Measuring equipment and programs

Abstract

To provide a measuring device and a program that are capable of improving accuracy in measuring the activation level of odorant receptors.SOLUTION: A measuring device 1, which is used in an area having a plurality of odorant receptors and measures the degree of activation of the odorant receptors by a test article, comprises: a signal acquisition unit 10 that acquires a signal based on the action of the odorant receptors; a probability calculation unit 17 that calculates, on the basis of the over-time waveform of the acquired signal, the probability that the waveform is derived from receptor responses; and an activation level calculation unit 18 that calculates the degree of over-time activation of the odorant receptors as an activation level, using the signal from which a predetermined probability or higher has been calculated.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a measurement device and a program. [Background technology]

[0002] Quantifying odors has been done in the past. Olfactory receptors induce signal transduction through the action of extracellular substances (ligands). There are various types of receptors depending on the ligand and function, but the responsiveness of receptors and ligands has not been fully elucidated. Furthermore, recent genetic analysis has revealed proteins that are structurally similar to receptors but whose functions are unknown; these are called orphan receptors.

[0003] In order to investigate the relationship between receptors and ligands, it is expected that a measurement technique for measuring the responsiveness of receptors will be established. For example, a receptor array in which specific receptors having different genetic information are arranged one by one, and a measurement technique in which a specific ligand is simultaneously applied to the array have been proposed (for example, see Patent Document 1). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2019 / 035476 Summary of the Invention [Problem to be solved by the invention]

[0005] The measurement technique disclosed in Patent Document 1 is useful in that it can measure the change in activity of each receptor by measuring the responsiveness of the receptor over time. In addition, it is preferable from the viewpoint of measurement accuracy if it is possible to eliminate changes that are not caused by the ligand. The present invention has been made in consideration of the above-mentioned points, and has an object to provide a measurement device and a program that can improve the accuracy of measuring the activity of olfactory receptors. [Means for solving the problem]

[0006] According to one aspect of the present invention, a plurality of olfactory receptors arranged on a substrate are The degree of activation of the olfactory receptors by the test substance was Using the change in brightness appearing in the image containing the olfactory receptor in response to the test substance, A measuring device for measuring, The substrate has the plurality of olfactory receptors arranged in separate compartments, and by acquiring images of each of the compartments over a predetermined period of time including the timing of contact of the test substance with the olfactory receptors, The olfactory receptor response A signal acquisition unit that acquires a signal based on the a combining unit that combines adjacent pixels that show a luminance change of a predetermined value or more among the pixels in the captured image to generate a combined region; Obtained Each of the connected regions in the captured image Over time Brightness change Based on The olfactory receptor a probability calculation unit that calculates the probability that the signal is due to a receptor response; The binding region of The above Using the signal, In each of the compartments The olfactory receptor was found to react join The number of regions, the probability, and the signal brightness and an activity calculation unit that calculates the degree of activation of the olfactory receptor over time as activity based on the rate of change.

[0007] In addition, it is preferable that the measurement device further includes an extraction unit that extracts time series information of the luminance change rate for pixels of an image captured of the region, the signal acquisition unit acquires the image, and the probability calculation unit calculates the probability that the extracted time series information is a waveform derived from a receptor response.

[0008] In addition, it is preferable that the measurement device further includes a pixel identification unit that identifies the pixels that show a luminance change of a predetermined amount or more during the activity measurement period, and the extraction unit extracts the time series information of the luminance change rate of the identified pixels.

[0009] In addition, it is preferable that the measurement device further includes a combining unit that combines adjacent pixels among the identified pixels, and the extraction unit extracts the time series information of the luminance change rate of the combined pixels that have an area equal to or greater than a predetermined value among the combined pixels.

[0010] In addition, it is preferable that the measuring device further includes a reference brightness calculation unit that calculates a reference brightness based on the brightness of the pixel at a predetermined time before the olfactory receptor comes into contact with the test substance and the average brightness of the pixel for a predetermined period immediately prior to the contact, and the pixel identification unit identifies the pixel whose average rate of brightness change during the activity measurement period is equal to or greater than a predetermined value relative to the reference brightness.

