Particle analysis system, information processing method, and computer-readable storage medium

Abstract

The invention relates to a particle analysis system, an information processing method, and a computer readable storage medium. A particle analysis system includes: a light detector that acquires light generated by irradiating particles with excitation light; and an information processing unit that outputs a spectrogram including spectral information of an autofluorescence population specified in a two-dimensional map of measurement data, each measurement data corresponding to the acquired light, and spectral information of the measurement data corresponding to the autofluorescence population specified in the two-dimensional map. And the information processing unit records spectral information of the autofluorescence population as an autofluorescence reference spectrum in the fluorescence separation process.

Description

[0001] This application is a divisional application of Chinese National Stage Application No. 202080044902.9 of PCT Application No. PCT / JP2020 / 024072, International Filing Date 19 June 2020, entitled “Particle Analysis System with Autofluorescence Spectrum Correction”, the entire contents of which are incorporated herein by reference. TECHNICAL FIELD

[0002] The present disclosure relates to a particle analysis system, an information processing method, and a program. BACKGROUND

[0003] In order to analyze properties of microparticles such as cells, microorganisms, or liposomes, an analysis method using an apparatus that measures intensities and spectra of fluorescence or scattered light emitted from microparticles (for example, a flow cytometer or the like) is used. For example, a flow cytometer irradiates microparticles flowing in a flow path with excitation light such as laser light, and fluorescence, scattered light, or the like emitted by the microparticles is detected by a light detector such as a plurality of photomultiplier tubes (PMTs). The detected light is quantified by being converted into an electric signal. By statistically processing this quantified data, characteristics of the above-described microparticles are analyzed.

[0004] For fluorescence detection in a flow cytometer, in addition to a method of selecting a plurality of light beams in a discontinuous wavelength range using a wavelength selection element such as a filter and measuring light intensities of each wavelength range, there is a method of measuring light intensities as a spectrum in a continuous wavelength range. For example, there is a technique for analyzing fluorescence intensities of each light emitting element such as a fluorescent dye with which microparticles are labeled by separating (deconvoluting) a spectrum obtained by irradiating microparticles labeled with a plurality of fluorescent dyes with laser light from a spectrum of each fluorescent dye (spectrum reference). According to this technique, the measured spectrum can be expressed as a linear sum of values obtained by multiplying a reference spectrum of each light emitting element by a predetermined coefficient. Thereby, fluorescence intensities of each fluorescent dye of the labeled microparticles can be calculated.

[0005] Analysis data of a spectral flow cytometer can be displayed in a spectral diagram, a histogram, and a two-dimensional diagram. The spectral diagram expresses a channel of a light receiving element or a detection wavelength on a horizontal axis, expresses a light intensity on a vertical axis, and expresses information on a number of microparticles (a number of events or a density) (population information) with a shade or a tint. The spectral diagram makes it possible to intuitively grasp a fluorescence spectrum of microparticles and population information.

[0006] In a spectrogram, when a logarithmic axis is used as a coordinate axis representing light intensity, the spectrum of a low-intensity particle is difficult to represent with high dispersion, and negative numbers cannot be displayed. Further, the use of a linear axis makes it difficult to determine the spectral shape of a low-intensity particle. Therefore, the following Patent Literature 1 discloses a technique of using a linear axis for data smaller than a predetermined value and using a logarithmic axis for data larger than the predetermined value.

[0007] Bibliographic List

[0008] Patent Literature

[0009] Patent Literature 1: JP 5817369 B2. SUMMARY

[0010] Technical Problem

[0011] Since many minute substances that are objects to be measured by a flow cytometer emit autofluorescence, in order to accurately analyze the fluorescence intensity, it is necessary to identify the autofluorescence of the object to be measured, and perform correction based on the identified autofluorescence.

[0012] Further, since the autofluorescence varies depending on the type of the particle, the contained substance, and the like, the object to be measured can include populations having different autofluorescence. Therefore, identifying a plurality of autofluorescence populations (AFPs) having different autofluorescence from the measurement data will increase the accuracy of the analysis, but it is not easy to separate a plurality of autofluorescence populations from the measured autofluorescence.

[0013] Therefore, the present disclosure proposes a particle analysis system, an information processing method, and a program that facilitate identification of a plurality of autofluorescence populations.

[0014] Solution to Problem

[0015] According to the present disclosure, there is provided a particle analysis system including: a light detector that acquires light generated by irradiating a particle with excitation light; and an information processing unit that outputs a spectrogram including spectral information of an autofluorescence population specified in a two-dimensional map of measurement data and spectral information of the measurement data, each of the measurement data corresponding to the acquired light, and the information processing unit records the spectral information of the autofluorescence population as an autofluorescence reference spectrum in a fluorescence separation process.

[0016] Further, according to the present disclosure, there is provided an information processing method including: outputting, by a processor, a spectrogram including spectral information of an autofluorescence population specified in a two-dimensional map of measurement data and spectral information of the measurement data, each of the measurement data corresponding to light generated by irradiating a particle with excitation light; and recording the spectral information of the autofluorescence population as an autofluorescence reference spectrum in a fluorescence separation process.

[0017] As described above, according to the present disclosure, it is possible to facilitate the recognition of a plurality of autofluorescence populations.

[0018] Note that the above effects are not necessarily restrictive, and any of the effects shown in the present specification or other effects that can be understood from the present specification can be exhibited together with or in place of the above effects. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a diagram showing a schematic configuration of a particle analysis system according to an embodiment of the present disclosure.

[0020] Figure 2 is a diagram showing a schematic configuration of a flow cytometer as an example of a measurement apparatus.

[0021] Figure 3 is a diagram showing an example of a configuration of a flow cytometer.

[0022] Figure 4 is a functional block diagram showing an example of a functional configuration of an information processing apparatus according to an embodiment of the present disclosure.

[0023] Figure 5 is a diagram showing an example of an autofluorescence screen for recognizing an autofluorescence population.

[0024] Figure 6A is a diagram showing an initial state of an autofluorescence screen.

[0025] Figure 6B is an enlarged view of a part of Step #1.

[0026] Figure 6C is a diagram showing a state in which a target data is selected.

[0027] Figure 6D is a diagram showing a two-dimensional graph of one laser light source, a VF adjustment window, and a spectral graph.

[0028] Figure 6E is a diagram for explaining display of a strip chart and a user operation.

[0029] Figure 6F is a diagram showing a state in which an autofluorescence population is separated.

[0030] Figure 6G is Figure 6F is an enlarged view of a part of Step #2 in

[0031] Figure 6H is an enlarged view of a list.

[0032] Figure 7 is a diagram showing an example of an autofluorescence screen when only five laser light sources are used.

