Sample measurement apparatus, and flow path device for sample measurement apparatus

Abstract

To provide a sample measurement apparatus capable of quickly and accurately identifying a minute object to be measured.SOLUTION: A sample measurement apparatus 1 comprises a flow path device 10 and a measurement unit 30. The flow path device 10 includes a flow path tip 11 in which an introduction part 13, a minute flow path 14 and a discharge part 15 are formed, and an electrode tip 21 in which a first electrode 23 and a second electrode 24 are formed on a substrate. The minute flow path 14 is formed in the flow path tip 11. The introduction part 13 is arranged on one end of the minute flow path 14. The discharge part 15 is arranged on the other end of the minute flow path. The first electrode 23 and the second electrode 24 are arranged at positions corresponding to the introduction part 13 and the discharge part 15. The measurement unit 30 applies an AC voltage to the first electrode 23 and second electrode 24 and measures the AC characteristic of the object 42 to be measured at the time when the object 42 to be measured has passed through the minute flow path 14. The flow path device 10 is constituted by bonding the electrode tip 21 and flow path tip 11.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to a sample measurement device and a flow path device for a sample measurement device, and particularly to a sample measurement device capable of measuring minute measurement objects and a flow path device for a sample measurement device.

Background Art

[0002] As detection methods for viruses, bacteria, microorganisms, or viroids (hereinafter also simply referred to as viruses, etc.), the polymerase chain reaction (PCR) method, the immunochromatography method, and the like are known. On the other hand, as another detection method, a sensing method for viruses, etc. by electrical measurement has been studied. As an example of the electrical measurement method, there is a method of dispersing the virus, etc. to be detected in water and electrically detecting the virus, etc. as particles. From the viewpoints of prevention and prevention of spread of infectious diseases, etc., detection of viruses, etc. in environments such as indoors, livestock houses, and outdoors is required. In such environmental sensing, the above electrical measurement method is suitable (for example, Patent Documents 1 and 2).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] As described above, from the viewpoints of prevention and prevention of spread of infectious diseases, etc., a technology for quickly and accurately identifying minute measurement objects such as viruses, bacteria, microorganisms, or viroids in the environment is required. In view of such problems, an object of the present invention is to provide a sample measurement device capable of quickly and accurately identifying minute measurement objects.

Means for Solving the Problems

[0005] A sample measurement device according to one aspect of the present invention includes a flow path device and a measurement unit. The flow path device includes a flow path chip in which an introduction part, a micro flow path, and a discharge part are formed, and an electrode chip in which a first electrode and a second electrode are formed on a substrate. The micro flow path is formed in the flow path chip. The introduction part is disposed on one side of the micro flow path, and the discharge part is disposed on the other side of the micro flow path. The first electrode is disposed at a position corresponding to the introduction part, and the second electrode is disposed at a position corresponding to the discharge part. The measurement unit applies an alternating voltage to the first electrode and the second electrode, measures the alternating characteristics of the measurement object when the measurement object passes through the micro flow path, and the flow path device is configured by bonding the electrode chip and the flow path chip.

[0006] A flow path device for a sample measurement device according to one aspect of the present invention includes a flow path chip in which an introduction part, a micro flow path, and a discharge part are formed, and an electrode chip in which a first electrode and a second electrode are formed on a substrate. The micro flow path is formed in the flow path chip. The introduction part is disposed on one side of the micro flow path, and the discharge part is disposed on the other side of the micro flow path. The first electrode is disposed at a position corresponding to the introduction part, and the second electrode is disposed at a position corresponding to the discharge part. The electrode chip and the flow path chip are bonded together and configured to measure alternating characteristics.

Effects of the Invention

[0007] According to the present invention, it is possible to provide a sample measurement device capable of quickly and accurately identifying a minute measurement object.

