Information processing apparatus, information processing method, storage medium, and optical measurement system

Abstract

The present invention sets a suitable fluorescence separation method for an object to be measured. An information processing apparatus according to an embodiment includes a separation unit (14) that calculates, from a fluorescence signal measured from a biological sample, fluorescence intensities of one or more fluorescences emitted from one or more fluorescent dyes and auto-fluorescence of the biological sample, by using a calculation using a least square method, the method using a fluorescence spectral reference of the one or more fluorescent dyes and a spontaneous fluorescence spectrum of the biological sample labeled with the fluorescent dyes. In the calculation using the least square method, upper and lower limit values of the fluorescence intensities are set for the one or more fluorescences and the auto-fluorescence.

Description

Technical Field

[0001] This disclosure relates to information processing apparatus, information processing method, storage medium, and optical measurement system. Background Technology

[0002] Flow cytometry is widely used when analyzing proteins in biologically relevant microparticles (hereinafter referred to as microparticles), such as cells, microorganisms, or liposomes. Flow cytometry is a method of analyzing multiple microparticles one by one by irradiating them with a laser beam (excitation beam) of a specific wavelength through a flow path and detecting the fluorescent beam or scattered beam emitted from each microparticle. In this flow cytometry, the type, size, structure, etc. of each microparticle can be determined by converting the light detected by a photodetector into an electrical signal for quantification and performing statistical analysis.

[0003] In addition, in recent years, next-generation flow cytometers, such as spectroscopic flow cytometers, have been developed that can be used without worrying about leakage, even without deploying many highly sensitive photodetectors.

[0004] Unlike traditional flow cytometers, spectroscopic flow cytometers do not have a configuration that sets up a high-sensitivity photodetector for a single fluorescent dye, and therefore can obtain a large amount of fluorescence information from a single particle. Consequently, various fluorescence separation processes can be used to extract fluorescence information from spectroscopic flow cytometry.

[0005] Reference List

[0006] Patent documents

[0007] Patent Document 1: JP2012-52985A Summary of the Invention

[0008] Technical issues

[0009] However, in flow cytometry, variations exist in fluorescence separation performance, processing time, reliability, and result stability depending on the instrument's performance and the type of microparticles being measured. Therefore, it is difficult to determine a suitable fluorescence separation method based on the analyte.

[0010] Therefore, this disclosure provides an information processing apparatus, information processing method, program, and optical measurement system that enable the setting of a suitable fluorescence separation method according to the object to be measured.

[0011] Solution to the problem

[0012] The information processing apparatus according to an embodiment includes a separation unit that calculates the fluorescence intensity of one or more fluorescent beams and autofluorescent beams emitted from a biological sample labeled with one or more fluorescent dyes and the biological sample, respectively, using a least-squares arithmetic operation. The least-squares method uses a fluorescence spectral reference for each fluorescent dye and the autofluorescence spectrum of the biological sample. In the arithmetic operation using the least-squares method, an upper limit and a lower limit value for the fluorescence intensity are set for each of the one or more fluorescent beams and the autofluorescent beams. Attached Figure Description

[0013] Figure 1 This is a schematic diagram illustrating an example configuration of a spectroscopic flow cytometer used in the embodiment.

[0014] Figure 2 It is shown Figure 1 A block diagram illustrating a schematic configuration example of a flow cytometer.

[0015] Figure 3 This is a block diagram illustrating a schematic configuration example of an information processing system according to this embodiment.

[0016] Figure 4 This is a diagram used to illustrate the outline of the demixing according to the implementation method.

[0017] Figure 5 This is a graph showing an example of the spectral information and standard deviation obtained when unstained microparticles are used as unstained samples.

[0018] Figure 6 This is a diagram illustrating an example of a reference spectrum that does not include autofluorescence.

[0019] Figure 7 This is a diagram illustrating an example of a reference spectrum that includes an autofluorescence spectrum.

[0020] Figure 8 This is a two-dimensional graph showing the unmixing results when a reference spectrum excluding autofluorescence is used.

[0021] Figure 9 This is a two-dimensional graph showing the unmixing results when using a reference spectrum that includes autofluorescence.

[0022] Figure 10 This is a diagram illustrating examples of demixing results when using a reference spectrum that includes only the autofluorescence spectrum and when using a reference spectrum that includes both the autofluorescence spectrum of the fluorescent dye and the fluorescence spectrum reference.

[0023] Figure 11A diagram illustrating an example of a constrained reference spectrum according to this embodiment;

[0024] Figure 12 This is a flowchart illustrating an example of the automatic determination operation of the autofluorescence correction parameter ε according to this embodiment.

[0025] Figure 13 This is a diagram (part 1) used to explain the change in fluorescence separation performance when the autofluorescence correction parameter ε is changed according to the embodiment.

[0026] Figure 14 This is a diagram (part 2) used to explain the change in fluorescence separation performance when the autofluorescence correction parameter ε is changed according to the embodiment.

[0027] Figure 15 This is a diagram (part 3) used to explain the change in fluorescence separation performance when the autofluorescence correction parameter ε is changed according to the embodiment.

[0028] Figure 16 This is a graph showing the change in the standard deviation of the autofluorescence amount obtained from unstained samples when the autofluorescence correction parameter ε is varied with different predetermined widths Δ.

[0029] Figure 17 This is a diagram (example) showing the fluorescence separation performance when no penalty term is provided and the autofluorescence spectrum is unrestricted, and when a penalty term is provided and the autofluorescence spectrum is restricted.

[0030] Preferred embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Note that components having substantially the same functional configuration are denoted by the same reference numerals in this specification and the drawings, and redundant descriptions are omitted. Detailed Implementation

[0031] Note that the descriptions will be given in the following order.

[0032] 1. Introduction

[0033] 2. Example

[0034] 2.1 Overview of Flow Cytometry

[0035] 2.2 Schematic configuration example of a spectroscopic flow cytometer

[0036] 2.3 Illustrative Configuration Example of an Information Processing System

[0037] 2.4 Regarding unmixing

[0038] 2.5 Optimization of Fixed Noise for Each Measurement Channel

[0039] 2.6 Regarding finite autofluorescence correction

[0040] 2.7 Automatic Determination of Limited Autofluorescence Correction Parameters

[0041] 2.8 Functions and Effects

[0042] 1. Introduction

[0043] In flow cytometry, both in fundamental medicine and clinical settings, multicolor analysis using multiple fluorescent dyes has become widespread to advance comprehensive interpretation. However, when multiple fluorescent dyes are used in a single measurement, as in multicolor analysis, light from dyes other than the target dye leaks into individual photodetectors, potentially reducing analytical accuracy. Therefore, in flow cytometry compatible with multicolor analysis, it is conceivable to perform fluorescence correction to extract only the target light information from the target fluorescent dye.

[0044] Fluorescence correction is, for example, performing corrections to subtract light that has leaked in order to obtain light from the target fluorescent dye.

[0045] However, in the case of fluorescent dyes with similar spectra, there is a large leakage to the photodetector, so fluorescence correction cannot be performed in some cases.

[0046] As a solution to this problem, for example, the use of spectral flow cytometry can be envisioned. Spectral flow cytometry is a system that analyzes the fluorescence amount of each particle by deconvolving (demixing) fluorescence data measured from the particles using spectral information from a fluorescent dye used for staining, and includes an array of highly sensitive photodetectors for detecting the spectrum instead of the many highly sensitive photodetectors included in conventional flow cytometers.

[0047] As described above, this type of spectroscopic flow cytometer can obtain a large amount of fluorescence information from a single particle. Therefore, various fluorescence separation processes can be used to obtain fluorescence information from the spectroscopic flow cytometer.

[0048] However, variations exist in fluorescence separation performance, processing time, reliability, and result stability depending on the properties of the flow cytometer itself and the particles being measured. Therefore, it is difficult to determine a suitable fluorescence separation method for each analyte.

[0049] Furthermore, many existing spectroscopic flow cytometers are configured to allow users to easily operate them by limiting the degree of freedom of parameters to a range controllable by a typical user. Therefore, there are instances where the separation capability of the fluorescent dyes originally inherent in the spectroscopic flow cytometer cannot be maximized.