[0033] Figure 8 is a flowchart showing a processing flow of identifying an autofluorescence population.

[0034] Figure 9 is a block diagram showing an example of a hardware configuration of an information processing apparatus according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0035] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Descriptions will be made in the following order.

[0036] 1. Embodiment

[0037] 1.1 Configuration of particle analysis system

[0038] 1.2 Configuration of measurement apparatus

[0039] 1.3 Functional configuration of information processing apparatus

[0040] 1.4 Examples of screens for identifying autofluorescence population

[0041] 1.5 Processing flow of identifying autofluorescence population

[0042] 1.6 Band chart display and user operation flow

[0043] 1.7 Effects

[0044] 1.8 Example of hardware configuration of information processing apparatus

[0045] 1.9 Summary

[0046] 1. Embodiment

[0047] 1.1 Configuration of particle analysis system

[0048] Figure 1 is a diagram showing a schematic configuration of a particle analysis system 1 according to an embodiment of the present disclosure. As shown in Figure 1 the particle analysis system 1 includes an information processing apparatus 10 and a measurement apparatus 20 that measures a spectrum corresponding to a sample S. The information processing apparatus 10 and the measurement apparatus 20 are connected through various wired or wireless networks.

[0049] Examples of the microparticles that are the sample S in the present embodiment include cells, microorganisms, and biologically relevant microparticles. The biologically relevant microparticles include chromosomes, liposomes, mitochondria, organelles (cellular organelles), and the like that constitute various cells. The cells include animal cells such as blood cells and plant cells. The microorganisms include bacteria such as Escherichia coli, viruses such as tobacco mosaic virus, and fungi such as yeast. Furthermore, the biologically relevant microparticles can include biologically relevant polymers such as nucleic acids, proteins such as enzymes, or complexes thereof.

[0050] The information processing apparatus 10 acquires measurement data of the sample S measured by the measurement apparatus 20, separates the spectrum as the acquired measurement data into a plurality of spectra, and analyzes the intensities of the separated spectra. For example, the information processing apparatus 10 separates the fluorescence spectrum of the acquired sample S into fluorescence spectra derived from a plurality of fluorescent dyes that label the sample S, and analyzes the amounts of fluorescence of the separated respective fluorescence spectra. Based on the amounts of fluorescence, the properties of the labeled microparticles can be analyzed.

[0051] In Figure 1 In the example illustrated, although a case where the information processing apparatus 10 according to the present embodiment is provided as an apparatus different from the measurement apparatus 20 is illustrated, the functions of the information processing apparatus 10 according to the present embodiment can be implemented in a computer that controls the operation of the measurement apparatus 20, or can be implemented in a computer provided in the housing of the measurement apparatus 20. The detailed configuration of the information processing apparatus 10 will be described later in detail.

[0052] The measurement apparatus 20 irradiates the sample S with laser light, detects fluorescence and scattered light from the sample S, and measures a spectrum corresponding to the sample S based on the detection results of the light. That is, the measurement apparatus 20 has a function as a measurement unit.

[0053] Hereinafter, the measurement apparatus 20 is a flow cytometer that measures a fluorescence spectrum of a sample S, and detailed description of the present technology will be given.

[0054] 1.2 Configuration of Measurement Apparatus

[0055] Next, the configuration of the measurement apparatus 20 will be described. Figure 2 is a diagram that shows a schematic configuration of a flow cytometer as an example of a measurement apparatus. Furthermore, Figure 3 is a diagram that shows an example of the structure of a flow cytometer. Figure 2 and Figure 3 The flow cytometer illustrated in

[0056] Referring to Figure 2In a flow cytometer, a laser having a wavelength capable of exciting a fluorescent dye that can be used for staining of the microparticles (sample) S is emitted from the laser light source 21 to the simply stained, multiply stained, or unstained microparticles S flowing in the microchannel 22. The light detector 23 detects fluorescence, scattered light, and the like emitted from the microparticles S irradiated with the laser light. Furthermore, although not shown in Figure 2 and Figure 3 , an optical system such as a lens for guiding the laser light to the microparticles S and an optical system for guiding the fluorescence, scattered light, and the like emitted from the microparticles S to the light detector 23 is provided in the flow cytometer.

[0057] The laser light source 21 emits laser light of a predetermined wavelength (for example, wavelengths λ = 320 nm (nanometers), 355 nm, 405 nm, 488 nm, 561 nm, 637 nm, and 808 nm). In the example of Figure 2 , one laser light source 21 is shown, and in the example of Figure 3 , N (N is a positive integer) laser light sources 21 represented by LD-1 to LD-N are shown. N is preferably 3 or more, in which the wavelengths of the laser light sources are 405 nm, 488 nm, and 637 nm. Most preferably, by using seven laser light sources 21 including wavelengths of 320 nm, 355 nm, 561 nm, and 808 nm, the excitation wavelength range of 40 or more colors of fluorescent dyes can be covered.

[0058] The N laser light sources 21 irradiate the microparticles S with excitation light on different axes. When three laser light sources are used, 405 nm is preferably arranged in the upstream direction of the flow of the microparticles S, and 808 nm and 637 nm are arranged centered on the laser light spot of 488 nm in the downstream direction of the flow of the microparticles S, and when seven laser light sources are used, 561 nm, 405 nm, and 320 nm are preferably arranged in the upstream direction of the flow of the microparticles S, and 808 nm, 355 nm, and 637 nm are arranged in the downstream direction of the flow of the microparticles S. This arrangement makes it possible to reduce crosstalk when detecting the fluorescence spectrum of each excitation wavelength.

[0059] The microchannel 22 is provided so that the microparticles S flow in a row in the flow direction. A known microchannel chip or the like is used as the microchannel 22.

[0060] Furthermore, as shown in Figure 3 , the light detector 23 includes a detector 230 and N light-receiving element units 231.

[0061] Detector 230 is a device for detecting forward-scattered light emitted from particle S. Detector 230 is implemented, for example, by a charge-coupled device (CCD), complementary metal-oxide-semiconductor (CMOS), or photodiode. Measurement data of the forward-scattered light detected by detector 230 is output to information processing device 10 according to this embodiment.

[0062] The light receiving element unit 231 is a device for detecting the fluorescence spectrum emitted from the particles S. Each light receiving element unit 231 detects the fluorescence spectrum emitted from the particles S by laser radiation from a corresponding laser source 21. In addition, some light receiving element units 231 also detect side-scattered light.

