JP6842322B2 - Analysis equipment - Google Patents

Description

The present invention relates to an analyzer, and is suitable for analyzing components contained in blood or interstitial fluid, for example.

As an analyzer for analyzing components in blood, the analyzer of Patent Document 1 below has been proposed. The analyzer of Patent Document 1 below irradiates the cornea of the eyeball with an excitation light beam having a single wavelength from visible light to the near infrared region, and shows the intensity distribution of Raman scattered light generated in the corneum for each wavelength. Blood components are analyzed based on Raman spectra.

According to Patent Document 1, the excitation wavelength shift wavenumber 420～1500Cm ^-1 or converted to 2850～3000Cm ^-1 a, preferably ^{420~450cm -1, 460~550cm -1, 750~800cm -1} , 850 ^{~940cm -1, 1000~1090cm -1, 1090~1170cm -1} , 1200~1300cm -1, 1300~1390cm -1, the concentration of glucose from the intensity of the peak in the 1400～1500Cm ^-1 or 2850～3000Cm ^-1 It is stated that it can be quantified.

Japanese Unexamined Patent Publication No. 9-12207

However, it was found that the concentration of lactic acid in the blood tends to increase even in healthy people who are in the pre-stage of a disease such as diabetes or who develop a disease such as diabetes. .. Therefore, the peak of the shift wavenumber includes the intensity derived from lactic acid, and there is a concern that the intensity may be high. In this case, if the glucose concentration is obtained from the intensity of the peak of the shift wavenumber, the error from the actual glucose concentration becomes large, and as a result, the reliability of the analysis result becomes unreliable.

By the way, glucose and lactic acid belong to the same metabolic pathway called glycolysis. In general, if the metabolic pathways are the same, a part of each of the spectral waveforms corresponding to a plurality of substances belonging to the metabolic pathway tends to overlap. Therefore, in the Raman spectrum in which the spectral waveforms corresponding to each of a plurality of substances are mixed, the peak of the wave number peculiar to the spectral waveform corresponding to the substance to be detected is in addition to the intensity derived from the substance to be detected, and other substances. Derivative strength may be included in no small measure. Therefore, when the concentration of the substance is obtained from the intensity of the peak of a predetermined wave number in the Raman spectrum, the error from the actual concentration may become large. In this case, as in the case of glucose, there is a concern that the reliability of the analysis result will be lost.

Therefore, the present invention proposes an analyzer that can improve the reliability of analysis results.

In order to solve the above problems, the analyzer of the present invention is a first substance derived from a substance to be detected contained in a peak of a predetermined wave number in a Raman spectrum showing an intensity distribution for each wave number of Raman scattered light generated in blood or interstitial fluid. Of the intensity and the second intensity derived from another substance contained in the peak and belonging to the same metabolic pathway as the substance to be detected, the prediction unit for predicting the second intensity and the prediction unit An extraction unit that extracts the first intensity contained in the peak of the predetermined wave number based on the predicted second intensity, and a concentration of the substance to be detected based on the intensity extracted by the extraction unit. It is characterized by including a concentration detecting unit for detecting the above.

According to this analyzer, even if the second intensity derived from another substance contained in the peak of a predetermined wave number is unknown, the unknown second intensity is predicted, and the second intensity is obtained from the intensity of the peak. The first intensity derived from the substance to be detected can be extracted by removing the above. Therefore, the concentration can be directly detected from the first intensity derived from the substance to be detected. Therefore, even when the intensity derived from other substances contained in the peak of a predetermined wave number is high, the concentration of the substance to be detected can be approximated to the actual concentration. In this way, the analyzer of the present invention can improve the reliability of the analysis result.

It is preferable that the prediction unit detects the concentration of the other substance from the intensity of the peak having a wave number different from the predetermined wave number, and predicts the second intensity based on the detected concentration.

In this way, even if the concentration of another substance is likely to fluctuate in blood or interstitial fluid, the second intensity derived from the other substance that becomes unknown can be predicted in a state that reflects the concentration. Can be done.

Further, when the second intensity is less than a predetermined threshold value, the extraction unit preferably extracts the intensity at the peak of the predetermined wave number including the first intensity.

In this way, even if the intensity of the peak of a predetermined wave number is simply extracted, the degree to which the second intensity derived from another substance affects as an error becomes small. Therefore, even when the degree of influence of the second intensity as an error is small, the second intensity derived from the substance to be detected is uniformly removed from the intensity of the peak of the predetermined wave number. Compared with the case of extracting 1 intensity, the processing load of the extraction unit can be reduced.

Moreover, it is preferable that the metabolic pathway is glycolytic.

Regardless of which substance belongs to glycolysis, predict the second intensity of other substances contained as unknown together with the first intensity derived from the substance to be detected, and remove the second intensity from the intensity of the peak. The first intensity derived from the substance to be detected can be extracted. Therefore, the concentrations of various substances belonging to glycolysis can be detected in a state that approximates the actual concentration. Therefore, highly reliable information can be provided as an index for detection and treatment of glucose metabolism disorders.

Further, it is preferable that the substance to be detected is glucose and the other substance is lactic acid.

When the substance to be detected is glucose and the other substance is lactic acid, even if the concentration of lactic acid in blood or interstitial fluid is high, the concentration of glucose that is close to the actual concentration can be detected. Therefore, highly reliable information can be provided as an index for the detection and treatment of diseases such as diabetes.

Further, it is preferable to further provide a notification unit for notifying the risk of developing diabetes according to the concentration of lactic acid.

