JP7209771B2 - Blood analyzer and blood analysis method - Google Patents

Description

The present invention relates to a blood analyzer and a blood analysis method.

A method for detecting erythrocytes infected with malaria parasites by flow cytometry is known. As shown in FIG. 23, in Patent Document 1, in a scattergram with two axes of scattered light intensity (FSCL) and fluorescence intensity (SFLL), the fluorescence intensity is greater than that of malaria-uninfected red blood cells and less than that of white blood cells. The appearance of erythrocytes infected with malaria parasites has been described. In addition, in this scattergram, from the region with the lowest fluorescence intensity, erythrocytes infected with ring form (single) malaria parasite, erythrocytes infected with malaria parasite with ring form (multiple), erythrocytes infected with tropozoite malaria parasite, schizont It has been described that erythrocytes containing malaria parasites at a given stage of development, such as erythrocytes infected with malaria parasites, appear in different regions in turn. Based on the malaria-infected red blood cells thus detected, the infection rate of the red blood cells infected with the malaria parasite is determined.

JP 2006-304774 A

The inventors found that when the presence or absence of malaria parasite infection is determined based on the particle distribution of such a scattergram, the determination result of malaria is positive even though the subject is not suffering from malaria. , so-called false positives were found to occur infrequently. The inventors then identified particles that caused false positives.

In view of such problems, an object of the present invention is to provide a blood analysis apparatus and a blood analysis method capable of determining the presence or absence of erythrocytes or extracellular vesicles containing nucleic acid inclusion bodies.

A first aspect of the present invention relates to a blood analyzer. A blood analyzer (10) according to this aspect includes a sample preparation section (30) that mixes a blood sample and a fluorescent dye that stains nucleic acids to prepare a measurement sample, and a measurement sample prepared by the sample preparation section (30). A light-receiving part (105) for receiving fluorescence generated by irradiating a sample with light, and red blood cells containing nucleic acid inclusion bodies and cells based on the fluorescence intensity obtained by processing the signal from the light-receiving part (105). a control unit (51) for determining the presence or absence of at least one of the outer vesicles by distinguishing from the presence or absence of malaria-infected red blood cells .

Extracellular vesicles are vesicles released from cells, and are a concept including microparticles derived from nucleated cells and microparticles derived from non-nucleated cells. Extracellular vesicles include, for example, exosomes, microvesicles (MV: Microvesicles), apoptotic bodies and the like.

Red blood cells containing nucleic acid inclusion bodies are red blood cells containing nucleic acid inclusion bodies that remain after the nucleic acid aggregates inside the cells. Nucleic acid inclusion bodies include Howell-Jolly bodies or basophilic plaques. In reticulocytes, RNA existing inside is dispersed within the reticulocytes, and nucleic acids do not exist as aggregates. Reticulocytes are therefore distinct from red blood cells, which contain inclusion bodies of nucleic acids.

"Determining the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles" means determining whether at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles is present. determination of the presence or absence of extracellular vesicles; and determination of the presence or absence of erythrocytes containing nucleic acid inclusion bodies. When determining whether or not at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles is present, the determination result is, for example, “at least one is present” or “both are absent”. When determining the presence or absence of extracellular vesicles, the determination result is, for example, "extracellular vesicles exist" or "extracellular vesicles do not exist". When determining the presence or absence of erythrocytes containing nucleic acid inclusion bodies, the determination result is, for example, "there are erythrocytes containing nucleic acid inclusion bodies" or "there are no erythrocytes containing nucleic acid inclusion bodies". The concept of "determining the presence or absence" is not limited to strictly determining whether particles are present, but also includes determining whether a certain number of particles are present in a blood specimen.

When classifying blood cells based on fluorescence intensity, the inventors found that red blood cells containing nucleic acid inclusion bodies contained in a blood sample and extracellular vesicles are different from the region where blood cells such as leukocytes are distributed. was found to be distributed in For example, erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles are distributed in a region different from that of blood cells such as leukocytes in a scattergram based on fluorescence intensity. In addition, erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles are distributed in a range different from that in which blood cells such as leukocytes are distributed, for example, in a frequency distribution diagram based on fluorescence intensity. Therefore, according to the blood analyzer of this aspect, the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles can be determined based on the fluorescence intensity.

In addition, erythrocytes infected with malaria parasites may be distributed in regions corresponding to erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles. In this case, it is difficult to accurately determine the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles. However, the inventors identified groups of particles corresponding to erythrocytes and extracellular vesicles containing nucleic acid inclusion bodies, and created a frequency distribution for fluorescence intensity based on the identified particle groups. It was found that in the case of blood samples in which erythrocytes were present, the variation in the frequency distribution was reduced. This is because when a blood sample contains erythrocytes infected with malaria parasites, in the frequency distribution, a mountain shape with a significantly high frequency tends to appear in a portion corresponding to single ring form erythrocytes. Therefore, based on the value indicating the variation of the frequency distribution, it is possible to determine whether or not there are erythrocytes infected with malaria parasites. It is possible to suppress the determination that at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles is present.

In the blood analyzer (10) according to this aspect, the control unit (51) specifies the particle group (G6) included in the range (403) where the fluorescence intensity is lower than that of the white blood cell, and the specified particle group (G6) Based on this, the presence or absence of at least one of erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles can be determined.

In the blood analyzer (10) according to this aspect, the sample preparation section (30) may be configured to further mix a diluent for contracting red blood cells to prepare a measurement sample.

In this case, the control unit (51) identifies the particle group (G6) included in the range (403) whose fluorescence intensity is greater than that of red blood cells contracted by the diluent and less than that of white blood cells, and the identified particle group Based on (G6), the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles can be determined.

In the blood analysis apparatus (10) according to this aspect, the light receiving units (103, 105) further receive scattered light generated by irradiating the measurement sample with light, and the control unit (51) controls the fluorescence intensity and the light receiving unit ( 105), and the scattered light intensity obtained by processing the signal from 105). By using the fluorescence intensity and the scattered light intensity, a particle group corresponding to erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles can be identified with high accuracy.

In this case, the control unit (51) identifies the particle group (G6) contained in the range (403) in which the fluorescence intensity and the scattered light intensity are smaller than those of the white blood cells, and based on the identified particle group (G6), the nucleic acid and/or extracellular vesicles.

In the blood analyzer (10) according to this aspect, the controller (51) determines the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles based on the number of particle groups (G6). can be configured to

In the blood analyzer (10) according to this aspect, the controller (51) controls the erythrocytes containing nucleic acid inclusion bodies and the extracellular It may be configured to determine the presence or absence of at least one of the vesicles. The presence of erythrocytes infected with the malaria parasite in the blood sample reduces the variability of the frequency distribution based on the particle swarm, and the absence of erythrocytes infected with the malaria parasite in the blood sample increases the variability of the frequency distribution based on the particle swarm. . Therefore, by determining the magnitude of the coefficient of variation, it is possible to determine the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles.

In this case, the value indicating the dispersion of the particle group (G6) can be the coefficient of variation, the standard deviation, or the half width of the frequency distribution diagram (500).

In the blood analyzer (10) according to this aspect, the controller (51) controls at least red blood cells containing inclusion bodies of nucleic acids and extracellular vesicles based on the fact that the value indicating the variation is equal to or greater than the first threshold value. It may be configured to determine the presence or absence of one.

In the blood analyzer (10) according to this aspect, the controller (51) controls the value indicating the variation to be equal to or greater than the first threshold and the number of the particle groups (G6) to be equal to or greater than the second threshold. can be configured to determine the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles. In this way, the presence or absence of at least one of erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles can be determined more accurately.

The blood analyzer (10) according to this aspect further comprises an output section (53) that outputs information, and the control section (51) controls the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles. can be configured to output the determination result regarding to the output unit (53). In this way, a doctor or the like can determine the possibility that a blood sample contains at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles, the possibility that extracellular vesicles are contained, and the possibility that blood samples contain erythrocytes containing nucleic acid inclusion bodies. can be included, etc. Physicians and the like can use, for example, red blood cells containing inclusion bodies of nucleic acids, or certain diseases that may be associated with extracellular vesicles, as criteria for determining the condition of a subject. In this case, the doctor or the like may perform further tests, such as checking the blood sample under a microscope.

In this case, the control unit (51) controls the erythrocytes containing nucleic acid inclusion bodies and the extracellular It can be configured to cause an output unit (53) to output information indicating the reliability of the determination result regarding the presence or absence of at least one of the vesicles. In this way, a doctor or the like can know the reliability of the determination result regarding the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles. In addition, doctors, etc. can know that red blood cells containing nucleic acid inclusion bodies and particles other than extracellular vesicles, such as red blood cells infected with malaria parasite, may be distributed. Further examination, such as confirmation with a microscope, can be performed.

In this case, the output unit (53) has a display unit (53a) for displaying information, and the control unit (51) outputs the information indicating the reliability to the erythrocytes containing nucleic acid inclusion bodies and the extracellular It may be configured to be displayed on the display section (53a) together with the determination result regarding the presence or absence of at least one of the vesicles. In this way, the doctor or the like can obtain the determination results regarding the presence or absence of at least one of the erythrocytes containing the nucleic acid inclusion bodies and the extracellular vesicles, and the determination regarding the presence or absence of at least one of the erythrocytes containing the nucleic acid inclusion bodies and the extracellular vesicles. You can visually grasp the reliability of the results.

In this case, the control unit (51) can be configured to further display the frequency distribution diagram (500) with respect to the fluorescence intensity of the particle group (G6) on the display unit (53a). In this way, a doctor or the like can grasp the condition of the blood sample quickly and in detail.

Also, the controller (51) may be configured to further display the scattergram (400) based on the fluorescence intensity on the display (53a). Also in this case, a doctor or the like can grasp the condition of the blood sample quickly and in detail.

A blood analysis apparatus (10) according to this aspect includes a flow cell (101) through which a measurement sample prepared by a sample preparation section (30) flows, and a light source (102) that irradiates the measurement sample flowing through the flow cell (101) with light. , and the light receiving portion (105) may be configured to receive fluorescence generated from particles contained in the measurement sample by irradiation with light.

In this case, the light source (102) may be configured to emit light in the blue-violet wavelength band. By doing so, the light irradiated to the flow cell can be narrowed down, so that small particles can be detected.

In the blood analyzer (10) according to this aspect, the extracellular vesicles are bodies released from cells, such as apoptotic bodies. In other words, extracellular vesicles in this case is a concept that includes apoptotic bodies.

In the blood analyzer (10) according to this aspect, the red blood cells containing nucleic acid inclusion bodies contain Howell-Jolly bodies or basophilic spots. In other words, nucleic acid inclusion bodies in this case are concepts that include Howell-Jolly bodies and basophilic spots. For example, if a physician believes that red blood cells containing Howell-Jolly bodies are present, he or she may assume splenic dysfunction, etc.; etc. can be assumed.

A second aspect of the present invention relates to a blood cell analysis method. The blood cell analysis method according to this aspect is based on fluorescence generated by irradiating a measurement sample prepared by mixing a blood sample and a fluorescent dye that stains nucleic acids with light, and erythrocytes containing nucleic acid inclusion bodies and cells The presence or absence of at least one of the outer vesicles is discriminated from the presence or absence of malaria-infected red blood cells (S103, S121 to S128, S131 to S136).

