irradiates the liquid drop containing the particles in the liquid flow chamber, so that the liquid drop containing the particles is irradiated by the laser in sequence to generate an optical signal, and the optical signal comprises a fluorescence signal and a scattered light signal;
analyzing the scattered light signal by using a forward scattering detection device to obtain the size of the particles and/or the size of the liquid drops;
alternatively, one or more of the following features are acquired with a side scatter detection device: the internal composition of the particle, the structure of the particle, the complexity of the particle; the direction of the scattered light detection part is vertical to the direction of the laser; the side scatter detection device comprises a third lens and a second detector; the third lens is used for dividing the second part of the optical signal into a scattered light detection part and a fluorescence detection part; detecting the scattered light detecting portion with the second detector;
or, detecting the fluorescence detection part by using a fluorescence energy detection device to acquire fluorescence characteristic information of the particles and/or fluorescence characteristic information of the liquid drops;
or detecting a third part of the optical signal by using a fluorescence imaging device to obtain a fluorescence topography image of the particle;
or, acquiring a global morphology image of the particles by using a cell imaging device;
or acquiring a droplet topography image of the droplet by using the droplet imaging device.
Preferably, the method further comprises: at a flow velocity of the droplets of less than or equal to 1 m/s, one or more of the following characteristics are obtained: the internal composition of the particle, the structure of the particle, the complexity of the particle, the fluorescence topography image of the particle, the global topography image of the particle, the droplet topography image of the droplet;
alternatively, when the flow velocity of the droplets is greater than 1 m/s, one or more of the following characteristics are obtained: fluorescence characteristic information of the particle, size of the droplet, fluorescence characteristic information of the droplet.
Preferably, the obtaining of the sorted classification of the droplets using the features of the droplets specifically comprises:
obtaining a first classification of the droplet using one or more characteristics of the particle within the droplet;
obtaining a second classification of the droplets using one or more of the droplet topography images, the size of the droplets, and fluorescence signature information of the droplets;
a sorted classification of the droplets is obtained using the first classification of the droplets and the second classification of the droplets.
Preferably, the method further comprises outputting an analysis sort report comprising one or more of: a characteristic of each of the droplets, a sort classification of each of the droplets, whether each of the droplets falls into a specified location, the number of the particles or the droplets falling into the respective specified location.
The particle analyzing and sorting device and method provided by the embodiment of the application can realize the following beneficial effects:
by utilizing the fluorescence energy, the fluorescence morphology imaging, the cell imaging and the like of the particles, the particles are comprehensively analyzed and then sorted, so that the efficiency and the accuracy of particle analysis and sorting can be effectively improved, and the survival rate of the particles can be improved.
Drawings
FIG. 1 is a schematic view of a first configuration of a particle analyzing and sorting apparatus according to an embodiment of the present application;
FIG. 2 is a schematic view of a second structure of a particle analyzing and sorting apparatus according to an embodiment of the present application;
FIG. 3 is a schematic view of a third structure of a particle analyzing and sorting apparatus according to an embodiment of the present application;
FIG. 4 is a fourth schematic view of the particle analyzing and sorting apparatus according to the embodiment of the present application;
FIG. 5 is a schematic view of a fifth configuration of a particle analyzing and sorting apparatus according to an embodiment of the present application;
fig. 6 is a sixth configuration diagram of the particle analyzing and sorting apparatus according to the embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The singular forms "a", "an" and "the" include plural referents unless the context clearly dictates otherwise. As used herein, the terms "first" and "second" are used interchangeably to distinguish one element or class of elements from another element or class of elements, respectively, and are not intended to denote the position or importance of the individual elements.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.
As shown in fig. 1, the present application provides a particle analysis and sorting apparatus, which includes a loading module, a detection module, a control module, and a sorting module.
The loading module is used for placing the sample liquid containing the particles into the loading device. For example, the loading module is used to divide the sample liquid containing particles into at least two equal parts, which are respectively fed into the loading device. For example, the sample loading device may respectively place the sample liquid containing the particles after being equally divided into the designated positions according to a preset path, for example, the preset path may be a path which is formed by connecting the center points of at least two sample loading holes, contains all the sample loading holes, and has no repetition, such as a circular radial scanning path shown in fig. 3, or a step scanning path shown in fig. 4, and the like.
