JP2016200458A - Optical device and information processing system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an optical device and an information processing system with which it is possible to measure the type or state of a sample noninvasively.SOLUTION: The optical device comprises an irradiation system 10 for radiating a linearly polarized light in a prescribed direction of polarization toward a sample, and optical detection systems 30-1 to 30-3 for detecting scattered light caused by incidence of the linearly polarized light on the sample, the irradiation system 10 including a VCSEL 11 for radiating the linearly polarized light, the optical detection systems 30-1 to 30-3 being disposed on optical paths in mutually different directions of scattering angle and including polarization filters 31-1 to 31-3 for allowing the linearly polarized component of scattered light to pass through at a predetermined angle and optical receivers 35-1 to 35-3 for receiving the light having passed through the polarization filters 31-1 to 31-3.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an optical device and an information processing system.

  Conventionally, a flow cytometer is known as a technique for identifying the cell type of a cell (see, for example, Patent Document 1). In a flow cytometer, cells are flowed one by one in a narrow channel, and the cells flowing in the channel are irradiated with laser light to measure forward scattered light and side scattered light to reflect the size of the cell. The cell type of the cell is identified from the combination of the scattered light intensity and the side scattered light intensity reflecting information such as intracellular structure and granules.

  However, side scattered light (side scattered light intensity) is mixed with information on various proteins and various organelles in the cell, and it is impossible to distinguish from what kind of particles the scattered light is. It is difficult to identify the cell type of the cell. For this reason, in the flow cytometer, a fluorescent dye is introduced into a cell to distinguish from what kind of particles the side scattered light is scattered.

  As described above, the cell type of a cell cannot be measured non-invasively with a flow cytometer. In addition, since the flow cytometer measures a single cell, it cannot measure the type and state of a sample having a complicated fine structure other than the single cell, such as a colony, a colloid, and a gel.

  The present invention has been made in view of the above circumstances, and an object thereof is to provide an optical device and an information processing system capable of noninvasively measuring the type or state of a sample.

  In order to solve the above-described problems and achieve the object, an optical device according to one embodiment of the present invention includes an irradiation system that emits linearly polarized light having a predetermined polarization direction toward a sample, and the linearly polarized light is applied to the sample. A plurality of light detection systems that detect scattered light generated by the incidence, wherein the irradiation system includes a vertical surface emitting laser that emits the linearly polarized light, and the plurality of light detection systems have different scattering angles. A polarizing element that is arranged on the optical path in the direction and passes the linearly polarized light component of the scattered light at a predetermined angle, and a light receiver that receives the light that has passed through the polarizing element.

  According to the present invention, it is possible to noninvasively measure the type or state of a sample.

FIG. 1 is a configuration diagram illustrating an example of an information processing system according to the first embodiment. FIG. 2 is a plan view showing an example of a laser emission port of the VCSEL of the first embodiment. FIG. 3 is a side view showing an example of the laser emission port of the VCSEL of the first embodiment. FIG. 4 is an explanatory view of scattering of various particles mixed in the cell. FIG. 5 is a detailed view of the scattering shown in FIG. FIG. 6 is an explanatory diagram of the principle of the first embodiment. FIG. 7 is a diagram showing the scattered light intensity distribution on the magnetic field vibration surface. FIG. 8 is a diagram showing the scattered light intensity distribution on the electric field vibration surface. FIG. 9 is a diagram illustrating an example of a temporal change in scattered light of a sample. FIG. 10 is a diagram showing the time change of the volume of the overlapping portion when a certain particle moves with the passage of time due to thermal motion. FIG. 11 is a conceptual diagram of a time correlation function. FIG. 12 is a diagram showing a time correlation function of scattered light intensity. FIG. 13 is an explanatory diagram of interference of scattered light and an optical path difference. FIG. 14 is a graph showing the analysis results of monodisperse particles of polystyrene latex. FIG. 15 is a diagram showing H (Γ) obtained by inverse Laplace transform of g ⁽²⁾ (τ) -1 and g ⁽²⁾ (τ) -1. FIG. 16 is a block diagram illustrating an example of a hardware configuration of the information processing apparatus according to the first embodiment. FIG. 17 is a block diagram illustrating an example of a functional configuration of the information processing apparatus according to the first embodiment. FIG. 18 is a diagram illustrating identification information of the first embodiment. FIG. 19 is a diagram illustrating identification information of the second embodiment. FIG. 20 is a diagram illustrating an example of the position dependency of the scattered light intensity of the polymer solution. FIG. 21 is a diagram illustrating an example of the position dependency of the scattered light intensity of a biological system or gel. FIG. 22 is a diagram illustrating an example of an ensemble average correlation function-correlation time. FIG. 23 is a diagram illustrating an example of relaxation time distribution-relaxation time. FIG. 24 is a block diagram illustrating an example of a functional configuration of the information processing apparatus according to the second embodiment. FIG. 25 is a diagram illustrating identification information of the third embodiment. FIG. 26 is a diagram illustrating identification information of the fourth embodiment.

  Hereinafter, embodiments of an optical device and an information processing system according to the present invention will be described in detail with reference to the accompanying drawings.

(First embodiment)
FIG. 1 is a configuration diagram illustrating an example of an information processing system 1 according to the first embodiment. As shown in FIG. 1, the information processing system 1 includes an irradiation system 10, a stage 21, a thermostat 22, a sample holder 23, a sample 25, a half mirror 26, an optical microscope 27, and a light detection system 30. -1 to 30-3 (an example of a plurality of light detection systems) and the information processing apparatus 100 are provided.

  The irradiation system 10, the stage 21, the thermostat 22, the sample holder 23, the sample 25, the half mirror 26, the optical microscope 27, and the light detection systems 30-1 to 30-3 constitute an optical device. However, in the example shown in FIG. 1, the dark box is not shown for easy understanding of the internal configuration of the optical device. In the first embodiment, the case where the number of light detection systems is three will be described as an example. However, the present invention is not limited to this, and the number may be two or four or more.

  The irradiation system 10 emits linearly polarized light 24 having a predetermined polarization direction toward a sample 25. As shown in FIG. 1, a VCSEL (Vertical Cavity Surface Emitting LASER) 11 A collimating lens 13, a reflecting mirror 14, and a cylindrical plano-convex lens 15. However, the irradiation system 10 is not limited to these configurations, and some configurations may be omitted, other configurations may be added, or some configurations may be replaced with other configurations. .

  The VCSEL 11 emits linearly polarized light 24 that is laser light polarized in a predetermined polarization direction in a direction orthogonal to the substrate surface. The predetermined polarization direction may be one direction with respect to the sample 25. In the first embodiment, the case where the oscillation wavelength of the VCSEL 11 is in the 780 nm band will be described as an example, but the present invention is not limited to this. In the first embodiment, since the irradiation system 10 uses the VCSEL 11 as a light source, the linearly polarized light 24 in a predetermined polarization direction can be used without using a polarizing element such as a polarizing filter as in the case where an edge emitting laser is used as the light source. Can be injected.

  FIG. 2 is a plan view showing an example of the laser emission port 12 of the VCSEL 11 of the first embodiment, and FIG. 3 is a side view showing an example of the laser emission port 12 of the VCSEL 11 of the first embodiment.