[0063] Depending on the excitation wavelength of the laser source 21, each photoreceiving element unit 231 has a detection wavelength range longer than the excitation wavelength. For example, when the excitation wavelength is 320 nm and 355 nm, the detection wavelength range is 360.5 nm to 843.8 nm, and when the excitation wavelength is 405 nm, the detection wavelength range is 413.6 nm to 843.8 nm. When the excitation wavelength is 488 nm, the detection wavelength range is 492.9 nm to 843.4 nm; when the excitation wavelength is 561 nm, the detection wavelength range is 555.3 nm to 843.8 nm; when the excitation wavelength is 638 nm, the detection wavelength range is 643.3 nm to 843.8 nm; and when the excitation wavelength is 808 nm, the detection wavelength range is 823.5 nm to 920.0 nm. As described above, spectral data can be generated using a wide detection wavelength range longer than the excitation wavelength, and the spectra corresponding to 40 or more fluorescent dyes can be separated and detected.

[0064] Spectral data is generated from each optical receiving element unit 231, and the generated spectral data is output to the information processing device 10 according to this embodiment. Furthermore, side-scattered light data is generated from some of the optical receiving element units 231, and the generated side-scattered light data is output to the information processing device 10 according to this embodiment.

[0065] In addition, such as Figure 1 As shown, the measuring device 20 includes a setting storage unit 20a, a setting storage unit 20b, and a search unit 20c. The setting storage unit 20a stores the parameters and labels set during the measurement as setting information in the setting storage unit 20b. The setting storage unit 20b stores the setting information. The search unit 20c searches for and displays the setting information using at least one of the parameters and labels selected by the user. The control unit controls the laser light source 21, photodetector 23, etc., in the measuring device 20 based on the setting information selected by the user on the display screen.

[0066] The parameters include on / off of each laser light source 21, flow rate of the microchannel 22, sensitivity adjustment value of the detector 230 and the light receiving element unit 231, threshold value as cell detection, detection time window, and the like.

[0067] The label is information about the measurement. Examples of the label include "TBNK panel", "T cell 20C", "PD-1 30C", "Prof. Yamauchi", "OMIP-15", "Euroflow", "44 colors", and the like. "TBNK panel" is an example indicating a cell type. "T cell 20C" is an example indicating a cell type and a number of colors. "PD-1 30C" is an example indicating a cell (receptor) type and a number of colors. "Prof. Yamauchi" is an example indicating a measurer or a measurer requester. "OMIP-15" is an example indicating a standard measurement protocol. "Euroflow" is an example indicating a standardized organization name. "44 colors" is an example indicating a number of colors.

[0068] By reusing the parameters stored in the setting storage unit 20b, the user can efficiently perform the setting of the parameters. Here, the configuration of any one or all of the setting saving unit 20a, the setting storage unit 20b, and the search unit 20c can be included in the information processing apparatus 10, rather than the measurement apparatus 20.

[0069] 1.3 Functional Configuration of Information Processing Apparatus

[0070] Next, the functional configuration of the information processing apparatus 10 according to the embodiment of the present disclosure will be described. Figure 4 is a functional block diagram showing an example of the functional configuration of the information processing apparatus 10 according to the embodiment of the present disclosure. As Figure 4 indicated, the information processing apparatus 10 according to the present embodiment includes a measurement data acquisition unit 101, an AFP recognition unit 102, a storage unit 110, and a UI control unit 120.

[0071] (Measurement Data Acquisition Unit)

[0072] The measurement data acquisition unit 101 acquires measurement data generated by the measurement apparatus 20 from the measurement apparatus 20. Here, the measurement data of the microparticle S acquired from the measurement apparatus 20 is, for example, autofluorescence data indicating the intensity of the forward scattering light, the side scattering light, and the spectrum generated by irradiating a plurality of unstained microparticles S with laser light. For the measurement of the forward scattering light, the side scattering light, and the spectrum of a plurality of microparticles S, there is a small but certain time width. Therefore, for example, the cumulative intensity, the maximum intensity, or the time width (detection time width) that exceeds the detection threshold value in the small time width is used as the measurement data according to the present embodiment.

[0073] The measurement data acquisition unit 101 stores the acquired measurement data in the storage unit 110. At this time, the measurement data acquisition unit 101 can associate the acquired measurement data with time information such as the date and time when the measurement data was acquired or with information related to the measurement conditions of the measuring device 20, so as to store the information in the storage unit 110.

[0074] The AFP identification unit 102 identifies autofluorescence populations by interacting with the user via the UI control unit 120. Specifically, the AFP identification unit 102 creates two-dimensional maps, spectral maps, etc., for identifying autofluorescence populations based on autofluorescence data stored in the storage unit 110, and displays them on the UI control unit 120. Then, the AFP identification unit 102 updates the storage unit 110 and the screen based on operations performed by the user on the screen displayed on the UI control unit 120, and repeats the process of having the UI control unit 120 display the updated screen to identify autofluorescence populations.

[0075] The AFP identification unit 102 includes a target selection unit 106, an AFP separation unit 107, and an AFP selection unit 108. The target selection unit 106 performs processing related to the selection of target data for identifying autofluorescent populations. The AFP separation unit 107 performs processing related to the separation of autofluorescent populations. The AFP selection unit 108 performs processing related to selecting autofluorescent populations from the separated autofluorescent populations for use in the fluorescence separation process. Fluorescence separation processing is described in JP 5540952 B2, JP5601098 B2, JP 5834584 B2, and JP 5985140 B2.

[0076] (Storage unit)

[0077] Storage unit 110 is a storage device (means) included in information processing device 10, and stores information obtained by each functional unit of information processing device 10. Furthermore, storage unit 110 appropriately outputs the stored information in response to requests from each functional unit of information processing device 10. Storage unit 110 stores, for example, autofluorescence data acquired by measurement data acquisition unit 101, data related to the processing of AFP identification unit 102, etc. Storage unit 110 also stores execution data, such as programs corresponding to various applications of UI control unit 120 for displaying various information on the display screen. Storage unit 110 appropriately stores temporary data that may occur during processing by information processing device 10. Furthermore, storage unit 110 may be equipped with various databases. These databases may be, for example, databases storing the aforementioned autofluorescence data or data related to the processing of AFP identification unit 102.

[0078] (UI control unit)

[0079] The UI control unit 120 performs display control on a display device (not shown) such as a display included in the information processing device 10 or a display device such as a display disposed outside the information processing device 10. For example, the UI control unit 120 performs display control on a screen created by the AFP identification unit 102.

[0080] The UI control unit 120 also accepts user operations on the display screen and notifies the AFP identification unit 102 of information corresponding to the accepted operations. For example, the UI control unit 120 accepts a user's gate operation and notifies the AFP identification unit 102 of information about the created gate. Furthermore, the UI control unit 120 accepts a user's selection operation and notifies the AFP identification unit 102 of the selected information.

