JP6896516B2 - 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 Plasmodium malaria by a flow cytometry method is known. As shown in FIG. 23, in Patent Document 1, in a scattergram having two axes of scattered light intensity (FSCL) and fluorescence intensity (SFLL), the fluorescence intensity is in a range larger than that of uninfected erythrocytes and smaller than that of leukocytes. It has been described that erythrocytes infected with Plasmodium appear. In this scattergram, from the region with low fluorescence intensity, erythrocytes infected with ring foam (single) Plasmodium, erythrocytes infected with ring foam (multi) Plasmodium, erythrocytes infected with tropozoite Plasmodium, and schizont. It is described that erythrocytes containing Plasmodium at a predetermined growth stage, such as erythrocytes infected with Plasmodium, appear in different regions in order. Based on the malaria-infected erythrocytes detected in this way, the infection rate of erythrocytes infected with Plasmodium malaria is determined.

Japanese Unexamined Patent Publication No. 2006-304774

When the inventors determine the presence or absence of malaria protozoan infection based on the particle distribution of such a scattergram, the determination result of malaria is positive even though the subject does not have malaria. We have found that so-called false positives rarely occur.

In view of these problems, it is an object of the present invention to provide a blood analyzer and a blood analysis method capable of suppressing the occurrence of false positives and determining the presence or absence of Plasmodium infection with higher accuracy.

The first aspect of the present invention relates to a blood analyzer. The blood analyzer (10) according to this aspect is a measurement prepared by a sample preparation unit (30) that prepares a measurement sample by mixing a blood sample and a fluorescent dye that stains nucleic acid, and a sample preparation unit (30). Based on the light receiving part (103, 105) that receives the fluorescence and scattered light generated by irradiating the sample with light, and the fluorescence intensity and scattered light intensity obtained by processing the signal from the light receiving part (103, 105). A control unit (51) for determining the presence or absence of malaria protozoa infection based on a value indicating variation in the distribution of the first particle group (G4) included in the identified single ring foam red blood cell appearance range (204). To be equipped with.

In the blood analyzer according to this embodiment, the single ring foam erythrocyte is an erythrocyte containing one ring foam Plasmodium. The range in which single-ring foam erythrocytes appear is, for example, the region in which single-ring foam erythrocytes are generally distributed when a scattergram is created based on fluorescence intensity and scattered light intensity. The first particle group is a collection of particles classified as single ring foam erythrocytes. The value indicating the variation in the distribution of the first particle group indicates how much each particle of the first particle group is distributed in a range in which the single ring foam erythrocytes appear. The value indicating the variation in the distribution of the first particle group is, for example, a value indicating the variation in the frequency distribution with respect to the fluorescence intensity of the first particle group. The value indicating the variation of the frequency distribution is a value related to the variation of the appearance frequency of particles in the frequency distribution, such as the coefficient of variation, the standard deviation, and the half width of the frequency distribution map. "Determining the presence or absence of Plasmodium infection" is not limited to strictly determining whether or not there are erythrocytes infected with Plasmodium, and a certain number of erythrocytes infected with Plasmodium are present in the blood sample. It is a concept that also includes determining whether or not to do so.

Here, the inventors have found that erythrocytes containing extracellular vesicles and inclusion bodies of nucleic acids appear in scattergrams of blood samples in which false positives occur. Then, the inventors have found that erythrocytes containing extracellular vesicles and nucleic acid inclusion bodies appearing in the scattergram are the cause of false positives in the determination of malaria. Furthermore, the inventors continued their diligent investigation, and found that when a frequency distribution of fluorescence intensity was created for the first particle group, which is a group of particles classified as single ring form erythrocytes, a false positive result was obtained in the case of a blood sample. We found that the frequency distribution variability was greater than that of blood samples infected with malaria.

In the case of false positives, the variation in the frequency distribution with respect to the fluorescence intensity based on the first particle group becomes large for the following reasons. In the case of a blood sample infected with malaria, one mountain shape having a remarkably high frequency is likely to appear in the frequency distribution based on the first particle group. On the other hand, in the case of blood samples that produce false positives, in the frequency distribution based on the first particle group, erythrocytes including extracellular vesicles and inclusion bodies of nucleic acids are distributed over a wide range of fluorescence intensities, and there is a large difference in frequency. Is unlikely to occur. Therefore, when the frequency distribution with respect to the fluorescence intensity is created based on the first particle group, there is a large difference in the variation of the frequency distribution between the case of the blood sample infected with malaria and the case of the blood sample producing false positives.

Focusing on this point, the blood analyzer according to this embodiment is configured to determine the presence or absence of infection with Plasmodium malaria based on a value indicating variation in the distribution of the first particle group. Therefore, according to the blood analyzer according to this aspect, when the distribution of the first particle group varies widely, the occurrence of false positives can be suppressed by avoiding determining that there is infection with Plasmodium malaria, for example. Therefore, the presence or absence of Plasmodium infection can be determined with higher accuracy.

In the blood analyzer (10) according to this embodiment, the control unit (51) separates the first particle group (G4) from the second particle group (G5) included in the range (205) in which multilingual erythrocytes appear. It is preferable to specify. Multi-ring foam erythrocytes are erythrocytes containing multiple ring-form Plasmodium. When the first particle group is not separated from the second particle group, not only red blood cells containing one ring-form malaria but also multiple ring-form malaria such as two or three are contained in the particle group to be determined. It contains red blood cells with high fluorescence intensity, and the frequency distribution of particles tends to widen despite being infected with malaria. Therefore, when making a determination based on the frequency distribution, it is preferable to specify the first particle group separately from the second particle group, which is a collection of particles classified into multilingual erythrocytes.

In the blood analyzer (10) according to this embodiment, the value indicating the variation is preferably a value indicating the variation of the frequency distribution with respect to the fluorescence intensity of the first particle group (G4). While the amount of nucleic acid contained in single ring foam erythrocytes is approximately a predetermined amount, the amount of nucleic acid contained in erythrocytes including extracellular vesicles and inclusion bodies of nucleic acids varies. Therefore, according to the value indicating the variation in the frequency distribution with respect to the fluorescence intensity of the first particle group, the presence or absence of infection with Plasmodium malaria can be determined with higher accuracy.

In the blood analyzer (10) according to this aspect, the value indicating the variation can be the coefficient of variation, the standard deviation, or the half width of the frequency distribution map (300).

In the blood analyzer (10) according to this embodiment, the sample preparation unit (30) may be configured to further mix a diluent that contracts red blood cells to prepare a measurement sample. In this way, the erythrocytes are contracted by the preparation of the measurement sample, and the erythrocytes infected with Plasmodium are contracted while retaining the Plasmodium inside. As a result, the size of the erythrocytes infected with Plasmodium becomes a size according to the morphology of the Plasmodium held inside. Therefore, the first particle group and the second particle group can be accurately identified based on the scattered light.

In the blood analyzer (10) according to this embodiment, the control unit (51) has a value indicating variation and the number of the third particle group (G3) included in the range (203) in which erythrocytes infected with Plasmodium infection appear. Can be configured to determine the presence or absence of Plasmodium infection.

In this case, the control unit (51) determines that the blood sample is malaria based on the fact that the number of the third particle group (G3) is equal to or greater than the first threshold value and the value indicating variation is less than the second threshold value. It may be configured to determine that it is infected with a protozoan.

Further, in the control unit (51), the number of the third particle group (G3) is equal to or more than the first threshold value, the value indicating variation is less than the second threshold value, and the number of the first particle group (G4) is large. A blood sample may be configured to determine that it is infected with Plasmodium based on a third threshold or greater.

The blood analyzer (10) according to this embodiment further includes an output unit (53) for outputting information, and the control unit (51) is configured to output a determination result regarding infection with Plasmodium malaria to the output unit (53). Can be done. In this way, 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. In addition, since the doctor or the like can know that the subject may have malaria, further tests such as checking the blood sample with a microscope can be performed.

In this case, the control unit (51) is configured to output information indicating the reliability of the determination result regarding the infection of Plasmodium malaria to the output unit (53) when the value indicating the variation is equal to or higher than a predetermined threshold value. obtain. In this way, doctors and the like can know the reliability of the determination result regarding the infection of Plasmodium malaria. In addition, since doctors and the like can know that particles other than malaria-infected erythrocytes, for example, erythrocytes containing extracellular vesicles and inclusion bodies of nucleic acids may be distributed, the blood sample is confirmed with a microscope. Further inspections such as can be performed.

In this case, the output unit (53) includes a display unit (53a) for displaying information, and the control unit (51) displays information indicating reliability together with a determination result regarding infection with Plasmodium. It may be configured to be displayed in 53a). In this way, the doctor or the like can visually grasp the determination result regarding the infection of the malaria protozoan and the reliability of the determination result regarding the infection of the malaria protozoan.

In this case, the control unit (51) may be configured to further display the frequency distribution diagram (300) with respect to the fluorescence intensity of the first particle group (G4) on the display unit (53a). In this way, the doctor or the like can quickly and in detail grasp the state of the blood sample.

Further, the control unit (51) may be configured to further display the scattergram (200) based on the fluorescence intensity and the scattered light intensity on the display unit (53a). In this case as well, the doctor or the like can quickly and in detail grasp the state of the blood sample.

The blood analyzer (10) according to this embodiment includes a flow cell (101) for flowing a measurement sample prepared by the sample preparation unit (30) and a light source (102) for irradiating the measurement sample flowing through the flow cell (101) with light. , And the light receiving units (103, 105) may be configured to receive the fluorescence and scattered light generated from the 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 bluish-purple wavelength band. By doing so, the light irradiating the flow cell can be narrowed down to a small size, so that small particles can be detected.

A second aspect of the present invention relates to a blood cell analysis method. In the blood cell analysis method according to this embodiment, single ring foam erythrocytes identified based on fluorescence and scattered light generated by irradiating a measurement sample prepared by mixing a blood sample and a fluorescent dye that stains nucleic acid with light are used. The presence or absence of Plasmodium infection is determined based on the value indicating the variation in the distribution of the first particle group (G4) included in the appearance range (204) (S103, S111 to S118, S121 to S128).