  The high-order mode filter 12-1 at the laser emission port 12 is formed of a SiN film having a thickness of λ / 4, and is provided in a peripheral region excluding the central portion of the element. The shape of the high-order mode filter 12-1 is an anisotropic shape divided into two in the α direction in order to improve the stability of polarization. Here, in the low reflection region 12-2, which is a region where the high-order mode filter 12-1 is provided, the multilayer mirror is terminated with a low refractive index of λ / 4 thickness, and the reflectance decreases. For this reason, the fundamental mode has a mode distribution in the central portion of the element, and the high-order mode has a mode distribution in the peripheral portion of the element. Therefore, the high-order mode filter 12-1 has a multilayer structure with respect to the high-order mode. Oscillation is suppressed by selectively reducing the reflectance of the film reflector. As a result, only the fundamental transverse mode oscillates and the single mode output increases, so in the example shown in FIGS. 2 and 3, the laser emission port 12 emits laser light polarized in the X direction.

  Further, in the VCSEL, since the laser emission ports can be arranged on a chip on the same plane with a high density of about several tens of μm, arraying is easier than with an edge emitting laser. For this reason, in the VCSEL 11 of the first embodiment, when the laser emission ports 12 are arranged at a regular interval (for example, 30 μm intervals) in a 6 × 6 two-dimensional array, that is, a total of 36 channels of the laser emission ports 12 are arranged. Although the case will be described as an example, the number of channels and the arrangement interval are not limited to these and can be arbitrarily designed.

  The collimating lens 13 is disposed on the optical path of the linearly polarized light 24 emitted from the VCSEL 11 and makes the light beam of the linearly polarized light 24 substantially parallel light.

  The reflection mirror 14 reflects the linearly polarized light 24 that has been made substantially parallel light by the collimator lens 13 toward the sample 25. Thereby, the linearly polarized light 24 is irradiated to the sample 25. The cylindrical plano-convex lens 15 condenses the linearly polarized light 24 reflected by the reflecting mirror 14. However, the cylindrical plano-convex lens 15 may be omitted.

  In addition, the incident angle θ from the VCSEL 11 to the sample 25 is basically set upward in the vertical direction.

  The sample 25 is a substance to be measured, and fine particles such as cells, microorganisms / organelles / intracellular characters, proteins, gels, solids, liquid crystals, colloids, polymer solutions, polymer melts, and electrolyte solutions. A solution in which is dissolved. Note that the sample 25 may be either transparent or opaque, and may be heterogeneous or a highly viscous and complicated shape.

  The sample 25 is accommodated in the sample holder 23. Examples of the sample holder 23 include a sample cell and a petri dish that are transparent to laser light. However, the sample holder 23 may be omitted, and the sample 25 may be directly arranged on the stage 21 (specifically, the thermostat 22).

  The thermostat 22 is for keeping the temperature of the sample 25 constant.

  The optical microscope 27 is provided in a direction in which the linearly polarized light 24 is emitted from the sample 25. As a result, it is possible to observe the state in which the linearly polarized light 24 is irradiated on the sample 25 with a fine magnification. Note that a half mirror 26 is disposed in front of the optical microscope 27, and the scattered light linearly transmitted through the sample 25 is bent and guided to the light detection system 30-1.

  The light detection systems 30-1 to 30-3 detect scattered light generated when the linearly polarized light 24 enters the sample 25. Specifically, the light detection systems 30-1 to 30-3 detect the intensity of the scattered light. The light detection systems 30-1 to 30-3 are arranged on optical paths in different scattering angle directions.

  The scattering angle can be set between 0 degrees and 180 degrees with the axial direction of the linearly polarized light 24 (upward vertical direction in FIG. 1) being 0 degrees, but the influence of reflection is large between 90 degrees and 180 degrees. Thus, it becomes difficult to obtain internal information of the sample 25.

  For this reason, in the first embodiment, the scattering angle direction in which the light detection system 30-1 is arranged is 90 degrees, the scattering angle direction in which the light detection system 30-2 is arranged is 60 degrees, and the light detection system 30- However, the present invention is not limited to this, and any scattering angle direction may be used as long as the direction is 0 degree to 90 degrees. However, at least one of the light detection systems is preferably arranged in the axial direction (90-degree direction) of the laser light emitted from the VCSEL 11.

  The scattering angle is specifically an angle formed by a line connecting the illumination center on the axis of the linearly polarized light 24 and the center line of a light receiver described later included in the light detection system.

  Further, the light detection systems 30-1 to 30-3 are preferably arranged on substantially the same plane, and in particular, substantially the same plane in the electric field vibration plane of a predetermined polarization direction in which the linearly polarized light 24 is polarized. It is preferable.

  The light detection system 30-1 includes a polarizing filter 31-1 (an example of a polarizing element), a pinhole 32-1, a stray light prevention plate 33-1, a light diffusion plate 34-1, and a light receiver 35-1. including. The light detection system 30-2 includes a polarizing filter 31-2 (an example of a polarizing element), a pinhole 32-2, a stray light prevention plate 33-2, a light diffusion plate 34-2, and a light receiver 35-2. including. The light detection system 30-3 includes a polarizing filter 31-3 (an example of a polarizing element), a pinhole 32-3, a stray light prevention plate 33-3, a light diffusion plate 34-3, and a light receiver 35-3. including.

  However, the light detection systems 30-1 to 30-3 are not limited to these configurations, respectively, and some configurations may be omitted, other configurations may be added, or some configurations may be omitted. It may be replaced with the configuration of

  In the following description, each of the components included in the light detection systems 30-1 to 30-3 will be described by taking the light detection system 30-1 as an example, but the same applies to the light detection systems 30-2 and 30-3. .

  The polarization filter 31-1 polarizes the scattered light in a predetermined angular direction by allowing the linearly polarized component of the scattered light to pass through at a predetermined angle. Specifically, the polarization filter 31-1 allows the linearly polarized component of the scattered light to pass in the polarization direction of the electric field vibration surface or the magnetic field vibration surface of the predetermined polarization direction in which the linearly polarized light 24 is polarized. Is polarized on the electric field vibration surface or the magnetic field vibration surface of the predetermined polarization direction in which the linearly polarized light 24 is polarized. In place of the polarizing filter 31-1, a polarizing beam splitter having the same function as the polarizing filter may be used.

  The pinhole 32-1 allows the light polarized by the polarizing filter 31-1 to pass through. The stray light prevention plate 33-1 is for preventing stray light from entering the light receiver 35-1. The light diffusing plate 34-1 is for preventing damage to the light receiver 35-1.

  The light receiver 35-1 receives light that has passed through the polarizing filter 31-1, and receives light that has passed through the pinhole 32-1. Specifically, the light receiver 35-1 detects the intensity of the received light, converts the detected light intensity into an electrical signal, and outputs the electrical signal to the information processing apparatus 100. Examples of the light receiver 35-1 include a photomultiplier tube and an avalanche diode.

  The information processing apparatus 100 measures the identification information for identifying the type and state of the sample 25 by analyzing the electrical signals output from the light receivers 35-1 to 35-3, To identify the condition.

  In the first embodiment, the positional relationship between the irradiation system 10 and the light detection systems 30-1 to 30-3 is fixed, but the positions of the irradiation system 10 and the light detection systems 30-1 to 30-3 are fixed. These positional relationships may be changed by making controllable. In this way, the scattering angle dependency can also be investigated.

  Next, before explaining the details of the analysis performed by the information processing apparatus 100 according to the first embodiment, in a conventional flow cytometer, if a fluorescent dye is not introduced, information such as intracellular structure and granules is obtained. The reason why it cannot be measured will be explained with reference to “Research on Fine Structure Analysis of Human Nucleated Cells by Light Scattering Measurement (by Yutaka Nagai)”.