[0081] 1.4 Example of a screen used to identify autofluorescent populations

[0082] Next, we will refer to Figures 5 to 7 An example of an autofluorescence screen used to identify autofluorescence populations is described. Figure 5 This is a diagram illustrating an example of an autofluorescence screen used to identify autofluorescence populations. (See diagram for example.) Figure 5 As shown, the autofluorescence screen 2 includes an event quantity selection section 2a for selecting the number of events and a graphic shape selection section 2b for selecting the graphic shape used to create the gating. Rectangles, ellipses, and polygons are available as graphic shapes for creating the gating.

[0083] As part of the user's operation steps, the autofluorescence screen 2 includes step #1 (corresponding to step 1 on the screen) part 3, step #2 (corresponding to step 2 on the screen) part 4, and step #3 (corresponding to step 3 on the screen) part 5. The target selection unit 106 processes step #1 part 3, the AFP separation unit 107 processes step #2 part 4, and the AFP selection unit 108 processes step #3 part 5.

[0084] Figure 6A This is a diagram showing the initial state of the autofluorescent screen 2. (Example) Figure 6A As shown, step #3 section 5 is not displayed in the initial state. In the initial state, the user selects the number of events using event quantity selection section 2a. Then, AFP identification unit 102 uses the autofluorescence data of the selected number of events to display step #1 section 3 and step #2 section 4. Note that although AFP identification unit 102 causes UI control unit 120 to display a screen, in the following text, "causing UI control unit 120 to display" is simply referred to as "display" for simplicity.

[0085] In step #1, the AFP identification unit 102 creates and displays a two-dimensional graph 31 using autofluorescence data. The user uses the target selection button 30 to select whether to use a group for searching autofluorescence populations or to use all displayed events. When a group for searching autofluorescence populations is selected (when the target selection button 30 is not selected), the user selects a graphic shape from the graphic shape selection section 2b.

[0086] AFP identification unit 102 accepts the user's selection. Note that although AFP identification unit 102 accepts the user's operation via UI control unit 120, in the following text, "accepted via UI control unit 120" is simply referred to as "accepted" for simplicity.

[0087] Figure 6B This is an enlarged view of step #1, part 3. For example... Figure 6B As shown, in the two-dimensional graph 31, the x-axis (FSC_A: forward scattering region) represents the intensity of forward scattered light, and the y-axis (SCC_A: side scattering region) represents the intensity of side scattered light. "_A" indicates that the measured value is the cumulative intensity. Furthermore, the AFP recognition unit 102 displays a message prompting the creation of a gating mechanism for identifying target data of autofluorescence populations (Step 1: Creating a target population gating mechanism for searching autofluorescence on the scattering map).

[0088] The user selects target data for identifying autofluorescence populations by gating the displayed two-dimensional graph 31. When the target data selection is accepted, the AFP identification unit 102 creates and displays a two-dimensional graph 32 of the selected target data.

[0089] Figure 6C This is a diagram showing the status of the selected target data. Figure 6C In step #1, the target selection button 30 is selected, and all events have been selected to identify autofluorescence populations. In step #2, the AFP recognition unit 102 creates and displays a two-dimensional graph 41, a virtual filter (VF) adjustment window 42, and a spectrum 43 for each laser source 21 based on the target data selected in step #1.

[0090] In the two-dimensional graph 41, the density plot or dot plot is selected by the graph selection toggle button 40. Here, the density plot represents information about the number of events using shading or hue, while the dot plot represents information without information about the number of events. VF is a filter that adjusts the wavelength range of fluorescence intensity to be displayed, and the wavelength range of fluorescence intensity to be displayed is adjusted by the VF adjustment window 42.

[0091] Figure 6D This is a diagram showing a two-dimensional image 41, a VF adjustment window 42, and a spectrum 43 of a laser source 21. (See diagram 43 for details.) Figure 6DAs shown, the x-axis (VF-320_A) of the two-dimensional graph 41 represents the intensity of light filtered by the VF, and the y-axis (SCC_A) represents the intensity of side-scattered light. The AFP recognition unit 102 updates the two-dimensional graph 41 by adjusting the wavelength range through the VF adjustment window 42. The adjustment of the VF adjustment window 42 is performed by channel or wavelength. "320" is the wavelength (nm) of the laser source 21. Here, only the two-dimensional graph 41 needs to be displayed so that the target data can be separated from the measurement data, and the two axes of the two-dimensional graph 41 can be selected from the light intensity of side-scattered or forward-scattered light or the light intensity in the wavelength range pre-selected by the VF. The two-dimensional graph 41 may have one axis representing the light intensity in a first wavelength range and another axis representing the light intensity in a second wavelength range.

[0092] In spectrum 43, the x-axis represents wavelength or channel, and the y-axis (LD 320_A) represents fluorescence intensity. "320" is the wavelength (nm) of the laser source 21. The shading of the colors indicates information about the number of events.

[0093] return Figure 6C As step #2, the AFP identification unit 102 displays a message prompting the creation of a gating mechanism for the estimated autofluorescence population (Step 2: Creating a gating mechanism for the guessed autofluorescence (AF) population on the VF / SSC plot). The user adjusts the wavelength range using the VF adjustment window 42 to gating the autofluorescence population using a two-dimensional plot 41 where the target data is divided into multiple groups. The user can use any number of the seven two-dimensional plots 41 to perform gating.

[0094] Figure 6F It is a diagram showing the state of separation of autofluorescent populations, and Figure 6G yes Figure 6F A magnified view of a portion of step #2, section 4. Figure 6G In the process, gating is performed using a two-dimensional graph 41 corresponding to a laser source 21 with wavelengths of 320 nm and 405 nm to create four gating points 45.

[0095] When the strobe 45 is created, the AFP identification unit 102 displays the strobe 45 in different colors in the two-dimensional graph 41. For example, the AFP identification unit 102 displays the corresponding four strobes 45 in red, blue, purple, and green. In addition, the AFP identification unit 102 similarly colors and updates the two-dimensional graph 32 displayed in step #1.

[0096] Furthermore, in spectral graph 43, the AFP identification unit 102 displays the average spectral intensity 46, which indicates the average spectral intensity of each gated data point, superimposed on the spectral intensity 47 of the entire target data in the same color as the gated color in 2D graph 41. In spectral graph 43, the spectral intensity 47 of the entire target data is displayed, for example, in grayscale. The user determines the autofluorescence population used in the fluorescence separation process by examining the relationship between the average spectral intensity 46 and the spectral intensity 47 of the entire target data.