According to the blood analysis method according to this aspect, the same effects as those of the first aspect can be achieved.
A third aspect of the present invention relates to a blood cell analyzer. A blood cell analyzer (10) according to this aspect includes a sample preparation section (30) that mixes a blood sample and a fluorescent dye that stains nucleic acids to prepare a measurement sample, and a measurement sample prepared by the sample preparation section (30). a light-receiving unit (105) for receiving fluorescence generated by irradiating a sample with light, and based on the fluorescence intensity obtained by processing the signal from the light-receiving unit (105); , red blood cells containing nucleic acid inclusion bodies or specimens containing extracellular vesicles.
A fourth aspect of the present invention relates to a blood cell analysis method. The blood cell analysis method according to this aspect is based on fluorescence generated by irradiating a measurement sample prepared by mixing a blood sample and a fluorescent dye that stains a nucleic acid with light to detect a sample containing malaria-infected red blood cells and a nucleic acid. Red blood cells containing inclusion bodies or specimens containing extracellular vesicles are discriminated (S103, S121 to S128, S131 to S136).

According to the present invention, the presence or absence of erythrocytes and extracellular vesicles containing nucleic acid inclusion bodies that cause false positives can be determined, and the presence or absence of malaria parasite infection can be determined with higher accuracy.

FIG. 1 is a block diagram showing the configuration of a blood analyzer according to Embodiment 1. FIG. FIG. 2 is a schematic diagram showing the configuration of an optical detection unit according to Embodiment 1. FIG. FIG. 3 is a flowchart showing processing of a measuring unit according to the first embodiment; 4 is a flowchart illustrating processing of an information processing unit according to the first embodiment; FIG. FIG. 5A is a flowchart showing analysis processing according to the first embodiment. FIG. 5(b) is a schematic diagram showing a scattergram based on the first measurement according to the first embodiment. FIG. 6 is a flowchart showing determination processing for malaria according to the first embodiment. FIGS. 7A to 7D are scattergrams based on four specific specimens according to the first embodiment. 7(e) to (h) are frequency distribution diagrams based on specific four types of specimens according to the first embodiment. FIGS. 8A to 8D are scattergrams based on four specific specimens according to the first embodiment. FIGS. 8(e) to 8(h) are frequency distribution diagrams based on four specific specimens according to the first embodiment. 9A and 9B are scattergrams based on two specific types of specimens according to the first embodiment. 9(c) and (d) are frequency distribution diagrams based on two specific types of specimens according to the first embodiment. 10 is a schematic diagram illustrating a configuration of a screen displayed on the display unit according to the first embodiment; FIG. 11A and 11B are diagrams showing verification results of determination processing performed by the inventors according to the first embodiment. FIG. 12( a ) is a scattergram based on blood samples that produce false positives according to Embodiment 1; FIG. 12(b) is an image obtained when a blood sample that causes false positives according to Embodiment 1 is observed under a microscope. FIG. 13( a ) is a scattergram based on blood samples that produce false positives according to Embodiment 1; FIGS. 13(b) and 13(c) are images obtained by microscopic observation of blood specimens that cause false positives according to Embodiment 1. FIG. 14(a) is a scattergram created based on Jurkat cells before apoptosis induction according to Embodiment 1. FIG. 14(b) is a scattergram generated based on Jurkat cells after inducing apoptosis according to Embodiment 1. FIG. FIG. 15 is an image obtained when a blood sample of a mouse that produces false positives according to Embodiment 1 is observed under a microscope. FIG. 16 is a flowchart showing determination processing for malaria, erythrocytes containing nucleic acid inclusion bodies, and extracellular vesicles according to the second embodiment. 17 is a schematic diagram illustrating a configuration of a screen displayed on a display unit according to the second embodiment; FIG. FIG. 18 is a schematic diagram showing a scattergram based on the first measurement according to the third embodiment. FIG. 19 is a flowchart showing determination processing for erythrocytes and extracellular vesicles containing nucleic acid inclusion bodies according to the third embodiment. FIGS. 20(a) to (d) are scattergrams based on four specific specimens according to the third embodiment. 20(e) to (h) are frequency distribution diagrams based on specific four types of specimens according to the third embodiment. FIGS. 21A and 21B are scattergrams based on two specific specimens according to the third embodiment. 21(c) and (d) are frequency distribution diagrams based on two specific types of specimens according to the third embodiment. FIG. 22 is a schematic diagram illustrating a configuration of a screen displayed on a display unit according to the third embodiment; FIG. 23 is a schematic diagram for explaining the configuration of a scattergram according to related art.

<Embodiment 1>
The blood analyzer 10 of Embodiment 1 measures a measurement sample prepared from a blood sample and a reagent to identify a population containing erythrocytes infected with malaria parasite, and determines whether the blood sample is infected with malaria. judge.

Invasion of erythrocytes by merozoites, one of the forms of the malaria parasite, initiates the red endotype life cycle of the malaria parasite. In the redai type life cycle, the morphology of the malaria parasite changes in order from ring form to trophozoite to schizont. The schizont divides into multiple merozoites, destroying red blood cells in the process. This releases a large number of merozoites into the blood. The merozoites invade the next erythrocyte and begin the red intra-type life cycle again. By repeating such a cycle, the malaria parasite proliferates. Some of the merozoites released into the blood differentiate into dioecious gametocytes. When an infected person is sucked by a mosquito, the gametocytes enter the mosquito's body and the mosquito carries the malaria parasite.

Hereinafter, red blood cells that are not infected with malaria parasites are referred to as "malaria-uninfected red blood cells". Malaria-free red blood cells include mature red blood cells as well as reticulocytes. Red blood cells infected with malaria parasite are referred to as "malaria-infected red blood cells". Malaria-infected erythrocytes include erythrocytes infected with ringform malaria parasites, erythrocytes infected with trophozoite malaria parasites, and erythrocytes infected with schizont malaria parasites. Red blood cells infected with one ring form malaria parasite, ie containing one ring form malaria parasite, are referred to as "single ring form erythrocytes". Red blood cells infected with multiple ring-form malaria parasites, ie red blood cells containing multiple ring-form malaria parasites, are referred to as "multi-ring form erythrocytes."

As shown in FIG. 1 , the blood analyzer 10 includes a measuring section 11 and an information processing section 12 . The measurement unit 11 includes a measurement control unit 21 , a storage unit 22 , a suction unit 23 , a sample preparation unit 30 , an optical detection unit 41 , an electrical resistance detection unit 42 and a signal processing circuit 43 .

The measurement control unit 21 is configured by, for example, a CPU, an MPU, and the like. The measurement control unit 21 receives signals output from each unit of the measurement unit 11 and controls each unit of the measurement unit 11 . The measurement control section 21 communicates with the information processing section 12 . The storage unit 22 is composed of, for example, a ROM, a RAM, a hard disk, and the like. The measurement control unit 21 executes processing based on programs stored in the storage unit 22 . The suction unit 23 has a suction tube (not shown) and sucks a blood sample contained in a sample container (not shown) through the suction tube. A blood sample is whole peripheral blood drawn from a subject.

The sample container is transported by the rack transport section while being held by a sample rack (not shown), and positioned at the extraction position. The sample container positioned at the take-out position is taken out from the sample rack, stirred, and then transported to the suction position by the suction unit 23 . When the specimen container is positioned at the aspiration position, the aspirator 23 aspirates the blood specimen contained in the specimen container through the aspiration tube. The sample container is then returned to its original position in the sample rack. If the blood analyzer 10 does not have a structure for transporting the sample rack and a structure for transporting the sample container, the operator positions the sample container at the aspiration position.

Reagent containers 31 , 32 and 33 are connected to the sample preparation section 30 . The reagent container 31 contains a first diluent that contracts red blood cells. The reagent container 32 contains a staining reagent containing a fluorescent dye that specifically stains nucleic acids. The reagent container 33 contains the second diluent. The sample preparation section 30 has a reaction bath 34 . The suction unit 23 moves the suction tube above the reaction tank 34 and discharges the sucked blood sample into the reaction tank 34 . In the reaction tank 34, the blood sample, the first diluent, and the staining reagent are mixed to prepare the first measurement sample. The first measurement sample is used to measure white blood cells and malaria-infected red blood cells. In addition, the blood specimen and the second diluent are mixed in the reaction tank 34 to prepare a second measurement sample. A second measurement sample is used to measure red blood cells and platelets.

Here, the first diluent, the second diluent, and the staining reagent will be described.

The first diluent contains two surfactants with different hemolytic powers. Specifically, the first diluent contains 2.95 mM lauryltrimethylammonium chloride, which is a cationic surfactant, and 1.11 mM stearyltrimethylammonium chloride, which is a cationic surfactant. Stearyltrimethylammonium chloride has stronger hemolytic power than lauryltrimethylammonium chloride. The two types of surfactants may be surfactants other than the above combinations as long as they have different hemolytic powers.

The first diluent further contains 2.90 mM PBC-44, which is a nonionic surfactant, 20 mM ADA, an appropriate amount of NaCl, and 1 L of purified water. The pH of ADA is 6.1. Moreover, the pH of the first diluent is 5.0 or more and 7.0 or less. In order to contract the blood cells, the osmotic pressure of the first diluent is preferably 200 mOsm/kg·H2O or more. Specifically, the osmotic pressure of the first diluent is 200 mOsm/kg·H2O or more and 300 mOsm/kg·H2O or less.

According to the first diluent as described above, the red blood cells are contracted by the preparation of the first measurement sample, and the malaria-infected red blood cells are contracted while retaining the malaria parasite inside. Further, according to the first diluent, the erythrocyte membrane is dissolved to such an extent that the fluorescent dye can permeate into the erythrocyte and the shape of the erythrocyte is maintained. Specifically, in the case of malaria-infected erythrocytes, the cell membrane of erythrocytes is partially lysed so that the fluorescent dye can permeate while the malaria parasite is retained inside the erythrocytes.

The second diluent is a diluent for measuring erythrocytes by the sheath flow DC detection method, unlike the first diluent for contracting erythrocytes. The second diluent also serves as a sheath liquid for flowing the first measurement sample through the flow cell 101 of the optical detection unit 41 and as a sheath liquid for flowing the second measurement sample through the flow cell of the electrical resistance detection unit 42. Used. The first diluent is not used as sheath fluid.

The staining reagent contains a fluorescent dye that specifically stains nucleic acids, preferably a fluorescent dye that stains DNA more strongly than RNA. The fluorescent dye of Embodiment 1 is Hoechst 34580, for example. The staining reagent is obtained by dissolving a fluorescent dye in a solvent, and the solvent of the staining reagent is ethylene glycol, for example. The concentration of the fluorescent dye in the staining reagent is preferably 0.3 μM or more and 0.6 μM or less, specifically 0.45 μM. Also, the concentration of the fluorescent dye in the first measurement sample is preferably 0.15 μM or more and 1.0 μM or less. The chemical formula of Hoechst 34580 is shown below.

Non-malaria-infected erythrocytes are hardly stained with the above fluorescent dyes because they do not have nuclei. On the other hand, in the case of malaria-infected red blood cells, the nucleic acid of the malaria parasite that has entered the inside of the red blood cells is stained. Thus, malaria-uninfected red blood cells are largely unstained with a fluorescent dye, whereas malaria-infected red blood cells are stained with a fluorescent dye. Therefore, malaria-uninfected erythrocytes and malaria-infected erythrocytes can be discriminated based on the difference in fluorescence intensity in a scattergram, which will be described later. Since leukocytes have a nucleus, they are stained with a fluorescent dye, whereas platelet aggregation does not have a nucleus, so it is hardly stained with a fluorescent dye.

Instead of separating the first diluent and the staining reagent, a single reagent containing the first diluent and the fluorescent dye may be mixed with the blood sample to prepare the first measurement sample.

The optical detection unit 41 performs the first measurement based on the first measurement sample by flow cytometry. The optical detection section 41 includes a flow cell 101 , a light source 102 and light receiving sections 103 , 104 and 105 . During the first measurement, the flow cell 101 is supplied with the first measurement sample from the sample preparation section 30 through the channel.