  FIG. 4 is an explanatory view of scattering of various particles mixed in a cell, and FIG. 5 is a detailed view of scattering indicated by reference numeral 43 in FIG.

  In the flow cytometer, as described above, the cells flowing in the flow path are irradiated with laser light to measure the forward scattered light and the side scattered light, but the side scattered light (side scattered light intensity) Information on various proteins in the cell and various organelles are mixed. Then, the scattering of small particles indicated by reference numeral 41 in FIG. 4 and the scattering of large particles indicated by reference numeral 42 in FIG. 4 are mixed as indicated by reference numeral 43 in FIG. It was difficult to cleanly separate the shape of large particles from the shape of scattering.

  For this reason, in the flow cytometer, by introducing a fluorescent dye into the cell, the scattering shape of small particles and the scattering shape of large particles are distinguished, and the intracellular information is measured. However, in a flow cytometer, since a fluorescent dye is introduced into a cell, the cell is invaded and cannot be used for applications such as regenerative medicine in which a cell taken out from the body is returned to the body.

  Next, the principle that the information processing apparatus 100 according to the first embodiment can noninvasively measure the type and state of a sample having a complicated fine structure will be described.

  First, as shown in FIG. 6, the present inventors show the scattered light intensity distribution when an incident wave, which is a linearly polarized component of a linearly polarized beam, is irradiated onto the particle 51, and the magnetic field vibration surface 52 and the electric field vibration surface 53. We focused on thinking separately.

  7 shows the scattered light intensity distribution on the magnetic field vibration surface 52 (hereinafter, the magnetic field vibration surface 52 may be referred to as the I1 plane), and FIG. 8 shows the electric field vibration surface 53 (hereinafter, the electric field vibration surface 53 is referred to as I2 plane). 2 shows a scattered light intensity distribution in a case called a plane. θ is an angle between the incident direction and the outgoing direction of light, and it can be confirmed that the scattered light intensity corresponding to the angle differs depending on the polarization direction.

  Then, the inventors detect light with the optical apparatus as described in FIG. 1, that is, transmit and scatter the linearly polarized light 24, which is polarized incident light, to the sample 25, and are different on the same plane. In the light detection systems 30-1 to 30-3 arranged at an angle, the type and state of the sample 25 having a complicated fine structure can be selected by detecting the scattered light with light having a specific polarization direction. I found it.

  For example, the inventors set the linearly polarized light 24 as an incident wave in which the electric field vibration surface 53 is polarized in the vertical direction as shown in FIG. 6, and arranges the light detection system 30-1 on the linear axis of the incident wave. The scattered light intensity polarized on the electric field vibration surface 53 of the incident wave is detected, and the light detection systems 30-2 and 30-3 are different on the same plane of the electric field vibration surface 53 in the polarization direction of the incident wave. The scattered light intensity is detected by different polarization planes, ie, the electric field vibration surface 53 and the magnetic field vibration surface 52, which are arranged at angles. Then, the inventors calculate the ratio of the scattered light intensity of each of the light detection systems 30-1 to 30-3, and compares it with statistical data of various samples calculated in advance, so that the type of the sample 25 and We found that the condition could be identified.

  As shown in FIG. 8, on the I2 plane which is the electric field vibration surface 53 of the outgoing light polarized in a certain direction, a characteristic scattered light distribution is shown, and the shape changes significantly depending on the particle size. For this reason, when the light detection systems 30-1 to 30-3 are arranged on the I2 plane at different angles and scattered light is detected, the intensity of characteristic scattered light in each of the light detection systems 30-1 to 30-3 is increased. can get. Then, by converting the intensity of the obtained scattered light into statistical data, the characteristics of the sample 25 can be digitized, and the type and state of the sample 25 can be identified.

  For example, when there is no change in the polarization angle in the scattered light intensity distribution on the I2 plane in FIG. 8, assuming that the incident wave and the intensity in the linear direction are 1, the intensity in the arrow direction is assumed to be 0.8. However, when the polarized light is incident on the sample 25, the rotation of the polarization angle occurs, so that a drastic change occurs due to the scattered light intensity distribution on the I2 plane, and a pattern peculiar to the sample 25 appears clearly. This is a very effective means for identifying the type and state of the.

  The present inventors obtained a high correct answer rate in discrimination of the type of the sample 25 by this method compared with noninvasive analysis without using a fluorescent dye or the like, but applying the dynamic light scattering method, That is, it has been found that by calculating the time average correlation function-correlation time relaxation data from the time variation of the scattered light and obtaining the time correlation function, a higher correct answer rate can be obtained.

  Next, referring to “Basics and Applications of Light Scattering Method (Kodansha, edited by Mitsuhiro Shibayama et al.)”, The information processing apparatus 100 according to the first embodiment explains how to use the principle of the dynamic light scattering method. To do.

  First, when a sample is irradiated with light, a dipole that oscillates in a molecule in the sample is induced, which emits light as a secondary light source. When the scatterer moves in the medium due to Brownian motion or the like, the frequency of the scattered light changes slightly due to Doppler shift. The dynamic light scattering method obtains knowledge about the motion of the scatterer by using this subtle change in frequency. However, since the change in the scattered light is very small and measurement is almost impossible, the motion of the object is examined by examining the time correlation of the scattered light intensity.

  FIG. 9 is a diagram illustrating an example of a temporal change in scattered light of a sample. As shown in FIG. 9, the scattered light intensity A (t) varies with time t. Here, the time average <A (t)> of A (t) is obtained by integrating A (t) over a long period of time T and dividing by T, as shown in Equation (1).

  Here, the long-term average of the product of A = A (t) at time t and A = A (t + τ) at time t + τ after time τ has elapsed therefrom is referred to as a time correlation function of A (t).

FIG. 10 is a diagram showing the time change of the volume of the overlapping portion when a certain particle moves with the passage of time due to thermal motion, and FIG. 11 is a conceptual diagram of the time correlation function. As shown in FIGS. 10 and 11, the time correlation function can be compared to the time change of the volume of the overlapping portion shown in FIG. That is, at time zero (t = 0), it is the particle volume itself, but decays to zero over time as τ ₁ , τ ₂ , and τ ₃ elapse.

  In the case of the dynamic light scattering method, the physical quantity A is a dielectric constant, a polarizability, a refractive index, a scattered photoelectric field E proportional to them, and a scattered light intensity I.

  When the deviation of A from the average value <A> is δA (t) = δA≡A− <A>, and the time correlation function of δA (t) is handled by an equation including the relaxation rate Γ, Equation (2) It is represented by

Next, the correlation function of the scattered photoelectric field is G ⁽¹⁾ (τ) (first-order correlation function), and the correlation function of the scattered light intensity is G ⁽²⁾ (τ) (second-order correlation function). Using the scattered photoelectric field E (q, t) and the scattered light intensity I _s (q, t), G ⁽¹⁾ (τ) is expressed by Equation (3), and G ⁽²⁾ (τ) is It is expressed by equation (4).

Here, * represents a complex conjugate amount. The relationship between G ⁽¹⁾ (τ) and G ⁽²⁾ (τ) is expressed by Equation (5).

Here, when g ⁽¹⁾ (τ) represented by Formula (6) normalized in the case of τ = 0 and g ⁽²⁾ (τ) represented by Formula (7) are defined, the scattered photoelectric field Siegelt's relational expression that links the correlation function between the light intensity and the scattered light intensity is derived.

  Thereby, a time correlation function of the scattered light intensity as shown in FIG. 12 is obtained.

