Particulate sorting device, particulate sorting method, program, and particulate sorting system

Abstract

A particle sorting apparatus includes a determination unit that performs sorting determination of a particle, the determination unit performing the determination using rule data that defines relationships between particles in terms of particle populations to which the particles belong and particle populations to which different particles within a predetermined range around the particle belong, the particle population to which the particle that is a target of the sorting determination and the different particle within the predetermined range can belong including (a) a particle population of particles to be sorted, (b) a particle population of particles that are not sorted but are ignorable in the determination, and (c) a particle population of particles that are neither the particles to be sorted nor the ignorable particles, the ignorable particles including red blood cells.

Description

[0001] Differential citations of relevant applications

[0002] This application claims the benefit of Japanese priority patent application JP2020-120407, filed on July 14, 2020, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to particle sorting apparatus, particle sorting method, procedure and particle sorting system. Background Technology

[0004] Various particle sorting devices have been developed to separate particles. For example, in particle sorting systems used in flow cytometers, a laminar flow comprising a sample solution containing cells and a sheath fluid is discharged from pores formed in a flow cell or microchip. A predetermined vibration is imparted to the laminar flow upon discharge to form droplets. The direction of movement of the formed droplets is electrically controlled by whether the droplets contain target particles, thereby sorting the target particles.

[0005] Unlike the aforementioned technologies, a technique has also been developed for sorting target particles within a microchip without forming droplets. For example, Patent Document 1, described below, discloses "a microchip comprising: a sample liquid introduction flow path through which a sample liquid containing particles flows; at least one pair of sheath fluid introduction flow paths, connecting to the sample liquid introduction flow paths from both sides and introducing sheath fluid around the sample liquid; a merging flow path, communicating with the sample liquid introduction flow path and the sheath fluid introduction flow path, through which liquids flowing through the sample liquid introduction flow path and the sheath fluid introduction flow path merge and flow through the merging flow path; a negative pressure suction unit, communicating with the merging flow path and suctioning the fine particles to be collected; and at least one pair of waste liquid flow paths, disposed on both sides of the negative pressure suction unit and communicating with the merging flow path" (claim 1). In the microchip, target particles are collected into the negative pressure suction unit by suction.

[0006] Reference List

[0007] Patent documents

[0008] Patent Document 1: Japanese Patent Application Publication No. 2012-127922 Summary of the Invention

[0009] Technical issues

[0010] Particle sorting devices typically involve sorting target cells from blood samples. The quantity of blood-derived samples is usually limited, and it is desirable to obtain as many target cells as possible in a single particle sorting process. Furthermore, because there is a possibility that cells other than target cells may affect the operation after sorting (e.g., culture or genetic manipulation), it is desirable to discard cells other than target cells that could affect the operation after sorting, rather than sorting as many cells as possible.

[0011] In this respect, in the particle sorting device described above, sorting can be performed in a configuration to collect only target cells. In such a configuration, for example, if there is a possibility that non-target cells present near the target cell will be collected together when the target cell is collected, the target cell will not be collected and can be discarded. Discarding also increases the proportion of target cells in the collected cell population, but the collection rate tends to be lower.

[0012] Note that, for example, red blood cells in the blood have little effect on the aforementioned operations (e.g., culture or genetic manipulation) after sorting. Therefore, depending on the purpose of sorting, red blood cells can be collected together with target cells. However, in the above setup, because red blood cells are identified as non-target cells, target cells are discarded without collection when red blood cells are present near target cells. Furthermore, the collection rate of target cells is low due to the high proportion of red blood cells and the high frequency of their presence near target cells. Note that although a step called hemolysis to remove red blood cells is also performed, this step has limitations and in some cases cannot completely eliminate red blood cells.

[0013] In view of the above, it is desirable to provide a technique for improving the collection rate of target particles while reducing the impact on the purity of the target particles to be sorted in fine particle sorting.

[0014] Solution to the problem

[0015] The inventors have discovered that the above-mentioned objective can be achieved by a particle sorting device that performs specific sorting processes.

[0016] That is, this disclosure provides:

[0017] A particle sorting device includes: a determining unit for performing particle sorting and determining;

[0018] The determination unit performs the determination using rule data, which defines the relationships between the particles based on the particle population to which the particle being determined as the sorting target belongs and the particle populations to which different particles within a predetermined range around the particle belong.

[0019] The particle groups to which the particles used for sorting and determination of targets, and the different particles within a predetermined range, may belong include the following particle groups:

[0020] (a) The particle population of particles to be sorted.

[0021] (b) A population of particles that were not sorted but were negligible in the determination process, and

[0022] (c) A population of particles that are neither particles to be sorted nor negligible particles.

[0023] Negligible particles include red blood cells.

[0024] The determining unit can change the rule data used in the determining process, and

[0025] At least one rule data point can be defined to determine the availability of a cell:

[0026] Among them, the particle that is the target for sorting belongs to (a) the particle population of the particles to be sorted, and the different particles within a predetermined range around the particle belong to (b) the particle population of negligible particles, and the path of the different particles is the path of the particles to be sorted.

[0027] The particle sorting device may further include a regular data generation unit to generate regular data, and

[0028] The rule data generation unit can generate rule data based on the particles that are the targets for sorting and the particle groups to which different particles within a predetermined range may belong.

[0029] The particle sorting device may further include an input unit that receives a gating operation for setting the particles as the sorting target and the particle groups to which the different particles belong within a predetermined range.

[0030] The determining unit can determine which particle group a particle belongs to based on the light generated by illuminating the particles flowing in the flow path.

[0031] Particle sorting devices can be used to sort blood cells.

[0032] The particle sorting device can be used to selectively sort predetermined T cells from blood cells.

[0033] Rule-based data can be multidimensional.

[0034] Rule-based data can be two-dimensional matrix data.

[0035] The determination unit can perform determination when the particle to be determined as the sorting target and one or more different particles exist within a predetermined range.

[0036] The determining unit can determine the relationship between corresponding particles in a particle group consisting of particles that are the sorting targets, different particles within a predetermined range, and all different particles in the particle group.

[0037] The determination of a unit can be achieved using rule data that defines whether each particle is negligible relative to all distinct particles.

[0038] As a result of determining the relationship, the determining unit may not assign a path to a particle that is determined to be negligible relative to all other particles, and may assign a path to particles other than those determined to be negligible.

[0039] The determination unit can use rule data to determine the path of the particle as the sorting target. The rule data defines the path of the particle as the sorting target based on the assigned path.

[0040] In addition, this disclosure also provides a particle sorting device, comprising:

[0041] The unit is identified, and particle sorting is performed.

[0042] The determining unit performs the determination using rule data, which defines the relationships between the particles based on the particle population to which the particle being determined as the sorting target belongs and the particle populations to which different particles within a predetermined range around the particle belong.

[0043] The particle groups to which the particles used for sorting and determination of targets, and the different particles within a predetermined range, may belong include the following particle groups:

[0044] (a) The particle population of particles to be sorted.

[0045] (b) A population of particles that were not sorted but were negligible in the determination process, and

[0046] (c) A population of particles that are neither particles to be sorted nor negligible particles.

[0047] Furthermore, this disclosure also provides a particle sorting method, comprising:

[0048] The process involves using rule-based data to perform particle sorting, whereby the rule-based data defines the relationships between the particles based on the particle population to which the target particle belongs and the particle populations to which different particles within a predetermined range around the target particle belong.

[0049] The particle groups to which the particles used for sorting and determination of targets, and the different particles within a predetermined range, may belong include the following particle groups:

[0050] (a) The particle population of particles to be sorted.

[0051] (b) A population of particles that were not sorted but were negligible in the determination process, and

[0052] (c) A population of particles that are neither particles to be sorted nor negligible particles.

[0053] Negligible particles, including red blood cells.

[0054] Furthermore, this disclosure also provides

[0055] A procedure for causing a particle sorting device to perform a particle sorting method, the particle sorting method comprising:

[0056] The process involves using rule-based data to perform particle sorting, whereby the rule-based data defines the relationships between the particles based on the particle population to which the target particle belongs and the particle populations to which different particles within a predetermined range around the target particle belong.

[0057] The particle groups to which the particles used for sorting and determination of targets, and the different particles within a predetermined range, may belong include the following particle groups:

[0058] (a) The particle population of particles to be sorted.

[0059] (b) A population of particles that were not sorted but were negligible in the determination process, and

[0060] (c) A population of particles that are neither particles to be sorted nor negligible particles.

[0061] Negligible particles include red blood cells.

[0062] In addition, this disclosure also provides a particle sorting system, including:

[0063] The unit is determined to perform particle sorting and determination; and

[0064] The rule data generation unit generates the rule data used in the sorting determination.

[0065] The determining unit performs the determination using rule data, which defines the relationships between the particles based on the particle population to which the particle being determined as the sorting target belongs and the particle populations to which different particles within a predetermined range around the particle belong.

[0066] The particle groups to which the target particles for sorting and the different particles within a predetermined range may belong include the following particle groups:

[0067] (a) The particle population of particles to be sorted.

[0068] (b) A population of particles that were not sorted but were negligible in the determination process, and

[0069] (c) A population of particles that are neither particles to be sorted nor negligible particles.

[0070] Negligible particles include red blood cells.

[0071] <Advantages of the Invention> Attached Figure Description

[0072] Figure 1 A diagram illustrating an example configuration of the microchip for particle sorting described in this disclosure.

[0073] Figure 2 This is a diagram illustrating an example of a particle sorting process using the particle sorting microchip used in this disclosure.

[0074] Figure 3 This is an enlarged view of an example of a particle sorting unit of a particle sorting microchip used in this disclosure.

[0075] Figure 4 This is a block diagram of the control unit.

[0076] Figure 5A This is an enlarged view of the connecting flow path section.

[0077] Figure 5B This is an enlarged view of the connecting flow path section.

[0078] Figure 6A This is an enlarged view of the connecting flow path section.

[0079] Figure 6B This is an enlarged view of the connecting flow path section.

[0080] Figure 7 This is a diagram showing an example of a gating mechanism.

[0081] Figure 8 This is a diagram illustrating an example of a sorting determination pattern.

[0082] Figure 9 This is a flowchart illustrating an example of the sorting and determination process.

[0083] Figure 10 This is a diagram illustrating an example of the path assignment table and rule data used in the sorting determination process.

[0084] Figure 11 This is a diagram illustrating the rule data used in the sorting determination process and an example of the sorting determination result when the sorting determination process is performed using rule data.

[0085] Figure 12 This is a diagram illustrating the rule data used in the sorting determination process and an example of the sorting determination result when the sorting determination process is performed using rule data.

[0086] Figure 13 This is a diagram illustrating the rule data used in the sorting determination process and an example of the sorting determination result when the sorting determination process is performed using rule data.

[0087] Figure 14 This is a diagram illustrating the rule data used in the sorting determination process and an example of the sorting determination result when the sorting determination process is performed using rule data.

[0088] Figure 15 This is a schematic diagram illustrating an example of a particle sorting apparatus according to an embodiment of the present disclosure.

[0089] Figure 16 This is a diagram showing an example of a gating mechanism.

[0090] Figure 17 This is a diagram illustrating an example of a sorting determination pattern.

[0091] Figure 18A , Figure 18B and Figure 18C This is a diagram illustrating an example of the path assignment table and rule data used in the sorting determination process.

[0092] Figure 19 This is a flowchart illustrating an example of the sorting and determination process.

[0093] Figure 20A , Figure 20B and Figure 20C This is a diagram illustrating an example of the path assignment table and rule data used in the sorting determination process.

[0094] Figure 21 To show the use Figure 20A , Figure 20B and Figure 20C The diagram shows the sorting and determination results when the rule data is processed.

[0095] Figure 22A , Figure 22B and Figure 22C This is a diagram illustrating an example of the path assignment table and rule data used in the sorting determination process.

[0096] Figure 23 This shows the use of Figure 22A , Figure 22B and Figure 22C The diagram shows the sorting and determination results when the rule data is processed.

[0097] Figure 24A , Figure 24B and Figure 24C This is a diagram illustrating an example of the path assignment table and rule data used in the sorting determination process.

[0098] Figure 25 This shows the use of Figure 24A , Figure 24B and Figure 24C The diagram shows the sorting and determination results when the rule data is processed.

[0099] Figure 26A , Figure 26B and Figure 26C This is a diagram illustrating an example of the path assignment table and rule data used in the sorting determination process.

[0100] Figure 27 This shows the use of Figure 26A , Figure 26B and Figure 26C The diagram shows the sorting and determination results when the rule data is processed.

[0101] Figure 28A , Figure 28B and Figure 28C This is a diagram illustrating an example of the path assignment table and rule data used in the sorting determination process.

[0102] Figure 29 This shows the use of Figure 28A , Figure 28B and Figure 28C The diagram shows the sorting and determination results when the rule data is processed. Detailed Implementation

[0103] Suitable embodiments for carrying out this disclosure will be described below. It should be noted that the embodiments described below illustrate typical embodiments of this disclosure, and the scope of this disclosure is not limited to these embodiments. It should be noted that the description of this disclosure will proceed in the following order.

[0104] 1. First Embodiment (Particle Sorting Device)

[0105] (1) Description of the first embodiment

[0106] (2) Example of a closed-type particle sorting device

[0107] (3) Determine the details of the process

[0108] (3-1) Determine the basic concepts of processing

[0109] (3-2) Example of determining the processing flow (emphasizing purity and increasing the collection rate)

[0110] (3-3) Various sorting determination modes are achieved by changing the rule data.

[0111] (3-3-1) Example of sorting treatment to determine the purity of target cells according to priority.

[0112] (3-3-2) Another example of sorting to determine the purity of target cells according to priority.

[0113] (3-3-3) Example of sorting treatment to determine the yield of target cells according to priority.

[0114] (3-3-4) Example of sorting and determination treatment that emphasizes the purity of target cells and increases the collection rate

[0115] (3-3-5) Example

[0116] (4) Example of a particle sorting device configured as a flow cytometer

[0117] (5) Determine the details of the process

[0118] (5-1) Determine the basic concepts of processing

[0119] (5-2) Example of determining the processing flow

[0120] (5-3) Various sorting determination modes are achieved by changing the rule data.

[0121] (5-3-1) Example of sorting and determination treatment that emphasizes the purity of target cells and increases the collection rate

[0122] (5-3-2) Example of sorting and determining the purity of target cells

[0123] (5-3-3) Example of considering narrow-range sorting determination process in sorting determination

[0124] (5-3-4) Example of sorting and determining the collection rate of target cells.

[0125] (5-3-5) Example of a sorting determination process where sorting is determined only when the range considered in the sorting determination includes only one particle.

[0126] 2. Second Implementation Method (Particle Sorting Method)

[0127] 3. Third Implementation Method (Program)

[0128] 4. Fourth Implementation Method (Particle Sorting System)

[0129] 1. First Embodiment (Particle Sorting Device)

[0130] (1) Description of the first embodiment

[0131] The particle sorting apparatus according to a first embodiment of this disclosure includes a determination unit for performing particle sorting determination. The determination unit can perform the determination using rule data that defines a relationship between particles based on the particle group to which the particle being sorted belongs and the particle groups to which different particles within a predetermined range surrounding the particle belong. The particle groups to which the particle being sorted and the different particles within the predetermined range may belong may include the following particle groups:

[0132] (a) The particle population of particles to be sorted.

[0133] (b) A population of particles that were not sorted but were negligible in the determination process, and

[0134] (c) A population of particles that are neither particles to be sorted nor negligible particles.

[0135] Because the particle sorting apparatus according to the first embodiment of this disclosure includes a determination unit that performs particle sorting determination using rule data, it is possible to perform sorting determination to improve the collection rate of particles to be sorted while reducing the impact on the purity of the particles to be sorted.

[0136] In an advantageous embodiment of this disclosure, negligible particles include red blood cells. That is, the particle sorting device is capable of generating rule data that includes red blood cells as negligible particles, and performing particle sorting determination based on the rule data.

[0137] As described above, depending on the object being sorted, red blood cells can be collected together with target cells. By setting the particle population such that negligible particles include red blood cells, the determination unit of the particle sorting device can perform sorting determination to ignore red blood cells. As a result, the collection rate of target cells can be improved while suppressing the impact on subsequent operations such as culture and gene manipulation.

[0138] In this embodiment, the sample being sorted by the particle sorting device is, for example, a sample containing biological particles, specifically, a sample containing cells, and more specifically, a sample containing blood cells. In this embodiment, the particles to be sorted can be, for example, cells, particularly blood cells, more specifically, leukocytes, and even more specifically, at least one selected from the group consisting of T cells, B cells, granulocytes, and monocytes. That is, the particle sorting device according to the first embodiment of this disclosure can be used to sort blood cells, and more specifically, to selectively sort predetermined leukocytes (e.g., T cells) from blood cells.

[0139] In a preferred embodiment of this disclosure, the determining unit can be configured to change the rule data used in the determining process. As a result, the particle sorting apparatus can perform particle sorting processing based on the object. For example, it can perform not only sorting processing that allows target cells and red blood cells to be sorted together, but also sorting processing that does not allow target cells and red blood cells to be sorted together.

[0140] In this embodiment, at least one of the rule data available to the decision unit can be defined as:

[0141] In cases where the particle that is the target for sorting belongs to (a) the particle population of the particle to be sorted, and different particles within a predetermined range around the particle belong to (b) the particle population of negligible particles, for example, the path of the different particles is the path of the particle to be sorted.

[0142] This defined rule-based data allows negligible particles to be collected along with the particles to be sorted. As a result, the collection rate of target cells can be increased while suppressing the impact on subsequent sorting operations.

[0143] In the following description, the configuration and sorting process of the particle sorting apparatus according to the first embodiment of the present disclosure will be described with reference to the accompanying drawings.

[0144] (2) Example of a closed-type particle sorting device

[0145] (2-1) Equipment configuration and sorting operation

[0146] The particle sorting apparatus according to the first embodiment of this disclosure can be configured as an apparatus for sorting particles in an enclosed space. For example, the particle sorting apparatus can be configured as an apparatus for sorting particles by controlling the flow path through which the particles travel. Figure 1 An example configuration of a particle sorting apparatus according to a first embodiment of the present invention is shown. Figure 1 An example of the flow path structure of a chip included in the device is also shown. Figure 2 An example flowchart of a sorting operation performed by a particle sorting device is shown.

[0147] Figure 1 The particle sorting device 100 shown includes a light irradiation unit 101, a detection unit 102, a control unit 103, and a particle sorting microchip 150. For example... Figure 4 As shown, the control unit 103 may include a signal processing unit 104, a determination unit 105, and a sorting control unit 106.

[0148] In the following text, the particle sorting microchip 150 will be described first, and then another component of the particle sorting device 100 will be described while describing the sorting operation performed by the particle sorting device 100.

[0149] Figure 1 The particle sorting microchip 150 shown includes a sample liquid flow path 152 and a sheath fluid flow path 154 that merges with the sample liquid flow path 152 at a merging section 162. The particle sorting microchip 150 is further provided with a sample liquid inlet 151 and a sheath fluid inlet 153.

[0150] It should be noted that, Figure 1 In the diagram, a portion of the sheath fluid flow path 154 is represented by a dashed line. This dashed portion is located lower than the sample fluid flow path 152, represented by a solid line (a position shifted in the direction of the optical axis indicated by the arrow), and the sheath fluid flow path 154 and the sample fluid flow path 152 are not connected to each other at the intersection of the flow paths represented by the dashed lines and the solid lines. Furthermore, in... Figure 1 In the diagram, the sample liquid flow path 152 is shown to bend twice between the sample liquid inlet 151 and the merging section 162 to facilitate the distinction between the sample-flow path 152 and the sheath-flow path 154. The sample liquid flow path 152 can be arranged linearly between the sample liquid inlet 151 and the merging section 162 in this manner without bending.

[0151] In the particle sorting operation, the sample liquid containing particles is introduced into the sample liquid flow path 152 from the sample liquid inlet 151, and the sheath liquid not containing particles is introduced into the sheath liquid flow path 154 from the sheath liquid inlet 153.

[0152] The particle sorting microchip 150 includes a merging flow path 155, which includes a merging section 162 at one end. The merging flow path 155 includes a sorting determination unit 156 for performing particle sorting determination.

[0153] The sample liquid and sheath liquid merge at the merging section 162 and flow toward the particle sorting unit 157 in the merging flow path 155. Specifically, the sample liquid and sheath liquid merge at the merging section 162 to form a laminar flow, wherein, for example, the periphery of the sample liquid is surrounded by the sheath liquid. Advantageously, the fine particles are substantially aligned in the laminar flow. By including the sample-flow path 152 merged at the merging section 162 and two sheath liquid flow paths 154, and the merging flow path 155 having the merging section 162 as one end, a laminar flow containing substantially aligned and flowing fine particles is formed. This makes it easier to distinguish, in the sorting determination unit (also referred to as the detection area) 156 described below, the light generated by light irradiating one particle in light irradiation and the light generated by light irradiating another particle in light irradiation.

[0154] The particle sorting microchip 150 further includes a particle sorting unit 157 at the other end of the merged flow path 155. Figure 3 An enlarged view of the particle sorting unit 157 is shown. (See attached image.) Figure 3As shown in Figure A, the merging flow path 155 is connected at one end to the particle collection flow path 159 via the connecting flow path 170. Figure 3 As shown in Figure A, the merging flow path 155, the connecting flow path 170, and the fine particle collection flow path 159 can be coaxial.

[0155] When the particles to be collected flow into the particle sorting unit 157, such as Figure 3 As shown in Figure B, a flow is formed from the merging flow path 155 through the connecting flow path 170 into the particle collection flow path 159, and the particles to be collected (also referred to as "particles to be sorted" in this specification) are collected into the particle collection flow path 159. In this way, the particles to be collected flow through the connecting flow path 170 to the fine particle collection flow path 159.

[0156] If particles that are not to be collected flow into the particle sorting unit 157, they flow into the branch flow path 158, such as... Figure 3 As shown in C. In this case, no flow is formed into the particle collection flow path 159.

[0157] like Figure 1 As shown, the particle collection flow path 159 is formed to extend linearly from the particle sorting unit 157, make a U-shaped turn, and reach the same plane as the plane on which the sample liquid inlet 151 and the sheath liquid inlet 153 are formed. The liquid flowing through the particle collection flow path 159 is discharged from the end of the collection flow path 163 to the outside of the chip.

[0158] like Figure 1 As shown, the two branch flow paths 158 are also formed to extend linearly from the particle sorting unit 157, make a U-shaped turn, and reach the same plane as the plane where the sample liquid inlet 151 and the sheath liquid inlet 153 are formed. The liquid flowing in the branch flow path 158 is discharged from the branch flow path end 166 to the outside of the chip.

[0159] exist Figure 1 In the diagram, the display method of the particle collection flow path 159 is changed to solid and dashed lines in the U-shaped section. This change indicates that the position in the optical axis direction changes along the way. By changing the position in the optical axis direction in this way, the particle collection flow path 159 and the branch flow path 158 are not connected to each other at the portion where they intersect.

[0160] The collection flow path end 163 and the two branch flow path ends 166 are both formed on a plane on which the sample liquid inlet 151 and the sheath liquid inlet 153 are formed. Furthermore, the introduction flow path inlet 164 for introducing liquid into the introduction flow path 161 described below is also formed on the plane. As described above, all inlets for liquid introduction and all outlets for liquid discharge are formed on one surface of the particle sorting microchip 150. This facilitates attaching the chip to the particle sorting device 100. For example, the connection between the flow paths provided in the particle sorting device 100 and the flow paths of the particle sorting microchip 150 is easier compared to a case where the inlets and / or outlets are formed on more than two planes.