[0011] According to another aspect of the present invention, a plurality of olfactory receptors arranged on a substrate are The degree of activation of the olfactory receptors by the test substance was Using the change in brightness that appears in the image containing the olfactory receptor in response to the test substance, A program for operating a computer as a measurement device, The substrate has the plurality of olfactory receptors arranged in separate compartments, The computer, By acquiring images of each of the sections over a predetermined period of time including the timing of contact of the test substance with the olfactory receptor, The olfactory receptor response Based on Imaging a signal acquisition unit that acquires a signal; a combining unit that combines adjacent pixels that show a luminance change of a predetermined value or more among the pixels in the captured image to generate a combined region; Obtained Each of the connected regions in the captured image Over time Brightness change Based on The olfactory receptor A probability calculation unit that calculates the probability that the signal is due to a receptor response, The binding region of The above Using the signal, The degree of activation of the olfactory receptor over time is calculated as an activity level based on the number of binding regions in each of the sections where a reaction was observed in the olfactory receptor, the probability, and the rate of change in brightness of the signal. activity calculation unit, Function as do. Effect of the Invention

[0012] The present invention can provide a measurement device and a program that can improve the accuracy of measuring the activity of olfactory receptors. [Brief description of the drawings]

[0013] [Figure 1] 1 is a plan view showing an array of olfactory receptor regions that are the measurement targets of a measurement device according to a first embodiment of the present invention. FIG. [Diagram 2] 1 is a block diagram showing a configuration of a measurement device according to a first embodiment. [Diagram 3] 4 is a graph showing a waveform derived from a receptor response determined in the measurement device of the first embodiment. [Figure 4]4 is a graph showing a waveform of noise determined by the measurement device of the first embodiment. [Diagram 5] FIG. 4 is a screen diagram showing a screen output by the measurement device of the first embodiment. [Figure 6] FIG. 4 is a screen diagram showing a screen output by the measurement device of the first embodiment. [Figure 7] FIG. 4 is a screen diagram showing a screen output by the measurement device of the first embodiment. [Figure 8] 4 is a flowchart showing the flow of operations of the measurement device of the first embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] A measuring device 1 and a program according to an embodiment of the present invention will be described below with reference to FIGS. First, an array 100 on which olfactory receptors that are the subject of measurement by the measurement device 1 are arranged will be described. 1, the array 100 includes a substrate 5 and a hydrophobic coating 6 on the substrate 5. A plurality of through-holes 2 are provided in the hydrophobic coating 6. The through-holes 2 reach the substrate 5.

[0015] Nucleic acid 3 capable of forming a specific olfactory receptor (hereinafter also simply referred to as receptor) is mounted in the through-hole 2 in contact with the substrate 5. Here, the nucleic acid 3 includes a nucleic acid containing a gene encoding the specific receptor. A plurality of nucleic acids 3 are mounted on the array 100 and in contact with the substrate 5, and the nucleic acid 3 is mounted in each of the through-holes 2 of the array 100. For example, different types of nucleic acid 3 containing a gene encoding a specific receptor may be mounted in each of the through-holes 2.

[0016] When the receptor comes into contact with a test substance (ligand), a change occurs in the cell state. Specifically, a change occurs in the intracellular calcium concentration or the intracellular cAMP concentration. Such a change can be measured by using a cAMP-sensitive dye, a cAMP-sensitive fluorescent protein, a calcium-sensitive dye, or a calcium-sensitive fluorescent protein. For example, the activity of the receptor can be measured by measuring the change in brightness caused by the cAMP-sensitive dye or the cAMP-sensitive fluorescent protein.