According to the blood analysis method according to this aspect, the same effect as that of the first aspect can be achieved.

According to the present invention, it is possible to suppress the occurrence of false positives and determine the presence or absence of malaria protozoan infection with higher accuracy.

FIG. 1 is a block diagram showing a configuration of a blood analyzer according to the first embodiment. FIG. 2 is a schematic view showing the configuration of the optical detection unit according to the first embodiment. FIG. 3 is a flowchart showing the processing of the measurement unit according to the first embodiment. FIG. 4 is a flowchart showing the processing of the information processing unit according to the first embodiment. FIG. 5A is a flowchart showing the analysis process according to the first embodiment. FIG. 5B is a schematic diagram showing a scattergram based on the first measurement according to the first embodiment. FIG. 6 is a flowchart showing a determination process for malaria according to the first embodiment. 7 (a) to 7 (d) are scattergrams based on four specific types of samples according to the first embodiment. 7 (e) to 7 (h) are frequency distribution diagrams based on four specific types of samples according to the first embodiment. 8 (a) to 8 (d) are scattergrams based on four specific types of samples according to the first embodiment. 8 (e) to 8 (h) are frequency distribution diagrams based on four specific types of samples according to the first embodiment. 9 (a) and 9 (b) are scattergrams based on two specific types of samples according to the first embodiment. 9 (c) and 9 (d) are frequency distribution diagrams based on two specific types of samples according to the first embodiment. FIG. 10 is a schematic view showing the configuration of a screen displayed on the display unit according to the first embodiment. 11 (a) and 11 (b) are diagrams showing the verification results of the determination process performed by the inventors according to the first embodiment. FIG. 12 (a) is a scattergram based on a blood sample producing a false positive according to the first embodiment. FIG. 12B is an image obtained when a blood sample producing a false positive according to the first embodiment is observed with a microscope. FIG. 13 (a) is a scattergram based on a blood sample producing a false positive according to the first embodiment. 13 (b) and 13 (c) are images obtained when a blood sample producing a false positive according to the first embodiment is observed with a microscope. FIG. 14 (a) is a scattergram prepared based on Jurkat cells before introducing apoptosis according to the first embodiment. FIG. 14 (b) is a scattergram prepared based on Jurkat cells after inducing apoptosis according to the first embodiment. FIG. 15 is an image obtained when a blood sample of a mouse producing a false positive according to the first embodiment is observed with a microscope. FIG. 16 is a flowchart showing a determination process for malaria, erythrocytes containing nucleic acid inclusion bodies, and extracellular vesicles according to the second embodiment. FIG. 17 is a schematic view showing the configuration of a screen displayed on the display unit according to the second embodiment. FIG. 18 is a schematic view showing a scattergram based on the first measurement according to the third embodiment. FIG. 19 is a flowchart showing a determination process for erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles according to the third embodiment. 20 (a) to 20 (d) are scattergrams based on four specific types of samples according to the third embodiment. 20 (e) to 20 (h) are frequency distribution diagrams based on four specific types of samples according to the third embodiment. 21 (a) and 21 (b) are scattergrams based on two specific types of samples according to the third embodiment. 21 (c) and 21 (d) are frequency distribution diagrams based on two specific types of samples according to the third embodiment. FIG. 22 is a schematic view showing the configuration of the screen displayed on the display unit according to the third embodiment. FIG. 23 is a schematic diagram for explaining the structure of the scattergram according to the related technology.

<Embodiment 1>
The blood analyzer 10 of the first embodiment measures a measurement sample prepared from a blood sample and a reagent to identify a population containing erythrocytes infected with Plasmodium, and whether or not the blood sample is infected with malaria. To judge.

When merozoite, one of the forms of Plasmodium, invades erythrocytes, the red blood cell life cycle of Plasmodium begins. In the red-inner life cycle, the morphology of Plasmodium changes in the order of ring form, trophozoite, and schizont. Schizont divides into multiple merozoites, destroying red blood cells. This releases a large number of merozoites into the blood. Merozoite invades the next red blood cell, and the red blood cell life cycle begins again. By repeating this cycle, Plasmodium protozoan grows. Some of the merozoite released into the blood differentiates into hermaphroditic gametosites. When an infected person is sucked by a mosquito, gametosites invade the mosquito's body and the mosquito carries the Plasmodium.

Hereinafter, erythrocytes that are not infected with Plasmodium malaria will be referred to as "malaria non-infected erythrocytes". Malaria non-infected erythrocytes include mature erythrocytes as well as reticulocytes. Erythrocytes infected with Plasmodium malaria are referred to as "malaria-infected erythrocytes". Malaria-infected erythrocytes include erythrocytes infected with Ringfoam Plasmodium, erythrocytes infected with Trofozoite Plasmodium, and erythrocytes infected with Sizonto Plasmodium. Red blood cells infected with one ring-form Plasmodium, that is, red blood cells containing one ring-form Plasmodium are referred to as "single ring-form erythrocytes". Erythrocytes infected with a plurality of ring-form Plasmodium, that is, erythrocytes containing a plurality of ring-form Plasmodium are referred to as "multi-ring-form erythrocytes".

As shown in FIG. 1, the blood analyzer 10 includes a measuring unit 11 and an information processing unit 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 electric resistance type detection unit 42, and a signal processing circuit 43.

The measurement control unit 21 is composed of, 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 unit 21 communicates with the information processing unit 12. The storage unit 22 is composed of, for example, a ROM, a RAM, a hard disk, or the like. The measurement control unit 21 executes the process based on the program stored in the storage unit 22. The suction unit 23 has a suction tube (not shown), and sucks the blood sample contained in the sample container (not shown) by the suction tube. The blood sample is whole blood of peripheral blood collected from the subject.

The sample container is transported by the rack transport unit while being held in a sample rack (not shown), and is positioned at the take-out 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 sample container is positioned at the suction position, the suction unit 23 sucks the blood sample contained in the sample container by the suction tube. The sample container is then returned to its original position in the sample rack. When the blood analyzer 10 does not have a configuration for transporting the sample rack and a configuration for transporting the sample container, the sample container is positioned at the suction position by the operator.

Reagent containers 31, 32, and 33 are connected to the sample preparation unit 30. The reagent container 31 contains a first diluent that causes red blood cells to contract. 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 unit 30 has a reaction tank 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 vessel 34, the blood sample, the first diluted solution, and the staining reagent are mixed to prepare the first measurement sample. The first measurement sample is used for measuring leukocytes and malaria-infected erythrocytes. Further, in the reaction tank 34, the blood sample and the second diluted solution are mixed to prepare a second measurement sample. The second measurement sample is used for measuring red blood cells and platelets.

Here, the first diluted solution, the second diluted solution, and the dyeing reagent will be described.

The first diluent contains two types of surfactants having 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 is more hemolytic 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. 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 diluted solution as described above, the erythrocytes are contracted by the preparation of the first measurement sample, and the malaria-infected erythrocytes are contracted while retaining the Plasmodium inside. Further, according to the first diluted solution, the cell membrane of erythrocytes is lysed to the extent that the fluorescent dye can permeate into the erythrocytes and the shape of the erythrocytes is maintained. In the case of malaria-infected erythrocytes, specifically, the cell membrane of the erythrocytes is partially lysed so that the fluorescent dye can permeate while the Plasmodium is retained inside the erythrocytes.

The second diluent is different from the first diluent for contracting erythrocytes, and is a diluent for measuring erythrocytes by the sheath flow DC detection method. The second diluent can also be used as a sheath liquid for flowing the first measurement sample through the flow cell 101 of the optical detection unit 41 and a sheath liquid for flowing the second measurement sample through the flow cell of the electric resistance type detection unit 42. Used. The first diluent is not used as a sheath liquid.

The staining reagent contains a fluorescent dye that specifically stains nucleic acid, and preferably contains a fluorescent dye that stains DNA more strongly than RNA. The fluorescent dye of the first embodiment is, for example, Hoechst 34580. The dyeing reagent is a solvent in which a fluorescent dye is dissolved, and the solvent of the dyeing reagent is, for example, ethylene glycol. The concentration of the fluorescent dye in the dyeing reagent is preferably 0.3 μM or more and 0.6 μM or less, specifically 0.45 μM. 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.

According to the fluorescent dyes as described above, malaria uninfected erythrocytes are almost unstained because they do not have nuclei. On the other hand, in the case of malaria-infected erythrocytes, the nucleic acid of Plasmodium that has entered the inside of the erythrocytes is stained. Thus, malaria-infected erythrocytes are largely unstained with fluorescent dyes, whereas malaria-infected erythrocytes are stained with fluorescent dyes. Therefore, it is possible to distinguish between non-malaria-infected erythrocytes and malaria-infected erythrocytes based on the difference in fluorescence intensity in the scattergram described later. Since leukocytes have nuclei, they are stained with a fluorescent dye, and platelet aggregation is hardly stained with a fluorescent dye because they do not have nuclei.

The first measurement sample may be prepared by mixing one reagent containing the first dilution solution and the fluorescent dye with a blood sample without separating the first dilution solution and the dyeing reagent.

The optical detection unit 41 performs the first measurement based on the first measurement sample by the flow cytometry method. The optical detection unit 41 includes a flow cell 101, a light source 102, and light receiving units 103, 104, 105. At the time of the first measurement, the flow cell 101 is supplied with the first measurement sample from the sample preparation unit 30 via the flow path.

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

The electric resistance type detection unit 42 performs the second measurement based on the second measurement sample by the sheath flow DC detection method. At the time of the second measurement, the second measurement sample is supplied from the sample preparation unit 30 to the flow cell (not shown) of the electric resistance type detection unit 42 via the flow path. The electric resistance type detection unit 42 applies a voltage to the second measurement sample flowing through the flow cell of the electric resistance type detection unit 42, and detects the particles by capturing the change in the voltage due to the passage of the particles. The electric resistance type detection unit 42 outputs the 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 to 105. Specifically, the signal processing circuit 43 extracts the waveform corresponding to the particles based on the signals output from the light receiving units 103 to 105, and first information the peak value, width, area, etc. of the waveform for each particle. Calculate as. Hereinafter, the peak values of the waveforms based on the signals output from the light receiving units 103 and 105 are referred to as "forward scattered light intensity" and "fluorescence intensity", respectively. The forward scattered light intensity and the 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 electric resistance type detection unit 42 as the second information.