The particles may be cells, bacteria, etc., including but not limited to, biological particulate matter, such as microorganisms including bacteria such as E.coli, viruses such as tobacco mosaic virus, fungi such as yeast, ribosomes, chromosomes, mitochondria, organelles, etc., and biologically-relevant polymers such as nucleic acids, proteins, and complexes thereof; the particles may also be artificial particles such as latex particles, gel particles, industrial particles, and the like, including but not limited to particles formed of organic polymeric materials including polystyrene and the like, inorganic materials including glass, silica, magnetic materials, and the like, and metallic materials including metal colloids and the like, and the like. It should be noted that although the shape of these particulate materials is generally spherical, the particles may have a non-spherical shape. Further, the size, mass, etc. of the particles are also not limited. The sample fluid encapsulates the particles to form droplets, and droplets comprising a plurality of particles can flow in the fluid flow chamber, each of the droplets comprising one or more of the particles.
The detection module is used for acquiring the characteristics of the liquid drops. For example, the characteristics of the droplets include one or more of the following: a droplet topography image, a droplet size, fluorescence characteristic information of the droplet, characteristics of the particle within the droplet, and the like. For example, if the droplet contains one of the particles, the detection module is configured to obtain one or more of the following characteristics of the particle within the droplet: the size of the particles, the fluorescence characteristic information of the particles, the internal composition of the particles, the structure of the particles, the complexity of the particles, the fluorescence topography image of the particles and the overall topography image of the particles. Alternatively, if the droplet contains a number of said particles, the detection module is adapted to obtain one or more of the following characteristics of the droplet: the shape image of the liquid drop, the size of the liquid drop, the fluorescence characteristic information of the liquid drop and the like.
As shown in fig. 2, the detection module includes an emitter, a flow chamber, and one or more of the following: a forward scatter detection device, a side scatter detection device, a fluorescence energy detection device, a fluorescence imaging device, a cell imaging device, a droplet imaging device. The emitter is used for emitting at least one light wave or sound wave, and the light wave or sound wave is hit on the particles in the liquid flow chamber to generate reflection or radiation. The emitter may also emit multiple light or sound waves, such as laser light, simultaneously. The flow chamber is configured to restrict the flow of the droplets, e.g., the flow chamber allows only one of the droplets to pass through, such that the droplets containing the particles are sequentially irradiated with laser light to generate optical signals, which include fluorescent signals and scattered light signals.
The forward scatter detection device includes a first detector for detecting a first portion of the optical signal, the first portion of the optical signal including a scattered light signal, the first portion of the optical signal having a direction parallel to a direction of the laser light, and the first portion of the optical signal may be referred to as Forward Scatter (FSC). The first detector is used for acquiring the size of the particles. Alternatively, the first detector is used to obtain the size of a droplet containing a number of particles.
The side scatter detection device comprises a second detector, for example, the second part of the optical signal is divided into a plurality of signals after passing through the spectroscopic sheet, for example, the second part of the optical signal also comprises a fluorescence signal and a scattered light signal, the second part of the optical signal is divided into a scattered light detection portion and a fluorescence detection portion by the spectroscopic sheet, and the second detector is used for detecting the scattered light detection portion. For example, the third lens is disposed such that the direction of the scattered light detecting section, which may be referred to as Side Scatter (SSC), is perpendicular to the direction of the laser light. The second detector is used for acquiring one or more of the following characteristics of the particles: the internal composition of the particle, the structure of the particle, the complexity of the particle. The complexity of the particles may include microscopic information of the particle surface, such as the roughness of the particle surface.
The fluorescence energy detecting apparatus includes a third detector for detecting the fluorescence detecting portion, for example, and acquiring fluorescence characteristic information of the particle. For example, the particles are labeled with different fluorescein or fluorochromes, and the characteristics contained in different particles differ, which may be different cytoplasms, such as antigens, DNA, RNA, etc. The particles containing different features will have different fluorescence signature information when labeled. The fluorescence signature information includes one or more of the following characteristics of the particle: a fluorescence wavelength of the particle, a fluorescence energy of the particle, a fluorescein content of the particle, a feature of the particle, and a quantity of each feature of the particle. Alternatively, the third detector is used to obtain fluorescence characteristic information of a droplet containing a plurality of particles.