[0050] Therefore, the following embodiments propose an information processing device, information processing method, program, and optical measurement system, wherein the separation capability of fluorescent dyes is further improved by enabling the setting of a suitable fluorescence separation method according to the object to be measured.

[0051] 2. Example

[0052] The first embodiment of this disclosure will be described in detail below with reference to the accompanying drawings.

[0053] 2.1 Overview of Flow Cytometry

[0054] The flow cytometer according to this embodiment can be a device that analyzes each sample using an analytical method called flow cytometry. In a flow cytometer, the sample is labeled with a fluorescent reagent that emits light under specific conditions, and the emitted light is collected as fluorescence information when the sample is irradiated with an excitation beam. Cells can be analyzed from this fluorescence information.

[0055] In a typical flow cytometer, fluorescent beams emitted from the sample are segmented and extracted for each wavelength range using optical filters, and the data obtained by measuring the fluorescence is used as information about the fluorescent dye (corresponding to the following fluorescent dye information).

[0056] Simultaneously, in a spectroscopic flow cytometer, a spectrometer including a prism separates fluorescent beams of light at various wavelengths without using optical filters and measures the intensity of light at each wavelength, thereby obtaining spectral information of the light emitted from the sample. Hereinafter, the measured spectral information will be referred to as the measurement spectrum. Then, using a fluorescence spectral reference, this measurement spectrum for each fluorescent dye is separated using a method called spectral unmixing (hereinafter simply referred to as unmixing).

[0057] Here, the fluorescence spectral benchmark is the spectral information used as a reference for each fluorescent dye, and can be, for example, the spectral information of the fluorescent component measured from a sample labeled with a single fluorescent dye (hereinafter also referred to as a single-stained sample). Furthermore, the definition of the fluorescence spectral benchmark may include, for example, the spectral information of the autofluorescent component measured from an unlabeled sample (hereinafter also referred to as an unstained sample) (hereinafter referred to as the autofluorescence spectrum). As a fluorescence spectral benchmark, values ​​actually measured by a flow cytometer can be used, or catalog values ​​provided by the fluorescent dye supplier can be used, etc.

[0058] In this embodiment, demixing is a method for obtaining fluorescence dye information (e.g., fluorescence intensity) of each fluorescent dye from a measurement spectrum by using a linear sum of the fluorescence spectral references of each fluorescent dye and approximating the measurement spectrum measured by a flow cytometer. The fluorescence dye information of each fluorescent dye obtained through demixing is then used for analysis of samples such as cells.

[0059] It should be noted that the fluorescence signal in this specification can be defined as a concept that includes both the measured spectrum and the information of the fluorescent dye.

[0060] In this embodiment, a spectroscopic flow cytometer capable of acquiring both measurement spectrum and fluorescent dye information is exemplified as an optical measurement device. However, this disclosure is not limited to this, and a conventional flow cytometer capable of acquiring fluorescent dye information can also be used.

[0061] In flow cytometers, methods such as microchip methods, droplet methods, cuvette methods, and flow cell methods exist for providing samples to observation points (hereinafter referred to as points) along the flow path. In this embodiment, a flow cytometer using the microchip method (partially, the flow cell method) is illustrated, but this disclosure is not limited thereto, and flow cytometers using other supply methods may also be used.

[0062] Furthermore, flow cytometers include analyzer types for analyzing samples (such as cells) and cell sorter types for analyzing and sorting samples. In this embodiment, an analyzer-type flow cytometer is illustrated, but this disclosure is not limited thereto, and a classifier-type flow cytometer may also be used.

[0063] Furthermore, this disclosure is not limited to flow cytometers, but can be various optical measurement devices that utilize an excitation beam to illuminate a sample and analyze the sample based on its fluorescence. For example, this disclosure can be a microscope for acquiring images of samples such as tissue sections on a glass slide.

[0064] 2.2 Schematic configuration example of a spectroscopic flow cytometer

[0065] Figure 1 This is a schematic diagram illustrating a illustrative configuration example of the spectroscopic flow cytometer (hereinafter simply referred to as a flow cytometer) used in this embodiment. Furthermore, Figure 2 It shows Figure 1 A block diagram illustrating a schematic configuration example of a flow cytometer. Note that, for ease of reference, [the diagram is missing here]. Figure 1 and Figure 2 Some optical elements are omitted in each of the diagrams.

[0066] like Figure 1 and Figure 2 As shown, the flow cytometer 1 according to this embodiment includes a light source unit 100, a demultiplexing optical system 150, a scattered light detection unit 130 and a fluorescence detection unit 140, and uses a microchip 120 to detect light from a sample supplied to a predetermined flow path.

[0067] The sample is, for example, a biologically derived particle, such as a cell, microorganism, or bioassociated particle, and includes groups of multiple biologically derived particles. The sample can be, for example, cells, such as animal cells (e.g., blood cells) or plant cells; microorganisms, such as bacteria including *Escherichia coli*, viruses including tobacco mosaic virus, or fungi including yeast; bioassociated particles of cells that constitute chromosomes; liposomes, mitochondria, exogenous bodies, or various organelles; or biologically derived microparticles, such as bioassociated polymers including nucleic acids, proteins, lipids, glycans, and their complexes. Furthermore, the sample broadly includes synthetic particles such as latex particles, gel particles, or industrial particles. Additionally, industrial particles can be, for example, organic or inorganic polymer materials, or metals. Organic polymer materials include polystyrene, styrene-divinylbenzene, polymethyl methacrylate, etc. Inorganic polymer materials include glass, silica, magnetic materials, etc. Metals include colloidal gold, aluminum, etc. Each of these particles is typically spherical in shape, but can be non-spherical, and there are no particular limitations on their size, mass, etc.

[0068] Here, the sample is labeled (stained) with one or more fluorescent dyes. Samples can be labeled with fluorescent dyes using known methods. For example, when the sample is cells, a fluorescently labeled antibody that selectively binds to antigens present on the cell surface is mixed with the cells to be measured, and the fluorescently labeled antibody binds to the antigens on the cell surface. Therefore, the cells to be measured can be labeled with a fluorescent dye.

[0069] Fluorescently labeled antibodies are antibodies to which a fluorescent dye binds as a label. Specifically, fluorescently labeled antibodies can be antibodies obtained by binding anti-Biotin to a biotin-labeled antibody via an anti-Biotin-protein reaction. Alternatively, fluorescently labeled antibodies can be antibodies to which a fluorescent dye binds directly. Note that polyclonal or monoclonal antibodies can be used as antibodies. Furthermore, there are no particular limitations on the fluorescent dye used to label the sample, and at least one known dye used for staining cells, etc., can be used.

[0070] (Light source unit 100)

[0071] like Figure 1 As shown, the light source unit 100 includes, for example, one or more (three in this example) excitation light sources 101 to 103, a total reflection mirror 111, dichroic mirrors 112 and 113, a total reflection mirror 115, and an objective lens 116.

[0072] In this configuration, total reflection mirror 111, dichroic mirrors 112 and 113, and total reflection mirror 115 constitute a waveguide optical system that guides the excitation beams L1 to L3 emitted from excitation light sources 101 to 103 to a predetermined optical path.

[0073] Objective lens 116 constitutes a focusing optical system that converges excitation beams L1 to L3 propagating along a predetermined optical path onto a spot 123a disposed in the flow path within microchip 120. Note that the number of spots 123a is not limited to one. That is, excitation beams L1 to L3 can converge onto different spots. Furthermore, the focusing positions of excitation beams L1 to L3 do not need to be aligned with spot 123a, and can move back and forth along their respective optical axes.

[0074] exist Figure 1 In the example shown, three excitation sources 101 to 103 are arranged, each emitting excitation beams L1 to L3 with different wavelengths. For example, for each of the excitation sources 101 to 103, a laser source emitting coherent light can be used. For example, excitation source 102 can be a diode-pumped solid-state laser (DPSS laser) emitting a blue laser beam (peak wavelength: 488 nm, power: 20 mW). Furthermore, excitation source 101 can be a laser diode emitting a red laser beam (peak wavelength: 637 nm, power: 20 mW), and similarly, excitation source 103 can be a laser diode emitting a near-ultraviolet laser beam (peak wavelength: 405 nm, power: 8 mW). Moreover, the excitation beams L1 to L3 emitted from excitation sources 101 to 103 can be pulsed beams.