The measurement control unit 21 inputs the first information obtained by the signal processing of the signal processing circuit 43 at the time of the first measurement and the second information obtained by the signal processing of the signal processing circuit 43 at the time of the second measurement. , Stored in the storage unit 22. When the first measurement and the second measurement are completed, the measurement control unit 21 transmits the first information and the second information stored in the storage unit 22 to the information processing unit 12 as measurement data.

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

The control unit 51 is composed of, for example, a CPU, an MPU, and the like. The control unit 51 receives signals 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, or the like. The control unit 51 executes the process based on the program 52a stored in the storage unit 52. The program 52a includes a program for performing the processes shown in FIGS. 4, 5 (a), and 6 which will be described later.

The control unit 51 determines the presence or absence of infection with Plasmodium malaria based on the value indicating the variation in the distribution of the particle group included in the range in which the single ring foam erythrocytes appear, which is specified based on the fluorescence intensity and the scattered light intensity. By doing this, it is possible to clearly determine whether or not malaria-infected erythrocytes are included in the particle group included in the range where single ring form erythrocytes appear. Is positive, so-called false positives can be suppressed. Therefore, the presence or absence of Plasmodium infection can be determined with higher accuracy. The determination process 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 composed of, for example, a display. The voice output unit 53b outputs information as voice. 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 the analysis result and the like in the storage unit 52, and outputs the analysis result and the like to the output unit 53. The control unit 51 receives an instruction from the operator via the input unit 54.

Next, the optical detection unit 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, a light receiving unit 103 to 105, a collimator lens 111, a condenser lens 112, a beam stopper 113, a condenser lens 114, and the like. A dichroic mirror 115 and an optical filter 116 are provided.

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

The light source 102 emits light in the bluish-purple wavelength band. Specifically, the light source 102 is a semiconductor laser light source, and emits a bluish-purple laser light having a wavelength of 405 nm. The light emitted from the light source 102 excites the fluorescent dye contained in the dyeing reagent to generate fluorescence in a predetermined wavelength band from the fluorescent dye. The light source 102 may emit light in a band other than the bluish-purple wavelength band as long as the emitted light causes fluorescence from the fluorescent dye. Further, the shorter the wavelength of the light emitted from the light source 102, the smaller the light emitted to the flow cell 101 can be narrowed down, so that smaller particles can be detected. Therefore, it is desirable that the wavelength of the light emitted from the light source 102 is set to the bluish-purple wavelength band as described above.

The collimator lens 111 and the condensing lens 112 condense the light emitted from the light source 102 and irradiate the first measurement sample flowing in the flow cell 101. 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. The forward scattered light reflects information about the size of the particles, the side scattered light reflects the internal information of the particles, and the fluorescence reflects the degree of staining of the particles. Of the light irradiated to the flow cell 101, the light transmitted through the flow cell 101 without being irradiated to the particles is blocked by the beam stopper 113. The light receiving unit 103 is composed of, for example, a photodiode. The light receiving unit 103 receives the forward scattered light and outputs an electric signal corresponding to the received forward scattered light.

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

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

As shown in FIG. 3, in step S11, the measurement control unit 21 determines whether or not a start instruction has been received from the information processing unit 12. Upon receiving the start instruction, in step S12, the measurement control unit 21 prepares the first measurement sample and the second measurement sample.

Specifically, the sample rack is transported by the rack transport unit, and the sample container is positioned at the take-out position. The measurement control unit 21 controls each part of the measurement unit 11 to take out the sample container from the sample rack and stir it at the extraction position, and positions the sample container after stirring at the suction position. The measurement control unit 21 controls the suction unit 23 to suck the blood sample from the sample container by the suction tube, and discharge the sucked blood sample into the reaction tank 34. The sample container that has been aspirated is returned to its original position in the sample rack. The measurement control unit 21 controls the sample preparation unit 30 to mix the blood sample, the first diluent, and the staining reagent in the reaction vessel 34 to prepare the first measurement sample. Further, the measurement control unit 21 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.

When the blood analyzer 10 does not have a configuration for transporting the sample rack and a configuration for transporting the sample container, the measurement control unit 21 controls the suction unit 23 and positions the sample container at the suction position by the operator. The blood sample is sucked from the suction tube.

In step S13, the measurement control unit 21 controls the optical detection unit 41 to perform the first measurement, and controls the electrical resistance type detection unit 42 to perform the second measurement. At this time, the measurement control unit 21 flows the first measurement sample through the flow cell 101, and stores the first information acquired during the time T1 in the storage unit 22. Further, the measurement control unit 21 flows the second measurement sample through the flow cell of the electric resistance type detection unit 42, and stores the second information acquired during the time T2 in the storage unit 22. 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 S15, the measurement control unit 21 determines whether or not the start instruction of the triple counting mode has been received from the information processing unit 12. When the start instruction of the triple counting mode has not been received, in step S16, the measurement control unit 21 determines whether or not the end instruction has been received from the information processing unit 12. If the end instruction has not been received, the process is returned to step S15. If the start instruction of the triple counting mode is not received and the end instruction is received, the processing of the measuring unit 11 ends.

Upon receiving the start instruction of the triple counting mode, 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 type detection unit 42 to perform the second measurement in the triple counting mode. At this time, the measurement control unit 21 flows the first measurement sample through the flow cell 101, and stores the first information acquired during the time three times the time T1 in the storage unit 22. Further, the measurement control unit 21 flows the second measurement sample through the flow cell of the electric resistance type detection unit 42, and stores the second information acquired during the time three times as long as the time T2 in the storage unit 22. As a result, the first information based on the first measurement sample, which is about three times the amount, and the second information based on the second measurement sample, which is about three times the amount, are obtained as compared with the measurement in the normal mode performed in step S13. To be acquired.

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 of step S18 to the information processing unit 12 as measurement data in the triple counting mode. In this way, the processing of the measuring unit 11 is completed. When the process shown in FIG. 3 is completed, the measurement control unit 21 returns the process to step S11 and performs the same measurement on the subsequent blood sample.

Next, the processing of the information processing unit 12 will be described with reference to the 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 54. Upon receiving the start instruction from the operator, in step S22, the control unit 51 transmits the start instruction to the measurement unit 11. As a result, the measurement unit 11 starts the processes after step S12 in FIG. 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 swarms G3 per unit volume is equal to or greater than the threshold value th1 based on the measurement data in the normal mode. The particle group G3 is a particle group included in the range in which malaria-infected erythrocytes, which will be described later, appear. The particle swarm G3 will be described later with reference to FIG. 5 (b). The threshold value th1 is set to 100 or more and 500 or less, for example, 100. The threshold value th1 can be changed by the operator via the input unit 54. In step S24, the control unit 51 may determine whether or not the number of particle swarms G3 is equal to or greater than a predetermined threshold value.

When the number of particle swarms G3 per unit volume is equal to or greater than the threshold value th1, in step S25, the control unit 51 transmits an end instruction to the measurement unit 11 and proceeds to the process in step S26. As a result, YES is determined in step S16 of FIG. 3, and the process of the measuring unit 11 shown in FIG. 3 is completed. On the other hand, when the number of particle swarms G3 per unit volume is less than the threshold value th1, in step S28, the control unit 51 transmits a start instruction of the triple counting mode to the measurement unit 11. 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 swarms G3 per unit volume is less than the threshold value th1, for example, "malaria negative" is easily determined in the determination process described later based on the measurement data in the normal mode. Is not preferable. Even if a subject has malaria, there may be few malaria-infected red blood cells in the subject's blood sample. In this case, if a determination of "malaria negative" is made, a false negative will occur. It is also important to monitor until the malaria-infected red blood cells are completely eliminated, even if the treatment gradually reduces the malaria-infected red blood cells.

Therefore, when the number of particle group G3 is small, the control unit 51 further acquires the measurement data in the triple counting mode, and performs the analysis process described later using the acquired measurement data in the triple counting mode. As a result, the analysis process is performed using the first information and the second information based on the blood cell count, which is about three times the blood cell count acquired in the normal mode. Therefore, the obtained analysis result is the bias of the measurement sample, etc. It is less likely to be affected by the condition of the blood sample, and the condition of the blood sample is properly reflected. Therefore, it is possible to prevent the output of malaria analysis results with low accuracy.

Subsequently, in step S26, the control unit 51 performs an analysis process. The analysis process will be described later with reference to FIG. 5 (a). In step S27, the control unit 51 outputs the analysis result obtained by the analysis process of step S26 to the output unit 53. Specifically, the control unit 51 displays the number of blood cells, a scattergram, a frequency distribution map, a determination result, information indicating reliability, and the like on the display unit 53a as an analysis result. The screen displayed on the display unit 53a will be described later with reference to FIG. The control unit 51 may output this information to a device other than the blood analyzer 10. Further, the control unit 51 may output the number of blood cells, the determination result, and the like from the voice output unit 53b by voice.

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

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

In the following steps S101 and S102, when the control unit 51 does not receive the measurement data in the triple counting mode, counts using the measurement data in the normal mode, and receives the measurement data in the triple counting mode. Counting is performed using the measurement data in the triple counting mode.

As shown in FIG. 5A, in step S101, the control unit 51 blood cells based on the second information included in the measurement data, that is, the second information obtained in the second measurement by the electric resistance type detection unit 42. To count. Specifically, the control unit 51 counts red blood cells and platelets. In step S102, the control unit 51 counts blood cells based on the first information included in the measurement data, that is, the first information obtained in the first measurement by the optical detection unit 41. Specifically, the control unit 51 counts white blood cells, non-malaria-infected erythrocytes, malaria-infected erythrocytes, single-ring foam erythrocytes, and multi-ring foam erythrocytes.

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 represents the forward scattered light intensity and the horizontal axis represents the fluorescence intensity. Each particle detected in the first measurement is plotted on the scattergram 200 based on the forward scattered light intensity and fluorescence intensity associated with each particle.