[0161] like Figure 1 and Figure 3 As shown, the microparticle sorting microchip 150 includes an inlet flow path 161 for introducing liquid into the connection flow path 170.

[0162] By introducing liquid from the inlet flow path 161 into the connecting flow path 170, the interior of the connecting flow path 170 is filled with liquid. As a result, non-target fine particles can be prevented from entering the fine particle collection flow path 159.

[0163] The particle sorting microchip 150 includes two branch flow paths 158 connected to the other end of the merging flow path 155. As described above, in the particle sorting microchip used in this disclosure, the merging flow path can be branched into a connecting flow path and at least one branch flow path.

[0164] Fine particles other than the particles to be collected flow into one of the two branch flow paths 158 without entering the fine particle collection flow path 159.

[0165] like Figure 2 As shown, the particle sorting operation using the particle sorting microchip 150 includes: a flow step S1 in which liquid containing particles flows into a merging flow path 155; a determination step S2 in which it is determined whether the particles flowing through the merging flow path 155 are particles to be collected; and a collection step S3 in which the particles to be collected are collected into the particle collection flow path 159.

[0166] Each step will be described below.

[0167] (2-2) Flow steps

[0168] In the flow step S1, a sample liquid containing fine particles and a sheath liquid without fine particles are introduced into the sample liquid flow path 152 and the sheath liquid flow path 154 from the sample liquid inlet 151 and the sheath liquid inlet 153, respectively.

[0169] The sample liquid and sheath liquid merge at the merging section 162 to form a laminar flow, wherein, for example, the outer periphery of the sample liquid is surrounded by the sheath liquid. Advantageously, the fine particles are substantially aligned in the laminar flow. That is, in the flow step S1, a laminar flow containing substantially aligned and flowing fine particles can be formed.

[0170] In this way, in the flow step S1, the liquid containing fine particles flows through the merging flow path 155 as a laminar flow. The liquid flows from the merging section 162 toward the particle sorting unit 157 in the merging flow path 155.

[0171] (2-3) Determine the steps

[0172] In determination step S2, it is determined whether the fine particles flowing in the merging flow path 155 are particles to be collected. This determination can be made by determination unit 105. Determination unit 105 can make the determination based on the light generated by irradiating light into particles through light irradiation unit 101. An example of determination step S2 will be described in more detail below.

[0173] In the determination step S2, the light irradiation unit 101 irradiates the particles flowing through the merging flow path 155 (specifically, the sorting determination unit 156) in the particle sorting microchip 150 with light (e.g., excitation light), and the detection unit 102 detects the light generated by the light irradiation. The determination unit 105 determines whether the fine particles are to be collected based on the characteristics of the light detected by the detection unit 102. For example, the determination unit 105 may make the determination based on scattered light, fluorescence, or an image (e.g., a dark-field image and / or a bright-field image). In the collection step S3 described below, the control unit 103 controls the flow in the particle sorting microchip 150, so that the particles to be collected are collected in the particle collection flow path 159.

[0174] The light illumination unit 101 uses light (e.g., excitation light) to illuminate particles flowing in a flow path within the particle sorting microchip 150. The light illumination unit 101 may include a light source that emits light and an objective lens that focuses the excitation light onto the fine particles flowing through the sorting unit. The light source can be selected by those skilled in the art for the analytical purpose and may be, for example, a laser diode, an SHG laser, a solid-state laser, a gas laser, a high-intensity LED, or a halogen lamp, or a combination of two or more of these. In addition to the light source and objective lens, the light illumination unit may include other optical elements as needed.

[0175] In one embodiment of this disclosure, detection unit 102 detects scattered light and / or fluorescence generated from particles by light irradiation from light irradiation unit 101. Detection unit 102 may include a condenser lens and a detector, the condenser lens collecting the fluorescence and / or scattered light generated from the particles. Such a detector may include, but is not limited to, a PMT, photodiode, CCD, and CMOS. Detection unit 102 may include other optical elements besides the condenser lens and detector as needed. Detection unit 102 may further include, for example, a beam splitter. Examples of optical components constituting a beam splitter include gratings, prisms, and optical filters. For example, the beam splitter allows light of a wavelength to be detected to be detected separately from other wavelengths. Detection unit 102 may convert the detected light into an analog electrical signal via photoelectric conversion. Detection unit 102 may also convert the analog electrical signal into a digital electrical signal via A / D conversion.

[0176] In other embodiments of this disclosure, the detection unit 102 may acquire an image generated by light illumination from the light illumination unit 101. For example, the image may be a dark-field image, a bright-field image, or both. In this embodiment, the light illumination unit 101 may include, for example, a halogen lamp or a laser, and the detection unit 102 may include a CCD or CMOS. The detection unit 102 may be, for example, an image sensor, wherein a substrate incorporating a CMOS sensor and a substrate incorporating a digital signal processor (DSP) are stacked. By operating the DSP of the image sensor as a machine learning unit, the image sensor can operate as a so-called AI sensor. The detection unit 102 including the image sensor may determine whether a fine particle is a particle to be collected based on, for example, a learning model. Furthermore, the learning model may be updated in real time while performing the method according to the first embodiment of this disclosure. For example, the DSP may perform machine learning processing during the reset of the pixel array units in the CMOS sensor, during the exposure of the pixel array units, or during the reading of pixel signals from individual unit pixels of the pixel array units. Examples of image sensors operating as AI sensors may include the imaging apparatus disclosed in WO 2018 / 051809.

[0177] The signal processing unit 104, included in the control unit 103, can process the waveform of the digital electrical signal obtained by the detection unit 102 to generate information (data) regarding the characteristics of the light determined by the determination unit 105. As information about the characteristics of the light, the signal processing unit 104 can obtain, for example, one, two, or three of the waveform's width, height, and area from the waveform of the digital electrical signal. Furthermore, the information about the characteristics of the light can include, for example, the time when the light has been detected. Specifically, in embodiments that detect scattered light and / or fluorescence, the above-described processing performed by the signal processing unit 104 can be executed.

[0178] The determination unit 105 included in the control unit 103 determines whether a particle is a particle to be collected based on light generated by illuminating the particles flowing in the flow path.

[0179] In embodiments that detect scattered light and / or fluorescence, the control unit 103 processes the waveform of the digital electrical signal obtained by the detection unit 102, and the determination unit 105 determines whether a particle is a particle to be collected based on information related to the characteristics of the light generated by the processing. For example, in a determination based on scattered light, characteristics of the particle's external shape and / or internal structure can be specified, and whether a particle is a particle to be collected can be determined based on these characteristics. Furthermore, by pre-treating fine particles such as cells, it is possible to determine whether fine particles are particles to be collected based on characteristics similar to those used in flow cytometry. Additionally, it is possible to label fine particles such as cells with antibodies or dyes (especially fluorescent dyes) to determine whether fine particles are particles to be collected based on the characteristics of the surface antigens of the fine particles.

[0180] In the implementation of image acquisition, a determination unit 105 included in the control unit 103 determines whether fine particles are particles to be collected based on the acquired image (e.g., a dark-field image, a bright-field image, or both). For example, whether fine particles are particles to be collected can be determined based on one or more combinations of the form, size, and color of the fine particles (specifically, cells).

[0181] For example, the determination can be based on whether predetermined conditions are met based on information about the properties of the light. These conditions can be those indicating that the fine particles are particles to be collected. The conditions can be appropriately set by someone skilled in the art and can be conditions relating to the properties of the light, such as those used in the field of flow cytometry.

[0182] A single light beam can be applied to one location in the sorting determination unit 156, or the light beam can be applied to multiple locations in the sorting determination unit 156. For example, the microchip 150 can be configured to apply the light beam to each of two different locations in the sorting determination unit 156 (i.e., there are two locations in the sorting determination unit 156 to which light is applied). In this case, for example, it can be determined whether a fine particle is to be collected based on the light (e.g., fluorescence and / or scattered light) generated by illuminating the fine particle at one location. Furthermore, the velocity of the fine particles in the flow path can be calculated based on the difference between the time when the light generated by illuminating the fine particle at one location has been detected and the time when the light generated by illuminating the fine particle at another location has been detected. For calculation, the distance between the two illuminating locations can be predetermined, and the velocity of the particle can be determined based on the difference between the two detection times and the distance. Furthermore, the arrival time to the particle sorting unit 157 described below can be accurately predicted based on the velocity. By accurately predicting the arrival time, the timing of forming the flow into the particle collection flow path 159 can be optimized. Furthermore, if the difference between the time when a specific particle arrives at the particle sorting unit 157 and the time when a particle in front of or behind the specific particle arrives at the particle sorting unit 157 is equal to or less than a predetermined threshold, it can be determined that the specific particle will not be collected. When the distance between the specific particle and the particles in front of or behind the specific particle is small, the possibility of collecting the particles in front of or behind the specific particle together during the absorption of the specific particle increases. By determining that the specific particle will not be collected when the particles in front of or behind the specific particle may be collected together, the collection of particles in front of or behind the specific particle can be prevented. As a result, the purity of the target particle among the collected particles can be increased. For example, Japanese Patent Application Publication No. 2014-202573 discloses a microchip in which a light beam is applied to each of two different positions in the sorting determination unit 156 and a specific example of a device including the microchip.

[0183] Note that the control unit 103 can control the light irradiation of the light irradiation unit 101 and / or the light detection of the detection unit 102. Furthermore, the control unit 103 can control the drive of the pump used to supply liquid to the particle sorting microchip 150. For example, the control unit 103 may include a hard disk, an OS, a CPU, and a memory storing a program for causing the particle sorting device 100 to execute the particle sorting method according to the first embodiment of the present invention. For example, the functions of the control unit 103 can be implemented in a general-purpose computer. The program can be recorded on a recording medium such as a micro SD memory card, an SD memory card, or flash memory. The program recorded on the recording medium can be read by a drive (not shown) provided in the particle sorting device 100, and the control unit 103 can cause the particle sorting device 100 to execute the particle sorting method according to the first embodiment of the present disclosure based on the read program.

[0184] (2-4) Collection steps

[0185] In collection step S3, particles identified as to be collected in determination step S2 are collected into particle collection flow path 159. Collection step S3 is performed in particle sorting unit 157 within microchip 150. In particle sorting unit 157, the laminar flow passing through merging flow path 155 flows into two branch flow paths 158 respectively. Although Figure 1 The particle sorting unit 157 shown includes two branch flow paths 158, but the number of branch flow paths is not limited to two. For example, the particle sorting unit 157 may be provided with one or more (e.g., 2, 3, or 4) branch flow paths. The branch flow paths can be configured as follows: Figure 1 It can branch in a Y-shape on a plane, as in the example, or it can be configured to branch in three dimensions.

[0186] Figure 5A and Figure 5B An enlarged view of the vicinity of the connecting flow path 170 is shown. Figure 5A This is a schematic 3D view of the area near the connecting flow path 170. Figure 5B This is a schematic cross-sectional view in a plane passing through the centerline of the inlet flow path 161 and the centerline of the connecting flow path 170. The connecting flow path 170 includes a flow path 170a on the side of the sorting and determining unit 156 (hereinafter also referred to as the upstream connecting flow path 170a), a flow path 170b on the side of the particle collection flow path 159 (hereinafter also referred to as the downstream connecting flow path 170b), and a junction point 170c between the connecting flow path 170 and the inlet flow path 161. The inlet flow path 161 is configured to be substantially perpendicular to the axis of the flow path of the connecting flow path 170. Figure 5A and Figure 5B In this configuration, the two inlet flow paths 161 are positioned facing each other at approximately the center of the connecting flow path 170, but only one inlet flow path may be configured.

[0187] The shape and dimensions of the cross-section of the upstream connecting flow path 170a can be the same as the shape and dimensions of the downstream connecting flow path 170b. For example, as Figure 5A and 5B As shown, the cross-sections of the upstream connecting flow path 170a and the downstream connecting flow path 170b can also be approximately circular with the same dimensions. Alternatively, both transverse cross-sections can be rectangular (e.g., square or rectangular) with the same dimensions.

[0188] Liquid is supplied from two inlet flow paths 161 to the connecting flow path 170, such as Figure 5B As indicated by the arrows, liquid flows from connection point 170c to both upstream connection flow path 170a and downstream connection flow path 170b.

[0189] Without performing the collection step, the liquid flow is as follows.

[0190] Liquid flowing into the upstream connecting flow path 170a exits from the connecting surface of the connecting flow path 170 together with the merging flow path 155, and then flows into the two branch flow paths 158 respectively. Since the liquid leaves the connecting surface as described above, liquid and particles that do not need to be collected into the particle collection flow path 159 can be prevented from entering the particle collection flow path 159 through the connecting flow path 170.

[0191] Liquid flowing into downstream connecting flow path 170b flows into particle collection flow path 159. As a result, the interior of particle collection flow path 159 is filled with liquid.

[0192] Even when performing the collection step, liquid can be supplied from both inlet flow paths 161 to the connecting flow path 170. However, due to pressure fluctuations in the particle collection flow path 159, particularly by generating negative pressure in the particle collection flow path 159, a flow forms from the merging flow path 155 through the connecting flow path 170 to the particle collection flow path 159. That is, a flow forms sequentially from the merging flow path 155 to the particle collection flow path 159 through the upstream connecting flow path 170a, the node 170c, and the downstream connecting flow path 170b. In this way, the particles to be collected are collected in the fine particle collection flow path 159.

[0193] The cross-sectional shape and / or size of the upstream connecting flow path 170a may also be different from the shape and / or size of the downstream connecting flow path 170b. Figure 6A and Figure 6B The image shows an example where the two flow paths have different dimensions. For example... Figure 6A and Figure 6B As shown, the connecting flow path 180 includes a flow path 180a on the side of the sorting and determining unit 156 (hereinafter also referred to as the upstream connecting flow path 180a), a flow path 180b on the side of the particle collection flow path 159 (hereinafter also referred to as the downstream connecting flow path 180b), and a junction point 180c between the connecting flow path 180 and the inlet flow path 161. The cross-sections of both the upstream connecting flow path 180a and the downstream connecting flow path 180b are approximately circular, but the diameter of the latter's cross-section is larger than that of the former. By making the diameter of the latter's cross-section larger than that of the former, compared to the case where both diameters are the same, it is more effective to prevent the discharge of particles sorted into the particle collection flow path 159 into the merging flow path 155 immediately after the particle sorting operation under negative pressure via the connecting flow path 180.

[0194] For example, if both the cross-section of the upstream connecting flow path 180a and the cross-section of the downstream connecting flow path 180b are rectangular, the area of ​​the latter's cross-section can be made larger than the area of ​​the former's cross-section to more effectively prevent the collected fine particles from being discharged into the merging flow path 155 through the connecting flow path 180, as described above.

[0195] In collection step S3, due to pressure fluctuations in the particle collection flow path 159, the particles to be collected are collected into the particle collection flow path via the connecting flow path. Collection can be performed, for example, by generating a negative pressure in the particle collection flow path 159 as described above. For example, a negative pressure can be generated by deforming the wall defining the particle collection flow path 159 by an actuator 107 (specifically, a piezoelectric actuator) attached to the outside of the microchip 150. The negative pressure can form a flow into the particle collection flow path 159. To generate a negative pressure, for example, the actuator 107 can be attached to the outside of the microchip 150 so that the wall of the particle collection flow path 159 can be deformed. Due to the deformation of the wall, the internal space of the particle collection flow path 159 can be changed, and a negative pressure can be generated. The actuator 107 can be, for example, a piezoelectric actuator. When the particles to be collected are drawn into the particle collection flow path 159, a laminar sample liquid or a laminar sample liquid and sheath liquid can also flow into the particle collection flow path 159. In this way, the particles to be collected are sorted in the particle sorting unit 157 and collected in the particle collection flow path 159.

[0196] To prevent particles that are not intended for collection from entering the particle collection flow path 159 through the connecting flow path 170, the connecting flow path 170 is provided with an inlet flow path 161. Liquid is introduced into the connecting flow path 170 through the inlet flow path 161. By introducing liquid, the connecting flow path 170 is filled with liquid. Furthermore, by forming a flow from the connecting flow path 170 toward the merging flow path 155 by a portion of the liquid, fine particles other than those intended for collection are prevented from entering the fine particle collection flow path 159. Due to the flow of liquid flowing through the merging flow path 155 into the branch flow path 158, the liquid forming a flow from the connecting flow path 170 toward the merging flow path 155 flows through the branch flow path 158, similar to the liquid that does not flow through the merging flow path 155.

[0197] It should be noted that the remaining portion of the liquid introduced into the connecting flow path 170 flows to the particle collection flow path 159. Therefore, the particle collection flow path 159 may be filled with liquid.

[0198] The flow entering branch flow path 158 can be discharged to the outside of the microchip at branch flow path end 160. Furthermore, particles already collected in particle collection flow path 159 can be discharged to the outside of the microchip at collection flow path end 163. A container can be connected to collection flow path end 163 via a flow path such as a tube. Particles to be collected can be collected in the container.

[0199] like Figure 1 and Figure 3 As shown, in the particle sorting microchip used in the first embodiment of this disclosure, the merging flow path, connecting flow path, and collecting flow path can be linearly aligned. With these three flow paths linearly aligned (particularly coaxial), the collecting step can be performed more efficiently compared to, for example, when the connecting flow path and collecting flow path are arranged at an angle relative to the merging flow path. For example, the suction volume required to guide the particles to be collected to the connecting flow path can be reduced.

[0200] Furthermore, in the particle sorting microchip used in the first embodiment of this disclosure, the particles are substantially arranged in the merging flow path and flow towards the connecting flow path. Therefore, the suction volume in the collection step can also be reduced.

[0201] As described above, in the particle sorting microchip used in the first embodiment of this disclosure, liquid is supplied from the inlet flow path to the connecting flow path. As a result, a flow is formed in the connecting flow path from the connection point between the inlet flow path and the connecting flow path toward the merging flow path, preventing liquid flowing through the merging flow path from entering the connecting flow path, and preventing fine particles other than the particles to be collected from flowing into the collection flow path through the connecting flow path. When the collection step is performed, as described above, for example, the particles to be collected are collected into the collection flow path through the connecting flow path by a negative pressure generated in the collection flow path.

[0202] (2-5) Particle sorting: microchips and particles

[0203] In this disclosure, “micro” means that at least a portion of the flow path contained in the microparticle sorting microchip has a size on the order of μm, specifically, a cross-sectional size on the order of μm.

[0204] That is, in this disclosure, "microchip" refers to a chip that includes flow paths on the order of μm, specifically, a chip that includes flow paths with cross-sectional dimensions on the order of μm. For example, a chip including a particle sorting unit may be referred to as a microchip according to the first embodiment of this disclosure, the particle sorting unit including flow paths with cross-sectional dimensions on the order of μm. For example, in particle sorting unit 157, the cross-section of merging flow path 155 is, for example, rectangular, and the width of merging flow path 155 in particle sorting unit 157 may be, for example, from 100 μm to 500 μm, specifically, from 100 μm to 300 μm. The width of branch flow paths branching from merging flow path 155 may be smaller than the width of merging flow path 155. The cross-section of connecting flow path 170 may be, for example, circular, and the diameter of the junction of connecting flow path 170 and merging flow path 155 may be, for example, from 10 μm to 60 μm, specifically, from 20 μm to 50 μm. These dimensions of the flow path can be appropriately varied according to the size of the fine particles, especially the size of the particles to be collected.

[0205] The microparticle sorting microchip 150 can be manufactured by methods known in the art. For example, the biological microparticle sorting microchip 150 can be manufactured by bonding two or more substrates having predetermined flow paths formed therein. For example, the flow paths can be formed on all or more substrates (specifically, both substrates), or they can be formed on only some of the two or more substrates (specifically, one of the two substrates). To facilitate positioning when bonding the substrates together, it is preferable to form the flow paths on only one substrate. For example, as... Figure 1 As shown by the dashed and solid lines in the figure, by stacking three or more substrates with flow paths, a flow path structure can be manufactured in which two flow paths are configured to intersect each other at different locations in the optical axis direction (and thus not communicate with each other) and when viewed from the optical axis direction.

[0206] Materials known in this art can be used as materials for forming the microparticle sorting microchip 150. Examples of materials include, but are not limited to, polycarbonate, cyclic olefin polymers, polypropylene, PDMS (polydimethylsiloxane), polymethyl methacrylate (PMMA), polyethylene, polystyrene, glass, and silicon. In particular, polymeric materials such as polycarbonate, cyclic olefin polymers, and polypropylene are especially advantageous because they have excellent processability and the ability to inexpensively produce microchips using molding equipment.

[0207] The particle sorting microchip 150 is preferably transparent. For example, the particle sorting microchip 150 may be transparent at least in the portion through which light (laser and scattered light) passes. For example, the sorting determination unit may be transparent. The entire particle sorting microchip 150 may be transparent.

[0208] It should be noted that although the embodiment in which the flow path assembly is formed in a disposable particle sorting microchip 150 has been described above, in this disclosure, the flow path assembly does not necessarily need to be formed in the microchip 150. For example, the flow path assembly can be formed in a substrate such as plastic or glass. Furthermore, the flow path assembly can have a two-dimensional or three-dimensional structure.

[0209] In this disclosure, the microparticles can be microparticles having a size capable of flowing in the flow paths of a microparticle sorting chip. In this disclosure, those skilled in the art can appropriately select fine microparticles. In this disclosure, fine microparticles can include biological microparticles such as cells, cell clusters, microorganisms, and liposomes, as well as synthetic microparticles such as gel microparticles, beads, latex microparticles, polymer microparticles, and industrial microparticles.

[0210] Biological microparticles (also known as bioparticles) can include chromosomes, liposomes, mitochondria, organelles, etc., that make up various cells. Cells can include animal cells (such as hematopoietic cells) and plant cells. In particular, cells can be blood cells or tissue cells. Blood cells can be, for example, floating cells such as T cells and B cells. Tissue cells can be, for example, cultured adhesive cells or adhesive cells isolated from tissues. Cellular material can include, for example, spheroids and organoids. Microorganisms can include bacteria such as Escherichia coli, viruses such as tobacco mosaic virus, and fungi such as yeast. In addition, biological microparticles can also include biological macromolecules, such as nucleic acids, proteins, and their complexes. These biological macromolecules can be, for example, those extracted from cells or those contained in blood samples or other liquid samples.

[0211] The synthetic microparticles can be, for example, microparticles formed from organic or inorganic polymeric materials or metals. Organic polymeric materials can include polystyrene, divinyl styrene, and polymethyl methacrylate. Inorganic polymeric materials can include glass, silica, and magnetic materials. Metals can include colloidal gold, aluminum, etc. The synthetic microparticles can be, for example, gel microparticles or beads, and more specifically, gel microparticles or beads having one or more combinations selected from oligonucleotides, peptides, proteins, and enzymes bound thereto. The shape of the microparticles can be spherical or substantially spherical, or can be non-spherical. Those skilled in the art can appropriately select the size and mass of the microparticles according to the flow path dimensions of the microchip. Simultaneously, the flow path dimensions of the microchip can also be appropriately selected according to the size and mass of the microparticles. In this disclosure, chemical or biological markers, such as fluorescent dyes or fluorescent proteins, can be appropriately attached to the microparticles. This labeling can make the microparticles easier to detect. Those skilled in the art can appropriately select the tags to be attached. Molecules that specifically react with the microparticles (e.g., antibodies, aptamers, DNA, or RNA) can bind to the label.

[0212] According to one embodiment of this disclosure, the fine particles can be biological particles, specifically, cells.