[0017] Next, an overview of the measurement device 1 will be described. The measuring device 1 measures the activity of the receptor by measuring the luminance change for a predetermined period of time when the test substance contacts the olfactory receptor. The measuring device 1 measures the degree of activation of the olfactory receptor by the test substance for a region (region including the through-hole 2) including cells expressing a plurality of olfactory receptors. The measuring device 1 measures the activity of the receptor using, for example, an image (for example, a moving image) obtained by capturing an image of one surface of the substrate 5 of the array 100. At this time, it is preferable for the measuring device 1 to remove the luminance change that is not due to the activation of the receptor in terms of accuracy. The measuring device 1 according to this embodiment distinguishes between responses due to the activation of the receptor and responses that are not, and removes the responses that are not due to the activation from the calculation of the activity. In this way, the measuring device 1 according to this embodiment improves the accuracy of the measurement of the activity. The measuring device 1 according to this embodiment distinguishes between luminance changes due to the activation of the receptor and changes that are not, for example, using a learning model.

[0018] Next, the configuration of the measurement device 1 according to this embodiment will be described with reference to FIG. As shown in FIG. 2, the measurement device 1 includes a signal acquisition unit 10, a signal storage unit 11, a reference brightness calculation unit 12, a pixel identification unit 13, a combination unit 14, an extraction unit 15, a learning model storage unit 16, a probability calculation unit 17, an activity calculation unit 18, and an output unit 19.

[0019] The signal acquiring unit 10 is realized, for example, by the operation of a CPU. The signal acquiring unit 10 acquires, for example, a signal based on the operation of an olfactory receptor. The signal acquiring unit 10 acquires, for example, a captured image (for example, a moving image) of an area including a plurality of olfactory receptors of the array 100.

[0020] The signal storage unit 11 is, for example, a recording medium such as a hard disk, etc. The signal storage unit 11 stores the acquired signals.

[0021] The reference brightness calculation unit 12 is realized, for example, by the operation of a CPU. The reference brightness calculation unit 12 calculates a reference brightness for correcting unevenness in the excitation light intensity in the microscope field of view and the amount of pigment or fluorescent protein present in each cell. Specifically, the reference brightness calculation unit 12 calculates the reference brightness based on the average brightness of pixels in a predetermined period immediately before the olfactory receptor comes into contact with the test substance. The reference brightness calculation unit 12 calculates the reference brightness for each pixel included in the acquired captured image. For example, the reference brightness calculation unit 12 calculates the average brightness of pixels in a predetermined period immediately before the olfactory receptor comes into contact with the test substance.

[0022] The pixel identifying unit 13 is realized, for example, by the operation of a CPU. The pixel identifying unit 13 identifies pixels that show a luminance change of a predetermined value or more during the activity measurement period. For example, the pixel identifying unit 13 identifies pixels whose average luminance change rate during the activity measurement period is greater than a predetermined value, relative to a reference luminance. Specifically, the pixel identifying unit 13 identifies pixels whose luminance change rate is greater than a predetermined value, relative to the standard deviation of the luminance change rate during the predetermined period in which the reference luminance was calculated. The pixel identifying unit 13 identifies pixels whose average luminance change rate during the period in which the olfactory receptor is in contact with the test substance is greater than or equal to +5SD relative to the standard deviation SD (hereinafter also referred to as pixels with increased fluorescent luminance).

[0023] The combining unit 14 is realized, for example, by the operation of a CPU. The combining unit 14 combines adjacent pixels among the identified pixels. For example, the combining unit 14 combines adjacent pixels with increased fluorescent luminance.

[0024] The extraction unit 15 is realized, for example, by the operation of a CPU. The extraction unit 15 extracts time-series information on the luminance change rate for pixels in a captured image of an area. The extraction unit 15 extracts, for example, luminance changes of pixels identified by the pixel identification unit 13. The extraction unit 15 calculates the luminance change rate for combined regions in which adjacent pixels with increased fluorescent luminance on the captured image are combined, and which have an area of ​​a predetermined area or more. Specifically, the extraction unit 15 calculates the luminance change rate for combined regions in which adjacent pixels with increased fluorescent luminance on the captured image are combined, and which have an area of ​​a predetermined area or more (for example, 100 μm 2 The extraction unit 15 calculates the luminance change rate for all periods measured. The extraction unit 15 extracts time-series information of the calculated luminance change rate.