In the scattergram 200, the leukocytes are generally distributed in the region 201 where the forward scattered light intensity and the fluorescence intensity are high. Non-malaria-infected erythrocytes are smaller than leukocytes and are contracted by the first diluent. In addition, malaria non-infected erythrocytes are almost unstained with fluorescent dyes. Therefore, malaria non-infected erythrocytes are generally distributed in region 202. The forward scattered light intensity of the region 202 is smaller than that of the region 201 corresponding to leukocytes. The fluorescence intensity of the region 202 is smaller than that of the region 201.

Malaria-infected erythrocytes are also smaller than leukocytes and are contracted by the first diluent. In addition, malaria-infected erythrocytes are stained with a fluorescent dye because they retain Plasmodium malaria inside. Therefore, malaria-infected erythrocytes are generally distributed in region 203. The forward scattered light intensity of region 203 is smaller than that of region 201 corresponding to leukocytes. The fluorescence intensity of region 203 is greater than that of region 202, which corresponds to uninfected erythrocytes, and smaller than that of region 201, which corresponds to leukocytes.

Since the malaria-infected erythrocytes are contracted while retaining the malaria protozoa inside, the size of the malaria-infected erythrocytes becomes a size according to the morphology of the malaria protozoa retained inside. Therefore, the size of single-ring foam erythrocytes and multi-ring foam erythrocytes is generally smaller than that of erythrocytes infected with other forms of Plasmodium, and the size of single-ring foam erythrocytes and multi-ring foam erythrocytes are similar. Moreover, since the multi-ring foam erythrocytes retain a plurality of Plasmodium malaria inside, the fluorescence intensity of the multi-ring foam erythrocytes is higher than that of the single ring foam erythrocytes. Therefore, the single ring foam erythrocytes are generally distributed in the region 204, and the multi ring foam erythrocytes are generally distributed in the region 205. Regions 204 and 205 are included in region 203 corresponding to malaria-infected erythrocytes. The regions 204 and 205 do not overlap each other and are adjacent to each other in the horizontal axis direction, and are located at the left end in the region 203. The fluorescence intensity of region 205 is greater than that of region 204.

In addition, "the fluorescence intensity of the first region is larger than that of the second region" means that the maximum value and the minimum value of the fluorescence intensity of the first region are larger than the maximum value and the minimum value of the fluorescence intensity of the second region, respectively. Is shown. "The fluorescence intensity of the first region is smaller than that of the second region" means that the maximum and minimum values of the fluorescence intensity of the first region are smaller than the maximum and minimum values of the fluorescence intensity of the second region, respectively. .. The same applies to the expressions relating to the magnitude relationship between the forward scattered light intensity in the first region and the forward scattered light intensity in the second region.

In the process of step S102, the control unit 51 counts blood cells based on the fluorescence intensity and the scattered light intensity of the measurement data. Specifically, the control unit 51 includes a particle group G1 included in the range in which leukocytes appear, a particle group G2 included in the range in which non-malaria-infected erythrocytes appear, and a particle group G3 included in the range in which malaria-infected erythrocytes appear. , The particle group G4 included in the range in which single-ring foam erythrocytes appear, and the particle group G5 included in the range in which multi-ring foam erythrocytes appear. In the scattergram 200, the range in which leukocytes appear corresponds to region 201, the range in which non-malaria-infected erythrocytes appear corresponds to region 202, the range in which malaria-infected erythrocytes appear corresponds to region 203, and the range in which single-ring foam erythrocytes appear. Corresponds to region 204, and the range in which multiring foam erythrocytes appear corresponds to region 205. Then, the control unit 51 acquires the number of each blood cell by counting the number of each specified particle group.

In the blood cell counting in step S102, the control unit 51 does not create the scattergram and set the region, but counts the blood cells by data processing according to the same procedure as in the case of creating the scattergram and setting the region. Do. 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 scattergram, and count the blood cells contained in the set region. The control unit 51 does not create a scattergram for the purpose of counting blood cells, but creates a scattergram when displaying a screen described later on the display unit 53a.

The scattergram 200 may be set with regions corresponding to gametogony, trophozoite, and schizont. In this case, in step S102, the control unit 51 counts the number of particle swarms included in the range where gametogony appears, the number of particle swarms included in the range where trophozoite appears, and the number of particle swarms included in the range where schizont appears. You may.

Subsequently, in step S103, the control unit 51 performs a determination process described later with reference to FIG. The determination process determines the presence or absence of malaria in the target blood sample. In this way, the analysis process is completed.

Here, the inventors have 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 erythrocytes. In addition, the inventors have found that in blood samples collected from subjects not suffering from malaria, the particles distributed in region 203 include apoptotic bodies, erythrocytes containing Howell-Jolly bodies, and the like. It was. Apoptotic bodies are a type of extracellular vesicle. Howell-Jolly bodies are a type of nucleic acid inclusion body. In addition, the inventors have stated that the apoptotic erythrocytes and the erythrocytes containing the Howell-Jolly erythrocytes are distributed from the region 204 corresponding to the single ring foam erythrocytes in the direction in which the fluorescence intensity and the forward scattered light intensity increase. I found it.

The process by which the inventors have found that apoptotic bodies and erythrocytes containing Howell-Jolly bodies are distributed in the region 203 will be described later with reference to FIGS. 12 (a) to 15 (Fig. 15).

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

As shown in FIG. 6, in step S111, the control unit 51 determines whether or not the number of particle swarms G3 per unit volume is equal to or greater than the threshold value th11. As shown in FIG. 5B, the particle swarm G3 is a particle swarm that is included in the range in which malaria-infected erythrocytes appear. The number of particle swarms G3 per unit volume is, for example, the number of acquired particle swarms G3 divided by the volume of the first measurement sample flowed into the flow cell 101 during the acquisition of the first information. The threshold value th11 is set so that the target blood sample can be determined to be "malaria negative" based on the number of particle swarms G3 per unit volume. The threshold th11 is set to, for example, 200.

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 swarms G3 is equal to or greater than a predetermined threshold value. Further, the threshold value th11 can be changed by the operator via the input unit 54. Similarly, the threshold values th12 and th13 described later and the threshold values th21, th22, th23, th31 and th32 described later in the second and third embodiments can be changed by the operator via the input unit 54. This allows the operator to fine-tune the determination in each determination step.

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

On the other hand, when the number of particle swarms G3 per unit volume is equal to or greater than the threshold value th11, in step S113, the control unit 51 determines that the target blood sample is “malaria positive?”, And the determination result is stored in the storage unit 52. Remember. The determination result of "malaria positive?" Indicates that the target blood sample is likely to contain malaria-infected erythrocytes, 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 swarms G4 per unit volume is equal to or greater than the threshold value th12. As shown in FIG. 5B, the particle swarm G4 is a particle swarm that is included in the range in which single ring foam erythrocytes appear. The number of particle swarms G4 per unit volume is, for example, the number of acquired particle swarms G4 divided by the volume of the first measurement sample flowed into the flow cell 101 during the acquisition of the first information. The threshold value th12 is set so that it can be determined whether or not malaria-infected erythrocytes are distributed in the region 204 corresponding to the single ring form erythrocytes in the target blood sample based on the number of particle groups G4 per unit volume. Will be done. The threshold th12 is set to, for example, 150.

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 swarms G4 is equal to or greater than a predetermined threshold value. Further, the process of step S114 may be omitted. However, in the case of a blood sample infected with Plasmodium malaria, it is desirable to determine the number of particle group G4 in step S114 because a large number of particles are particularly distributed in the region 204.

When the number of particle swarms G4 per unit volume is less than the threshold value th12, the control unit 51 ends the determination process. In this case, the determination result is "malaria positive?" Stored in step S113.

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

In the calculation of the coefficient of variation in step S115, the control unit 51 does not create the frequency distribution map, but calculates the coefficient of variation by data processing according to the same procedure as in the case of creating the frequency distribution map. However, the present invention is not limited to this, and the control unit 51 may create a frequency distribution map and calculate the coefficient of variation. The control unit 51 does not create a frequency distribution map for the purpose of calculating the coefficient of variation, but when displaying the screen described later on the display unit 53a, the control unit 51 creates a frequency distribution map and displays the created frequency distribution map in the display unit. Display on 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 intensity of light other than the fluorescence intensity. Further, the value indicating the variation calculated in step S115 is not limited to the value indicating the variation of the one-axis distribution, and may be a value indicating the variation of the two-axis or three-axis distribution. For example, the value of the distribution on the scattergram 200 It may vary. Further, the scattergram 200 is not limited to the fluorescence intensity and the forward scattered light intensity, and may be created based on a combination of other light intensities.

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 value th13. The threshold value th13 is set so that the target blood sample can be determined to be “malaria positive” based on the coefficient of variation. The threshold th13 is set to, for example, 10%.

Here, the amount of nucleic acid contained in single ring foam erythrocytes is substantially a predetermined amount, whereas the amount of nucleic acid contained in apoptotic bodies and the amount of nucleic acids contained in erythrocytes including Howell-Jolly bodies vary. Therefore, when the particles are distributed in the region 204 corresponding to the single ring foam erythrocytes, if the blood sample contains malaria-infected erythrocytes, the variation in the frequency distribution based on the particle group G4 becomes small, and the blood sample contains malaria-infected erythrocytes. Otherwise, the variation in the frequency distribution based on the particle group G4 will be large. 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 erythrocytes.

If the coefficient of variation is less than the threshold value th13, in step S117, the control unit 51 determines that the target blood sample is “malaria positive” and stores the determination result in the storage unit 52. Then, the control unit 51 ends 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 the threshold value th13 or more, in step S118, the control unit 51 determines that “malaria is positive or scatter abnormality”, and stores the determination result in the storage unit 52. The "scatter abnormality" included in the determination result in this case is information indicating the reliability of the determination result regarding the infection of Plasmodium malaria. Specifically, the "scatter abnormality" is information indicating that the reliability of the determination result for malaria is not high. Then, the control unit 51 ends the determination process.

When the coefficient of variation is the threshold value th13 or more, it is unlikely that malaria-infected erythrocytes are present, so it is possible to determine that malaria-infected erythrocytes are not present. However, in this case, it is desirable to determine "malaria negative, scatter abnormality" rather than simply determining "malaria negative".