Here, in the case of other than spherical particles, when g ⁽¹⁾ (τ) and g ⁽²⁾ (τ) are respectively replaced with particle scattering functions, equations (8) and (9) are derived.

  This is the most important basic formula in the dynamic light scattering method, and is used when evaluating the diffusion coefficient and particle size from the correlation function.

Here, the diffusion coefficient D and the scattering vector q when the relaxation rate is Γ (the relaxation time is the inverse Γ ⁻¹ of the relaxation rate, but the relaxation time is represented by τ _R in the first embodiment) Is related to the equation (10).

  Therefore, when the above basic equation is rewritten, Equation (11) is obtained.

When the scatterer is a dilute solution of monodisperse particles, the hydrodynamic radius R _{h of the} particles can be estimated from the diffusion coefficient D using the Einstein-Stokes equation as shown in Equation (12).

Here, k _B is the Boltzmann constant, η is the viscosity of the medium, and D ₀ is the diffusion coefficient at zero concentration.

Next, the scattering vector q will be described. FIG. 13 is an explanatory diagram of interference of scattered light and an optical path difference. In FIG. 13, the phase shift of the scattered light from the origin O and the element _j is represented by q · _Rj , and this vector q is called a scattering vector. In the light scattering measurement, the absolute value of the scattering vector q plays an important role. The scattering vector q is represented by the formula (13), and the absolute value of the scattering vector q is represented by the formula (14).

Also, Γ can be evaluated as shown in Equation (15) from a semilogarithmic plot of g ⁽¹⁾ (τ) with respect to τ.

That is, in the example in which monodisperse particles of polystyrene latex are analyzed, a graph as shown in FIG. 14 is obtained, and Γ is obtained from this slope. If Γ is obtained, the diffusion coefficient D is obtained from the equation (10), and the hydrodynamic radius R _h is also obtained.

In the above description, the monodispersed system is explained. However, when there is a distribution in the particle size, g ⁽¹⁾ (τ) is expressed as Equation (16) using the particle size distribution function H (Γ). The

When H (Γ) is unknown, it can be seen that g ⁽¹⁾ (τ) is a Laplace transform system (F (s) = ∫f (t) e− ^st dt) of H (Γ). Therefore, the particle size distribution function H (Γ) can be evaluated as shown in Expression (17) or Expression (18) by performing inverse Laplace transform on g ⁽¹⁾ (τ) by the CONTIN method.

FIG. 15 is a diagram showing H (Γ) obtained by inverse Laplace transform of g ⁽²⁾ (τ) -1 and g ⁽²⁾ (τ) -1. In FIG. 15, H (Γ) is a single peak, but the polydisperse sample is broadened with respect to the relaxation time (τ _R ) or has a plurality of peaks.

In the first embodiment, the information processing apparatus 100 acquires the detected scattered light intensity in time series for each of the light detection systems 30-1 to 30-3, and calculates the time from the time variation of the acquired scattered light intensity. By calculating the relaxation information of the correlation function-correlation time and obtaining the time correlation function g ⁽¹⁾ (τ), g ⁽²⁾ (τ), a plurality of peaks of the diffusion coefficient D, relaxation time-particle size distribution function diagram A method for obtaining information on various factors such as the relative value of.

  FIG. 16 is a block diagram illustrating an example of a hardware configuration of the information processing apparatus 100 according to the first embodiment. As shown in FIG. 16, the information processing apparatus 100 includes a control device 101 such as a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit), and a main memory such as a ROM (Read Only Memory) and a RAM (Random Access Memory). A device 102, an auxiliary storage device 103 such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive), a display device 104 such as a display, an input device 105 such as a mouse, keyboard or touch panel, a communication interface, etc. The communication apparatus 106 is provided and has a hardware configuration using a normal computer.

  FIG. 17 is a block diagram illustrating an example of a functional configuration of the information processing apparatus 100 according to the first embodiment. As illustrated in FIG. 17, the information processing apparatus 100 includes a signal processing unit 121, an input unit 123, a main control unit 125, a thermostatic plate control unit 127, a lighting control unit 129, a registration unit 131, and a storage unit. 133 and the identification part 135 are included.

  The main control unit 125, the constant temperature plate control unit 127, the lighting control unit 129, the registration unit 131, and the identification unit 135 can be realized by, for example, the control device 101 and the main storage device 102, and the storage unit 133 is, for example, an auxiliary device This can be realized by the storage device 103.

  The signal processing unit 121 processes an electrical signal indicating the intensity of light output from the light receivers 35-1 to 35-3 and receives it as a digital signal. Examples of the signal processing unit 121 include a preamplifier-discriminator and a pulse interval measuring device.

  The input unit 123 inputs a digital signal processed by the signal processing unit 121. For example, a digital input circuit as an interface with the information processing apparatus 100 may be used.

  The main control unit 125 controls the constant temperature plate control unit 127, the lighting control unit 129, the registration unit 131, the storage unit 133, the identification unit 135, and the like.

  The constant temperature plate control unit 127 controls the temperature of the constant temperature plate 22.

  The lighting control unit 129 controls lighting of the VCSEL 11. Specifically, the lighting control unit 129 controls which laser emission port 12 (channel) of the VCSEL 11 emits the linearly polarized light 24 based on a user operation, a program, or the like. Thereby, the linearly polarized light 24 can be irradiated to the sample 25 regardless of the position of the sample 25 accommodated in the sample holder 23 on the stage 21.

  The registration unit 131 acquires a plurality of scattered light intensity detection results by the light detection systems 30-1 to 30-3 performed on samples of the same type or state, and statistical processing based on the plurality of intensity detection results The identification information in which the type or state and the statistical processing result are associated with each other is generated and registered in the storage unit 133. Specifically, the registration unit 131 calculates relaxation information of the time average correlation function-correlation time of each of the plurality of intensity detection results, and statistically processes the plurality of relaxation information. In addition, when the registration part 131 produces | generates identification information, the classification and state of the sample 25 are known.

For example, the registration unit 131 acquires the detected scattered light intensity in time series for each of the light detection systems 30-1 to 30-3, and calculates the time correlation function-correlation time from the time variation of the acquired scattered light intensity. And calculating the time correlation function g ⁽¹⁾ (τ), g ⁽²⁾ (τ) to obtain the diffusion coefficient D, the relative value of multiple peaks in the relaxation time-particle size distribution function diagram, and the like. Ask. And the registration part 131 repeats the above-mentioned process with respect to the sample of the same classification or a state, respectively, and the diffusion coefficient D, relaxation time-particle size distribution for each of the light detection systems 30-1 to 30-3. Multiple relative values of multiple peaks in the function diagram are obtained. The registration unit 131 statistically processes the obtained plurality of diffusion coefficients D, the relative values of the plurality of peaks in the relaxation time-particle size distribution function diagram for each of the light detection systems 30-1 to 30-3, and the identification information. Is generated.

  The identification unit 135 identifies the type or state of the sample based on the intensity of the scattered light detected by the light detection systems 30-1 to 30-3. When the identification unit 135 performs identification, the type and state of the sample 25 are unknown. Specifically, the identification unit 135 acquires the intensity detection result of the scattered light by the light detection systems 30-1 to 30-3 performed on the sample of unknown type or state, and based on the intensity detection result Comparison with identification information is performed to identify an unknown type or state. Specifically, the identification unit 135 calculates relaxation information of the time average correlation function-correlation time of the intensity detection result, compares the relaxation information with the identification information registered in the storage unit 133, and determines the unknown type or state. Is identified.