[0097] In step #3, as Figure 6F As shown, the AFP identification unit 102 displays a message prompting the selection of the autofluorescence population to be used in the fluorescence separation process and the gating list 51 created in step #2 (Step 3: Select the gating to be used for autofluorescence for further analysis). Figure 6H This is a magnified view of list 51. (For example...) Figure 6H As shown, List 51 includes “Used as autofluorescence”, “Used as base”, “Gated”, “Event”, “Parent%”, and “Total%”.

[0098] "Use as autofluorescence" indicates whether the user has selected a gating group as the autofluorescent population to be used in the fluorescence separation process. Gating groups marked with a checkmark are the autofluorescent populations to be used in the fluorescence separation process. Users select the autofluorescent population to be used in the fluorescence separation process by checking "Use as autofluorescence".

[0099] "Use as Basis" indicates whether the user has selected a gate as the basic autofluorescence population in the fluorescence separation process. The snake-eye gate is the gate selected as the basic autofluorescence population. The user selects the basic autofluorescence population by marking the snake-eye gate in "Use as Basis". The fluorescence separation process includes:

[0100] 1) Subtract the spectrum of the basic autofluorescence population from the spectrum of each stained cell;

[0101] 2) Fluorescence separation is performed using a spectral reference and the spectra of an autofluorescence population other than the spectrum of the basic autofluorescence population; and

[0102] 3) As a result of fluorescence separation, the fluorescence intensity of the basic autofluorescence population is added back to the fluorescence intensity of each dye. Users typically select the autofluorescence population with the lowest fluorescence intensity as the basic autofluorescence population. Here, a basic autofluorescence population may not be selected; in this case, steps 1) and 3) are not performed, and fluorescence separation is performed in step 2) using the reference spectrum and all autofluorescence spectra to obtain the fluorescence intensity of each dye. Whether to select "Use as Basis" is up to the user. Least squares or weighted least squares is used for fluorescence separation.

[0103] "Gantry" is the name of the strobe. "AF-A", "AF-B", "AF-C", and "AF-D" are strobe names created by the AFP identification unit 102. The square to the left of the strobe name indicates the color of the strobe.

[0104] "Event" represents the number of data points selected. "Parent %" indicates the ratio of the number of selected data points to the number of selected data points in the parent generation, in %. "Total %" indicates the ratio of the number of selected data points to the total number of target data points, in %. Figure 6H In this example, since the total number of target data is "10,000" and the entire target data is selected by the parent generation, for example, when the number of data selected by "AFA" is "766", "parent generation %" is "7.66%" and "total parent generation %" is "7.66%".

[0105] Figure 5 The autofluorescence screen 2 is shown when measurements are performed using all seven laser sources 21. When some laser sources 21 are not used, the autofluorescence screen 2 includes a two-dimensional graph 41 showing the number of laser sources 21 used, a VF adjustment window 42, and a spectrum 43. Figure 7 This is a diagram illustrating an example of an autofluorescent screen 2c when only five laser light sources 21 are used. Figure 7 As shown, since the laser source 21 with wavelengths of 355nm and 808nm is not used, the two-dimensional graph 41, VF adjustment window 42 and spectrum 43 based on the measurement data using the laser source 21 with wavelengths of 355nm and 808nm are not displayed.

[0106] 1.5 Processing procedure for identifying autofluorescent populations

[0107] Next, the processing procedure for identifying autofluorescent populations will be described. Figure 8 This is a flowchart illustrating the process for identifying autofluorescent populations. For example... Figure 8As shown, the AFP identification unit 102 uses autofluorescence data to create and display a two-dimensional graph 31 with FSC_A as the x-axis and SCC_A as the y-axis (step S1). Then, the AFP identification unit 102 accepts the designation of target data through a gating performed by the user (step S2). When the designation of target data is accepted, the AFP identification unit 102 displays a two-dimensional graph 32 of the target data.

[0108] Then, the AFP recognition unit 102 creates and displays a two-dimensional plot 41, a VF adjustment window 42, and a spectrum 43 of the target data (step S3). Note that when the user's channel specification is accepted using the VF adjustment window 42, the AFP recognition unit 102 updates the two-dimensional plot 41. Furthermore, when the user's operation on the spectrum 43 is accepted, the AFP recognition unit 102 updates the spectrum 43. Then, the AFP recognition unit 102 accepts gating from the user's autofluorescence population (step S4). When gating from the user's autofluorescence population is accepted, the AFP recognition unit 102 updates the spectrum 43, the two-dimensional plot 42, and the two-dimensional plot 41.

[0109] Then, when the user completes the gating of the autofluorescence population, the AFP recognition unit 102 displays the gating list 51 (step S5) and accepts the selection of the autofluorescence population from the user in the gating list 51 (step S6). Then, the AFP recognition unit 102 stores the information of the selected autofluorescence population in the storage unit 110 (step S7).

[0110] As described above, the AFP identification unit 102 can make it easy for the user to select an autofluorescence population by displaying autofluorescence screens 2 and 2c, including two-dimensional graphs 31, 32 and 41, a spectrum 43, a gating list 51, etc.

[0111] 1.6. Strip chart display and user operation flow

[0112] The AFP separation unit 107 can control the display of spectra of measurement data and autofluorescence data. Here, as the number of laser sources 21 installed in the measurement device 20 increases, a wide screen area is needed to display the spectra corresponding to each laser source 21. Furthermore, because processing such as axis switching is required for each spectra, it is necessary to jointly display and control the spectra corresponding to multiple laser sources. Therefore, the AFP separation unit 107 can control the display of the bandgap 44, in which the spectra corresponding to the laser sources 21 used for measurement are displayed side-by-side.

[0113] Figure 6E This is a diagram used to illustrate the display of the strip chart 44 and user operations. For example... Figure 6EAs shown in the strip diagram 44, the fluorescence intensity obtained by irradiating each laser source 21 with excitation light can be displayed side-by-side as a spectrum. The horizontal axis represents the light intensity, and the vertical axis represents the channel of the light receiving element unit 231 corresponding to each laser source. Here, the horizontal axis does not provide the same channel storage width for all laser sources 21, but rather sets the channel storage width according to the light receiving element unit 231 corresponding to each laser source 21, thereby reducing the display area.

[0114] In addition, such as Figure 6E As shown, the user can select the group used to display the bandgap 44, select the display parameters for the y-axis of the bandgap 44, and adjust the display range of the y-axis in the bandgap 44. Here, in the display parameters, the display of the spectrum is related to any one of the area (cumulative intensity), height (maximum intensity), or width (detection time width). The AFP separation unit 107 updates the bandgap 44 according to the selection of display parameters and the adjustment of the display range. Therefore, the user does not need to select parameters for each laser source 21, select display targets, etc., and can easily grasp the fluorescence spectrum information of the particles.

[0115] Furthermore, the band plot 44 allows gating to be set by the user and can display a two-dimensional plot, a spectrum plot 43, and a band plot 44 according to the set gating.