Next, with reference to FIGS. 7 (a) to 9 (d), determinations made specifically for 10 types of samples will be described.

7 (a) and 7 (b) are scattergrams 200 based on blood samples collected from a subject suffering from malaria. 7 (c) and 7 (d) are scattergrams 200 based on cultured malaria. 8 (a) and 8 (b) are scattergrams 200 when apoptosis is induced in Jurkat cells. 8 (c) and 8 (d) are scattergrams 200 based on blood samples collected from subjects not suffering from malaria. 9 (a) and 9 (b) are scattergrams 200 based on blood samples collected from mice not suffering from malaria. In either case, the particles located at the left end of the region 202 are cut as noise components.

The blood sample collected from the mouse always contains erythrocytes including Howell-Jolly bodies. In the following description of the determination, a blood sample collected from a mouse is used as an example of a human blood sample containing red blood cells containing Howell-Jolly bodies.

In each of the 10 types of samples shown in FIGS. 7 (a) to (d), 8 (a) to (d), 9 (a), and (b), the region 203 corresponding to malaria-infected erythrocytes. And a predetermined number of particles appear in the region 204 corresponding to the single ring foam erythrocytes. The numbers of the particle swarms G4 in FIGS. 7 (a) to (d), 8 (a) to (d), 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 coefficient of variation of the frequency distribution with respect to the fluorescence intensity of the particle group G4 is calculated in step S115.

7 (e) to (h), 8 (e) to (h), 9 (c), and (d) are shown in FIGS. 7 (a) to 7 (d) and 8 (a) to 8 (d), respectively. d), FIG. 9 is a frequency distribution diagram 300 created based on the scattergram 200 of FIGS. 9A and 9B. In the frequency distribution diagram 300, the horizontal axis represents the fluorescence intensity and the vertical axis represents the frequency. The frequency distribution diagram 300 shows a frequency distribution based only on the particle swarm G3 included in the range in which single ring form erythrocytes appear. The frequency distribution diagram 300 is normalized based on the value of the maximum frequency.

With reference to the frequency distribution diagrams 300 of FIGS. 7 (e) to 7 (h), the shape of the frequency distribution is a sharp shape in each case. The coefficients of variation of FIGS. 7 (e) to 7 (h) are 7.3%, 6.4%, 7.4%, and 6.3%, respectively. Therefore, in any of the cases of FIGS. 7 (e) to 7 (h), YES is determined in step S116 of FIG. 6, and these samples are determined to be “malaria positive”. Here, the samples shown in FIGS. 7 (e) to 7 (h) are all samples infected with malaria, as described above. Therefore, according to the determination process shown in FIG. 6, it can be seen that a 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 8 (h), FIGS. 9 (c) and 9 (d), the shape of the frequency distribution is not completely sharp in any case. The coefficients of variation of FIGS. 8 (e) to 8 (h), 9 (c) and 9 (d) are 19.6%, 18.8%, 25.1%, 21.1% and 16.5%, respectively. , 18.0%. Therefore, in any of FIGS. 8 (e) to 8 (h), 9 (c), and (d), NO was determined in step S116 of FIG. 6, and these samples were classified as "malaria positive? Scatter abnormality". It is judged. Here, the samples shown in FIGS. 8 (e) to 8 (h), 9 (c), and (d) are all samples that are not infected with malaria. Therefore, according to the determination process shown in FIG. 6, it can be seen that it is possible to prevent these six samples from being erroneously determined as “malaria positive”.

As described above, according to the determination process shown in FIG. 6, even if particles appear in regions 203 and 204 when malaria-infected erythrocytes are not present in the blood sample, erroneous determination of “malaria positive” is avoided. Then, it is possible to make an appropriate judgment as "malaria positive? Scatter abnormality". In addition, when malaria-infected erythrocytes are present in the blood sample, it is possible to make an appropriate determination as "malaria positive". Therefore, it is possible to suppress false positives and determine the presence or absence of malaria protozoan infection with high accuracy.

In addition, when a human suffers from malaria, the function of the spleen is reduced, so that the blood sample may always contain red blood cells including Howell-Jolly bodies. In this case, both malaria-infected erythrocytes and erythrocytes containing Howell-Jolly bodies are present in the blood sample, but since it is determined to be YES in step S111 of FIG. 6, the determination result is "malaria negative". 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, comment areas 63, a scattergram 200, and a frequency distribution diagram 300. The list area 61 displays the counting results of white blood cells, red blood cells, platelets, and the like in a list format. The list area 62 displays the count result of malaria-infected erythrocytes and the ratio of malaria-infected erythrocytes. The malaria-infected erythrocyte ratio is obtained by dividing the number of blood cells in the region 203 corresponding to the malaria-infected erythrocyte shown in FIG. 5 (b) by the number of erythrocytes acquired in step S101 of FIG. 5 (a).

The comment area 63 displays the determination result obtained by the determination process of FIG. Specifically, when step S112 of FIG. 6 is executed, nothing is displayed in the comment area 63. Even in this case, "malaria negative" may be displayed in the comment area 63. If NO is determined in step S114 of FIG. 6, "Malaria positive?" Is displayed in the comment area 63. When step S117 of FIG. 6 is executed, “malaria positive” is displayed in the comment area 63. When step S118 of FIG. 6 is executed, “malaria positive? Scattergram abnormality” is displayed in the comment area 63 as illustrated in FIG.

When "malaria positive" or "malaria negative" is displayed in the comment area 63, the doctor or the like determines whether or not the subject has malaria, and the malaria is completely cured in the subject being treated. It is possible to judge whether or not it has been done. Further, when "Malaria positive?" Is displayed in the comment area 63, 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 confirming the blood sample with 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 and the like can know that particles other than malaria-infected erythrocytes, such as erythrocytes containing extracellular vesicles and inclusion bodies of nucleic acids, may be distributed in the region 203 of the scattergram 200. In this case, the doctor or the like can perform further tests such as confirming the blood sample with a microscope. Further, by displaying the scattergram 200 and the frequency distribution map 300 on the screen 60, the doctor or the like can quickly and in detail grasp the state of the blood sample.

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

In the determination process of the first embodiment shown in FIG. 6, the inventors omit step S114 and change the determination process to determine “malaria negative” in step S118 as the determination process of Verification Example 1. That is, in the determination process of Verification Example 1, when the determination in both steps S111 and S116 is YES, the determination result is "malaria positive", and the determination in either step S111 or S116 is NO. The judgment result was "malaria negative".

Further, in the determination process of the first embodiment shown in FIG. 6, the inventors omit steps S114 to S118 and change the determination process to determine “malaria positive” in step S113, which is referred to as the determination process of Verification Example 2. did. 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 samples and 130 malaria-negative samples, prepared a first measurement sample based on these samples, and measured the prepared first measurement sample by the optical detection unit 41. did. Then, the inventors perform the analysis process shown in FIG. 5A using the measurement data obtained by the first measurement, and determine malaria by the determination processes of Verification Examples 1 and 2 set as described above. Was done. Based on the malaria determination results obtained by the determination processes of Verification Examples 1 and 2, the inventors verified whether or not the malaria determination was properly performed. In this verification, the region of the scattergram 200 shown in FIG. 5B was finely adjusted for each sample by using an automatic fractionation algorithm. Further, in this verification, the threshold value th11 in step S111 was set to 30, and the threshold value th13 in step S116 was set to 20%.

As shown in FIG. 11A, according to Verification Example 1, all 27 malaria-positive samples were properly determined to be malaria-positive. Of the 130 malaria-negative samples, 2 were erroneously determined to be malaria-positive, but 128 were properly determined to be 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. 11B, according to Verification Example 2, all 27 malaria-positive samples were properly determined to be malaria-positive. Of the 130 malaria-negative samples, 48 were properly determined to be malaria-negative, but 82 were erroneously determined to be 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 as compared with the determination process of Verification Example 2. 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 the specificity can be improved and false positives can be suppressed. I can say.

<Discussion on erythrocytes containing nucleic acid inclusion bodies and extracellular vesicles>
The inventors have included an apoptotic body, which is a type of extracellular vesicle, and a Howell-Jolly body, which is a type of nucleic acid inclusion body, in the region 203 corresponding to malaria-infected erythrocytes shown in FIG. 5 (b). The process of finding the distribution of red blood cells will be explained. The erythrocyte containing the inclusion body of nucleic acid is an erythrocyte containing an inclusion body of nucleic acid in which nucleic acid aggregates and remains inside the cell. In reticulocytes, the RNA existing inside is dispersed in the reticulocytes, and the nucleic acid does not exist as an aggregate. Therefore, reticulocytes are different from red blood cells that contain inclusion bodies of nucleic acids.

First, the inventors investigated a method for determining that a malaria determination result is positive when particles are distributed in the region 203 corresponding to malaria-infected erythrocytes, and found that the subject is not suffering from malaria. We have found that so-called false positives, in which the judgment result of malaria is positive, rarely occur. That is, the inventors have found that particles may be distributed in the region 203 corresponding to malaria-infected erythrocytes even when the subject is not suffering from malaria.

Next, the inventors conducted the following observations and experiments on the event that the particles were distributed in the region 203 even though the subject was not affected by malaria.

The inventors observed under a microscope a blood sample in which particles were distributed in region 203 even though the subject was not affected by malaria, that is, 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. 12A, the particle swarms distributed in the region 203 are distributed in the oblique direction from the origin. That is, the particle swarms 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. 12B is an image showing the result of observing the blood sample shown in FIG. 12A with a microscope. As shown in FIG. 12B, in this blood sample, particles mixed with erythrocytes, leukocytes, and platelets, which are different from any of erythrocytes, leukocytes, and platelets, and have a size of about platelets may be present. Do you get it. The inventors considered that the particles were likely to be extracellular vesicles.

FIG. 13 (a) is a scattergram 200 created based on other blood samples that produce false positives. As shown in FIG. 13A, also in this blood sample, the particle swarms distributed in the region 203 are distributed in the oblique direction from the origin. 13 (b) and 13 (c) are images showing the results of observing the blood sample shown in FIG. 13 (a) with a microscope. As shown in FIGS. 13 (b) and 13 (c), the blood sample also contained particles considered to be extracellular vesicles mixed with erythrocytes, leukocytes, 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, the particles considered to be extracellular vesicles are found. It turned out to exist.