[0075] For example, the total reflection mirror 111 reflects the excitation beam L1 emitted from the excitation source 101 in a predetermined direction.

[0076] Dichroic mirror 112 is an optical element that makes the optical axis of the excitation beam L1 reflected by total internal reflection mirror 111 coincide with or parallel to the optical axis of the excitation beam L2 emitted from excitation source 102. For example, dichroic mirror 112 transmits the excitation beam L1 from total internal reflection mirror 111 and reflects the excitation beam L2 from excitation source 102. As dichroic mirror 112, for example, a dichroic mirror designed to transmit light with a wavelength of 637 nm and reflect light with a wavelength of 488 nm can be used.

[0077] Dichroic mirror 113 is an optical element that makes the optical axes of the excitation beams L1 and L2 from dichroic mirror 112 coincide with or parallel to the optical axis of the excitation beam L3 emitted from excitation source 103. For example, dichroic mirror 113 transmits the excitation beam L1 from total internal reflection mirror 111 and reflects the excitation beam L3 from excitation source 103. As dichroic mirror 113, for example, a dichroic mirror designed to transmit light with a wavelength of 637 nm and light with a wavelength of 488 nm and reflect light with a wavelength of 405 nm can be used.

[0078] The excitation beams L1 to L3, which are ultimately collected as light traveling in the same direction by the dichroic mirror 113, are totally reflected by the total reflection mirror 115 and incident on the objective lens 116.

[0079] It should be noted that the beam shaping unit for converting the excitation beams L1 to L3 into parallel light can be arranged in the optical path from each excitation source 101 to 103 to the objective lens 116. The beam shaping unit may include, for example, one or more lenses, mirrors, etc.

[0080] Objective lens 116 focuses the incident excitation beams L1 to L3 onto a predetermined spot 123a on the flow path in the microchip 120, which will be described later. As the sample passes through the spot 123a, the spot 123a is illuminated with the excitation beams L1 to L3 as pulsed beams. Therefore, a fluorescence beam is emitted from the sample, and the excitation beams L1 to L3 are scattered by the sample to produce a scattered beam.

[0081] In this specification, among the scattered light generated from the sample in all directions, the component that travels forward along the direction of travel of the excitation beams L1 to L3 within a predetermined angle range is called the forward scattered beam L12, the component that travels backward along the direction of travel of the excitation beams L1 to L3 within a predetermined angle range is called the backscattered light, and the component that travels in a direction outside a predetermined angle relative to the optical axis of the excitation beams L1 to L3 is called the side scattered light.

[0082] Objective lens 116 has a numerical aperture, for example, corresponding to about 30° to 40° relative to the optical axis. In the fluorescence beam emitted from the sample, the component that travels forward within a predetermined angular range along the travel direction of the excitation beams L1 to L3 (hereinafter referred to as fluorescence beam L13) and the forward-scattered beam L12 are input to a demultiplexing optical system 150 arranged forward along the travel direction of the excitation beams L1 to L3.

[0083] (Demultiplexing optical system 150)

[0084] like Figure 1 and Figure 2 As shown, for example, the demultiplexing optical system 150 includes a filter 151, a collimating lens 152, a dichroic mirror 153, and a total reflection mirror 154 (see...). Figure 1 However, this disclosure is not limited to this configuration and various modifications can be made.

[0085] A filter 151, positioned downstream of the microchip 120 along the optical path of the excitation beams L1 to L3, selectively blocks, for example, a portion of the excitation beams L1 to L3 (e.g., excitation beams L1 and L3) within the beam L11 propagating downstream of the microchip 120. Here, the light traveling downstream of the microchip 120 includes the excitation beams L1 to L3 (including their forward-scattered beams) emitted from the sample in the microchip 120 and the fluorescence beam L13. Therefore, the filter 151 blocks components of the excitation beams L1 and L3, while allowing the components of the excitation beam L2 (referred to as the forward-scattered beam L12) and the fluorescence beam L13 to pass through.

[0086] Note that the filter 151 is arranged to be tilted relative to the optical axis of the beam L16. Therefore, the return light of the beam L16 reflected by the filter 151 is prevented from being incident on the scattered light detection unit 130 and the like via the objective lens 116.

[0087] For example, the forward-scattered beam L12 and the fluorescent beam L13, which have passed through the filter 151, are converted into parallel light by the collimating lens 152, and then demultiplexed by the dichroic mirror 153. For example, the dichroic mirror 153 reflects the forward-scattered beam L12 and transmits the fluorescent beam L13, which is outside the incident beam. The forward-scattered beam L12 reflected by the dichroic mirror 153 is guided to the scattered light detection unit 130, and the fluorescent beam L13, which has passed through the dichroic mirror 153, is guided to the fluorescence detection unit 140.

[0088] (Scattered light detection unit 130)

[0089] The scattered light detection unit 130 includes, for example, a plurality of lenses 131, 133, and 135, which shape the beam cross section of the forward-scattered beam L12 reflected by the dichroic mirror 153 and the total reflection mirror 132; a diaphragm 137, which adjusts the amount of light in the forward-scattered beam L12; a mask 134, which selectively transmits light having a specific wavelength of the forward-scattered beam L12 (e.g., a component of the excitation beam L2); and a photodetector 136, which detects light passing through the mask 134 and the lens 135 and incident thereon.

[0090] The photodetector 136 includes, for example, a two-dimensional image sensor, a photodiode, etc., and detects the amount and magnitude of light that has passed through the mask 134 and the lens 135 and is incident on the mask 134 and the lens 135. The signal detected by the photodetector 136 is input to, for example, the device control unit 11, the data recording unit 13, and / or the data analysis unit 14 in the information processing system 10, which will be described later.

[0091] (Fluorescence detection unit 140)

[0092] For example, the fluorescence detection unit 140 includes a spectroscopic optical system 141 and a photodetector 142. The spectroscopic optical system 141 disperses the spectrum of the incident fluorescence beam L13 into a dispersed beam L14 for each wavelength, and the photodetector 142 detects the amount of light in the dispersed beam L14 for each predetermined wavelength band (also called a channel).

[0093] The spectral optical system 141 includes, for example, one or more optical elements 141a (such as prisms and diffraction gratings) and spectralizes the incident fluorescence L13 into a dispersive beam 7L14 to be emitted at an angle that varies according to the wavelength.

[0094] The photodetector 142 may include, for example, multiple light receiving units that receive light for each channel. In this case, the multiple light receiving units may be arranged in one, two, or more columns along the beam-splitting direction by the beam-splitting optical system 141. Furthermore, for example, a photoelectric conversion element such as a photomultiplier tube may be used for each light receiving unit. However, a two-dimensional image sensor or the like may be used instead of multiple light receiving units.

[0095] The signal (fluorescence signal) detected by photodetector 142 and indicating the amount of light for each channel of fluorescence L13 is input to, for example, the device control unit 11, data recording unit 13 and / or data analysis unit 14 in the information processing system 10 described later.

[0096] 2.3 Illustrative Configuration Example of an Information Processing System

[0097] Figure 3 This is a block diagram illustrating a schematic configuration example of an information processing system according to this embodiment. For example... Figure 3 As shown, the information processing system 10 generally includes a device control unit 11 (i.e., flow cytometer 1) for setting measurement conditions and controlling the operation of the device, a fluorescence spectroscopy detection unit 12 for detecting the fluorescence amount of many samples, a data recording unit 13 for recording the spectral information of each detected sample, and a data analysis unit 14 for performing various data processing to obtain the desired analytical results from the recorded data.