Light emitted from the light source 102 is applied to the first measurement sample flowing through the flow cell 101 . When the first measurement sample is irradiated with light from the light source 102, particles in the first measurement sample generate forward scattered light, side scattered light, and fluorescence. The light receiving units 103 to 105 respectively receive forward scattered light, side scattered light, and fluorescence. The light receiving units 103 to 105 output signals based on the received light to the signal processing circuit 43, respectively. A detailed configuration of the optical detection unit 41 will be described later with reference to FIG.

The electrical resistance detection unit 42 performs the second measurement based on the second measurement sample by the sheath flow DC detection method. A flow cell (not shown) of the electrical resistance detection unit 42 is supplied with the second measurement sample from the sample preparation unit 30 through the flow path during the second measurement. The electrical resistance detection unit 42 applies a voltage to the second measurement sample flowing in the flow cell of the electrical resistance detection unit 42, and detects particles by detecting changes in the voltage due to the passage of the particles. The electrical resistance detection unit 42 outputs a detection signal to the signal processing circuit 43 .

The signal processing circuit 43 performs signal processing on the signals output from the light receiving units 103-105. Specifically, the signal processing circuit 43 extracts the waveform corresponding to the particle based on the signals output from the light receiving units 103 to 105, and uses the peak value, width, area, etc. of the waveform for each particle as the first information. Calculate as Hereinafter, peak values of waveforms based on signals output from light receiving units 103 and 105 are referred to as "forward scattered light intensity" and "fluorescence intensity", respectively. Note that the forward scattered light intensity and fluorescence intensity may be the width and area of the waveform, respectively. Further, the signal processing circuit 43 calculates the peak value of the signal output from the electrical resistance detection section 42 as second information.

The measurement control unit 21 converts the first information obtained by the signal processing of the signal processing circuit 43 during the first measurement and the second information obtained by the signal processing of the signal processing circuit 43 during the second measurement. , is stored in the storage unit 22 . When the first measurement and the second measurement are finished, the measurement control section 21 transmits the first information and the second information stored in the storage section 22 to the information processing section 12 as measurement data.

The information processing section 12 includes a control section 51 , a storage section 52 , an output section 53 and an input section 54 . The output unit 53 includes a display unit 53a and an audio output unit 53b.

The control unit 51 is configured by, for example, a CPU, an MPU, and the like. The control unit 51 receives a signal output by each unit of the information processing unit 12 and controls each unit of the information processing unit 12 . The control unit 51 communicates with the measurement unit 11 . The storage unit 52 is composed of, for example, a ROM, a RAM, a hard disk, and the like. The control unit 51 executes processing based on a program 52 a stored in the storage unit 52 . The program 52a includes a program for performing processes shown in FIGS. 4, 5A, and 6, which will be described later.

The control unit 51 determines the presence or absence of malaria parasite infection based on the value indicating the variation in the distribution of the particle group included in the range in which the single ring form red blood cells identified based on the fluorescence intensity and the scattered light intensity appear. This makes it possible to clearly determine whether or not malaria-infected erythrocytes are included in the particle group contained in the range in which single ring form erythrocytes appear. becomes positive, so-called false positive can be suppressed. Therefore, the presence or absence of malaria parasite infection can be determined with higher accuracy. The determination processing performed by the control unit 51 will be described later with reference to FIG.

The display unit 53a displays information. The display unit 53a is configured by, for example, a display. The audio output unit 53b outputs information as audio. The audio output unit 53b is composed of, for example, a speaker. The input unit 54 is composed of a mouse and a keyboard. The control unit 51 stores analysis results and the like in the storage unit 52 and outputs the analysis results and the like to the output unit 53 . The control unit 51 receives instructions from the operator via the input unit 54 .

Next, the optical detection section 41 shown in FIG. 1 will be described in detail.

As shown in FIG. 2, the optical detection unit 41 includes a flow cell 101, a light source 102, light receiving units 103 to 105, a collimator lens 111, a condenser lens 112, a beam stopper 113, a condenser lens 114, A dichroic mirror 115 and an optical filter 116 are provided.

The flow cell 101 is tubular and made of a translucent material. The first measurement sample is flowed through the flow cell 101 while being wrapped in the sheath liquid. As a result, the particles contained in the first measurement sample pass through the flow cell 101 while being aligned in a line.

The light source 102 emits light in the blue-violet wavelength band. Specifically, the light source 102 is a semiconductor laser light source and emits blue-violet laser light with a wavelength of 405 nm. The light emitted from the light source 102 excites the fluorochrome contained in the staining reagent, causing the fluorochrome to emit fluorescence in a predetermined wavelength band. Note that the light source 102 may emit light in a band other than the blue-violet wavelength band as long as the emitted light causes the fluorescent dye to emit fluorescence. In addition, the shorter the wavelength of the light emitted from the light source 102, the smaller the light irradiating the flow cell 101 can be narrowed down, so that smaller particles can be detected. Therefore, it is desirable to set the wavelength of the light emitted from the light source 102 to the blue-violet wavelength band as described above.

The collimator lens 111 and the condenser lens 112 collect the light emitted from the light source 102 and irradiate the first measurement sample flowing through the flow cell 101 with the light. As described above, when the first measurement sample is irradiated with light, the particles in the first measurement sample generate forward scattered light, side scattered light, and fluorescence. Forward scattered light reflects information about the particle size, side scattered light reflects the internal information of the particle, and fluorescence reflects the degree of staining of the particle. Of the light irradiated to the flow cell 101 , the light that passes through the flow cell 101 without being irradiated to the particles is blocked by the beam stopper 113 . The light receiving section 103 is composed of, for example, a photodiode. The light receiving unit 103 receives forward scattered light and outputs an electrical signal corresponding to the received forward scattered light.

Condensing lens 114 collects side scattered light and fluorescent light generated on the side of flow cell 101 . The dichroic mirror 115 reflects the side scattered light condensed by the condensing lens 114 and transmits the fluorescence condensed by the condensing lens 114 . The light receiving section 104 is composed of, for example, a photodiode. The light receiving unit 104 receives the side scattered light reflected by the dichroic mirror 115 and outputs an electrical signal corresponding to the received side scattered light. The optical filter 116 transmits only the fluorescence to be received by the light receiving section 105 out of the light transmitted through the dichroic mirror 115 . The light receiving section 105 is composed of, for example, an avalanche photodiode. The light receiving unit 105 receives fluorescence transmitted through the optical filter 116 and outputs an electrical signal corresponding to the received fluorescence.

Next, processing of the measurement unit 11 will be described with reference to a flowchart.

As shown in FIG. 3 , in step S<b>11 , the measurement control section 21 determines whether or not a start instruction has been received from the information processing section 12 . Upon receiving the start instruction, the measurement control unit 21 prepares the first measurement sample and the second measurement sample in step S12.

Specifically, the sample rack is transported by the rack transporter, and the sample container is positioned at the extraction position. The measurement control unit 21 controls each part of the measurement unit 11, takes out the sample container from the sample rack at the take-out position, stirs the sample container, and positions the stirred sample container at the aspiration position. The measurement control unit 21 controls the aspirating unit 23 to aspirate the blood sample from the sample container through the aspirating tube and discharge the aspirated blood sample into the reaction vessel 34 . The sample container that has been aspirated is returned to its original position on the sample rack. The measurement control unit 21 controls the sample preparation unit 30 to mix the blood specimen, the first diluent, and the staining reagent in the reaction tank 34 to prepare the first measurement sample. The measurement control unit 21 also controls the sample preparation unit 30 to mix the blood sample and the second diluent in the reaction tank 34 to prepare the second measurement sample.

If blood analyzer 10 does not have a configuration for transporting a sample rack and a configuration for transporting a sample container, measurement control unit 21 controls aspiration unit 23 to control the sample container positioned at the aspiration position by the operator. Aspirate the blood sample from the aspiration tube.

In step S13, the measurement control section 21 controls the optical detection section 41 to perform the first measurement, and controls the electrical resistance detection section 42 to perform the second measurement. At this time, the measurement control unit 21 allows the first measurement sample to flow through the flow cell 101 and causes the storage unit 22 to store the first information acquired during the time T1. In addition, the measurement control unit 21 causes the second measurement sample to flow through the flow cell of the electrical resistance detection unit 42, and causes the storage unit 22 to store the second information acquired during the time T2. In step S14, the measurement control unit 21 transmits the first information and the second information stored in the storage unit 22 in the measurement in step S13 to the information processing unit 12 as measurement data in the normal mode.

Subsequently, in step S<b>15 , the measurement control section 21 determines whether or not an instruction to start the triple counting mode has been received from the information processing section 12 . If the instruction to start the triple counting mode has not been received, the measurement control section 21 determines in step S16 whether or not an instruction to end has been received from the information processing section 12 . If no end instruction has been received, the process returns to step S15. When the termination instruction is received without receiving the instruction to start the triple counting mode, the processing of the measuring unit 11 ends.

Upon receiving the triple counting mode start instruction, in step S17, the measurement control unit 21 prepares the first measurement sample and the second measurement sample again in the same manner as in step S12. In step S18, the measurement control unit 21 controls the optical detection unit 41 to perform the first measurement in the triple counting mode, and controls the electrical resistance detection unit 42 to perform the second measurement in the triple counting mode. At this time, the measurement control unit 21 allows the first measurement sample to flow through the flow cell 101, and causes the storage unit 22 to store the first information acquired during the time three times the time T1. The measurement control unit 21 causes the second measurement sample to flow through the flow cell of the electrical resistance detection unit 42, and causes the storage unit 22 to store the second information acquired during the time three times the time T2. As a result, the first information based on about three times the amount of the first measurement sample and the second information based on about three times the amount of the second measurement sample are obtained compared to the normal mode measurement performed in step S13. is obtained.

In step S19, the measurement control unit 21 transmits the first information and the second information stored in the storage unit 22 in the measurement in step S18 to the information processing unit 12 as measurement data in the triple counting mode. Thus, the processing of the measurement unit 11 ends. After completing the process shown in FIG. 3, the measurement control unit 21 returns the process to step S11, and performs similar measurements on subsequent blood samples.

Next, processing of the information processing section 12 will be described with reference to a flowchart.

As shown in FIG. 4, in step S21, the control unit 51 determines whether or not a start instruction has been received from the operator via the input unit . Upon receiving the start instruction from the operator, the control unit 51 transmits the start instruction to the measurement unit 11 in step S22. As a result, the processing after step S12 in FIG. 3 is started in the measurement unit 11 . Subsequently, in step S23, the control unit 51 determines whether or not the measurement data in the normal mode transmitted by the measurement unit 11 in step S14 of FIG. 3 has been received.

Upon receiving the measurement data in the normal mode, in step S24, the control unit 51 determines whether or not the number of particle groups G3 per unit volume is equal to or greater than the threshold th1 based on the measurement data in the normal mode. The particle group G3 is a particle group included in a range where malaria-infected red blood cells, which will be described later, appear. The particle group G3 will be described later with reference to FIG. 5(b). Note that the threshold th1 is set between 100 and 500, and is set to 100, for example. The threshold th1 can be changed via the input unit 54 by the operator. In step S24, the control unit 51 may determine whether or not the number of particle groups G3 is greater than or equal to a predetermined threshold.