The fluorescence imaging apparatus includes a fourth detector, for example, a Time Delay Integration Charge Coupled device (TDI-CCD), such as a high speed detection Time Delay Integration camera (TDI camera). The fourth detector is used for detecting a third part of an optical signal generated after the particles are irradiated by the laser and acquiring a fluorescence topography image of the particles. The third portion of the optical signal also includes a fluorescence signal, the fourth detector is configured to detect the fluorescence signal in the third portion of the optical signal, and the fluorescence signal in the third portion of the optical signal received by the fourth detector may be referred to as a high-speed fluorescence imaging optical path. And the image shot by the fourth detector moves along with the flow of the particles, and the obtained particle image is integrated in time to obtain a three-dimensional fluorescence morphology image of the particles. The fourth detector can be an area array CCD, the pixel in the vertical direction is in the direction of integral progression (stage), and the fourth detector is sequentially sensitive along the direction of the integral progression when working. The direction of the integration orders of the fourth detector is parallel to the flow direction of the particles, and the direction of the integration orders of the fourth detector is perpendicular to the high-speed fluorescence imaging optical path, i.e. the direction of the integration orders of the fourth detector 109 is perpendicular to the direction of the third portion of the optical signal. In an alternative embodiment of the present application, the working time of the fourth detector is matched with the flow velocity of the particles, for example, the fourth detector can detect the fluorescence signal in the third part of the optical signal generated after each of the particles is irradiated by the laser light, so as to obtain the fluorescence topography image of each of the particles. In an alternative embodiment of the present application, the detection module further comprises a converging lens or a shaping lens or an imaging lens or a filtering lens, such as a convex lens, a concave lens or a combination of a convex lens and a concave lens, respectively, arranged in front of the beam splitter, the flow cell, the first detector and/or the fourth detector. The shaping lens is used for shaping the optical signal into a preset shape, the imaging lens is used for imaging an object clearly at the other end of the lens, and the filtering lens is used for filtering the light wave/sound wave signal with a preset wavelength.
The cell imaging device comprises a fifth detector, for example, the fifth detector is a scientific camera, and indexes such as the resolution, the zoom range of a lens and the shutter speed of the fifth detector are sufficient for directly shooting an image seen by the microscope. The fifth detector is used for acquiring the overall shape image of the particles. The fifth detector may also be a TDI camera. In another embodiment of the present application, the fifth detector and the fourth detector may be the same device.
The droplet imaging apparatus comprises a sixth detector, for example a microscope. The sixth detector is used for acquiring a liquid drop morphology image containing a plurality of particles.
In another embodiment of the present application, the apparatus is further configured to automatically analyze and sort the droplet containing a number of the particles, for example, the detection module is configured to obtain one or more of the following characteristics when the flow velocity of the droplet is ≦ 1 m/sec: the internal composition of the particles, the structure of the particles, the complexity of the particles, the fluorescence topography image of the particles, the global topography image of the particles, the droplet topography image of the droplets. Alternatively, the detection module is configured to obtain one or more of the following characteristics when the flow velocity of the droplet is greater than 1 m/s: fluorescence characteristic information of the particle, size of the droplet, fluorescence characteristic information of the droplet. For example, the fluorescence topography image of the particle includes, but is not limited to, a three-dimensional fluorescence topography, a two-dimensional fluorescence profile topography of the particle; the fluorescence signature information of the particle includes, but is not limited to, a two-dimensional fluorescence signal of the particle. For example, if the particle contains feature a, the third detector obtains a high level signal, and if the particle does not contain feature a, the third detector obtains a low level signal; a third detector obtains a two-dimensional fluorescence signal as the particles flow in the flow chamber. The device automatically analyzes and sorts the liquid drops according to the change of the flow velocity of the liquid drops, and the number of the fluorescence appearance images/overall appearance images of the particles is consistent with the number of the particles in the liquid flow chamber.
In an optional embodiment of the application, the detection module further comprises at least one lighting device. The illumination device is used for illuminating the liquid flow chamber, for example, the illumination device is an illumination optical fiber, and the illumination optical fiber couples laser emitted by the plurality of emitters and irradiates the particles, so that the energy of signals received by each detector is more, the detection efficiency can be improved, and a more accurate detection result can be obtained. For example, the detection module includes an illumination device in one-to-one correspondence with a forward scatter detection device, a side scatter detection device, a fluorescence energy detection device, a fluorescence imaging device, a cell imaging device, or a droplet imaging device.