[0025] The learning model storage unit 16 is, for example, a recording medium such as a hard disk. The learning model storage unit 16 stores a learning model for determining whether the time-series information of the luminance change is due to a receptor reaction or due to noise. That is, the learning model storage unit 16 stores a learning model in which the time-series information of the luminance change rate is an explanatory variable, and whether the time-series information reflects a change in the cell state due to a response between the receptor and the test substance is an objective variable.

[0026] The probability calculation unit 17 is realized by, for example, the operation of a CPU. The probability calculation unit 17 calculates the probability that the waveform is derived from a receptor response based on the time-dependent waveform of the acquired signal. In this embodiment, the probability calculation unit 17 calculates the probability that the waveform is derived from a receptor response for the extracted time-series information. The probability calculation unit 17 calculates the probability that the waveform reflects a change in the cell state, for example, using a learning model. For example, for a waveform as shown in FIG. 3, the probability calculation unit 17 calculates the probability that the waveform reflects a change in the cell state as high for time-series information in which the luminance change rate increases after contact with the test substance. On the other hand, the probability calculation unit 17 calculates the probability that the waveform reflects a change in the cell state as low for a waveform as shown in FIG. 4. That is, the probability calculation unit 17 calculates the possibility that the waveform shown in FIG. 4 is noise as high.

[0027] The activity calculation unit 18 is realized by, for example, the operation of a CPU. The activity calculation unit 18 calculates the degree of activation of the olfactory receptor over time using a signal calculated to be equal to or higher than a predetermined probability. For example, the activity calculation unit 18 counts the number of regions (ROI: Region Of Interest) present in each section on the array 100 for each region. The activity calculation unit 18 also calculates the degree of activation from the number of ROIs present in the same section on the array 100, the probability that the ROI is expected to be derived from a receptor response, and time-series information on the luminance change rate of each ROI. Specifically, the activity calculation unit 18 calculates the degree of activation of the receptor caused by the test substance at each time point of the continuous images measured continuously in the time direction from various information. The activity calculation unit 18 calculates the degree of activation using, for example, the following equation 1.

number

[0028] The output unit 19 is realized by, for example, the operation of a CPU. The output unit 19 outputs the calculated degree of activation. For example, as shown in FIG. 5, the output unit 19 outputs an animation showing the position of the array 100 and the degree of activation shown by a bar graph. In addition, the output unit 19 outputs a three-dimensional line graph in which the vertical axis indicates the degree of activation, the horizontal axis indicates time (hours), and the depth indicates the type of receptor, for example, as shown in FIG. 6. In addition, the output unit 19 outputs a tiled display in which the vertical axis of the three-dimensional line graph is replaced with color, for example, as shown in FIG. 7.

[0029] Next, the flow of operations of the measurement device 1 will be described with reference to FIG. First, the signal acquisition unit 10 acquires a signal (step S1). Next, the reference luminance calculation unit 12 calculates a reference luminance from the acquired signal (step S2). Next, the pixel identification unit 13 identifies pixels that show a luminance change of a predetermined amount or more (step S3).

[0030] Next, the combining unit 14 combines adjacent pixels having a brightness change rate equal to or greater than a predetermined value (step S4). Next, the extracting unit 15 extracts time-series information of the calculated brightness change rate (step S5). Next, the probability calculating unit 17 calculates the probability that the time-series information reflects a change in the cell state (step S6).

[0031] Next, the activity calculation unit 18 calculates the degree of activation of the olfactory receptor over time (step S7), and then the output unit 19 outputs the calculated activity (step S8).

[0032] Next, the program will be described. Each component included in the measurement device 1 can be realized by hardware, software, or a combination of these. Here, being realized by software means being realized by a computer reading and executing a program.

