JP2008278789A - Method for discriminating neuronal cell and glial cell - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To separate a cell in a cell separation region based on the judged result of an image obtained in a cell sorter cell-detection region to use a flow path formed on a substrate. <P>SOLUTION: Discrimination of a neuronal cell and a neuroblast cell is performed by the presence or absence of a notch on a line showing the circumferential length of a cell from the real body image of neuronal cell and glial cell. Concretely, as an example, the image is processed as pixels formed by dividing the image to the proper number of sections in X and Y directions, each pixel is binarized by comparing the brightness of the pixel with a prescribed threshold value and both cells are discriminated by the comparison result. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a cell discrimination method suitable for nerve cells and glial cells by applying a flow path formed on a substrate to a cell sorter that separates cells by allowing cells to flow down together with a buffer solution.

  Several methods are known for separating specific cells from biological tissue pieces. As a method for discriminating between cardiomyocytes and fibroblasts, a method of separating by density gradient centrifugation using Percoll is often performed by paying attention to the difference in specific gravity of each cell. This method is a method of separating and collecting cells so as not to disturb a layer of cells separated as a result of centrifugation, but it is not always possible to separate them with sufficient accuracy.

  Separation and recovery of specific cells is an important technique in biological and medical analysis. For example, cells after fluorescent staining are isolated in units of cells in charged droplets. Applying a high electric field in a direction normal to the drop direction in the process of dropping, based on the presence or absence of fluorescence of the cells in the drop and the amount of light scattering. Then, there is a cell sorter that controls the drop direction of the liquid droplets and fractionates and collects them in a plurality of containers placed underneath (Non-Patent Document 1: Kamarck, ME, Methods Enzymol. Vol. 151, p150-165). (1987)).

However, this technology is expensive, requires a large device, requires a high electric field of several thousand volts, requires a large amount of sample, and damages cells in the process of creating droplets. There are problems such as possibility and inability to directly observe the sample. In order to solve these problems, the present inventors utilize microfabrication technology to cause cells to flow down with a buffer solution through a flow path formed on a substrate, collect cell images, and perform cell separation. A cell sorter to perform is proposed (Japanese Patent Laid-Open No. 2006-180810, Japanese Patent Laid-Open No. 2006-220423).
Kamarck, ME, Methods Enzymol. Vol.151, p150-165 (1987) JP 2006-180810 A JP 2006-220423 A

  The present invention relates to a cell identification method for nerve cells and glial cells, which enables cell separation with high accuracy and high speed by means of a substantial image of nerve cells and glial cells by means of a cell sorter that collects the cells and separates them. The purpose is to provide.

  The inventor of the present application has examined the entity images of nerve cells and glial cells in detail, and as a result, has found that each cell can be identified from the entity image by evaluating according to a predetermined standard. In the present invention, cells flowing down together with the buffer solution are detected as solid images using a CCD camera or the like at a predetermined position, and cells flowing continuously at high speed in the flow path are evaluated by the above criteria. Identify.