The control module is used for obtaining the sorting classification of the liquid drops by utilizing the characteristics of the liquid drops. For example, the control module is configured to integrate and analyze the characteristics of the droplets obtained by the detection module, calculate a sorting classification of the droplets, and send the sorting classification of the droplets to the sorting module; receiving results of the sorting module monitoring droplet movement. In an alternative embodiment of the present application, the control module is further configured to predict the velocity, direction, trajectory of the droplet movement and output to the sorting module in order to allow the droplet to fall into a designated position corresponding to each sorting classification. In an optional embodiment of the present application, the control module may automatically classify the droplets according to a preset standard by using the characteristics of the droplets, or may manually classify the droplets. In another embodiment of the present application, the control module is further configured to output an analysis sorting report, for example, the analysis sorting report including one or more of: characteristics of each droplet, sorting classification of each droplet, whether each droplet falls into a specified location, number of particles or droplets falling into each specified location.
The sorting module is used for placing the liquid drops into a specified position by utilizing the sorting classification of the liquid drops. For example, the sorting module is used to sort droplets containing several of the particles into different sample tubes/cell culture dishes/cell troughs/sorting wells using sorting of the droplets. For example, the sorting module is used to control the movement of the droplets so that they fall into a specified location. The method for controlling the movement of the liquid drops is not limited, for example, the sorting module further comprises a charging plate and a deflecting plate, wherein the charging plate is used for charging the liquid drops when the liquid drops are about to leave the liquid flow chamber, so that the liquid drops are charged after leaving the liquid flow chamber; the deflection plate is used for attracting or repelling the charged liquid drops, so that the charged liquid drops are deflected and move according to the speed, direction and track predicted by the control module, or the uncharged liquid drops are not deflected, so that each liquid drop falls into a designated position respectively. For example, the sorting module is further configured to monitor a motion process of the droplet, the sorting module includes a monitoring device such as a camera, and the monitoring device is configured to acquire an actual motion trajectory of the droplet, for example, the sorting module is configured to monitor whether the droplet falls into a specified position, or monitor whether the actual motion trajectory of the droplet is consistent with a prediction, and output a monitoring result to the control module. For example, the sorting module obtains an actual motion trajectory of the droplet, adjusts the charge amount of the deflection plate to correct the motion trajectory of the droplet inconsistent with the predicted motion trajectory, or the sorting module marks the droplet with the actual motion trajectory inconsistent with the predicted motion trajectory as a waste droplet, adjusts the deflection plate so that the waste droplet falls into a waste tank, or the analysis sorting report further includes the waste droplet/the number of particles contained in the waste droplet.
In another embodiment of the present application, the sorting module is further configured to obtain an interval time between each droplet, and control the charging plate to charge and discharge the deflection plate and each droplet by using the interval time between the droplets, so that each droplet falls into a specific position.
In another embodiment of the present application, as shown in fig. 5 and 6, the sorting module comprises sorting wells that are axisymmetrically distributed.
Based on the particle analysis and sorting device, the particle analysis and sorting method comprises the following steps: placing a sample liquid containing particles into a loading device; the sample fluid enwraps the particles to form droplets, each of the droplets containing one or more of the particles; acquiring one or more of the following characteristics of the droplet with a detection module: a droplet topography image of the droplet, a size of the droplet, fluorescence signature information of the droplet, a signature of the particle within the droplet; the characteristics of the particles within the droplets include one or more of the following characteristics: the size of the particle, the fluorescence characteristic information of the particle, the internal composition of the particle, the structure of the particle, the complexity of the particle, the fluorescence topography image of the particle, the overall topography image of the particle; obtaining a sorting classification of the droplets using the characteristics of the droplets; and placing the liquid drops into a designated position by utilizing the sorting classification of the liquid drops.
For example, the emitter is controlled to emit at least one laser that impinges on the particle-containing droplets in the flow chamber; the liquid drop containing the particles sequentially generates optical signals under the irradiation of the laser, wherein the optical signals comprise fluorescence signals and scattered light signals;
detecting a first portion of the optical signal with a forward scatter detection device, obtaining a size of the particle and/or a size of the droplet; or, the second part of the optical signal is divided into a scattered light detection part and a fluorescence detection part by using a light splitting sheet; detecting the scattered light detection portion with a side scatter detection device, obtaining one or more of the following characteristics of the particle: the internal composition of the particle, the structure of the particle, the complexity of the particle; the direction of the scattered light detection part is vertical to the direction of the laser; or, detecting the fluorescence detection part by using a fluorescence energy detection device to acquire fluorescence characteristic information of the particles and/or fluorescence characteristic information of the liquid drops; or detecting a third part of the optical signal by using a fluorescence imaging device to obtain a fluorescence topography image of the particle; or, acquiring an overall morphology image of the particles by using cell imaging equipment; or acquiring a droplet topography image of the droplet by using a droplet imaging device.