For example, the identification unit 135 acquires the detected scattered light intensity in time series for each of the light detection systems 30-1 to 30-3, and calculates the time correlation function-correlation time from the time change of the acquired scattered light intensity. And calculating the time correlation function g ⁽¹⁾ (τ), g ⁽²⁾ (τ) to obtain the diffusion coefficient D, the relative value of multiple peaks in the relaxation time-particle size distribution function diagram, and the like. Ask. Then, the identification unit 135 compares the obtained diffusion coefficient D, the relative values of a plurality of peaks in the relaxation time-particle size distribution function diagram with the identification information registered in the storage unit 133, and identifies an unknown type or state. To do.

Example 1
Example 1 describes an example in which cells are used as the sample 25 and the cell type is identified in the first embodiment. In the first embodiment, the light detection systems 30-1 to 30-3 are arranged on the same plane of the electric field vibration plane of a predetermined polarization direction in which the linearly polarized light 24 is polarized, and the light detection systems 30-1 to 30-3 are arranged. The distributed scattering angle directions were 90, 60 and 45 degrees, respectively.

  The cell types to be identified are neutrophils, lymphocytes, basophils, and eosinophils, each of which detects the intensity of scattered light for 10000 events. It is assumed that identification information is generated by statistically processing the intensity detection. FIG. 18 is a diagram illustrating the identification information of Example 1, and is a statistical analysis diagram of the statistical processing result described above. S1 represents the light detection system 30-1, S2 represents the light detection system 30-2, and S3 represents the light detection system 30-3. In FIG. 18, since the scattered light intensities of S2 and S3 are very small values compared to the scattered light intensity of S1, the axes of the scattered light intensities of S2 and S3 are expanded 100 times.

  Then, the identification unit 135 uses the identification information shown in FIG. 18 to identify the cell type for each of 100 events, with neutrophils, lymphocytes, basophils, and eosinophils as unknown cells. Table 1 shows the correct answer rate.

  In Table 1, H indicates that the polarization direction of the corresponding light detection system is the magnetic field vibration plane with respect to the polarization direction of the irradiation system 10, and E indicates the corresponding light detection with respect to the polarization direction of the irradiation system 10. The polarization direction of the system indicates an electric field vibration plane, and-indicates that the corresponding light detection system is not used.

  In Table 1, as a comparative example, a result of statistical analysis based on scattered light intensity without using the polarizing filters 31-1 to 31-3 is also shown.

  From Table 1, it can be confirmed that the correct answer rate is significantly improved in Experiment Nos. 1 to 10 in which polarization is considered, compared to Comparative Examples 1 and 2 in which polarization is not considered. In particular, when identification is performed using the light detection system of S3 in addition to the light detection systems of S1 and S2, a good accuracy rate is shown.

  However, in Example 1, the correct answer rate of 100% has not been approached yet. This is because, as shown in FIG. 18, the relative positions of the statistical analysis of each cell cannot be completely separated.

  In Example 1, it can be seen that the correct answer rate is better when the scattered light intensity at the electric field vibration plane (E) is positively acquired as the polarization direction. Considering the light reception in S1, the fact that S1 receives the irradiation light polarized on the electric field vibration surface (E) as E-polarized light means that light that is scattered by the cell of Example 1 and has not undergone polarization. Is observing. In addition, the fact that S1 receives the irradiation light polarized on the electric field vibration plane (E) as H-polarized light means that the light scattered by the cell of Example 1 and observing the polarized light is observed. is there. That is, it is presumed that the light receiving unpolarized light is observed stronger than the polarized light and the S / N ratio is improved.

(Example 2)
In Example 2, an example in which cells are used as the sample 25 and the cell type is identified in the first embodiment will be described. Also in the second embodiment, the light detection systems 30-1 to 30-3 are arranged on the same plane of the electric field vibration surface of the predetermined polarization direction in which the linearly polarized light 24 is polarized, and the light detection systems 30-1 to 30-3 are provided. The distributed scattering angle directions were 90, 60 and 45 degrees, respectively.

Further, the cell types to be identified are neutrophils, lymphocytes, basophils, and eosinophils, each of which obtains a temporal change in scattered light intensity by 10,000 events, and a time correlation function-correlation time relaxation information. Is calculated, and the time correlation functions g ⁽¹⁾ (τ), g ⁽²⁾ (τ) are obtained to obtain relative values of a plurality of peaks of the relaxation time-particle size distribution function diagram, and statistical processing is performed for identification information. Is generated.

FIG. 19 is a diagram illustrating identification information of the second embodiment, and is a statistical analysis diagram of the statistical processing result described above. In FIG. 19, a graph of the relaxation time-particle size distribution function diagram as shown in FIG. 15 is finally obtained, and the largest of several peaks appearing in the graph is represented by P1, the second largest peak. Each relaxation time (τ _R ) and peak intensity ratio P1 / P2 are determined as P2.

  As a result of identifying the neutrophils, lymphocytes, basophils, and eosinophils as unknown cells, the identification unit 135 identifies the cell types for 100 events each using the identification information shown in FIG. Table 2 shows the correct answer rate.

  In Table 2, the correct answer rate is closer to 100% than Example 1. This is because, as shown in FIG. 19, the relative positions of the statistical analysis of each cell can be separated.

  Also in Example 2, it can be seen that the correct answer rate is better when the polarization direction positively acquires the scattered light intensity at the electric field vibration plane (E). The reason is the same as in the first embodiment.

  In Examples 1 and 2 described above, an example in which cells are used as a sample and the cell type is identified has been described. However, the sample may be other than the cell as long as it is described above, and not only the type but also the state is identified. You can also

  For example, in the field of regenerative medicine, undifferentiated cells may be mixed in differentiated cell groups. However, if the first embodiment is applied, undifferentiated cells are included in cell groups. It can also be expected that the state of the cell group can be identified, such as whether it is mixed.

  As described above, according to the first embodiment, since the type or state of the sample is measured by the polarization of light, it is possible to noninvasively measure the type or state of the sample, and the colony, colloid, and gel It can also be applied to a sample with a complicated fine structure other than a single cell. In particular, the first embodiment is suitable for regenerative medicine and the like because the type or state of the sample can be measured non-invasively. In addition, according to the first embodiment, since the VCSEL is used as the light source of the irradiation system, it is possible to emit linearly polarized light in a predetermined polarization direction without using a polarization element or the like, so that the configuration of the irradiation system is simplified. In addition, the cost can be reduced and the optical device and the information processing system can be simplified and reduced in cost.

(Second Embodiment)
In the first embodiment, the present inventors calculate the ratio of the scattered light intensity of each of the light detection systems 30-1 to 30-3, and by comparing with statistical data of various samples calculated in advance, It has been explained that the type and state of the sample 25 can be identified.

  By the way, when the sample 25 has a remarkable measurement position dependency on the scattered light intensity, the scattered light intensity greatly changes when the measurement position is changed. However, the present inventors have proposed the light detection systems 30-1 to 30-3. In each, a time average scattered light intensity, which is a temporal change in scattered light intensity at each position on the polarization plane, is calculated, an ensemble average is calculated from the calculated time average scattered light intensity at each position, and is calculated in advance. It was also found that the type and state of the sample 25 having the measurement position dependency can be identified by comparing with the statistical data of various samples.

  Further, the present inventors further obtain ensemble average correlation function-relaxation time relaxation data based on time average correlation function-correlation time relaxation data of scattered light intensity at each position of the sample 25. It was also found that a high correct answer rate can be obtained.

