JP2021177124A - Measurement apparatus - Google Patents

Abstract

To provide an electrochemical measurement apparatus capable of measuring physical characteristics of a sample more accurately and also measuring the behavior of the sample.SOLUTION: A classification device 1 includes: a measuring unit that includes a plurality of first electrodes 7a, 7b, 7c existing respectively in a plurality of partitioned regions 2a, 2b, 2c partitioned in a matrix; voltage applying means 11 that applies a voltage to each of the plurality of first electrodes and a second electrode 9; an impedance measuring unit 13 that measures impedance between the first electrode and the second electrode; a first storage unit 25 that stores an impedance value corresponding to each partitioned region measured by the impedance measuring unit; a second storage unit 27 that stores a classification pattern based on the impedance value corresponding to each partitioned region; and a classification determining unit 29 that classifies a measurement object using the classification pattern stored in the second storage unit 27 and a pattern based on the impedance value stored in the first storage unit 25.SELECTED DRAWING: Figure 1

Description

The present invention relates to a measuring device. More specifically, the present invention relates to an electrochemical measuring device capable of measuring the physical properties and behavior of cells.

Japanese Patent No. 5617532 describes a dielectric cytometry apparatus and a cell sorting method using a dielectric cytometry.

Japanese Patent No. 5617532

With conventional dielectric cytometry, there are problems that the physical properties of the sample near the electrode cannot be measured and that the measured value fluctuates depending on the distance between the electrode and the sample.

Therefore, an object of the present specification is to provide an electrochemical measuring device capable of measuring the physical characteristics of a sample more accurately and also measuring the behavior of a sample.

The above problem is based on the finding that the physical properties of the sample existing near the electrode can also be measured by making the electrode smaller than the cross-sectional area of the sample. In addition, the physical characteristics of the sample can be measured more accurately by reducing the distance between adjacent electrodes, and the physical characteristics of the sample can be measured more accurately by providing a partition wall that allows the solution to pass but not the sample to pass between the electrodes to which the voltage is applied. Based on the knowledge that can be measured.

The invention first described herein relates to measuring device 1. This measuring device includes a measuring unit 8 including a plurality of first electrodes 7a, 7b, 7c existing in each of the plurality of compartment regions 2a, 2b, 2c partitioned in a matrix.
A second electrode 9 that generates an electric field between each of the plurality of first electrodes,
A voltage applying means 11 for applying a voltage to each of the plurality of first electrodes and the second electrode, and
An impedance measuring unit 13 that measures the impedance between each electrode of the plurality of first electrodes and the second electrode and obtains an impedance value corresponding to each partition region.
The first storage unit 25 that stores the impedance value corresponding to each partition area measured by the impedance measurement unit, and
A second storage unit 27 that stores a classification pattern based on the impedance value corresponding to each partition area, and
It has a classification determination unit 29 that classifies measurement targets by using a classification pattern stored by the second storage unit 27 and a pattern based on the impedance value stored by the first storage unit 25.

This classification device preferably further includes an injection needle body 31. Of course, it may further have a syringe body 32. Then, the sorting device 1 is provided in the recessed portion 33 provided on the outer peripheral surface of the injection needle main body 31. In this case, the classification pattern is, for example, a classification pattern based on the impedance value measured for blood.
Since such a configuration is adopted, various analyzes can be performed when injecting or infusing. Diseases such as infectious diseases, which would increase medical costs if left untreated, can be measured at an early stage regardless of the patient's will, so the spread of infection can be prevented. In addition, it is also beneficial for health promotion because it is possible to diagnose diseases whose medical expenses increase when they become serious without requiring special diagnosis.

The classification device preferably further includes a drip container 35 capable of supplying a liquid to the injection needle body 31. When the drip solution is supplied to the target using the drip container 35, the classification device 1 provided on the injection needle main body 31 can continuously perform the classification based on the blood of the target.
Patient information can be obtained at the time of infusion. Since it is being infused, measurement can be continued for a relatively long time, so high sensitivity is not required and patterning including changes over time is possible.

This classification device may be a classification device for grasping the presence / absence of a specific disease or the presence / absence of a specific situation. For example, the presence or absence of illness, the presence or absence of cancer markers, and the possibility of cerebral infarction can be diagnosed during infusion.

This classification device further includes an alarm device 39, and when the classification determination unit 29 determines that the pattern based on the impedance value corresponds to the classification pattern stored in relation to the information related to the warning among the classification patterns. An alarm may be output using the alarm device 39.
An alert can be output when the patient undergoing infusion is likely to become serious.