[0116] 1.7 Effects

[0117] As described above, according to this embodiment, the target selection unit 106 displays a two-dimensional graph 31 and accepts the user's selection of autofluorescence data for identifying autofluorescence populations. Then, the AFP separation unit 107 displays a two-dimensional graph 41 with multiple optical axes, a VF adjustment window 42, and a spectrum 43, and accepts the autofluorescence populations separated by the user in the two-dimensional graph 41. The AFP separation unit 107 then updates the two-dimensional graph 41 with the color of the autofluorescence population to be separated and superimposes the average spectral intensity 46 of the autofluorescence population to be separated onto the spectrum 43, displaying it in different colors. Here, different colors indicate that one of the hue, brightness, and saturation is different. Then, the AFP selection unit 108 displays a list 51 and prompts the user to select the autofluorescence population for fluorescence separation processing. Therefore, the user can easily identify the autofluorescence population for fluorescence separation processing.

[0118] In this embodiment, since the AFP selection unit 108 accepts the autofluorescence population selected from list 51 as the basic autofluorescence population in the fluorescence separation process, the user can select the basic autofluorescence population and select the autofluorescence population.

[0119] Furthermore, in this embodiment, the measuring device 20 includes N laser light sources 21 for irradiating the microparticle S with excitation light on different axes, and N light receiving element units 231 for detecting the fluorescence spectrum emitted from the microparticle S by the laser radiation from the corresponding laser light sources 21. Therefore, the measuring device 20 can effectively collect abundant fluorescence spectral data.

[0120] Furthermore, in this embodiment, since the measuring device 20 stores parameters and tags used for measurement, the user can efficiently perform measurements by reusing previously used parameters.

[0121] 1.8 Example of hardware configuration for information processing equipment

[0122] Next, we will refer to Figure 9 The hardware configuration of an information processing apparatus according to embodiments of the present disclosure is described. Figure 9 This is a block diagram illustrating an example hardware configuration of an information processing apparatus according to an embodiment of the present disclosure. The illustrated information processing apparatus 900 can implement, for example, the information processing apparatus 10 in the above embodiment.

[0123] Information processing device 900 includes a central processing unit (CPU) 901, a read-only memory (ROM) 903, and a random access memory (RAM) 905. Information processing device 900 also includes a host bus 907, a bridge 909, an external bus 911, an interface 913, an input device 915, an output device 917, a storage device 919, a driver 921, a connection port 925, and a communication device 929. Instead of or together with the CPU 901, information processing device 900 may include processing circuitry referred to as a digital signal processor (DSP) or an application-specific integrated circuit (ASIC).

[0124] The CPU 901 functions as an arithmetic processing and control device, and controls all or part of the operation of the information processing device 900 according to various programs recorded in the ROM 903, RAM 905, storage device 919, or removable recording medium 923. For example, in the above embodiment, the CPU 901 controls the overall operation of corresponding functional units included in the information processing device 10. The ROM 903 stores programs, calculation parameters, etc., used by the CPU 901. The RAM 905 mainly stores programs used in the execution of the CPU 901, parameters that are appropriately changed during execution, etc. The CPU 901, ROM 903, and RAM 905 are interconnected via a host bus 907 consisting of internal buses (such as the CPU bus). Furthermore, the host bus 907 is connected to an external bus 911, such as a peripheral component interconnect / interface (PCI) bus, via a bridge 909.

[0125] Input device 915 is, for example, a user-operated device such as a mouse, keyboard, touch panel, button, switch, and joystick. Input device 915 may be, for example, a remote control device using infrared or other radio waves, or it may be an external connection device 927, such as a mobile phone corresponding to the operation of information processing device 900. Input device 915 includes input control circuitry that generates input signals based on user input information and outputs the generated signals to CPU 901. The user operates input device 915 to input various data into information processing device 900 and instruct processing operations.

[0126] The output device 917 is configured with a means capable of visually or audibly notifying the user of the information obtained. The output device 917 may be, for example, a display device such as an LCD, PDP, or OLED, an acoustic output device such as a speaker or headphones, a printer, etc. The output device 917 outputs the results obtained through the processing of the information processing device 900 as video in the form of text or images, or as acoustic sound.

[0127] Storage device 919 is an example of a storage unit configured as an information processing device 900 for data storage. Storage device 919 is configured, for example, as a magnetic storage unit device such as a hard disk drive (HDD), semiconductor storage device, optical storage device, or magneto-optical storage device. Storage device 919 stores programs executed by CPU 901, various data, and various data acquired from external sources. Storage device 919 can implement the functions of storage unit 110 according to the above embodiment.

[0128] Drive 921 is a reader / writer for a removable recording medium 923, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, and is either built into or externally attached to the information processing device 900. Drive 921 reads information recorded on the mounted removable recording medium 923 and outputs that information to RAM 905. Drive 921 also writes records to the mounted removable recording medium 923.

[0129] Connection port 925 is used to directly connect devices to information processing device 900. Connection port 925 can be, for example, a Universal Serial Bus (USB) port, an IEEE 1394 port, a Small Computer System Interface (SCSI) port, etc. Alternatively, connection port 925 can be an RS-232C port, an optical audio terminal, an High Definition Multimedia Interface (HDMI) (registered trademark) port, etc. By connecting external connection device 927 to connection port 925, various data can be exchanged between information processing device 900 and external connection device 927.

[0130] The communication device 929 is, for example, a communication interface configured to connect to a communication network NW. The communication device 929 can be, for example, a communication card for wired or wireless local area networks (LANs), Bluetooth (registered trademark), or wireless USB (WUSB). Furthermore, the communication device 929 can be a router for optical communication, a router for asymmetric digital subscriber line (ADSL), a modem for various types of communication, etc. The communication device 929 uses predetermined protocols such as TCP / IP to send signals to the Internet or another communication device, and receives signals from the Internet or another communication device. The communication network NW connected to the communication device 929 is a network connected via wired or wireless means, and is, for example, the Internet, a home LAN, infrared communication, radio wave communication, satellite communication, etc.

[0131] 1.9 Summary

[0132] Preferred embodiments of the present disclosure have been described in detail with reference to the accompanying drawings; however, the scope of the present disclosure is not limited to such examples. It will be apparent to those skilled in the art that various variations or modifications within the scope of the technical concept described in the claims can be conceived. It should be understood that these variations or modifications also fall within the scope of the present disclosure.