In addition, the inventors conducted an experiment to induce apoptosis in Jurkat cells and to confirm how apoptotic bodies, which are a type of extracellular vesicles, appear in Scattergram 200. The conditions for this experiment are as follows.

(Jurkat cells)
・ Medium: RPMI1640 medium supplemented with 10% FBS ・ Cell solution: ^{Jurkat cells cultured to about 1 × 10 6} / μL are diluted 10-fold with medium and cultured for 24 hours (apoptosis induction).
・ Inducer: Staurosporine 1 μM
-Stock solution: 250 μg / 500 μL DMSO (1 mM Staurosporine)
-Prepare a 100 μM Staurosporine solution obtained by diluting 1 mM Staurosporine 10-fold with a medium, and add 1/100 of the amount to the culture solution.

FIG. 14 (a) is a scattergram 200 created based on Jurkat cells prior to introducing apoptosis. Since the malaria-infected erythrocytes were absent in the Jurkat cells, as shown in FIG. 14 (a), the particles were hardly distributed in the region 203 of the scattergram 200. On the other hand, FIG. 14 (b) is a scattergram 200 created based on the Jurkat cells when 4 hours have passed after inducing apoptosis in the Jurkat cells shown in FIG. 14 (a).

Here, it is known that the apoptotic reaction proceeds over time after the induction of apoptosis. Since the particles distributed diagonally from the origin in FIG. 14B appeared after the induction of apoptosis, it can be said that they are apoptotic bodies, which are a type of extracellular vesicles. Further, also in the scattergram 200 shown in FIGS. 12 (a) and 13 (a), a large number of particles are distributed in a region similar to the distribution region of the apoptotic bodies shown in FIG. 14 (b). Was confirmed.

Next, the inventors microscopically used the blood sample shown in the scattergram 200 of FIG. 9A as a blood sample in which particles are distributed in the region 203 even though the subject is not suffering from malaria. Observed by. The blood sample of FIG. 9 (a) is a blood sample collected from a mouse not suffering from malaria.

FIG. 15 is an image showing the results of observing the mouse blood sample shown in FIG. 9A with a microscope. As shown in FIG. 15, red blood cells containing Howell-Jolly bodies were present in the blood sample of the mouse, mixed with normal mature red blood cells. Further, in the scattergram 200 created based on the blood sample of the mouse, as shown in FIG. 9A, the particles are distributed in the region 203, and the particle group distributed in the region 203 is obliquely oriented from the origin. It was distributed. From the above, the inventors have determined that even in a human blood sample in which particles are distributed in region 203 even though the subject is not suffering from malaria, erythrocytes containing Howell-Jolly bodies are present. I thought there was.

From the results of the above observations and experiments, the inventors have 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 a particle appears in the region 203 corresponding to malaria-infected erythrocytes even though the subject is not affected by malaria, the particle is a type of extracellular vesicle, small apoptosis. It was found to contain erythrocytes containing the body or Howell-Jolly bodies, a type of inclusion body of nucleic acid.

Then, the inventors have found that the variation in the frequency distribution with respect to the fluorescence intensity of the particle group G4 in the region 204 becomes large when at least one of the erythrocytes containing the inclusion bodies of nucleic acids and the extracellular vesicles is distributed in the region 204. We found that malaria-infected erythrocytes become smaller when they are distributed in region 204.

When malaria-infected erythrocytes are contained in the blood sample, a mountain shape having a remarkably high frequency is likely to appear in only one place in the frequency distribution based on the particle swarm G4. On the other hand, in the case of a blood sample that produces false positives, in the frequency distribution based on the particle group G4, erythrocytes or extracellular vesicles containing inclusion bodies of nucleic acids are distributed over a wide range of fluorescence intensities, and there is a large difference in frequency. Is unlikely to occur. Therefore, when the frequency distribution with respect to the fluorescence intensity is created based on the particle group G4, there is a large difference in the variation of the frequency distribution between the case where the malaria-infected erythrocytes are contained in the blood sample 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 in which the single ring foam erythrocytes appear, it becomes easy to clearly distinguish between the malaria positive case and the false positive case.

Based on these findings, the inventors configured the determination process for malaria as shown in FIG. 6 so that false positives could be suppressed.

The extracellular vesicle is a vesicle released from a cell, and is a concept including fine particles derived from nucleated cells and fine particles derived from non-nucleated cells. Examples of extracellular vesicles include exosomes, microvesicles (MV), apoptotic bodies and the like. Given the particle size, in addition to apoptotic bodies, some microvesicles may also be distributed in region 203. Erythrocytes containing inclusion bodies of nucleic acids include Howell-Jolly bodies, basophilic spots, and the like. In other words, nucleic acid inclusions are concepts that include Howell-Jolly bodies and basophilic spots. Basophilic spots are also a type of nucleic acid inclusion body. In addition to erythrocytes containing Howell-Jolly bodies, erythrocytes 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 the second embodiment and the third embodiment described later, "determining the presence or absence of at least one of an erythrocyte containing a nucleic acid inclusion body and an extracellular vesicle" means that the erythrocyte containing the nucleic acid inclusion body or the extracellular vesicle is determined. Determining the presence or absence, that is, determining the presence or absence of at least one of erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles. The determination process of the second embodiment has substantially the same configuration as shown in FIG. 16, although the determination content is different from that of the determination process of the first embodiment shown in FIG. 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 swarms G3 per unit volume is equal to or greater than the threshold value th21. As shown in FIG. 5B, the particle swarm G3 is a particle swarm that is included in the range in which malaria-infected erythrocytes appear. The threshold value th21 is set so that the target blood sample can be determined to be "malaria-negative, no erythrocytes containing nucleic acid inclusion bodies, and no extracellular vesicles" based on the number of particle groups G3 per unit volume. .. The threshold value th21 is set to, for example, the same value as the threshold value th11 in step S111 of FIG.

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 blood sample of interest is "malaria-negative, no erythrocytes containing nucleic acid inclusions, and no extracellular vesicles." , And the determination result is stored in the storage unit 52. Then, the control unit 51 ends the determination process.

On the other hand, when the number of particle swarms G3 per unit volume is equal to or greater than the threshold value th21, in step S123, the control unit 51 determines that the target blood sample is “malaria positive? Is there a vesicle? ”, And the determination result is stored in the storage unit 52. The judgment result of "Malaria positive? Red blood cells containing nucleic acid inclusion bodies or extracellular vesicles?" Is that the target blood sample contains malaria-infected erythrocytes and erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles. It is likely that at least one of the above is included, but it is difficult to determine which is included.

Subsequently, in step S124, the control unit 51 determines whether or not the number of particle swarms G4 per unit volume is equal to or greater than the threshold value th22. As shown in FIG. 5B, the particle swarm G4 is a particle swarm that is included in the range in which single ring foam erythrocytes appear. The threshold th22 is based on the number of particle groups G4 per unit volume, for the blood sample of interest, malaria-infected erythrocytes, erythrocytes containing nucleic acid inclusions, or extracellular vesicles in region 204 corresponding to single ring foam erythrocytes. It is set so that it can be determined whether or not the vesicles are distributed. The threshold value th22 is set to, for example, the same value as the threshold value th12 in step S114 of FIG.

When the number of particle swarms G4 per unit volume is less than the threshold value th22, the control unit 51 ends the determination process. In this case, the determination result is "malaria positive? Are there erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles?" Stored in step S123.

On the other hand, when the number of the particle group G4 per unit volume is equal to or greater than the threshold value th22, in step S125, the control unit 51 calculates a value indicating the variation in the frequency distribution with respect to the fluorescence intensity of the particle group 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. The value indicating the variation of the frequency distribution calculated in step S125 is not limited to the coefficient of variation, but 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 value th23. The threshold value th23 is set so that the target blood sample can be determined to be "malaria positive" or "erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles" based on the coefficient of variation. The threshold value th23 is set to, for example, the same value as the threshold value th13 in step S116 of FIG.

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

In step S127, the control unit 51 may determine "is there malaria positive, erythrocytes containing nucleic acid inclusion bodies, or extracellular vesicles?". The judgment result of "Malaria positive, erythrocytes containing nucleic acid inclusion bodies, or extracellular vesicles?" Can determine that malaria-infected erythrocytes are present in the target blood sample, but erythrocytes containing nucleic acid inclusion bodies, or It indicates a condition in which it is difficult to determine the presence of extracellular vesicles.

On the other hand, when the coefficient of variation is the threshold value th23 or more, in step S128, the control unit 51 determines that "there is an erythrocyte containing an inclusion body of nucleic acid or an extracellular vesicle", and stores the determination result in the storage unit 52. .. Then, the control unit 51 ends the determination process. In this case, the determination result is from "Malaria positive? Red blood cells containing nucleic acid inclusion bodies or extracellular vesicles?" Stored in step S113 to "Red blood cells containing nucleic acid inclusion bodies or extracellular vesicles?" Is changed to.

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

As shown in FIG. 17, also in the second embodiment, the result of the determination process shown in FIG. 16 is displayed on the screen 60. 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 determination result obtained by the determination process of FIG. Specifically, when step S122 of FIG. 16 is executed, "malaria negative, red blood cells containing nucleic acid inclusion bodies, and no extracellular vesicles" are displayed in the comment region 63. When NO is determined in step S124 of FIG. 16, "Malaria positive? Are there erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles?" Is displayed in the comment region 63. In this case, "malaria positive? Extracellular vesicles? Erythrocytes containing nucleic acid inclusion bodies?" May be displayed. When step S127 of FIG. 16 is executed, “malaria positive” is displayed in the comment area 63. When step S128 of FIG. 16 is performed, “with erythrocytes containing nucleic acid inclusions or extracellular vesicles” is displayed in the comment region 63, as illustrated in FIG.