The voltage applying means 11 preferably applies a voltage by sweeping the frequency in a frequency region of 100 kHz or more and 10 MHz or less. The classification pattern based on the impedance value is preferably a classification pattern obtained based on the phase value θ of the impedance value. The classification pattern is preferably a distribution map corresponding to each section area. The classification pattern is preferably a distribution map in which the value based on the impedance value is converted into a color corresponding to each partition region. The classification pattern is preferably a classification pattern obtained by measuring impedance values for a plurality of types of objects in advance and machine learning the classification patterns for each of a plurality of types of objects. For example, a classification pattern can be obtained by principal component analysis or deep learning and stored in advance.

The invention described in this specification can provide an electrochemical measuring device capable of measuring the physical characteristics of a sample more accurately and also measuring the behavior of the sample.

FIG. 1 is a conceptual diagram of this measuring device. FIG. 2 is a conceptual diagram of a classification device used for syringes and infusions. FIG. 2A is a conceptual diagram of a syringe. FIG. 2B is a partially enlarged view of the injection needle. FIG. 2C is a conceptual diagram of the drip device. FIG. 3 is a conceptual diagram for explaining the principle of the classification device. FIG. 4 is a conceptual diagram showing an example of a classification device in which the first electrode and the second electrode are provided on the substrate. FIG. 5 is a conceptual diagram showing a first electrode and a second electrode formed in an array. FIG. 6 is a conceptual diagram of the electrodes manufactured in the examples. FIG. 7 is a conceptual diagram showing a dielectric measuring device for measuring a dielectric spectrum. FIG. 8 is a photograph instead of a drawing showing the state of the electrodes and cells. FIG. 9 is a graph that replaces the drawings showing the measured Cole-Cole plot (FIG. 9 (A)) and frequency-phase plot (FIG. 9 (B)). FIG. 10 is a graph that replaces the drawings showing the Cole-Cole plot (FIG. 10 (A)) and the frequency-phase plot (FIG. 10 (B)) to show the effect of the distance between the electrodes. FIG. 11 is an alternative graph to the drawing showing a frequency-phase plot for examining the effects of non-electrolytes. FIG. 12 is a conceptual diagram showing how migrating cells are tracked. FIG. 13 is a photograph that replaces the drawing of the classification device obtained in the embodiment. FIG. 14, is a photograph instead of the drawing of the classification device obtained in the embodiment. a FIG. 15 is a conceptual diagram showing an example of analyzing the impedance measurement value of a certain partition region. FIG. 16 is a conceptual diagram showing an example of impedance values corresponding to each partition region. FIG. 17 is a conceptual diagram showing an example of impedance values corresponding to each partition region. FIG. 18 is a conceptual diagram showing how feature points are extracted by unsupervised learning.

Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. The present invention is not limited to the forms described below, and includes those which are appropriately modified by those skilled in the art from the following forms to the extent obvious to those skilled in the art.

The invention first described herein relates to a classification device 1. FIG. 1 is a conceptual diagram of this measuring device. As shown in FIG. 1, this apparatus stores an impedance value of a measuring unit 8 including a plurality of first electrodes 7a, 7b, 7c, a second electrode 9, a voltage applying means 11, an impedance measuring unit 13, and an impedance value. It has a first storage unit 25, a second storage unit 27 that stores the classification pattern, and a classification determination unit 29.
The measuring unit 8 is a region including a plurality of first electrodes 7a, 7b, 7c existing in each of the plurality of compartment regions 2a, 2b, 2c partitioned in a matrix. The second electrode 9 is an electrode that generates an electric field with each of the plurality of first electrodes. For example, an electric field is generated between the electrode 7a having the first electrode and the second electrode 9, and between another electrode 7a of the first electrode and the second electrode 9.
The voltage applying means 11 is a device that applies a voltage to each of the electrodes 7a, 7b, 7c and the second electrode of the plurality of first electrodes.
The impedance measuring unit 13 is a device for measuring the impedance between each electrode of the plurality of first electrodes and the second electrode and obtaining an impedance value corresponding to each partition region.
The first storage unit 25 is a device that stores the impedance value corresponding to each partition area measured by the impedance measuring unit.
The second storage unit 27 is a device that stores a classification pattern based on the impedance value corresponding to the image area. As for this classification pattern, various things may be measured in advance, and a classification pattern for various things may be obtained by machine learning or the like.
The classification determination unit 29 is an element for classifying the measurement target by using the classification pattern stored in the second storage unit 27 and the pattern based on the impedance value stored in the first storage unit 25.