When the number of particle groups G3 per unit volume is equal to or greater than the threshold th1, in step S25, the control unit 51 transmits an end instruction to the measurement unit 11, and advances the process to step S26. As a result, a determination of YES is made in step S16 of FIG. 3, and the processing of the measurement unit 11 shown in FIG. 3 ends. On the other hand, when the number of particle groups G3 per unit volume is less than the threshold value th1, the control unit 51 transmits an instruction to start the triple counting mode to the measurement unit 11 in step S28. As a result, YES is determined in step S15 of FIG. 3, and the processes of steps S17 to S19 of FIG. 3 are executed. Subsequently, in step S29, the control unit 51 determines whether or not the measurement data in the triple counting mode transmitted by the measurement unit 11 in step S19 of FIG. 3 has been received. Upon receiving the measurement data in the triple counting mode, the control unit 51 advances the process to step S26.

Here, when the number of particle groups G3 per unit volume is less than the threshold th1, based on the measurement data in the normal mode, in the determination process described later, for example, the determination of "malaria negative" is easily performed. is not preferred. Even if the subject has malaria, the malaria-infected red blood cells in the subject's blood sample may be low. In this case, if a "malaria-negative" determination is made, a false negative will occur. In addition, even if malaria-infected red blood cells gradually decrease with treatment, it is important to monitor until the malaria-infected red blood cells are completely gone.

Therefore, when the number of particle groups G3 is small, the control unit 51 further acquires measurement data in the triple counting mode, and uses the acquired measurement data in the triple counting mode to perform an analysis process, which will be described later. As a result, analysis processing is performed using the first information and the second information based on the blood cell count that is approximately three times the number of blood cells obtained in the normal mode. It is less likely to be influenced by Therefore, it is possible to prevent the output of low-precision malaria analysis results.

Subsequently, in step S26, the control unit 51 performs analysis processing. The analysis processing will be described later with reference to FIG. 5(a). In step S<b>27 , the control unit 51 outputs the analysis result obtained by the analysis processing in step S<b>26 to the output unit 53 . Specifically, the control unit 51 displays the number of blood cells, the scattergram, the frequency distribution map, the determination result, the information indicating the degree of reliability, etc. as the analysis result on the display unit 53a. The screen displayed on the display unit 53a will be described later with reference to FIG. Note that control unit 51 may output these pieces of information to a device other than blood analysis device 10 . Further, the control unit 51 may output the number of blood cells, the determination result, etc. by voice from the voice output unit 53b.

When the processing shown in FIG. 4 is completed, the control unit 51 returns the processing to step S21, determines YES in step S21 if there is a subsequent sample container, and performs the processing from step S22 onward for the subsequent blood sample in the same manner. go to If there is no subsequent sample container, the control unit 51 causes the process to wait in step S21 until a start instruction is received again.

Next, the analysis processing will be described with reference to the flowchart of FIG. 5(a).

In the following steps S101 and S102, when the measurement data in the triple counting mode is not received, the control unit 51 performs counting using the measurement data in the normal mode, and when the measurement data in the triple counting mode is received. , counting is performed using the measured data in the triple counting mode.

As shown in FIG. 5A, in step S101, the control unit 51 detects blood cells based on the second information included in the measurement data, that is, the second information obtained by the second measurement by the electrical resistance detection unit 42. to count. Specifically, the controller 51 counts red blood cells and platelets. In step S<b>102 , the control unit 51 counts blood cells based on the first information included in the measurement data, that is, the first information obtained by the first measurement by the optical detection unit 41 . Specifically, the control unit 51 counts white blood cells, malaria-uninfected red blood cells, malaria-infected red blood cells, single ring form red blood cells, and multi ring form red blood cells.

Here, the counting of blood cells in step S102 will be described with reference to FIG. 5(b).

In the scattergram 200 shown in FIG. 5B, the vertical axis indicates forward scattered light intensity, and the horizontal axis indicates fluorescence intensity. Each particle detected in the first measurement is plotted in scattergram 200 based on the forward scattered light intensity and fluorescence intensity associated with each particle.

In scattergram 200, white blood cells are generally distributed in region 201 where forward scattered light intensity and fluorescence intensity are high. Malaria-uninfected red blood cells are smaller than white blood cells and are contracted by the first diluent. Also, malaria-uninfected erythrocytes are hardly stained with fluorescent dyes. Therefore, non-malaria-infected red blood cells are generally distributed in region 202 . The forward scattered light intensity of region 202 is smaller than region 201 corresponding to white blood cells. The fluorescence intensity of region 202 is lower than that of region 201 .

Malaria-infected red blood cells are also smaller than white blood cells and are contracted by the first diluent. In addition, malaria-infected erythrocytes are stained with a fluorescent dye because they contain malaria parasites. Therefore, malaria-infected red blood cells are generally distributed in region 203 . The forward scattered light intensity of region 203 is lower than region 201 corresponding to white blood cells. The fluorescence intensity of region 203 is greater than region 202 corresponding to non-malaria-infected red blood cells and less than region 201 corresponding to white blood cells.

Since malaria-infected erythrocytes contract while retaining malaria parasites inside, the size of the malaria-infected erythrocytes corresponds to the morphology of the malaria parasites retained therein. Thus, single and multi-ring form red blood cells are generally smaller in size than red blood cells infected with other forms of malaria parasites, and single- and multi-ring form red blood cells are comparable in size. In addition, since multi-ring-form red blood cells retain multiple malaria parasites inside, the fluorescence intensity of multi-ring-form red blood cells is greater than that of single-ring-form red blood cells. Thus, single ring form red blood cells are generally distributed in region 204 and multi ring form red blood cells are generally distributed in region 205 . Regions 204 and 205 are included in region 203, which corresponds to malaria-infected red blood cells. The regions 204 and 205 are adjacent to each other in the horizontal direction without overlapping each other, and are positioned at the left end within the region 203 . The fluorescence intensity of region 205 is greater than that of region 204 .

Note that "the fluorescence intensity of the first region is greater than that of the second region" means that the maximum value and minimum value of the fluorescence intensity of the first region are respectively greater than the maximum value and minimum value of the fluorescence intensity of the second region. indicates “The fluorescence intensity of the first region is smaller than the second region” means that the maximum and minimum fluorescence intensity values of the first region are smaller than the maximum and minimum fluorescence intensity values of the second region, respectively. . The same applies to the expression regarding the magnitude relationship between the forward scattered light intensity of the first region and the forward scattered light intensity of the second region.

In the process of step S102, the control unit 51 counts blood cells based on the fluorescence intensity and scattered light intensity of the measurement data. Specifically, the control unit 51 controls the particle group G1 included in the range in which white blood cells appear, the particle group G2 included in the range in which non-malaria-infected red blood cells appear, and the particle group G3 included in the range in which malaria-infected red blood cells appear. , particle group G4 included in the range where single-ring-form red blood cells appear, and particle group G5 included in the range where multi-ring-form red blood cells appear. In the scattergram 200, the range in which white blood cells appear corresponds to region 201, the range in which malaria-uninfected red blood cells appear corresponds to region 202, the range in which malaria-infected red blood cells appear corresponds to region 203, and the range in which single-ring form red blood cells appear. corresponds to region 204 and the range in which multi-ring form red blood cells appear corresponds to region 205 . Then, the control unit 51 acquires the number of each blood cell by counting the number of each identified particle group.

In counting the blood cells in step S102, the control unit 51 does not create the scattergram and set the region, but counts the blood cells by data processing following the same procedure as when creating the scattergram and setting the region. conduct. However, the present invention is not limited to this, and the control unit 51 may create a scattergram, set a region in which blood cells are distributed in the created scattergram, and count blood cells contained in the set region. Although the control unit 51 does not create a scattergram for the purpose of counting blood cells, it creates a scattergram when displaying a screen, which will be described later, on the display unit 53a.

Regions corresponding to gametocytes, trophozoites, and schizonts may be set in the scattergram 200 . In this case, in step S102, the control unit 51 counts the number of particle groups included in the range in which gametocytes appear, the number of particle groups included in the range in which trophozoites appear, and the number of particle groups included in the range in which schizonts appear. You may

Subsequently, in step S103, the control unit 51 performs determination processing, which will be described later with reference to FIG. By the determination processing, the presence or absence of malaria is determined for the target blood sample. Thus, the analysis processing ends.

Here, the inventors found that in a blood sample collected from a subject not suffering from malaria, particles may be distributed in the region 203 corresponding to malaria-infected red blood cells. In addition, the inventors found that in a blood sample collected from a subject not suffering from malaria, the particles distributed in region 203 included apoptotic bodies, red blood cells including Howell-Jolly bodies, and the like. rice field. Apoptotic bodies are a type of extracellular vesicles. Howell-Jolly bodies are a type of nucleic acid inclusion bodies. The inventors also found that apoptotic bodies and erythrocytes containing Howell-Jolly bodies are distributed from the region 204 corresponding to single-ring-form erythrocytes in the direction of increasing fluorescence intensity and forward scattered light intensity. I found

The details of how the inventors discovered that erythrocytes containing apoptotic bodies and Howell-Jolly bodies are distributed in the region 203 will be described later with reference to FIGS.

When red blood cells containing apoptotic bodies or Howell-Jolly bodies are distributed in the region 203 in this manner, false positives may occur if a malaria-positive determination is made for the reason that the particles are distributed in the region 203, for example. There is Therefore, the inventors considered determining whether or not malaria-infected red blood cells are contained based on the variation in frequency distribution with respect to fluorescence intensity. Hereinafter, in the determination processing shown in FIG. 6, malaria determination processing is performed so that erroneous determination of malaria positive is suppressed when red blood cells containing apoptotic bodies or Howell-Jolly bodies are distributed in the region 203. .

As shown in FIG. 6, in step S111, the control unit 51 determines whether or not the number of particle groups G3 per unit volume is equal to or greater than a threshold th11. The particle group G3 is, as shown in FIG. 5(b), a particle group included in the range where malaria-infected red blood cells appear. The number of particle groups G3 per unit volume is obtained, for example, by dividing the number of acquired particle groups G3 by the volume of the first measurement sample flowed through the flow cell 101 during the acquisition of the first information. The threshold th11 is set based on the number of particle groups G3 per unit volume so that the target blood specimen can be determined to be “malaria negative”. The threshold th11 is set to 200, for example.

In step S111, the volume used for division may be the volume of the blood sample corresponding to the volume of the first measurement sample instead of the volume of the first measurement sample. In step S111, the control unit 51 may determine whether or not the number of particle groups G3 is equal to or greater than a predetermined threshold. Also, the threshold th11 can be changed via the input unit 54 by the operator. Thresholds th12 and th13, which will be described later, and threshold values th21, th22, th23, th31, and th32, which will be described later in the second and third embodiments, can also be changed by the operator through the input unit 54 in the same manner. This allows the operator to fine-tune the determination in each determination step.

When the number of particle groups G3 per unit volume is less than the threshold th11, the control unit 51 determines that the target blood sample is “malaria negative” and stores the determination result in the storage unit 52 in step S112. Then, the control unit 51 terminates the determination process.

On the other hand, when the number of particle groups G3 per unit volume is equal to or greater than the threshold th11, in step S113, the control unit 51 determines that the target blood sample is “malaria positive?” Remember. The determination result of "malaria positive?" indicates a state in which it is highly likely that the target blood sample contains malaria-infected red blood cells, but it is difficult to determine the target blood sample as "malaria positive."

Subsequently, in step S114, the control unit 51 determines whether or not the number of particle groups G4 per unit volume is equal to or greater than a threshold th12. The particle group G4 is, as shown in FIG. 5(b), a particle group included in the range where single-ring form red blood cells appear. The number of particle groups G4 per unit volume is obtained, for example, by dividing the number of acquired particle groups G4 by the volume of the first measurement sample flowed through the flow cell 101 during the acquisition of the first information. The threshold th12 is set based on the number of particle groups G4 per unit volume so that it can be determined whether or not malaria-infected red blood cells are distributed in the region 204 corresponding to the single ring form red blood cells in the target blood sample. be done. The threshold th12 is set to 150, for example.