Brief Description of the Drawings

[0008]

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BEST MODE FOR CARRYING OUT THE INVENTION

[0009] Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 and FIG. 2 are cross-sectional views for explaining the sample measuring apparatus according to the embodiment. As shown in FIGS. 1 and 2, the sample measuring apparatus 1 according to the present embodiment includes a flow path device 10 and a measuring unit 30. The flow path device 10 includes an introduction unit 13, a microchannel 14, a discharge unit 15, a first electrode 23, and a second electrode 24. Note that FIG. 2 shows a state in which the measurement object 42 is introduced into the sample measuring apparatus 1 shown in FIG. 1.

[0010] As shown in Fig. 2, the flow path device 10 includes a microchannel 14 through which a sample solution 40 containing a measurement target 42 dispersed in a solvent 41 flows, an introduction unit 13 disposed on one side (upstream side) of the microchannel 14 for introducing the sample solution 40 into the microchannel 14, and a discharge unit 15 disposed on the other side (downstream side) of the microchannel 14 from which the sample solution 40 is discharged. An inlet 16 is provided on the upper surface of the introduction unit 13, and the sample solution 40 is introduced into the introduction unit 13 through this inlet 16. An outlet 17 is provided on the upper surface of the discharge unit 15, and the sample solution 40 is discharged to the outside through this outlet 17. Further, a first electrode 23 is disposed at a position corresponding to the introduction unit 13 in a plan view. A second electrode 24 is disposed at a position corresponding to the discharge unit 15 in a plan view.

[0011] The sample measurement device 1 according to the present embodiment is a device used for identifying a measurement target 42 such as a virus, a bacterium, or a microorganism. Note that the sample measurement device 1 according to the present embodiment can identify a target other than a virus, a bacterium, or a microorganism as long as it is an object that can be dispersed in the solvent 41. In the present embodiment, an ionic liquid can be used as the solvent 41. Further, in the present embodiment, a liquid other than the ionic liquid (for example, an aqueous solution) may be used as the solvent 41.

[0012] Fig. 3 is an exploded perspective view for explaining the flow path device of the sample measurement device according to the present embodiment. As shown in Fig. 3, the flow path device 10 includes a flow path chip 11 in which an introduction unit 13, a microchannel 14, and a discharge unit 15 are formed, and an electrode chip 21 in which a first electrode 23 and a second electrode 24 are formed on a substrate 22. In the present embodiment, the flow path device 10 is configured by bonding the electrode chip 21 and the flow path chip 11. Note that Fig. 3 shows a state in which the flow path chip 11 is turned over.

[0013] The flow path chip 11 can be formed using silicone rubber 12. Specifically, the flow path chip 11 can be fabricated using micro-molding of silicone rubber 12. In the production of the mold for micro-molding, the microchannel 14 can be fabricated using the FIB-CVD (Focused-Ion-Beam Chemical-Vapor-Deposition) method, and the introduction part 13 and the discharge part 15 may be fabricated using photoresist. Also, the mold for micro-molding may be fabricated using the backside exposure method in which a master pattern made of photoresist is directly formed on a photomask.

[0014] The electrode chip 21 can be fabricated by forming a first electrode 23 and a second electrode 24 on a substrate 22. For example, a PCB substrate can be used as the substrate 22. Also, materials such as Au and Cu can be used for the first electrode 23 and the second electrode 24.

[0015] The flow path chip 11 and the electrode chip 21 may be adhered using an adhesive. Also, since the flow path chip 11 is formed using silicone rubber 12, the flow path chip 11 and the electrode chip 21 may be adhered using the adhesiveness of the silicone rubber 12.

[0016] For example, the area of a cross-section perpendicular to the direction in which the sample solution 40 in the microchannel 14 shown in FIG. 2 flows is 0.05 μm 2 or more and 100 μm 2 or less. Also, the length of the microchannel 14 is 0.1 μm or more and 100 μm or less. These sizes can be appropriately changed according to the size of the measurement object 42.