Therefore, the present invention provides the following cell identification method, cell identification / separation apparatus, and computer program used for the cell identification method.
(1) a channel for flowing down a buffer containing cells configured on the substrate, a cell detection region for detecting cells flowing down together with the buffer provided at a predetermined position of the channel, Cell separation comprising a cell separation region for separating cells according to the detected cells provided downstream of the cell detection region, and two flow paths for flowing the separated cells provided downstream of the cell separation region A cell identification method in cell separation using a chip,
Detecting a substance image of a cell flowing down the flow path together with a buffer in the cell detection region, and evaluating the substance image according to a predetermined standard; and separating the cell in the cell separation region based on the evaluation Including steps,
A method for identifying a cell between a neuron and a fibroblast, wherein the reference is the presence or absence of a notch formed in a line indicating the perimeter of the cell.
(2) The cell identification method for neuronal cells and fibroblasts according to (1) above, wherein the substance image of the cells detected in the cell detection region is captured independently for each cell.
(3) a channel for flowing down a buffer containing cells configured on the substrate, a cell detection region for detecting cells flowing down together with the buffer provided at a predetermined position of the channel, and Cell separation comprising a cell separation region for separating cells according to the detected cells provided downstream of the cell detection region, and two flow paths for flowing the separated cells provided downstream of the cell separation region A cell identification method in cell separation using a chip,
Detecting a substance image of a cell flowing down the flow path together with a buffer in the cell detection region;
Binarizing the entity image as pixels divided at predetermined intervals in the direction of each axis on the XY plane, and evaluating the continuity of the pixels having the predetermined brightness;
Determining the presence or absence of continuity of pixels of the predetermined brightness to identify cells,
A method of identifying a cell from a neuronal cell and a fibroblast when the pixel having the predetermined brightness is a neuron when the cell is continuous, and when the pixel is not continuous, the cell is a fibroblast.
(4) The presence or absence of the continuity of the pixels having the predetermined brightness is determined by determining whether adjacent pixels are at or above the predetermined brightness in each axial direction of the XY plane or in a direction shifted by 45 degrees. A method for distinguishing between nerve cells and fibroblasts.
(5) a channel for flowing down a buffer containing cells configured on the substrate, a cell detection region for detecting cells flowing down together with the buffer provided at a predetermined position of the channel, Cell separation comprising a cell separation region for separating cells according to the detected cells provided downstream of the cell detection region, and two flow paths for flowing the separated cells provided downstream of the cell separation region A cell identification method in cell separation using a chip,
Detecting a substance image of a cell flowing down the flow path together with a buffer in the cell detection region;
A step of detecting the brightness of the image on an axis direction rotated by a predetermined angle from one axis of the XY plane of the entity image, and the brightness of the image detected on each of the rotated axes Determining whether or not exceeds a predetermined threshold;
Including
When there is an axis where the brightness of the detected image on each of the rotated axes does not exceed a predetermined threshold, the cell is a nerve cell, and the brightness of the detected image exceeds a predetermined threshold on all axes A method for distinguishing between neuronal cells and fibroblasts, sometimes called fibroblasts.
(6) A cell identification / separation device used in the method described in (1) above,
A flow path for flowing a buffer solution containing cells formed on a substrate, a cell detection area for detecting cells flowing down together with the buffer solution provided at a predetermined position of the flow path, and the cell detection area A cell separation chip comprising a cell separation region for separating cells according to the detected cells provided downstream, and two flow paths for flowing the separated cells provided downstream of the cell separation region Means for installing
Means for detecting an entity image of a cell flowing down the flow path together with a buffer in the cell detection region;
Calculating a predetermined evaluation value for evaluating the entity image from the digital data of the entity image, and comparing the calculated evaluation value with a predetermined threshold to identify the cell;
And a means for applying an electric field to separate the identified cells in the cell separation region.
(7) A computer program used in the method described in (1) above,
A step of calculating a ratio of a perimeter to a cross-sectional area of the cell from digital data of a substance image of the cell detected in the cell detection region, and comparing the ratio with a predetermined threshold, Determining whether to apply an electric field to the region as the cell passes through,
A computer program for causing a computer to execute a process including:
(8) A computer program used in the method described in (3) above,
Based on the digital data of the cell entity image detected in the cell detection area, the entity image is represented as pixels divided at predetermined intervals in each axial direction of the XY plane, and the brightness of each pixel is defined as a predetermined reference. Binarization based on:
Dividing the entity image represented by the binarized pixels into a plurality of regions, and evaluating the number of pixels having a predetermined brightness in each region;
Determining whether the number of pixels of a predetermined brightness in a predetermined region exceeds a predetermined threshold; and based on the determination, an electric field is applied to the region when the cell passes through the cell separation region. Determining whether or not to apply,
A computer program for causing a computer to execute a process including:

  According to the present invention, cell separation between nerve cells and glial cells is possible with high accuracy and high speed.