  Therefore, in the second embodiment, the above method will be described. In the following, differences from the first embodiment will be mainly described, and components having the same functions as those in the first embodiment will be given the same names and symbols as those in the first embodiment, and the description thereof will be made. Omitted.

  In the following, regarding the ensemble average correlation function, the collection of polymer papers, Vol. 59, no. 10 (2002). When the scattering system is in thermal equilibrium, the time average of the scattered light intensity is calculated based on statistical mechanics. In statistical mechanics, it is assumed by the ergodic hypothesis that the statistical average and the time average agree.

  FIG. 20 is a diagram illustrating an example of the position dependency of the scattered light intensity of the polymer solution, and FIG. 21 is a diagram illustrating an example of the position dependency of the scattered light intensity of the biological system or the gel. As shown in FIG. 20, when the scattered light from the polymer solution is measured while shifting the measurement position (sample position), the scattered light intensity hardly changes even when the position is changed. However, as shown in FIG. When the scattered light from the system or gel is measured while shifting the measurement position (sample position), the scattered light intensity greatly changes when the position is changed.

  Thus, it can be seen that in biological systems such as cells and gels, the scattered light intensity has a significant position dependency. This is because biological systems such as cells and gels are non-ergodic systems in which the equivalence between the time average and the ensemble average (position average) does not hold.

Therefore, in order to describe such a system and accurately discriminate these types, properties, or states, we define time-average scattered light intensity <I> _T and ensemble scattered light intensity <I> _E. And you need to ask. The time-averaged scattered light intensity <I> _T, certain measurement points p, a long-time average of the scattered light intensity <I> p _t at a certain time t, ensemble scattered light intensity <I> _E is time-averaged scattered light Intensity <I> An ensemble average of _T. That is, the relationship shown in Equation (19) is established between the time-average scattered light intensity <I> _T and the ensemble scattered light intensity <I> _E.

When the measurement position dependency is significant like biological samples and gels, the inventors have compared the time average scattered light intensity <I with respect to the known samples in the respective polarization directions of the light detection systems 30-1 to 30-3. > Ensemble scattered light intensity <I> which is an ensemble average of _T <I> _E is obtained, and the relationship between the light detection systems 30-1 to 30-3 and the sample is statistically processed. By obtaining the ensemble scattered light intensity <I> _E , which is the ensemble average of _T in the polarization direction of each of the light detection systems 30-1 to 30-3, and comparing it with the statistical processing result, the unknown We found that we can estimate the known sample that seems to be the best fit for our sample. In addition, the present inventors consider the dynamic light scattering component in the ensemble average of the time average scattered light intensity <I> _T in the polarization direction of each of the light detection systems 30-1 to 30-3. We found that the estimation accuracy is improved.

Below, the method of considering a dynamic light-scattering component in the ensemble average of time average scattered light intensity <I> _T is demonstrated.

  As described above, in the non-ergodic system, the time average and the ensemble average are different. In addition, as the scattered light intensity has a time average and an ensemble average, the correlation function also has a time average correlation function and an ensemble average correlation function.

In FIG. 1, the linearly polarized light 24 is sequentially emitted from each laser emission port 12 (each channel) of the VCSEL 11, so that each of the light detection systems 30-1 to 30-3 is at each position (multiple points) on the sample 25. The intensity of scattered light can be measured. Thereby, at each position (each point) on the light detection systems 30-1 to 30-3 and the sample 25, the time-average correlation function g _t ⁽²⁾ (q, τ) -correlation is obtained by Expression (9). Time relaxation data can be obtained.

Then, for each photodetecting system 30-1 to 30-3, by using the relaxation data at each position (each point) on the sample 25, the equation (20), the ensemble average correlation function _g ^{en (1)} ( q, τ) -correlation time relaxation data can be determined.

  Here, sp is the spatial average, en is the ensemble average, I is the scattered light intensity, and γ is the device constant.

The ensemble average correlation function ^{_{g en (1) (q,}} τ) - relaxation data of the correlation time, so is represented by the graph shown in FIG. 22, the static component _I s (q) and dynamic component I _d (q). The static component I _s (q) is caused by speckle (glaring observed in a laser or the like), and has a different baseline in measurement of biological samples and gels depending on the measurement location. It is difficult to find a specific meaning. On the other hand, the dynamic component I _d (q) is important because it directly reflects the amplitude of the dynamic fluctuation in the scattering volume.

The thus obtained ensemble average correlation function ^{_{g en (1) (q,}} τ) - relaxation data of correlation times to inverse Laplace transform by CONTIN method, using the equation (21), the dynamic of the internal sample It is possible to acquire relaxation time distribution-relaxation time peak data that does not particularly assume fluctuations.

In this analysis method, the correlation function relaxation profile is fitted by the nonlinear least square method using the linear combination of Equation (21). Here, τ _{R, i} = τ _{R, 0} × (τ _{R, max} / τ _{R, 0} ) ^{i / (n−1)} (i = 0, 1,..., N−1), and arbitrary relaxation The function can be expanded by a linear combination of single exponential functions such as Equation (21). From such fitting, a distribution function P (τ _R ) of relaxation time τ _R is calculated, and peak data of relaxation time distribution-relaxation time as shown in FIG. 23 can be acquired.

  In the second embodiment, the information processing apparatus 200 calculates the time change of the scattered light intensity at each position on the known sample in the polarization direction for each of the light detection systems 30-1 to 30-3. Based on the time variation of the scattered light intensity, the time average correlation function-correlation time relaxation data is calculated. Based on the calculated relaxation data at each position on the known sample, the ensemble average correlation function-correlation time relaxation data is calculated. By obtaining, the method of obtaining the relaxation time distribution-relaxation time peak data is adopted. Then, the calculation of peak data is repeated, and the factors representing the characteristics of the most known sample are extracted from the information of various factors of the obtained peak data, and the relationship with the light detection systems 30-1 to 30-3 and The relation with a known sample is statistically processed and used as identification information for identification.

  In the second embodiment, the information processing apparatus 200 calculates the temporal change of the scattered light intensity at each position on the unknown sample in the polarization direction for each of the light detection systems 30-1 to 30-3. The time average correlation function-correlation time relaxation data is calculated from the time variation of the scattered light intensity, and the ensemble average correlation function-correlation time relaxation data is calculated based on the calculated relaxation data at each position on the unknown sample. Is obtained, peak data of relaxation time distribution-relaxation time is obtained, and an unknown sample is identified by comparing with identification information.

  FIG. 24 is a block diagram illustrating an example of a functional configuration of the information processing apparatus 200 according to the second embodiment. As illustrated in FIG. 24, in the information processing apparatus 200, a lighting control unit 229, a registration unit 231, and an identification unit 235 are different from those in the first embodiment.

  The lighting control unit 229 performs control so that the linearly polarized light 24 is sequentially emitted from each laser emission port 12 (each channel) of the VCSEL 11 based on a user operation or a program. Thereby, control can be performed so that linearly polarized light is incident on a plurality of positions on the sample 25.

  The registration unit 231 measures the type or state of the sample 25 by obtaining an ensemble average obtained by averaging the time average of scattered light at each position of the sample 25 for each of the light detection systems 30-1 to 30-3. To do. Specifically, the registration unit 231 calculates the ensemble average of each of the light detection systems 30-1 to 30-3 for a sample of the same type or state a plurality of times, and based on a plurality of ensemble averages obtained a plurality of times. Statistical processing is performed, identification information in which the type or state is associated with the statistical processing result is generated, and registered in the storage unit 133. In addition, when the registration part 231 produces | generates identification information, the classification and state of the sample 25 are known.