[0098] (Device Control Unit 11)

[0099] The device control unit 11 optimizes measurement conditions by changing the liquid inlet conditions of the sample flowing in the flow path of the microchip 120, the parameters of the laser output of the excitation light sources 101 to 103, the sensitivity control of the photodetectors 136 and 142, and the position adjustment of the optical stage of each optical element in the optical system, including the dichroic mirror 153. As a specific operating procedure, in order to set the optimal conditions for obtaining the desired results for the sample to be measured, the user supplies the actual sample to the microchip 120 and repeatedly adjusts various parameters as needed while observing the fluorescence signal detected by the photodetector 142. To make it possible to easily change the parameter settings, the device control unit 11 is composed of, for example, a terminal device (such as a personal computer (PC)). The user inputs changes to various parameters through control software mainly executed by the device control unit 11.

[0100] (Fluorescence spectroscopy detection unit 12)

[0101] For example, the fluorescence spectroscopy detection unit 12 corresponds to the reference. Figure 1 and Figure 2 The flow cytometer 1 described herein optically analyzes samples. Specifically, the fluorescence spectroscopy detection unit 12 first emits excitation beams L1 to L3 from excitation light sources 101 to 103, respectively, and illuminates the sample flowing in the flow path with the excitation beams L1 to L3. Next, the fluorescence spectroscopy detection unit 12 detects the fluorescence beam L13 emitted from the sample. For example, as described above, the fluorescence spectroscopy detection unit 12 uses a dichroic mirror 153, a filter 151, etc., to separate the beam with a specific wavelength (target fluorescence beam L13) from the light emitted from the sample, and uses a photodetector 142, such as a 32-channel photomultiplier tube (PMT) or an image sensor, to detect the separated beam. At this time, the fluorescence beam L13 is dispersed by a spectroscopic optical system 141 including, for example, a prism or a diffraction grating, and the beam with a wavelength that varies according to the channel of the photodetector 142 is detected. As a result, the spectral information of the detected beam (fluorescence beam) can be easily obtained. There are no particular limitations on the sample to be analyzed, and examples include cells and microbeads.

[0102] (Data Recording Unit 13)

[0103] The data recording unit 13 is a recording device, such as a memory or disk, that records spectral information of each sample acquired by the fluorescence spectroscopy detection unit 12, as well as information on the scattered beam, time, and location, in addition to spectral information. In normal sample analysis of cells, etc., thousands to millions of samples are analyzed under a single experimental condition. Therefore, in the data recording unit 13, for example, multiple spectral information entries are recorded in an organized manner for each experimental condition.

[0104] (Data Analysis Unit 14)

[0105] The data analysis unit (separation unit) 14, for example, is an information processing device such as a PC, which quantifies the light intensity in each wavelength region detected by the fluorescence spectroscopy detection unit 12 and performs unmixing to obtain the fluorescence amount (intensity) of each fluorescent dye used. For this unmixing, for example, a linear fit can be used using the least squares method with a fluorescence spectral reference calculated from experimental data.

[0106] A fluorescence spectral benchmark can be calculated using statistical processing of two types of spectral information obtained from a single stained sample stained with only one fluorescent dye and spectral information obtained from an unstained sample. By appropriately performing this statistical processing, the specific spectral shape of the fluorescence spectral benchmark of the stained fluorescent dye and the spectral shape of the autofluorescent component of the unstained sample (which is also one of the fluorescence spectral benchmarks) can be estimated from actual data measured by flow cytometer 1.

[0107] The calculated fluorescence spectrum baseline, along with information such as the name of the fluorescent molecule, the measurement date, and the sample type, is recorded in the data recording unit 13. The fluorescence intensity of the sample estimated by the data analysis unit 14 is also stored in the data recording unit 13, plotted and displayed for the purpose of analysis, and thus used by the user to analyze the sample.

[0108] In this manner, the data analysis unit 14 performs unmixing to calculate fluorescence amounts from spectral information measured from numerous samples (hereinafter referred to as measurement data). During unmixing, for example, the fluorescence amount of each fluorescent dye is calculated using a least-squares-based process. In this embodiment, parameters related to the unmixing performed by the data analysis unit 14 are correctly calculated from the measurement data, thereby achieving high resolution calculated according to the desired fluorescence separation process.

[0109] 2.4 Regarding unmixing

[0110] Figure 4 This is a diagram used to illustrate the general outline of the demixing process according to this embodiment. For example... Figure 4 As shown, in the unmixing according to this embodiment, the spectral waveform of the fluorescent dye extracted from the spectral information obtained from a single stained sample is used as the fluorescence spectral reference. Figure 4 The fluorescence spectral references R1 to R4 shown in (a) are used, and the spectral information of each fluorescent dye included in the measurement data (demixing) is calculated. Figure 4 The spectral information C1 to C4 shown in (c) is used to calculate the spectral information measured from the multi-stained samples. Figure 4 The fluorescence intensity of each fluorescent dye included in the spectral information (C1+C2+C3+C4) shown in (b) is shown.

[0111] In this unmixing, the least squares method (LSM) as shown in Equation (1) and the weighted least squares method (weighted LSM) as shown in Equation (2) can be used.

[0112]

[0113]

[0114] Note that in formulas (1) and (2), S denotes a matrix (hereinafter referred to as the reference spectrum), where the fluorescence spectral references used for unmixing are arranged in the column direction, S T The matrix y represents the transpose of the reference spectrum S. j This represents the measured spectral information (also known as the observation), and x i This represents the fluorescence intensity to be obtained. Note that in this specification, i and j are integers of 1 or greater. Additionally, in formula (2), L represents the weighting coefficient matrix represented by formula (3) below. Furthermore, in formula (3), λ i The weighting coefficient is represented by the following formula (4).

[0115]

[0116]

[0117] Poisson noise term

[0118] Fixed noise term

[0119] As shown in Equations (1) to (4), in unmixing, a general least squares (LSM) or whole least squares (WLSM) method is used, which includes a Poisson noise term based on the amount of light measured by flow cytometry. While LSM is computationally efficient and has a short processing time, it also contributes less to fractions with low fluorescence intensity. Therefore, when using WLSM, the separation performance between positive and negative values ​​in actual flow cytometry data is generally better.

[0120] Note that when using WLSM, it is desirable to set a fixed noise term to prevent excessive weights from being applied to data with small values. For this fixed noise term, a constant with improved separation performance based on evaluation experience during device development can be used as a fixed value.

[0121] 2.5 Optimization of Fixed Noise for Each Measurement Channel

[0122] In the unmixing algorithm according to this embodiment, fluorescence separation performance can be improved by setting the fixed noise term in formula (4) to an optimal value that varies according to the measurement channel. The value for the fixed noise term can be calculated, for example, by the variation of the measurement data of the unstained sample in each channel. The measurement data of the unstained sample includes all the autofluorescence of the sample, the noise of the device, the effect of the Raman shift of the excitation beams L1 to L3, etc. Since the fluorescent component from the fluorescent dye is detected in the form of autofluorescence added to the unstained sample, the measurement variation of the unstained sample determines the detection limit.

[0123] Figure 5 This is a graph showing an example of the spectral information and standard deviation obtained when unstained microparticles are used as unstained samples. Figure 5 (a) shows the spectral information obtained by measuring undyed microbeads, and Figure 5 (b) shows its standard deviation. This is based on... Figure 5 The waveform shown has a fixed noise term, which can improve the separation performance through demixing.

[0124] It should be noted that, through settings Figure 5 The waveforms shown allow for optimal conditions to be set for each sample to be measured, such as various types of batteries or microbeads, and for each experiment. Furthermore, since the measurement of samples in their unstained state, which is necessary even in measurements using a normal flow cytometer, is required by this setup, optimal separation can be performed without requiring additional work from the user.

[0125] 2.6 Regarding finite autofluorescence correction

[0126] Next, a separation algorithm for optimally performing the autofluorescence correction function according to this embodiment will be described.

[0127] Figure 6 This is a diagram illustrating an example of a reference spectrum that does not include autofluorescence spectra, and Figure 7 This is a diagram illustrating an example of a reference spectrum that includes an autofluorescence spectrum. Note that the reference spectrum here corresponds to the reference spectrum S in equations (1) and (2) above. Figure 6 The reference spectrum S shown includes fluorescence spectral references for four fluorescent components (fluorescent dyes): fluorescein isothiocyanate (FITC), phycoerythrin (PE), PE-Dazzle 594, and allophycocyanin (APC). In addition, besides... Figure 6 In addition to the four fluorescence spectral benchmarks shown, Figure 7 The baseline spectrum S shown also includes the autofluorescence spectrum of the sample itself. It should be noted that... Figure 6 and Figure 7A graph showing the spectral waveforms for each fluorescence spectral reference (including autofluorescence spectra) is presented, but in reality, the fluorescence intensity of each channel for each fluorescence spectral reference is stored in the row corresponding to each fluorescence spectral reference.