In step S114, the volume used for division may be the volume of the blood sample corresponding to the volume of the first measurement sample instead of the volume of the first measurement sample. In step S114, the control unit 51 may determine whether or not the number of particle groups G4 is greater than or equal to a predetermined threshold. Also, the process of step S114 can be omitted. However, in the case of a blood specimen infected with malaria parasite, since many particles are distributed particularly in the region 204, it is desirable to determine the number of particle groups G4 in step S114.

If the number of particle groups G4 per unit volume is less than the threshold th12, the control unit 51 terminates the determination process. In this case, the determination result is "malaria positive?" stored in step S113.

On the other hand, when the number of particle groups G4 per unit volume is equal to or greater than the threshold th12, in step S115, the control unit 51 calculates a value indicating the dispersion of the frequency distribution with respect to the fluorescence intensity of the particle groups G4. Specifically, in step S115, the control unit 51 calculates the coefficient of variation of the frequency distribution with respect to the fluorescence intensity of the particle group G4. Note that the value indicating the dispersion of the frequency distribution calculated in step S115 is not limited to the coefficient of variation, and may be the standard deviation or the half width of the frequency distribution map.

In calculating the coefficient of variation in step S115, the control unit 51 does not create a frequency distribution map, but calculates the coefficient of variation by data processing following the same procedure as when creating a frequency distribution map. However, without being limited to this, the control unit 51 may create a frequency distribution chart to calculate the coefficient of variation. Note that the control unit 51 does not create a frequency distribution map for the purpose of calculating the coefficient of variation, but creates a frequency distribution map when displaying a screen described later on the display unit 53a, and displays the created frequency distribution map on the display unit. 53a.

The value indicating the variation calculated in step S115 may be a value indicating the variation of the frequency distribution with respect to the light intensity other than the fluorescence intensity. Further, the value indicating the variation calculated in step S115 is not limited to the value indicating the variation in the uniaxial distribution, but may be a value indicating the variation in the distribution on the 2 or 3 axes. Variation is acceptable. Also, the scattergram 200 may be created based on a combination of other light intensities, not limited to the fluorescence intensity and the forward scattered light intensity.

Subsequently, in step S116, the control unit 51 determines whether or not the coefficient of variation calculated in step S115 is less than the threshold th13. The threshold th13 is set so that the target blood sample can be determined as "malaria positive" based on the coefficient of variation. The threshold th13 is set to 10%, for example.

Here, the amount of nucleic acid possessed by single ring form erythrocytes is substantially predetermined, whereas the amount of nucleic acid possessed by apoptotic bodies and the amount of nucleic acids possessed by erythrocytes containing Howell-Jolly bodies varies. Therefore, when the particles are distributed in the region 204 corresponding to single ring form red blood cells, if malaria-infected red blood cells are present in the blood sample, the variation in the frequency distribution based on the particle group G4 becomes small, and malaria-infected red blood cells are present in the blood sample. Otherwise, the dispersion of the frequency distribution based on the particle group G4 will increase. Therefore, by determining the magnitude of the coefficient of variation in step S116, it is possible to determine the presence or absence of malaria-infected red blood cells.

If the coefficient of variation is less than the threshold th13, the control unit 51 determines that the target blood sample is “malaria positive” and stores the determination result in the storage unit 52 in step S117. Then, the control unit 51 terminates the determination process. In this case, the determination result is changed from "malaria positive?" stored in step S113 to "malaria positive".

On the other hand, when the coefficient of variation is equal to or greater than the threshold th13, in step S118, the control unit 51 determines “malaria positive? "Scatter abnormality" included in the determination result in this case is information indicating the degree of reliability of the determination result regarding malaria parasite infection. Specifically, "scatter abnormality" is information indicating that the reliability of the determination result for malaria is not high. Then, the control unit 51 terminates the determination process.

Note that when the coefficient of variation is equal to or greater than the threshold th13, the possibility of the presence of malaria-infected red blood cells is low, so it is possible to determine that no malaria-infected red blood cells are present. However, in this case, it is desirable to determine "malaria negative, scatter abnormal" instead of simply determining "malaria negative".

Next, with reference to FIGS. 7(a) to 9(d), determinations performed on 10 types of specimens will be specifically described.

Figures 7(a) and (b) are scattergrams 200 based on blood samples taken from a subject suffering from malaria. Figures 7(c) and (d) are scattergrams 200 based on cultured malaria. FIGS. 8(a) and (b) are scattergrams 200 when apoptosis is induced in Jurkat cells. Figures 8(c) and (d) are scattergrams 200 based on blood samples taken from subjects who do not have malaria. Figures 9(a) and (b) are scattergrams 200 based on blood samples taken from malaria-free mice. In both cases, particles located at the left edge of region 202 are cut as being noise components.

It should be noted that blood samples collected from mice always contain red blood cells containing Howell-Jolly bodies. In the description of the determination below, a blood sample taken from a mouse is used as an example of a human blood sample containing red blood cells containing Howell-Jolly bodies.

7(a) to (d), FIGS. 8(a) to (d), and FIGS. 9(a) and (b), the region 203 corresponding to malaria-infected red blood cells is and a predetermined number of particles appear in a region 204 corresponding to single ring form red blood cells. The numbers of particle groups G4 in FIGS. 7(a) to (d), FIGS. 8(a) to (d), FIGS. 9(a) and (b) are 18768, 8208, 262, 204, 373 and 215, respectively. , 359, 5923, 4037, 1147. Therefore, according to the determination process shown in FIG. 6, YES is determined in steps S111 and S114, and the variation coefficient of the frequency distribution with respect to the fluorescence intensity of the particle group G4 is calculated in step S115.

FIGS. 7(e)-(h), FIGS. 8(e)-(h), FIGS. 9(c) and (d) are respectively FIGS. 7(a)-(d) and FIGS. 8(a)-( d), a frequency distribution map 300 created based on the scattergrams 200 of FIGS. 9(a) and 9(b). In the frequency distribution diagram 300, the horizontal axis indicates fluorescence intensity and the vertical axis indicates frequency. A frequency distribution diagram 300 shows a frequency distribution based only on the particle group G3 included in the range where single-ring-form red blood cells appear. The frequency distribution diagram 300 is normalized based on the maximum frequency value.

Referring to the frequency distribution diagrams 300 of FIGS. 7(e) to (h), the shape of the frequency distribution is sharp in any case. The coefficients of variation in FIGS. 7(e) to (h) are 7.3%, 6.4%, 7.4% and 6.3%, respectively. Therefore, in all cases of FIGS. 7(e) to (h), YES is determined in step S116 of FIG. 6, and these samples are determined to be "malaria positive". Here, the specimens shown in FIGS. 7(e) to (h) are all malaria-infected specimens, as described above. Therefore, according to the determination process shown in FIG. 6, it can be seen that the determination result of "malaria positive", which is an appropriate determination result, can be obtained for these four samples.

On the other hand, referring to the frequency distribution diagrams 300 of FIGS. 8(e) to (h) and FIGS. 9(c) and (d), the shape of the frequency distribution is not completely sharp in any case. The coefficients of variation in FIGS. 8(e) to (h), FIGS. 9(c) and (d) are 19.6%, 18.8%, 25.1%, 21.1% and 16.5%, respectively. , 18.0%. Therefore, in all cases of FIGS. 8 (e) to (h), 9 (c), and (d), it is determined as NO in step S116 in FIG. be judged. Here, the specimens shown in FIGS. 8(e) to (h) and FIGS. 9(c) and (d) are all specimens not infected with malaria. Therefore, according to the determination process shown in FIG. 6, it is possible to prevent these six specimens from being erroneously determined to be "malaria positive".

As described above, according to the determination process shown in FIG. 6, even if particles appear in the areas 203 and 204 when malaria-infected red blood cells are not present in the blood sample, an erroneous determination of "malaria positive" is avoided. By doing so, it is possible to make an appropriate determination of "malaria positive? scatter abnormality". In addition, when malaria-infected red blood cells are present in the blood sample, it is possible to make an appropriate determination of "malaria positive". Therefore, the presence or absence of malaria parasite infection can be determined with high accuracy while suppressing false positives.

In addition, when a person is infected with malaria, spleen function is impaired, and blood samples may always contain red blood cells containing Howell-Jolly bodies. In this case, the blood sample contains both malaria-infected red blood cells and red blood cells containing Howell-Jolly bodies. is avoided.

Next, the screen 60 displayed on the display unit 53a in step S27 of FIG. 4 will be described.

As shown in FIG. 10, the screen 60 includes list areas 61 and 62, a comment area 63, a scattergram 200, and a frequency distribution diagram 300. FIG. A list area 61 displays the count results of white blood cells, red blood cells, platelets, etc. in a list format. A list area 62 displays the count result of malaria-infected red blood cells and the ratio of malaria-infected red blood cells. The malaria-infected red blood cell ratio is obtained by dividing the blood cell count in the region 203 corresponding to the malaria-infected red blood cells shown in FIG. 5(b) by the red blood cell count obtained in step S101 of FIG. 5(a).

The comment area 63 displays the judgment result obtained by the judgment processing of FIG. Specifically, nothing is displayed in the comment area 63 when step S112 in FIG. 6 is executed. Also in this case, "malaria negative" may be displayed in the comment area 63. If NO is determined in step S114 of FIG. 6, the comment area 63 displays "malaria positive?". When step S117 in FIG. 6 is executed, the comment area 63 displays "malaria positive". When step S118 of FIG. 6 is executed, as illustrated in FIG. 10, the comment area 63 displays "Malaria positive? Abnormal scattergram".

When "malaria positive" or "malaria negative" is displayed in the comment area 63, the doctor or the like can determine whether or not the subject is suffering from malaria, and whether or not the subject under treatment is completely cured of malaria. It is possible to determine whether or not In addition, when the comment area 63 displays "Positive for malaria?", the doctor or the like can know that the subject may be suffering from malaria. In this case, the doctor or the like can perform further tests, such as checking the blood sample under a microscope.

Further, when "scatter abnormality" is displayed in the comment area 63, the doctor or the like can know that the reliability of the determination result regarding the presence or absence of malaria is not high. In addition, doctors can know that particles other than malaria-infected red blood cells, such as extracellular vesicles and nucleic acid inclusion bodies, may be distributed in region 203 of scattergram 200 . In this case, the doctor or the like can perform further tests, such as checking the blood sample under a microscope. In addition, since the scattergram 200 and the frequency distribution diagram 300 are displayed on the screen 60, the doctor or the like can grasp the condition of the blood sample quickly and in detail.

Next, verification of determination processing performed by the inventors will be described.

The inventors omit step S114 in the determination process of Embodiment 1 shown in FIG. That is, in the determination process of Verification Example 1, when the determination of both steps S111 and S116 is YES, the determination result is "malaria positive", and when the determination of one of steps S111 and S116 is NO , the judgment result was "malaria negative".

In addition, the inventors omit steps S114 to S118 in the determination process of Embodiment 1 shown in FIG. bottom. That is, in the determination process of Verification Example 2, when the determination in step S111 is YES, the determination result is "malaria positive", and when the determination in step S111 is NO, the determination result is "malaria negative". was done.

The inventors prepared 27 malaria-positive specimens and 130 malaria-negative specimens, prepared a first measurement sample based on these specimens, and measured the prepared first measurement sample by the optical detection unit 41. bottom. Then, using the measurement data obtained by the first measurement, the inventors performed the analysis process shown in FIG. did Based on the malaria determination results obtained by the determination processes of Verification Examples 1 and 2, the inventors verified whether or not malaria was properly determined. In this verification, an automatic segmentation algorithm was used to fine-tune the region of the scattergram 200 shown in FIG. 5(b) for each specimen. In this verification, the threshold th11 in step S111 was set to 30, and the threshold th13 in step S116 was set to 20%.