[0133] For example, although the particle analysis system 1 in the above embodiment is configured to include an information processing device 10 and a measuring device 20, the present technology is not limited to such an example. For example, the information processing device 10 may have the functions of the measuring device 20 (measurement function). In this case, the particle analysis system 1 is implemented by the information processing device 10. Furthermore, the measuring device 20 may have the functions of the information processing device 10 (data acquisition function, autofluorescence recognition function, and UI control function). In this case, the particle analysis system 1 is implemented by the measuring device 20. Furthermore, the measuring device 20 may have some of the functions of the information processing device 10, and the information processing device 10 may have some of the functions of the measuring device 20. Furthermore, the information processing device 10 may only have the autofluorescence recognition function. In this case, other functions can be implemented by another information processing device, etc.

[0134] Computer programs can also be created to enable hardware such as CPU, ROM, and RAM contained in the information processing device to perform functions equivalent to the corresponding configuration of the aforementioned information processing device. Storage media for storing the computer programs are also provided.

[0135] Furthermore, the effects described in this specification are illustrative or exemplary only, and not restrictive. That is, in addition to or instead of the effects described above, the technology according to this disclosure may exhibit other effects that are obvious to those skilled in the art from the description in this specification.

[0136] The following configurations are also within the scope of this disclosure. (1)

[0138] An information processing device, comprising:

[0139] The AFP separation unit displays a two-dimensional plot with autofluorescence intensity and side-scattered light intensity as axes, and a spectrum for autofluorescence data. It also displays the spectral intensity of a specified autofluorescence population in the two-dimensional plot, where the spectral intensity of the autofluorescence population is superimposed on the spectrum. (2)

[0141] According to the information processing device of (1), the AFP separation unit displays a two-dimensional plot and a spectral plot relative to each optical axis for autofluorescence data measured using multiple optical axes, and displays the spectral intensity of a specified autofluorescence population in the multiple two-dimensional plots, wherein the spectral intensity of the autofluorescence population is superimposed on the spectral plot. (3)

[0143] According to the information processing device of (1) or (2), wherein the AFP separation unit accepts parameter change operation and updates the spectrum, the parameter specifying any one of the cumulative intensity, maximum intensity and detection time width in the measurement time width relative to the spectral intensity of the spectrum. (4)

[0145] According to the information processing device of (1), (2) or (3), wherein the AFP separation unit superimposes and displays the spectral intensity of autofluorescence data and the average spectral intensity of autofluorescence population in different colors. (5)

[0147] The information processing apparatus according to any one of (1) to (4) further includes an AFP selection unit that displays a list of autofluorescent populations and accepts the selection of autofluorescent populations for fluorescence separation processing and the selection of autofluorescent populations used as basic autofluorescent populations in fluorescence separation processing. (6)

[0149] An information processing method, comprising:

[0150] The processor displays a two-dimensional plot with autofluorescence intensity and side-scattered light intensity as axes, and a spectral plot for autofluorescence data. It also displays the spectral intensity of a specified autofluorescence population in the two-dimensional plot, where the spectral intensity of the autofluorescence population is superimposed on the spectral plot. (7)

[0152] A program that enables a computer to be used as an AFP separation unit, which displays a two-dimensional plot with autofluorescence intensity and side-scattered light intensity as axes and a spectrum for autofluorescence data, and displays the spectral intensity of a specified autofluorescence population in the two-dimensional plot, wherein the spectral intensity of the autofluorescence population is superimposed on the spectrum. (8)

[0154] An information processing system, comprising:

[0155] A measuring device includes multiple measuring units that illuminate the object to be measured using light along multiple optical axes and measure the spectrum related to the emission of the object; and

[0156] An information processing device includes an AFP separation unit that displays a two-dimensional plot with the autofluorescence intensity and side-scattered light intensity at a specific wavelength as axes, and a spectral plot about each optical axis of the autofluorescence data measured by a measuring device, and displays the spectral intensity of a specified autofluorescence population in the two-dimensional plot, wherein the spectral intensity of the autofluorescence population is superimposed on the spectral plot. (9)

[0158] According to the information processing system in (8), where,

[0159] The measuring equipment also includes:

[0160] Storage unit, which stores the parameters used for measurement. (10)

[0162] A particle analysis system, comprising:

[0163] A photodetector acquires light generated by irradiating particles with excitation light; and

[0164] The information processing unit outputs a spectrum, which includes the spectral information of the autofluorescence population specified in the two-dimensional graph of the measurement data and the spectral information of the measurement data. Each measurement data corresponds to the acquired light, and the information processing unit records the spectral information of the autofluorescence population as an autofluorescence reference spectrum during the fluorescence separation process. (11)

[0166] According to the particle analysis system of (10), where,

[0167] One axis of the two-dimensional graph represents the light intensity within a predetermined wavelength range, and the information processing unit outputs the two-dimensional graph. (12)

[0169] According to the particle analysis system of (11), one axis of the two-dimensional graph represents the light intensity within a predetermined wavelength range, and the other axis represents the light intensity of the scattered light. (13)

[0171] According to the particle analysis system of (10), (11) or (12), where,

[0172] The photodetector includes a light receiving element unit, wherein one axis of the spectrum represents the channel or detection wavelength of the light receiving element unit, and the other axis represents the light intensity. (14)

[0174] According to any one of (10) to (13) of the particle analysis system, where,

[0175] The photodetector acquires light generated by irradiating particles with multiple excitation beams of different wavelength ranges, and

[0176] Two-dimensional plots and spectra are displayed in the same number as multiple excitation beams. (15)

[0178] According to any one of (10) to (14) of the particle analysis system, wherein the spectral information of the autofluorescence population is the average value of the spectral information corresponding to the measurement data of the particles included in the autofluorescence population. (16)

[0180] According to any one of (10) to (15) of the particle analysis system, where,

[0181] Specify multiple autofluorescent populations in the two-dimensional plot, and

[0182] The information processing unit outputs the spectral information of multiple autofluorescence populations as a list, and records the spectral information of the autofluorescence population specified in the list as the autofluorescence reference spectrum. (17)

[0184] According to any one of (10) to (16), a particle analysis system is provided, wherein a spectrum is displayed such that the spectral information of the autofluorescent population and the spectral information of the measurement data have different colors. (18)

[0186] According to any one of (10) to (17) of the particle analysis system, where,

[0187] A photodetector captures the fluorescence generated by irradiating particles labeled with a fluorescent dye with excitation light, and

[0188] The information processing unit obtains the fluorescence intensity information of the fluorescent dye by performing fluorescence separation processing on the spectral information of the measurement data corresponding to the acquired fluorescence using the recorded autofluorescence reference spectrum. (19)

[0190] According to the particle analysis system of (18), fluorescence separation is performed by using least squares or weighted least squares with a spectral reference including the recorded autofluorescence reference spectrum. (20)

[0192] A particle analysis system based on any one of (10) to (19), wherein the particle is a cell. (twenty one)