[0017] The measurement unit 30 is connected to the first electrode 23 and the second electrode 24 respectively. Then, the measurement unit 30 applies an alternating voltage to the first electrode 23 and the second electrode 24, and identifies the measurement object 42 based on the AC characteristics of the measurement object 42 when the measurement object 42 passes through the microchannel 14.

[0018] The measuring unit 30 may use any circuit as long as it can measure the AC characteristics of the object to be measured 42. The measuring unit 30 is configured to be able to apply an AC voltage with a frequency of several kHz or more and several GHz or less, preferably 1 kHz or more and 100 MHz or less, and more preferably 1 MHz or more and 10 MHz or less, to the first electrode 23 and the second electrode 24. For example, a lock-in amplifier may be used for the measuring unit 30.

[0019] Further, the measuring unit 30 is configured to obtain the composite impedance and the phase using the measured AC characteristics, and identify the object using the obtained composite impedance and phase. In the present embodiment, using the composite impedance and the phase, parameters corresponding to the resistance component, the zeta potential, and the dielectric constant of the object to be measured 42 are obtained respectively, and the object to be measured 42 may be identified using the obtained parameters corresponding to the resistance component, the zeta potential, and the dielectric constant.

[0020] Next, the operation when identifying the object to be measured 42 using the sample measuring device 1 according to the present embodiment will be described.

[0021] When identifying the object to be measured 42, first, the object to be measured 42 dispersed in the solvent 41 is caused to flow through the microchannel 14. Next, an AC voltage is applied to the first electrode 23 and the second electrode 24, and the AC characteristics of the object to be measured 42 when the object to be measured 42 passes through the microchannel 14 are measured. For example, the measuring unit 30 applies an AC voltage with a frequency of 1 kHz or more and 100 MHz or less to the first electrode 23 and the second electrode 24. In the present embodiment, an AC voltage may be applied to the first electrode 23 and the second electrode 24 in advance, and then the object to be measured 42 dispersed in the solvent 41 may be caused to flow through the microchannel 14.

[0022] In addition, in the present embodiment, the measurement unit 30 may apply a DC voltage between the first electrode 23 and the second electrode 24 to introduce the measurement object 42 charged positively or negatively from the introduction unit 13 into the microchannel 14. Specifically, when the measurement object 42 is positively charged, the first electrode 23 is set as the positive electrode, the second electrode 24 is set as the negative electrode, and a DC voltage for electrophoresis is applied between the first electrode 23 and the second electrode 24, so that the positively charged measurement object 42 can be introduced from the introduction unit 13 into the microchannel 14. When the measurement object 42 is negatively charged, the first electrode 23 is set as the negative electrode, the second electrode 24 is set as the positive electrode, and a DC voltage for electrophoresis is applied between the first electrode 23 and the second electrode 24, so that the negatively charged measurement object 42 can be introduced from the introduction unit 13 into the microchannel 14. At this time, the measurement unit 30 may superimpose and apply the AC voltage for measurement and the DC voltage for electrophoresis to the first electrode 23 and the second electrode 24.

[0023] At this time, by adjusting the magnitude and time of the DC voltage applied to the first electrode 23 and the second electrode 24, the speed at which the measurement object 42 passes through the microchannel 14 can be adjusted. In the present embodiment, the number of measurement objects 42 passing through the microchannel 14 is basically one. When the measurement object 42 is introduced into the microchannel 14 using the DC voltage applied to the first electrode 23 and the second electrode 24 in this way, the accuracy when introducing the measurement object 42 into the microchannel 14 can be improved. Therefore, the detection accuracy of the measurement object 42 can be improved.

[0024] That is, when the introduction unit 13 is pressurized to move the sample solution 40 into the microchannel 14 and the measurement object 42 is moved into the microchannel 14, there is a problem that the measurement accuracy cannot be improved because the moving speed cannot be controlled when the number of measurement objects 42 passing through the microchannel 14 is small, such as when the concentration of the measurement object 42 in the sample solution 40 is low. In contrast, in the present embodiment, since the measurement object 42 is introduced into the microchannel 14 using the DC voltage applied to the first electrode 23 and the second electrode 24, the accuracy when introducing the measurement object 42 into the microchannel 14 can be improved.