The partition areas 2a, 2b, 2c, and 2d are areas in the measuring unit 8. This region does not need to be particularly distinguished from the outside of the region, and the first electrodes 7a, 7b, and 7c may be provided in a matrix shape (lattice shape). The measuring unit 8 is a region where electrodes used for measurement exist. The measuring unit 8 is also conceptual, and it is not necessary to distinguish between the measuring unit and the non-measuring unit.

It is preferable that the impedance measuring unit 13, the first storage unit 25, the second storage unit 27, and the classification determination unit 29 are capable of exchanging information. The first storage unit 25, the second storage unit 27, and the classification determination unit 29 may be provided on the same substrate as the first electrode or the second electrode, or may be physically provided in another device. .. For example, the measurement data by the impedance measuring unit 13 may be wirelessly transmitted (released) through an antenna or the like, and the receiving device in the computer may receive the measurement data and transmit it to the first storage unit 25. The measurement data may be transmitted to the first storage unit 25 or the like using a communication means such as a LAN. The impedance measurement unit 13 may be capable of exchanging information with each storage unit, calculation unit, and control unit via a bus or the like. A computer has an input / output unit, a storage unit, a calculation unit, and a control unit. The control unit reads, for example, a control program stored in the storage unit, and uses information stored in the storage unit or an input / output unit. Using the input information, the calculation unit may perform various operations, and the information may be stored in the storage unit as appropriate and output from the input / output unit. For example, when measurement data is input from the impedance measurement unit 13, the classification determination unit 29 appropriately stores the impedance value in the first storage unit 25, reads out the stored impedance value, and stores the stored impedance value in the second storage unit 27. Perform pattern matching with the memorized classification pattern. This classification pattern is a classification pattern according to each of the above-mentioned division areas. The classification pattern may be a pattern based on binary data of a predetermined threshold value or more or less than a predetermined threshold value for each partition area, or may be a classification pattern based on grayscale data relating to a multi-step threshold value. The specific implementation of the classification may be software on a computer or hardware (eg, all-optical machine learning using diffractive deep neural networks, Science (2018) doi: 10.1126 / science. .aat8084) may be used.

FIG. 2 is a conceptual diagram of a classification device used for syringes and infusions. FIG. 2A is a conceptual diagram of a syringe. FIG. 2B is a partially enlarged view of the injection needle. The specification also provides needles, syringes and infusion devices with sorting devices. That is, it is preferable that this classification device further has an injection needle body 31. Of course, it may further have a syringe body 32. Then, the sorting device 1 is provided in the recessed portion 33 provided on the outer peripheral surface of the injection needle main body 31. The recessed portion 33 may have a size that can accommodate the sorting device 1. In this case, the classification pattern is, for example, a classification pattern based on the impedance value measured for blood or body fluid.

The second storage unit 27 stores the classification pattern according to the infusion location. The classification pattern may be obtained in advance by machine learning. Examples of classification patterns are those that bring about a certain concentration change (change over time), such as those at risk of cerebral infarction, and classification patterns peculiar to patients infected with infectious diseases such as AIDS patients. An example of another classification pattern is a memory of the classification pattern when the patient loses consciousness. An example of the classification pattern is, for example, when the risk of cerebral infarction is high, the period of concentration change of a predetermined mass portion (for example, 4 to 16 compartments) in the compartmental region is in the range of 1 Hz or more and 100 Hz or less, instead of all the compartmentalized regions. In the case of a classification pattern that gradually shortens with, the second storage unit stores the classification pattern. Then, when the impedance value actually measured is gradually shortened in the range of 10 Hz or more and 90 Hz or less in the concentration change cycle only in the 4 to 6 compartments, for example, the classification determination unit 29 causes a cerebral infarction in the patient. Judge that there is a risk of. An example of a specific process is as follows. The injection needle 31 is inserted into the patient. Then, the classification device 1 located outside the injection needle 31 is exposed to the body fluid of the patient. In this way, the classification device is installed within the patient. The impedance measuring unit of the classification device measures the impedance according to each compartment area of the patient's body fluid. The classification determination unit 29 pattern-matches the impedance measurement value of each partition region with the classification pattern, and when the classification pattern in question is matched, the alarm device 39 outputs an alarm as described later. Moi. Since such a configuration is adopted, various analyzes can be performed when injecting or infusing. Diseases such as infectious diseases, which would increase medical costs if left untreated, can be measured at an early stage regardless of the patient's will, so the spread of infection can be prevented. In addition, it is also beneficial for health promotion because it is possible to diagnose a disease whose medical expenses increase when it becomes serious without requiring a special diagnosis.