[0128] As described above, when performing unmixing, flow cytometer 1 uses the reference spectrum of the fluorescent dye as a reference (see [link]). Figure 6 Specifically, by analyzing the observed values ​​[y1, ..., y]... m Subtract the observed values ​​[y1, ..., y] from the original value. m The difference between the mean of the unstained samples (the mean of the autofluorescence amount) and the mean of the unstained samples, and using Figure 6 The reference spectrum S shown is subjected to WLSM (see Equations (2) to (4)) to obtain the fluorescence intensity [x1, ..., x] of each fluorescent dye. n ].

[0129] In this unmixing, such as Figure 7 As shown, a more ideal fluorescence separation process can be performed by incorporating the autofluorescence spectrum of the sample into the reference spectrum S. Specifically, WLSM is performed using the reference spectrum S, where... Figure 7 The autofluorescence spectra shown were added to the observed values ​​[y1, ..., y] as is. m In the formulas (2)-(4)), the fluorescence intensity [x1, ..., x] of each fluorescent dye is obtained. n ].

[0130] However, when the autofluorescence spectrum is added to the reference as is, the changes in the separation results of other fluorescent dyes are amplified, and the fluorescence separation performance may deteriorate. This will be referenced. Figure 8 and Figure 9 Describe it.

[0131] Figure 8 This is a two-dimensional graph showing the unmixing results when using a reference spectrum that does not include autofluorescence. Figure 9 This is a two-dimensional graph showing the unmixing results when using a reference spectrum that includes autofluorescence. (As shown in...) Figure 8 and Figure 9 In the two-dimensional graph enclosed by dashed lines, in the SSC_A×CD3_VioGreen_A two-dimensional graph, the lower left distribution D1 expands in the vertical axis direction. Figure 8 → Figure 9 ), and in the two-dimensional plot of CD16_FITC_A×CD56_PC5_A, the left distribution D2 in the plot expands in the horizontal axis direction ( Figure 8 → Figure 9 ).

[0132] As mentioned above, since fluorescence separation performance is degraded by using a reference spectrum that includes an autofluorescence spectrum, a fluorescence spectrum reference of a fluorescent dye whose shape closely approximates the autofluorescence spectrum included in the reference is considered to be included in the reference spectrum. This will refer to... Figure 10 Describe it.

[0133] Figure 10 This is a diagram illustrating examples of demixing results when using a reference spectrum that includes only the autofluorescence spectrum and when using a reference spectrum that includes both the autofluorescence spectrum of the fluorescent dye and the fluorescence spectrum reference. Figure 10 (a) shows a two-dimensional plot of measurement data from unstained samples. Figure 10 (b1) shows an example of a reference spectrum that includes only the autofluorescence spectrum of an unstained sample, and (c1) shows the results of unmixed measurement data from (a) using the reference spectrum shown in (b1). Furthermore, Figure 10 (b2) shows an example of a reference spectrum that includes a fluorescent dye as a reference spectrum in addition to the autofluorescence spectrum, and (c2) shows the results of the unmixing measurement data of (a) using the reference spectrum shown in (b2).

[0134] like Figure 10 As shown, it can be seen that the change in the autofluorescence component W2 when a reference spectrum including a fluorescent dye is used in addition to the autofluorescence spectrum ((b1)→(c1)) is unmixed is greater than the change in the autofluorescence component W1 when only the reference spectrum including the autofluorescence spectrum ((b2)→(c2)) is unmixed. As mentioned above, one of the factors is considered to be that the reference spectrum of (b2) includes a fluorescent dye with a spectral shape close to that of the autofluorescence spectrum.

[0135] Therefore, in this embodiment, as shown in the following formula (5), a penalty term for suppressing the autofluorescent component (autofluorescence spectrum) in the reference spectrum is added to the above formula (2) for performing WLSM. Note that in formula (5), p represents the penalty coefficient and I represents the identity matrix.

[0136]

[0137] Penalty term penalty items

[0138] The penalty coefficient p is a value determined based on the device conditions of flow cytometer 1. For example, when the upper limit of the detectable range of fluorescence intensity is set in flow cytometer 1 as a device condition, it is approximately 10. 6 At that time, the penalty coefficient can be set to approximately 10. -8 .

[0139] The penalty term pI suppresses the autofluorescence component in the reference spectrum by multiplying a line of autofluorescence spectrum A in the reference spectrum S by ε (0 < ε < 1), as shown in Equation (6) below. Note that in Equation (6), ε is the parameter used to correct the autofluorescence spectrum (autofluorescence correction parameter) and is a regularization parameter. Furthermore, A' represents the autofluorescence spectrum ε reduced by the autofluorescence correction parameter.

[0140] A′=εA (6)

[0141] The value of the autofluorescence correction parameter ε can be set to a value greater than 0 and less than 1, for example, below 0.1. Generally, the autofluorescence correction parameter ε can be determined, for example, using the following formula (7). It should be noted that in formula (7), L represents the weighted squared error (also called the weighting matrix), and A represents the autofluorescence spectrum before reduction.

[0142]

[0143] By utilizing this autofluorescence correction parameter ε to reduce the autofluorescence component in the reference spectrum S, such as... Figure 11 As shown, including Figure 7 The reference spectrum S of the autofluorescence spectrum A shown is converted into the reference spectrum S of the autofluorescence spectrum A', where the autofluorescence spectrum A is reduced to the reference spectrum S of the autofluorescence spectrum A' using the autofluorescence correction parameter ε. It should be noted that... Figure 11 A diagram illustrating an example of a restricted reference spectrum according to this embodiment.

[0144] In this way, by limiting the autofluorescent component in the reference spectrum S using the autofluorescence correction parameter ε, the increase in variation of the autofluorescent component can be suppressed. As a result, the influence of variations in the autofluorescent component during unmixing can be suppressed, and thus the degradation of fluorescence separation performance can be suppressed. That is, in this embodiment, by setting the penalty coefficient p and the autofluorescence correction parameter ε to appropriate values, the degradation of fluorescence separation performance can be suppressed even when using a reference spectrum that includes autofluorescent components.

[0145] Note that this example illustrates the limitation of autofluorescent components using only the autofluorescence correction parameter ε, but this embodiment is not limited to this, and the autofluorescence correction parameter ε can be used to limit the fluorescence spectral reference of fluorescent dyes. For example, the autofluorescence correction parameter ε can be used to limit fluorescent dyes that are included in a small absolute amount in the stained sample or that initially have a small fluorescence intensity. However, the autofluorescence correction parameter ε in this case can be a different value than the autofluorescence correction parameter ε used for another fluorescent dye and autofluorescence.

[0146] 2.7 Automatic Determination of Limited Autofluorescence Correction Parameters

[0147] In the above description, the penalty coefficient p (or penalty term pI) is a value determined based on the upper limit of fluorescence intensity set as a device condition as described above, and therefore can be automatically determined according to the device settings. That is, in this embodiment, for example, the data analysis unit 14 can automatically determine the penalty coefficient p based on the device conditions (upper limit of fluorescence intensity, etc.) set in the flow cytometer 1.

[0148] Meanwhile, the autofluorescence correction parameter ε is an amount that needs to be appropriately set for each type of sample or each group of samples (hereinafter referred to as sample groups). However, the autofluorescence correction parameter ε can also be determined automatically by the following methods.

[0149] Figure 12 This is a flowchart illustrating an example of the automatic determination operation of autofluorescence correction parameters according to this embodiment. It should be noted that, for example, this operation could be performed by the data analysis unit 14. Therefore, this operation will be described below as being performed by the data analysis unit (determination unit) 14.