[0194] The particle analysis system according to any one of (10) to (20) also includes:

[0195] Irradiation unit, irradiating excitation light; and

[0196] The flow path section is where particles flow through. (twenty two)

[0198] An information processing method, comprising:

[0199] Through processor

[0200] The output spectrum includes spectral information of the autofluorescence population specified in a two-dimensional plot of the measurement data and the spectral information of the measurement data, each measurement corresponding to the light generated by irradiating the particles with excitation light; and

[0201] The spectral information of the autofluorescence population was recorded during the fluorescence separation process as an autofluorescence reference spectrum. (twenty three)

[0203] A program that enables a computer to function as:

[0204] The information processing unit outputs a spectrum, which includes spectral information of the autofluorescence population specified in a two-dimensional plot of the measurement data and the spectral information of the measurement data. Each measurement data corresponds to the light generated by irradiating the particle with excitation light. The information processing unit also records the spectral information of the autofluorescence population as an autofluorescence reference spectrum during the fluorescence separation process.

[0205] At least one axis of the two-dimensional graph represents the light intensity corresponding to the light generated by any one of the multiple excitation beams.

[0206] Reference tag list

[0207] 1. Particle Analysis System

[0208] 2.2c autofluorescent screen

[0209] 3. Step #1

[0210] 4. Step #2

[0211] 5. Step #3

[0212] 10. Information processing equipment

[0213] 20 Measuring equipment

[0214] 20a Set storage unit

[0215] 20b Setting up storage units

[0216] 20c Search Unit

[0217] 21 Laser source

[0218] 22 microchannels

[0219] 23. Photodetector

[0220] 31 Two-dimensional diagram

[0221] 41 Two-dimensional diagram

[0222] 42 VF Adjustment Window

[0223] 43. Spectrum

[0224] 44. Strip chart

[0225] 45. Select

[0226] 46 Average spectral intensity

[0227] 47 Spectral Intensity

[0228] 51 List

[0229] 101 Measurement Data Acquisition Unit

[0230] 102 AFP identification unit

[0231] 106 Target Selection Unit

[0232] 107 AFP Separation Unit

[0233] 108 AFP Selection Unit

[0234] 110 storage units

[0235] 120 UI control unit

[0236] 230 detector

[0237] 231 Optical receiving element unit.

Claims

1. A particle analysis system, comprising: A photodetector acquires the light generated by irradiating particles with excitation light; as well as The information processing unit outputs a spectrum, which includes the spectral information of the autofluorescence population specified in a two-dimensional plot of the measurement data and the spectral information of the measurement data. Each measurement data corresponds to the acquired light. Furthermore, the information processing unit records the spectral information of the autofluorescence population as an autofluorescence reference spectrum during fluorescence separation processing. in, Multiple autofluorescent populations are specified in the two-dimensional diagram, and The information processing unit outputs a list of spectral information for multiple autofluorescence populations, and records the spectral information of a specified autofluorescence population in the list as an autofluorescence reference spectrum. Select one or more of the autofluorescence populations from the list for use in the fluorescence separation process, and The information processing unit performs the fluorescence separation process based on the autofluorescence population selected from the list.

2. The particle analysis system according to claim 1, wherein, One axis of the two-dimensional graph represents the light intensity within a predetermined wavelength range, and The information processing unit outputs the two-dimensional image.

3. The particle analysis system according to claim 2, wherein, One axis of the two-dimensional graph represents the light intensity within a predetermined wavelength range, and the other axis represents the light intensity of the scattered light.

4. The particle analysis system according to claim 1, wherein, The photodetector includes a light receiving element unit, and One axis of the spectrum represents the channel or detection wavelength of the light receiving element unit, and the other axis represents the light intensity.

5. The particle analysis system according to claim 1, wherein, The photodetector acquires light generated by irradiating the particle with multiple excitation beams of different wavelength ranges, and The two-dimensional plot and the spectrum are displayed in the same number as the plurality of excitation beams.

6. The particle analysis system according to claim 1, wherein, The spectral information of the autofluorescence population is the average value of the spectral information corresponding to the measurement data of the particles included in the autofluorescence population.

7. The particle analysis system according to claim 1, wherein, The spectrum is displayed such that the spectral information of the autofluorescent population and the spectral information of the measurement data have different colors.

8. The particle analysis system according to claim 1, wherein, The photodetector acquires the fluorescence generated by irradiating particles labeled with a fluorescent dye with the excitation light, and The information processing unit obtains the fluorescence intensity information of the fluorescent dye by performing fluorescence separation processing on the spectral information of the measurement data corresponding to the acquired fluorescence using the recorded autofluorescence reference spectrum.

9. The particle analysis system according to claim 8, wherein, The fluorescence separation process is performed using a least-squares method or a weighted least-squares method that includes a spectral reference of the recorded autofluorescence reference spectrum.

10. The particle analysis system according to claim 1, wherein, The particles are cells.

11. The particle analysis system according to claim 1, further comprising: The irradiation unit irradiates the excitation light; as well as The particles flow through the flow path section.

12. An information processing method, comprising: Through processor The output spectrum includes spectral information of an autofluorescent population specified in a two-dimensional plot of the measurement data and the spectral information of the measurement data, each measurement corresponding to light generated by irradiating the particles with excitation light; and The spectral information of the autofluorescence population is recorded during the fluorescence separation process as an autofluorescence reference spectrum. in, Multiple autofluorescent populations are specified in the two-dimensional diagram, and Output the spectral information of multiple autofluorescent populations as a list, and record the spectral information of the autofluorescent population specified in the list as an autofluorescence reference spectrum. Select one or more of the autofluorescence populations from the list for use in the fluorescence separation process, and The fluorescence separation process is performed based on the autofluorescent population selected from the list.

13. A computer-readable storage medium storing a program, which, when executed, causes a computer to function as: The information processing unit outputs a spectrum, which includes spectral information of an autofluorescent population specified in a two-dimensional plot of the measurement data and the spectral information of the measurement data. Each measurement data corresponds to light generated by irradiating a particle with excitation light. The information processing unit records the spectral information of the autofluorescent population as an autofluorescence reference spectrum during fluorescence separation processing. At least one axis of the two-dimensional graph represents the light intensity corresponding to the light generated by any one of the plurality of excitation beams. in, Multiple autofluorescent populations are specified in the two-dimensional diagram, and The information processing unit outputs a list of spectral information for multiple autofluorescence populations, and records the spectral information of a specified autofluorescence population in the list as an autofluorescence reference spectrum. Select one or more of the autofluorescence populations from the list for use in the fluorescence separation process, and The information processing unit performs the fluorescence separation process based on the autofluorescence population selected from the list.

Images