FIG. 2C is a conceptual diagram of the drip device. The classification device preferably further includes a drip container 35 capable of supplying a liquid to the injection needle body 31. When the drip solution is supplied to the target using the drip container 35, the classification device 1 provided on the injection needle main body 31 can continuously perform the classification based on the blood of the target.
Patient information can be obtained at the time of infusion. Since it is being infused, measurement can be continued for a relatively long time, so high sensitivity is not required and patterning including changes over time is possible.

This classification device may be a classification device for grasping the presence / absence of a specific disease or the presence / absence of a specific situation. For example, the presence or absence of illness, the presence or absence of cancer markers, and the possibility of cerebral infarction can be diagnosed during infusion.

This classification device further includes an alarm device 39, and when the classification determination unit 29 determines that the pattern based on the impedance value corresponds to the classification pattern stored in relation to the information related to the warning among the classification patterns. An alarm may be output using the alarm device 39. An alert can be output when the patient undergoing infusion is likely to become serious.

The voltage applying means 11 preferably applies a voltage by sweeping the frequency in a frequency region of 100 kHz or more and 10 MHz or less.

FIG. 3 is a conceptual diagram for explaining the principle of the classification device. As shown in FIG. 3, this classification device is a classification device 1 including a first electrode 7 and a second electrode 9, a voltage applying means 11, and an impedance measuring means 13. In this example, a solution tank 5 containing the solution 3 is described. Examples of solutions may be electrolyte solutions, and depending on cells and liposomes, media or culture medium. Another example of a solution is body fluids such as blood, urine, tears, saliva, runny nose, and semen. The solution tank 5 may be any as long as it can accommodate the solution, and its size and material can be appropriately selected according to the intended use.

In the example of FIG. 3, the first electrode 7 and the second electrode 9 exist in the solution tank 5, and at least a part of the surface thereof is exposed in the solution. The entire surface of the electrode may be exposed and come into contact with the solution, or a part of the electrode may be buried in the substrate or the solution. The surface area S of the portion 15 exposed to the solution tank 5 of the first electrode 7 is 0.1 μm ² or more and 100 μm ² or less. The value of S may be a 0.2 [mu] m ² or more 80 [mu] m ² or less, may be a 0.5 [mu] m ² or more 70 [mu] m ² or less, may be a 1 [mu] m ² or more 50 [mu] m ² or less, may be a 0.5 [mu] m ² or more 30 [mu] m ² or less, It may be ^{2 μm 2} or more and 10 ^{μm 2 or less, or 10 μm 2} or more and 50 μm ² or less. When a voltage is applied to such a minute electrode, the shape of the diffusion layer that transports ions to the electrode surface approaches a hemisphere, and the ions diffuse from the hemispherical surface toward the electrode, thus improving the physical characteristics of the sample. It is thought that it can be measured accurately. In other words, when using ordinary electrodes, it is difficult to distinguish between the resistance derived from the solution-electrode interface and the resistance derived from the solution existing between the electrodes only from the frequency characteristics, but by making the electrodes minute, it is possible to distinguish them. It is thought that such a problem can be solved. Since semiconductor chips have been miniaturized and speeded up, such microelectrodes can be manufactured by using the technology in the semiconductor manufacturing method.

The second electrode 9 may be the same as the first electrode. Further, a plurality of the first electrode 7 and the second electrode 9 may exist. FIG. 4 is a conceptual diagram showing an example of a classification device in which the first electrode and the second electrode are provided on the substrate. In the classification device shown in FIG. 4, the first electrode 7 and the second electrode 9 are provided on the substrate 21. Then, the second electrode 9 is provided in the recessed portion 23 of the substrate 21, and the adhesion preventing means 19 is a net covering the recessed portion. The net allows the solution to pass through the net, but the sample does not. As a result, it is possible to prevent the sample from adhering to the second electrode. As shown in FIG. 4, the first electrode 7 and the second electrode 9 may be in the form of an array provided on the substrate. Further, it is preferable that the first electrode 7 and the second electrode 9 can control the connection relationship so that the connection relationship can be adjusted.