[0150] like Figure 12 As shown, in this operation, firstly, the data analysis unit 14 performs measurement data correction (step S101). In the measurement data correction, in addition to the fluorescence correction described above, for example, a process is performed to extract measurement data obtained from unstained samples of the same or similar type as the stained sample to be analyzed from the measurement data recorded in the data recording unit 13.

[0151] Note that the unstained data extracted in step S101 may be measurement data measured using flow cytometer 1 each time an analysis is performed, or it may be unstained data recorded in data recording unit 13 by previous executions of unstained samples that are the same type or the same as the stained sample to be analyzed. Unstained samples that are the same type or the same as the stained sample to be analyzed may be unstained samples before the stained sample to be analyzed was labeled, unstained samples of the same type (e.g., the same type of cells, etc.) as the stained sample to be analyzed, etc.

[0152] Next, the simple mean of the corrected unstained data is calculated, and the calculated simple mean is subtracted from the unstained data (step S102).

[0153] Next, the data analysis unit 14 uses a reference spectrum S, which includes only the autofluorescence spectra of unstained samples that are the same as or of the same type as the unstained samples from which the unstained data were obtained, to unmix the unstained data obtained in step S102 (step S103).

[0154] Next, the data analysis unit 14 calculates the standard deviation σ0 of the autofluorescence intensity (hereinafter also referred to as the autofluorescence amount) calculated by unmixing in step S103 (step S104). Here, since the simple mean was subtracted from the unstained data in step S102, the distribution of the autofluorescence amount obtained in step S103 is a zero-centered distribution. Therefore, in step S104, the zero-centered standard deviation σ0 is calculated.

[0155] Next, the data analysis unit 14 sets the autofluorescence correction parameter ε to an initial value (step S105). The initial value of the autofluorescence correction parameter ε can be a value less than 1, such as 0.1.

[0156] Next, as shown in Equation (6), the data analysis unit 14 uses the autofluorescence correction parameter ε to attenuate the autofluorescence spectrum A included in the reference spectrum S (step S106).

[0157] Next, the data analysis unit 14 unmixes the unstained data obtained by subtracting the simple average value in step S102 with the reference spectrum S of the autofluorescence spectrum A attenuated using the autofluorescence correction parameter ε (step S107). Note that in step S107, since the unmixed object is the unstained data, the fluorescence amount obtained as a result of unmixing is the autofluorescence amount.

[0158] Next, in step S107, data analysis unit 14 calculates the standard deviation σ of the autofluorescence amount calculated through unmixing. 0n (Step S108). Note that, as in step S104, since the simple mean was subtracted from the unstained data in step S102, the distribution of autofluorescence obtained in step S107 is a zero-centered distribution. Therefore, in step S108, the zero-centered standard deviation σ is calculated. εn .

[0159] Next, the data analysis unit 14 determines whether the autofluorescence correction parameter ε is equal to or less than a preset minimum value ε_min (step S109). If the autofluorescence correction parameter ε is greater than the minimum value ε_min (No in step S109), the data analysis unit 14 reduces the autofluorescence correction parameter ε by a predetermined width Δ (step S110), then returns to step S106 and performs subsequent operations. Note that the predetermined width Δ can be, for example, a value sufficiently less than 1, such as 0.01 or 0.005.

[0160] Meanwhile, if the autofluorescence correction parameter ε has reached its minimum value ε_min or smaller ("Yes" in step S109), the data analysis unit 14 linearly interpolates the standard deviation σ for each autofluorescence correction parameter ε calculated by repeating steps S106 to S110. εn To obtain the optimal value of the autofluorescence correction parameter ε, for example, σ εn =σ0 autofluorescence correction parameter ε (step S111), and end this operation.

[0161] Note that the following scenario has been illustrated in the above operation: specifying the standard deviation σ at intervals of a preset width Δ. εn The standard deviation σ of linear interpolation is obtained through the fluorescence correction parameter ε. εn Therefore, the standard deviation σ εn The standard deviation σ0 is consistent with each other. However, this disclosure is not limited thereto. However, when the standard deviation σ εn When the standard deviation σ0 is less than or greater than the standard deviation σ0, the ratio of the amount of autofluorescence represented by the corrected autofluorescence spectrum A' to another fluorescence spectral reference deviates from the ratio of the autofluorescent component included in the measurement data to the fluorescence spectrum of another fluorescent dye, and there is a possibility that the degradation of fluorescence separation performance cannot be suppressed. Therefore, the expected standard deviation σ0 εn It is consistent to some extent with the standard deviation σ0.

[0162] As described above, the optimal autofluorescence correction parameter ε is determined by unmixing unstained data with a reference spectrum S that includes only autofluorescence spectra and a reference spectrum S that includes both autofluorescence and fluorescence spectra. The optimal value of the autofluorescence correction parameter ε can be determined using information typically measured in analyses performed using flow cytometer 1 (unstained data and autofluorescence spectra). Therefore, appropriate analyses can be performed without increasing the user's burden.

[0163] 2.8 Functions and Effects

[0164] As described above, according to this embodiment, since the autofluorescence component in the reference spectrum S is limited by the autofluorescence correction parameter ε, the increase in the variation of the autofluorescence component can be suppressed. As a result, the influence of the variation of the autofluorescence component during unmixing can be suppressed, and therefore the degradation of fluorescence separation performance can be suppressed. That is, in this embodiment, by setting the penalty coefficient p and the autofluorescence correction parameter ε to appropriate values, the degradation of fluorescence separation performance can be suppressed even when a reference spectrum including an autofluorescence component is used.

[0165] Figures 13 to 15 This is a diagram used to explain the change in fluorescence separation performance when the autofluorescence correction parameter ε according to this embodiment is changed. Figure 13This illustrates the case where the autofluorescence correction parameter ε is 1, meaning the autofluorescence component in the reference spectrum S is not reduced (unrestricted). Figure 14 This shows the case where the autofluorescence correction parameter ε is 0.1, and Figure 15 This shows the case where the autofluorescence correction parameter ε is 0.025.

[0166] It should be noted that, Figures 13 to 15 In the figure, (a) shows the fluorescence and autofluorescence spectra of each fluorescent dye obtained by unmixing the measured data with the reference spectrum S, and (b) shows the standard deviation σ of the autofluorescence amount obtained by unmixing the undyed data with the reference spectrum S. ε (c) shows two-dimensional curves of APC_Vio770 and PC5 (PE-Cy5) as fluorescent dyes to be separated, and (d) shows two-dimensional curves of FITC and VioGreen as fluorescent dyes to be separated.

[0167] exist Figures 13 to 15 In (a), the contour lines represent the measurement data, and the solid and dashed lines represent the fluorescence spectral references (including autofluorescence spectra). It should be noted that in the fluorescence spectral references, L1 to L3 are autofluorescence spectra.

[0168] As from Figures 13 to 15 As can be seen from this, when the autofluorescence correction parameter ε is set to 0.025 ( Figure 15 Specifically, the expansion of the variation between FITC and VioGreen (see (d) in each figure) is also small. This indicates that the fluorescence separation performance is improved when the autofluorescence correction parameter ε is set to 0.025 compared to when the autofluorescence correction parameter ε is set to 1 or 0.1.

[0169] Furthermore, in this embodiment, the optimal autofluorescence correction parameter ε is determined based on the unmixed results of unstained data and a reference spectrum S consisting only of autofluorescence spectra and a reference spectrum S consisting of both autofluorescence and fluorescence spectra. Therefore, the optimal value of the autofluorescence correction parameter ε can be determined using information typically measured in analyses performed using flow cytometer 1 (unstained data and autofluorescence spectra). Thus, appropriate analyses can be performed without increasing the user's burden.

[0170] Figure 16 This is a graph showing the change in the standard deviation of the autofluorescence amount obtained from unstained samples when the autofluorescence correction parameter ε is varied by different predetermined widths Δ, where (a) indicates the change in standard deviation in the range of 0 to 1 when the predetermined width Δ is 0.1, and (b) indicates the change in standard deviation in the range of 0 to 0.1 when the predetermined width Δ is 0.005. Figure 16As shown in (a) and (b), it can be seen that when the predetermined width Δ is set to a small value, that is, when the autofluorescence correction parameter ε is changed more finely (see (b)), a more optimized autofluorescence correction parameter ε that is close to the standard deviation σ0 can be obtained compared with when the predetermined width Δ is set to a large value (see (a)).