  FIG. 1 is a plan view schematically showing an example of a cell sorter that is convenient to which the present invention is applied as a configuration based on a cell separation device (cell sorter) disclosed in Japanese Patent Application Laid-Open No. 2006-180810.

  The cell sorter 100 has a structure including a substrate 101. A groove serving as a flow path is provided on the lower surface of the substrate 101, and an opening communicating with the groove is provided on the upper surface to serve as a supply port for a sample or a necessary buffer solution. In addition, reservoirs (203, 213) are provided to supply a sufficient buffer solution and adjust the flow rate in each flow path. The grooves and openings can be created by so-called injection molding in which a plastic such as PMMA is poured into a mold. The entire size of the chip substrate 101 is, for example, 20 × 30 × 1 mm (t), but is not limited to this size. For example, a 0.1 mm-thick laminate film is thermocompression bonded to the lower surface side of the chip substrate 101 where the grooves are engraved, so that the grooves engraved on the lower surface of the substrate 101 and the through-holes of the substrate 101 can be formed into channels and wells. It can be. For example, using an objective lens having a numerical aperture of 1.4 and a magnification of 100, cells flowing in the flow path through a 0.1 mm laminated film can be observed. Of course, a lens with a lower magnification than this can be observed without problems. The upper surface of the chip substrate 101 is provided with a hole 201 for introducing a sample buffer containing cells into the microchannel, and holes 201 ′, 202 and 202 ′ for introducing a buffer containing no cells. A reservoir 203 is provided. Specifically, holes 201 ′, 202, and 202 ′ are provided on the bottom surface of the well provided on the upper surface of the substrate 101 in order to form the reservoir 203.

  Accordingly, when a sufficient buffer solution is supplied to the reservoir 203, the holes 201, 201 ', 202 and 202' are connected by the buffer solution. As a result, a buffer solution having the same liquid level is supplied to the flow path 204 and the flow path 204 ′ connected to the holes 201 and 201 ′. Therefore, if the channel width of both channels (assuming that the channel height is equal), or the cross-sectional area and the channel length of both channels are substantially equal, the flow rates of both channels are substantially the same. can do. Similarly, a buffer solution having the same liquid level is supplied to the flow paths 205 and 205 ′ connected to the holes 202 and 202 ′, and the flow rate of the buffer solution flowing through the flow paths 205 and 205 ′ is the flow rate flowing through the flow path 204. It can be aligned to a predetermined ratio.

  The buffer solution containing the cells introduced into the holes 201 passes through the microchannel 204 (eg, width 20 μm, depth 15 μm) and is introduced to the cell detection region 221 and the cell separation region 222. On the other hand, the buffer solution containing no cells introduced into the holes 202 and 202 ′ passes through the flow channels 205 and 205 ′ (width 12 μm, depth 15 μm) and merges with the buffer solution containing cells in the microchannel 204. . Reference numeral 240 denotes a microchannel after joining, which becomes a cell detection region 221. Further, the microchannel 240 is extended to the cell separation region 222.

  On the other hand, the cell-free buffer introduced into the hole 201 ′ passes through the microchannel 204 ′ (eg, width 20 μm, depth 15 μm) and is introduced into the cell separation region 222, from the microchannel 240. Combine with a buffer containing the cells. The channel width of the channel through which the solution passes after joining will be described later. Further, the merged flow path is divided into micro flow paths 218 (for example, width 20 μm, depth 15 μm) and 219 (for example, width 20 μm, depth 15 μm) at the outlet of cell separation region 222.