As shown in FIG. 11(a), according to Verification Example 1, all 27 malaria-positive specimens were properly determined to be malaria-positive. Also, of the 130 malaria-negative specimens, 2 specimens were falsely identified as malaria-positive, while 128 specimens were correctly identified as malaria-negative. From this result, in Verification Example 1, the sensitivity was 27/27=100% and the specificity was 128/130=98.5%.

Subsequently, as shown in FIG. 11(b), according to Verification Example 2, all 27 malaria-positive specimens were properly determined to be malaria-positive. Also, of the 130 malaria-negative specimens, 48 specimens were correctly identified as malaria-negative, while 82 specimens were incorrectly identified as malaria-positive. From this result, in Verification Example 2, the sensitivity was 27/27=100% and the specificity was 48/130=36.9%.

From the results of FIGS. 11A and 11B, it was found that the determination process of Verification Example 1 can significantly improve the specificity compared to the determination process of Verification Example 2. FIG. Therefore, according to the determination process shown in FIG. 6 of the first embodiment, in addition to the determination in step S111, the determination in step S116 using the coefficient of variation is performed, so that it is possible to improve the specificity and suppress false positives. I can say.

<Discussion on erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles>
The inventors found that the region 203 corresponding to the malaria-infected red blood cells shown in FIG. The background to discovering that erythrocytes are distributed will be explained. Red blood cells containing nucleic acid inclusion bodies are red blood cells containing nucleic acid inclusion bodies that remain after the nucleic acid aggregates inside the cells. In reticulocytes, RNA existing inside is dispersed within the reticulocytes, and nucleic acids do not exist as aggregates. Reticulocytes are therefore distinct from red blood cells, which contain inclusion bodies of nucleic acids.

First, the inventors investigated a method for determining positive malaria determination results when particles were distributed in the region 203 corresponding to malaria-infected red blood cells. First, we found that so-called false positives, in which the results of malaria determination were positive, rarely occurred. That is, the inventors have found that particles may be distributed in the region 203 corresponding to malaria-infected red blood cells even when the subject does not suffer from malaria.

Next, the inventors conducted the following observations and experiments regarding the phenomenon that particles are distributed in the region 203 even though the subject is not suffering from malaria.

The inventors microscopically observed a blood sample in which particles were distributed in the region 203 even though the subject did not suffer from malaria, ie, a blood sample that produced false positives.

FIG. 12(a) is a scattergram 200 created based on a blood sample that produces false positives. As shown in FIG. 12(a), the particle groups distributed in the region 203 are distributed obliquely from the origin. That is, the particle groups distributed in the region 203 are distributed along a straight line in which the fluorescence intensity and the forward scattered light intensity are in a proportional relationship. FIG. 12(b) is an image showing the result of microscopic observation of the blood sample shown in FIG. 12(a). As shown in FIG. 12(b), in this blood sample, mixed with red blood cells, white blood cells, and platelets, particles different from any of red blood cells, white blood cells, and platelets and having a size similar to that of platelets are present. Do you get it. The inventors thought that the particles were likely extracellular vesicles.

FIG. 13(a) is a scattergram 200 generated based on other blood samples that produce false positives. As shown in FIG. 13(a), in this blood specimen as well, the particle groups distributed in the region 203 are distributed obliquely from the origin. FIGS. 13(b) and 13(c) are images showing the results of microscopic observation of the blood sample shown in FIG. 13(a). As shown in FIGS. 13(b) and (c), this blood sample also contained particles considered to be extracellular vesicles among red blood cells, white blood cells, and platelets.

From the results shown in FIGS. 12(a) to 13(c), in the blood sample in which the particles are distributed in the region 203 even though the subject is not suffering from malaria, particles considered to be extracellular vesicles are present. found to exist.

The inventors also conducted an experiment to induce apoptosis in Jurkat cells and confirm how apoptotic bodies, which are a kind of extracellular vesicles, appear in scattergram 200. The conditions for this experiment are as follows.

(Jurkat cells)
・Medium: 10% FBS-added RPMI1640 medium ・Cell solution: Jurkat cells cultured to about 1×10 ⁶ /μL were diluted 10-fold with culture medium and cultured for 24 hours (apoptosis induction).
・ Inducing agent: Staurosporine 1 μM
・Stock solution: 250 μg/500 μL DMSO (1 mM Staurosporine)
・Prepare a 100 μM Staurosporine solution by diluting 1 mM Staurosporine 10-fold with the medium and add 1/100 volume to the culture medium.

FIG. 14(a) is a scattergram 200 generated based on Jurkat cells prior to induction of apoptosis. Since malaria-infected red blood cells do not exist in Jurkat cells, almost no particles were distributed in the region 203 of the scattergram 200 as shown in FIG. 14(a). On the other hand, FIG. 14(b) is a scattergram 200 created based on the Jurkat cells shown in FIG. 14(a) 4 hours after apoptosis was induced.

Here, the apoptotic reaction is known to progress over time after the induction of apoptosis. Particles distributed obliquely from the origin in FIG. 14(b) can be said to be apoptotic bodies, which are a kind of extracellular vesicles, because they appeared after apoptosis was induced. Also in the scattergrams 200 shown in FIGS. 12(a) and 13(a), a large number of particles are distributed in the same region as the apoptotic body distribution region shown in FIG. 14(b). was confirmed.

Next, the inventors examined the blood sample shown in the scattergram 200 in FIG. observed by The blood sample in FIG. 9(a) is a blood sample collected from a malaria-free mouse.

FIG. 15 is an image showing the results of microscopic observation of the mouse blood sample shown in FIG. 9(a). As shown in FIG. 15, erythrocytes containing Howell-Jolly bodies were present among normal mature erythrocytes in the mouse blood sample. Moreover, in the scattergram 200 created based on the mouse blood sample, as shown in FIG. distributed. From the above, the inventors have found that even in a human blood sample in which particles are distributed in the region 203 even though the subject is not suffering from malaria, when red blood cells containing Howell-Jolly bodies are present I thought there was

From the above observations and experimental results, the inventors found that erythrocytes containing apoptotic bodies and Howell-Jolly bodies are distributed along a straight line in which fluorescence intensity and forward scattered light intensity are proportional. . The inventors also found that when particles appear in the region 203 corresponding to malaria-infected red blood cells even though the subject does not suffer from malaria, the particles are apoptotic small cells, which are a type of extracellular vesicles. corpuscles, or erythrocytes containing Howell-Jolly bodies, a type of nucleic acid inclusion body.

Then, the inventors found that when at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles are distributed in the region 204, the variation in the frequency distribution with respect to the fluorescence intensity of the particle group G4 in the region 204 increases, It was found that when malaria-infected red blood cells were distributed in region 204, they became smaller.

When malaria-infected erythrocytes are contained in a blood sample, in the frequency distribution based on the particle group G4, a mountain shape with a significantly high frequency tends to appear at only one location. On the other hand, in the case of blood specimens that cause false positives, in the frequency distribution based on particle group G4, erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles are distributed over a wide range of fluorescence intensities, resulting in a large difference in frequency. is less likely to occur. Therefore, when the frequency distribution for the fluorescence intensity is created based on the particle group G4, there is a large difference in the dispersion of the frequency distribution between the case where the blood sample contains malaria-infected red blood cells and the case where the blood sample causes false positives. Therefore, according to the variation in the frequency distribution of the particle group G4 included in the range where single ring form red blood cells appear, it becomes easier to clearly distinguish between malaria-positive cases and false-positive cases.

Based on these findings, the inventors configured the determination process for malaria as shown in FIG. 6 so as to suppress false positives.

Note that extracellular vesicles are vesicles released from cells, and are a concept including microparticles derived from nucleated cells and microparticles derived from non-nucleated cells. Extracellular vesicles include, for example, exosomes, microvesicles (MV: Microvesicles), apoptotic bodies and the like. Considering particle size, it is possible that in addition to apoptotic bodies, some of the microvesicles are also distributed in region 203 . Erythrocytes containing nucleic acid inclusion bodies include Howell-Jolly bodies, basophilic plaques, and the like. In other words, nucleic acid inclusion bodies are a concept that includes Howell-Jolly bodies and basophilic plaques. Basophilic spots are also a type of nucleic acid inclusion bodies. In addition to red blood cells containing Howell-Jolly bodies, red blood cells containing basophilic spots may also be distributed in region 203 . Therefore, by determining the variation in the fluorescence intensity of the particle group G4 as described above, it may be possible to determine the presence or absence of various extracellular vesicles and the presence or absence of erythrocytes containing inclusion bodies of various nucleic acids.

<Embodiment 2>
In the second embodiment, in the determination process, not only the presence or absence of malaria but also the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles is determined. In Embodiment 2 and Embodiment 3 described later, "determining the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles" means erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles. Determining the presence or absence, that is, determining whether or not at least one of erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles is present. As shown in FIG. 16, the determination process of the second embodiment has substantially the same configuration as the determination process of the first embodiment shown in FIG. 6, although the determination details are different. Other configurations of the second embodiment are the same as those of the first embodiment.

As shown in FIG. 16, in step S121, the control unit 51 determines whether or not the number of particle groups G3 per unit volume is equal to or greater than a threshold th21. The particle group G3 is, as shown in FIG. 5(b), a particle group included in the range where malaria-infected red blood cells appear. The threshold th21 is set based on the number of particle groups G3 per unit volume so that the target blood sample can be determined to be “malaria-negative, red blood cells containing nucleic acid inclusion bodies, and no extracellular vesicles”. . The threshold th21 is set to the same value as the threshold th11 in step S111 of FIG. 6, for example.

When the number of particle groups G3 per unit volume is less than the threshold th21, in step S122, the control unit 51 determines that the target blood sample is "malaria negative, red blood cells containing nucleic acid inclusion bodies, and no extracellular vesicles. , and the determination result is stored in the storage unit 52 . Then, the control unit 51 terminates the determination process.

On the other hand, if the number of particle groups G3 per unit volume is equal to or greater than the threshold value th21, in step S123, the control unit 51 determines whether the target blood specimen is "malaria positive? Is there a cell?”, and the determination result is stored in the storage unit 52. The determination result of "Malaria positive? Red blood cells containing nucleic acid inclusion bodies or extracellular vesicles?" is likely to be included, but it is difficult to determine which one is included.

Subsequently, in step S124, the control unit 51 determines whether or not the number of particle groups G4 per unit volume is equal to or greater than a threshold th22. The particle group G4 is, as shown in FIG. 5(b), a particle group included in the range where single-ring form red blood cells appear. The threshold th22 is based on the number of particle groups G4 per unit volume, and for the target blood sample, malaria-infected red blood cells, red blood cells containing inclusion bodies of nucleic acids, or extracellular small cells are present in the region 204 corresponding to single-ring-form red blood cells. It is set so that it can be determined whether cells are distributed or not. The threshold th22 is set to the same value as the threshold th12 in step S114 of FIG. 6, for example.

If the number of particle groups G4 per unit volume is less than the threshold th22, the control unit 51 terminates the determination process. In this case, the determination result is "Malaria positive? Erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles present?" stored in step S123.

On the other hand, when the number of particle groups G4 per unit volume is equal to or greater than the threshold th22, in step S125, the control unit 51 calculates a value indicating the dispersion of the frequency distribution with respect to the fluorescence intensity of the particle groups G4. Specifically, in step S125, the control unit 51 calculates the coefficient of variation of the frequency distribution with respect to the fluorescence intensity of the particle group G4. Note that the value indicating the dispersion of the frequency distribution calculated in step S125 is not limited to the coefficient of variation, and may be the standard deviation or the half width of the frequency distribution map.