When "malaria negative", "malaria positive?", "Malaria positive" or the like is displayed in the comment area 63, the doctor or the like can make the same judgment as in the first embodiment. Further, in the comment region 63, "Are there erythrocytes or extracellular vesicles containing nucleic acid inclusion bodies?", "There are erythrocytes or extracellular vesicles containing nucleic acid inclusion bodies", "Extracellular vesicles?", " When "Red blood cells containing nucleic acid inclusion bodies?" Is displayed, doctors and the like, for example, state the subject of a predetermined disease that may be related to red blood cells containing nucleic acid inclusion bodies or extracellular vesicles. It can be used as a judgment material for judging. For example, doctors can assume that spleen dysfunction is present when red blood cells containing Howell-Jolly bodies are present, and lead poisoning, benzol poisoning, and pernicious anemia when erythrocytes containing basophilic spots are present. Etc. can be assumed. Further, in this case, the doctor or the like can perform further tests such as confirming the blood sample with a microscope.

<Embodiment 3>
In the third embodiment, in the determination process, the presence or absence of at least one of erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles is determined. 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 the third embodiment, as shown in FIG. 18, in the scattergram 400, a region 403 corresponding to an erythrocyte containing an inclusion body of nucleic acid and an extracellular vesicle is provided. Further, the determination process of the third embodiment is configured as shown in FIG. Other configurations of the third embodiment are the same as those of the first embodiment.

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

In the scattergram 400, the leukocytes are generally distributed in a region 401 similar to region 201 of embodiment 1. Malaria non-infected erythrocytes are generally distributed in region 402 similar to region 202 of embodiment 1. Erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles are smaller than leukocytes and have a nucleic acid component inside, and are therefore stained with a fluorescent dye. Therefore, erythrocytes containing inclusion bodies of nucleic acids and extracellular vesicles are generally distributed in region 403. The forward scattered light intensity of region 403 is smaller than that of region 401 corresponding to leukocytes. The fluorescence intensity of region 403 is greater than that of region 402, which corresponds to malaria uninfected erythrocytes, and smaller than that of region 401, which corresponds to leukocytes. Further, as shown in FIGS. 8 (a), 8 (b), 9 (a), (b), 12 (a), 13 (a), and 14 (b), inclusion bodies of nucleic acids. The erythrocytes containing the erythrocytes and extracellular vesicles are distributed so as to overlap the region 204 of Embodiment 1 corresponding to the single ring form erythrocytes. Therefore, the region 403 corresponding to the erythrocytes containing the inclusion bodies of nucleic acids and the extracellular vesicles is set to overlap the above region 204.

Further, since the region 403 may be set to include erythrocytes containing inclusion bodies of nucleic acids distributed in the scattergram 200 and extracellular vesicles, the region 403 is set to be slightly smaller than the region 203 of the first embodiment. ing.

In the third embodiment, in the process of step S102 of FIG. 5A, instead of malaria-infected erythrocytes, single-ring foam erythrocytes, and multi-ring foam erythrocytes, nucleic acids are used based on the fluorescence intensity and scattered light intensity of the measured data. Red blood cells containing inclusion bodies and extracellular vesicles are counted. Specifically, the control unit 51 identifies erythrocytes containing inclusion bodies of nucleic acids and particle swarm G6 included in the range in which extracellular vesicles appear. In the scattergram 400, the extent to which erythrocytes containing nucleic acid inclusions and extracellular vesicles appear corresponds to region 403. Then, the control unit 51 acquires the number of erythrocytes containing the inclusion bodies of nucleic acids and the number of extracellular vesicles by counting the number of the specified particle group G6. The acquisition of the white blood cell count 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 swarms G6 per unit volume is equal to or greater than the threshold value th31. The number of particle swarms G6 per unit volume is, for example, the number of acquired particle swarms G6 divided by the volume of the first measurement sample flowed into the flow cell 101 during the acquisition of the first information. The threshold value th31 is set so that it can be determined that the target blood sample has "no erythrocytes containing nucleic acid inclusion bodies and no extracellular vesicles" based on the number of particle groups G6 per unit volume. The threshold th31 is set to, for example, 200.

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

On the other hand, when the number of the particle group G6 per unit volume is equal to or greater than the threshold value th31, in step S133, the control unit 51 calculates a value indicating the variation in 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. The value indicating the variation of the frequency distribution calculated in step S133 is not limited to the coefficient of variation, but may be the standard deviation or the half width of the frequency distribution map.

In the calculation of the coefficient of variation in step S133, the control unit 51 does not create the frequency distribution map, but calculates the coefficient of variation by data processing according to the same procedure as in the case of creating the frequency distribution map. However, the present invention is not limited to this, and the control unit 51 may create a frequency distribution map and calculate the coefficient of variation. The control unit 51 does not create a frequency distribution map for the purpose of calculating the coefficient of variation, but when displaying the screen described later on the display unit 53a, the control unit 51 creates a frequency distribution map and displays the created frequency distribution map in the display unit. Display on 53a.

In step S133, the control unit 51 replaces the coefficient of variation based on the particle group G6, for example, the fluorescence intensity of the particle group whose fluorescence intensity is included in the range from the minimum value to the maximum value in the horizontal axis direction of the region 403. The coefficient of variation of the frequency distribution with respect to is may be calculated. That is, in step S133, the control unit 51 may calculate the coefficient of variation based on the particle swarm in which the fluorescence intensity included in the measurement data is in a predetermined range.

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 value th32. The threshold value th32 is set so that it can be determined that the target blood sample has "erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles" based on the coefficient of variation. In the horizontal axis direction, the width of the region 403 of the third embodiment is set to be larger than the width of the region 204 corresponding to the single ring foam erythrocytes shown in FIG. 5 (b). Therefore, the threshold value th32 is set to a value larger than the threshold value th13 in step S116 of FIG. The threshold th32 is set to, for example, 20%.

Here, if the blood sample contains malaria-infected erythrocytes, the variation in the frequency distribution based on the particle group G6 becomes small, and if the blood sample does not contain the malaria-infected erythrocytes, the variation in the frequency distribution based on the particle group G6 becomes 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 the erythrocytes containing the inclusion bodies of nucleic acids and the extracellular vesicles.

When the coefficient of variation is the threshold value th32 or more, in step S135, the control unit 51 determines that "there is an erythrocyte containing an inclusion body of nucleic acid or an extracellular vesicle", and stores the determination result in the storage unit 52. Then, the control unit 51 ends the determination process. On the other hand, when 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 inclusions or extracellular vesicles? Scatter abnormality". The determination result is stored in the storage unit 52.

The judgment result of "Are there erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles?" Is likely that the target blood sample contains erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles. It indicates a state in which it is difficult to determine that "there are erythrocytes containing inclusion bodies of nucleic acids or extracellular vesicles". 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 the erythrocytes containing the inclusion bodies of nucleic acids and the extracellular vesicles. Specifically, the "scatter abnormality" is information indicating that the reliability of the determination result regarding the presence or absence of at least one of the erythrocytes containing the inclusion bodies of nucleic acids and the extracellular vesicles is not high. Then, the control unit 51 ends the determination process. If the coefficient of variation is less than the threshold value th32, it is highly possible that malaria-infected erythrocytes are present, and therefore, it may be determined to be “malaria positive”.

In the determination process shown in FIG. 19, when only blood samples containing no malaria-infected erythrocytes are targeted, steps S133, S134, and S136 may be omitted. In this case, if YES is determined in step S131, in step S135, the control unit 51 determines that the target blood sample has “erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles”.

Next, with reference to FIGS. 20 (a) to 21 (d), determinations made specifically for the six types of samples will be described.

20 (a) and 20 (b) are scattergrams 400 based on blood samples collected from a subject suffering from malaria. 20 (c) and 20 (d) are scattergrams 400 based on blood samples collected from subjects not suffering from malaria. 21 (a) and 21 (b) are scattergrams 400 based on blood samples collected from mice not suffering from malaria. In either case, the particles located at the left end of the region 402 are cut as noise components.

In each of the six types of samples shown in FIGS. 20 (a) to 20 (d), 21 (a) and 21 (b), the region 403 corresponding to the erythrocyte containing the inclusion body of nucleic acid and the extracellular vesicle. A predetermined number of particles appear in. The numbers of the particle swarms G6 in FIGS. 20 (a) to 20 (d), 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 coefficient of variation of the frequency distribution with respect to the fluorescence intensity of the particle group G6 is calculated in step S133.

20 (e) to (h), 21 (c), and (d) are created based on the histograms 400 of FIGS. 20 (a) to 20 (d), 21 (a), and 21 (b), respectively. It is a frequency distribution map 500. In the frequency distribution diagram 500, the horizontal axis represents the fluorescence intensity and the vertical axis represents the frequency. The frequency distribution diagram 500 shows a frequency distribution based only on erythrocytes containing inclusion bodies of nucleic acids and particle swarm G6 included in the range in which extracellular vesicles appear. The frequency distribution diagram 500 is normalized based on the value of the maximum frequency.

With reference to the frequency distribution diagrams 500 of FIGS. 20 (e) and 20 (f), the shape of the frequency distribution is a sharp shape in each case. The coefficients of variation in FIGS. 20 (e) and 20 (f) are 16.5% and 8.2%, respectively. Therefore, in both cases of FIGS. 20 (e) and 20 (f), YES was determined in step S134 of FIG. 19, and for these samples, "Are there red blood cells or extracellular vesicles containing nucleic acid inclusion bodies? Scatter abnormality?" Is determined. Here, the samples shown in FIGS. 20 (e) and 20 (f) are all samples infected with malaria, as described above. In addition, with or without malaria-infected erythrocytes, blood samples may have erythrocytes or extracellular vesicles containing nucleic acid inclusions, or neither. Therefore, according to the determination process shown in FIG. 19, it is not the determination result that clarifies the presence or absence of the inclusion bodies of nucleic acids or the presence or absence of extracellular vesicles in these two samples, but "erythrocytes containing inclusion bodies of nucleic acids". , Or there are extracellular vesicles? Scatter abnormality ”can be obtained.