  206, 206 ′ and 207, 207 ′ are holes for introducing a gel containing an electrolyte, respectively. The gels introduced into the holes 206 and 207 are microstructures 208, 209 on the lower surface of the substrate 101 (for example, 200 μm wide × high Through the grooves 206 ′ and 207 ′. Accordingly, the microstructures 208 and 209 are filled with a gel containing an electrolyte. The ends of the micro structures 208 and 209 on the flow path 247 side are composed of connecting portions 241 and 242 having a liquid junction structure of about 20 μm length connected to the micro flow paths 204 and 204 ′, respectively. The gel can be directly brought into contact with the buffer solution flowing through the flow channel 247 where the micro flow channel 240 and the micro flow channel 204 ′ merge. The area where the gel and the buffer come into contact is, for example, 15 μm (length along the flow path) × 15 μm (height). Electrodes indicated by black circles are inserted into the holes 206 and 207 for introducing the gel, and these electrodes are connected to the power source 215 through the wirings 106 and 107 and the switch 216. The switch 216 is turned on only when a voltage is applied to the buffer solution flowing through the flow path 247 where the micro flow path 240 and the micro flow path 204 ′ merge.

  The gels from the connecting portions 241 and 242 come into contact with the buffer solution flowing through the flow channel 247 formed by the micro flow channel 240 and the micro flow channel 204 ′ joining in the cell separation region 222. As shown in the figure, the connecting part 241 is positioned upstream of the connecting part 242 rather than the connecting part 242. This is because when a positive voltage is applied to the electrode of the hole 206 and a negative voltage is applied to the electrode of the hole 207, the cells flowing through the microchannel 240 are efficiently moved to the channel 218. That is, an electrophoretic force acts on a cell that is negatively charged when an electric current is passed, but a combined vector of this electrophoretic force vector and a force vector received from a buffer flowing in the flow path is It becomes the power that actually works on the cell. When the connecting portion 241 is positioned upstream of the flow path rather than the connecting portion 242, the connecting portions 241 and 242 actually act on the cells as compared with the case where the connecting portions 241 and 242 are formed at the same level with respect to the flow direction of the flow path. The direction of the force vector is directed more directly toward the connecting portion 242 or 241. Therefore, the cell can be moved to the microchannel 218 or the microchannel 219 stably at a lower voltage, and the electric field can be used efficiently.

  In the downstream part of the microchannels 218 and 219, cell collection holes 211 and 212 distributed in the cell separation region 222 are formed. In each of the holes 211 and 212, a reservoir 213 that includes them is provided. Specifically, holes 211 and 212 are provided on the bottom surface of the well provided on the upper surface of the substrate 101 in order to form the reservoir 213. The reservoir 213 is filled with a buffer solution, and the position of the buffer solution is lower than the position of the buffer solution filled in the reservoir 203.

  Since the liquid level of the buffer solution in the reservoir 203 is higher than that of the reservoir 213, this drop serves as a driving force for the movement of the buffer solution flowing through the flow path, and creates a stable flow without pulsation. If the volume of the reservoir 213 is sufficiently large, all of the buffer solution containing the cells introduced into the holes 201 can flow into the flow path 204.

  The cells that flow down the cell detection area 221 are captured as real images by the camera 251, and the computer 252 determines whether the captured cells are nerve cells or glial cells based on a discrimination method described later. Only when the computer 252 determines that the cell is a glial cell, the computer 252 turns on the switch 216 when the cell reaches the cell separation region 222. As a result, nerve cells flow down the microchannel 218, and glial cells flow down the microchannel 219.

  FIG. 2 shows that after the buffer solution containing the cells from the microchannel 204 and the buffer solution from the microchannels 205 and 205 ′ merge, it enters the cell detection region 221 on the microchannel 240, It is a figure explaining the condition which flows down the micro flow path 240, merges with the buffer solution from micro flow path 204 ', and flows down the micro flow path 247 further. As shown in the figure, the cell separation region 222 includes a downstream end of the microchannel 204 ′, a downstream end of the microchannel 240, a part of the connecting part 241, a part of the connecting part 242, and a micro channel. 247.