Subsequently, in step S126, the control unit 51 determines whether or not the coefficient of variation calculated in step S125 is less than the threshold th23. The threshold th23 is set based on the coefficient of variation so that the target blood sample can be determined to be “malaria-positive” or “erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles present”. The threshold th23 is set to the same value as the threshold th13 in step S116 of FIG. 6, for example.

When the coefficient of variation is less than the threshold value th23, the control unit 51 determines that the target blood sample is “malaria positive” and stores the determination result in the storage unit 52 in step S127. Then, the control unit 51 terminates the determination process. In this case, the determination result is changed from "Malaria positive? Erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles present?" stored in step S123 to "Malaria positive."

In step S127, the control unit 51 may determine that "malaria-positive, erythrocytes containing nucleic acid inclusion bodies, or extracellular vesicles present?" The determination result of "Malaria positive, red blood cells containing nucleic acid inclusion bodies, or extracellular vesicles?" This indicates a condition in which it is difficult to determine that extracellular vesicles are present.

On the other hand, if the coefficient of variation is equal to or greater than the threshold th23, in step S128, the control unit 51 determines that “red blood cells containing nucleic acid inclusion bodies or extracellular vesicles are present,” and stores the determination result in the storage unit 52. . Then, the control unit 51 terminates the determination process. In this case, the determination result is changed from "Malaria positive? Red blood cells containing nucleic acid inclusion bodies or extracellular vesicles present?" ”.

In step S128, the control unit 51 may determine that "malaria positive? Erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles present". The determination result of "Malaria positive? Red blood cells containing nucleic acid inclusion bodies, or extracellular vesicles present" can be determined as the presence of red blood cells or extracellular vesicles containing nucleic acid inclusion bodies in the target blood sample, This indicates a condition in which it is difficult to determine that malaria-infected red blood cells are present.

As shown in FIG. 17, the result of the determination process shown in FIG. 16 is also displayed on the screen 60 in the second embodiment. The screen 60 of the second embodiment has the same configuration as the screen 60 of the first embodiment shown in FIG.

Also in the second embodiment, the comment area 63 displays the judgment result obtained by the judgment processing of FIG. Specifically, when step S122 of FIG. 16 is executed, the comment area 63 displays "malaria negative, red blood cells containing nucleic acid inclusion bodies, and no extracellular vesicles". If NO is determined in step S124 of FIG. 16, the comment area 63 displays "Malaria positive? Erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles present?" In this case, "Malaria-positive? Extracellular vesicles? Erythrocytes containing nucleic acid inclusion bodies?" may be displayed. When step S127 in FIG. 16 is executed, "malaria positive" is displayed in the comment area 63. FIG. When step S128 of FIG. 16 is executed, as exemplified in FIG. 17, the comment area 63 displays "red blood cells containing nucleic acid inclusion bodies or extracellular vesicles present".

When "Malaria negative", "Malaria positive?", "Malaria positive", etc. are displayed in the comment area 63, the doctor or the like can make the same determination as in the first embodiment. In addition, in the comment area 63, "Are there erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles?", "Are there erythrocytes or extracellular vesicles containing nucleic acid inclusion bodies?" Red blood cells containing nucleic acid inclusion bodies?" is displayed, the physician or the like may, for example, identify a predetermined disease possibly associated with red blood cells containing nucleic acid inclusion bodies or extracellular vesicles, and determine the condition of the subject. It can be used as a judgment material for judging. For example, if a physician believes that red blood cells containing Howell-Jolly bodies are present, he or she may assume splenic dysfunction, etc.; etc. can be assumed. Also, in this case, the doctor or the like can perform further tests such as checking the blood sample under a microscope.

<Embodiment 3>
In Embodiment 3, the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles is determined in the determination process. As described above, in the scattergram 200, erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles may be distributed in the region 203 corresponding to malaria-infected erythrocytes. In Embodiment 3, as shown in FIG. 18, a scattergram 400 is provided with regions 403 corresponding to erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles. Also, the determination processing of the third embodiment is configured as shown in FIG. 19 . Other configurations of the third embodiment are the same as those of the first embodiment.

As shown in FIG. 18, scattergram 400 has axes similar to scattergram 200 . That is, in the scattergram 400, the vertical axis indicates forward scattered light intensity, and the horizontal axis indicates fluorescence intensity.

In scattergram 400, white blood cells are generally distributed in region 401 similar to region 201 in the first embodiment. Malaria-free red blood cells are generally distributed in a region 402 similar to region 202 of the first embodiment. Erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles are smaller than leukocytes and are stained with fluorescent dyes because they contain nucleic acid components inside. Thus, red blood cells containing nucleic acid inclusion bodies and extracellular vesicles are generally distributed in region 403 . The forward scattered light intensity of region 403 is smaller than region 401 corresponding to white blood cells. The fluorescence intensity of region 403 is greater than region 402 corresponding to non-malaria-infected red blood cells and less than region 401 corresponding to white blood cells. In addition, as shown in FIGS. 8(a), (b), 9(a), (b), 12(a), 13(a), and 14(b), nucleic acid inclusion bodies Red blood cells containing and extracellular vesicles are distributed overlying region 204 of embodiment 1 corresponding to single ring form red blood cells. Therefore, a region 403 corresponding to erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles is set so as to overlap region 204 described above.

In addition, since the region 403 may be set to include red blood cells containing nucleic acid inclusion bodies distributed in the scattergram 200 and extracellular vesicles, the region 403 is set slightly smaller than the region 203 of the first embodiment. ing.

In the third embodiment, in the process of step S102 in FIG. 5A, based on the fluorescence intensity and scattered light intensity of the measurement data, instead of malaria-infected erythrocytes, single ring form erythrocytes, and multiring form erythrocytes, nucleic acid Erythrocytes containing inclusion bodies and extracellular vesicles are counted. Specifically, the control unit 51 identifies the particle group G6 that is included in the range in which the red blood cells containing the nucleic acid inclusion bodies and the extracellular vesicles appear. In the scattergram 400 , the range in which erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles appear corresponds to region 403 . Then, the control unit 51 obtains the number of erythrocytes and extracellular vesicles containing nucleic acid inclusion bodies by counting the number of the specified particle group G6. Acquisition of the number of white blood cells is performed in the same manner as in the first embodiment.

As shown in FIG. 19, in step S131, the control unit 51 determines whether or not the number of particle groups G6 per unit volume is equal to or greater than a threshold th31. The number of particle groups G6 per unit volume is obtained, for example, by dividing the number of acquired particle groups G6 by the volume of the first measurement sample flowed through the flow cell 101 during the acquisition of the first information. The threshold th31 is set based on the number of particle groups G6 per unit volume so that it can be determined that the target blood specimen has "red blood cells containing nucleic acid inclusion bodies and no extracellular vesicles". The threshold th31 is set to 200, for example.

When the number of particle groups G6 per unit volume is less than the threshold value th31, in step S132, the control unit 51 determines that the target blood specimen has "no red blood cells containing inclusion bodies of nucleic acids and no extracellular vesicles." and stores the determination result in the storage unit 52 . Then, the control unit 51 terminates the determination process.

On the other hand, when the number of particle groups G6 per unit volume is equal to or greater than the threshold th31, in step S133, the control unit 51 calculates a value indicating the dispersion of the frequency distribution with respect to the fluorescence intensity of the particle group G6. Specifically, in step S133, the control unit 51 calculates the coefficient of variation of the frequency distribution with respect to the fluorescence intensity of the particle group G6. Note that the value indicating the dispersion of the frequency distribution calculated in step S133 is not limited to the coefficient of variation, and may be the standard deviation or the half width of the frequency distribution map.

In calculating the coefficient of variation in step S133, the control unit 51 does not create a frequency distribution map, but calculates the coefficient of variation by data processing following the same procedure as when creating a frequency distribution map. However, without being limited to this, the control unit 51 may create a frequency distribution chart to calculate the coefficient of variation. Note that the control unit 51 does not create a frequency distribution map for the purpose of calculating the coefficient of variation, but creates a frequency distribution map when displaying a screen described later on the display unit 53a, and displays the created frequency distribution map on the display unit. 53a.

In step S133, instead of the coefficient of variation based on the particle group G6, the control unit 51 determines, for example, the fluorescence intensity You may calculate the variation coefficient of the frequency distribution with respect to. That is, in step S133, the control unit 51 may calculate the coefficient of variation based on the particle group whose fluorescence intensity is within a predetermined range and included in the measurement data.

Subsequently, in step S134, the control unit 51 determines whether or not the coefficient of variation calculated in step S133 is less than the threshold th32. The threshold th32 is set based on the coefficient of variation so that it can be determined that "red blood cells containing nucleic acid inclusion bodies or extracellular vesicles are present" for the target blood sample. In addition, in the horizontal direction, the width of the region 403 in the third embodiment is set larger than the width of the region 204 corresponding to the single ring form red blood cells shown in FIG. 5(b). Therefore, the threshold th32 is set to a value larger than the threshold th13 in step S116 of FIG. The threshold th32 is set to 20%, for example.

Here, if malaria-infected red blood cells are present in the blood sample, the variation in the frequency distribution based on the particle group G6 will be small, and if the blood sample does not contain malaria-infected red blood cells, the variation in the frequency distribution based on the particle group G6 will be large. Therefore, by determining the magnitude of the coefficient of variation in step S134, it is possible to determine the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles.

When the coefficient of variation is equal to or greater than the threshold th32, in step S135, the control unit 51 determines that “red blood cells containing nucleic acid inclusion bodies or extracellular vesicles are present” and stores the determination result in the storage unit 52. Then, the control unit 51 terminates the determination process. On the other hand, if the coefficient of variation is less than the threshold value th32, in step S136, the control unit 51 determines that the target blood sample has "erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles? Scatter abnormality", A determination result is stored in the storage unit 52 .

The determination result of "Are there red blood cells containing nucleic acid inclusion bodies or extracellular vesicles?" It indicates a state in which it is difficult to determine that "red blood cells containing inclusion bodies of nucleic acids or extracellular vesicles are present". The “scatter abnormality” included in the determination result in this case is information indicating the reliability of the determination result regarding the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles. Specifically, "scatter abnormality" is information indicating that the reliability of the determination result regarding the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles is not high. Then, the control unit 51 terminates the determination process. Note that when the coefficient of variation is less than the threshold th32, there is a high possibility that malaria-infected red blood cells are present, so it may be determined as "malaria positive".

In addition, in the determination process shown in FIG. 19, steps S133, S134, and S136 may be omitted when only blood specimens that do not contain malaria-infected red blood cells are targeted. In this case, if YES is determined in step S131, in step S135, the control unit 51 determines that the target blood sample "contains erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles".

Next, with reference to FIG. 20(a) to FIG. 21(d), determinations performed on six types of specimens will be specifically described.

Figures 20(a) and (b) are scattergrams 400 based on blood samples taken from a subject suffering from malaria. Figures 20(c) and (d) are scattergrams 400 based on blood samples taken from subjects who do not have malaria. Figures 21 (a) and (b) are scattergrams 400 based on blood samples taken from mice that do not have malaria. In both cases, particles located at the left edge of region 402 are cut as being noise components.

In the six types of specimens shown in FIGS. 20(a) to (d), FIGS. 21(a) and (b), in each case, the region 403 corresponding to erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles A certain number of particles appear in . The numbers of particle groups G6 in FIGS. 20(a) to (d), FIGS. 21(a) and (b) are 20134, 8273, 216, 5193, 1427 and 573, respectively. Therefore, according to the determination process shown in FIG. 19, YES is determined in step S131, and the variation coefficient of the frequency distribution with respect to the fluorescence intensity of the particle group G6 is calculated in step S133.