[0213] (3) Determine the details of the process

[0214] (3-1) Determine the basic concepts of processing

[0215] In collection step S3, the particle sorting device 100 generates a negative pressure in, for example, the particle collection flow path 159 when collecting the particles to be collected as described above, and thus, a flow is formed from the confluence flow path 155 through the connecting flow path 170 to the particle collection flow path 159. Therefore, along with the particles to be collected, the fluid (specifically, liquid) within a predetermined range around the particles to be collected is collected into the fine particle collection flow path 159. When different particles are present within a predetermined range (more specifically, within a predetermined range in front of and behind the direction of travel of the particles to be collected), these different particles are also collected into the fine particle collection flow path 159 when the particles to be collected are collected. Therefore, in cases where different particles are particles that should not be collected, the determining unit 105 determines that the particles to be collected will not be collected, thereby increasing the purity of the particles to be collected among the collected particles.

[0216] In the determination step S2, the determination unit 105 can determine whether different particles exist within a predetermined range based on the time at which light generated by light illuminating the particle that is the sorting target has been detected and the time at which light generated by light illuminating different particles flowing in front of or behind the particle has been detected. For example, as described in (2-3), the velocities of these particles in the merging flow path 155 can be specified. Therefore, for example, the determination unit 105 can determine whether different particles exist within the predetermined range based on the difference between a previous time and a subsequent time. More specifically, the determination unit 105 can determine whether different particles exist within the predetermined range based on whether the difference is equal to or less than a predetermined value. In other words, the predetermined range can be a range specified based on a predetermined value related to the time difference.

[0217] Predefined values ​​can be specified in advance. For example, in the case of generating a negative pressure, the predetermined values ​​can be specified by specifying how far different particles should be kept away from the particles that are the target particles for sorting, so as not to be collected in the fine particle collection flow path 159.

[0218] Note that in this specification, the predetermined value is also referred to as "Guard Time". Furthermore, since a predetermined range can be specified based on the predetermined value as described above, the term "Guard Time" can also be used to mean a predetermined range in this specification.

[0219] As described above, the determining unit 105 can determine whether to collect a specific particle based on the presence of different particles within a predetermined range around the particle that is the target for sorting and / or based on the type of different particles. Then, if different particles are present within the predetermined range, the determining unit 105 determines that the particle that is the target for sorting will not be sorted, and therefore, the purity of the target particle among the collected particles as described above can be increased. Simultaneously, if the post-sorting processing is not affected by red blood cells, although red blood cells are allowed to be collected along with the target particles, the target particles are not collected, resulting in a reduced collection rate of the target particles. In this respect, if different particles are allowed to be collected within a predetermined range around the target particles, the collection rate of the target particles can be increased when they can be sorted, which can be advantageous depending on the type or purpose of the post-sorting processing.

[0220] In the following text, the methods for increasing purity and increasing collection rate described above will be used as examples of sorting specific white blood cells from blood.

[0221] First, to sort blood cells 100 times using a particle sorting device, a sample is prepared and gated. Sample preparation can be performed using methods known in the art, such as flow cytometry, and those skilled in the art can appropriately select the sample preparation method. For example, for sample preparation, the blood can be hemolyzed. Hemolysis results in the lysis of red blood cells in the blood. Hemolysis can be performed using hemolytic agents known to those skilled in the art.

[0222] In some cases, attempts to hemolyze all red blood cells also affect white blood cells. Therefore, hemolysis can be terminated before all red blood cells are hemolyzed. That is, unhemolyzed red blood cells may be present in a blood sample obtained through hemolysis.

[0223] A portion of the blood sample prepared by the hemolysis treatment described above is used for gating. Those skilled in the art can appropriately configure the gating to make it possible to sort target cells (e.g., T cells). For gating, scattered light and fluorescence generated by irradiating the cells in the sample can be used.

[0224] The following will refer to Figure 7 Describe an example of gating. This example demonstrates gating to selectively collect cytotoxic T cells and helper T cells from a blood sample.

[0225] As described in (2) above, the blood sample is fed into the microparticle sorting chip 150 of the microparticle sorting device 100, and the light generated in each microparticle in the blood sample by the light irradiation unit 101 and the detection unit 102 is detected.

[0226] For example, such as Figure 7 As shown in Figure A, two-dimensional plots (dot plots) of forward scattered light (FSC) and side scattered light (SSC) are generated using data related to the detection light. For the generated two-dimensional plots, gates R1 and R5 are set. Gate R1 is the gate for lymphocytes and gate R5 is the gate for red blood cells. Gate R5 can include not only red blood cells but also, for example, cell debris or foam.

[0227] When gate R1 evolves into a histogram based on CD3, the following is obtained: Figure 7 The histogram shown in B is used to define a gate R2 for the histogram. Gate R2 is the gate for CD3-positive cells (i.e., T cells).

[0228] Developing gate R2 into a two-dimensional graph based on CD4 and CD8 yields, as follows: Figure 7 The diagram shown in Figure C is a two-dimensional plot. Gates R3 and R4 are set for the two-dimensional plot. Gate R3 is a gate for CD8-positive and CD4-negative cells (i.e., cytotoxic T cells). Gate R4 is a gate for CD8-negative and CD4-positive cells (i.e., helper T cells).

[0229] By gating as described above, the cell population contained in the blood sample was divided into the following cell populations.

[0230] Cell population 0: Cells other than cell populations 1 through 3 below.

[0231] Cell population 1: Cells belonging to phyla R1, R2, and R3 (cytotoxic T cells)

[0232] Cell population 2: Cells belonging to phyla R1, R2, and R4 (helper T cells)

[0233] Cell population 3: Cells belonging to phylum R5 (red blood cells)

[0234] By gating and sorting cell populations 1 and 2 as described above, a cell population containing higher levels of cytotoxic T cells and helper T cells is obtained. The process of sorting cells belonging to either cell population 1 or 2 from a blood sample will be described.

[0235] Figure 8 This is a diagram illustrating an example of a sorting determination pattern based on the presence or absence of cells (specifically, cells flowing in front of or behind the cell) within a predetermined range around the cell (i.e., during the protection time).

[0236] Cases 1 through 9 are shown in Figure 8The left side shows "Examples of particles present during the protection time". In these cases, the circled number in the center during the protection time represents the cell that was identified as a sorting target. The numbers correspond to the numbers assigned to the aforementioned cell populations. Furthermore, the direction from left to right in the diagram during the protection time represents the direction of travel of the particles that were identified as sorting targets in the merging flow path 155.

[0237] exist Figure 8 In this context, determination mode A is a mode used to determine that even if the particles to be sorted are target cells, and different particles exist around the cells within a protective timeframe, the particles that are the target particles for sorting will not be sorted. In other words, determination mode A is a mode that emphasizes the purity of the target unit. Figure 8 In this context, Deterministic Mode B is a determination mode used to improve the collection rate of the target cell while maintaining as much purity as possible compared to Deterministic Mode A. Regarding the details of the determination modes, Deterministic Mode A will be explained first, followed by Deterministic Mode B.

[0238] In case 1 of mode A, since the particle to be sorted belongs to cell population 0 and there are no other cells during the protection time, the determination unit 105 determines that the particle will not be sorted.

[0239] In cases 2 and 3, since the microparticle to be sorted belongs to cell population 1 or cell population 2 (i.e., cytotoxic T cells or helper T cells) and there are no other microparticles during the protection period, the determining unit 105 determines that the microparticle is to be sorted.

[0240] In case 4, since the particle that is the target for sorting belongs to cell population 3 (i.e., red blood cells) and there are no other particles during the protection time, the determination unit 105 determines that the particle will not be sorted.

[0241] In case 5, the particles targeted for sorting belong to cell population 1, but particles belonging to cell population 0 exist within the protection time (after the cells targeted for sorting). The particles targeted for sorting are the target cells, but when collecting the particles, particles belonging to cell population 0 are also collected together. When collecting particles belonging to cell population 0, the purity of the target cells decreases. Therefore, in case 5, the determination unit 105 determines not to sort the particles targeted for sorting.

[0242] In case 6, the particles targeted for sorting belong to cell population 1, but particles belonging to cell population 0 are present within the protection time (before the cells targeted for sorting). The particles targeted for sorting are the target cells, but when collecting the particles, particles belonging to cell population 0 are also collected together. Therefore, in case 6, similar to case 5, the determining unit 105 determines not to sort the particles targeted for sorting.

[0243] In case 7, the particle targeted for sorting belongs to cell population 1, and particles belonging to cell population 2 exist within the protection time (after the cell targeted for sorting). The particle targeted for sorting is the target cell, and when the particles are collected, particles belonging to cell population 2 are also collected together. The particles belonging to cell population 2 are the target cells and are advantageously collected. Therefore, in case 7, the determining unit 105 determines that the particle targeted for sorting will be sorted.

[0244] In case 8, particles belonging to cell population 1 and cell population 3 (specifically, red blood cells) are present during the protection time (before the cells being sorted). The particles being sorted are target cells, and when cells are collected, cells belonging to cell population 3 are also collected together. Since particles belonging to cell population 3 are not target cells, the purity of the target cells decreases when the particles are collected. Therefore, in case 8, the determination unit 105 determines not to sort the particles being sorted.

[0245] In case 9, the particles belonging to cell population 1 that are the target for sorting, and the particles belonging to cell population 2 and cell population 3, respectively, exist before and after the particles that are the target for sorting during the protection time. The particles that are the target for sorting are target cells, and when collecting the particles, the particles belonging to cell population 2 and cell population 3 are also collected together. Since the particles belonging to cell population 2 are target cells, while the particles belonging to cell population 3 are not target cells, the purity of the target cells decreases when the particles belonging to cell population 3 are collected. Therefore, in case 9, the determination unit 105 determines not to sort the particles that are the target for sorting.

[0246] As described above, in determination mode A, in order to increase the purity of the target cells, in cases 8 and 9, determination unit 105 determines that particles targeted for sorting will not be sorted. However, as described above, when it is permissible for particles belonging to cell population 3 to be collected together with the target cells, for example, when particles belonging to cell population 3 do not affect the processing after the sorting operation, it is advantageous to determine that particles in cases 8 and 9 are also to be sorted, in order to increase the collection rate of target cells. This determination mode is... Figure 8 The determination mode B is shown in the figure. Specifically, in determination mode B, the following determinations can be made.

[0247] For cases 1 to 7, similar to determination mode A, sorting determination is performed in determination mode B.

[0248] Regarding case 8, the particles identified as the sorting target are target cells, and when collecting the particles, particles belonging to cell population 3 are also collected together. Particles belonging to cell population 3 are not target cells, but are allowed to be collected together with the target cells. Therefore, in case 8, the determining unit 105 determines that the particles identified as the sorting target will be sorted.

[0249] Regarding case 9, the particles identified as the target for sorting are target cells, and when collecting particles, particles belonging to cell population 2 and particles belonging to cell population 3 are also collected together. Particles belonging to cell population 2 are target cells and are advantageously collected together. Particles belonging to cell population 3 are not target cells but are allowed to be collected. Therefore, in case 9, the determining unit 105 determines that the particles identified as the target for sorting will be sorted.

[0250] Figure 8 The determination modes A and B can be achieved by performing sorting determination using rule data, which defines the relationship between particles based on the particle population to which the particle being sorted belongs and the particle populations to which different particles within a predetermined range around the particle belong. More specifically, according to this disclosure,

[0251] The determination unit can perform the determination using rule data that defines the relationship between the particles based on the particle population to which the particle being determined as the sorting target belongs and the particle populations to which different particles within a predetermined range around the particle belong.

[0252] The particle groups to which the particles used for sorting and determination of targets, and the different particles within a predetermined range, may belong include the following particle groups:

[0253] (a) The particle population of particles to be sorted.

[0254] (b) A population of particles that were not sorted but were negligible in the determination process, and

[0255] (c) A population of particles that are neither particles to be sorted nor negligible particles.

[0256] Here, for example, the relationship could be the path that different particles should take, which is specified based on the particle population to which the particle being identified as the sorting target belongs and the particle population to which the different particles belong.

[0257] For example, by setting cell populations 1 and 2 as particle populations (a), cell population 3 as particle populations (b), and cell population 0 as particle populations (c), the following can be achieved: Figure 8 The two determination modes mentioned above.

[0258] (3-2) Example of determining the processing flow (emphasizing purity and increasing the collection rate)

[0259] Reference Figure 9 and Figure 10 The description is performed by the determining unit 105 for implementing the reference. Figure 8 A specific example of the sorting determination process described in sorting determination mode B. Figure 9 An example flowchart of the sorting and determination process is shown. Figure 9 A schematic diagram is also shown to illustrate the sorting determination based on the processes in Cases 2 and 9 above. Figure 10 An example of the path allocation table and rule data used in the determination process is shown.

[0260] exist Figure 9 In step S101, the determining unit 105 obtains information about the characteristics of light generated when light is irradiated onto the particles that are the sorting targets. For example, the information about the characteristics of the light may be the kind of information generated by the signal processing unit 104 as described above.

[0261] In step S102, the determining unit 105 determines which particle group a particle belongs to based on light generated by illuminating the particles flowing in the flow path. Specifically, the determining unit 105 determines the particle group to which the particle being identified as the sorting target belongs based on information about the characteristics of the light obtained in step S101.

[0262] Specifically, the determining unit 105 determines, based on this information, which of the cell populations 0, 1, 2, and 3 the particle belongs to.

[0263] For example, regarding case 2, such as Figure 9 As shown, the determining unit 105 determines that the microparticles used as the sorting target belong to cell population 1.

[0264] In addition, regarding situation 9, such as Figure 9 As shown, the determining unit 105 determines that the microparticles used as the sorting target belong to cell population 1.

[0265] In step S103, the determining unit 105 determines the path of the particles that are the sorting targets based on the particle population determined in step S102. For example, in this specification, the determining unit 105 may refer to path allocation data, in which the particle population and the paths that particles belonging to the particle population should take are associated with each other. For example, the path allocation data may be data that defines, based on the type of the particle population, whether the path that particles belonging to the particle population should travel is the path traveled by the particles to be sorted or the path traveled by particles that are not the sorting targets. The path allocation data may be, for example, as follows: Figure 10 The path allocation table shown.

[0266] In step S103, specifically, if the particle belongs to cell population 1 or cell population 2, the particle's path is determined as fine particle collection flow path 159. Furthermore, if the particle belongs to cell population 0 or cell population 3, the particle's path is designated as branch flow path 158. For example, the paths can be encoded, and a code assigned to each path can be provided to the particle. For example, as... Figure 10 As shown in the "path assignment table," particles belonging to cell population 1 or cell population 2 are particles to be sorted, and the fact that the particle's path is the fine particle collection flow path 159 can be represented by "1". Furthermore, particles belonging to cell population 0 or 3 are not particles targeted for sorting, and the fact that the particle's path is the branch flow path 158 can be represented by "0". With the paths encoded as described above, the determining unit 105 assigns a code of "1" or "0" to each particle based on the type of cell population determined in step S102.

[0267] For example, regarding case 2, since the particles that are the targets for sorting belong to cell population 1, such as... Figure 9 As shown, therefore, unit 105 is determined by referring to... Figure 10 The path assignment table in the table assigns path 1 to the particle.

[0268] Regarding situation 9, since the particles used to determine the target in the sorting belong to cell population 1, such as... Figure 9 As shown, therefore, unit 105 is determined by referring to... Figure 10 The path assignment table in the table assigns path 1 to the particle that is the target for sorting.

[0269] In step S104, the determining unit 105 determines whether different particles exist within a predetermined range around the particles that are the sorting targets (i.e., within the protection time).

[0270] Specifically, in steps S101 to S103, the determining unit 105 determines whether there are different particles within a predetermined range in front of or behind the direction of travel of the particles to be processed. This determination can be based on the time when light generated by illuminating the particles that are the targets for sorting has been detected and the time when light generated by illuminating particles flowing in front of and / or behind the particles has been detected. For example, if the absolute value of the difference between these times is less than or equal to a predetermined value, the determining unit 105 determines that there are different particles. If the absolute value is greater than the predetermined value, the determining unit 105 determines that there are no other particles.

[0271] In step S104, if the determining unit 105 determines that different particles exist within a predetermined range around the particle that is the sorting target, the process proceeds to step S105. If the determining unit 105 determines that there are no other particles within the predetermined range around the particle that is the sorting target, the process proceeds to step S109.

[0272] For example, regarding case 2, since there are no other particles within a predetermined range around the particle that is the target for sorting, the determination unit 105 causes the process to proceed to step S109.

[0273] Furthermore, regarding case 9, since different particles exist within a predetermined range around the particles that are the targets for sorting, the determination unit 105 causes the process to proceed to step S105.

[0274] As described above, in an advantageous embodiment of this disclosure, the determining unit determines whether different particles exist within a predetermined range around the particle that is the target for sorting. When the determining unit determines that different particles exist within the predetermined range, a determination can be made using rule data. As a result, rule data can be used only when necessary to perform the determination, reducing unnecessary processing.

[0275] Furthermore, in the process of this example, after the specifying step (steps S101 to S103) which specifies the path of the particles to be determined as the sorting target, the existence determination step (step S104) is performed to determine whether different particles exist within a predetermined range. However, the existence determination step can be performed first, and then the specification step can be performed in the determination process according to the first embodiment of this disclosure.

[0276] In step S105, the determining unit 105 determines the particle group to which other particles existing within the specified range belong. This determination can be performed in the same manner as steps S101 and S102 described above.

[0277] For example, in case 9, the determining unit 105 determines that the particles present in front of the particles that are the sorting targets belong to cell population 2 and the particles present behind the particles that are the sorting targets belong to cell population 3.

[0278] In step S106, the determining unit 105 specifies the relationship between the particle being determined as the sorting target and the different particles by referring to rule data, based on the particle group to which the particle being determined as the sorting target (i.e., the particle to be processed in steps S101 to S103) belongs and the particle group to which different particles (i.e., the particle to be processed in step S105) within a predetermined range around the particle belong. The relationship between these particles (more specifically, the paths of different particles based on the relationship between these particles) is defined.

[0279] exist Figure 10 An example of rule-based data is shown in the image. Figure 10 In the rule data shown, a value of 0 or 1 is specified based on the type of cell population to which the particles used for sorting belong, and the type of cell population to which different particles belong (in... Figure 10 (Used as an underscore 0 or 1). For example, if the cell population to which the particle being identified as the sorting target belongs is 1 or 2 (i.e., in the case of the particles to be sorted), and the cell populations to which the different particles belong are 1, 2, or 3, the determining unit 105 can specify the relationship between the particle being identified as the sorting target and the different particles as "1", and in other cases, it can specify the relationship between the two particles as "0". "1" means that the path of the different particles is the flow path through which the particles to be sorted travel (particle collection flow path 159), and "0" means that the path of the different particles is not the flow path through which the particles being sorted target travel (branch flow path 158).

[0280] That is, the rule data is defined such that, when the particle being sorted belongs to a particle population (a) of the particles to be sorted (in this example, cell population 1 or 2), and different particles within a predetermined range around that particle belong to a particle population (b) of negligible particles (in this example, cell population 3), the path of the different particles is the path of the particles to be sorted (in this example, relation 1). With such defined rule data, for example, when negligible particles such as red blood cells are present within the aforementioned predetermined range, it is possible to collect the particles together with the target particles. Therefore, sorting can be performed, thereby enhancing the purity of the target particles and increasing the collection rate.

[0281] Furthermore, the rule data is defined such that, when the particle being identified as the sorting target belongs to a particle population (1) of the particles to be sorted (in this example, cell population 1 or cell population 2), and different particles within a predetermined range around that particle belong to a particle population (a) of the particles to be sorted, the path of the different particles is the path of the particles to be sorted (in this example, relation 1). With this defined rule data, when both the particle being identified as the sorting target and the different particles within the predetermined range are target particles, these particles can be collected together.

[0282] Furthermore, the rule data is defined such that if the particle being identified as the sorting target belongs to a particle population (a) of particles to be sorted (in this example, cell population 1 or 2), and different particles within a predetermined range around that particle belong to a particle population (c) of particles that are neither particles to be sorted nor negligible particles (in this example, cell population 0), then the path of the different particles is not the path of the target particle (in this example, relation 0). By defining the rule data in this way, it is possible to prevent the collection of uncollected particles along with the target particles.

[0283] Rule data definition: In the case that the particle that is the target of sorting belongs to the particle population (b) of negligible particles (in this example, cell population 3), even if different particles within a predetermined range around the particle belong to one of the particle populations (a) to (c), the paths of different particles and the paths of particles that are not the target of sorting (in this example, relation 0).

[0284] Furthermore, the rule data is defined as follows: when the particle that is the target of sorting belongs to a particle population that is neither a particle to be sorted nor a negligible particle (in this example, cell population 0), even if different particles within a predetermined range around the particle belong to one of the particle populations (a) to (c), the path of the different particles is defined as the path of the particle that is not the target of sorting (in this example, relation 0).

[0285] By using such defined rules, the purity of the target particles can be improved.

[0286] For example, regarding case 9, the cell population to which the particle that is the target for sorting belongs is "1", and the cell population to which the particle preceding the target particle belongs is "2". Therefore, as Figure 10 As shown, the reference rule data for unit 105 is determined and "1" (in) is set to "1" (in) Figure 10 The underscore (+) indicates the path of the particle that exists in front of the particle.

[0287] Furthermore, the cell population to which the particle that is the target for sorting belongs is "1", and the cell population to which the particles following the target particle belong is "3". Therefore, as Figure 10 As shown, the reference rule data for the determination unit 105 is used to assign "1" (in...). Figure 10 The underlined part (in Chinese) represents the path of the particle that follows it.

[0288] In step S107, the determining unit 105 determines whether to sort the particles that are the sorting targets based on the path of the particles specified in step S103 and the relationship specified in step S106 (i.e., the paths of different particles based on the relationship between the two particles).

[0289] More specifically, if the path of the particle targeted for sorting is the same path traversed by the particles to be sorted (particle collection flow path 159) and the paths of different particles are also the same paths traversed by the particles to be sorted, the determination unit 105 ultimately determines that the particle targeted for sorting will be sorted. Furthermore, if the path of the particle targeted for sorting is the same flow path traversed by the particles to be sorted, but the paths of different particles (at least one of the paths of the different particles if there are two or more different particles) are not the flow path traversed by the particle targeted for sorting (branch flow path 158), the determination unit 105 ultimately determines that the particle targeted for sorting will not be sorted. Moreover, if the path of the particle targeted for sorting is not the same flow path traversed by the particle targeted for sorting, the particle targeted for sorting will not be sorted, regardless of whether the paths of the different particles are any flow paths.

[0290] In this way, by considering the path allocation results based on rule data, the path of the particle to be sorted can be determined. Sorting can be performed based on the type of particle to be sorted and the different types of particles, and negligible particles (such as red blood cells) can be collected.

[0291] For example, if the path of the particle designated as the sorting target in step S103 is "1" and all relationships specified in step S106 (specifically, the paths of different particles) are "1", the determination unit 105 determines that the particle designated as the sorting target will be sorted. In other cases (e.g., if the path of the particle designated as the sorting target is "0" and one or more relationships are "0"), the determination unit 105 determines that the particle designated as the sorting target will not be sorted. This determination prevents non-target cells from being collected into the target cell.

[0292] For example, regarding case 9, the path of the particle specified as the sorting target in step S103 is "1", and the relationships specified in step S106 are all "1". Therefore, in step S107, the determining unit 105 determines that the particle as the sorting target will be sorted.

[0293] Step S108 is an example of a process performed by the determining unit 105 when no other particles are present during the protection period. In step S108, the determining unit 105 determines whether to sort the particles that are the sorting targets based on the path determined in step S103. For example, the determining unit 105 determines that if the path of the particle that is the sorting target in step S103 is specified as "1", the particle will not be sorted, and determines that if the path of the particle is specified as "0", the particle will not be sorted.