As mentioned above, the blood of people in the pre-diabetic stage tends to have increased levels of lactic acid. Therefore, it is possible to promote the prevention of diabetes by notifying the risk of developing diabetes according to the concentration of lactic acid.

As described above, according to the present invention, there is provided an analyzer capable of improving the reliability of analysis results.

It is a figure which shows the structure of an analysis system. It is a figure which shows the structure of the analyzer. It is a figure which illustrates the lactate calibration curve. It is a flowchart which shows the analysis method. It is a figure which shows the structure of another analysis system.

Hereinafter, embodiments and modifications thereof for carrying out the analyzer according to the present invention will be illustrated together with the accompanying drawings. The embodiments illustrated below and variations thereof are for facilitating the understanding of the present invention, and are not for limiting the interpretation of the present invention. The present invention can be modified and improved without departing from the spirit of the present invention.

<Analysis system configuration>
FIG. 1 is a diagram showing a configuration of an analysis system. As shown in FIG. 1, the analysis system 1 of the present embodiment analyzes the concentration of a substance contained in the sample SPL based on the Raman scattered light generated in the sample SPL by irradiation with the excitation light. The analysis system 1 includes a light source 2, an irradiation unit 3, a Raman light propagation unit 4, a spectroscope 5, and an analyzer 6 as main components. In the present embodiment, the sample SPL is blood or interstitial fluid collected from a human.

The light source 2 is a light source that emits excitation light. Since the Raman scattered light generated in the sample SPL by irradiation with the excitation light tends to be weak, the light source 2 is preferably a light source that emits high-intensity excitation light. Further, since the concentration of the substance contained in the sample SPL is calculated based on the wavelength of the excitation light, it is preferable that the light source 2 is a light source that emits the excitation light of a single wavelength. Examples of such a light source 2 include a solid-state laser. The wavelength of the excitation light is, for example, a single wavelength selected from 514 nm, 532 nm, 633 nm, 670 nm, and 785 nm.

The irradiation unit 3 is configured to irradiate the sample SPL with the excitation light emitted from the light source 2. For example, the irradiation unit 3 may include a mirror that reflects the excitation light emitted from the light source 2 toward the sample SPL, and a condensing lens that collects the excitation light reflected by the mirror on the sample SPL.

The Raman light propagation unit 4 is configured to propagate the Raman scattered light generated in the sample SPL to the spectroscope 5. For example, the Raman light propagation unit 4 may be composed of a collimating lens that collimates the Raman scattered light generated in the sample SPL and a condensing lens that collects the Raman scattered light collimated by the collimating lens on the spectroscope 5.

When the sample SPL is irradiated with the excitation light, the interaction between the excitation light and the sample SPL causes the sample SPL to generate Rayleigh scattered light having a wavelength different from the wavelength of the excitation light and the same wavelength as the wavelength of the excitation light. Rayleigh scattered light is generated. The Raman light propagation unit 4 has a filter 41 that removes the Rayleigh scattered light. In the example shown in FIG. 1, the filter 41 is arranged between the collimating lens and the condenser lens.

The spectroscope 5 has a diffraction grid 51 and a photodetector 52. The diffraction grid 51 is an optical element that divides the light supplied from the sample SPL through the Raman light propagation unit 4 for each wavelength and guides the light to the light receiving surface of the photodetector 52.

The photodetector 52 has a plurality of light receiving elements arranged one-dimensionally or two-dimensionally in the light receiving surface. The photodetector 52 stores a charge proportional to the intensity of light of each wavelength exposed to the light receiving element in the light receiving surface, and outputs data indicating the intensity distribution of each wavelength of the light to the analyzer 6. In the present embodiment, the Rayleigh scattered light is removed by the filter 41 of the Raman light propagation unit 4, so that the Raman scattered light is incident on the light receiving surface of the photodetector 52. Therefore, the data output to the photodetector 52 shows the intensity distribution of the Raman scattered light for each wavelength. Specific examples of the photodetector 52 include a photodiode, a CCD (Charge Coupled Device), and a CMOS (Complementary Metal Oxide Semiconductor).

The analyzer 6 is configured to calculate the concentration of the component contained in the sample SPL based on the data given from the photodetector 52 of the spectroscope 5 and notify the calculated concentration of the component as necessary. To.

<Analyzer configuration>
Next, the analyzer 6 will be described in detail. FIG. 2 is a diagram showing an outline of the configuration of the analyzer according to the present embodiment. As shown in FIG. 2, the analyzer 6 includes an input unit 61, a storage unit 62, a display unit 63, and a control unit 64 as constituent elements.

The input unit 61 is composed of hardware capable of inputting various information such as commands and set values according to the user's operation. Specific examples of the input unit 61 include a mouse, a keyboard, a portable semiconductor memory connector, a communication interface for exchanging information via network communication or serial communication, and the like. Examples of the semiconductor memory include a USB (Universal Serial Bus) memory and a CF (Compact Flash) memory.

The storage unit 62 is composed of hardware that stores data given from the input unit 61 or the control unit 64 and can read the stored data. Specific examples of the storage unit 62 include magnetic disks represented by HD (Hard Disk), semiconductor memories, optical disks, and the like.

The storage unit 62 includes a first storage area for storing various programs, a second storage area for storing various data such as setting data input from the input unit 61, and an expansion for developing the program and data. Areas and are included. In the first storage area of the present embodiment, an analysis program for executing a process for analyzing the components of blood or interstitial fluid is stored.

The display unit 63 is composed of hardware that displays information shown in the data given by the control unit 64. Specific examples of the display unit 63 include a liquid crystal display, an EL (Electro Luminescence) display, a plasma display, and the like.