[0033] The program can be stored and provided to the computer using various types of non-transitory computer readable media. The non-transitory computer readable media includes various types of tangible storage media. Examples of the non-transitory computer readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROM (Read Only Memory), CD-R, CD-R / W, and semiconductor memory (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (random access memory)). The display program may also be provided to the computer by various types of transitory computer readable media. Examples of the transitory computer readable media include electric signals, optical signals, and electromagnetic waves. The transitory computer readable media can provide the program to the computer via a wired communication path such as an electric wire and an optical fiber, or via a wireless communication path.

[0034] The measuring device 1 and the program according to the above-described first embodiment provide the following advantages. (1) A measuring device 1 that measures the degree of activation of olfactory receptors by a test substance in an area containing multiple olfactory receptors, and includes a signal acquisition unit 10 that acquires a signal based on the operation of the olfactory receptor, a probability calculation unit 17 that calculates the probability that the waveform of the acquired signal is due to a receptor response based on the waveform of the acquired signal over time, and an activity calculation unit 18 that calculates the degree of activation of the olfactory receptors over time as activity using a signal that is calculated to have a predetermined probability or higher. The program also operates a computer as a measuring device 1 that measures the degree of olfactory receptor activation by a test substance in an area containing multiple olfactory receptors, and causes the computer to function as a signal acquisition unit 10 that acquires a signal based on the operation of the olfactory receptor, a probability calculation unit 17 that calculates the probability that the waveform of the acquired signal is due to a receptor response based on the waveform over time of the acquired signal, and an activity calculation unit 18 that calculates the degree of olfactory receptor activation over time as activity using a signal that is calculated to have a predetermined probability or higher. This makes it possible to remove noise components from the receptor reaction while taking into account the likelihood that the reaction is a reaction, thereby improving the accuracy of the calculated activity.

[0035] The measurement device 1 further includes an extraction unit 15 that extracts time series information of the luminance change rate for pixels of an image of the region, the signal acquisition unit 10 acquires the image, and the probability calculation unit 17 calculates the probability that the extracted time series information is a waveform derived from a receptor response. This makes it possible to calculate the activity based on the luminance of the pixel of the image of the region. Therefore, it is possible to perform measurements using a simpler configuration.

[0036] The measurement device 1 further includes a pixel specifying unit 13 that specifies pixels that show a luminance change of a predetermined value or more during the activity measurement period, and the extraction unit 15 extracts time-series information on the luminance change rate of the specified pixels. This makes it possible to exclude obvious noise from the extraction in advance, thereby further improving the accuracy of activity calculation.

[0037] The measurement device 1 further includes a combining unit 14 that combines adjacent pixels among the identified pixels, and an extracting unit 15 extracts time-series information on the luminance change rate of combined pixels that have an area equal to or larger than a predetermined value among the combined pixels. This makes it possible to exclude pixels that are likely to be noise, thereby improving the accuracy of activity calculation.

[0038] The measuring device 1 further includes a reference brightness calculation unit 12 that calculates a reference brightness based on the brightness of the pixel at a predetermined time before the olfactory receptor comes into contact with the test substance and the average brightness of the pixel for a predetermined period immediately before the contact, and the pixel identification unit 13 identifies pixels whose average brightness change rate during the activity measurement period is equal to or greater than a predetermined value relative to the reference brightness. This makes it possible to remove noise from the electron microscope in advance, thereby further improving the accuracy of activity calculation.

[0039] Although each preferred embodiment of the measuring device of the present invention has been described above, the present invention is not limited to the above-mentioned embodiments and can be modified as appropriate. For example, in the above embodiment, the signal acquisition unit 10 acquires a captured image, but is not limited to this. The signal acquisition unit 10 may, for example, use a patch clamp method to provide a needle to each receptor and acquire a current value obtained according to the degree of activation as a signal. In this case, the reference brightness calculation unit 12, the pixel specification unit 13, the extraction unit 15, and the combination unit 14 may not be provided.