[0294] In step S109, the determining unit 105 sends the determination result obtained in step S107 or S108 to the sorting control unit 106. For example, if the sorting control unit 106 receives a determination result indicating that particles to be sorted will be sorted, the sorting control unit 106 drives the particle sorting device to perform the particle collection step S3. If the sorting control unit 106 receives a determination result indicating that particles to be sorted will not be sorted, the sorting control unit 106 controls the particle sorting device not to perform the particle collection step S3.

[0295] The determination unit 105 performs the above-described sorting determination process for each particle that is the target of sorting determination.

[0296] Using the rule data employed in the sorting process described above, when the target particle belongs to particle population (a), even if the surrounding particles belong to a negligible particle population (b), the target particle can still be determined to be sorted. More specifically, this determination is possible because the rule data defines the relationship as "1" when the target particle belongs to cell population 1 or 2 and the different particles belong to cell population 3. Therefore, the collection rate of the target particles can be increased while maintaining their purity.

[0297] Furthermore, the aforementioned rule data can be as follows: Figure 10 The data shown can be multidimensional, and can be, for example, two-dimensional or three-dimensional matrix data. Multidimensional data allows for the definition of relationships between the particle population to which the particle being identified as the sorting target belongs and the particle populations to which different particles belong. For example, if the number of different particle types is one, two-dimensional matrix data can be used, and if the number of different particle types is two, either two-dimensional or three-dimensional matrix data can be used.

[0298] (3-3) Various sorting determination modes are achieved by changing the rule data.

[0299] In this disclosure, the determination unit can be configured to change the rule data used in the determination process. As a result, by changing the rule data used in the determination process, various determination modes can be implemented, such as a determination mode for increasing the collection rate of a target cell and a determination mode for increasing the purity of a target cell. Therefore, various needs of equipment users can be met.

[0300] Furthermore, the particle sorting apparatus according to the first embodiment of the present invention may include multiple rule data and relationships between particles, the particles being sorted according to a particle group to which the particle being determined as the sorting target belongs, and different particle groups to which different particles within a predetermined range around the particle belong. Multiple rule data may be stored, for example, in a control unit of the particle sorting apparatus. Multiple rule data may be stored in a recording medium. The recording medium may be inside the particle sorting apparatus or outside the apparatus. The control unit can acquire the rule data stored in the recording medium, and the rule data can be used for particle sorting determination.

[0301] Furthermore, the particle sorting apparatus according to the first embodiment of this disclosure may further include a rule data generation unit for generating rule data. For example, the rule data generation unit may be included in the control unit 103 described above. For example, the rule data may be generated based on gating a specified particle population and assigning each particle population to (a) to (c) described above. To achieve this rule data generation, preferably, the particle sorting apparatus may further include an input unit that receives a gating operation for setting the particles as sorting targets and the particle groups to which the different particles belong within a predetermined range. The configuration of the input unit may be suitably set by those skilled in the art, and may be, for example, as described above. Such an input unit may include, for example, an input device capable of setting doors (e.g., a mouse, touchpad, or keypad), and the input device may be used in conjunction with a display device that displays the doors to be set.

[0302] Regarding cases 1 to 9 described in (3-1) above, it is explained that various sorting determination modes can be achieved by changing the rule data. Note that the gating of the cell population used in the following sorting determination modes is the same as the gating described in (3-1) above.

[0303] (3-3-1) Example of sorting treatment to determine the purity of target cells according to priority.

[0304] Figure 11 Examples of rule-based data used in sorting determination that emphasizes the purity of target cells are shown, as well as examples of sorting determination results when sorting determination is performed using rule-based data.

[0305] It should be noted that the sorting results are consistent with the above reference. Figure 8 The sorting and determination results are the same.

[0306] exist Figure 11 The rule data is shown in the upper left corner. The rule data specifies that when the particle being sorted belongs to cell population 1 or cell population 2, and different particles surrounding the particle also belong to cell population 1 or cell population 2, the path of the different particles is the flow path of the particle being sorted (represented by the underlined number 1 in the rule data table). Additionally, the rule data specifies that in other cases, the path of the different particles is the flow path of the non-sorting particles (represented by the underlined number 0 in the table). Figure 11 The path allocation table shown in the upper right corner is similar to that in... Figure 10 The path allocation table described in [the document] is the same.

[0307] Figure 11 The lower part shows the sorting determination results for cases 1 through 9. The sorting determination process for cases 1 through 9 will be described below.

[0308] (Regarding scenarios 1 through 4)

[0309] In cases 1 to 4, since no other particles exist within a predetermined range (protection time) around the particle that is the target for sorting, in step S104, the determining unit 105 advances the process to step S109. Therefore, in step S109, the determining unit 105 determines whether to sort the particle that is the target for sorting based on the path specified by the determining unit 105 in steps S101 to S103.

[0310] For example, in cases 1 and 4, such as Figure 11 As shown, in step S103, the determining unit 105 assigns "0" as the path for the particle that is the sorting target; that is, the determining unit 105 designates the path of the particle as branch flow path 158. In step S109, the determining unit 105 determines that the particle will not be sorted based on the fact that "0" is assigned to the path of the particle that is the sorting target. For example, the determining unit 105 will indicate that the particle will not be sorted (in the path of the particle that is the sorting target). Figure 11 (Shown in italics) The particles assigned as the sorting target are used as the sorting result.

[0311] In cases 2 and 3, such as Figure 11 As shown, in step S103, the determining unit 105 assigns "1" as the path for the particles that are the sorting targets; that is, the determining unit 105 designates the path of the particles as the fine particle collection flow path 159. In step S109, the determining unit 105 determines the particles to be sorted based on the fact that "1" is assigned to the path of the particles that are the sorting targets. For example, the determining unit 105 will indicate the "1" (in the path of the particles) that the particles will be sorted. Figure 11 (Described in italics) Assigned to particles as the target for sorting.

[0312] (Regarding situations 5 through 9)

[0313] In cases 5 to 9, since different particles exist within a predetermined range (protection time) around the particle that is the target for sorting, unlike cases 1 to 4, the determining unit 105 causes the process to proceed to step S105 in step S104. Each case will be described below.

[0314] Regarding case 5, in step S103, the determining unit 105 assigns "1" as the path for determining the particle sorting target, that is, the determining unit 105 designates the path of the particle that is the sorting target as the particle collection flow path 159.

[0315] Next, in step S105, the determining unit 105 specifies that different particles existing behind the particles that are the sorting determination target belong to cell population 0.

[0316] Next, in step S106, the determination unit 105 references rule data and specifies the relationship between the particle being determined as the sorting target and the different particles. Since the particle being determined as the sorting target belongs to cell population 1 and the different particles belong to cell population 0, the determination unit 105 specifies "0" (in...). Figure 11 The underlined text indicates the relationship between these particles and specifies whether the paths of different particles are the flow paths (branch flow paths 158) through which the particles of the sorting target travel.

[0317] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. Although the path specified in step S103 is "1", not all values ​​are "1" because the relationship specified in step S106 is "0". Since not all values ​​are "1", the determining unit 105 determines not to sort the particles that are the sorting determination target. For example, the determining unit 105 will indicate "0" (in the context of the path) that the particles will not be sorted. Figure 11 (Shown in italics) The particles assigned as the sorting target are used as the sorting result.

[0318] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0319] Regarding case 6, in step S103, the determining unit 105 assigns "1" as the path of the particles that are the sorting and determining targets, that is, the determining unit 105 designates the path of the particles as the fine particle collection flow path 159.

[0320] Next, in step S105, the determining unit 105 designates different particles existing in front of the particles that are the sorting determination target as belonging to cell population 0.

[0321] Next, in step S106, the determination unit 105 references the rule data and specifies the relationship between the particles used as the sorting determination target and the different particles. Similar to case 5, the determination unit 105 specifies "0" (in... Figure 11 The underlined text indicates the relationship between these particles. That is, the determining unit 105 specifies the paths of different particles as the flow paths (branch flow paths 158) for particles that are not sorting targets.

[0322] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. Specifically, similar to case 5, the determining unit 105 determines not to sort the particles that are the sorting determination target.

[0323] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0324] Regarding case 7, in step S103, the determining unit 105 assigns "1" as the path of the particles that are the sorting and determining targets, that is, the determining unit 105 designates the path of the particles as the fine particle collection flow path 159.

[0325] Next, in step S105, the determining unit 105 designates different particles that exist behind the particles that are the sorting determination targets and belong to cell population 2.

[0326] Next, in step S106, the determination unit 105 references the rule data and specifies the relationship between the particle being identified as the sorting target and the different particles. Since the particle being identified as the sorting target belongs to cell population 1 and the different particles belong to cell population 2, the determination unit 105 specifies "1" (in...). Figure 11 The underlined text indicates the relationship between particles. That is, the path of different particles specified by the determining unit 105 is the flow path (fine particle collection flow path 159) through which the particles to be sorted travel.

[0327] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. The path specified in step S103 is "1", the relationship specified in step S106 is "1", and therefore, all values ​​are 1. Because all values ​​are 1, the determining unit 105 determines that the particles that are the sorting determination target will be sorted. For example, the determining unit 105 will indicate that the particles will be sorted in the "1" (in Figure 11 (Shown in italics) The particles assigned as the sorting target are used as the sorting result.

[0328] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0329] Regarding case 8, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the particle collection flow path 159.

[0330] Next, in step S105, the determining unit 105 designates different particles present in front of the particles that are the sorting determination target to belong to cell population 3.

[0331] Next, in step S106, the determination unit 105 references the rule data and specifies the relationship between the particle being identified as the sorting target and the different particles. Since the particle being identified as the sorting target belongs to cell population 1 and the different particles belong to cell population 3, the determination unit 105 specifies "0" (in...). Figure 11 The underlined text represents the relationship between particles. Unit 105 determines whether the paths of different particles are the flow paths (branch flow paths 158) through which the particles of the sorting target travel.

[0332] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. Specifically, although the path specified in step S103 is "1", not all values ​​are "1" because the relationship specified in step S106 is "0". Since not all values ​​are "1", the determining unit 105 determines not to sort the particles that are the sorting determination target. For example, the determining unit 105 will indicate "0" (in the context of the path) that the particles will not be sorted. Figure 11 (Shown in italics) The particles assigned as the sorting target are used as the sorting result.

[0333] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0334] Regarding case 9, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the particle collection flow path 159.

[0335] Next, in step S105, the determining unit 105 designates different particles that exist behind the particle that is the target of sorting to belong to cell population 3, and designates different particles that exist in front of the particle that is the target of sorting to belong to cell population 2.

[0336] Next, in step S106, the determination unit 105 references the rule data and specifies the relationship between the particle as the sorting target and each of the two different particles. Since the particle as the sorting target belongs to cell population 1 and the different particles following it belong to cell population 3, the determination unit 105 specifies "0" (…). Figure 11 The underlined part () represents the relationship between particles; that is, determining whether the path of different particles behind a particle specified by the determining unit 105 is the flow path (branch flow path 158) traversed by the particle being sorted. Furthermore, since the particle being sorted belongs to cell population 1 and the different particles in front of the particle belong to cell population 2, the determining unit 105 specifies "1" (…). Figure 11 The underlined part represents the relationship between particles, that is, the path of different particles existing in front of the particles specified by the determining unit 105 is the path through which the particles to be sorted travel (fine particle collection flow path 159).

[0337] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. More specifically, although the path specified in step S103 is "1" and the relationship between the particle that is the sorting determination target and different particles existing in front of the particle specified in step S106 is "1", the relationship between the particle that is the sorting determination target and different particles existing in front of or behind the particle is "0". Therefore, since not all values ​​are 1, the determining unit 105 determines not to sort the particles that are the sorting determination target. For example, the determining unit 105 will indicate "0" (in the context of the path) that the particle will not be sorted. Figure 11 (Shown in italics) The particles assigned as the sorting target are used as the sorting result.

[0338] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0339] As mentioned above, Figure 11 The rule data shown enables the determination of sorting that emphasizes the purity of target cells.

[0340] Note that it can be said that... Figure 11 The rule data shown is defined as follows.

[0341] The rule data is defined such that, when the particle being identified as the sorting target belongs to a particle population (a) of particles to be sorted (in this example, cell population 1 or cell population 2), and different particles within a predetermined range around that particle also belong to a particle population (a) of particles to be sorted, the path of the different particles is the path of the particles to be sorted (in this example, relation 1). With this defined rule data, particles can be collected together when both the particle being identified as the sorting target and the different particles within the predetermined range are target particles.

[0342] The rule data is defined such that, when the particle being sorted belongs to a particle population (a) of particles to be sorted (in this example, cell population 1 or 2) and different particles within a predetermined range around the particle belong to a particle population (b) of negligible particles (in this example, cell population 3), the path of the different particles is not the path of the particle being sorted (in this example, relation 0). By using rule data defined in this way, it is possible to prevent the particle from being collected along with the target particle when negligible particles (such as red blood cells) are present within the predetermined range. As a result, the purity of the target particle can be improved.

[0343] Furthermore, the rule data is defined such that if the particle being identified as the sorting target belongs to a particle population (a) of particles to be sorted (in this example, cell population 1 or cell population 2), and different particles within a predetermined range around that particle belong to a particle population (c) of particles that are neither particles to be sorted nor negligible particles (in this example, cell population 0), then the path of the different particles is not the path of the target particle (in this example, relation 0). This defined rule data prevents the collection of uncollected particles along with the target particles.

[0344] The rule data is defined such that if the particle that is the target of sorting belongs to a particle population (b) of negligible particles (in this example, cell population 3), then even if different particles within a predetermined range around the particle belong to any of the particle populations (a) to (c), the path of the different particles is not the path of the particle that is the target of sorting (in this example, relation 0).

[0345] Furthermore, the rule data is defined as follows: Similarly, when the particle that is the target for sorting belongs to a particle population (c) of particles that are neither particles to be sorted nor negligible particles (in this example, cell population 0), even if different particles within a predetermined range around the particle belong to any of the particle populations (a) to (c), the path of the different particles is also the path of the particle that is not the target for sorting (in this example, relation 0).

[0346] The defined rules allow for improvements in the purity of the target particles.

[0347] (3-3-2) Another example of sorting to determine the purity of target cells

[0348] Figure 12 Another example of rule-based data used in sorting determination that emphasizes the purity of target cells is shown, along with an example of sorting determination results when performing sorting determination using rule-based data. Rule-based data is used to determine which particles, as the target of sorting determination, will not be sorted when different particles are present during the protection period.

[0349] exist Figure 12 The upper left corner displays the rule data. The rule data defines whether the paths of different particles are the flow paths traversed by the target particles, regardless of which cell population the target particles belong to (indicated by an underlined "0" in the table). That is, using the rule data, the determination unit 105 determines that if different particles exist within the protection time, it will not sort the target particles. Figure 12 The path allocation table shown in the upper right corner and Figure 10 The path allocation table described herein is the same.

[0350] Figure 12 The lower part shows the sorting determination results for cases 1 through 9. The sorting determination process for cases 1 through 9 will be described below.

[0351] (Regarding scenarios 1 through 4)

[0352] In cases 1 to 4, since the rule data is not referenced, the same sorting determination result as described in (3-3-1) above is obtained.

[0353] (Regarding situations 5 through 9)

[0354] In cases 5, 6, and 8, the rule data is referenced, but the relationship specified in step S106 is the same as that described in (3-3-1) above. Therefore, the same sorting determination result as described in (3-3-1) above is obtained.

[0355] The following will describe cases 7 and 9 in which different sorting results were obtained than those described in (3-3-1) above.

[0356] Regarding case 8, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the particle collection flow path 159.

[0357] Next, in step S105, the determining unit 105 designates different particles that exist behind the particles that are the sorting determination targets and belong to cell population 2.

[0358] Next, in step S106, the determination unit 105 references the rule data and specifies the relationship between the particle being identified as the sorting target and the different particles. Since the particle being identified as the sorting target belongs to cell population 1 and the different particles belong to cell population 2, the determination unit 105 specifies "0" ( Figure 12 The underlined part represents the relationship between particles. Unit 105 determines whether the paths of different particles are the flow paths (branch flow paths 158) through which the particles of the sorting target travel.

[0359] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. Although the path specified in step S103 is "1", not all values ​​are "1" because the relationship specified in step S106 is "0". Since not all values ​​are "1", the determining unit 105 determines not to sort the particles that are the sorting determination target. For example, the determining unit 105 will indicate "0" (in the context of the path) that the particles will not be sorted. Figure 12 (Shown in italics) Assigned to particles as targets for sorting.

[0360] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0361] Regarding case 9, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the particle collection flow path 159.

[0362] Next, in step S105, the determining unit 105 designates different particles that exist behind the particle that is the target of sorting to belong to cell population 3, and designates different particles that exist in front of the particle that is the target of sorting to belong to cell population 2.

[0363] Next, in step S106, the determination unit 105 references the rule data and specifies the relationship between the particle as the sorting target and each of the two different particles. Since the particle as the sorting target belongs to cell population 1 and the different particles following it belong to cell population 3, the determination unit 105 specifies "0" (…). Figure 12 The underlined part () represents the relationship between particles; that is, determining whether the path of different particles behind a particle specified by the determining unit 105 is the flow path (branch flow path 158) traversed by the particle being sorted. Furthermore, since the particle being sorted belongs to cell population 1 and the different particles in front of the particle belong to cell population 2, the determining unit 105 specifies "0" (…). Figure 12 The underlined part represents the relationship between particles, that is, whether the path of different particles in front of the particle specified by the determining unit 105 is the flow path (branch flow path 158) through which the particle of the sorting target travels.

[0364] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. More specifically, although the path specified in step S103 is "1", the relationship between the particle that is the sorting determination target specified in step S106 and different particles existing in front of or behind the particle is "0". Therefore, since not all values ​​are 1, the determining unit 105 determines not to sort the particles that are the sorting determination target. For example, the determining unit 105 will indicate "0" (in the context of the path) that the particle will not be sorted. Figure 12 (Shown in italics) Assigned to particles as targets for sorting.

[0365] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0366] As mentioned above, Figure 12 The rule data shown can also enable the sorting and determination of target cell purity.

[0367] Note that it can be said that... Figure 12 The rule data is defined as follows.

[0368] This rule data definition ensures that regardless of which of the particle groups (a) to (c) the target particle belongs to, the path of the different particles is not the path of the target particle. By using this defined rule data, it is possible to prevent the collection of more than two types of particles in a single sorting process. This determination process also allows for an increase in the purity of the target particles.

[0369] (3-3-3) Example of sorting treatment to determine the yield of target cells according to priority.

[0370] Figure 13 Examples of rule data used in sorting determination that emphasizes the yield of target cells are shown, along with examples of sorting determination results when using rule data to perform the sorting determination. Rule data is used to determine that if the particle targeted for sorting determination is a particle to be sorted, the particle targeted for sorting determination will be sorted even if the different particles present during the protection time are any particles.

[0371] exist Figure 13 The rule data is shown in the upper left corner. The rule data defines that, when the target particle belongs to cell population 1 or 2, the path of the different particles is the flow path of the target particle (represented by an underlined "1" in the table), even if the different particles belong to any cell population. Furthermore, the rule data defines that, when the target particle belongs to cell population 0 or 3, the path of the different particles is also the flow path of the particles (represented by an underlined "0" in the table), even if the non-target particle belongs to any cell population. That is, when using this rule data, if the target particle is a particle that is being sorted, regardless of the types of different particles present during the protection time, the target particle will be sorted. Figure 13 The path allocation table shown in the upper right corner is... Figure 10 The path allocation table described herein is the same.

[0372] Figure 13 The lower part shows the sorting determination results for cases 1 through 9. The sorting determination process for cases 1 through 9 will be described below.

[0373] (Regarding scenarios 1 through 4)

[0374] In cases 1 to 4, since the rule data is not referenced, the same sorting determination result as described in (3-3-1) above is obtained.

[0375] (Regarding situations 5 through 9)

[0376] Regarding case 5, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the particle collection flow path 159.

[0377] Next, in step S105, the determining unit 105 specifies that different particles existing behind the particles that are the sorting determination target belong to cell population 0.

[0378] Next, in step S106, the determination unit 105 references rule data and specifies the relationship between the particle being determined as the sorting target and the different particles. Since the particle being determined as the sorting target belongs to cell population 1 and the different particles belong to cell population 0, the determination unit 105 specifies "1" (in...). Figure 13 The underlined part represents the relationship between particles, that is, the path of different particles specified by the determining unit 105 is the flow path of the particles as the sorting target (fine particle collection flow path 159).

[0379] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. Since the path specified in step S103 is "1" and the relationship specified in step S106 is "1", all values ​​are "1". Since all values ​​are "1", the determining unit 105 determines that the particles that are the sorting determination target will be sorted. For example, the determining unit 105 will indicate that the particles will be sorted in the "1" (in Figure 13 (Shown in italics) The particles assigned as the sorting targets are the sorting results.

[0380] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0381] Regarding case 6, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the particle collection flow path 159.

[0382] Next, in step S105, the determining unit 105 designates different particles existing in front of the particles that are the sorting determination target as belonging to cell population 0.

[0383] Next, in step S106, the determination unit 105 references the rule data and specifies the relationship between the particles used as the sorting determination target and the different particles. Similar to case 5, the determination unit 105 specifies "1" (in... Figure 13 The underlined text indicates the relationship between particles. That is, the path of different particles specified by the determination unit 105 is the flow path (fine particle collection flow path 159) of the particles that are the sorting targets.

[0384] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. More specifically, similar to case 5, the determining unit 105 determines that the particles that are the sorting determination target will be sorted.

[0385] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0386] Regarding case 7, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the particle collection flow path 159.

[0387] Next, in step S105, the determining unit 105 designates different particles that exist behind the particles that are the sorting determination targets and belong to cell population 2.

[0388] Next, in step S106, the determination unit 105 references the rule data and specifies the relationship between the particle being identified as the sorting target and the different particles. Since the particle being identified as the sorting target belongs to cell population 1 and the different particles belong to cell population 2, the determination unit 105 specifies "1" (in...). Figure 11 The underlined part represents the relationship between particles, that is, the path of different particles specified by the determining unit 105 is the flow path of the particles as the sorting target (fine particle collection flow path 159).

[0389] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. Since the path specified in step S103 is "1" and the relationship specified in step S106 is "1", all values ​​are "1". Since all values ​​are "1", the determining unit 105 determines that the particles that are the sorting determination target will be sorted. For example, the determining unit 105 will indicate that the particles will be sorted in the "1" (in Figure 13 (Shown in italics) The particles assigned as the sorting targets are the sorting results.

[0390] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0391] Regarding case 8, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the particle collection flow path 159.

[0392] Next, in step S105, the determining unit 105 designates different particles present in front of the particles that are the sorting determination target to belong to cell population 3.

[0393] Next, in step S106, the determination unit 105 references rule data and specifies the relationship between the particle being determined as the sorting target and the different particles. Since the particle being determined as the sorting target belongs to cell population 1 and the different particles belong to cell population 3, the determination unit 105 specifies "1" (in...). Figure 13 The underlined part represents the relationship between particles, that is, the path of different particles specified by the determining unit 105 is the flow path of the particles as the sorting target (fine particle collection flow path 159).

[0394] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. More specifically, since the path specified in step S103 is "1" and the relationship specified in step S106 is "1", all values ​​are "1". Since all values ​​are "1", the determining unit 105 determines that the particles that are the sorting determination target will be sorted. For example, the determining unit 105 will indicate that the particles will be sorted in the "1" (in Figure 13 (Shown in italics) The particles assigned as the sorting targets are the sorting results.