The control unit 64 is composed of a program stored in the first storage area of the storage unit 62 and hardware that controls the analyzer 6 based on the data stored in the second storage area of the storage unit 62. .. Specific examples of the control unit 64 include chip components having a CPU (Central Processing Unit), a ROM (Read On Memory), and a RAM (Random Access Memory).

When the control unit 64 reads the analysis program stored in the first storage area of the storage unit 62, the control unit 64 expands the read analysis program in the expansion area of the storage unit 62. In this case, the control unit 64 functions as a spectrum acquisition unit 71, a conversion unit 72, a prediction unit 73, an extraction unit 74, a concentration detection unit 75, and a notification unit 76, and analyzes components contained in blood or interstitial fluid. Execute the process.

The spectrum acquisition unit 71 drives the light source 2 by appropriately adjusting set values such as the intensity of the excitation light emitted from the light source 2, and irradiates the blood or interstitial fluid arranged in the predetermined arrangement region with the excitation light. Further, the spectrum acquisition unit 71 acquires Raman spectrum data showing the intensity distribution of Raman scattered light generated from blood or interstitial fluid for each wavelength by irradiation with excitation light from the spectroscope 5.

The conversion unit 72 converts the wavelength of the Raman spectrum into a wave number called a Raman shift amount, based on the data acquired by the spectrum acquisition unit 71. Specifically, each wavelength in the Raman spectrum is converted into a wave number which is the number of waves included in a unit length, and each converted wave number is a Raman shift which is a difference from the wave number of the excitation light emitted from the light source 2. Converted to quantity. As a result, for example, a Raman spectrum having an intensity on the vertical axis and a wavelength on the horizontal axis becomes a Raman spectrum having an intensity on the vertical axis and a Raman shift amount on the horizontal axis.

It is known that a substance has a peculiar vibration energy according to its structure, and the Raman shift amount has a peculiar waveform reflecting the structure of the substance. Therefore, in the Raman spectrum, spectral waveforms corresponding to each of a plurality of substances existing in blood or interstitial fluid, which is a sample SPL, are mixed.

The prediction unit 73 is derived from the first intensity derived from the substance to be detected included in the peak of a predetermined wave number in the Raman spectrum and the other substance belonging to the same metabolic pathway as the metabolic pathway to which the substance to be detected is included in the peak. Of the second intensity of the above, the second intensity is predicted. Metabolic pathways are chemical reactions that occur in a chain within a cell. This metabolic pathway includes starting materials, end products, and multiple intermediates produced between the starting and end products.

In the present embodiment, glucose, which is a starting substance of glycolysis, which is one of the typical metabolic pathways, is a substance to be detected. In addition, lactic acid, which is the final product under anaerobic conditions in the same glycolysis system as glucose, is another substance to be predicted.

As described above, the Raman spectrum contains a mixture of spectral waveforms corresponding to each of a plurality of substances present in blood or interstitial fluid. Therefore, in the Raman spectrum converted by the conversion unit 72, a glucose spectrum waveform corresponding to glucose and a lactic acid spectrum waveform corresponding to lactic acid belonging to the same glycolytic system as the glucose are mixed.

The glucose spectrum waveform has multiple peaks, each of which appears uniquely in different wavenumbers. In this glucose spectral waveform, a peak appearing in the specific wave number of 904cm ^-1 is liable to be a value reflecting a more concentration of glucose compared to the peak appearing in specific other wavenumber than wavenumber of 904cm ^-1. On the other hand, the lactate spectrum waveform also has a plurality of peaks, and each of these peaks appears peculiarly to a wave number other than the wave number of ^{904 cm -1.}

However, most of the lactate spectral waveforms overlap so as to be buried in the glucose spectral waveform. Therefore, in the Raman spectrum in which the glucose spectrum waveform and the lactate spectrum waveform are mixed, the ^{peak appearing at a wave number of 904 cm -1} is the first intensity derived from glucose and the second intensity derived from lactic acid belonging to the same glycolysis system as glucose. And will be included. Further, the first intensity and the second intensity cannot be directly grasped from the intensity of the peak at the wave number ^{of 904 cm -1 in the Raman spectrum, and are unknown.}

In the prediction unit 73 of the present embodiment, the second intensity derived from lactic acid contained in the wave number of ^{904 cm -1 is predicted.} For example, the data of the lactate calibration curve input from the input unit 61 is stored in the second storage area of the storage unit 62. As shown in FIG. 3, this lactic acid calibration curve shows the relationship between the intensity and the concentration (mg / dl) of lactic acid for each of a plurality of wave numbers in which a peculiar peak appears in the lactic acid spectrum waveform. The wavenumbers are specifically 826 cm ^-1 , 1046 cm ^-1 , 1082 cm ^-1 , 1130 cm ^-1 , 1418 cm ^-1 , 1458 cm ^-1 , 1730 cm ^-1 and 2940 cm ^-1 . Among the peaks appearing in these wave numbers, the peak appearing in ^{the wave number of 826 cm -1} does not overlap with the spectrum waveforms other than the lactate spectrum waveform and appears in an isolated state.

The prediction unit 73 ^{recognizes the intensity of the peak peculiar to the lactate spectrum waveform appearing in the wave number of 826 cm -1} , and uses the data of the lactate calibration curve stored in the storage unit 62 to correspond to the intensity of the recognized peak. The concentration of lactic acid (mg / dl) is detected.