[0025] Also, in the present embodiment, by switching the polarities of the DC voltages applied to the first electrode 23 and the second electrode 24, the measurement object 42 flowing through the microchannel 14 can be reciprocated. Thereby, the detection accuracy of the measurement object 42 can be further improved.

[0026] Further, in the present embodiment, since equipment (such as an external pump) for introducing the measurement object 42 into the microchannel 14 is not required, the apparatus configuration can be miniaturized. Also, in the present embodiment, since concentration polarization can be induced with a DC voltage and the state can be measured by AC measurement, the surface potential of the measurement object 42 can be measured more accurately.

[0027] After measuring the AC characteristics of the measurement object 42 as described above, the measurement object 42 is specified using the measured AC characteristics. Specifically, the complex impedance and the phase are obtained using the measured AC characteristics, and the measurement object 42 is specified using the obtained complex impedance and phase.

[0028] In the present embodiment, parameters corresponding to the resistance component, zeta potential, and dielectric constant of the measurement object 42 are respectively obtained using the complex impedance and the phase, and the measurement object 42 may be specified using the obtained parameters corresponding to the resistance component, zeta potential, and dielectric constant. For example, the measurement object 42 may be specified by mapping the parameters corresponding to the resistance component, zeta potential, and dielectric constant of the measurement object 42 on a three-dimensional coordinate with each of the resistance component, zeta potential, and dielectric constant as an axis. Here, the parameter corresponding to the resistance component is a parameter corresponding to the size of the measurement object 42. The parameter corresponding to the zeta potential is a parameter corresponding to the surface potential of the measurement object 42. The parameter corresponding to the dielectric constant is a parameter corresponding to the structure such as the spherical shell structure or membrane capacitance of the measurement object 42 or a parameter corresponding to the substance of the measurement object 42.

[0029] Since the object to be measured 42 has different sizes, surface potentials, and structures, the resistance component, zeta potential, and dielectric constant, which are parameters corresponding to these, are obtained, and the parameters corresponding to the resistance component, zeta potential, and dielectric constant of the object to be measured 42 are mapped on a three-dimensional coordinate, whereby the object to be measured 42 can be classified. For example, by mapping the measurement results of a plurality of types of objects to be measured 42 on a three-dimensional coordinate and accumulating the data, the accuracy in identifying the object to be measured 42 can be improved.

[0030] Also, in the present embodiment, the in-phase component, which is an AC characteristic, and the phase component whose phase is shifted from that of the in-phase component are extracted using a lock-in amplifier, and the complex impedance and the phase are obtained using the extracted in-phase component and phase component, and the object may be identified using the time change of the complex impedance and the time change of the phase.

[0031] FIG. 4 is a graph showing the AC characteristics measured by the sample measuring device according to the present embodiment, and shows the AC characteristics measured using a lock-in amplifier. That is, FIG. 4 shows the time response waveforms of the current and the phase change, respectively. Looking at the enlarged view shown in FIG. 4, it can be seen that the changes in the current and the phase are synchronized and are waveforms derived from the same object to be measured 42.

[0032] FIG. 5 is a graph showing an example of the measurement results of the sample measuring device according to the present embodiment. FIG. 5 shows histograms of the current change values for polystyrene beads having a diameter of 1 μm, polystyrene beads having a diameter of 2 μm, and Escherichia coli, respectively. In the measurement of FIG. 5, the width, height, and length of the microchannel 14 of the flow path device 10 were 3 μm, 4 μm, and 30 μm, respectively. Also, Au plating was used for the first electrode 23 and the second electrode 24. Also, the measurement was performed using a lock-in amplifier.

[0033] As shown in FIG. 5, in this embodiment, a unimodal distribution according to the particle size was obtained. Here, the horizontal axis in FIG. 5 represents the current value, and since the larger the particle size of the measurement object 42, the larger the amount of current change, it is suggested that a change in the current value according to the particle size of the measurement object 42 is obtained.