[0395] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0396] Regarding case 9, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the particle collection flow path 159.

[0397] Next, in step S105, the determining unit 105 designates different particles that exist behind the particle that is the target of sorting to belong to cell population 3, and designates different particles that exist in front of the particle that is the target of sorting to belong to cell population 2.

[0398] Next, in step S106, the determination unit 105 references rule data and specifies the relationship between the particle as the sorting target and each of the two different particles. Since the particle as the sorting target belongs to cell population 1 and the different particles following the particle belong to cell population 3, the determination unit 105 specifies "1" (in...). Figure 13The underlined text indicates a relationship between particles; that is, the determining unit 105 specifies that the path of different particles existing behind the particle is the flow path (fine particle collection flow path 159) of the particle that is the sorting target. Furthermore, since the particle that is the sorting target belongs to cell population 1 and the different particles existing in front of the particle belong to cell population 2, the determining unit 105 specifies "1" (…). Figure 13 The underlined part represents the relationship between particles, that is, the path of different particles existing in front of the particles specified by the determining unit 105 is the path through which the particles to be sorted travel (fine particle collection flow path 159).

[0399] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. More specifically, the path specified in step S103 is "1", and the relationship between the particles that are the sorting determination target and the different particles existing in front of or behind the particles specified in step S106 is "1". Therefore, since all values ​​are "1", the determining unit 105 determines that the particles that are the sorting determination target will be sorted. For example, the determining unit 105 will indicate that the particles will be sorted at "1" (in Figure 13 (Shown in italics) The particles assigned as the sorting targets are the sorting results.

[0400] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0401] As mentioned above, Figure 13 The rule data shown enables the determination of sorting that emphasizes the yield of target cells.

[0402] Note that it can be said that... Figure 13 The rule data is defined as follows.

[0403] The rule data is defined such that, when the particle that is the target of sorting belongs to a particle population (a) of the particles to be sorted (in this example, cell population 1 or 2), the path of the different particles is the path of the particles to be sorted (in this example, relation 1, even if the different particles within a predetermined range around the particle belong to any one of particle populations (a) to (c)).

[0404] The rule data is defined such that if the particle that is the target of sorting belongs to a particle population (b) of negligible particles (in this example, cell population 3), then even if different particles within a predetermined range around the particle belong to any of the particle populations (a) to (c), the path of the different particles is not the path of the particle that is the target of sorting (in this example, relation 0).

[0405] Furthermore, the rule data is defined as follows: Similarly, when the particle that is the target for sorting belongs to a particle population (c) of particles that are neither particles to be sorted nor negligible particles (in this example, cell population 0), even if different particles within a predetermined range around the particle belong to any of the particle populations (a) to (c), the path of the different particles is also the path of the particle that is not the target for sorting (in this example, relation 0).

[0406] By using such defined rules, the yield of target particles can be improved.

[0407] (3-3-4) Example of sorting and determination treatment that emphasizes the purity of target cells and increases the collection rate

[0408] Figure 14 Examples of rule data used in a sorting determination process to emphasize the purity of target cells and increase the collection rate are shown, along with examples of sorting determination results when the sorting determination is performed using rule data. Rule data is used to sort particles that are the target of sorting determination in cases where different particles are negligible during the protection time, so that the different particles are ignored in the sorting determination.

[0409] exist Figure 14 The rule data is shown in the upper left corner. The rule data defines the path of the target particle as the flow path (indicated by the underlined number 1 in the rule data table) when the particle being sorted belongs to cell population 1 or 2, and different particles surrounding it also belong to cell population 1, 2, or 3. In other cases, the rule data defines whether the path of the target particle is the flow path (indicated by the underlined number 0 in the table). Figure 11 The rule data shown is Figure 14 The difference between the rule data shown is the case where the particles used to determine the target for sorting belong to cell population 1 or 2 and different particles belong to cell population 3.

[0410] Figure 14 The path allocation table shown in the upper right corner is... Figure 10 The path allocation table shown is the same.

[0411] Figure 14 The lower part shows the sorting determination results for cases 1 through 9. The sorting determination process for cases 1 through 9 will be described below.

[0412] (Regarding scenarios 1 through 4)

[0413] In cases 1 to 4, since the rule data is not referenced, the same sorting determination result as described in (3-3-1) above is obtained.

[0414] (Regarding situations 5 through 9)

[0415] In cases 5 through 7, the rule data is referenced, but the relationship specified in step S106 is the same as that described in (3-3-1) above. Therefore, the same sorting determination result as described in (3-3-1) above is obtained.

[0416] Cases 8 and 9, in which different sorting results were obtained than those described in (3-3-1) above, will be described below.

[0417] Regarding case 8, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the fine particle collection flow path 159.

[0418] Next, in step S105, the determining unit 105 designates different particles present in front of the particles that are the sorting determination target to belong to cell population 3.

[0419] Next, in step S106, the determination unit 105 references rule data and specifies the relationship between the particle being identified as the sorting target and the different particles. Since the particle being identified as the sorting target belongs to cell population 1 and the different particles belong to cell population 3, the determination unit 105 specifies "1" (in...). Figure 14 The underlined part represents the relationship between particles, that is, the path of different particles specified by the determining unit 105 is the flow path of the particles as the sorting target (fine particle collection flow path 159).

[0420] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. More specifically, since the path specified in step S103 is "1" and the relationship specified in step S106 is "1", all values ​​are "1". Since all values ​​are "1", the determining unit 105 determines that the particles that are the sorting determination target will be sorted. For example, the determining unit 105 will indicate that the particles will be sorted in the "1" (in Figure 14 (Shown in italics) The particles assigned as the sorting target are used as the sorting result.

[0421] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0422] Regarding case 9, in step S103, the determining unit 105 assigns "1" as the path of the particle as the sorting target, that is, the determining unit 105 specifies the path of the particle as the particle collection flow path 159.

[0423] Next, in step S105, the determining unit 105 designates different particles that exist behind the particle that is the target of sorting to belong to cell population 3, and designates different particles that exist in front of the particle that is the target of sorting to belong to cell population 2.

[0424] Next, in step S106, the determination unit 105 references rule data and specifies the relationship between the particle as the sorting target and each of the two different particles. Since the particle as the sorting target belongs to cell population 1 and the different particles following the particle belong to cell population 3, the determination unit 105 specifies "1" (in...). Figure 14 The underlined characters (in Chinese) represent the relationship between particles; that is, the determining unit 105 specifies that the path of different particles existing behind the particle is the flow path (fine particle collection flow path 159) for the particle that is the sorting target. Furthermore, since the particle that is the sorting target belongs to cell population 1 and the different particles existing in front of the particle belong to cell population 2, the determining unit 105 specifies "1" (in Chinese). Figure 14 The underlined part represents the relationship between particles, that is, the path of different particles existing in front of the particles specified by the determining unit 105 is the path through which the particles to be sorted travel (fine particle collection flow path 159).

[0425] Next, in step S107, the determining unit 105 determines whether to sort the particles that are the sorting determination target based on the path specified in step S103 and the relationship specified in step S106. More specifically, since the path specified in step S103 is "1", and the relationship between the particles that are the sorting determination target and the different particles existing in front of or behind the particles specified in step S106 is "1", therefore, since all values ​​are "1", the determining unit 105 determines that the particles that are the sorting determination target will be sorted. For example, the determining unit 105 will indicate that the particles will be sorted at "1" (in Figure 14 (Shown in italics) The particles assigned as the sorting target are used as the sorting result.

[0426] Next, in step S109, the determining unit 105 sends the sorting determination result obtained in step S107 to the sorting control unit 106.

[0427] As mentioned above, Figure 14The rule data shown allows for increasing the collection rate while maintaining the purity of the target cell as much as possible.

[0428] Notice, Figure 14 The rule data shown is Figure 10 The rule data shown is the same. Therefore, Figure 14 The rule data shown can be said to be defined as described in step S106 of (3-2) above.

[0429] (3-3-5) Example

[0430] Cases 1 to 9 were described in (3-3-1) above. A total of 292 patterns containing particles exist within the predetermined range considered through the above gating, including cases 1 to 9. For all 292 patterns, Microsoft Excel was used to verify whether sorting could be appropriately performed using the sorting determination process described in (3-3-1) above. The results showed that sorting could be appropriately performed by performing the sorting determination process on any pattern.

[0431] Furthermore, similar verification was performed according to any of the sorting and determination processes described in (3-3-2) to (3-3-4) above. The results confirmed that all 292 patterns could be appropriately sorted and determined through any sorting and determination process.

[0432] (4) Example of a particle sorting device configured as a flow cytometer

[0433] The particle sorting apparatus according to the first embodiment of this disclosure can be configured to form droplets containing particles and sort the particles by controlling the direction of movement of the droplets. For example, the particle sorting apparatus can be configured as a particle sorting apparatus for performing flow cytometry. Figure 15 An example configuration of a particle sorting apparatus according to a first embodiment of the present disclosure is shown.

[0434] Figure 15 The particle sorting device 200 shown includes a control unit 1, a light irradiation unit 2, a chip T with a flow path, a detection unit 3, an output unit 4, an input unit 5, and a sorting unit 6, through which the particles to be analyzed flow. The particle sorting device 200 is configured as a flow cytometry system.

[0435] (4-1) Illumination Unit

[0436] The light irradiation unit 2 is configured to irradiate predetermined positions in the flow path of the chip T with light. When a particle passes through the light irradiation position in the flow path, the particle is irradiated with light and thus generates fluorescence and / or scattered light.

[0437] The light irradiation unit 2 includes at least one light source that emits light, preferably multiple light sources that emit beams of different wavelengths. The light source can be a laser light source, but it can also be another light source, such as an LED.

[0438] The light source can be a laser source that emits a laser beam of a single wavelength, such as a laser source with a fixed oscillation wavelength or a laser source with a variable oscillation wavelength. The wavelength of the laser source refers to the oscillation wavelength. The laser beam emitted from each laser source can be applied to the particle without changing the oscillation wavelength.

[0439] When the light source is a laser light source, the light source can be selected from the group consisting of semiconductor lasers, argon-ion (Ar) lasers, helium-neon (He-Ne) lasers, dye lasers, krypton (Cr) lasers, and solid-state lasers that combine semiconductor lasers and wavelength conversion optical elements, and can be particularly advantageously semiconductor lasers.

[0440] When the light irradiation unit 2 includes multiple light sources, the light irradiation unit 2 can be configured such that light beams emitted from the light sources are combined and the combined light is applied to the particles. The light irradiation location can be one or more; that is, the light irradiation unit 2 can be configured such that multiple excitation beams are combined and applied to one or more (e.g., 1, 2, 3, 4, or 5) spots. The particle sorting device 200 can be configured to allow particles to pass through the spots.

[0441] To configure the light illumination unit 2 in this manner, the light illumination unit 2 may include a light-guiding optical system for guiding multiple light beams to a predetermined position. The light-guiding optical system may include optical components such as a beam splitter group and a lens group for combining the multiple light beams. Furthermore, the light-guiding optical system may include a lens group for collecting the combined excitation light, and may include, for example, an objective lens.

[0442] (4-2) Chip

[0443] Chip T can be configured, for example, as a flow cell. Chip T has flow paths. The flow path structure set in chip T is configured, for example, to form a flow (specifically, laminar flow) in which particles are substantially aligned and flow.

[0444] Figure 15The chip T shown includes flow paths P11, P12a, P12b, and P13. A sample solution containing microparticles is introduced into the sample flow path P11 from a container (bag) B1 containing the sample solution. The sample solution flows through the sample flow path P11 toward the main flow path P13. Sheath fluid is introduced into the chip T from a container (bag) B2 containing sheath fluid. The sheath fluid flows through two sheath fluid flow paths P12a and P12b toward the main flow path P13. The sample solution flow path P11 and the sheath fluid flow paths P12a and P12b are configured to merge to form the main flow path P13. The sample solution supplied to the sample flow path P11 and the sheath fluid supplied to the sheath fluid flow paths P12a and P12b merge at the point where the three flow paths merge, and then flow in the main flow path P13. In the main flow path P13, for example, the sample solution flows in laminar flow sandwiched between the sheath fluids. In laminar flow, the microparticles are substantially aligned. The particles aligned and flowing in the main flow path P13 are irradiated by light (specifically, a laser beam) generated by the light irradiation unit 2, and the light generated by the light irradiation is detected by the detection unit 3.

[0445] Chip T can have a two-dimensional or three-dimensional flow path structure. Chip T can have a substrate shape formed of plastic or glass material. The structure of chip T and the structure of the flow paths disposed on chip T are not limited to... Figure 15 The structure shown. For example, chip structures and flow path structures known in the art of flow cytometry can be employed. That is, in this disclosure, for example, fluorescence detection can be achieved through fluorescence detection by a flow cytometer.

[0446] The cross-sectional shape of the flow path disposed within chip T can be, for example, circular, elliptical, or rectangular (square or rectangular). When the cross-section of the flow path is circular or elliptical, its diameter or main axis can be, for example, 1 mm or less, specifically, 10 μm or more and 1 mm or less. When the cross-section of the flow path is square or rectangular, the length of one side or the longer side can be, for example, 1 mm or less, specifically, 10 μm or more and 1 mm or less.

[0447] Chip T has an outlet for discharging laminar flow. Droplets are formed by vibrating chip T. Each formed droplet may include one or more microparticles. Microparticles can be sorted by charging each droplet and controlling the direction of travel of the charged droplets.

[0448] (4-3) Sorting Unit

[0449] The sorting unit 6 can be configured to form charged droplets containing microparticles and can control the direction of movement of the droplets to sort the microparticles as described above. For example, the sorting unit 6 may include: a vibrating element that vibrates the chip T to form droplets; a charging unit that charges the droplets; and a deflecting plate that controls the direction of movement of the charged droplets. The sorting unit 6 can perform the sorting process under the control of, for example, the sorting control unit described later.

[0450] A vibrating element vibrates the chip T to atomize the laminar liquid discharged from the outlet. The vibrating element can be, for example, a piezoelectric element. The vibrating element may or may not be integrally formed with the chip T. If the vibrating element is not integrally formed with the chip T, it may be arranged to contact the chip T.

[0451] The charging unit applies a positive or negative charge to the droplet exiting from the outlet. For example, the charging unit applies the charge to the droplet by means of an electrode inserted into electrical contact with the sample solution or sheath fluid, which is fed through a flow path.

[0452] The particle sorting device 200 can apply one of a positive charge and a negative charge to a portion of a droplet discharged from the outlet by synchronizing the frequency of the driving voltage of the vibrating element with the switching timing of the voltage (charging voltage) of the charging unit. The charge does not necessarily need to be applied to a portion of the droplet, and therefore, the portion of the droplet can be an uncharged droplet.

[0453] A deflector plate can be configured to control the direction of droplet movement. For example, the deflector plate can be a pair of deflector plates arranged facing each other across the path of the droplet. The deflector plate can change the direction of movement of the droplet by an electric current acting between the deflector plate and the charge applied to the droplet. The deflector plate can be an electrode commonly used in the art.

[0454] The particle sorting device 200 can be configured such that a plurality of collection containers for collecting droplets can be interchangeably attached thereto. The plurality of collection containers may include one or more collection containers for collecting particles that are the target of sorting and one or more containers for collecting particles that are not the target of sorting. Containers known in the art can be used as the plurality of collection containers.

[0455] (4-4) Detection Unit

[0456] The detection unit 3 detects the light generated by the light irradiation unit 2 irradiating the microparticles. For example, the detection unit 3 may be configured to detect the light generated by irradiating microparticles flowing in the flow path of the chip T. The light detected by the detection unit 3 may include, for example, fluorescence and / or scattered light. Scattered light may be one or more of, for example, forward scattered light, backscattered light, and side scattered light.

[0457] Detection unit 3 includes at least one photodetector for detecting light generated by illuminating the particles with light from illumination unit 2. Each photodetector includes one or more light-receiving elements, such as an array of light-receiving elements. Each photodetector may include, for example, one or more photomultiplier tubes (PMTs) and / or photodiodes as light-receiving elements, and specifically includes one or more PMTs. The photodetector may include, for example, an array of PMTs arranged in a one-dimensional direction.

[0458] The detection unit 3 may include a beam-splitting unit for dispersing light. The beam-splitting unit may be disposed in each photodetector. The beam-splitting unit may be configured, for example, to disperse light (e.g., fluorescence) so that light of a predetermined detection wavelength reaches a light-receiving device (e.g., a PMT) assigned the predetermined detection wavelength.

[0459] The detection unit 3 may include one or more measuring instruments selected from fluorometers, scattered light meters, transmitted light meters, reflected light meters, diffractometers, ultraviolet spectrometers, infrared spectrometers, Raman spectrometers, FRET meters, and FISH meters. Furthermore, the detection unit 3 may also include two-dimensional light receiving elements such as CCDs and CMOS sensors.

[0460] The detection unit 3 may include a signal processing unit. The signal processing unit converts the electrical signal obtained by the fluorescence detector into a digital signal. The signal processing unit may include, for example, an A / D converter as a means of performing the conversion. The optical signal detected by the photodetector may be converted into a digital signal by the signal processing unit and transmitted to the control unit 1. The digital signal is processed by the control unit 1 into optical data and used in the sorting and determination process described below.

[0461] The detection unit 3 (specifically, a photodetector) is positioned at a location capable of detecting light generated from the particles. For example, as... Figure 15 As shown, the detection unit 3 can be arranged such that the chip T (specifically, the main path P13) is sandwiched between the light irradiation unit 2 and the detection unit 3, or the detection unit 3 can be arranged on the same side as the light irradiation unit 2 relative to the chip T.

[0462] (4-5) Control Unit

[0463] For example, control unit 1 includes a determining unit 201 and a sorting control unit 202, such as Figure 15 As shown.

[0464] The determining unit 201 determines whether a particle is to be collected based on the characteristics of the light obtained by illuminating the particle with light by the light irradiation unit. For example, the determining unit 201 may determine based on scattered light, fluorescence, or an image (e.g., a dark-field image and / or a bright-field image). The description of the determining unit 105 in (2) above also applies to the determining unit 201.

[0465] The sorting control unit 202 controls the sorting unit 6 to perform particle sorting based on the determination result obtained by the determination unit 201.

[0466] The following describes a configuration example of control unit 1. The sorting determination and sorting control performed by control unit 1 can be implemented through, for example, the following configuration, but the configuration of control unit 1 is not limited to the following.

[0467] Control unit 1 may include, for example, a central processing unit (CPU), RAM, and ROM. The CPU, RAM, and ROM may be interconnected via a bus. Input / output interfaces may be further connected to the bus. Output unit 4 and input unit 5 may be connected to the bus via input / output interfaces.

[0468] In addition, communication devices, storage devices, and drives can be connected to the input / output interface, for example.

[0469] The communication device connects the control unit 1 to a network via wired or wireless means. The communication device allows the control unit 1 to acquire various types of data (e.g., optical data and / or SR data) via the network. For example, the acquired data may be stored in a storage unit (not shown). The type of communication device can be appropriately selected by those skilled in the art.

[0470] The storage device may store an operating system (e.g., WINDOWS, UNIX, or LINUX), a program for causing an information processing device (or particle analysis device or particle analysis system) to execute an information processing method according to the first embodiment of this disclosure, various other programs, optical data, SR data, and other types of data.

[0471] The driver is capable of reading data (e.g., optical data and SR data) or programs recorded on a recording medium and outputting the read data or programs to RAM. Recording media may be, for example, a micro SD memory card, an SD memory card, or a refresh memory, but is not limited to these.

[0472] (4-6) Output Unit and Input Unit

[0473] Output unit 4 may include output devices that output various types of data. For example, output unit 4 may include a device that outputs the sorting determination results. The output device may include, for example, a display device (monitor). Furthermore, output unit 4 may include, for example, a printing device. The printing device can print the sorting determination results onto a printing medium such as paper for output.

[0474] Input unit 5 is, for example, a device for receiving user operations. Input unit 5 may include, for example, a mouse, keyboard, or display (in which case, the user operation may be a touch operation on the display). Input unit 5 accepts, for example, a gating operation by the user. Furthermore, input unit 5 accepts a user operation specifying which of the particle populations (a), (b), and (c) a corresponding gate is used for.

[0475] (5) Determine the details of the process

[0476] (5-1) Determine the basic concepts of processing

[0477] The following describes an example of the determination process when the embodiments of this disclosure are applied to the particle sorting apparatus described in (4) above.

[0478] The following will refer to Figure 16 Describe an example of gating. This example is an example of gating in which cytotoxic T cells and helper T cells are collected as a cell population from a blood sample, and granulocytes and monocytes are collected as a cell population.

[0479] The blood sample described in (3) above flows into the chip T of the particle sorting device 200 described in (5) above, and is detected by the detection unit 3 by the light generated by the light irradiation unit 2 irradiating each particle in the blood sample with light.

[0480] For example, such as Figure 16 As shown in Figure A, using data about the detection light, a two-dimensional plot (dot plot) of forward scattered light (FSC) and side scattered light (SSC) is generated. Gates R1, R5, and R6 are set for the generated two-dimensional plot. Gate R1 is for lymphocytes, gate R5 is for erythrocytes, and gate R6 is for granulocytes and monocytes. Gate R5 can include not only erythrocytes but also, for example, cell debris or foam.

[0481] When gate R1 evolves into a histogram based on CD3, it obtains, for example, Figure 16 The histogram shown in B. A gate R2 is set for the histogram. Gate R2 is the gate for CD3-positive cells (i.e., T cells).

[0482] When gate R2 evolves into a two-dimensional curve based on CD4 and CD8, the following is obtained: Figure 16The curve shown in Figure C is a two-dimensional curve. Gates R3 and R4 are set for the two-dimensional plot. Gate R3 is the gate for CD8-positive and CD4-negative cells (i.e., cytotoxic T cells). Gate R4 is the gate for CD8-negative and CD4-positive cells (i.e., helper T cells).

[0483] Through the gating process described above, the cell population contained in the blood sample was divided into the following cell populations.

[0484] Cell population 0: Cells other than cell populations 1 through 4 below.

[0485] Cell population 1: Cells belonging to phyla R1, R2, and R3 (cytotoxic T cells)

[0486] Cell population 2: Cells belonging to phyla R1, R2, and R4 (helper T cells)

[0487] Cell population 3: Cells belonging to phylum R5 (red blood cells)

[0488] Cell population 4: Cells belonging to phylum R6 (granulocytes and monocytes)

[0489] By sorting cell population 1 and cell population 2 into one collection container and cell population 4 into another collection container through gating as described above, a cell population containing high levels of cytotoxic T cells and helper T cells and a cell population containing high levels of granulocytes and monocytes can be obtained.

[0490] like Figure 15 As shown, the path of droplets traveling to the containers collecting cell population 1 and cell population 2 is designated as flow 0, the path of droplets traveling to the container collecting cell population 4 is designated as flow 1, and the path of droplets traveling to the containers collecting cell population 0 and cell population 3 is designated as flow 2. As described above, in this example, in addition to determining whether to sort particles, the path of the particles is also determined. In other words, in this example, two or more types of particles to be collected are selectively collected in two or more containers.

[0491] The following describes the sorting of cells from a blood sample that belong to one of cell populations 1 and 2, and the sorting of cells that belong to cell population 4.

[0492] Figure 17 This is a diagram illustrating an example of a sorting determination pattern based on the presence or absence of cells as the target for sorting and cells within a predetermined range around the cell (specifically, cells flowing in front of or behind the cell).