When the prediction unit 73 detects the concentration of lactic acid (mg / dl), the prediction unit 73 predicts the intensity of each peak peculiar to the lactic acid spectrum waveform by a multivariate analysis method based on the concentration of lactic acid (mg / dl). .. Specifically, a linear equation is established for each of the above wavenumbers based on the lactate calibration curve. For example, when the concentration of lactic acid (mg / dl) is X and the intensity of lactic acid is Y, the concentration (mg / dl) and intensity of lactic acid appearing at ^{826 cm -1 are expressed by the following formula (1), 1046 cm.} The concentration (mg / dl) and intensity of lactic acid appearing in ^{-1 are expressed by the following formula (2).} Also, the strength and the concentration of lactic acid appearing at 1082cm ^-1 (mg / dl) is expressed by the following equation (3), the strength and the concentration of lactic acid appearing at 1130 cm ^-1 (mg / dl) the following equation (4) The concentration (mg / dl) and intensity of lactic acid appearing ^{in 1418 cm -1} are represented by the following formula (5). Furthermore, the strength and the concentration of lactic acid appearing at 1458cm ^-1 (mg / dl) is expressed by the following equation (6), the strength and the concentration of lactic acid appearing at 1730 cm ^-1 (mg / dl) following equation (7) The concentration (mg / dl) and intensity of lactic acid appearing ^{in 2940 cm -1} are represented by the following formula (8).

X = Y / 1.7736 ・ ・ ・ (1)
X = Y / 0.6198 ・ ・ ・ (2)
X = Y / 0.5364 ・ ・ ・ (3)
X = Y / 0.3448 ・ ・ ・ (4)
X = Y / 0.5057 ・ ・ ・ (5)
X = Y / 1.098 ・ ・ ・ (6)
X = Y / 0.6747 ・ ・ ・ (7)
X = Y / 0.7464 ・ ・ ・ (8)

Next, the above equations (1) to (8) are substituted into the following multivariate analysis equations (9), and the right side of the above equations (1) to (8) is multiplied by the corresponding coefficients c1 to c8. Coefficients c1 to c8 are determined so that the sum of the sums most closely resembles the concentration of lactic acid (mg / dl) detected in advance. Thereby, the intensity Y of each peak peculiar to the lactate spectrum waveform can be calculated.

X = c1 × Y / 1.7736 ＋ c2 × Y / 0.6198 ＋ c3 × Y / 0.5364 ＋ c4 × Y / 0.3448 ＋ c5 × Y / 0.5057 ＋ c6 × Y / 1.098 ＋ c7 × Y / 0.6747 ＋ c8 × Y / 0.7464 ・ ・ ・ (9)

When the prediction unit 73 calculates the intensity of each peak peculiar to the lactate spectrum waveform, the prediction unit 73 generates a lactate spectrum waveform in which the distance from each peak is minimized. By generating this lactic acid spectrum waveform, the second intensity derived from lactic acid contained in the peak of the wave number of ^{904 cm -1 in} the Raman spectrum in which the glucose spectrum waveform and the lactic acid spectrum waveform coexist can be obtained.

As described above, the prediction unit 73 of the present embodiment detects the concentration of lactic acid based on the intensity of the peak peculiar to the lactic acid spectrum waveform that appears in isolation without overlapping with other spectrum waveforms, and determines the detected concentration of lactic acid. Based on this, the second intensity derived from lactic acid can be predicted.

The prediction unit 73 displays the lactic acid spectrum waveform generated as described above on the display screen of the display unit 63, and deforms the lactic acid spectrum waveform according to the coefficients c1 to c8 input from the input unit 61. It may be. In this way, the prediction unit 73 displays the lactate spectrum waveform deformed in response to the input from the input unit 61 on the display screen in real time, and the lactate spectrum waveform approximates each peak peculiar to the lactate spectrum waveform. Can be decided.

The extraction unit 74 extracts the first intensity derived from glucose contained in the peak of a predetermined wave number in the Raman spectrum based on the second intensity derived from lactic acid predicted by the prediction unit 73. For example, although not shown here, a glucose calibration curve showing the relationship between glucose intensity and concentration for each of a plurality of wave numbers in which a peculiar peak appears in the glucose spectrum waveform is similar to the lactate calibration curve data shown in FIG. Data is stored in the storage unit 62. The glucose calibration curve data is input from the input unit 61 and stored in the second storage area of the storage unit 62.

The extraction unit 74 reads out the glucose calibration curve data from the storage unit 62, and uses the glucose calibration curve to generate a glucose spectrum waveform in the same manner as the prediction unit 73. Then, the extraction unit 74 subtracts the intensity of the lactic acid spectrum waveform generated by the prediction unit 73 for each wave number from the intensity of the generated glucose spectrum waveform to generate a new glucose spectrum waveform. ^{The intensity of the peak appearing at 904 cm -1} of the new glucose spectrum waveform is approximately the same as the first intensity derived from the substance to be detected.

As described above, the extraction unit 74 of the present embodiment generates a glucose spectrum waveform based on the Raman spectrum, and subtracts the lactic acid spectrum waveform generated by the prediction unit 73 from the glucose spectrum waveform for each wave number to obtain glucose. The first intensity of origin can be extracted.

