Evaluation system and evaluation method

Abstract

To provide a novel evaluation system and evaluation method for evaluating the state of a cell.SOLUTION: Provided is an evaluation system having: a Raman spectroscopic device for performing Raman spectroscopic analysis on extracellular vesicles contained in a cell culture supernatant; and an analysis device for evaluating the state of a cell based on the Raman spectrum obtained by the Raman spectroscopic analysis.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an evaluation system and an evaluation method. [Background technology]

[0002] Cell culture is generally performed manually by technicians in clean rooms called cell processing centers (CPCs).Manual culture, which involves frequent opening and closing of culture vessels, poses a risk of biological contamination, so the development of closed-system automated culture equipment that ensures the sterility of the culture environment is being promoted.

[0003] Cell growth patterns are affected by subtle differences in the number of passages, cell line, and other uncontrolled culture processes. Therefore, monitoring cell status and optimizing culture conditions may lead to better proliferation rates and differentiation induction efficiencies.

[0004] On the other hand, cell status is generally evaluated by collecting cells and measuring the expression levels of specific markers using flow cytometry, quantitative RT-PCR, etc. This method requires cell collection, making it difficult to apply to monitoring.

[0005] A method for assessing the state of living cells involves measuring components in culture supernatants that can be recovered from cell culture systems. For example, WO2015166845A1 (Patent Document 1) describes how "stem cells with unknown differentiation states or cells induced to differentiate from stem cells are used as test cells, and the differentiation state of the test cells is evaluated based on the amount of a predetermined substance present in the culture supernatant of the test cells." Furthermore, US2021-0301248 (Patent Document 2) describes how "the content of exosome markers in the culture supernatant changes in three patterns depending on the process of cell differentiation induction." [Prior art documents] [Patent documents]

[0006] [Patent Document 1] WO2015166845A1 [Patent Document 2] US2021-0301248 Summary of the Invention [Problem to be solved by the invention]

[0007] An object of the present invention is to provide a novel evaluation system and evaluation method for evaluating the state of cells. [Means for solving the problem]

[0008] One embodiment of the present invention is an evaluation system for evaluating the state of a cell, comprising: a Raman spectroscopic device for performing Raman spectroscopic analysis on extracellular vesicles contained in a culture supernatant of the cell; and an analyzer for evaluating the state of the cell based on the Raman spectrum obtained by the Raman spectroscopic analysis. the cells are pluripotent stem cells, dopaminergic neural progenitor cells, ectoderm, or mesoderm, and the state of the cells is a differentiation stage of the cells; and the state of the cells is evaluated using a classifier created based on a pair of the Raman spectrum and data on the state of the cells corresponding to the Raman spectrum. It is a rating system . before The extracellular vesicles may be exosomes. In the Raman spectrum, the peaks of 713±10, 830±10, 858±10, 885±10, 895±10, 919±10, 942±10, 997±10, 1040±10, 1065±10, 1107±10, 1133±10, 1175±10, 1299±10, 1372±10, 1420±10, 1443±10, 1739±10, 2663±10, 2730±10, 2850±10, 2887±10, 2936±10, and 2964±10 cm -1 The state of the cell may be evaluated based on the measurement results in at least one range selected from the group consisting of . table The device may also be equipped with a display device. Another embodiment of the present invention is an automatic culture system comprising any one of the evaluation systems described above and an automatic culture device for culturing the cells. A further embodiment of the present invention is a method for evaluating the state of a cell, comprising: performing Raman spectroscopy on extracellular vesicles isolated from a culture supernatant of the cell; and evaluating the state of the cell based on the Raman spectrum obtained by the Raman spectroscopy. fruit , The cells are pluripotent stem cells, dopamine neural progenitor cells, ectoderm, or mesoderm, and the state of the cells is a differentiation stage of the cells. The state of the cells is evaluated using a classifier created based on a pair of the Raman spectrum and data on the state of the cells corresponding to the Raman spectrum. , an evaluation method . before The extracellular vesicles may be exosomes. In the Raman spectrum, the peaks of 713±10, 830±10, 858±10, 885±10, 895±10, 919±10, 942±10, 997±10, 1040±10, 1065±10, 1107±10, 1133±10, 1175±10, 1299±10, 1372±10, 1420±10, 1443±10, 1739±10, 2663±10, 2730±10, 2850±10, 2887±10, 2936±10, and 2964±10 cm -1 The state of the cells may be evaluated based on the measurement results in at least one range selected from the group consisting of: [Effects of the Invention]