  Here, the reason why the buffer solution not containing the cells flowing down the flow paths 205 and 205 ′ and the buffer solution containing the cells flowing down the micro flow path 204 is merged in the upstream portion of the cell detection region 221 will be described. In the flow path 204 through which the buffer solution containing cells flows, flow paths 205 and 205 ′ through which the buffer solution not containing cells joins in the upstream portion of the cell detection region 221. The holes 201 and 202, 202 'have openings in a common buffer buffer reservoir 203. Therefore, the flow rate of the buffer solution flowing down each channel is proportional to the channel width because the channel height is the same. The width of the flow path 240 after the merge of these buffer solutions is assumed to be substantially equal to the width of the flow path 204 through which the buffer solution containing cells flows. “Substantially equal” means that they are equal in consideration of machining accuracy and are not strictly equal. As a result, the buffer solution flowing down the flow path 204 is pushed to the central portion at a constant ratio by the buffer solution flowing down the flow paths 205 and 205 ′, so that cells flowing while colliding with the side wall in the flow path 204 In the flow path 240 after merging, it does not collide with the side wall.

  In the micro flow path 247 in the cell separation region 222, the buffer solution flowing down the flow path 240 and the flow path 204 'flows down while maintaining the flow paths of the same width while maintaining the respective flow layers. The cells flowing down in the flow path 204 of the cell detection region 221 are detected, and in the cell separation region 222, the cells are separated by applying an electric field by the connecting portions 241 and 242 that are in contact with the buffer solution in which the gel flows down.

  FIG. 3A is a diagram schematically showing a configuration in which cells passing through the cell detection region 221 are imaged with a CCD camera. Reference numeral 11 in the figure is a light source of a stereomicroscope. A band-pass filter 12 transmits only light having a specific wavelength from the light of the light source 11. For example, when a sample such as a cell is used, damage to the sample can be prevented by using a narrow band near a wavelength of 700 nm. Reference numeral 13 denotes a shutter, which has a function of blocking light irradiation while image measurement is not being performed, such as when the XY stage 15 is moved. Reference numeral 14 denotes a condenser lens.

  Mounted on the XY stage 15 is a cell sorter 100 constituted by a micro flow path, and the position of the cell sorter 100 is adjusted to a position suitable for measurement by moving the XY stage by a driving device 22. To be able to. Cells flowing down the cell detection region 221 of the cell sorter 100 are observed with the objective lens 16. The focal position of the objective lens 16 can be moved by the driving device 17. For example, if the thickness of the laminate film on the bottom surface of the substrate 101 of the cell sorter is 0.18 mm or less, the objective lens 16 can observe the cells with a sufficient size with a numerical aperture of 1.4 and a magnification of 40 times. The cells in the flow path are imaged by the high-speed camera 251 by the dichroic mirror 18 and the band-pass filter 19 that reflect light having the same wavelength as that transmitted through the band-pass filter 12, and an image is captured at, for example, 200 frames per second. . The image captured by the camera 251 is processed by the computer 252 as described later, and it is determined whether the image is a nerve cell or a glial cell. Prior to this image processing, if necessary, the focusing operation of the cells flowing down the cell detection region 221 and the detection of the moving speed are also performed.

  Here, the correction of the image accompanying the movement of the cell will be described.

FIG. 3B is a diagram schematically illustrating the problem of an image when an object moving at a speed v is photographed with the camera shutter opened for a time t. If the object is a perfect circle having a size of 1 as indicated by a broken line, it can be captured by the camera as an ellipse extended in the moving direction by vt. FIGS. 3C and 3D are views for explaining the concept of correcting the image captured by the camera in consideration of this. That is, the size in the moving direction of the object may be compressed as in the following equation (1) for the L × L image region. As a result, the shape shown by an ellipse in FIG. 3C is corrected to be shown by a perfect circle in FIG.

  With reference to FIG. 4, an actual image of nerve cells and glial cells obtained by imaging a cell passing through the cell detection region 221 of the flow path 204 with a CCD camera will be described. The image shown in FIG. 4 is an image in which the influence due to the movement of the cells is corrected as described in FIG. As the CCD camera, for example, a camera capable of capturing an image at 200 frames per second is used. With this imaging ability, even if the flow rate of the buffer solution flowing down the flow path of the cell detection region 221 is about 1 mm / sec, it can be recognized in cell units. Alternatively, as shown schematically in FIG. 2, it can be recognized as a continuously flowing cell. From these images, the images are recognized in cell units and identified as follows.