The extraction unit 74 compares the second intensity derived from lactic acid predicted by the prediction unit 73 with a predetermined threshold value, and if the second intensity is less than the predetermined threshold value, 904 cm ^{-1 in the Raman spectrum.} The intensity of the peak of may be extracted. ^{For example, the extraction unit 74 recognizes the intensity at a wave number of 904 cm -1} from the lactic acid spectrum waveform generated by the prediction unit 73 as the second intensity derived from lactic acid. When the second intensity is less than a predetermined threshold value, the degree to which the second intensity affects as an error is small. In this case, the extraction unit 74 acquires the Raman spectrum converted by the conversion unit 72 without generating the glucose spectrum waveform. Then, the extraction unit 74 extracts the intensity of the peak ^{of 904 cm -1 in the Raman spectrum.} In this way, the extraction unit 74 can change the extraction process according to the comparison result between the second intensity derived from lactic acid predicted by the prediction unit 73 and the predetermined threshold value.

The concentration detection unit 75 detects the glucose concentration based on the intensity extracted by the extraction unit 74. In the case of the present embodiment, the concentration detection unit 75 detects the intensity of the peak appearing at ^{904 cm -1 in the glucose spectrum waveform newly generated by the extraction unit 74.} Then, the concentration detection unit 75 detects the glucose concentration corresponding to the detected intensity by using the glucose calibration curve.

When the extraction unit 74 extracts ^{the intensity of the peak of 904 cm -1 in} the Raman spectrum as described above, the concentration detection unit 75 detects the glucose concentration corresponding to the intensity using the glucose calibration curve.

As described above, the concentration detection unit 75 of the present embodiment can detect the glucose concentration based on the intensity extracted by the extraction unit 74.

The notification unit 76 notifies the degree of risk of developing diabetes according to the concentration of lactic acid. For example, setting data indicating a normal range of lactic acid concentration and a concentration threshold value larger than the upper limit of the normal range is stored in the storage unit 62. The data of the normal range of the lactic acid concentration and the concentration threshold value are input from the input unit 61 and stored in the second storage area of the storage unit 62.

The notification unit 76 recognizes the concentration of lactic acid detected by the prediction unit 73, and also recognizes the normal range and the concentration threshold value shown in the data read from the second storage region.

Then, when the concentration of lactic acid detected by the prediction unit 73 is within the normal range, the notification unit 76 displays on the display unit 63 in a predetermined display format that the risk of developing diabetes is low. Display on the screen. Further, the notification unit 76 indicates that the risk of developing diabetes is medium risk when the concentration of lactic acid detected by the prediction unit 73 is larger than the upper limit of the normal range and within the range below the concentration threshold. It is displayed on the display screen of the display unit 63 in a predetermined display format. Further, the notification unit 76 displays on the display unit 63 in a predetermined display format that the risk of developing diabetes is high when the concentration of lactic acid detected by the prediction unit 73 is equal to or higher than the concentration threshold value. Display on the screen.

As described above, the notification unit 76 of the present embodiment can notify the risk of developing diabetes according to the concentration of lactic acid.

At least one of the concentration of lactic acid detected by the prediction unit 73, the lactic acid spectrum waveform generated by the prediction unit 73, the glucose intensity corrected by the extraction unit 74, and the glucose spectrum waveform generated by the extraction unit 74 is. It may be displayed along with the risk of developing diabetes. In addition, at least one of the risk of developing diabetes, the concentration of lactic acid detected by the prediction unit 73, and the intensity of glucose corrected by the extraction unit 74 is output by voice in addition to or instead of the display. You may.

<Analysis method>
Next, the analysis method by the above-mentioned analyzer 6 will be described. The analysis method of the present embodiment is executed by the control unit 64 that develops the analysis program in the expansion area of the storage unit 62. FIG. 4 is a flowchart showing an analysis method.

As shown in FIG. 4, the control unit 64 starts the analysis process by expanding the analysis program to the expansion area of the storage unit 62 at the time when the execution command for component analysis is given from the input unit 61, for example. Proceed to the spectrum acquisition step SP1.

In the spectrum acquisition step SP1, the control unit 64 drives the light source 2 by appropriately adjusting the intensity of the excitation light emitted from the light source 2, and causes the blood or interstitial fluid to be irradiated with the excitation light. Then, the spectrum acquisition unit 71 acquires Raman spectrum data indicating the intensity distribution of Raman scattered light generated from blood or interstitial fluid for each wavelength by irradiation with excitation light from the spectroscope 5, and then proceeds to wave number conversion step SP2.

In the wave number conversion step SP2, the control unit 64 converts the wavelength of the Raman spectrum acquired in the spectrum acquisition step SP1 into a wave number called a Raman shift amount, and proceeds to the prediction step SP3.

In the prediction step SP3, the control unit 64 has a second intensity of the first intensity derived from glucose contained in the peak of the wave number ^{of 904 cm -1 in the Raman spectrum and the second intensity derived from the lactic acid intensity contained in the peak.} Predict. For example, as described above, the control unit 64 detects the concentration of lactic acid based on the intensity of the peak peculiar to the lactic acid spectral waveform that appears in isolation without overlapping with other spectral waveforms. Then, the control unit 64 detects the intensity of each of the plurality of peaks peculiar to the lactic acid spectrum waveform by multivariate analysis based on the concentration of lactic acid. After that, the control unit 64 predicts the second intensity derived from the lactic acid intensity by generating a lactic acid spectrum waveform that minimizes the distance from each peak, and proceeds to the extraction step SP4.