  For example, the ensemble average can be an ensemble average obtained by averaging the time average of the intensity of scattered light at each position of the sample.

  Further, for example, the ensemble average may be an ensemble average correlation function-correlation time relaxation data using a time average correlation function-correlation time relaxation data of scattered light intensity at each position of the sample. In this case, the registration unit 231 acquires the time-series scattered light intensity at each position on the sample in the polarization direction for each of the light detection systems 30-1 to 30-3, and the acquired time-series scattered light intensity. Then, the time change of the scattered light intensity is calculated, and the relaxation data of the time average correlation function-correlation time is calculated from the time change of the calculated scattered light intensity. The registration unit 231 then calculates the ensemble average correlation function-correlation time from the relaxation data of the time average correlation function-correlation time at each position on the sample 25 in the polarization direction for each of the light detection systems 30-1 to 30-3. By obtaining the relaxation data, the peak data of relaxation time distribution-relaxation time is obtained. Further, the registration unit 231 repeats calculation of peak data. And the registration part 231 extracts the factor which represents the characteristic of the sample most among the information of the various factors of the peak data obtained in this way, the relationship with the photodetection systems 30-1 to 30-3 and the sample Statistical processing of the relationship.

  The identification unit 235 measures the type or state of the sample 25 by obtaining an ensemble average obtained by averaging the time average of the scattered light at each position of the sample 25 for each of the light detection systems 30-1 to 30-3. To do. Specifically, the identification unit 235 identifies the type or state of the sample 25 based on the ensemble average of each of the light detection systems 30-1 to 30-3. Specifically, the identification unit 235 compares the identification information based on the ensemble averages of the light detection systems 30-1 to 30-3 obtained for the sample 25 of unknown type or state, Identify the condition.

  For example, the ensemble average can be an ensemble average obtained by averaging the time average of the intensity of scattered light at each position of the sample.

  Further, for example, the ensemble average may be an ensemble average correlation function-correlation time relaxation data using a time average correlation function-correlation time relaxation data of scattered light intensity at each position of the sample. In this case, the identification unit 235 acquires the time-series scattered light intensity at each position on the sample in the polarization direction for each of the light detection systems 30-1 to 30-3, and the acquired time-series scattered light intensity. Then, the time change of the scattered light intensity is calculated, and the relaxation data of the time average correlation function-correlation time is calculated from the time change of the calculated scattered light intensity. Then, the identification unit 235 calculates the ensemble average correlation function-correlation time from the relaxation data of the time average correlation function-correlation time at each position on the sample 25 in the polarization direction for each of the light detection systems 30-1 to 30-3. By obtaining the relaxation data, the peak data of relaxation time distribution-relaxation time is obtained. Furthermore, the identification unit 235 compares the obtained peak data with the identification information registered in the storage unit 133 to identify an unknown type or state.

Example 3
In Example 3, an example in which cells are used as the sample 25 and the cell type is identified in the second embodiment will be described. In the third embodiment, the light detection systems 30-1 to 30-3 are arranged on the same plane of the electric field vibration plane of a predetermined polarization direction in which the linearly polarized light 24 is polarized, and the light detection systems 30-1 to 30-3 are provided. The distributed scattering angle directions were 90, 60 and 45 degrees, respectively.

Further, the cell types to be identified are neutrophils, lymphocytes, basophils, and eosinophils, each of which is irradiated with linearly polarized light 24 at an arbitrary place for 10,000 events. The registration unit 231 calculates the time-average scattered light intensity <I> _T from the temporal change of the scattered light intensity at each position of the cell type (polarization plane) for each of the light detection systems 30-1 to 30-3. The ensemble scattered light intensity <I> _E , which is the ensemble average of _T , was calculated. However, in order to make the distribution of the ensemble scattered light intensity <I> _E having a certain range, the registration unit 231 applies linearly polarized light 24 from each laser emission port 12 (each channel) of the VCSEL 11 when measuring the event of each cell type. For each of the light detection systems 30-1 to 30-3, the time average scattered light intensity <I> _T is calculated at each position of the cell type, and the calculated time average scattered light intensity <I> at each position is calculated. _The ensemble scattered light intensity <I> _E , which is an ensemble average of _T , is calculated, and the ensemble scattered light intensity <I> _E previously calculated based on the ensemble scattered light intensity <I> _E is statistically processed to obtain identification information. It is assumed that it is generated.

  FIG. 25 is a diagram illustrating the identification information of Example 3, and is a statistical analysis diagram of the statistical processing result described above. S1 represents the light detection system 30-1, S2 represents the light detection system 30-2, and S3 represents the light detection system 30-3. In FIG. 25, since the scattered light intensities of S2 and S3 are very small values compared to the scattered light intensity of S1, the axes of the scattered light intensities of S2 and S3 are expanded 100 times.

  Then, the identification unit 235 uses the identification information shown in FIG. 25 to identify the cell types for 100 events each, using neutrophils, lymphocytes, basophils, and eosinophils as unknown cells. Table 3 shows the correct answer rate.

  In Table 3, H indicates that the polarization direction of the corresponding light detection system is the magnetic field vibration plane with respect to the polarization direction of the irradiation system 10, and E indicates the corresponding light detection with respect to the polarization direction of the irradiation system 10. The polarization direction of the system indicates an electric field vibration plane, and-indicates that the corresponding light detection system is not used.

  In Table 3, as a comparative example, a result of statistical analysis based on scattered light intensity without using the polarizing filters 31-1 to 31-3 is also shown.

  From Table 3, it can be confirmed that the correct answer rate is significantly improved in Experiment Nos. 21 to 30 in which polarization is considered, compared to Comparative Examples 3 and 4 in which polarization is not considered. In particular, when identification is performed using the light detection system of S3 in addition to the light detection systems of S1 and S2, a good accuracy rate is shown.

  However, in Example 3, the correct answer rate of 100% has not been approached yet. This is because, as shown in FIG. 25, the relative positions of the statistical analysis of each cell cannot be completely separated.

  In Example 3, it can be seen that the correct answer rate is better when the scattered light intensity at the electric field vibration plane (E) is positively acquired as the polarization direction. Considering the light reception in S1, the fact that S1 receives the irradiation light polarized on the electric field oscillation surface (E) as E-polarized light means that the light is scattered by the cell of Example 3 and no polarization occurs. Is observing. In addition, the fact that S1 receives the irradiation light polarized on the electric field oscillation plane (E) as H-polarized light means that light that is scattered by the cell of Example 3 and polarized at 90 degrees is observed. That's what it means. That is, it is presumed that the light receiving unpolarized light is observed stronger than the polarized light and the S / N ratio is improved.

Example 4
In Example 4, an example in which cells are used as the sample 25 and the cell type is identified in the second embodiment will be described. Also in Example 4, the light detection systems 30-1 to 30-3 are arranged on the same plane of the electric field vibration surface, and the scattering angle directions in which the light detection systems 30-1 to 30-3 are arranged are 90 degrees, respectively. Direction, 60 degree direction, and 45 degree direction.