FIGS. 20(e)-(h), FIGS. 21(c), and (d) are created based on the scattergrams 400 of FIGS. 20(a)-(d), FIGS. 21(a), and (b), respectively. 500 is a modified frequency distribution diagram 500. FIG. In the frequency distribution diagram 500, the horizontal axis indicates fluorescence intensity, and the vertical axis indicates frequency. A frequency distribution diagram 500 shows a frequency distribution based only on the particle group G6 included in the range where erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles appear. The frequency distribution diagram 500 is normalized based on the maximum frequency value.

Referring to the frequency distribution diagrams 500 of FIGS. 20(e) and (f), the shape of the frequency distribution is sharp in both cases. The coefficients of variation in FIGS. 20(e) and (f) are 16.5% and 8.2%, respectively. Therefore, in both cases of FIGS. 20(e) and 20(f), step S134 of FIG. 19 is determined to be YES, and for these specimens, "RBCs containing nucleic acid inclusion bodies or extracellular vesicles present? Scatter abnormality" ” is determined. Here, the specimens shown in FIGS. 20(e) and (f) are specimens infected with malaria, as described above. Also, irrespective of the presence or absence of malaria-infected red blood cells, there is a possibility that red blood cells containing inclusion bodies of nucleic acids or extracellular vesicles may be present in the blood sample, or neither may be present. Therefore, according to the determination process shown in FIG. 19, for these two specimens, it is not a determination result that clearly indicates the presence or absence of erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles, but "red blood cells containing nucleic acid inclusion bodies". , or presence of extracellular vesicles?scatter abnormality" can be obtained.

On the other hand, referring to the frequency distribution diagrams 500 of FIGS. 20(g), (h), FIGS. 21(c), and (d), the shape of the frequency distribution is not completely sharp in any case. The coefficients of variation in FIGS. 20(g), (h), FIGS. 21(c), and (d) are 26.5%, 22.3%, 30.8%, and 32.0%, respectively. Therefore, in all cases of FIGS. 20(g), (h), FIGS. 21(c), and (d), the determination in step S134 of FIG. , or presence of extracellular vesicles”. Here, the specimens shown in FIGS. 20(g), (h), FIGS. 21(c), and (d) are all specimens not infected with malaria. Therefore, according to the determination process shown in FIG. 19, these two specimens are not determined to be "malaria positive", and the appropriate determination result of "red blood cells containing inclusion bodies of nucleic acids, or extracellular vesicles present" can be obtained.

As described above, according to the determination process shown in FIG. 19, if the blood sample contains erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles and does not contain malaria-infected erythrocytes, the "nucleic acid Proper determination of "red blood cells containing inclusion bodies, or presence of extracellular vesicles" can be performed. In addition, when malaria-infected red blood cells are present in a blood sample, instead of judging “red blood cells containing nucleic acid inclusion bodies or extracellular vesicles present”, “red blood cells containing nucleic acid inclusion bodies or extracellular vesicles” Appropriate determination of "vesicle presence? scatter abnormality" can be performed.

As shown in FIG. 22, the result of the determination process shown in FIG. 19 is also displayed on the screen 60 in the third embodiment. The list area 62 of the third embodiment displays the counting results of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles, that is, the counting results of the particle group G6 in FIG.

Also in the third embodiment, the comment area 63 displays the judgment result obtained by the judgment processing of FIG. Specifically, when step S132 of FIG. 19 is executed, the comment area 63 displays “erythrocytes containing nucleic acid inclusion bodies and no extracellular vesicles”. When step S136 of FIG. 19 is executed, the comment area 63 displays "Red blood cells containing nucleic acid inclusion bodies or extracellular vesicles present? Scatter abnormality". In this case, "extracellular vesicle? erythrocyte containing inclusion body of nucleic acid? scatter abnormality" may be displayed. When step S135 of FIG. 19 is executed, as exemplified in FIG. 22, the comment area 63 displays "red blood cells containing nucleic acid inclusion bodies or extracellular vesicles present".

In the comment area 63, "Are there erythrocytes or extracellular vesicles containing nucleic acid inclusion bodies?", "Are there erythrocytes or extracellular vesicles containing nucleic acid inclusion bodies?" Red blood cells containing inclusion bodies?" is displayed, the physician or the like can know that the blood sample may contain red blood cells containing nucleic acid inclusion bodies or extracellular vesicles. Then, as in the second embodiment, a physician or the like may, for example, determine a predetermined disease possibly associated with erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles in order to determine the condition of the subject. It can be made into materials. Further tests may also be performed by the physician or the like, such as microscopic examination of the blood sample.

Further, when "abnormal scatter" is displayed in the comment area 63, the doctor or the like indicates that the reliability of the determination result regarding the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles is not high. can know. In this case, a doctor or the like may know that erythrocytes containing nucleic acid inclusion bodies and particles other than extracellular vesicles, such as malaria-infected erythrocytes, may be distributed in region 403 of scattergram 400. can. In addition, since the scattergram 400 and the frequency distribution diagram 500 are displayed on the screen 60, the doctor or the like can grasp the condition of the blood sample quickly and in detail.

In Embodiments 2 and 3, the presence or absence of extracellular vesicles may be determined instead of determining whether at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles is present, The presence or absence of red blood cells containing nucleic acid inclusion bodies may be determined. In this case, in Embodiments 2 and 3, of the red blood cells and extracellular vesicles containing nucleic acid inclusion bodies, only the extracellular vesicles may be displayed in the comment area 63. The display may be made only for red blood cells containing. Further, in the third embodiment, the list area 62 may display the counting result of only extracellular vesicles, or the counting result of only red blood cells containing nucleic acid inclusion bodies.

In Embodiments 2 and 3, whether or not at least one of these two types of particles is included is determined without distinguishing between extracellular vesicles and erythrocytes containing nucleic acid inclusion bodies. The presence or absence of particles may be determined by distinguishing them. For example, when it is determined as NO in step S134 of FIG. 19, the presence or absence of extracellular vesicles and inclusion bodies of nucleic acids further according to the value of the coefficient of variation or according to the distribution angle of the particle group G6 of FIG. The presence or absence of red blood cells containing may be determined separately.

10 blood analyzer 30 sample preparation unit 51 control unit 53 output unit 53a display unit 101 flow cell 102 light source 103, 105 light receiving unit 400 scattergram 403 region 500 frequency distribution chart G6 particle group

Claims (23)

a sample preparation unit that mixes a blood sample and a fluorescent dye that stains nucleic acids to prepare a measurement sample;
a light receiving unit that receives fluorescence generated by irradiating the measurement sample prepared by the sample preparation unit with light;
A controller that determines the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles by distinguishing from the presence or absence of malaria-infected erythrocytes based on the fluorescence intensity obtained by processing the signal from the light-receiving unit. and a hematology analyzer. The control unit specifies a particle group in which the fluorescence intensity is lower than that of white blood cells, and based on the specified particle group, the presence or absence of at least one of red blood cells containing nucleic acid inclusion bodies and extracellular vesicles. 2. The blood analyzer according to claim 1, which determines 3. The blood analyzer according to claim 1, wherein said sample preparation unit further mixes a diluent that contracts red blood cells to prepare said measurement sample. The control unit identifies a particle group in which the fluorescence intensity is greater than that of red blood cells contracted by the diluent and less than that of white blood cells , and based on the identified particle group, a nucleic acid inclusion body. The blood analyzer according to claim 3, which determines the presence or absence of at least one of red blood cells containing and extracellular vesicles. The light receiving unit further receives scattered light generated by irradiating the measurement sample with light,
The control unit determines the presence or absence of at least one of red blood cells containing nucleic acid inclusion bodies and extracellular vesicles based on the fluorescence intensity and the scattered light intensity obtained by processing the signal from the light receiving unit. 5. The blood analyzer according to any one of claims 1 to 4, wherein The control unit identifies a particle group in which the fluorescence intensity and the scattered light intensity are lower than those of white blood cells, and based on the identified particle group, red blood cells containing inclusion bodies of nucleic acids and extracellular vesicles. 6. The blood analyzer according to claim 5, which determines the presence or absence of at least one of 7. The blood analyzer according to claim 2, wherein the controller determines the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles based on the number of the particle groups. . 2, wherein the control unit determines the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles based on a value indicating variation in the frequency distribution of the particle group with respect to the fluorescence intensity, 4 or 6, the blood analyzer. 9. The blood analyzer according to claim 8, wherein the value indicating the variation of the particle group is a coefficient of variation, a standard deviation, or a half width of a frequency distribution diagram. 10. The control unit determines the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles based on the fact that the value indicating the variation is equal to or greater than a first threshold value, A hematology analyzer as described. Based on the fact that the value indicating the variation is greater than or equal to a first threshold and the number of the particle groups is greater than or equal to a second threshold, the control unit controls the erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles 11. The blood analyzer according to any one of claims 8 to 10, which determines the presence or absence of at least one of further comprising an output unit for outputting information,
12. The blood analyzer according to any one of claims 8 to 11, wherein said control unit causes said output unit to output determination results regarding the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles. . The control unit determines the presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles when a value indicating variation in the frequency distribution of the specified particle group with respect to the fluorescence intensity is less than a predetermined threshold. 13. The blood analyzer according to claim 12, wherein the output unit outputs information indicating the reliability of the determination result regarding. The output unit comprises a display unit for displaying information,
14. The blood analysis according to claim 13, wherein the control unit causes the display unit to display information indicating the degree of reliability together with determination results regarding the presence or absence of at least one of erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles. Device. 15. The blood analysis apparatus according to claim 14, wherein said control section further causes said display section to display a frequency distribution diagram for said fluorescence intensity of said particle group. 16. The blood analyzer according to claim 14, wherein said control section further causes said display section to display a scattergram based on said fluorescence intensity. a flow cell through which the measurement sample prepared by the sample preparation unit flows;
a light source that irradiates the light onto the measurement sample flowing through the flow cell,
17. The blood analysis apparatus according to any one of claims 1 to 16, wherein said light receiving unit receives said fluorescence generated from particles contained in said measurement sample due to irradiation of said light. 18. The blood analyzer according to claim 17, wherein said light source emits light in a blue-violet wavelength band. 19. The blood analyzer according to any one of claims 1 to 18, wherein said extracellular vesicles contain apoptotic bodies. 20. The blood analyzer according to any one of claims 1 to 19, wherein the erythrocytes containing nucleic acid inclusion bodies contain Howell-Jolly bodies or basophilic spots. The presence or absence of at least one of erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles is determined based on the fluorescence generated by irradiating a measurement sample prepared by mixing a blood sample and a fluorescent dye that stains nucleic acids with light. A blood analysis method for determining the presence or absence of malaria-infected red blood cells . a sample preparation unit that mixes a blood sample and a fluorescent dye that stains nucleic acids to prepare a measurement sample;
a light receiving unit that receives fluorescence generated by irradiating the measurement sample prepared by the sample preparation unit with light;
A blood analyzer that distinguishes between a specimen containing malaria-infected red blood cells and a specimen containing either red blood cells containing nucleic acid inclusion bodies or extracellular vesicles, based on the fluorescence intensity obtained by processing the signal from the light-receiving unit. . Based on the fluorescence generated by irradiating light on a measurement sample prepared by mixing a blood sample and a fluorescent dye that stains nucleic acids, a sample containing malaria-infected red blood cells and red blood cells or extracellular small cells containing nucleic acid inclusion bodies are detected. A blood analysis method for distinguishing between specimens containing cells.

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