In the extraction step SP4, the control unit 64 extracts the first intensity derived from glucose contained in the peak of the wave number of ^{904 cm -1 in} the Raman spectrum based on the second intensity derived from the lactic acid intensity predicted in the prediction step SP3. .. For example, as described above, the control unit 64 uses the glucose calibration curve to execute the same arithmetic processing as in the case of generating the lactate spectrum waveform to generate the glucose spectrum waveform. Then, the control unit 64 subtracts the intensity of the lactic acid spectrum waveform from the intensity of the glucose spectrum waveform for each wave number to generate a new glucose spectrum waveform. By generating this new glucose spectrum waveform, the control unit 64 extracts the first intensity derived from glucose contained in the peak of the wave number of ^{904 cm -1 in the Raman spectrum, and proceeds to the concentration detection step SP5.}

In the concentration detection step SP5, the control unit 64 detects the glucose concentration based on the intensity extracted in the extraction step SP4. For example, as described above, the control unit 64 recognizes the intensity of the peak appearing in the wave number of ^{904 cm -1} in the new glucose spectrum waveform generated in the extraction step SP4. Then, the control unit 64 detects the glucose concentration corresponding to the intensity of the recognized peak using the glucose calibration curve, and proceeds to the notification step SP6.

In the notification step SP6, the control unit 64 notifies the degree of risk of developing diabetes according to the concentration of lactic acid. For example, as described above, the control unit 64 recognizes the concentration of lactic acid detected in the prediction step SP3. Then, the control unit 64 detects the risk of developing diabetes based on the recognized concentration of lactic acid and the normal range and concentration threshold value stored in advance in the storage unit 62, notifies the risk, and then performs an analysis process. finish.

In the extraction step SP4, the control unit 64 compares the second intensity derived from lactic acid predicted in the prediction step SP3 with a predetermined threshold value, and if the second intensity is less than the predetermined threshold value, Raman The intensity of the 904 cm ^-1 peak in the spectrum may be extracted. In this case, in the concentration detection step SP5, the control unit 64 detects the concentration of glucose corresponding to the intensity of the peak ^{of 904 cm -1 in the Raman spectrum by using the glucose calibration curve.}

As described above, the analyzer 6 of the present embodiment includes a prediction unit 73, an extraction unit 74, and a concentration detection unit 75. The prediction unit 73 includes the first intensity derived from glucose contained in the peak of the wave number ^{of 904 cm -1 in} the Raman spectrum showing the intensity distribution of the Raman scattered light generated in blood or interstitial fluid for each wave number, and the lactic acid contained in the peak. Of the second strength of origin, the second strength is predicted. The extraction unit 74 extracts the glucose-derived first intensity contained in the peak of the wave number ^{of 904 cm -1 in} the Raman spectrum based on the lactic acid-derived second intensity predicted by the prediction unit 73. The concentration detection unit 75 detects the glucose concentration based on the intensity extracted by the extraction unit 74.

According to this analyzer 6, even if ^{the second intensity derived from lactic acid contained in the peak of the wave number of 904 cm -1 in} the Raman spectrum is unknown, the unknown second intensity is predicted and the intensity of the peak is predicted. The first intensity derived from glucose can be extracted by removing the second intensity from. Therefore, the concentration can be detected directly from the first intensity derived from glucose. Therefore, even when the second intensity derived from lactic acid contained in the peak of the wave number of 904 cm ^{-1 in the Raman spectrum is high, the glucose concentration can be approximated to the actual concentration.} In this way, the analyzer 6 of the present embodiment can improve the reliability of the analysis result.

Also, the prediction unit 73 of the present embodiment, the concentration of lactic acid from the intensity of peaks characteristic of lactic spectrum waveforms appearing in isolation without overlapping with other spectrum wave number of different 826 ^-1 and a wavenumber of 904Cm ^-1 Is detected, and the second intensity derived from lactic acid is predicted based on the detected concentration.

Therefore, even when the concentration of another substance is likely to fluctuate in blood or interstitial fluid, the unknown second intensity derived from lactic acid can be predicted in a state reflecting the concentration.

Further, as described above, the extraction unit 74 of the present embodiment extracts the intensity of the peak of the wave number ^{of 904 cm -1 in} the Raman spectrum when the second intensity derived from lactic acid is less than a predetermined threshold value. Can be configured.

In this way, even if ^{the intensity of the peak of the wave number of 904 cm -1 in} the Raman spectrum is simply extracted, the degree to which the second intensity derived from lactic acid affects as an error becomes small. Therefore, even when the degree of influence of the second intensity as an error is small, the first intensity derived from glucose is uniformly extracted by removing the second intensity derived from lactic acid from the intensity of the peak of ^{904 cm -1.} Compared with the case, the processing load of the extraction unit 74 can be reduced.

Further, in the case of the present embodiment, a notification unit 76 for notifying the risk of developing diabetes is provided according to the concentration of lactic acid.

As mentioned above, the blood of people in the pre-diabetic stage tends to have increased levels of lactic acid. Therefore, it is possible to promote the prevention of diabetes by notifying the risk of developing diabetes according to the concentration of lactic acid.

The above embodiment is an example of the present invention and can be modified without departing from the spirit of the present invention.

For example, in the above embodiment, the prediction unit 73 predicts the second intensity derived from lactic acid contained in the wave number ^{of 904 cm -1 in} the Raman spectrum by generating the lactic acid spectrum waveform based on the Raman spectrum. It may be predicted by the method of. For example, a ^{plurality of known values different from each other are prepared as the intensities of peaks appearing in a wave number of 904 cm -1 in} the Raman spectrum, and the second intensity derived from lactic acid measured for each of these values is stored in the storage unit 62 as a database. deep. ^{In this way, the prediction unit 73 detects the intensity of the peak appearing in the wave number of 904 cm -1 in} the Raman spectrum converted by the conversion unit 72, and detects the second intensity derived from lactic acid by referring to the database. obtain.