FIG. 5 is a conceptual diagram showing a first electrode and a second electrode formed in an array. It is preferable that a plurality of the first electrode 7 and the second electrode 9 are present, and the minimum distance d to the adjacent first electrode 7 or the second electrode 9 is 31 mm or less. If the value of d is too small, the adjacent electrodes will be energized, so the value of d is preferably 0.1 μm or more and 25 mm or less. The lower limit may be 1 μm or more, or 5 μm or more. On the other hand, the upper limit of d may be 20 mm or less, 15 mm or less, 10 mm or less, 1 mm or less, 500 μm or less, 100 μm or less, or 50 μm or less. However, it may be 30 μm or less, 20 μm or less, 5 μm or less, 4 μm or less, or 3 μm or less. In FIG. 5, a portion 15 of the electrodes exposed to the solution tank 5 is drawn. Further, in the array-shaped electrodes of FIG. 5, whichever is the first electrode 7 or the second electrode 9 may be used.

The voltage applying means 11 is an element for applying a voltage between the first electrode 7 and the second electrode 9. The voltage applying means 11 is a means for applying a voltage between the first electrode 7 and the second electrode 9. The applied voltage may be alternating current or direct current, but is usually an alternating voltage. The voltage applying means 11 is preferably capable of controlling the frequency of the AC voltage applied between the electrodes. Since the voltage applied between the two electrodes in dielectric cytometry or the like is known, a known overvoltage voltage may be appropriately adjusted and applied between the first electrode 7 and the second electrode 9. .. Then, it is preferable that the control unit can control which electrode of the electrode array having a plurality of electrodes a voltage is applied to.

The impedance measuring means 13 is an element for measuring the current flowing between the first electrode 7 and the second electrode 9. The impedance measuring means 13 is known. The impedance measuring means 13 may be capable of measuring various physical properties by measuring the current between the two electrodes.

This classification device is, for example, a device for measuring the physical properties or movement of the sample 17 contained in the solution and existing in the vicinity of the first electrode. The example of sample 17 is a biological cell or a liposome, and it is preferable that the surface area S is smaller than the cross-sectional area of the biological cell or the liposome. An example in the vicinity of the first electrode is a region in which the distance to the first electrode is short in the electrode adjacent to the first electrode.

This device preferably has an adhesion preventing means 19 for preventing the sample 17 contained in the solution from adhering to the second electrode. The adhesion preventing means 19 may also prevent the sample from adhering to the first electrode. Examples of the adhesion preventing means 19 are a net and a semipermeable membrane, which will be described later. When the adhesion preventing means 19 is a net, it is preferable that the mesh size of the net is smaller than that of the sample (cross-sectional area). By using such a net, it is possible to effectively prevent the sample from adhering to the electrodes while ensuring the movement of the solution.

The substrate may be composed of an insulator. It is preferable that the substrate is made of a transparent or translucent insulator. An example of such an insulator is transparent ceramics. Transparent ceramics can be achieved by using, for example, one or more of _{Al 2} O ₃ , Y ₂ O _{3 and YAG.} If the substrate is transparent, it is easy to observe their behavior, especially when the sample is cells or liposomes.

Next, the principle of the classification device will be briefly explained.
A complex resistance (complex impedance) between electrodes can be obtained by applying an AC voltage between the electrode plates and measuring the flowing current. When the frequency of the applied AC voltage is changed, the measured complex resistance also changes. Such measurement can be performed using a commercially available precision impedance analyzer (current measuring device).

The frequency-dependent complex resistance is corrected by correcting factors such as the shape of the measuring vessel and the transmission characteristics of the electrical wiring between the complex resistance measuring instrument and the measuring vessel. Can be converted to rate. The frequency dependence of the complex permittivity is called the complex permittivity dispersion (dielectric spectrum).

The complex permittivity dispersion of a cell suspension can be expressed by a single relaxation function (eg, Cole-Cole function) or by superposition of multiple relaxation functions. The variable can be optimized by performing a non-linear adaptation using the undetermined coefficient included in the relaxation function as a variable for the experimentally obtained complex permittivity variance. For example, in the case of the Cole-Cole function, the variables that characterize the dispersion curve are relaxation intensity and relaxation frequency. These dielectric variables are closely related to the structure and physical properties of cells. A method for estimating the electrical property values of the phases (cell membrane, cytoplasm, etc.) constituting the cell from the dielectric variable is described in, for example, Japanese Patent Application Laid-Open No. 2009-42141.