[0040] In the above embodiment, the learning model storage unit 16 may store a learning model in which the time series information (e.g., matrix data) of the luminance change rate of receptors related to a specific odor is the explanatory variable, and the physiological action occurring when smelling the odor is the objective variable. For example, the effect on the physical state represented by indices such as electroencephalogram, electrocardiogram, heart rate, blood pressure, respiratory rate, skin conductance, and electromyogram caused by the aroma odor of herbs or citrus fruits may be stored as the objective variable. This allows the probability calculation unit 17 to calculate the effect of the test substance on the physical state. Furthermore, the probability calculation unit 17 can obtain a scent that brings about a desired effect by replacing the objective variable and the explanatory variable. For example, it becomes possible to select a test substance with a scent that can provide a relaxing effect. [Explanation of symbols]

[0041] 1. Measurement equipment 10 Signal Acquisition Unit 12 Reference luminance calculation section 13 Pixel Identification Unit 14 Joint 15 Extraction part 17 Probability Calculation Section 18 Activity calculation part

Claims

1. A measuring device that measures the degree of activation of a plurality of olfactory receptors arranged on a substrate by a test substance by utilizing a change in brightness appearing in an image including the olfactory receptors in response to the test substance, the substrate having the plurality of olfactory receptors arranged in separate compartments, a signal acquisition unit that acquires images of each of the sections over time for a predetermined period including the timing of contact of the test substance with the olfactory receptor, thereby acquiring a signal based on the response of the olfactory receptor; a combining unit that combines adjacent pixels that show a luminance change of a predetermined value or more among the pixels in the captured image to generate a combined region; a probability calculation unit that calculates a probability that the signal is derived from a receptor response of the olfactory receptor based on a change in luminance over time of each of the binding regions in the acquired captured image; an activity calculation unit that uses the signals from the binding regions that are calculated to have a predetermined probability or higher to calculate the degree of activation of the olfactory receptor over time as activity based on the number of binding regions in each of the sections where a reaction was observed in the olfactory receptor, the probability, and the luminance change rate of the signal; A measuring device comprising:

2. The measurement device according to claim 1 , wherein the activity calculation section calculates the activity at each point in time of the continuous captured images measured continuously in a time direction.

3. Further comprising an extraction unit for extracting time series information of a luminance change rate of a combined region having an area equal to or larger than a predetermined value among the combined regions, The measurement device according to claim 1 , wherein the probability calculation unit calculates a probability that the extracted time-series information is a signal derived from the receptor response.

4. a pixel specifying unit that specifies the pixel that exhibits a luminance change of a predetermined value or more during the predetermined period, The measurement apparatus according to claim 3 , wherein the extraction unit extracts the time-series information of a luminance change rate of the combined region that includes the identified pixel.

5. A reference luminance calculation unit calculates a reference luminance based on the luminance of the pixel at a predetermined time before the olfactory receptor comes into contact with the test substance and the average luminance of the pixel during a predetermined period immediately before the contact, The measurement device according to claim 4 , wherein the pixel specifying unit specifies the pixels whose average rate of change in luminance during the measurement period of the activity is equal to or greater than a predetermined value with respect to the reference luminance.

6. A program for operating a computer as a measuring device that measures the degree of activation of a plurality of olfactory receptors arranged on a substrate by a test substance by utilizing a change in brightness appearing in an image including the olfactory receptors in response to the test substance, the substrate being arranged so that the plurality of olfactory receptors are arranged in separate compartments, The computer, a signal acquisition unit that acquires images of each of the sections over time for a predetermined period including the timing of contact of the test substance with the olfactory receptor, thereby acquiring an image signal based on the response of the olfactory receptor; a combining unit that combines adjacent pixels that show a luminance change of a predetermined value or more among the pixels in the captured image to generate a combined region; a probability calculation unit that calculates a probability that the signal is derived from a receptor response of the olfactory receptor based on a change over time in luminance of each of the binding regions in the acquired captured image; an activity calculation unit that uses the signals of the binding regions that are calculated to have a predetermined probability or higher to calculate the degree of activation of the olfactory receptor over time as activity based on the number of binding regions in each of the sections where a reaction was observed in the olfactory receptor, the probability, and the rate of change in luminance of the signal; A program that functions as a

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