  The cell types to be identified were neutrophils, lymphocytes, basophils, and eosinophils, and each was irradiated with linearly polarized light 24 at an arbitrary place for 10,000 events. The registration unit 231 calculates, for each of the light detection systems 30-1 to 30-3, time-average correlation function-correlation time relaxation data from the time change of the scattered light intensity at each position of the cell type (polarization plane). The relaxation time distribution-relaxation time peak data was obtained by calculating the ensemble average correlation function-correlation time relaxation data using the calculated time-average correlation function-correlation time relaxation data at each position. However, in order to make the relaxation time distribution-relaxation time peak data into a distribution having a certain range, the registration unit 231 uses 50 events for each cell type event measurement, and uses the relaxation time distribution-relaxation time peak data. It is assumed that identification information is generated by statistically processing the obtained peak data of a plurality of relaxation time distributions-relaxation times.

FIG. 26 is a diagram illustrating the identification information of Example 4, and is a statistical analysis diagram of the statistical processing result described above. In FIG. 26, a graph of relaxation time distribution-relaxation time as shown in FIG. 23 is finally obtained, the largest of several peaks appearing in the graph is P1, and the second largest peak is P2. Each relaxation time τ _R and peak intensity ratio P1 / P2 are obtained.

  Then, the identification unit 135 uses the identification information shown in FIG. 26 to identify the cell type for each of 100 events, with neutrophils, lymphocytes, basophils, and eosinophils as unknown cells. Table 4 shows the correct answer rate.

  In Table 4, the correct answer rate is closer to 100% than Example 3. This is because, as shown in FIG. 26, the relative positions of the statistical analysis of each cell can be separated.

  Also in Example 4, it can be seen that the correct answer rate is better when the polarization direction positively acquires the scattered light intensity at the electric field vibration plane (E). The reason is the same as in the third embodiment.

  In Examples 3 and 4 described above, an example in which cells are used as a sample and a cell type is identified has been described. However, the sample may be other than a cell as long as it is described above, and not only the type but also the state is identified. You can also

  For example, in the field of regenerative medicine, undifferentiated cells may be mixed in differentiated cell groups, but if this embodiment is applied, undifferentiated cells are mixed in cell groups. It can also be expected that the state of the cell group can be identified.

  As described above, according to the second embodiment, since the type or state of the sample is measured based on the polarization of light, the type or state of the sample can be measured non-invasively, and the scattered light intensity greatly depends on the measurement position. The present invention can also be applied to a sample having a complicated fine structure other than a single cell such as a colony, a colloid, and a gel. In particular, the present embodiment is suitable for regenerative medicine and the like because the type or state of the sample can be measured non-invasively. In addition, according to the second embodiment, since VCSEL is used as the light source of the irradiation system, it is possible to emit linearly polarized light in a predetermined polarization direction without moving through a polarizing element or the like, and control such as moving the position of the stage. Even if not, linearly polarized light can be incident on a plurality of positions on the sample. For this reason, according to the second embodiment, the configuration of the irradiation system can be simplified and the cost can be reduced. Further, the configuration of the optical device can be simplified and the cost can be reduced. Simplification and cost reduction can be further achieved.

1 Information processing system 10 Irradiation system 11 VCSEL
13 Collimating Lens 14 Reflecting Mirror 15 Cylindrical Plano-Convex Lens 21 Stage 22 Constant Temperature Plate 23 Sample Holder 25 Sample 26 Half Mirror 27 Optical Microscope 30-1, 30-2, 30-3 Photodetection System 31-1, 31-2, 31 -3 Polarizing filter 32-1, 32-2, 32-3 Pinhole 33-1, 33-2, 33-3 Stray light prevention plate 34-1, 34-2, 34-3 Light diffusion plate 35-1, 35 -2, 35-3 Photoreceiver 100, 200 Information processing apparatus 101 Control apparatus 102 Main storage apparatus 103 Auxiliary storage apparatus 104 Display apparatus 105 Input apparatus 106 Communication apparatus 121 Signal processing section 123 Input section 125 Main control section 127 Constant temperature plate control section 129, 229 Lighting control unit 131, 231 Registration unit 133 Storage unit 135, 235 Identification unit

JP 2010-200696 A

Claims (13)

An irradiation system that emits linearly polarized light in a predetermined polarization direction toward the sample;
A plurality of light detection systems for detecting scattered light generated when the linearly polarized light enters the sample, and
The irradiation system includes a vertical surface emitting laser that emits the linearly polarized light,
The plurality of light detection systems are arranged on optical paths in different scattering angle directions, respectively, a polarizing element that allows a linearly polarized component of the scattered light to pass through at a predetermined angle, and light that has passed through the polarizing element. An optical device including a light receiver for receiving light.   The optical device according to claim 1, wherein the plurality of light detection systems are arranged on substantially the same plane.   The optical device according to claim 2, wherein the substantially same plane is substantially the same plane in the electric field vibration plane of the predetermined polarization direction.   The polarization element included in each of the plurality of light detection systems allows the linearly polarized component of the scattered light to pass in the polarization direction of the electric field vibration surface or the magnetic field vibration surface of the predetermined polarization direction. The optical apparatus as described in any one. The plurality of light detection systems detect the intensity of scattered light generated when the linearly polarized light enters the sample,
The optical device according to any one of claims 1 to 4, wherein the light receiver included in each of the plurality of light detection systems receives light that has passed through the polarizing element and detects the intensity of the received light. . An optical device according to claim 5;
Based on the intensity of scattered light detected by the plurality of light detection systems, an identification unit for identifying the type or state of the sample,
An information processing system comprising: An optical device according to claim 5;
A plurality of scattered light intensity detection results obtained by the plurality of light detection systems performed on samples of the same type or state are obtained, and statistical processing based on the plurality of intensity detection results is performed, and the type or state and statistics are obtained. A registration unit for registering identification information associated with a processing result;
An information processing system comprising:   Obtaining the intensity detection result of the scattered light by the plurality of light detection systems performed on the sample of the unknown type or state, performing a comparison with the identification information based on the intensity detection result, the unknown type or The information processing system according to claim 7, further comprising an identification unit that identifies a state. The registration unit calculates relaxation information of time average correlation function-correlation time for each of the plurality of intensity detection results, and statistically processes the plurality of relaxation information,
The said identification part calculates the relaxation information of the time average correlation function-correlation time of the said intensity | strength detection result, compares the said relaxation information and the said identification information, and identifies the said unknown classification or state. Information processing system. An optical device according to claim 5,
The irradiation system includes a vertical surface emitting laser array in which a plurality of the vertical surface emitting lasers are arranged and the linearly polarized light is emitted to a plurality of positions on the sample,
For each of the light detection systems, obtain an ensemble average obtained by averaging the time average of the intensity of the scattered light at each position of the sample, and based on the ensemble average of each of the plurality of light detection systems, An information processing system further comprising an identification unit for identifying a state. An optical device according to claim 5,
The irradiation system includes a vertical surface emitting laser array in which a plurality of the vertical surface emitting lasers are arranged and the linearly polarized light is emitted to a plurality of positions on the sample,
For each light detection system, obtain an ensemble average obtained by averaging the time average of the intensity of scattered light at each position of the sample of the same type or state, and based on the plurality of ensemble averages obtained multiple times An information processing system further comprising a registration unit that performs statistical processing and registers identification information in which the type or state is associated with a statistical processing result.   For each of the light detection systems, obtain an ensemble average obtained by averaging time averages of the intensity of scattered light at each position of a sample of an unknown type or state, and the identification based on the ensemble average of each of the plurality of light detection systems The information processing system according to claim 11, further comprising an identification unit that performs comparison with information and identifies the unknown type or state.   13. The information processing according to claim 12, wherein the ensemble average is ensemble average correlation function-relaxation time relaxation data using time average correlation function-correlation time relaxation data of scattered light intensity at each position of the sample. system.