[0034] As described above, in the invention according to this embodiment, the measurement object 42 is measured using the flow path device 10 including the microchannel 14, the introduction part 13 for introducing the sample solution 40 into the microchannel 14, the discharge part 15 from which the sample solution 40 is discharged from the microchannel 14, the first electrode 23 arranged at a position corresponding to the introduction part 13, and the second electrode 24 arranged at a position corresponding to the discharge part 15. Therefore, according to the present invention, it is possible to provide a sample measurement device capable of quickly and accurately identifying a minute measurement object.

[0035] FIG. 6 is a diagram for explaining the effect of the present invention. As shown in the left diagram of FIG. 6, in the conventional nanopore configuration, that is, in the configuration in which electrodes are provided on each of the upper and lower surfaces of a substrate having a hole through which the measurement object passes, since the insulating substrate is sandwiched between two electrodes, the capacitance of the flow path device tends to increase. That is, assuming that the capacitance of the flow path device is C, the dielectric constant of the substrate is ε, the thickness of the substrate is d, and the area of the substrate is S, the capacitance of the device is represented by C = εS / d. For this reason, in the conventional nanopore configuration, as shown in the left diagram of FIG. 6, since d is small and S is large, the capacitance of the flow path device tends to increase. On the other hand, in the flow path device (straw-type nanopore) according to this embodiment, as shown in the right diagram of FIG. 6, since d can be increased while S can be decreased, the capacitance of the flow path device can be decreased.

[0036] FIG. 7 is a top view for explaining the state of the electric field in the microchannel. The left diagram of FIG. 7 shows the state of the electric field of the conventional nanopore, and the right diagram shows the state of the electric field of the straw-shaped nanopore of the present embodiment. As shown in the left diagram of FIG. 7, in the conventional nanopore, the electric field was concentrated only in the hole through which the object to be measured passed. In contrast, in the present embodiment, when viewed in plan, the first electrode 23 and the second electrode 24 are configured to sandwich the microchannel 14. Therefore, as shown in FIG. 7, when an alternating voltage is applied to the first electrode 23 and the second electrode 24, the electric field can be concentrated in the vicinity of the microchannel 14, so that the detection accuracy of the object to be measured 42 can be improved.

[0037] In the present embodiment, since the capacitance of the flow path device can be reduced as described above, as shown in FIG. 8, the cut-off frequency can be set to 400 times (2 MHz) that of the conventional one. Therefore, the detection accuracy of the object to be measured can be improved.

[0038] Further, in the present embodiment, the measurement unit 30 may further include a prediction model generation unit that uses the measured AC characteristics and the information of the object to be measured 42 as teacher data and generates a prediction model for predicting the object to be measured 42 based on the measured AC characteristics by machine learning.

[0039] The prediction model generation unit may extract the in-phase component, which is an AC characteristic, and the phase component whose phase is shifted from the in-phase component, obtain the complex impedance and the phase using the extracted in-phase component and phase component, and generate a prediction model using the feature amount of the time change of the complex impedance and the feature amount of the time change of the phase.

[0040] The prediction model generation unit may generate a prediction model by machine learning using a neural network. For example, the prediction model generation unit may generate a prediction model by machine learning using CNN (Convolution Neural Network) or LSTM (Long Short Term Memory).

[0041] Hereinafter, machine learning will be described in detail. In classifying bacterial species from individual measured waveforms derived from bacteria, the inventors of the present application have worked on the development of a measurement unit 30 (classifier) that uses a neural network in order to obtain higher accuracy. As a result, after extracting feature quantities as shown in FIG. 9, a classification algorithm using the neural network shown in FIG. 10 was constructed. That is, in the spike (waveform) shown in FIG. 9, the height h of the spike and the width t of the spike are used as feature quantities n (n = 0, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90) were extracted, and a total of 12 feature quantities per spike were extracted. Here, the value of n corresponds to the depth (%) when the baseline is 0% and the bottom of the spike is 100%, and the width t of the spike at each depth n is extracted as a feature quantity.