Example 1
FIG. 4A is a photograph showing an example of a substance image of a nerve cell captured by a CCD camera. On the other hand, FIG. 4B is a photograph showing an example of an actual image of glial cells captured by a CCD camera. As can be seen from the length of the line segment of 10 μm indicating the size of each photograph, the size is about 12 μm, and both cells cannot be identified by simply comparing the size.

  The inventor of the present application noticed that both cells could be identified with high accuracy by examining the actual images of nerve cells and glial cells and focusing on the presence or absence of whisker-like projections on the surface. . That is, since the nerve cell has a whisker-like projection on the surface, it can be recognized that the periphery of the cell is intermittent when viewed as an image. On the other hand, glial cells do not have whiskers and can be recognized as continuous cells.

  As an example of the automatic evaluation by paying attention to the above features, the image is treated as an appropriate number of pixels divided in the X and Y axis directions, and each pixel compares its brightness with a predetermined threshold value. An example of binarization processing will be described.

  First, the nerve cell entity image shown in FIG. 4A is treated as a pixel obtained by dividing the image into 20 parts in the X and Y axis directions, as shown in FIG. 5A. Each pixel is binarized by comparing its brightness with a predetermined threshold value and replaced with 0,1. FIG. 6A shows the result of the binarization process. In the figure, only pixels that are above the threshold are indicated by “1”.

  On the other hand, the glial cell entity image shown in FIG. 4B is treated as a pixel obtained by dividing the image into 20 parts in the X and Y axis directions as shown in FIG. 5B. Each pixel is binarized by comparing its brightness with a predetermined threshold value and replaced with 0,1. FIG. 6B shows the result of the binarization process. In the figure, only pixels that are above the threshold are indicated by “1”.

  In FIG. 6A, the pixel “1” that is equal to or greater than the threshold appears in the peripheral portion of the image in a substantially continuous form, but the continuity of the adjacent pixel “1” is lost in the regions 61, 62, and 63 indicated by the broken lines. It has been broken. On the other hand, in FIG. 6B, the continuity of the pixel “1” in which the pixel “1” that is equal to or higher than the threshold value of the image is adjacent to the entire peripheral portion of the image is seen.

  Here, the continuity of adjacent pixels “1” can be seen is not only that if adjacent pixels are “1” in both the X-axis direction and the Y-axis direction, they are not continuous, Even in the case of pixels that are adjacent in the 45-degree direction, if they are “1”, they are consecutive.

(Example 2)
In the second embodiment, cells are identified by paying attention to a change in brightness of an image on an axis obtained by inclining a substance image of a cell from the X axis at a predetermined angular interval.

7A shows axes θ ₀ , θ ₁ , θ ₂ , and the like obtained by inclining the entity image of the nerve cell shown in FIG. 4A from the origin (center of gravity) of the X and Y axes at a predetermined angle. , Θ _n , focusing on the change in brightness of the image, detecting the brightest position at the outermost background with a predetermined change rate (differential value) or more from the background brightness, and connecting these positions with bold lines FIG. FIG. 7B is a diagram showing changes in image brightness on axes θ ₀ , θ ₁ , θ ₂ , ---, θ _n .

FIG. 8A shows the brightness of an image on axes θ ₀ , θ ₁ , θ ₂ , ---, θ _{n obtained} by inclining the actual image of glial cells shown in FIG. FIG. 4 is a diagram showing positions where the outermost brightness is brightened at a predetermined rate of change (differential value) or more, and these positions are connected by bold lines, focusing on the change in height. FIG. 8B is a diagram showing changes in image brightness on the axes θ ₀ , θ ₁ , θ ₂ , ---, θ _n .