In another embodiment of the present application, the first classification of the droplet is derived using one or more characteristics of the particle within the droplet. For example, knowing one or more characteristics of cell B, cell C, cell D, cell E, manually/automatically/semi-automatically selecting one or more characteristics of the particle to compare with one or more characteristics of cell B, cell C, cell D, cell E, respectively, to obtain the similarity of the particle to cell B, cell C, cell D, cell E, respectively, and selecting cells with similarity satisfying a predetermined criterion as the first classification of the droplet. For example, the particles are most similar to cell B, the first classification of the droplets being cell B. Alternatively, the particle has a 90% similarity to cell B, the particle has a 85% similarity to cell C, the particle has a 70% similarity to cell D, the particle has a 60% similarity to cell E, and assuming a similarity of greater than 80% is the first classification of the droplet, which is either cell B or cell C.
A second classification of the droplets is obtained using one or more of the droplet topography images, the size of the droplets, and the fluorescence signature information of the droplets. For example, it is known that characteristics of a droplet containing a cell B, a droplet containing a cell C, a droplet containing a cell D, and a droplet containing a cell E are compared with droplets containing a plurality of the particles, respectively, to obtain similarities between the droplets containing the plurality of the particles and the droplets containing the respective cells, respectively, and the second classification of the droplets in which the similarities satisfy a predetermined criterion is selected. For example, a droplet comprising a number of the particles has a droplet topography image similarity of 80% to a droplet comprising cells B, a droplet comprising a number of the particles has a droplet topography image similarity of 60% to a droplet comprising cells C, a droplet comprising a number of the particles has a droplet topography image similarity of 70% to a droplet comprising cells D, a droplet comprising a number of the particles has a droplet topography image similarity of 75% to a droplet comprising cells E, and a second classification of a droplet assuming a droplet topography image similarity of greater than 70% is cell B or cell E.
And comprehensively utilizing the first classification of the liquid drops and the second classification of the liquid drops to obtain the classification of the liquid drops. For example, the first classification of the droplet is cell B or cell C, the second classification of the droplet is cell B or cell E, and taking the intersection of the first classification of the droplet and the second classification of the droplet results in the sorting classification of the droplet as cell B.
And placing the liquid drops into a designated position by utilizing the sorting classification of the liquid drops. In another embodiment of the present application, the method further comprises recording the number of particles/droplets put in each designated position, or recording the number of waste droplets by marking particles not put in the designated position as waste droplets.
In another embodiment of the present application, the method further comprises obtaining one or more of the following characteristics when the flow velocity of the droplets is ≦ 1 m/sec: the internal composition of the particle, the structure of the particle, the complexity of the particle, the fluorescence topography image of the particle, the global topography image of the particle, the droplet topography image of the droplet; alternatively, when the flow velocity of the droplets is greater than 1 m/s, one or more of the following characteristics are obtained: fluorescence characteristic information of the particle, size of the droplet, fluorescence characteristic information of the droplet.
In another embodiment of the present application, the method further comprises automatically analytically sorting a sample or population containing the particles, generating an analytically sorting report comprising information of characteristics of the droplets, sorting classification of the droplets, whether each of the droplets falls into a specified location, number of particles or droplets falling into each specified location, purity of particles within each sort well, etc.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. The particle analyzing and sorting device is characterized by comprising a sample loading module, a detection module, a control module and a sorting module;
the loading module is used for placing a sample liquid containing particles into a loading device; the sample fluid enwraps the particles to form droplets, each of the droplets containing one or more of the particles;
the detection module is used for acquiring one or more of the following characteristics of the liquid drop: a droplet topography image of the droplet, a size of the droplet, fluorescence signature information of the droplet, a signature of the particle within the droplet; the characteristics of the particles within the droplets include one or more of the following characteristics: the size of the particle, the fluorescence characteristic information of the particle, the internal composition of the particle, the structure of the particle, the complexity of the particle, the fluorescence topography image of the particle, the overall topography image of the particle;
the control module is used for obtaining the sorting classification of the liquid drops by utilizing the characteristics of the liquid drops;
the sorting module is used for placing the liquid drops into a specified position by utilizing the sorting classification of the liquid drops.