Further, in the above embodiment, the wave number of the intensity of lactic acid predicted by the prediction unit 73 was set to 904 cm ^-1 . However, this wavenumber may be other than the wavenumber of ^{904 cm -1} as long as the wavenumber in which a peak peculiar to the glucose spectrum waveform appears. However, as described above, the value in the glucose spectrum waveform, peak appearing in specific wave number of 904cm ^-1 is reflecting the concentration of more glucose than the peak appearing in specific other wavenumber than wave number of 904cm ^-1 It is easy to become. Therefore, it is preferable that the wave number of the intensity of lactic acid predicted by the prediction unit 73 is 904 cm ^-1.

Further, in the above embodiment, the notification unit 76 for notifying the risk of developing diabetes according to the concentration of lactic acid is provided, but the notification unit 76 may be omitted. When the notification unit 76 is omitted, the above notification step SP6 is also omitted.

Further, in the above embodiment, glucose, which is a starting substance of glycolysis, was applied as a substance to be detected. In addition, lactic acid, which is the final product of glycolysis, was applied as another substance belonging to the same metabolic pathway as the substance to be detected. However, as long as it belongs to glycolysis, a substance other than glucose may be applied as a substance to be detected, and a substance other than lactic acid may be applied as another substance. Even if a substance other than glucose and lactic acid is applied, a peak peculiar to the spectral waveform corresponding to the substance to be detected appears at a predetermined wave number in the Raman spectrum by executing the same treatment as in the case described in the above embodiment. The second intensity derived from other substances contained in can be predicted. Further, based on the predicted second intensity, the first intensity derived from the substance to be detected contained in the peak appearing at a predetermined wave number in the Raman spectrum can be extracted, and the concentration of the detection target can be detected. Therefore, the concentrations of various substances belonging to glycolysis can be detected in a state that approximates the actual concentration. Therefore, highly reliable information can be provided as an index for detection and treatment of glucose metabolism disorders.

Furthermore, if the substance to be detected and other substances belong to the same metabolic pathway, a metabolic pathway other than glycolysis may be applied. For example, when a fat metabolic pathway such as β-oxidation or a lipid synthesis system is applied, the concentrations of various substances belonging to the fat metabolic pathway can be detected in a state close to the actual concentration as described above. Therefore, highly reliable information can be provided as an index for the detection and treatment of abnormal lipid metabolism such as hyperlipidemia. Further, when a protein metabolic pathway such as a urea cycle or an amino acid-degrading system is applied, the concentrations of various substances belonging to the protein metabolic pathway can be detected in a state close to the actual concentration as described above. Therefore, highly reliable information can be provided as an index for finding and treating abnormal protein metabolism such as renal failure, uremia, and gout.

When a substance highly dependent on metabolic abnormalities is used as the substance to be detected, the concentration in blood or interstitial fluid fluctuates according to the metabolic abnormality, and the substance to be detected corresponds to the fluctuation. It is considered useful that a substance having a second intensity that increases or decreases at a peak peculiar to the spectrum waveform to be metabolized is another substance.

Further, in the above embodiment, blood collected from a person was adopted as the sample SPL to be irradiated with the excitation light. However, the sample SPL irradiated with the excitation light may be blood flowing through the human body. When the blood flowing through the human body is used as the sample SPL, for example, the control unit 64 controls the optical system of the irradiation unit 3 to change the depth of the laser with respect to the human body, depending on the presence or absence of blood components obtained at the depth. , The focus should be on the blood vessels in the human body. Further, although human blood is used as the sample SPL, it can be applied to living organisms other than humans such as animals.

Further, in the above embodiment, the sample SPL is irradiated with excitation light having a single wavelength with respect to the sample SPL. However, as illustrated in FIG. 5, the sample SPL may be irradiated with the first laser beam and the second laser beam having different wavelengths from each other. In the analysis system 100 of FIG. 5, for example, a first light source 21 that emits pump light which is a pulsed laser light of 1064 nm and a second light source 22 that emits Stokes light which is a pulsed laser light of 1100 nm are provided. .. The pump light emitted from the first light source 21 reaches the dichroic mirror DM through the light delay device 31. The optical delayer 31 changes the optical path length, for example, to match the irradiation timing of the pump light with the Stokes light. The Stokes light emitted from the second light source 22 reaches the dichroic mirror DM via the mirror M. In the dichroic mirror DM, the pump light and the Stokes light are superposed, and the superposed pump light and the Stokes light are condensed and irradiated on the sample SPL. This irradiation produces CARS (Coherent Anti-Stokes Raman Scattering) light having a wavelength different from that of the Stokes light in the sample SPL, which is different from the wavelength of the pump light. The CARS light generated in the sample SPL passes through the optical filter 42 of the Raman light propagation unit 4 and reaches the spectroscope 5. The optical filter 42 is a filter that cuts stray light other than CARS light. The CARS light that has reached the spectroscope 5 is divided by wavelength by the diffraction lattice 51, and Raman spectrum data showing the intensity distribution of the CARS light for each wavelength is output from the spectroscope 5. Each wavelength in this Raman spectrum is converted by the conversion unit 72 into a wave number which is the number of waves included in the unit length. However, it does not have to be converted into the Raman shift amount.