On the other hand, referring to the frequency distribution diagram 500 of FIGS. 20 (g), 20 (h), 21 (c), and (d), the shape of the frequency distribution is not completely sharp in any case. The coefficients of variation of FIGS. 20 (g), 20 (h), 21 (c), and (d) are 26.5%, 22.3%, 30.8%, and 32.0%, respectively. Therefore, in any of FIGS. 20 (g), 20 (h), 21 (c), and (d), NO was determined in step S134 of FIG. , Or there are extracellular vesicles. " Here, the samples shown in FIGS. 20 (g), 20 (h), 21 (c), and (d) are all samples that are not infected with malaria. Therefore, according to the determination process shown in FIG. 19, the appropriate determination result of "there are erythrocytes containing nucleic acid inclusion bodies or extracellular vesicles" without being determined as "malaria positive" for these two samples. It turns out that you can get.

As described above, according to the determination process shown in FIG. 19, when erythrocytes containing inclusion bodies of nucleic acids or extracellular vesicles are present in the blood sample and erythrocytes infected with malaria are not present, the “nucleic acid Appropriate determination of "with erythrocytes containing inclusion bodies or extracellular vesicles" can be performed. In addition, when malaria-infected erythrocytes are present in the blood sample, instead of determining "erythrocytes containing inclusion bodies of nucleic acids or extracellular vesicles", "erythrocytes containing inclusion bodies of nucleic acids or extracellular erythrocytes" are not determined. Appropriate judgment of "Are there vesicles? Scatter abnormality" can be made.

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

Also in the third embodiment, the comment area 63 displays the determination result obtained by the determination process of FIG. Specifically, when step S132 of FIG. 19 is executed, "no erythrocytes containing inclusion bodies of nucleic acids and no extracellular vesicles" is displayed in the comment region 63. When step S136 of FIG. 19 is executed, "Are there red blood cells or extracellular vesicles containing nucleic acid inclusion bodies? Scatter abnormality" is displayed in the comment region 63. In this case, "extracellular vesicles? Red blood cells containing inclusion bodies of nucleic acids? Scatter abnormalities" may be displayed. When step S135 of FIG. 19 is performed, “with erythrocytes containing nucleic acid inclusions or extracellular vesicles” is displayed in the comment region 63, as illustrated in FIG.

In the comment region 63, "Are there erythrocytes or extracellular vesicles containing nucleic acid inclusion bodies?", "There are erythrocytes or extracellular vesicles containing nucleic acid inclusion bodies", "Extracellular vesicles?", "Nucleic acid When "Red blood cells containing inclusion bodies?" Is displayed, doctors and the like can know that the blood sample may contain red blood cells containing inclusion bodies of nucleic acids or extracellular vesicles. Then, as in the second embodiment, the doctor or the like determines the condition of the subject for a predetermined disease that may be related to, for example, erythrocytes containing inclusion bodies of nucleic acids or extracellular vesicles. Can be used as a material. In addition, doctors and the like can also perform further tests such as confirming a blood sample with a microscope.

Further, when "scatter abnormality" is displayed in the comment area 63, doctors and the like indicate that the reliability of the determination result regarding the presence or absence of at least one of the erythrocytes containing the inclusion bodies of nucleic acids and the extracellular vesicles is not high. You can know. In this case, doctors and others may know that erythrocytes containing nucleic acid inclusions and particles other than extracellular vesicles, such as malaria-infected erythrocytes, may be distributed in region 403 of the scattergram 400. it can. Further, by displaying the scattergram 400 and the frequency distribution map 500 on the screen 60, the doctor or the like can quickly and in detail grasp the state of the blood sample.

In embodiments 2 and 3, the presence or absence of extracellular vesicles may be determined instead of determining the presence or absence of at least one of erythrocytes containing nucleic acid inclusions and extracellular vesicles. The presence or absence of erythrocytes containing inclusion bodies of nucleic acids may be determined. In this case, in the second and third embodiments, the comment region 63 may display only the extracellular vesicles among the erythrocytes containing the inclusion bodies of nucleic acids and the extracellular vesicles, and the inclusion bodies of nucleic acids may be displayed. Labeling may be made only for red blood cells containing. Further, in the third embodiment, the counting result of only extracellular vesicles may be displayed in the wrist region 62, or the counting result of only red blood cells containing inclusion bodies of nucleic acids may be displayed.

In embodiments 2 and 3, it was determined whether or not at least one of these two types of particles was contained without distinguishing between extracellular vesicles and erythrocytes containing inclusion bodies of nucleic acids. The presence or absence may be determined by distinguishing the particles. For example, when NO is determined in step S134 of FIG. 19, the presence or absence of extracellular vesicles and inclusion bodies of nucleic acids are further determined according to the value of the coefficient of variation or the distribution angle of the particle group G6 of FIG. The presence or absence of red blood cells containing red blood cells 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 200 Scattergram 203, 204, 205 Region 300 Histogram distribution map 400 Histogram 403 Region 500 Histogram distribution map G3, G4, G5, G6 Histogram

Claims (29)

A sample preparation unit that prepares a measurement sample by mixing a blood sample and a fluorescent dye that stains nucleic acid,
A light receiving unit that receives fluorescence and scattered light generated by irradiating the measurement sample prepared by the sample preparation unit with light, and a light receiving unit.
Based on the value indicating the variation in the distribution of the first particle group included in the range in which the single ring foam erythrocytes appear, which was specified based on the fluorescence intensity and the scattered light intensity obtained by processing the signal from the light receiving portion. A blood analyzer comprising a control unit for determining the presence or absence of Plasmodium infection. The blood analyzer according to claim 1, wherein the control unit specifies the first particle group separately from the second particle group included in the range in which multilingual erythrocytes appear. The blood analyzer according to claim 1 or 2, wherein the value indicating the variation is a value indicating the variation of the frequency distribution with respect to the fluorescence intensity of the first particle group. The blood analyzer according to any one of claims 1 to 3, wherein the value indicating the variation is a coefficient of variation, a standard deviation, or a half width of a frequency distribution map. The blood analyzer according to any one of claims 1 to 4, wherein the sample preparation unit further mixes a diluent for contracting red blood cells to prepare the measurement sample. The control unit determines the presence or absence of infection with Plasmodium based on the value indicating the variation and the number of third particle groups included in the range in which erythrocytes infected with Plasmodium appear. The blood analyzer according to any one of the above. In the control unit, the blood sample is infected with Plasmodium based on the fact that the number of the third particle group is equal to or more than the first threshold value and the value indicating the variation is less than the second threshold value. The blood analyzer according to claim 6. In the control unit, the number of the third particle group is equal to or greater than the first threshold value, the value indicating the variation is less than the second threshold value, and the number of the first particle group is equal to or greater than the third threshold value. The blood analyzer according to claim 6, wherein the blood sample is determined to be infected with Plasmodium based on the above. It also has an output section that outputs information.
The blood analyzer according to any one of claims 1 to 8, wherein the control unit outputs a determination result regarding infection with Plasmodium malaria to the output unit. The blood analyzer according to claim 9, wherein the control unit outputs information indicating the reliability of a determination result regarding infection with Plasmodium malaria to the output unit when the value indicating the variation is equal to or higher than a predetermined threshold value. .. The output unit includes a display unit for displaying information.
The blood analyzer according to claim 10, wherein the control unit displays information indicating the reliability on the display unit together with a determination result regarding infection with Plasmodium malaria. The blood analyzer according to claim 11, wherein the control unit further displays a frequency distribution map of the first particle group with respect to the fluorescence intensity on the display unit. The blood analyzer according to claim 11 or 12, wherein the control unit further displays a scattergram based on the fluorescence intensity and the scattered light intensity on the display unit. A flow cell for flowing the measurement sample prepared by the sample preparation unit, and
A light source for irradiating the measurement sample flowing through the flow cell with the light is provided.
The blood analyzer according to any one of claims 1 to 13, wherein the light receiving unit receives the fluorescence generated from the particles contained in the measurement sample and the scattered light by irradiation with the light. The blood analyzer according to claim 14, wherein the light source emits light in a bluish-purple wavelength band. A group of first particles included in the range in which single ring foam erythrocytes identified based on fluorescence and scattered light generated by irradiating a measurement sample prepared by mixing a blood sample and a fluorescent dye that stains nucleic acid with light appear. A blood analysis method for determining the presence or absence of Plasmodium infection based on a value indicating variation in the distribution of erythrocytes. The blood analysis method according to claim 16, wherein the first particle group is specified separately from the second particle group included in the range in which multilingual erythrocytes appear. Value indicating the variation, the a value indicating the variation of the frequency distribution for the intensity of the fluorescence of the first particle group, the blood analysis method according to claim 16 or 17. The blood analysis method according to any one of claims 16 to 18, wherein the value indicating the variation is a coefficient of variation, a standard deviation, or a half width of a frequency distribution map. The blood analysis method according to any one of claims 16 to 19, wherein the blood sample and the fluorescent dye are further mixed with a diluent for contracting red blood cells to prepare the measurement sample. Any one of claims 16 to 20, which determines the presence or absence of malaria protozoan infection based on the value indicating the variation and the number of third particle groups included in the range in which erythrocytes infected with malaria protozoan appear. The blood analysis method described in. Claim that the blood sample is determined to be infected with Plasmodium based on the number of the third particle group being equal to or greater than the first threshold value and the value indicating the variation being less than the second threshold value. Item 21. The blood analysis method according to item 21. Based on the fact that the number of the third particle group is equal to or greater than the first threshold value, the value indicating the variation is less than the second threshold value, and the number of the first particle group is equal to or greater than the third threshold value. The blood analysis method according to claim 21, wherein the blood sample is determined to be infected with Plasmodium malaria. The blood analysis method according to any one of claims 16 to 23, which displays a determination result regarding infection with Plasmodium malaria. The blood analysis method according to claim 24, wherein when the value indicating the variation is equal to or higher than a predetermined threshold value, information indicating the reliability of the determination result regarding the infection of Plasmodium malaria is displayed. The blood analysis method according to claim 25, wherein the information indicating the reliability is displayed together with the determination result regarding the infection of Plasmodium malaria. Show histogram to the intensity of the fluorescence of the first particle group, the blood analysis method according to claim 26. The blood analysis method according to claim 26 or 27, further displaying a scattergram based on the intensity of the fluorescence and the intensity of the scattered light. The blood analysis method according to any one of claims 16 to 28, wherein the light irradiated to the measurement sample is light in the bluish-purple wavelength band.

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