The classification pattern based on the impedance value is preferably a classification pattern obtained based on the phase value θ of the impedance value. The classification pattern is preferably a distribution map corresponding to each section area. The classification pattern is preferably a distribution map in which the value based on the impedance value is converted into a color corresponding to each partition region. The classification pattern is preferably a classification pattern obtained by measuring impedance values for a plurality of types of objects in advance and machine learning the classification patterns for each of a plurality of types of objects. For example, a classification pattern can be obtained by principal component analysis or deep learning and stored in advance.

(Reference example)
In manufacturing the sorting device, we developed electrodes on the substrate (chip). FIG. 6 is a conceptual diagram of the electrodes manufactured in the examples. The electrode surface is made of titanium nitride (TiN) and is the part that comes into contact with samples such as solutions and animal cells. Non-doped silicate glass (NSG, SiO2), aluminum (Al), silicon oxide (SiO2), silicon (Si) were used.

Spare tip
Thirty-six electrode pads of 10 μm square at 20 μm intervals were used as a grid electrode array of 6 rows and 6 columns, covering a region of ^{28900 μm 2.}

Tip for tracking fibrillation behavior
A grid electrode array of 6 rows and 6 columns was formed with 36 electrode pads of 6.6 μm square at intervals of 3.4 μm, covering an area of ^{3200 μm 2.}

Dielectric measuring device FIG. 7 shows a dielectric measuring device for measuring a dielectric spectrum. In this example, the dielectric spectrum was measured using an Agilent 4294A Precision Impedance Analyzer. The Z value and phase were measured.

Glucose solution and PBS were used as the solutions. As an example of the sample, polystyrene beads having a diameter of 25 μm were used here.

Two 10 μm square electrodes were brought into contact with the MGM-450 insect medium at intervals of 20 μm, and an insect cell mass was added to the medium. The electrodes were observed using an optical microscope, and impedance measurements from 100 Hz to 1000000 Hz were performed at 100 mV using an LCR meter between two electrodes with no cell mass on top of the electrodes to obtain Z and θ values. Similarly, two 10 μm square electrodes were brought into contact with the MGM-450 insect medium at intervals of 20 μm, and an insect cell mass was added to the medium. The electrodes were observed using an optical microscope, and impedance measurements from 100 Hz to 1000000 Hz were performed at 100 mV using an LCR meter between the two electrodes with cell clusters on top of the electrodes to obtain Z and θ values. FIG. 8 is a photograph instead of a drawing showing the state of the electrodes and cells. FIG. 9 is a measured Cole-Cole plot (FIG. 9 (A)) and frequency-phase plot (FIG. 9 (B)). The peak near 10000 Hz observed when the measurement result was illustrated on the θ-Hz plane was shifted to the low frequency side in the measurement between the two electrodes with the cell mass on the upper part of the electrode.

Examination of the distance between the electrodes As the electrodes, a 10 μm square electrode, a 6.6 μm square electrode, and a probe needle of a manual prober were used. The 10 μm square electrode and the 6.6 μm square electrode are both connected by independent conductors, and the opposite end of the conductors is probed with a probe needle of a manual prober to obtain continuity.

Two 6.6 μm square electrodes were brought into contact with phosphate buffered saline, and impedance measurements from 100 Hz to 100000000 Hz were performed at 100 mV using an LCR meter to obtain Z and θ values. The θ value is -80 ° at 100Hz, -60 ° at 10000Hz, -80 ° at 10000000Hz, and -75 ° at 100000000. The electrochemical properties of the intermediate material and the electrochemical properties of the intermediate material between the electrodes in the electrode surface region appearing near 10000 Hz, which was not measured by the conventional technique, were confirmed. The measurement results did not change when the electrode spacing was in the range of 3 μm to 60 μm.

One 6.6 μm square electrode and a probe needle of a manual prober were brought into contact with phosphate buffered saline, and impedance measurements from 100 Hz to 100000000 Hz were performed at 100 mV using an LCR meter to obtain Z and θ values. FIG. 10 is a graph that replaces the drawings showing the Cole-Cole plot (FIG. 10 (A)) and the frequency-phase plot (FIG. 10 (B)) to show the effect of the distance between the electrodes. When the electrode spacing was changed in the range of 2.5 mm to 8 mm, the θ value was -80 ° at 100 Hz and -60 ° at 10000 Hz, which was the same as in the above embodiment, but the value of θ was around 10000000 Hz. Increased from -80 ° to -70 ° depending on the distance between the electrodes, and the value of θ increased from -75 ° to -45 ° depending on the distance between the electrodes near 100000000 Hz. The electrochemical properties of the inter-electrode intermediate material in the electrode surface region appeared around 10000 Hz and did not change by changing the distance between the electrodes. On the other hand, the electrochemical properties of the inter-electrode intermediate material in the region away from the electrode surface appeared in the high-frequency region and changed by changing the distance between the electrodes.