[0493] exist Figure 17 Cases 1 through 9 are shown in the "Examples of Patterns with Particulate Matter" section on the left. Figure 17The arrow in the diagram indicates the "range to be considered in the sorting determination of the target droplet" which corresponds to the predetermined range.

[0494] In these cases, the "current droplet" is the droplet containing the particles that are the target for sorting, the "previous droplet" is the droplet that formed before the current droplet, and the "subsequent droplet" is the droplet that formed after the current droplet.

[0495] The particles present in these droplets are represented by circled numbers. These numbers correspond to the numbers assigned to the aforementioned cell populations. The droplet at the center of this droplet is the particle targeted for sorting.

[0496] In addition, Figure 17 In the diagram, the dashed line defining the "range considered in determining the sorting of the target droplet" covers both the preceding and following droplets. When determining whether to sort the particle that is the target of the sorting determination, particles other than the particle that is the target of the sorting determination, existing within the range defined by the dashed line, are considered. It should be noted that the dashed line also covers both the preceding and subsequent droplets, because it is considered that there is a possibility that light generated by irradiating particles with light is typically detected before droplet formation in the aforementioned particle sorting device, and that particles contained in the preceding or subsequent droplets are included in the droplet that is the target of the sorting, and that the preceding or subsequent droplet is sorted together with the current droplet.

[0497] Note that the predetermined range can be appropriately set by those skilled in the art, similar to the protection time described in (3) above. For example, in a sorting and determination process emphasizing purity, by expanding the predetermined range along the direction of droplet movement, the collection rate of target cells is slightly reduced, but the accuracy of sorting and determination can be improved. Conversely, by narrowing the predetermined range, the accuracy is slightly reduced, but the collection rate can be improved. Furthermore, in a sorting and determination process emphasizing collection rate, by expanding the predetermined range along the direction of droplet movement, the collection rate of target cells can be improved. Conversely, by narrowing the predetermined range, the collection rate of target cells is slightly reduced, but the purity can be increased.

[0498] Figure 17 Determination Mode 1 describes a situation where, even if the particle being sorted is a target cell, different cells exist within a predetermined range around the target cell; in such cases, the target cell will not be sorted. In other words, Determination Mode 1 is a determination mode used to collect target cells with high purity. Figure 17 In this context, Determination Mode 2 is a determination mode that improves the collection rate of the target cell while maintaining the purity of the target cell as much as possible, as in Determination Mode 1. Regarding the details of the determination modes, Determination Mode 1 will be explained first, followed by Determination Mode 2.

[0499] In pattern 1, cases 1 through 9 are determined as follows.

[0500] In case 1, since the particle that is the target for sorting belongs to cell population 0 and there are no different cells within the predetermined range, the determining unit 201 determines that the particle will not be sorted and determines that the path of the particle is path 2.

[0501] In case 2, the microparticles targeted for sorting belong to cell population 1 (i.e., cytotoxic T cells) and different cells are not present within the predetermined range. Therefore, the determining unit 201 determines that the microparticles will be sorted and determines that the path of the microparticles is path 0.

[0502] In case 3, the particles targeted for sorting belong to cell population 4 (i.e., granulocytes or monocytes) and different cell types are not present within the predetermined range. Therefore, the determining unit 201 determines that the particles will be sorted and determines that the particle's path is path 1.

[0503] In case 4, since the particle that is the target for sorting belongs to cell population 3 (i.e., red blood cells) and there are no different cells during the protection time, the determination unit 201 determines that the particle will not be sorted and determines that the path of the particle is path 2.

[0504] In case 5, the particle targeted for sorting belongs to cell population 1, but particles belonging to cell population 0 exist within a predetermined range (after the particle targeted for sorting). Although the particle targeted for sorting is the target cell, when collecting the current droplet to collect the particle, there is a possibility that particles belonging to cell population 0 included in subsequent droplets may also be collected. When particles belonging to cell population 0 are collected together with the target cell, the purity of the target cell decreases. Therefore, in case 5, the determining unit 201 determines that the particle targeted for sorting will not be sorted, and determines that the path of the particle is path 2.

[0505] In case 6, the particle targeted for sorting belongs to cell population 1, but cells belonging to cell population 4 are present within a predetermined range (in front of the particle targeted for sorting). Although the particle targeted for sorting is the target cell, when the current droplet is sorted to collect particles, particles belonging to cell population 4 contained in the current droplet are also collected together. Therefore, in case 6, the determining unit 201 determines that the cell targeted for sorting is not sorted and determines that the path of the particle is path 2.

[0506] In case 7, the particle targeted for sorting belongs to cell population 1, and cells belonging to cell population 2 exist within a predetermined range. The cell targeted for sorting is the target cell. When collecting cells, cells belonging to cell population 2 are also collected together. Because cells belonging to cell population 2 are target cells, these cells are advantageously collected together with the particle targeted for sorting. Therefore, in case 7, the determination unit 201 determines that the particle targeted for sorting will be sorted, and determines that the path of the particle is path 0.

[0507] In case 8, the particles targeted for sorting belong to cell population 1. Furthermore, in case 8, within a predetermined range, particles belonging to cell population 3 (specifically, red blood cells) are present in front of the particles targeted for sorting, and cells belonging to cell population 2 are present behind the particles targeted for sorting. Although the particles targeted for sorting are target cells, there is a possibility that particles belonging to cell population 3 may also be collected when collecting droplets containing the particles. Because cells belonging to cell population 3 are not target cells, the purity of the target cells decreases when collecting the cells. Therefore, in case 8, the determining unit 201 determines that the particles targeted for sorting will not be sorted, and determines that the path of the particles is path 2.

[0508] In case 9, particles belonging to cell population 2 and those belonging to cell population 3, which are the target for sorting, exist within a predetermined range behind the particles that are the target for sorting. Although the particles that are the target for sorting are target cells, there is a possibility that particles belonging to cell population 3 may also be collected when collecting the current droplet containing the cells. Since the particles belonging to cell population 3 are not target cells, the purity of the target cells decreases when cells are collected together with the particles that are the target for sorting. Therefore, in case 9, the determination unit 105 determines that the particles that are the target for sorting will not be sorted, and determines that the path of the particles is path 2.

[0509] As described above, in determination mode 1, in cases 8 and 9, determination unit 201 determines not to sort the particles that are the target of sorting, in order to increase the purity of the target cells. However, as described above (3), in cases where it is permissible for particles belonging to cell population 3 to be collected together with the target cells, for example, where cells belonging to cell population 3 do not affect the processing after the sorting operation, it is advantageous to determine that particles should also be sorted in cases 8 and 9 to increase the collection rate of target cells.

[0510] The determination mode for increasing the collection rate will be described with reference to determination mode 2.

[0511] exist Figure 17 In cases 1 through 7, unit 201 is determined as shown in the reference. Figure 17 The process involves sorting and determining the composition of the samples.

[0512] In case 8, within a predetermined range, the particle targeted for sorting belongs to cell population 1, and particles belonging to cell population 3 are located before the particle targeted for sorting, while cells belonging to cell population 2 are located after the particle targeted for sorting. Because the particle targeted for sorting is a target cell, particles belonging to cell population 3 are also collected when collecting cells. Particles belonging to cell population 3 are not target cells but are allowed to be collected together with target cells. Therefore, in case 8, the determining unit 201 determines that the particle targeted for sorting will be sorted and determines that the path of the particle targeted for sorting is path 0.

[0513] In case 9, particles belonging to cell population 2 and those belonging to cell population 3, which are the target particles for sorting, exist within a predetermined range behind the target particles. Although the target particles are the target cells, there is a possibility that particles belonging to cell population 3 may also be collected when collecting the current droplet containing the cells. Particles belonging to cell population 3 are not target cells, but are allowed to be collected together with the target cells. Therefore, in case 9, the determination unit 201 determines that the target particles will be sorted, and determines that the path of the target particles is path 0.

[0514] The aforementioned determination modes 1 and 2 can be implemented using rule data, which defines the relationship between particles based on the particle population to which the particle being determined as the sorting target belongs and the particle populations to which different particles within a predetermined range around the particle belong. More specifically, according to this disclosure, the determination unit 201 performs determination using rule data, which defines the relationship between particles based on the particle population to which the particle being determined as the sorting target belongs and the particle populations to which different particles within a predetermined range around the particle belong. The particle populations to which the particle being determined as the sorting target and the particles within the predetermined range may belong may include the following particle populations (a) to (c):

[0515] (a) The particle population of particles to be sorted;

[0516] (b) A population of particles that were not sorted but are negligible in the determination; and

[0517] (c) A population of particles that are neither particles to be sorted nor negligible particles.

[0518] Note that this relationship can be more specifically defined as whether a particular particle is negligible relative to other particles in the sorting determination process.

[0519] By setting cell populations 1 and 2 as particle populations (a), cell population 3 as particle populations (b), and cell population 0 as particle populations (c), the above... Figure 17 Both mode 1 and mode 2 are possible.

[0520] Furthermore, by using rule data that sets the total number of particles (a) to (c), it is possible to determine that multiple types of target particles are assigned to multiple different paths. Therefore, multiple types of target particles can be selectively collected into multiple specified collection containers through a single sorting operation.

[0521] For this allocation of multiple paths, preferably, in addition to the rule data described above, rule data for determining the overlap of paths assigned to particles is also used.

[0522] (5-2) Example of determining the processing flow

[0523] Reference Figure 18A , Figure 18B and Figure 18C and Figure 19 Describe a specific example of using rule-based data for sorting and determining the process. Figure 18A A path assignment table is shown that relates to the assignment of paths to the particle population during processing. Figure 18B This shows rule data that defines whether a particular particle can be ignored in sorting determination from the perspective of different particles. Figure 18C The data shows rule data for determining the path of a target particle based on the relationship between the paths assigned to two particles. Figure 19 An example flowchart of the sorting and determination process is shown. Figure 19 In addition to the flowchart, a diagram is shown to describe the sorting and determination process in case 8 above.

[0524] exist Figure 19 In step S201 shown, the determining unit 201 acquires information about the characteristics of light generated by illuminating the particles that are the sorting targets. For example, the information about the characteristics of the light can be based on the light detected by the detection unit as described above.

[0525] In step S202, the determining unit 201 determines which particle population a particle belongs to based on the light generated by illuminating the particles flowing in the flow path. Specifically, the determining unit 201 determines the particle population to which the particle, which is the target for sorting, belongs based on the information about the light properties obtained in step S201. Specifically, the determining unit 201 determines which of the cell populations 0, 1, 2, 3, and 4 the particle belongs to based on this information.

[0526] For example, regarding case 8, such as Figure 19As shown, the determining unit 201 determines that the microparticles used as the sorting target belong to cell population 1.

[0527] In step S203, the determining unit 201 determines the path of the particles that are the sorting targets based on the number of particles determined in step S202. For example, in this specification, the determining unit 201 may refer to path allocation data in which a particle population and the paths that particles belonging to that particle population should traverse are associated with each other. For example, the path allocation data may be data that defines, based on the type of the particle population, whether the path that particles belonging to that particle population should travel is the path traveled by particles that are the sorting targets or not. For example, the path allocation data may be as follows: Figure 18A , Figure 18B and Figure 18C The path allocation table shown.

[0528] In step S203, specifically, when the particles belong to cell population 1 or 2, such as Figure 18A , Figure 18B and Figure 18C As shown, the particle's path is specified as "0". If the particle belongs to cell population 0 or 3, the particle's path is specified as path "2". If the particle belongs to cell population 4, the particle's path is specified as path "1".

[0529] Regarding case 8, since the particles used as targets for sorting belong to cell population 1, such as... Figure 19 As shown, therefore, unit 201 is determined by reference. Figure 18A The path assignment table in the table assigns path 1 to the particle.

[0530] The paths described in the path allocation table will be described below.

[0531] Path 0 is the path taken by particles belonging to cell populations 1 and 2 that are the sorting targets, and particles that have traveled to Path 0 are collected into the collection container (hereinafter referred to as "collection container 0").

[0532] Path 1 is the path taken by particles belonging to cell population 4 that are the sorting target, and particles that have traveled to Path 1 are collected into another collection container (hereinafter referred to as "collection container 1").

[0533] Path 2 is the path that non-sorting target particles travel through, and particles that have traveled to Path 2 are collected into another collection container (hereinafter referred to as "collection container 2").

[0534] For example, it can be like Figure 15 The configuration path and collection container are shown. Note that... Figure 15 An illustrative example is shown, and the configuration of the path and collection container is not limited to... Figure 15 Those shown in the image.

[0535] By applying a charge to the droplets containing particles in the sorting unit and deflecting the droplets using a deflector plate, control can be performed to move the droplets toward path 0, 1, or 2. For example, this process is performed as follows.

[0536] For example, the forward movement of positively charged droplets containing particles toward path 0 can be achieved by deflecting the direction of travel of the droplets using a deflector plate in the sorting unit. The droplets containing particles are collected in a collection container 0 located before path 0.

[0537] The movement to path 1 can be achieved by deflecting the negatively charged droplets containing particles in the sorting unit by using a deflector plate. The droplets containing particles are collected in a collection container 1 located before path 1.

[0538] The movement to path 2 is accomplished by moving an uncharged droplet containing particles in a straight line without being deflected by the deflector plates in the sorting unit. The droplet containing particles is collected in a collection container 2 located before path 2.

[0539] In step S204, the determining unit 201 determines whether there are different particles within a predetermined range around the particle that is the target for sorting.

[0540] Specifically, the determination unit 201 determines whether there are other particles within a predetermined range in front of or behind the particle to be processed in steps S201 to 203, in the direction of travel. This determination can be based on the time when light generated by light radiation onto the particle that is the target for sorting has been detected and the time when light generated by light radiation onto particles flowing in front of and / or behind the particle has been detected. For example, if the absolute value of the difference between these times is less than or equal to a predetermined value, the determination unit 201 determines that there are different particles. If the absolute value is greater than the predetermined value, the determination unit 201 determines that there are no other particles.

[0541] In step S204, if the determining unit 201 determines that different particles exist within a predetermined range around the particle that is the target for sorting, the determining unit 201 proceeds the process to step S205. If the determining unit 201 determines that no other particles exist within the predetermined range around the particle that is the target for sorting, the determining unit 201 proceeds the process to step S209.

[0542] Regarding case 8, determining unit 201 determines that there are two particles within a predetermined range and causes the process to proceed to step S205.

[0543] As described above, in an advantageous embodiment of this disclosure, the determining unit determines whether different particles exist within a predetermined range around the particle that is the target for sorting. When the determining unit determines that different particles exist within the predetermined range, the determining unit can use rule data for determination. As a result, rule data can be used only when necessary for determination, reducing unnecessary processing.

[0544] Furthermore, in the process of this example, after the specifying step (steps S201 to S203) which specifies the path of the particles to be determined as the sorting target, the existence determination step (step S204) is performed to determine whether different particles exist within a predetermined range. However, the existence determination step can be performed first, and then the specification step can be performed in the determination process according to the first embodiment of this disclosure.

[0545] In step S205, the determining unit 201 determines the particle group to which other particles existing within the specified range belong. This determination can be performed similarly to steps S201 and S202 described above.

[0546] Regarding case 8, the determining unit 201 determines that the particles present in front of the particles that are the sorting targets belong to cell population 3, and determines that the particles present behind the particles that are the sorting targets belong to cell population 2.

[0547] In step S206, the determining unit 201 determines the relationship between each particle in a particle group consisting of the particle used as the sorting target and different particles within a predetermined range, and all the different particles in the particle group. The determining unit 201 may use rule data to determine the relationship, which defines whether each particle is negligible relative to all the different particles.

[0548] More specifically, first, the reference rule data of the unit 201 is determined. This rule data defines the relationship between particles based on the particle group to which the particle that is the target of sorting (i.e., the particle to be processed in steps S201 to S203) belongs and the particle group to which different particles (i.e., the particle to be processed in step S105) within a predetermined range around the particle belong, and specifies the relationship between specific particles and different particles within the predetermined range.

[0549] More specifically, this relationship can be about whether a specific particle within a predetermined range is negligible relative to different particles, and even more specifically, about whether a specific particle within a predetermined range is negligible in the processing after sorting different particles. The relationship can be appropriately set according to the processing after the sorting operation. For example, user-defined relationships for operations performed after sorting, and rule data can be set according to these settings.

[0550] Examples of rule data include Figure 18BThe table shown is titled "Rule Data". Figure 18B The rule data shown specifies a value of 0 or 1 based on the type of cell population to which a specific particle belongs, and the types of cell populations to which different particles belong (in... Figure 18B The value is represented by an underscore 0 or 1. "0" indicates that a particular particle is not negligible relative to other particles. "1" indicates that a particular particle is negligible relative to other particles.

[0551] For example, if a particular particle belongs to a cell population of 1 and different particles belong to any cell population, determining unit 201 will specify the relationship between the particles as "0". This also applies to cases where a specific particle belongs to a cell population of any one of 0, 2, and 4.

[0552] Furthermore, when a particle belongs to one of three cell populations and different particles belong to cell populations 1 or 2, the determination unit 201 specifies the relationship between particles as "1", meaning that a particle is determined to be negligible relative to different particles. Conversely, when a particle belongs to one of three cell populations and different particles belong to cell populations 0, 3, and 4, the determination unit 201 specifies the relationship between particles as "0", meaning that different particles cannot ignore the particle.

[0553] Regarding case 8, the determining unit 201 determines the relationship between the particle that is the target for sorting and the particles existing before and after the particle. Since the particle that is the target for sorting belongs to cell population 1 and the particles existing before the particle belong to cell population 3, the determining unit 201 refers to coarse data and specifies the relationship between the two particles as "0". Similarly, the determining unit 201 specifies the relationship between the particle that is the target for sorting and the particles existing after the particle as "0".

[0554] The determining unit 201 also specifies the relationship between the particles in front of the particle and each particle that is the sorting target, as well as the particles behind the particle. Since the particles in front of the particle belong to cell population 3, and the particles that are the sorting targets belong to cell population 1, the determining unit 201 refers to the rule data and specifies the relationship between the two particles as "1". Similarly, the determining unit 201 specifies the relationship between the particles in front of the particle and the particles behind the particle as "1".

[0555] The determining unit 201 also specifies the relationship between particles existing behind a particle and each particle that is the sorting target, as well as particles existing in front of the particle. Since the particles existing behind the particle belong to cell population 2, while the particles that are the sorting targets belong to cell population 1, the determining unit 201 refers to the rule data and specifies the relationship between the two particles as "0". Similarly, the determining unit 201 specifies the relationship between particles existing behind a particle and particles existing in front of the particle as "0".

[0556] That is, the rule data specifies that a particle is negligible relative to different particles when it belongs to a population of negligible particles (b) (cell population 3 in this example) and different particles belong to a population of sorted particles (a) (cell population 1 or 2 in this example). Furthermore, in other cases, the rule data defines a particular particle as not negligible relative to different particles. By using rule data defined in this way, it is possible to collect particles along with target particles when negligible particles (such as red blood cells) are present within a predetermined range. As a result, the collection rate of target particles can be improved.

[0557] In step S206, the determining unit 201 further determines whether the particles are negligible in the sorting determination based on the relationship specified above.

[0558] For example, if the relationship between a certain particle and different particles within a specified range is negligible, the particle is determined to be negligible; otherwise, if the relationship between a certain particle and different particles within a specified range is not negligible, the particle is determined to be non-negligible.

[0559] Regarding case 8, as described above, the relationship specified for the two different particles that are the target particles for sorting is "0". Therefore, the determination unit 201 determines that the particle that is the target particles for sorting is "not negligible". Furthermore, for the two different particles that exist before the particle, both specified relationships are "1" as described above. Therefore, the determination unit 201 determines that the particle that exists before the particle is "negligible". Furthermore, for the two different particles that exist after the particle, the specified relationship is "0" as described above. Therefore, the determination unit 201 determines that the particle that exists before the particle is not "negligible".

[0560] In step S207, the determining unit 201 specifies the paths of all particles that were determined to be non-negligible in step S206. That is, the determining unit 201 does not need to specify the paths of particles that were determined to be negligible in step S206. For example, the path assignment table can be referenced to perform the path specification.

[0561] Regarding case 8, the determining unit 201 determines the particle that is the sorting target and the path of the particles that exist behind that particle, wherein the sorting target was determined to be non-negligible in step S206. The determining unit 201 refers to the path allocation table and specifies that the path of the particle that is the sorting target is path 0 (in...). Figure 19 (This is shown as "flow 0"). Similarly, the determining unit 201 specifies that the path of the particle existing behind the particle is path 0 (shown as "flow 0").

[0562] As described above, in the first embodiment of the present invention, the determining unit, as a result of determining the relationship, does not assign a path to the particle determined to be negligible for all different particles, and assigns a path to the particles other than the particles determined to be negligible.

[0563] In step S208, the determining unit 201 finally determines the path of the particles that are the sorting targets on the path specified in step S207. As a result, it is determined whether the particles that are the sorting targets are sorted. In addition, a container in which the particles that are the sorting targets are to be collected is also determined.

[0564] For example, if more than two paths for particles are specified in step S207 (i.e., if more than two paths are specified), the determining unit 201 can refer to Figure 18C The rule data is shown, and finally, in step S208, the path of the droplet containing the particle as the sorting target is determined. The rule data defines that if the path specified in step S207 matches this path, the path is the path of the droplet containing the particle as the sorting target; and defines whether the path of the droplet containing the particle as the sorting target is the path traveled by the particle if the path specified in step S207 does not match this path. In the first embodiment of the invention, a path can be associated with a collection container. As a result, when a path is specified, a collection container for collecting droplets containing particles is also specified.

[0565] Regarding case 8, since the paths of the two particles specified in step S207 are both "0", the determination unit 201 refers to the rule data and specifies the path of the droplet containing the particle as the sorting determination target as path 0.

[0566] Step S209 illustrates an example of the process performed by the determining unit 201 when no other particles are present within a predetermined range. In step S209, the determining unit 201 determines the path specified in step S203 as the path of the particles to be sorted. As a result, it is determined whether to sort the particles to be sorted, and a container is determined where the particles to be sorted are collected.

[0567] In step S210, the determining unit 201 transmits the determination result obtained in step S208 or S209 to the sorting control unit 202. Based on the determination result, the sorting control unit 202 controls the particle sorting device (specifically, the sorting unit) to guide the movement direction of droplets containing particles determined as sorting targets to a designated path. As a result, the particles determined as sorting targets are collected into a collection container associated with the designated path.

[0568] Regarding case 8, in step S208, path 0 has been designated as the path containing the droplet containing the particle determined as the sorting target. The determination unit 201 transmits the determination result to the sorting control unit 202. Based on this determination result, the sorting control unit 202 controls the sorting unit to guide the droplet to path 0 and causes the droplet to travel along path 0. As a result, the particle determined as the sorting target is collected in the collection container 0.

[0569] The determination unit 201 performs the above-described sorting determination process for each particle that is the target of sorting determination.

[0570] (5-3) Various sorting determination modes are achieved by changing the rule data.

[0571] Furthermore, regarding the particle sorting device 200, the determination unit 201 can be configured to change the rule data used in the determination process. As a result, by changing the rule data used in the determination process, various determination modes can be implemented, such as determination modes for improving the collection rate of the target cell and determination modes for improving the purity of the target cell. Therefore, various needs of the device user can be met.

[0572] The following explains how various sorting determination modes can be achieved by changing the rule data in cases 1 to 9 described in (5-1) above. Note that the gating of the cell population used in the following sorting determination modes is the same as that described in (5-1) above.