[0171] also, Figure 17 This is a graph showing the fluorescence separation performance when no penalty term is provided, with unrestricted autofluorescence spectra, and the fluorescence separation performance when a penalty term is provided and the autofluorescence spectrum is restricted (in this embodiment). Figure 17 In the figures, (a) shows the change in autofluorescence intensity (standard deviation σ0) when the unstained data is not mixed with a reference spectrum that includes only autofluorescence spectra, and (b) shows the change in autofluorescence intensity (standard deviation σ0) when the unstained data is not mixed with a reference spectrum that includes both infinite autofluorescence and fluorescence spectra. εn (h) shows the variation in the amount of autofluorescence (standard deviation σ) when the unstained data is not mixed with a reference spectrum that includes a limited autofluorescence spectrum and a fluorescence spectral reference. εn ).

[0172] Furthermore, (c) to (g) are two-dimensional graphs showing the fluorescence separation performance when the unstained data is not mixed with the reference spectrum of the unrestricted autofluorescence spectrum and the fluorescence spectral reference shown in (b), and (i) to (m) are two-dimensional graphs showing the fluorescence separation performance when the unstained data is not mixed with the reference spectrum of the limited autofluorescence spectrum and the fluorescence spectral reference shown in (h).

[0173] It should be noted that, Figure 17 In (h) to (m), the penalty coefficient p is 10. -7 Furthermore, the autofluorescence correction parameter ε is 0.005.

[0174] For reference Figure 17 As can be seen from (c) to (g) and (i) to (m) in this embodiment, the demixed fluorescence separation performance is improved by providing a penalty term pI and limiting the autofluorescence spectrum in the reference spectrum S.

[0175] For example, as shown in (c) and (i), in the relationship between FitC and VioGreen, the autofluorescence spectrum is unrestricted when no penalty term is provided (see (c)), and the standard deviation σ of FITC... FITC The standard deviation σ of VioGreen is 257. VioGreen The value is 271. On the other hand, when a penalty term is provided and the autofluorescence spectrum is restricted (see (i)), the standard deviation σ of FITC is... FITCIt is 190, and VioGreen's standard deviation σ VioGreen The answer is 192. That is, for FITC, fluorescence separation performance is improved by 26%, and for VioGreen, fluorescence separation performance is improved by 30%.

[0176] Additionally, as shown in (f) and (l), in the relationship between VioBlue and APC, when no penalty term is provided and the autofluorescence spectrum is not restricted (see (f)), the standard deviation σ of VioBlue is... VioBlue The value is 268. On the other hand, when a penalty term is provided and the autofluorescence spectrum is restricted (see (l)), the standard deviation σ of VioBlue is... VioBlue The answer is 189. That is, the fluorescence separation performance has improved by 30%.

[0177] 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 these examples. It will be apparent to those skilled in the art that various modifications or variations within the scope of the technical concept described in the claims will be conceived, and it should be understood that these modifications or variations also fall within the scope of the present disclosure.

[0178] Furthermore, the effects described in this specification are merely illustrative or exemplary, and not restrictive. That is, based on the description in this specification, the technology disclosed herein may exhibit other effects, in conjunction with or in lieu of the aforementioned effects, that are obvious to those skilled in the art.

[0179] It should be noted that the following configurations also fall within the technical scope of this disclosure. (1)

[0181] An information processing device includes a separation unit that calculates the fluorescence intensity of one or more fluorescent beams and autofluorescent beams emitted from the one or more fluorescent dyes and the biological sample, respectively, using least-squares arithmetic operations from fluorescence signals measured from a biological sample labeled with one or more fluorescent dyes. The least-squares method uses a fluorescence spectral reference for each of the fluorescent dyes and the autofluorescence spectrum of the biological sample.

[0182] In the arithmetic operation using the least squares method, an upper limit and a lower limit value for the fluorescence intensity are set for each of the one or more fluorescent beams and the spontaneously fluorescent beam. (2)

[0184] According to the information processing apparatus described in (1), wherein

[0185] The separation unit calculates the fluorescence intensity of the fluorescence beam emitted from the one or more fluorescent dyes and the spontaneous fluorescence beam emitted from the biological sample using an arithmetic formula that includes a penalty term, wherein the penalty term sets an upper limit and a lower limit for the fluorescence intensity of each of the one or more fluorescent dyes and the biological sample. (3)

[0187] According to the information processing device described in (2), wherein

[0188] The arithmetic formula is represented by the following formula (5):

[0189]

[0190] Where, x i (i is an integer of 1 or greater) represents the fluorescence intensity of each of the one or more fluorescent beams and the spontaneously fluorescent beam, y j (j is an integer of 1 or greater) represents the fluorescence signal, and S represents the reference spectrum including the fluorescence spectral reference of each of the fluorescent dyes and the reference spectrum of the autofluorescence spectrum of the biological sample. T Let L represent the transpose of the reference spectrum S, L represent the weighting coefficient matrix, p represent the penalty coefficient, I represent the identity matrix, and pI represent the penalty term. (4)

[0192] The information processing apparatus according to any one of (1) to (3), wherein

[0193] In the arithmetic operation using the least squares method, the upper limit and lower limit values ​​set for at least one of the one or more fluorescent beams and the spontaneous fluorescent beam are different from the upper limit and lower limit values ​​set for the other of the one or more fluorescent beams and the spontaneous fluorescent beam. (5)

[0195] According to the information processing device described in (4), wherein

[0196] At least one of the one or more fluorescent beams and the spontaneously fluorescent beam is the spontaneously fluorescent beam. (6)

[0198] According to the information processing apparatus described in (2) or (3), wherein

[0199] The arithmetic formula includes an autofluorescence correction parameter for setting different upper limits between at least one of the one or more fluorescent beams and the autofluorescence beam and the other of the one or more fluorescent beams and the autofluorescence beam. (7)

[0201] According to the information processing device described in (3), wherein

[0202] At least one of the one or more fluorescence spectral references included in the reference spectrum S and the autofluorescence spectrum is reduced using an autofluorescence correction parameter having a value greater than 0 and less than 1. (8)

[0204] The information processing apparatus according to (6) or (7) further includes a determining unit for determining the autofluorescence correction parameters, wherein...

[0205] Determine unit

[0206] The first standard deviation of the fluorescence intensity of the autofluorescence beam emitted by the unstained biological sample is calculated by performing arithmetic operations on the fluorescence signal measured from the unstained biological sample using the least squares method based on the autofluorescence spectrum.

[0207] A second standard deviation of the fluorescence intensity of the autofluorescent beam emitted from the unstained biological sample is calculated by performing the arithmetic operation on the fluorescence signal measured from the unstained biological sample using the least squares method based on the fluorescence spectral reference of each of the fluorescent dyes and the autofluorescence spectrum.

[0208] The autofluorescence correction parameters are determined such that the second standard deviation is consistent with or close to the first standard deviation. (9)

[0210] The information processing apparatus according to any one of (1) to (8), wherein

[0211] The least squares method is the weighted least squares method. (10)

[0213] An information processing method includes: calculating, respectively, the fluorescence intensity of one or more fluorescent beams and autofluorescent beams emitted from the one or more fluorescent dyes and the biological sample from fluorescence signals measured by a least-squares arithmetic operation, wherein the least-squares method uses a fluorescence spectral reference for each of the fluorescent dyes and the autofluorescence spectrum of the biological sample, wherein...

[0214] In the arithmetic operation using the least squares method, an upper limit and a lower limit value for the fluorescence intensity are set for each of the one or more fluorescent beams and the spontaneously fluorescent beam. (11)

[0216] A program for enabling a computer to analyze biological samples labeled with one or more fluorescent dyes, wherein...