[0042] Then, a prediction model was generated using the extracted feature quantities. At this time, the neural network as shown in FIG. 10 was used. By combining and using the sample measurement device according to the above-described embodiment and machine learning, a sample measurement device with a maximum accuracy of 97.6% could be constructed.

Example

[0043] Hereinafter, examples will be described. <Experimental method> The following were prepared as bacterial samples. Phosphate buffered saline (PBS; 17-516Q, Lonza, Morrisville, NC, USA) was used as the measurement solvent, and 0.01% artificial lipid-type surfactant (Lipidure BL206, NOF Corporation) was used as the anti-adsorbent. In addition, the following six bacteria were used from human infectious bacteria. (1) S. enterica (Se, NBRC 3313) (2) V. parahaemolyticus (Vp, NBRC12711) (3) P. vulgaris (Pv, NBRC 3045) (4) Klebsiella pneumoniae (Kp, NBRC 13277) (5) Mycobacterium intracellulare (Mi, distributed by Kobe City Institute of Environmental Health) (6) Mycobacterium mesophilicum (Mm, NBRC 15688)

[0044] Mycobacterium intracellulare was cultured on "7H11 agar medium", and the rest were cultured on "standard agar medium". One colony of each bacterial culture was dispersed in 300 μL of the measurement solution and used for measurement immediately after vortexing for about 10 seconds.

[0045] (AC nanopore measurement method) The microchannels in the conventional nanopore in the left figure of Fig. 6 and the microchannels in the present invention are hereinafter also referred to as nanopores. In this experiment, measurements were performed using these nanopores. Here, the method of measuring the AC characteristics of a sample using the nanopores as described above is referred to as the AC nanopore measurement method. A lock-in amplifier was used for the measurement. The lock-in amplifier extracts only the signal component having the same frequency as the reference signal from the noise background and measures the magnitude and phase of the current. In the AC nanopore measurement method, a spike-like downward current and an upward phase change are synchronously observed for a single particle. That is, a waveform similar to that in Fig. 4 is obtained. The magnitude of the current is proportional to the volume of the particle and was used to determine the size of the bacterium. Furthermore, these sets of current and phase spike waveforms were used as features for machine learning to classify bacteria.

[0046] (Nanopore) In the AC nanopore measurement method used in this experiment, a commercially available nanopore (NP2000, Izon Science Ltd.: hereinafter referred to as the Izon nanopore) and a straw-type nanopore according to the present invention (see Fig. 1) were used. The cross-sectional shape of the microchannel of the straw-type nanopore was 3 × 3 μm, and the length was 30 μm.

[0047] (Measurement method) For Izon nanopores, in all experiments, the bacterial suspension was added to the upper cell with a pressure head of 3 mm (30 Pa), and driven by hydrostatic pressure. For straw-type nanopores, 50 pl was injected into the inlet and 20 pl was injected into the outlet, and driven by the pressure head generated by the difference. The applied voltage was measured as 0.1 V for Izon nanopores and 0.7 V for straw-type nanopores. In all measurements, a minimum of 500 counts were measured.

[0048] <Experimental Results> The change in the magnitude of the current accompanying the passage of particles (objects to be measured) is proportional to the volume of the particles. Figure 11 is a histogram of the size distribution of bacterial particles measured by the AC nanopore measurement method using straw-type nanopores. In Figure 11, the horizontal axis indicates the magnitude of the current, and the vertical axis indicates the frequency. The histogram was created by counting at least 500 particles for each particle size, but due to fluctuations in the counts, the vertical axis was normalized so that the total count for each particle was 100%. In the histogram shown in Figure 11, since each bacterial size (current value) has an overlapping distribution, it was difficult to classify bacteria based only on size.