[0573] (5-3-1) Example of sorting and determination treatment that emphasizes the purity of target cells and increases the collection rate

[0574] Reference Figure 20A , Figure 20B and Figure 20C and Figure 21 This describes an example of the sorting and determination process. This sorting and determination process implements the above-mentioned reference. Figure 17 Sorting determination mode 2.

[0575] Figure 20A The path allocation table is shown as described above. Figure 20BThis illustrates rule data defining whether a particular particle is negligible in sorting determination from the perspective of its relationship with different particles. Figure 20C The diagram illustrates rule data for defining the paths of droplets as targets for sorting, based on path-based relationships. These diagrams are related to those above. Figure 18A , Figure 18B and Figure 18C The same as those described in the text.

[0576] Figure 21 An example of the sorting determination result is shown when sorting determination is performed using rule data.

[0577] Figure 21 The sorting results for cases 1 through 9 are shown. The sorting process for cases 1 through 9 will be described below.

[0578] (Regarding scenarios 1 through 4)

[0579] In cases 1 to 4, since there are no other particles within a predetermined range around the particle that is the target for sorting, in step S204, the determining unit 201 advances the process to step S209. To this end, based on the path specified in steps S201 to S203, the determining unit 201 determines the path of the particle that is the target for sorting in step S209.

[0580] Each case will be described below.

[0581] In Case 1, in step S202, determining unit 201 determines that the particle designated as the sorting target belongs to cell population 0. In step S203, based on the fact that the particle designated as the sorting target has been assigned to cell population 0, determining unit 201 designates "2" as the path of the particle, that is, designates the path of the particle as the path to the collection container (collection container 2), and particles that are not the sorting target will be collected. In step S209, determining unit 201 finally determines that the path designated in step S203 is the path of the particle.

[0582] In scenario 2, in step S202, determining unit 201 determines that the particles targeted for sorting belong to cell population 1. In step S203, based on the fact that the particles targeted for sorting have been designated as belonging to cell population 1, determining unit 201 designates "0" as the path of the particles, that is, designates the path of the particles as the path to the collection container (collection container 0), in which particles belonging to cell populations 1 and 2, which are the particles targeted for sorting, will be collected. In step S209, determining unit 201 finally determines that the path designated in step S203 is the path of the particles.

[0583] In case 3, in step S202, determining unit 201 determines that the particle designated as the sorting target belongs to cell population 4. In step S203, based on the fact that the particle designated as the sorting target has been assigned to cell population 4, determining unit 201 assigns "1" as the path of the particle, and designates the path of the particle as a path leading to the collection container (collection container 1), in which the particle belonging to cell population 4 is the particle to be sorted. In step S209, determining unit 201 finally determines that the path assigned in step S203 is the path of the particle.

[0584] In scenario 4, in step S202, determining unit 201 determines that the particles targeted for sorting belong to cell population 3. In step S203, based on the fact that the particles targeted for sorting have been designated as belonging to cell population 3, determining unit 201 designates "2" as the path of the particles, that is, designates the path of the particles as the path to the collection container (collection container 2), in which particles that are not the sorting targets are collected. In step S209, determining unit 201 finally determines that the path designated in step S203 is the path of the particles.

[0585] (Regarding situations 5 through 9)

[0586] In cases 5 to 9, unlike cases 1 to 4, since different particles exist within a predetermined range (protection time) around the particle that is the target for sorting, in step S204, the determining unit 201 advances the process to step S205.

[0587] Each case will be described below.

[0588] Regarding case 5, in step S203, the determining unit 201 designates “0” as the path of the particle as the sorting target, that is, designates the path of the particle as the path leading to the collection container (collection container 0), in which the particles belonging to cell populations 1 and 2 as the sorting target particles are collected.

[0589] Next, in step S205, the determining unit 201 determines that the different particles present behind the particles that are the sorting determination target belong to cell population 0.

[0590] Next, in step S206, the determining unit 201 refers to rule data that defines the relationship between particles based on the particle group to which the particle to which the particle being determined as the sorting target belongs and the particle groups to which different particles within a predetermined range around the particle belong. Figure 20B The rules shown are defined, and the relationship between the previous particle and the next particle is specified.

[0591] Since the particles that are the targets for sorting belong to cell population 1 and the different particles belong to cell population 0, the determination unit 201 refers to the rule data and specifies "0" (non-negligible) as the relationship relative to the particles that are the targets for sorting and "0" (non-negligible) as the relationship relative to the different particles.

[0592] In step S206, the determining unit 201 determines whether a particle is negligible in the sorting determination for each particle based on the relationship specified above. As described above, since "0" is specified for any particle, the determining unit 201 determines that no particle can be ignored.

[0593] Next, in step S207, the determining unit 201 determines the paths of all particles that were determined to be non-negligible in step S206. That is, the determining unit 201 assigns a path of "0" to the particles that are the sorting targets, and assigns a path of "2" to different particles.

[0594] In step S208, the determining unit 201 finally determines the path of the particle that is the sorting target based on the path specified in step S207. Since the two paths are inconsistent with each other, the determining unit 201 determines whether the path of the droplet containing the particle that is the sorting target is the path traveled by the particle.

[0595] More specifically, in step S208, since the paths of more than two particles were specified in step S207, the determining unit 201 refers to, for example... Figure 20C The rules shown are used to determine the paths of the droplets, ultimately identifying the paths of droplets containing particles that are the targets for sorting. In the rules data, if one particle's path is "0" and another particle's path is "2", the final path is defined as "2" (in...). Figure 20C (Indicated by underlined italics). Therefore, the determining unit 201 ultimately determines that the path of the droplets containing the particles that are the sorting targets is the path to the collection container (collection container 2), in which particles that are not the sorting targets are collected.

[0596] Next, in step S210, the determining unit 201 transmits the sorting determination result obtained in step 208 to the sorting control unit 202.

[0597] Regarding case 6, in step S203, the determining unit 201 designates “0” as the path of the particle that is the target of sorting, that is, the path of the particle that is the path leading to the collection container (collection container 0), in which the particles belonging to cell populations 1 and 2 that are the target particles of sorting are collected.

[0598] Next, in step S205, the determining unit 201 determines that the different particles existing before the particles that are the sorting targets belong to cell population 4.

[0599] Next, in step S206, the determining unit 201 refers to rule data that defines the relationship between particles based on the particle group to which the particle being determined as the sorting target belongs and the particle groups to which different particles within a predetermined range around the particle belong. Figure 20B (The rules data shown in the figure) specify the relationship between the previous particle and the next particle.

[0600] Since the particles that are the targets for sorting belong to cell population 1, and different particles belong to cell population 4, the determination unit 201 refers to the rule data and specifies "0" (non-negligible) as the relationship for the particles that are the targets for sorting, and specifies "0" (non-negligible) as the relationship for different particles.

[0601] In step S206, the determining unit 201 further determines, based on the relationship specified above, whether a particle is negligible in the sorting determination for each particle. As described above, since "0" is specified for any particle, the determining unit 201 determines that no particle can be ignored.

[0602] Next, in step S207, the determining unit 201 determines the paths of all particles that were determined to be non-negligible in step S206. That is, the determining unit 201 assigns a path of "0" to the particles that are the sorting targets, and assigns a path of "1" to different particles.

[0603] In step S208, the determining unit 201 finally determines the path of the particle that is the sorting target based on the path specified in step S207. Specifically, because the two paths are inconsistent with each other, the determining unit 201 determines whether the path of the droplet containing the particle that is the sorting target is the path traveled by the particle.

[0604] More specifically, in step S208, since a path was specified for each of the two or more particles in step S207, determining unit 201 refers to, for example... Figure 20C The rules shown are used to determine the paths of droplets containing particles that are the targets for sorting. In the rules data, if one particle's path is "0" and another particle's path is "1", the final path is defined as "2" (in...). Figure 20C (Indicated by underlined italics). Therefore, the determining unit 201 ultimately determines that the path of the droplets containing the particles that are the sorting targets is the path to the collection container (collection container 2), in which particles that are not the sorting targets are collected.

[0605] Next, in step S210, the determining unit 201 transmits the sorting determination result obtained in step 208 to the sorting control unit 202.

[0606] Regarding case 7, in step S203, the determining unit 201 designates “0” as the path of the particle as the sorting target, that is, designates the path of the particle as the path to the collection container (collection container 0), in which the particles belonging to cell populations 1 and 2 as the sorting target particles are collected.

[0607] Next, in step S205, the determining unit 201 determines that the different particles present behind the particles that are the sorting determination targets belong to cell population 2.

[0608] Next, in step S206, the determining unit 201 refers to rule data that defines the relationship between particles based on the particle group to which the particle being determined as the sorting target belongs and the particle groups to which different particles within a predetermined range around the particle belong. Figure 20B (The rules data shown in the figure) and specify the relationship between the previous particle and the next particle.

[0609] Since the particles that are the targets for sorting belong to cell population 1 and different particles belong to cell population 2, the determination unit 201 refers to the rule data and specifies "0" (non-negligible) as the relationship for the particles that are the targets for sorting and "0" (non-negligible) as the relationship for different particles.

[0610] In step S206, the determining unit 201 determines whether a particle is negligible in the sorting determination for each particle based on the relationship specified above. As described above, since "0" is specified for any particle, the determining unit 201 determines that no particle can be ignored.

[0611] Next, in step S207, the determining unit 201 determines the paths of all particles that were determined to be non-negligible in step S206. That is, the determining unit 201 assigns a path of "0" to the particles that are the sorting targets, and assigns a path of "0" to different particles.

[0612] In step S208, the determining unit 201 finally determines the path of the particle that is the sorting target based on the path specified in step S207. Specifically, because the two paths are consistent with each other, the determining unit 201 determines that the path of the droplet containing the particle that is the sorting target is the path traveled by the particle that is the sorting target.

[0613] Since the paths of more than two particles are specified in step S207, the determination unit 201 refers to, for example... Figure 20C The rules data are shown, and the paths of droplets containing particles as the sorting targets are ultimately determined. In the rules data, if the path of one particle is "0" and the paths of different particles are "0", the final path is defined as "0" (in...). Figure 20C (Indicated by underlined italics). To this end, the determining unit 201 designates "0" as the path of the droplet containing the microparticles that are the sorting targets, that is, designates the path of the droplet as the path leading to the collection container (collection container 0), in which microparticles belonging to cell populations 1 and 2 that are the microparticles that are the sorting targets are collected.

[0614] Next, in step S210, the determining unit 201 transmits the sorting determination result obtained in step 208 to the sorting control unit 202.

[0615] Regarding case 8, in step S203, the determining unit 201 designates "0" as the path of the particle as the sorting target, that is, designates the path of the particle as the path leading to the collection container (collection container 0), in which the particles belonging to cell populations 1 and 2 as the sorting target particles are collected.

[0616] Next, in step S205, the determining unit 201 determines that the different particles present in front of the particle that is the target of sorting belong to cell population 3, and the different particles present behind the particle that is the target of sorting belong to cell population 2.

[0617] Next, in step S206, the determining unit 201 refers to rule data that defines the relationship between particles based on the particle group to which the particle being determined as the sorting target belongs and the particle groups to which different particles within a predetermined range around the particle belong. Figure 20B (The rules data shown in the figure) and specify the relationship between the previous particle and the next particle.

[0618] For the particle (belonging to cell population 1) that is the target for sorting, the relationship between the particle and the particles in front of it is "0" according to the rule data, and the relationship between the particle and the particles behind it is also "0" according to the rule data. Therefore, the determination unit 201 determines that the particle that is the target for sorting in the sorting determination is non-negligible relative to different particles.

[0619] For particles located in front of the microparticle (belonging to cell population 3), the relationship between the microparticle and the target microparticle for sorting is "1" according to the rule data, and the relationship between the microparticle and the microparticle located behind the microparticle is also "1" according to the rule data. Therefore, the determination unit 201 determines that the microparticle located in front of the microparticle is negligible relative to different microparticles in the sorting determination.

[0620] For particles located behind the main particle (belonging to cell population 2), the relationship between them and the particles that are the target for sorting is "0" according to the rule data, and the relationship between them and the particles located in front of the main particle is also "0" according to the rule data. Therefore, the determination unit 201 determines that the particles located in front of the main particle are not negligible relative to different particles in the sorting determination.

[0621] Next, in step S207, the determining unit 201 specifies the paths of all particles that were determined to be non-negligible in step S206, that is, the paths of the particles that are the sorting targets and the particles that exist after the particles. Specifically, the determining unit 201 specifies "0" for the paths of the particles that are the sorting targets and "0" for the paths of the particles that exist after the particles.

[0622] In step S208, the determining unit 201 finally determines the path of the particle that is the sorting target based on the path specified in step S207. Specifically, since the two paths are consistent with each other, the determining unit 201 determines that the path of the droplet containing the particle that is the sorting target is the path traveled by the particle that is the sorting target.

[0623] More specifically, in step S208, since the paths of the two particles were specified in step S207, the determining unit 201 refers to, for example... Figure 20C The rules shown are used to determine the paths of droplets containing particles that are the targets for sorting. In the rules data, if the path of one particle is "0" and the paths of different particles are both "0", the final path is defined as "0" (in...). Figure 20C (Indicated by underlined italics). To this end, the determining unit 201 assigns "0" as the path containing the droplet that is the particle that is the sorting target, that is, the path of the final determined droplet is the path to the collection container (collection container 0), in which the particles belonging to cell populations 1 and 2 that are the particles that are the sorting target are collected.

[0624] Next, in step S210, the determining unit 201 transmits the sorting determination result obtained in step 208 to the sorting control unit 202.

[0625] Regarding case 9, in step S203, the determining unit 201 designates "0" as the path of the particle as the sorting target, that is, designates the path of the particle as the path leading to the collection container (collection container 0), in which the particles belonging to cell populations 1 and 2 as the sorting target particles are collected.

[0626] Next, in step S205, the determining unit 201 determines that the different particles present behind the particles that are the sorting determination targets belong to cell population 3.

[0627] Next, in step S206, the reference rule data for unit 201 is determined, and the relationship between the two particles is specified. Figure 20B The rule data shown defines the relationship between particles based on the particle population to which the particle being identified as the sorting target belongs and the particle population to which different particles within a predetermined range around the particle belong.

[0628] Regarding the particle (belonging to cell population 1) that serves as the target for sorting, according to the rule data, its relationship with the particles that exist behind it is "0". Therefore, the determination unit 201 determines that the particle that serves as the target for sorting in the sorting determination is non-negligible relative to different particles.

[0629] Regarding the particles (belonging to cell population 3), the relationship between the particles following them and the particles that are the sorting-determination targets is "1" according to the rule data. Therefore, the determination unit 201 determines that the particles following the particles in the sorting determination are negligible relative to the different particles.

[0630] Next, in step S207, the determining unit 201 specifies the paths of all particles that were determined to be non-negligible in step S206 (i.e., only the particles that are the sorting targets). That is, the determining unit 201 specifies a path of "0" for the particles that are the sorting targets.

[0631] In step S208, the determining unit 201 finally determines the path of the particle as the sorting target based on the path specified in step S207.

[0632] More specifically, in step S208, since the path was only specified for the particles that are the target of sorting in step S207, the determination unit 201 finally determines that the specified path "0" is the final path.

[0633] Next, in step S210, the determining unit 201 transmits the sorting determination result obtained in step 208 to the sorting control unit 202.

[0634] As described above, by using the definition as Figure 20A , Figure 20B and Figure 20C The rule data showing whether the particles are negligible can be used as a reference. Figure 17 The described sorting and determination mode 2 is implemented to achieve a sorting and determination process that emphasizes the purity of target cells and improves the collection rate of target cells.

[0635] Note that the rule data can be defined as follows.

[0636] The rule data specifies that a particle is negligible relative to the other particles if it belongs to a population of negligible particles (b) (cell population 3 in this example) within a defined range, and different particles belong to a population of particles to be sorted (a) (cell population 1 or 2 in this example). Furthermore, in other cases, the rule data defines a particular particle as not negligible relative to the other particles. By using rule data defined in this way, it is possible to collect the target particles along with the negligible particles (such as red blood cells) even when they are present within a predetermined range. As a result, the collection rate of the target particles can be improved.

[0637] (5-3-2) Example of sorting and determining the purity of target cells

[0638] Reference Figure 22A , Figure 22B and Figure 22C and Figure 23 This describes an example of the sorting and determination process. This process emphasizes the purity of the target cells and achieves the results described above. Figure 17 The sorting determination mode 1 is described.

[0639] Figure 22A The path allocation table is as described above. Figure 22B The data shows rule data that defines whether a particular particle can be ignored in sorting determination from the perspective of its relationship with different particles. Figure 22C The diagram illustrates rule data for defining the paths of droplets that serve as the sorting targets for particle identification, based on path-based relational definitions.

[0640] Figure 23 An example of the sorting determination result is shown when sorting determination is performed using rule data.

[0641] Figure 23 The sorting results for cases 1 through 9 are shown. The sorting process for cases 1 through 9 will be described below.

[0642] (Regarding scenarios 1 through 4)

[0643] In cases 1 through 4, the same processing as described above (5-3-1) for cases 1 through 4 is performed, and the same processing results are obtained.

[0644] (Regarding situations 5 through 9)

[0645] Furthermore, for cases 5 to 7, the same processing as described in cases 5 to 7 in (5-3-1) above is performed, and the same processing results are obtained.

[0646] For cases 8 and 9, a different determination process than the determination process described in (5-3-1) above is executed. These cases will be described below.

[0647] Regarding case 8, in step S203, the determining unit 201 designates "0" as the path of the particle as the sorting target, that is, designates the path of the particle as the path leading to the collection container (collection container 0), in which the particles belonging to cell populations 1 and 2 as the sorting target particles are collected.

[0648] Next, in step S205, the determining unit 201 determines that the different particles present in front of the particle that is the target of sorting belong to cell population 3, and the different particles present behind the particle that is the target of sorting belong to cell population 2.

[0649] Next, in step S206, the determining unit 201 refers to rule data that defines the relationship between particles based on the particle group to which the particle being determined as the sorting target belongs and the particle groups to which different particles within a predetermined range around the particle belong. Figure 22B (The rules shown are data), and the relationship between the previous and next particles is specified. Figure 20B The rule data shown is different. Figure 22B The rule data shown does not include "1". Therefore, when using this rule data, it is determined that particles cannot be ignored.

[0650] For the particle (belonging to cell population 1) that is the target for sorting, the relationship between the particle and the particles in front of it is "0" according to the rule data, and the relationship between the particle and the particles behind it is also "0" according to the rule data. Therefore, the determination unit 201 determines that the particle that is the target for sorting in the sorting determination is non-negligible relative to different particles.

[0651] For particles present in front of the microparticle (belonging to cell population 3), the relationship between the microparticle and the microparticle being determined as the sorting target is "0" according to the rule data, and the relationship between the microparticle and the microparticle present behind the microparticle is also "0" according to the rule data. Therefore, the determination unit 201 determines that the microparticles present in front of the microparticle in the sorting determination are not negligible relative to different microparticles.

[0652] For particles located behind the microparticle (belonging to cell population 2), the relationship between the microparticle and the target microparticle for sorting determination is "0" according to the rule data, and the relationship between the microparticle and the microparticle located in front of the microparticle is also "0" according to the rule data. Therefore, the determination unit 201 determines that the microparticle located in front of the microparticle in the sorting determination is not negligible relative to different microparticles.

[0653] Next, in step S207, the determining unit 201 specifies the paths of all particles determined to be non-negligible in step S206 (i.e., particles that are the sorting targets, particles existing in front of the particles, and particles existing behind the particles). Specifically, the determining unit 201 specifies a path of "0" for the particles that are the sorting targets, and also specifies a path of "0" for particles existing after the particles. Simultaneously, the determining unit 201 specifies a path of "2" for particles existing behind the particles.

[0654] In step S208, the determining unit 201 finally determines the path of the particles that are the sorting targets based on the path specified in step S207. Specifically, since the three paths are inconsistent with each other, the determining unit 201 designates path "2" through which the particles that are not the sorting targets travel as the path of the droplets containing the particles that are the sorting targets. That is, the path of the droplets is finally determined as the path to the collection container (collection container 2), in which the particles that are not the sorting targets are collected.

[0655] Next, in step S210, the determining unit 201 transmits the sorting determination result obtained in step 208 to the sorting control unit 202.

[0656] As described above, by using Figure 22A , Figure 22B and Figure 22C The rules shown in the figure define whether a relationship is negligible, and can be used for reference. Figure 17 The described sorting method is mode 1 and can increase the purity of target cells.

[0657] Note that the rule data can be defined as follows.

[0658] This rule data specifies that if a particle belongs to any of the particle groups (a) to (c) within a defined range, that particle is non-negligible relative to the other particles. By using this defined rule data, the purity of the target particle can be improved.

[0659] (5-3-3) Example of considering narrow-range sorting determination process in sorting determination

[0660] In (5-3-1) and (5-3-2) above, the range of particle presence considered in the sorting determination is set to include not only the droplet containing the particle as the target of sorting determination, but also a portion of the droplet in front of and behind the droplet. This is to eliminate the possibility that particles contained in the droplet in front of and behind the droplet are contained in the droplet containing the particle as the target of sorting determination, and to improve the purity of the target particle. However, in some cases, the collection rate is more important than purity. In such cases, the range can be narrowed. By narrowing the range, the collection rate of the target particle can be increased. As an example of such a case, the following will refer to Figure 24A , Figure 24B and Figure 24C and Figure 25 The description covers the results of a sorting process where the range is set to include droplets containing particles that are the target particles for sorting, but excludes droplets in front of and behind these droplets.

[0661] Figure 24A , Figure 24B and Figure 24C The path assignment table and rule data used in the sorting determination process are shown, and they are the same as those described above (5-3-2). Figure 25 This is a diagram showing the results of the sorting and determination process. For example... Figure 25 As shown, Figure 25 The range of particles to be considered in the sorting determination is narrower than that described in (5-3-2) above. Figure 23 The range of particles to be considered in the sorting process.

[0662] (Regarding scenarios 1 through 4)

[0663] In cases 1 through 4, the same processing as described above (5-3-2) for cases 1 through 4 is performed, and the same processing results are obtained.

[0664] (Regarding situations 5 through 9)

[0665] Regarding case 5, since the range is narrowed, in step S204, determining unit 201 advances the process to step S209 because, unlike the case described above (5-3-2), there are no other particles within a predetermined range around the particle that is the target for sorting. As a result, the sorting determination process result in case 5 is the same as that in case 2. Consequently, the target particles discarded in (5-3-2) are also collected in collection container 0 in case 5.

[0666] Regarding cases 6 and 7, the range is narrowed, but the number of particles considered in the sorting determination remains unchanged. Therefore, the same sorting determination process as described above (5-3-2) is performed, and the same results are obtained.

[0667] Regarding case 8, since the range is narrowed, in step S204, the determining unit 201 advances the process to step S209 because, unlike the case described above (5-3-2), there are no other particles within a predetermined range around the particle that is the target for sorting. As a result, the sorting determination process result for case 8 is the same as that for case 2. Consequently, the target particles discarded in (5-3-2) above are also collected in the collection container 0 within the housing 5.

[0668] Regarding case 9, since the range is narrowed, in step S204, determining unit 201 advances the process to step S209 because, unlike the case described above (5-3-2), there are no other particles within a predetermined range around the particle that is the target for sorting.

[0669] In case 9, in steps S201 to S203, it is determined that the particles targeted for sorting belong to cell population 2, and the path of the particles is designated as "0". Therefore, in step S209, the determining unit 201 finally determines that the path of the particles targeted for sorting is "0", that is, the path of the particles is designated as a path leading to the collection container (collection container 0), and the particles belonging to cell populations 1 and 2 are collected in the collection container.