2. The apparatus of claim 1, wherein the detection module comprises one or more of an emitter, a flow cell, and: a forward scatter detection device, a side scatter detection device, a fluorescence energy detection device, a fluorescence imaging device, a cell imaging device, a droplet imaging device;
the emitter is used for emitting at least one laser which irradiates on the liquid drop containing the particles in the liquid flow chamber;
the liquid flow chamber is used for limiting the flow of the liquid drop, so that the liquid drop containing the particles is sequentially irradiated by the laser to generate an optical signal, and the optical signal comprises a fluorescence signal and a scattered light signal;
the forward scatter detection device is used for analyzing the scattered light signals; the forward scatter detection device comprises a first detector for detecting a first portion of the optical signal, acquiring the size of the particle and/or the size of the droplet; the direction of the first portion of the optical signal is parallel to the direction of the laser light;
alternatively, the side scatter detection device comprises a third lens and a second detector; the third lens is used for dividing the second part of the optical signal into a scattered light detection part and a fluorescence detection part; the second detector is used for detecting the scattered light detection part and acquiring one or more of the following characteristics: the internal composition of the particle, the structure of the particle, the complexity of the particle; the direction of the scattered light detection part is vertical to the direction of the laser;
or, the fluorescence energy detection device comprises a third detector for detecting the fluorescence detection part and acquiring the fluorescence characteristic information of the particles and/or the fluorescence characteristic information of the liquid drops;
or the fluorescence imaging device comprises a fourth detector, and the fourth detector is used for detecting a third part of the optical signal and acquiring a fluorescence topography image of the particle;
or, the cell imaging device comprises a fifth detector for acquiring an overall morphology image of the particle;
alternatively, the droplet imaging apparatus includes a sixth detector for acquiring a droplet topography image of the droplet.
3. The apparatus of claim 1, wherein the detection module comprises at least one illumination device for illuminating the flow chamber.
4. The apparatus of claim 1, wherein the detection module is configured to obtain one or more of the following characteristics when the flow velocity of the droplet is less than or equal to 1 m/s: the internal composition of the particle, the structure of the particle, the complexity of the particle, the fluorescence topography image of the particle, the global topography image of the particle, the droplet topography image of the droplet;
alternatively, the detection module is configured to obtain one or more of the following characteristics when the flow velocity of the droplet is greater than 1 m/s: fluorescence characteristic information of the particle, size of the droplet, fluorescence characteristic information of the droplet.
5. The apparatus of claim 1, wherein the control module is further configured to output an analysis sort report that includes one or more of: a characteristic of each of the droplets, a sort classification of each of the droplets, whether each of the droplets falls into a specified location, the number of the particles or the droplets falling into the respective specified location.
6. A method of analytical sorting of particles, the method comprising:
placing a sample liquid containing particles into a loading device; the sample fluid enwraps the particles to form droplets, each of the droplets containing one or more of the particles;
acquiring one or more of the following characteristics of the droplet with a detection module: a droplet topography image of the droplet, a size of the droplet, fluorescence signature information of the droplet, a signature of the particle within the droplet; the characteristics of the particles within the droplets include one or more of the following characteristics: the size of the particle, the fluorescence characteristic information of the particle, the internal composition of the particle, the structure of the particle, the complexity of the particle, the fluorescence topography image of the particle, the overall topography image of the particle;
obtaining a sorting classification of the droplets using the characteristics of the droplets;
and placing the liquid drops into a designated position by utilizing the sorting classification of the liquid drops.
7. The method of claim 6, wherein the obtaining the characteristics of the droplet using the detection module specifically comprises:
controlling the emitter to emit at least one laser, wherein the laser irradiates the liquid drop containing the particles in the liquid flow chamber, so that the liquid drop containing the particles is irradiated by the laser in sequence to generate an optical signal, and the optical signal comprises a fluorescence signal and a scattered light signal;
analyzing the scattered light signal by using a forward scattering detection device to obtain the size of the particles and/or the size of the liquid drops;
alternatively, one or more of the following features are acquired with a side scatter detection device: the internal composition of the particle, the structure of the particle, the complexity of the particle; the direction of the scattered light detection part is vertical to the direction of the laser; the side scatter detection device comprises a third lens and a second detector; the third lens is used for dividing the second part of the optical signal into a scattered light detection part and a fluorescence detection part; detecting the scattered light detecting portion with the second detector;
or, detecting the fluorescence detection part by using a fluorescence energy detection device to acquire fluorescence characteristic information of the particles and/or fluorescence characteristic information of the liquid drops;
or detecting a third part of the optical signal by using a fluorescence imaging device to obtain a fluorescence topography image of the particle;
or, acquiring a global morphology image of the particles by using a cell imaging device;
or acquiring a droplet topography image of the droplet by using the droplet imaging device.