[0049] Therefore, the inventors of the present application classified bacteria by machine learning. First, the pulse waveforms of the magnitude and phase of the current obtained by the AC nanopore measurement method were used for learning. In machine learning, the number of waveforms in the waveform set consisting of the magnitude and phase of the current was first made uniform. Next, for the peak height of each waveform when the peak height was set to 100% and the width of the waveform for each 10% increase, the 12 combinations with the highest learning effect were used as learning data (see Figure 9). For CNN-based classification, the model was constructed with three layers (one input layer, one intermediate layer, and one output layer).

[0050] Figure 12 and Figure 13 respectively show the matrix evaluations of the classification accuracy of particles when the random forest method and the CNN method are applied to the measurement results by Izon nanopores. In Figure 12 and Figure 13, (a) shows only the magnitude of the current, (b) shows only the phase, and (c) shows the classification results of the magnitude and phase of the current. In Figure 12 and Figure 13, the darker the color of the cells on the downward diagonal from the upper right, the higher the classification accuracy. The numerical values within the matrix are the number of classified particles.

[0051] Comparing the random forest method and the CNN method, as shown in (a), when only the magnitude of the current was used, the classification accuracy was 61.4% for the random forest method and 66.6% for the CNN method. As shown in (b), when only the phase was used, the classification accuracy was 57.2% for the random forest method and 70.7% for the CNN method. On the other hand, as shown in (c), when both the magnitude and phase of the current were used, the classification accuracy was 66.5% for the random forest method and 78.3% for the CNN method, indicating that the CNN method showed a higher classification accuracy.

[0052] Next, the classification accuracy of particles when the CNN method is applied to the measurement results in the straw-type nanopore is examined. Figure 14 is a diagram showing the matrix evaluation of the classification accuracy of particles when the CNN method is applied to the measurement results in the straw-type nanopore. As shown in Figure 14, in the measurement by the straw-type nanopore, it was found that the classification accuracy was higher in all sample sets compared to the measurement by the Izon nanopore (Figure 13). Comparing the case of using both the magnitude and phase of the current (c), the classification accuracy of the Izon nanopore (Figure 13) was 78.3%, while the classification accuracy of the straw-type nanopore (Figure 14) was 97.8%, indicating that the straw-type nanopore showed a classification accuracy more than 19% higher. From these results, it was found that the combination of the CNN method and the straw-type nanopore can significantly improve the classification accuracy of bacteria.

[0053] In the above description, an example using bacteria as the particles to be measured was explained. However, in order to confirm the classification accuracy for smaller particles, the experimental results when viruses are used as the measurement targets in the AC nanopore measurement method using a straw-type nanopore will be explained. Here, the following four viruses were used as the measurement targets. (A) Influenza Virus A type (H1N1) (B) Influenza Virus A type (H3N2) (C) Influenza Virus B type (Tokio / 53 / 99 strain) (D) Respiratory Syncytial Virus

[0054] For these viruses, the classification accuracy was evaluated when the CNN method was applied to the measurement results of the magnitude and phase of the current to classify the particles. Figure 15 is a diagram showing the matrix evaluation of the classification accuracy of the particles when the CNN method is applied to the measurement results of the magnitude and phase of the current for viruses in a straw-type nanopore. The numerical values in the matrix of Figure 15 are the correct classification rates of the particles. As shown in Figure 15, high classification accuracies were shown: 0.94 for Influenza Virus A type (H1N1), 1.00 for Influenza Virus A type (H3N2), 0.95 for Influenza Virus B type (Tokio / 53 / 99 strain), and 0.86 for Respiratory Syncytial Virus. The overall classification accuracy was 96.52%, and it was confirmed that the classification accuracy was generally equivalent to that in the case of bacteria (97.8%, Figure 14).

[0055] Therefore, by performing measurement by the AC nanopore measurement method using the straw-type nanopore according to the present invention, it is possible to classify fine particles such as bacteria and viruses with high accuracy.