Each thick line in FIG. 7 (A) and FIG. 8 (A) is a line indicating the periphery of the cell. As is clear by comparing the two figures, in FIG. 7 (A), the axis θ _{n− In} FIG. 8A, the line indicating the periphery of the cell is continuous on all the axes, whereas the line indicating the periphery of the cell on ₂ is cut off. That is, it can be seen that the lines indicating the periphery of the cell are discontinuous in the nerve cell and the lines indicating the periphery of the cell are continuous in the glial cell. It should be noted that in Example 2, the same image as in Example 1 was evaluated, but the position where the line surrounding the cell is discontinuous corresponds to one area, that is, the region 63 indicated by the broken line. This means that only the position to be detected could be detected. This is because the way of marking the shaft was rough. Therefore, in the first embodiment, it is important to select an optimum value of the pixel size, and in the second embodiment, it is important to optimally select a step of rotation of the shaft.

It is a top view which shows typically an example of the convenient cell sorter by applying this invention. The buffer solution of the microchannels 205 and 205 ′ joins the buffer solution containing the cells of the microchannel 204 and flows down the microchannel 240, and flows down the microchannel 204 ′ immediately before the cell detection region 221. It is a figure explaining the condition which joins with the buffer solution to flow and flows down micro240. (A) is a diagram schematically showing a configuration in which cells passing through the cell detection region 221 are imaged with a CCD camera, and (B) is an image of an object moving at a speed v with the camera shutter opened for a time t. The figure explaining the problem of the image at the time, (C), (D) is a figure explaining the idea of correcting the image captured by the camera. (A) is a photograph showing an example of an entity image of a nerve cell captured by a CCD camera, and (B) is a photograph showing two examples of an entity image of a glial cell captured by a CCD camera. (A), (B) is a figure explaining the example which handles the actual image of the neuron | cell and the glial cell shown to FIG. 4 (A), (B) as a pixel each divided into 20 in the X-axis and Y-axis directions. (A), (B) is a figure which shows the result of the binarization process of the pixel shown to FIG. 5 (A), (B). FIGS. 4A and 4B are views for identifying cells by focusing on the change in brightness of an image on an axis obtained by inclining the entity image of the nerve cell shown in FIG. FIG. (A) and (B) are views for identifying cells by paying attention to a change in brightness of an image on an axis obtained by inclining the actual image of the glial cell shown in FIG. FIG.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 100 ... Cell sorter, 101 ... Substrate, 106, 107 ... Wiring, 201, 201 ', 202, 202', 206, 207 ... Hole, 206 ', 207' ... Air vent, 203, 213 ... Reservoir, 204, 204 ', 205 , 205 ', 240, 218, 219 ... flow path, 208, 209 ... microstructure, 215 ... power source, 216 ... switch, 221 ... cell detection region, 222 ... cell separation region, 241, 242 ... junction of liquid junction structure 251 ... Camera, 252 ... Computer, 61, 62 and 63 ... A region where the continuity of the adjacent pixel "1" is lost.

Claims (8)