8. The method of claim 6, wherein the method further comprises: at a flow velocity of the droplets of less than or equal to 1 m/s, one or more of the following characteristics are obtained: the internal composition of the particle, the structure of the particle, the complexity of the particle, the fluorescence topography image of the particle, the global topography image of the particle, the droplet topography image of the droplet;
alternatively, when the flow velocity of the droplets is greater than 1 m/s, one or more of the following characteristics are obtained: fluorescence characteristic information of the particle, size of the droplet, fluorescence characteristic information of the droplet.
9. The method of claim 6, wherein said using the characteristics of the droplets to derive the sorted classification of the droplets specifically comprises:
obtaining a first classification of the droplet using one or more characteristics of the particle within the droplet;
obtaining a second classification of the droplets using one or more of the droplet topography images, the size of the droplets, and fluorescence signature information of the droplets;
a sorted classification of the droplets is obtained using the first classification of the droplets and the second classification of the droplets.
10. The method of claim 6, further comprising outputting an analysis sort report, the analysis sort report including one or more of: a characteristic of each of the droplets, a sort classification of each of the droplets, whether each of the droplets falls into a specified location, the number of the particles or the droplets falling into the respective specified location.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010405704.2A CN111521547A (en) | 2020-05-13 | 2020-05-13 | Particle analyzing and sorting device and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010405704.2A CN111521547A (en) | 2020-05-13 | 2020-05-13 | Particle analyzing and sorting device and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111521547A true CN111521547A (en) | 2020-08-11 |
Family
ID=71912339
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010405704.2A Pending CN111521547A (en) | 2020-05-13 | 2020-05-13 | Particle analyzing and sorting device and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111521547A (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1795382A (en) * | 2003-03-28 | 2006-06-28 | 孟山都技术公司 | Apparatus, methods and processes for sorting particles and for providing sex-sorted animal sperm |
| CN104111344A (en) * | 2014-05-23 | 2014-10-22 | 苏州日和科技有限公司 | Fully automatic sample-injection mechanism of flow cytometer |
| CN104204767A (en) * | 2012-02-13 | 2014-12-10 | 奥维奇奥成像系统股份有限公司 | Flow cytometer with digital holographic microscope |
| CN107167416A (en) * | 2017-05-15 | 2017-09-15 | 中国科学院微生物研究所 | A kind of sorting type flow cytometer |
| CN107290562A (en) * | 2017-08-22 | 2017-10-24 | 重庆博奥新景医学科技有限公司 | A kind of automatic sample handling system detected for sample cell high flux |
| US20170356836A1 (en) * | 2016-06-14 | 2017-12-14 | Intellicyt | Method and Apparatus for Decreasing Tubing Carryover With Poly(2-hydroxyethyl methacrylate) Coating |
| CN208459417U (en) * | 2018-07-06 | 2019-02-01 | 天津科仪嘉欣科技有限公司 | A kind of full-automatic sample introduction mechanism of flow cytometer |
| CN110312926A (en) * | 2017-01-18 | 2019-10-08 | 高济生物医药科技(上海)有限公司 | It analyzes multiple drops and therefrom selects the method and relevant apparatus of certain droplet |
| CN110865054A (en) * | 2018-08-28 | 2020-03-06 | 昆山品源知识产权运营科技有限公司 | Particle sorting equipment and particle sorting method |
| CN110895237A (en) * | 2019-12-17 | 2020-03-20 | 复旦大学 | Micro-fluidic automatic separation and intelligent component identification system |
-
2020
- 2020-05-13 CN CN202010405704.2A patent/CN111521547A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1795382A (en) * | 2003-03-28 | 2006-06-28 | 孟山都技术公司 | Apparatus, methods and processes for sorting particles and for providing sex-sorted animal sperm |
| CN104204767A (en) * | 2012-02-13 | 2014-12-10 | 奥维奇奥成像系统股份有限公司 | Flow cytometer with digital holographic microscope |