[0217] The program causes the computer to perform the following processing: calculating, from the fluorescence signal measured from the biological sample, the fluorescence intensity of one or more fluorescent beams and autofluorescent beams emitted from the one or more fluorescent dyes and the biological sample, respectively, using least-squares arithmetic operations, wherein the least-squares method uses the fluorescence spectral reference of each fluorescent dye and the autofluorescence spectrum of the biological sample, and

[0218] In the arithmetic operation using the least squares method, an upper limit and a lower limit value for the fluorescence intensity are set for each of the one or more fluorescent beams and the spontaneously fluorescent beam. (12)

[0220] An optical measurement system, comprising:

[0221] An excitation light source is used to illuminate a biological sample labeled with one or more fluorescent dyes using one or more excitation beams;

[0222] The detection unit detects the fluorescence signal of the fluorescent beam and the autofluorescence emitted from the biological sample by irradiation with one or more excitation beams; and

[0223] A separation unit calculates the fluorescence intensity of one or more fluorescent beams and autofluorescent beams emitted from the one or more fluorescent dyes and the biological sample, respectively, from the fluorescence signal detected by the detection unit using least-squares arithmetic operations. The least-squares method uses the fluorescence spectral reference of each fluorescent dye and the autofluorescence spectrum of the biological sample.

[0224] In the arithmetic operation using the least squares method, an upper limit and a lower limit value for the fluorescence intensity are set for each of the one or more fluorescent beams and the spontaneously fluorescent beam.

[0225] Reference number list

[0226] 1. Flow cytometer

[0227] 10. Information Processing System

[0228] 11 Device Control Unit

[0229] 12 Fluorescence Spectroscopy Detection Unit

[0230] 13 Data Recording Unit

[0231] 14 Data Analysis Unit

[0232] 100 light source units

[0233] Excitation source 101 to 103

[0234] 111 and 115 Total Internal Reflection Mirrors

[0235] 112, 113 Dichroic mirrors

[0236] 116 Objective Lens

[0237] 120 microchips

[0238] 123a light spot

[0239] 130 Scattered Light Detection Unit

[0240] 131, 133, 135 lenses

[0241] 134 Mask

[0242] 136 Photodetector

[0243] 137 Diaphragm

[0244] 140 fluorescence detection units

[0245] 141 Spectroscopic Optical System

[0246] 141a Optical Components

[0247] 142 Photodetector

[0248] 150 Demultiplexing Optical System

[0249] 151 Filter

[0250] 152 Collimating Lens

[0251] 153 Dichroic Mirror

[0252] 154 Total Internal Reflection Mirror

[0253] L1, L2, L3 excitation beams

[0254] L11 beam

[0255] L12 Forward-scattering beam

[0256] L13 fluorescent beam

[0257] L14 Dispersed beam.

Claims

1. An information processing apparatus comprising a separation unit, the separation unit calculating, from fluorescence signals measured from a biological sample labeled with one or more fluorescent dyes, the fluorescence intensities of one or more fluorescent beams and an autofluorescent beam emitted from the one or more fluorescent dyes and the biological sample respectively using least-squares arithmetic operations, the least-squares method using a fluorescence spectral reference for each of the fluorescent dyes and the autofluorescence spectrum of the biological sample, wherein... In the arithmetic operation using the least squares method, an upper limit and a lower limit value for the fluorescence intensity are set for each of the one or more fluorescent beams and the spontaneously fluorescent beam.

2. The information processing apparatus according to claim 1, wherein... The separation unit calculates the fluorescence intensity of the fluorescence beam emitted from the one or more fluorescent dyes and the spontaneous fluorescence beam emitted from the biological sample using an arithmetic formula that includes a penalty term, wherein the penalty term sets an upper limit and a lower limit for the fluorescence intensity of each of the one or more fluorescent dyes and the biological sample.

3. The information processing apparatus according to claim 2, wherein... The arithmetic formula is represented by the following formula (5): in, x i The fluorescence intensity x1 to x represents the fluorescence intensity of the one or more fluorescent beams and the spontaneously emitted fluorescent beam. n Each of the following is an integer, where i is 1 or a larger integer, and y is a constant. j The fluorescence signals y1 to y2 represent the fluorescence signals y1 to y2. m In each of the above, j is an integer of 1 or greater, and S represents a reference spectrum including the fluorescence spectral reference of each of the fluorescent dyes and the autofluorescence spectrum of the biological sample. T Let L be the transpose of the reference spectrum S, L be the weighting coefficient matrix, p be the penalty coefficient, I be the identity matrix, and p[I] be the penalty term.

4. The information processing apparatus according to claim 1, wherein... In the arithmetic operation using the least squares method, the upper limit and lower limit values ​​set for at least one of the one or more fluorescent beams and the spontaneous fluorescent beam are different from the upper limit and lower limit values ​​set for the other of the one or more fluorescent beams and the spontaneous fluorescent beam.

5. The information processing apparatus according to claim 4, wherein At least one of the one or more fluorescent beams and the spontaneously fluorescent beam is the spontaneously fluorescent beam.

6. The information processing apparatus according to claim 2, wherein The arithmetic formula includes an autofluorescence correction parameter for setting different upper limits between at least one of the one or more fluorescent beams and the autofluorescence beam and the other of the one or more fluorescent beams and the autofluorescence beam.

7. The information processing apparatus according to claim 3, wherein At least one of the one or more fluorescence spectral references included in the reference spectrum S and the autofluorescence spectrum is reduced using an autofluorescence correction parameter having a value greater than 0 and less than 1.

8. The information processing apparatus according to claim 6, further comprising: The determining unit determines the autofluorescence correction parameters, wherein Determine unit The first standard deviation of the fluorescence intensity of the autofluorescence beam emitted by the unstained biological sample is calculated by performing arithmetic operations on the fluorescence signal measured from the unstained biological sample using the least squares method based on the autofluorescence spectrum. A second standard deviation of the fluorescence intensity of the autofluorescent beam emitted from the unstained biological sample is calculated by performing the arithmetic operation on the fluorescence signal measured from the unstained biological sample using the least squares method based on the fluorescence spectral reference of each of the fluorescent dyes and the autofluorescence spectrum. The autofluorescence correction parameters are determined such that the second standard deviation is consistent with or close to the first standard deviation.

9. The information processing apparatus according to claim 1, wherein The least squares method is the weighted least squares method.

10. An information processing method, comprising: The fluorescence intensity of one or more fluorescent beams and autofluorescent beams emitted from the one or more fluorescent dyes and the biological sample is calculated from the fluorescence signals measured by the least squares arithmetic operation using the least squares method, which uses the fluorescence spectral reference of each of the fluorescent dyes and the autofluorescence spectrum of the biological sample. In the arithmetic operation using the least squares method, an upper limit and a lower limit value for the fluorescence intensity are set for each of the one or more fluorescent beams and the spontaneously fluorescent beam.

11. A computer-readable storage medium having stored thereon a program for causing a computer to analyze biological samples labeled with one or more fluorescent dyes, wherein... The program causes the computer to perform the following processing: calculating, from the fluorescence signal measured from the biological sample, the fluorescence intensity of one or more fluorescent beams and autofluorescent beams emitted from the one or more fluorescent dyes and the biological sample, respectively, using least-squares arithmetic operations, wherein the least-squares method uses the fluorescence spectral reference of each fluorescent dye and the autofluorescence spectrum of the biological sample, and In the arithmetic operation using the least squares method, an upper limit and a lower limit value for the fluorescence intensity are set for each of the one or more fluorescent beams and the spontaneously fluorescent beam.

12. An optical measurement system, comprising: An excitation light source is used to illuminate a biological sample labeled with one or more fluorescent dyes using one or more excitation beams; The detection unit detects the fluorescence signal of the fluorescent beam and the autofluorescence emitted from the biological sample by irradiation with one or more excitation beams; as well as A separation unit calculates the fluorescence intensity of one or more fluorescent beams and autofluorescent beams emitted from the one or more fluorescent dyes and the biological sample, respectively, from the fluorescence signal detected by the detection unit using least-squares arithmetic operations. The least-squares method uses the fluorescence spectral reference of each fluorescent dye and the autofluorescence spectrum of the biological sample. In the arithmetic operation using the least squares method, an upper limit and a lower limit value for the fluorescence intensity are set for each of the one or more fluorescent beams and the spontaneously fluorescent beam.

Images