[0670] (5-3-4) Example of sorting and determining the collection rate of target cells.

[0671] In section (5-3-2) above, the sorting and determination process emphasizing the purity of target cells has been described. The collection rate of the target cells can be increased by changing the rule data referenced in step S208. The following will refer to... Figure 26A , Figure 26B and Figure 26C and Figure 27 Describe the sorting and identification process to improve the collection rate of target cells.

[0672] Figure 26A , Figure 26B and Figure 26C The path assignment table and rule data used in the sorting determination process are shown.

[0673] Figure 26A and Figure 26B The path assignment tables and rule data in this document are the same as those described above (5-3-2).

[0674] Figure 26C The rule data shown differs from that described in (5-3-2) above. Figure 26CIn this framework, path 0 has the highest priority, path 1 has the second highest priority, and path 2 has the lowest priority. That is, if particles assigned to path 0 are included in the range, even if particles assigned to path 1 or 2 are also included in the range, the path containing the droplet that is the target of sorting is defined as 0. If particles assigned to path 1 and particles assigned to path 2 are present in the range, the path containing the droplet that is the target of sorting is defined as 1. The path containing the droplet that is the target of sorting is defined as 2 only if the droplet in the range exists only for particles on path 2.

[0675] (Regarding scenarios 1 through 4)

[0676] For cases 1 to 4, perform the same processing as described in cases 1 to 4 in (5-3-2) above, and obtain the same processing results.

[0677] (Regarding situations 5 through 9)

[0678] Regarding case 5, in steps S201 to S207, the same processing as in (5-3-2) above is performed.

[0679] In step S208, the reference of unit 201 is determined. Figure 26C The rules shown are used to determine the paths of droplets containing particles that are the targets for sorting. In the rules data, if one particle's path is "0" and another particle's path is "2", the final path is defined as "0". Figure 26C (Described in underlined italics). To this end, the determining unit 201 ultimately determines that the path of the droplet containing the particles as the sorting target is the path to the collection container (collection container 0), in which the particles as the sorting target are collected.

[0680] Regarding case 6, in steps S201 to S207, the same processing as in (5-3-2) above is performed.

[0681] In step S208, the reference of unit 201 is determined. Figure 26C The rules shown are used to determine the paths of droplets containing particles that are the targets for sorting. In the rules data, if one particle's path is "0" and another particle's path is "1", the final path is "0" (in...). Figure 26C (Indicated by underlined italics). Therefore, the determining unit 201 ultimately determines that the path of the droplet containing the particles that are the sorting targets is a path to the collection container (collection container 0), in which the particles that are the sorting targets are collected.

[0682] Regarding case 7, in steps S201 to S207, the same processing as in (5-3-2) above is performed.

[0683] In step S208, the reference of unit 201 is determined. Figure 26C The rules shown are used to determine the paths of droplets containing particles that are the sorting targets. In the rules data, if the path for one particle is "0" and the paths for different particles are both "0", the final path is "0" (in...). Figure 26C (Indicated by underlined italics). Therefore, the determining unit 201 ultimately determines that the path of the droplet containing the particles that are the sorting targets is a path to the collection container (collection container 0), in which the particles that are the sorting targets are collected.

[0684] Furthermore, regarding case 8, in steps S201 to S207, the same processing as in (5-3-2) above is performed.

[0685] In step S208, the reference of unit 201 is determined. Figure 26C The rules shown are used to determine the paths of droplets containing the particles that are the sorting targets. Paths assigned to particles included in this range are "0" and "2". For any case where two paths are assigned to two particles and are "0" and "0", two paths are assigned to two particles and are "0" and "2", and two paths are assigned to two particles and are "2" and "0", the final path is defined as "0" (in...). Figure 26C (Indicated by underlined italics). Therefore, the determining unit 201 ultimately determines that the path of the droplet containing the particles that are the sorting targets is a path to the collection container (collection container 0), in which the particles that are the sorting targets are collected.

[0686] Regarding case 9, in steps S201 to S207, the same processing as in (5-3-2) above is performed.

[0687] In step S208, the reference of unit 201 is determined. Figure 26C The rules shown are used to determine the paths of droplets containing the particles that are the sorting targets. The paths assigned to particles within this range are "0" and "2". In the case where both paths assigned to two particles are "0" and "2", the final path is defined as "0" (in...). Figure 26C (Indicated by underlined italics). Therefore, the determining unit 201 ultimately determines that the path of the droplet containing the particles that are the sorting targets is a path to the collection container (collection container 0), in which the particles that are the sorting targets are collected.

[0688] (5-3-5) Example of a sorting determination process where sorting is determined only when the range considered in the sorting determination includes only one particle.

[0689] According to this disclosure, it can also be determined that particles are sorted only if the range considered in the sorting determination includes only one particle. This determination can further improve the purity of the target cells. (See reference...) Figure 28A , Figure 28B and Figure 28C and Figure 29 This describes the specific processing involved.

[0690] Figure 28A , Figure 28B and Figure 28C The path assignment table and rule data used in the sorting determination process are shown. Figure 28A The path allocation table and Figure 28B The rules in this context are the same as those described above (5-3-2). Figure 28C In the rule data, "2" is defined as the final path, regardless of the path assigned to each of the two particles. As a result, in cases where there are more than two particles in the range, the path that ultimately contains the droplet that is the target of sorting is determined as the path to the collection container (collection container 2), where particles that are not the target of sorting are collected.

[0691] Figure 29 This is a diagram used to describe the determined processing results using rule data in cases 1 through 9. Figure 29 In this process, the range of particles considered in the sorting determination is set to include not only the droplet containing the particle targeted for sorting determination, but also all droplets in front of and behind the droplet. This is to further improve the purity of the target particle.

[0692] (Regarding scenarios 1 through 4)

[0693] In cases 1 through 4, the same processing as described above (5-3-2) for cases 1 through 4 is performed, and the same processing results are obtained.

[0694] (Regarding situations 5 through 9)

[0695] For cases 5 to 9, the same processing as in (5-3-2) is performed in steps S201 to S207.

[0696] In step S208, the reference of unit 201 is determined. Figure 26C The rule data shown ultimately determines the path of the droplets containing the particles that are the sorting targets.

[0697] For example, regarding case 5, in the rule data, if one particle's path is "0" and another particle's path is "2", the final path is defined as "2" (in...). Figure 28C (Indicated by underlined italics). Therefore, the determining unit 201 ultimately determines that the path of the droplet containing the particles as the sorting target is the path to the collection container (collection container 2), in which the particles as the sorting target are collected.

[0698] In other cases, the determination unit 201 refers to the rule data and specifies the final path as "2", that is, the path containing the droplets that are the particles as the sorting targets is specified as the path to the collection container (collection container 2), in which the particles as the sorting targets are collected.

[0699] 2. Second Implementation Method (Particle Sorting Method)

[0700] This disclosure also provides a particle sorting method, comprising: a determination step, performing particle sorting determination using rule data, wherein the rule data defines relationships between particles based on the particle population to which the particle being sorted belongs and the particle populations to which different particles within a predetermined range surrounding the particle belong. The particle populations to which a particle may belong include the following:

[0701] (a) The particle population of particles to be sorted;

[0702] (b) A population of particles that were not sorted but are negligible in the determination; and

[0703] (c) A population of particles that are neither particles to be sorted nor negligible particles.

[0704] By performing the defined steps, the particles to be sorted can be collected at a high collection rate as described in section 1. That concludes the discussion.

[0705] Preferably, the negligible particles in the particle population (c) include red blood cells. Therefore, as described in section 1 above, red blood cells can be ignored in the determination step. As a result, the collection rate of target cells can be improved while suppressing the impact on subsequent operations such as culture and gene manipulation.

[0706] The determination step in the particle sorting method according to the second embodiment of this disclosure can be referenced. Figure 10 In Figure 10 and Figure 19 The described processing flow will be executed. That's all. Below, we will first explain the common steps of these two processing flows. Next, we will explain the unique processes specific to each processing flow.

[0707] (1) Steps common to both processing flows

[0708] The determination step may include a particle population determination step, which identifies the particle population to which the particle being targeted for sorting belongs. This step corresponds to the step described in reference 1. Figure 10 The described steps S102 and references Figure 19 Step S202 is described above. These steps are described in a way that applies to situations where a specific step exists.

[0709] Furthermore, the determination step may include a provisional determination step, which provisionally determines the path of the particles to be selected as the sorting target based on the determined total particle population. The provisional determination step corresponds to the reference step. Figure 10 The described steps S103 and references Figure 19 Step S203 is described above in section 1. The description of these steps applies to temporarily determined steps.

[0710] In a preferred embodiment of the present invention, the determining step includes a presence determining step of determining whether different particles exist within a predetermined range. In step 1, the presence determining step corresponds to the reference. Figure 10 The described steps S104 and references Figure 19 Step S204 is described above. These steps are described in a way that applies to situations where a specific step exists.

[0711] In an advantageous embodiment of this disclosure, the determining step may include a final determining step, which determines the path temporarily determined in the provisional determining step as the path of the particle to be the sorting target. This final determining step corresponds to the path referenced in 1. Figure 10 The described steps S108 and references Figure 19 Step S209 is described above. The description of these steps applies to the final determination steps.

[0712] In a preferred embodiment of the invention, the determining step includes a particle population determining step, which determines the particle population to which different particles belong. The particle population determining step corresponds to the reference step in 1. Figure 10 The described steps S105 and references Figure 19 Step S205 is described above. The description of these steps applies to the step of determining the total number of particles.

[0713] In a preferred embodiment of this disclosure, the determining step includes a relationship specifying step, which refers to rule data and specifies the relationship between multiple particles existing within a predetermined range. The relationship specifying step corresponds to referencing in step 1. Figure 10 The described steps S106 and references Figure 10 Step S206 is described above. The description of these steps applies to the relation description steps.

[0714] (2) Figure 10 The process flow is dedicated to specific steps.

[0715] In one embodiment of this disclosure, in the relationship specification step, reference is made to rule data and the relationship between the particle population to which the particle being identified as the sorting target belongs and the particle populations to which different particles belong is specified. This relationship specification step corresponds to the reference mentioned in section 1 above. Figure 10 Step S106 as described.

[0716] In one embodiment of this disclosure, the determination step includes a final determination step that determines whether to sort particles that are the target of the sorting determination, based on the path determined in the provisional determination step and the relationship specified in the relationship specification step. The final determination step corresponds to the step referenced in 1. Figure 10 Step S107 as described. That concludes the explanation.

[0717] (3) Figure 19 The unique steps in the processing flow

[0718] In different embodiments of this disclosure, during the relationship specification step, rule data can be referenced, and relationships with different particles can be specified for each particle existing within a predetermined range. The relationship specification step, which specifies relationships in this way, corresponds to a reference... Figure 19 Step S206 is described. In this embodiment, the relationship to be specified may be a relationship concerning whether the presence of different particles is negligible in the sorting determination.

[0719] In different implementations, the particle sorting method further includes a path designation step, which, based on the particle population to which the particles belong, designates the paths that the particles should traverse for all particles determined to be non-negligible in the relationship designation step. The path designation step corresponds to... Figure 19 Step S207. In the path specification step, for particles that are determined to be negligible in the path specification step, it is not necessary to specify the flow path that the particles should take.

[0720] In different implementations, the particle sorting method further includes a final determination step, which, based on the path specified in the path specification step, ultimately determines the path of the droplet containing the particles that are the sorting targets. The final determination step corresponds to... Figure 19 Step S208 in the process.

[0721] When specifying more than two paths in the path specification step, rule data can be used. This rule data defines the path of the droplet containing the particles that are the targets for sorting, based on the two or more paths. The rule data defines whether the droplet path is consistent when two or more paths are consistent, and whether the droplet path is not the path traveled by the particles to be sorted (e.g., the path traveled by discarded particles) when two or more paths are inconsistent.

[0722] 3. Third Implementation Method (Program)

[0723] This disclosure also provides a program for causing a particle sorting apparatus to perform the particle sorting method described in section 2 above. This program can be stored in a hard disk disposed in the particle sorting apparatus according to an embodiment of this disclosure, or the program can be recorded on a recording medium such as a micro SD memory card, SD memory card, or flash memory. For example, the control unit of the particle sorting apparatus can use this program to cause the particle sorting apparatus to perform the particle sorting method according to an embodiment of this disclosure.

[0724] 4. Fourth Implementation Method (Particle Sorting System)

[0725] This disclosure also provides a particle sorting and determination system, including a determination unit that performs the sorting determination described in 1. The system may further include, for example, a rule data generation unit that generates rule data for sorting determination. The rule data generation unit may generate the rule data based, for example, on settings related to a particle population (a) to (c) input by a user. The settings related to the particle population (a) to (c) may be gating or similar settings. The rule data generation unit may generate the rule data based on settings related to the total particle population and settings related to the purity and / or collection rate of the target particles.

[0726] It should be noted that this disclosure may also take the following configurations.

[0727] (1) A particle sorting device, comprising:

[0728] The unit is identified, and particle sorting is performed.

[0729] The determination unit uses rule data to perform the determination. The rule data defines the relationships between particles based on the particle population to which the particle being determined as the sorting target belongs and the particle populations to which different particles within a predetermined range around the particle belong.

[0730] The particle groups to which the target particles may belong, and the particle groups to which different particles within a predetermined range may belong, include the following particle groups:

[0731] (a) The particle population of particles to be sorted.

[0732] (b) A population of particles that were not sorted but can be ignored in the determination process, and

[0733] (c) A population of particles that are neither particles to be sorted nor particles that can be ignored.

[0734] Particles that can be ignored include red blood cells.

[0735] (2) The particle sorting device according to (1), wherein

[0736] The determining unit can change the rule data used in the determining process, and

[0737] At least one rule data definition that can be used by the defined unit:

[0738] Among them, the particle that is the target for sorting belongs to (a) the particle population of the particles to be sorted, and the different particles within a predetermined range around the particle belong to (b) the particle population of the particles that can be ignored, and the path of the different particles is the path of the particles to be sorted.

[0739] (3) The particle sorting device according to (1) or (2) further includes:

[0740] The rule data generation unit generates rule data, in which...

[0741] The rule data generation unit generates rule data based on the particles that are the targets for sorting and the particle groups to which different particles within a predetermined range may belong.

[0742] (4) The particle sorting apparatus according to any one of (1) to (3) further includes:

[0743] The input unit receives a gating operation to set the particle population to which the particle being identified as the sorting target may belong, and the particle population to which different particles within a predetermined range may belong.

[0744] (5) A particle sorting device according to any one of (1) to (4), wherein

[0745] The determining unit determines which particle group a particle belongs to based on the light generated by illuminating the particles flowing in the flow path.

[0746] (6) A particle sorting device according to any one of (1) to (5) for sorting blood cells.

[0747] (7) A particle sorting device according to any one of (1) to (6) for selectively sorting predetermined T cells from blood cells.

[0748] (8) A particle sorting device according to any one of (1) to (7), wherein

[0749] The rule data is multidimensional.

[0750] (9) A particle sorting device according to any one of (1) to (8), wherein

[0751] The rule data is a two-dimensional matrix.

[0752] (10) A particle sorting device according to any one of (1) to (9), wherein

[0753] The determination unit performs the determination, wherein the particle that serves as the target for sorting and determination and one or more different particles exist within a predetermined range.

[0754] (11) A particle sorting device, comprising:

[0755] The determination unit performs particle sorting and determination. This unit uses rule data to perform the determination, which defines the relationships between particles based on the particle population to which the target particle belongs and the particle populations to which different particles within a predetermined range around the target particle belong.

[0756] The particle groups that the target particles for sorting and the different particles within a predetermined range may belong to include the following particle groups:

[0757] (a) The particle population of particles to be sorted.

[0758] (b) A population of particles that were not sorted but can be ignored in the determination process, and

[0759] (c) A population of particles that are neither particles to be sorted nor particles that can be ignored.

[0760] (12) A particle sorting device according to any one of (1) to (11), wherein

[0761] The determining unit determines the relationship between each particle in a particle group consisting of the particle that serves as the sorting target and different particles within a predetermined range, and all the different particles in the particle group.

[0762] (13) The particle sorting device according to (12), wherein

[0763] The determination unit uses rule data to determine relationships, and the rule data defines whether each particle can be ignored relative to all different particles.

[0764] (14) The particle sorting device according to (13), wherein,

[0765] The determining unit does not assign paths to particles that are determined to be negligible relative to all distinct particles as a result of the determining relation, and assigns paths to particles other than those determined to be negligible.

[0766] (15) The particle sorting device according to (14), wherein,

[0767] The determination unit uses rule data, based on the assigned path definition, to determine the path of the particle that is the target of sorting.

[0768] (16) A particle sorting method, comprising:

[0769] The process involves performing a sorting determination step on the microparticle rule data. The microparticle rule data defines the relationships between particles based on the particle population to which the particle being sorted belongs and the particle populations to which different particles within a predetermined range around the particle belong.

[0770] The particle groups to which the target particles may belong, and the particle groups to which different particles within a predetermined range may belong, include the following particle groups:

[0771] (a) The particle population of particles to be sorted.

[0772] (b) A population of particles that were not sorted but can be ignored in the determination process, and

[0773] (c) A population of particles that are neither particles to be sorted nor particles that can be ignored.

[0774] Particles that can be ignored include red blood cells.

[0775] (17) A procedure for causing a particle sorting device to perform a particle sorting method, the particle sorting method comprising:

[0776] The process involves using rule-based data to perform particle sorting. This rule-based data defines the relationships between particles based on the particle population to which the target particle belongs and the particle populations to which different particles within a predetermined range around the target particle belong.

[0777] The particle groups to which the target particles may belong, and the particle groups to which different particles within a predetermined range may belong, include the following particle groups:

[0778] (a) The particle population of particles to be sorted.

[0779] (b) A population of particles that were not sorted but can be ignored in the determination process, and

[0780] (c) A population of particles that are neither particles to be sorted nor particles that can be ignored.

[0781] Particles that can be ignored include red blood cells.

[0782] (18) A particle sorting system, comprising:

[0783] The unit is determined to perform particle sorting and determination; and

[0784] The rule data generation unit generates rule data used in the sorting determination.

[0785] The determination unit uses rule data to perform the determination. The rule data defines the relationships between particles based on the particle population to which the particle being determined as the sorting target belongs and the particle populations to which different particles within a predetermined range around the particle belong.

[0786] The particle groups to which the target particles may belong, and the particle groups to which different particles within a predetermined range may belong, include the following particle groups:

[0787] (a) The particle population of particles to be sorted.

[0788] (b) A population of particles that were not sorted but can be ignored in the determination process, and

[0789] (c) A population of particles that are neither particles to be sorted nor particles that can be ignored.

[0790] Particles that can be ignored include red blood cells.

[0791] Those skilled in the art will understand that various modifications, combinations, sub-combinations and alterations may occur depending on design requirements and other factors, as long as they are within the scope of the appended claims or their equivalents.

[0792] [List of Reference Numbers]

[0793] 100 Particle Separation Device

[0794] 101 light irradiation units

[0795] 102 Detection Units

[0796] 103 Control Unit

[0797] 105 Determining the Unit

[0798] 150 microchips for particle sorting

[0799] 200 Particle Separation Device

[0800] 1 Control Unit

[0801] 2 Light Illumination Units

[0802] 3 Detection Unit

[0803] 201 Determining Unit

[0804] T-chip.

Claims

1. A particle sorting device, comprising: The unit is identified, and particle sorting is performed. The determining unit performs the sorting determination using rule data, which defines the relationship between particles based on the particle population to which the particle being sorted belongs and the particle populations to which different particles within a predetermined range around the particle belong. The rule data is multidimensional data. The particle groups to which the particles used for sorting and determination can belong, and the particle groups to which the different particles within a predetermined range can belong, include the following particle groups: (a) The particle population of particles to be sorted. (b) A population of particles that were not sorted but can be ignored in the sorting determination, and (c) A population of particles that are neither the particles to be sorted nor the particles that can be ignored. The particles that can be ignored include red blood cells.

2. The particle sorting device according to claim 1, wherein, The determining unit can change the rule data used in the sorting determination, and At least one rule data definition that can be used by the determining unit: Wherein, the particle that is the target for sorting belongs to (a) the particle group of the particles to be sorted, and the different particles within a predetermined range around the particle belong to (b) the particle group of the particles that can be ignored, and the path of the different particles is the path of the particles to be sorted.

3. The particle sorting device according to claim 1, further comprising: The rule data generation unit generates the rule data. The rule data generation unit generates the rule data based on the particle population to which the particle, which is the target for sorting, can belong, and the particle population to which the different particles within a predetermined range can belong.

4. The particle sorting device according to claim 1, further comprising: The input unit receives a gating operation to set the particle group to which the particle, as the sorting target, can belong and the particle group to which the different particles within a predetermined range can belong.

5. The particle sorting device according to claim 1, wherein, The determining unit determines the particle population to which the particles belong based on light generated by illuminating the particles flowing in the flow path.

6. The particle sorting device according to claim 1, used for sorting blood cells.

7. The particle sorting apparatus according to claim 1, for selectively sorting predetermined T cells from blood cells.

8. The particle sorting device according to claim 1, wherein, The multidimensional data is two-dimensional matrix data.

9. The particle sorting device according to claim 1, wherein, The determining unit performs the sorting determination when the particle that is the target of the sorting determination and one or more of the different particles exist within a predetermined range.

10. The particle sorting device according to claim 1, wherein, The determining unit determines the relationship between each particle in a particle group consisting of the particle as the sorting target and the different particles within a predetermined range, and all the different particles in the particle group.

11. The particle sorting apparatus according to claim 10, wherein, The determining unit uses the rule data to determine the relationship, the rule data defining whether each particle can be ignored relative to all the different particles.

12. The particle sorting apparatus according to claim 11, wherein, The determining unit does not assign paths to particles that are determined to be negligible relative to all the different particles as a result of determining the relationship, and assigns paths to particles other than those determined to be negligible particles.

13. The particle sorting apparatus according to claim 12, wherein, The determining unit uses the rule data to determine the path of the particle as the sorting target, the rule data defining the path of the particle as the sorting target based on the assigned path.

14. A method for sorting particles, comprising: The process involves determining the sorting steps for the microparticle-based rule data. This microparticle-based rule data defines the relationships between particles based on the particle population to which the target particle belongs and the particle populations to which different particles within a predetermined range around the target particle belong. The microparticle-based rule data is multidimensional data. The particle groups to which the particles used for sorting and determination can belong, and the particle groups to which the different particles within a predetermined range can belong, include the following particle groups: (a) The particle population of particles to be sorted. (b) A population of particles that were not sorted but can be ignored in the sorting determination, and (c) A population of particles that are neither the particles to be sorted nor the particles that can be ignored. The particles that can be ignored include red blood cells.

15. A computer-readable storage medium having a program stored thereon, the program, when executed by a particle sorting device, causing the particle sorting device to perform a particle sorting method, the particle sorting method comprising: The process involves using rule-based data to perform particle sorting. This rule-based data defines relationships between particles based on the particle population to which the target particle belongs and the particle populations to which different particles within a predetermined range around the target particle belong. This rule-based data is multidimensional. The particle groups to which the particles used for sorting and determination can belong, and the particle groups to which the different particles within a predetermined range can belong, include the following particle groups: (a) The particle population of particles to be sorted. (b) A population of particles that were not sorted but can be ignored in the sorting determination, and (c) A population of particles that are neither the particles to be sorted nor the particles that can be ignored. The particles that can be ignored include red blood cells.

16. A particle sorting system, comprising: The particle sorting device according to claim 1; as well as The rule data generation unit generates rule data used in the sorting determination.

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