[0056] As described above, the present invention has been described in accordance with the above embodiments. However, the present invention is not limited only to the configurations of the above embodiments, and it goes without saying that it includes various modifications, corrections, and combinations that can be made by those skilled in the art within the scope of the invention of the claims of the present patent application.

Description of Symbols

[0057] 1 Sample measurement device 10 Flow path device 11 Flow path chip 12 Silicone rubber 13 Introduction part 14 Micro flow path 15 Discharge part 16 Inlet 17 Outlet 21 Electrode chip 22 Substrate 23 First electrode 24 Second electrode 30 Measurement part 40 Sample solution 41 Solvent 42 Object to be measured

Claims

1. A flow path device; A measuring unit, the flow channel device includes a flow channel chip in which an inlet portion, a microflow channel, and a discharge portion are formed, and an electrode chip in which a first electrode and a second electrode are formed on a substrate; The microchannel is formed in the channel chip, The inlet portion is disposed on one side of the microchannel, the discharge portion is disposed on the other of the microchannels, The first electrode is disposed at a position corresponding to the introduction portion, The second electrode is disposed at a position corresponding to the discharge portion, the measurement unit applies an AC voltage to the first electrode and the second electrode, and measures AC characteristics of the object to be measured when the object to be measured passes through the microchannel; The flow channel device is configured by bonding the electrode chip and the flow channel chip together. Sample measurement device.

2. The object to be measured is the first electrode is introduced into the introduction portion through an introduction port that is an opening provided in the channel chip at a position corresponding to the first electrode, The sample measurement device according to claim 1 , wherein the sample is discharged from the discharge section through a discharge port that is an opening provided in the channel chip at a position corresponding to the second electrode.

3. The sample measurement device according to claim 1 or 2, wherein the measurement unit is configured to be capable of introducing the positively or negatively charged object to be measured from the introduction unit into the microchannel by applying a DC voltage between the first electrode and the second electrode.

4. The sample measurement device according to claim 3 , wherein the measurement section is configured to be able to apply the AC voltage and the DC voltage in a superimposed manner to the first electrode and the second electrode.

5. 3. The sample measurement device according to claim 1, wherein the measurement unit is configured to be able to apply an AC voltage having a frequency of 1 kHz to 100 MHz to the first electrode and the second electrode.

6. 3. The sample measurement device according to claim 1, wherein the measurement section determines a composite impedance and a phase using AC characteristics of the object to be measured, and identifies the object to be measured using the determined composite impedance and phase.

7. determining parameters corresponding to electrical properties of the object to be measured using the synthetic impedance and the phase; The sample measurement device according to claim 6 , wherein the measurement object is identified using a parameter corresponding to the determined electrical property.

8. 3. The sample measurement device according to claim 1, wherein the measurement unit includes a prediction model generation unit that uses the AC characteristics of the object to be measured and information about the object to be measured as teacher data and generates, by machine learning, a prediction model that predicts the object to be measured based on the AC characteristics of the object to be measured.

9. The prediction model generation unit, extracting an in-phase component and a phase component out of phase with the in-phase component, which are the AC characteristics; determining a synthetic impedance and a phase using the extracted in-phase component and the extracted phase component; The sample measurement device according to claim 8 , wherein the prediction model is generated using a feature amount of the time change of the synthetic impedance and a feature amount of the time change of the phase.

10. The sample measurement device according to claim 9 , wherein the prediction model generation unit generates the prediction model by machine learning using a neural network.

11. a channel chip having an inlet portion, a microchannel, and a discharge portion formed therein; an electrode chip having a first electrode and a second electrode formed on a substrate; The microchannel is formed in the channel chip, The inlet portion is disposed on one side of the microchannel, the discharge portion is disposed on the other of the microchannels, The first electrode is disposed at a position corresponding to the introduction portion, The second electrode is disposed at a position corresponding to the discharge portion, The electrode chip and the channel chip are bonded together. A flow path device for a sample measurement apparatus for measuring AC characteristics.

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