A flow path for flowing a buffer solution containing cells formed on a substrate, a cell detection area for detecting cells flowing down together with the buffer solution provided at a predetermined position of the flow path, and the cell detection area Utilizing a cell separation chip comprising a cell separation region for separating cells according to detected cells provided downstream of the cell, and two flow paths for flowing the separated cells provided downstream of the cell separation region A cell identification method in isolated cell separation,
Detecting a substance image of a cell flowing down the flow path together with a buffer in the cell detection region, and evaluating the substance image according to a predetermined standard; and separating the cell in the cell separation region based on the evaluation Including steps,
A method for identifying a cell between a neuron and a fibroblast, wherein the reference is the presence or absence of a notch formed in a line indicating the perimeter of the cell.   The cell identification method for a neuron and a fibroblast according to claim 1, wherein the substance image of the cell detected in the cell detection region is imaged independently for each cell. A flow path for flowing a buffer solution containing cells formed on a substrate, a cell detection area for detecting cells flowing down together with the buffer solution provided at a predetermined position of the flow path, and the cell detection area Utilizing a cell separation chip comprising a cell separation region for separating cells according to detected cells provided downstream of the cell, and two flow paths for flowing the separated cells provided downstream of the cell separation region A cell identification method in isolated cell separation,
Detecting a substance image of a cell flowing down the flow path together with a buffer in the cell detection region;
A step of binarizing the entity image as pixels obtained by dividing the entity image at predetermined intervals in each axial direction of the XY plane, with reference to the brightness of each pixel;
Evaluating the continuity of pixels of the predetermined brightness, and identifying cells by determining the presence or absence of continuity of the pixels of the predetermined brightness,
A method of identifying a cell from a neuronal cell and a fibroblast when the pixel having the predetermined brightness is a neuron when the cell is continuous, and when the pixel is not continuous, the cell is a fibroblast.   4. The nerve cells and fibers according to claim 3, wherein the pixels having the predetermined brightness have a continuity of pixels whose neighboring pixels are equal to or higher than the predetermined brightness in either the axial direction of the XY plane or a direction shifted by 45 degrees. A cell identification method for blast cells. A flow path for flowing a buffer solution containing cells formed on a substrate, a cell detection area for detecting cells flowing down together with the buffer solution provided at a predetermined position of the flow path, and the cell detection area Utilizing a cell separation chip comprising a cell separation region for separating cells according to detected cells provided downstream of the cell, and two flow paths for flowing the separated cells provided downstream of the cell separation region A cell identification method in isolated cell separation,
Detecting a substance image of a cell flowing down the flow path together with a buffer in the cell detection region;
A step of detecting the brightness of the image on an axis direction rotated by a predetermined angle from one axis of the XY plane of the entity image, and the brightness of the image detected on each of the rotated axes Determining whether or not exceeds a predetermined threshold;
Including
When there is an axis where the brightness of the detected image on each of the rotated axes does not exceed a predetermined threshold, the cell is a nerve cell, and the brightness of the detected image exceeds a predetermined threshold on all axes A method for distinguishing between neuronal cells and fibroblasts, sometimes called fibroblasts. A cell identification / separation device used in the method according to claim 1,
A flow path for flowing a buffer solution containing cells formed on a substrate, a cell detection area for detecting cells flowing down together with the buffer solution provided at a predetermined position of the flow path, and the cell detection area A cell separation chip comprising a cell separation region for separating cells according to the detected cells provided downstream, and two flow paths for flowing the separated cells provided downstream of the cell separation region Means for installing
Means for detecting an entity image of a cell flowing down the flow path together with a buffer in the cell detection region;
Calculating a predetermined evaluation value for evaluating the entity image from the digital data of the entity image, and comparing the calculated evaluation value with a predetermined threshold to identify the cell;
And a means for applying an electric field to separate the identified cells in the cell separation region. A computer program for use in the method of claim 1, comprising:
A step of calculating a ratio of a perimeter to a cross-sectional area of the cell from digital data of a substance image of the cell detected in the cell detection region, and comparing the ratio with a predetermined threshold, Determining whether to apply an electric field to the region as the cell passes through,
A computer program for causing a computer to execute a process including: A computer program for use in the method of claim 3, comprising:
Based on the digital data of the cell entity image detected in the cell detection area, the entity image is represented as pixels divided at predetermined intervals in each axial direction of the XY plane, and the brightness of each pixel is defined as a predetermined reference. Binarization based on:
Dividing the entity image represented by the binarized pixels into a plurality of regions, and evaluating the number of pixels having a predetermined brightness in each region;
Determining whether the number of pixels of a predetermined brightness in a predetermined region exceeds a predetermined threshold; and based on the determination, an electric field is applied to the region when the cell passes through the cell separation region. Determining whether or not to apply,
A computer program for causing a computer to execute a process including:

Images