Effect of non-electrode electrolyte Increase of θ derived from the electrochemical properties of the inter-electrode intermediate material (sample) in the electrode surface region and θ of θ derived from the electrochemical properties of the inter-electrode intermediate material in the region away from the electrode surface The increase means that two peaks occur on the θ-Hz plane, and the value of Hz at the bottom of the valley between these two peaks is around 10000 Hz, where the electrochemical characteristics of the inter-electrode intermediate material in the electrode surface region appear. When approaching, the electrochemical characteristics of the inter-electrode intermediate material in the electrode surface region and the electrochemical characteristics of the inter-electrode intermediate material in the region away from the electrode surface are separated as two peaks on the θ-Hz plane. Is expected to be difficult. When the measurement results so far are extrapolated, the Hz value at the bottom of the valley is 10 ^ (7.1 + 0.1 (distance between electrodes (mm))), and when the distance between electrodes is 31 mm or more, the electrodes in the electrode surface region It becomes difficult to separate the electrochemical characteristics of the intermediate material and the electrochemical characteristics of the intermediate material between the electrodes in a region away from the electrode surface as two peaks on the θ-Hz plane.

One 6.6 μm square electrode and a probe needle of a manual prober were brought into contact with phosphate buffered saline, and impedance measurements were performed at 100 mV from 100 Hz to 1000000 Hz using an LCR meter to obtain Z and θ values. FIG. 11 is an alternative graph to the drawing showing a frequency-phase plot for examining the effects of non-electrolytes. The peak around 10000 Hz observed when the measurement results were illustrated on the θ-Hz plane was shifted to the low frequency side by adding styrene beads, sugar, and eukaryotic cells to phosphate buffered saline.

In impedance measurement using an LCR meter in which two electrodes are brought into contact with a dispersed solution having an inhomogeneous structure such as micelles and particles, the electrochemical characteristics of the intermediate material between the electrodes in the electrode surface region and the region away from the electrode surface Under the limited conditions of separating and measuring the electrochemical properties of an intermediate substance between electrodes, one electrode is covered with a net so that inhomogeneous structures such as micelles, particles, and cells do not come into contact with each other. It was possible to know which of the two electrodes in contact with the inhomogeneous structure was in contact with.

Sample behavior analysis The durability of the chips was verified by continuously measuring the culture medium for 72 hours without cells. As a result, the impedance did not change. Next, 60 adjacent electrode pairs were repeatedly measured at 1 hour and 15 minute intervals. As a result, we were able to track the migrating cells. The situation is shown in FIG. FIG. 12 is a conceptual diagram showing how migrating cells are tracked. The location of the cells is surrounded by a dotted line. In other words, when the cell moves, the current value (and therefore the impedance) measured at the electrode changes, so it is possible to measure that the cell has moved.

In order to make a measuring part, 64 electrodes of 6.6 μm square were arranged on a silicon wafer at intervals of 3.4 μm so as to be 8 rows and 8 columns. Each electrode can be energized independently. A phosphate buffer solution in which styrene beads having a diameter of 10 μm was dispersed was dropped onto the measuring section, and the probe needle of the manual prober was brought into contact with the phosphate buffer droplets dropped on the measuring section. Impedance was measured between one of the electrodes on the measurement unit and the probe needle of the manual prober in contact with the acid buffer droplet, and this was performed on all 64 electrodes on the measurement unit.

The actually obtained classification devices are shown in FIGS. 13 and 14.

The phase value and Z value for each frequency are obtained for each electrode, and the phase value for each frequency is made to correspond to the relationship between the frequency and the XYZ value in the color matching function from the three RGB channels. Converted to the image. This is to suit the convenience of the image analysis tool. When the phase value at the time of 1000 Hz measurement corresponds to RGB of 401 nm light and the phase value at the time of 1000000 Hz measurement corresponds to RGB of 801 nm light, it is converted as shown in FIG. Measured values with peaks around 3.5 (log10 (Hz)) are converted to RGB (R: 106, G: 102, B: 48), and measurements with peaks around 4.5 (log10 (Hz)) are RGB. Is converted to (R: 59, G: 70, B: 127). The conversion table is shown in Table 1.