| CN104111344A (en) * | 2014-05-23 | 2014-10-22 | 苏州日和科技有限公司 | Fully automatic sample-injection mechanism of flow cytometer |
| US20170356836A1 (en) * | 2016-06-14 | 2017-12-14 | Intellicyt | Method and Apparatus for Decreasing Tubing Carryover With Poly(2-hydroxyethyl methacrylate) Coating |
| CN110312926A (en) * | 2017-01-18 | 2019-10-08 | 高济生物医药科技(上海)有限公司 | It analyzes multiple drops and therefrom selects the method and relevant apparatus of certain droplet |
| CN107167416A (en) * | 2017-05-15 | 2017-09-15 | 中国科学院微生物研究所 | A kind of sorting type flow cytometer |
| CN107290562A (en) * | 2017-08-22 | 2017-10-24 | 重庆博奥新景医学科技有限公司 | A kind of automatic sample handling system detected for sample cell high flux |
| CN208459417U (en) * | 2018-07-06 | 2019-02-01 | 天津科仪嘉欣科技有限公司 | A kind of full-automatic sample introduction mechanism of flow cytometer |
| CN110865054A (en) * | 2018-08-28 | 2020-03-06 | 昆山品源知识产权运营科技有限公司 | Particle sorting equipment and particle sorting method |
| CN110895237A (en) * | 2019-12-17 | 2020-03-20 | 复旦大学 | Micro-fluidic automatic separation and intelligent component identification system |
Non-Patent Citations (2)
| Title |
|---|
| 王康孙 主编: "《眼科激光基础与临床》", 30 April 2008, 上海科技教育出版社 * |
| 陈曲波 等主编: "《临床免疫检验标准化操作程序》", 31 August 2019, 上海科学技术出版社 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11305318B2 (en) | Particle sorting apparatus and particle sorting method | |
| US9835541B2 (en) | Enhancing flow cytometry discrimination with geometric transformation | |
| US11204309B2 (en) | Image processing device, fine particle sorting device, and image processing method | |
| KR100849948B1 (en) | High purity x-chromosome bearing or y-chromosome bearing populations of spermatozoa | |
| US20190049356A1 (en) | Multiple-Spot Time-Sequential Cytometry | |
| CA2992239C (en) | Cell analysis apparatus and methods | |
| CN105431725A (en) | Operatorless particle processing systems and methods | |
| JP2002523738A (en) | Multicellular organisms and other large object selection and storage devices | |
| US20210293691A1 (en) | Droplet processing methods and systems | |
| CN111855544B (en) | Fluorescence imaging device and imaging method thereof | |
| CN111521548A (en) | Particle analyzing and sorting device and method | |
| JP6685057B1 (en) | Imaging flow cytometer, sorting method, and calibration method | |
| CN111521547A (en) | Particle analyzing and sorting device and method | |
| CN111879685A (en) | Particle analysis and sorting device and charging delay setting method | |
| US20170248511A1 (en) | Flow Cytometry Cell Sorting Systems and Methods of Using the Same | |
| CN115428038A (en) | Sorting workflow for flexible image-based particle sorting | |
| CN111521549B (en) | Particle sorting device and method | |
| JP7557067B2 (en) | Classification workflows for flexible image-based particle sorting | |
| US20220299420A1 (en) | Systems and methods for image cytometry | |
| US20220390349A1 (en) | Methods and systems for classifying flow cyometer data | |
| WO2023189819A1 (en) | Particle sorting system and particle sorting method | |
| Sharpe | A new optical configuration for flow cytometric sorting of bovine spermatozoa by sex | |
| JP6508265B2 (en) | PARTICLE SEPARATING DEVICE AND PARTICLE SEPARATING METHOD | |
| US20240165621A1 (en) | Biological particle sorting device and method for adjusting sorting condition in biological particle sorting device | |
| CN117836606A (en) | Particle sorting apparatus and particle sorting method |
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 | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20211119 Address after: 201203 No. 1525 East Cheung Road, Shanghai, Pudong New Area Applicant after: SHANGHAI MICRO ELECTRONICS EQUIPMENT (GROUP) Co.,Ltd. Address before: 201499 building 10, No. 860, Xinyang Road, Situan Town, Fengxian District, Shanghai Applicant before: Huanyi Technology (Shanghai) Co.,Ltd. |
|
| TA01 | Transfer of patent application right | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200811 |
|
| RJ01 | Rejection of invention patent application after publication |