Summarizing the above, the analyzer 6 of the present invention is as follows. That is, the analyzer 6 includes a prediction unit 73, an extraction unit 74, and a concentration detection unit 75. The prediction unit 73 includes the first intensity derived from the substance to be detected included in the peak of a predetermined wave number in the Raman spectrum showing the intensity distribution of the Raman scattered light generated in blood or interstitial fluid for each wave number, and the peak thereof. Among the second intensities derived from other substances belonging to the same metabolic pathway as the metabolic pathway to which the substance to be detected belongs, the second intensity is predicted. The extraction unit 74 extracts the first intensity included in the peak of a predetermined wave number in the Raman spectrum based on the second intensity predicted by the prediction unit 73. The concentration detection unit 75 detects the concentration of the substance to be detected based on the intensity extracted by the extraction unit 74.

According to such an analyzer 6, even if the second intensity derived from another substance contained in the peak of a predetermined wave number is unknown, the unknown second intensity is predicted and the second intensity peaks. The first intensity derived from the substance to be detected can be extracted so as to be excluded from the intensity of. Therefore, when the intensity derived from another substance is high, the concentration can be detected directly from the first intensity derived from the substance to be detected. Therefore, even when the intensity derived from other substances contained in the peak of a predetermined wave number is high, the concentration of the substance to be detected can be approximated to the actual concentration.

The present invention may be used in the medical industry and the like.

1 ... analysis system, 2 ... light source, 3 ... irradiation unit, 4 ... Raman light propagation unit, 5 ... spectroscope, 6 ... analyzer, 61 ... input unit, 62 ... Storage unit, 63 ... Display unit, 64 ... Control unit, 71 ... Spectrum acquisition unit, 72 ... Conversion unit, 73 ... Prediction unit, 74 ... Extraction unit, 75 ... concentration detection unit, 76 ... notification unit, SPL ... sample.

Claims (11)

The first intensity derived from glucose contained in the peak of a predetermined wave number in the Raman spectrum showing the intensity distribution for each wave number of Raman scattered light generated by irradiating a sample which is blood or an interstitial liquid with excitation light of a single wavelength. Of the second intensity derived from lactic acid contained in the peak and belonging to the same metabolic pathway as the glucose to which the glucose belongs, a prediction unit for predicting the second intensity.
An extraction unit that extracts the first intensity included in the peak of the predetermined wave number based on the second intensity predicted by the prediction unit.
A concentration detection unit that detects the glucose concentration based on the intensity extracted by the extraction unit, and a concentration detection unit.
Equipped with a,
Unlike the predetermined wave number, the prediction unit detects the concentration of the lactic acid from the peak intensity peculiar to the lactic acid that appears in isolation without overlapping with other waveforms, and the second intensity is based on the detected concentration. An analyzer characterized in predicting. The analysis according to claim 1, wherein the extraction unit extracts the intensity at the peak of the predetermined wave number including the first intensity when the second intensity is less than a predetermined threshold value. apparatus. The analyzer according to claim 1 , further comprising a notification unit that notifies the degree of risk of developing diabetes according to the concentration of lactic acid. Further provided with a storage unit for storing data of a lactic acid calibration curve showing the relationship between the concentration of lactic acid and the peak intensity at a peak peculiar to lactic acid that appears in isolation without overlapping with the other waveforms.
The prediction unit detects the concentration of lactic acid using the data of the lactic acid calibration curve of the storage unit.
The analyzer according to any one of claims 1 to 3, wherein the analyzer is characterized by the above. The storage unit stores data of a lactic acid calibration curve showing the relationship between the concentration of lactic acid and the peak intensity for each wave number in which a peculiar peak appears in the lactic acid spectrum showing the Raman spectrum of lactic acid.
The prediction unit generates a lactic acid spectrum waveform based on the lactic acid calibration curve for each wave number in which a peculiar peak appears in the lactic acid spectrum and the detected concentration of lactic acid, and the second intensity is based on the lactic acid spectrum waveform. Predict
The analyzer according to claim 4. The storage unit stores data of a glucose calibration curve showing the relationship between the glucose concentration and the peak intensity for each wave number in which a peculiar peak appears in the glucose spectrum showing the Raman spectrum of glucose.
The extraction unit forms a glucose spectrum waveform using the data of the glucose calibration curve, and extracts the first intensity from the glucose spectrum waveform.
The analyzer according to claim 5. The concentration detection unit detects the glucose concentration using the data of the glucose calibration curve.
The analyzer according to claim 6. The wave number of the peak peculiar to lactic acid that appears in isolation without overlapping with the other waveforms is 826 cm. ^-1 Is
The analyzer according to any one of claims 1 to 7, wherein the analyzer is characterized by the above. The predetermined wave number is 904 cm. ^-1 Is
The analyzer according to claim 8. The first intensity derived from glucose contained in the peak of a predetermined wave number in the Raman spectrum showing the intensity distribution for each wave number of Raman scattered light generated by irradiating a sample which is blood or an interstitial liquid with excitation light of a single wavelength. And the prediction step of predicting the second intensity among the second intensity derived from lactic acid contained in the peak and belonging to the same metabolic pathway as the metabolic pathway to which the glucose belongs.
An extraction step of extracting the first intensity included in the peak of the predetermined wave number based on the second intensity predicted in the prediction step.
A concentration detection step that detects the glucose concentration based on the intensity extracted in the extraction step, and a concentration detection step.
With
In the prediction step, unlike the predetermined wave number, the concentration of the lactic acid is detected from the peak intensity peculiar to the lactic acid that appears in isolation without overlapping with other waveforms, and the second intensity is based on the detected concentration. Predict
An analysis method characterized by that. A notification step for notifying the risk of developing diabetes is further provided according to the concentration of lactic acid.
The analysis method according to claim 10.

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