The values of each of the 64 electrodes can be converted to RGB and arranged in a matrix corresponding to the arrangement of the electrodes of the measuring unit (FIG. 16).

Similarly, FIG. 17 is obtained by measuring and converting a phosphate buffer solution in which styrene beads having a diameter of 100 μm are dispersed.

By repeating the above steps, the phosphate buffer solution in which styrene beads having a diameter of 10 μm was dispersed was measured and converted into an RGB image, and the phosphate buffer solution in which styrene beads having a diameter of 100 μm were dispersed was measured. 50 sheets each of the files converted into RGB images were acquired.

Features were extracted from the images by unsupervised machine learning (Fig. 18).

A solution in which the diameter of polystyrene newly dispersed in the solution is 10 μm or 100 μm is measured, and the solution is classified according to the feature amount.

The body surface of the animal was sterilized and the blood was measured by inserting the measuring part. From the obtained features, diseased individuals and non-diseased individuals were classified.

Urine was dropped on the measuring part for measurement. From the obtained features, diseased individuals and non-diseased individuals were classified.

Blood was dropped on the measuring part for measurement. From the obtained features, diseased individuals and non-diseased individuals were classified.

The present invention can be used in the field of analytical instruments.

1 Sorting device 2a, 2b, 2c, 2d Partition region 3 Solution 5 Solution tank 7,7a, 7b, 7c, 7d First electrode 9 Second electrode 11 Voltage applying means 13 Impedance measuring means 15 Solution of the first electrode Part exposed in the tank 25 1st storage unit 27 2nd storage unit 29 Classification judgment unit

Claims (10)

A measuring unit (8) including a plurality of first electrodes (7a, 7b, 7c) existing in each partition region of a plurality of compartment regions (2a, 2b, 2c) partitioned in a matrix.
A second electrode (9) that generates an electric field between each of the plurality of first electrodes, and
A voltage applying means (11) for applying a voltage to each of the plurality of first electrodes and the second electrode, and
An impedance measuring unit (13) that measures the impedance between each electrode of the plurality of first electrodes and the second electrode and obtains an impedance value corresponding to each of the compartment regions.
A first storage unit (25) that stores impedance values corresponding to the respective partition regions measured by the impedance measurement unit, and a first storage unit (25).
A second storage unit (27) that stores a classification pattern based on the impedance value corresponding to each partition area, and
It has a classification determination unit (29) that classifies measurement targets using a classification pattern stored in the second storage unit (27) and a pattern based on the impedance value stored in the first storage unit (25). Sorting device (1). The classification device according to claim 1.
Further having an injection needle body (31)
The classification device (1) is provided in a recessed portion (33) provided on the outer peripheral surface of the injection needle body (31).
The classification pattern is a classification device based on impedance values measured for blood. The classification device according to claim 2.
Further having a drip container (35) capable of supplying a liquid to the injection needle body (31).
When the drip solution is supplied to the target using the drip container (35), the classification device (1) provided on the injection needle body (31) continuously classifies the target based on the blood. Can be a sorting device. The classification device according to claim 3.
A classification device for grasping the presence or absence of a specific disease or the presence or absence of a specific situation. The classification device according to claim 3.
Further equipped with an alarm device (39)
When the classification determination unit (29) determines that the pattern based on the impedance value corresponds to the classification pattern stored in association with the information related to the warning among the classification patterns, the alarm device (39) is used. A classification device that outputs an alarm. The classification device according to claim 1.
The voltage applying means (11) is a classification device for applying a voltage by sweeping a frequency in a frequency region of 100 kHz or more and 10 MHz or less. The classification device according to claim 1.
The classification pattern based on the impedance value is
A classification device that is a classification pattern obtained based on the phase value (θ) of the impedance value. The classification device according to claim 1.
The classification pattern is a classification device that is a distribution map corresponding to each section area. The classification device according to claim 1.
The classification pattern is a classification device in which a value based on the impedance value is converted into a color corresponding to each partition region. The classification device according to claim 1.
The classification pattern is a classification device obtained by measuring impedance values for a plurality of types of objects in advance and machine learning the classification patterns for each of a plurality of types of objects.

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