[0009] According to the present invention, a novel evaluation system and evaluation method for evaluating the state of a cell can be provided. Problems, configurations, and effects other than those described above will be described in the following embodiments. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a schematic diagram illustrating a configuration of an evaluation system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a schematic diagram showing a user interface displayed on a display of the evaluation system according to one embodiment of the present invention. [Figure 3] 4 is a control flowchart of an analysis device included in the evaluation system according to one embodiment of the present invention. [Figure 4] 1 is a schematic diagram of an automatic culture system equipped with an automatic culture device according to one embodiment of the present invention. [Figure 5]This is a representative Raman spectrum of an extracellular vesicle fraction isolated from the culture supernatant of iPS cells in one example of the present invention. [Figure 6] FIG. 1 is a scatter plot showing changes in the Raman spectrum of extracellular vesicles isolated from the culture supernatant during the differentiation culture process from iPS cells to dopaminergic neural progenitor cells in one example of the present invention. [Figure 7] FIG. 1 is a scatter plot showing changes in the Raman spectrum of extracellular vesicles isolated from the culture supernatant during the differentiation culture process from iPS cells to ectoderm and mesoderm in one example of the present invention. [Figure 8] FIG. 1 is a scatter plot showing changes in Raman spectra derived from extracellular vesicles isolated from culture supernatant under different culture conditions for iPS cells in one example of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, these embodiments are merely examples for realizing the present invention and do not limit the technical scope of the present invention.

[0012] ==Rating System== 1 is a schematic diagram of an evaluation system 101 according to the present invention. The evaluation system 101 for evaluating the state of a cell includes a Raman spectroscopic device 105 for performing Raman spectroscopic analysis on extracellular vesicles contained in a cell culture supernatant, and an analyzing device 108 for evaluating the state of the cell based on the Raman spectrum obtained by the Raman spectroscopic analysis. The analysis device 108 has a CPU and the like, and the CPU is provided with an input unit 106 for inputting the Raman spectrum obtained by Raman spectroscopic analysis in the Raman spectrometer 105 for inputting the Raman spectrum and data on the state of the cell from which the Raman spectrum was obtained, a memory unit 107 having a database that associates Raman spectra with data on the state of the cell from which the Raman spectrum was obtained and an evaluation program for evaluating the state of the cell based on the Raman spectrum, an analysis unit 110 for evaluating the state of the cell based on the Raman spectrum obtained by Raman spectroscopic analysis, and a control unit 111 that controls the operation of each device of the evaluation system 101. The evaluation system 101 may further include devices such as an extracellular vesicle isolation device 103 for isolating extracellular vesicles from the culture supernatant, a solution discharge device 104 for discharging unnecessary solution, and a display device 109 such as a display for displaying the analysis results. ==Automated Culture System== FIG. 4 is a schematic diagram of an automatic culture system equipped with an automatic culture device (including 401 to 409) and an evaluation system (including 410 to 420). The cell culture medium is supplied to a culture vessel 409 from a culture medium storage container 401 via a solution supply channel 404. The pressure within the culture environment is maintained by an air pressure control channel 402 and an outside air filter 403. The concentrations of various gases in the culture environment are regulated by a gas cylinder 407 and a gas supply channel 406. The movements of the culture medium and gas are regulated by a valve 405 and a pump 408, respectively. The culture supernatant is supplied from the culture vessel 409 to the extracellular vesicle isolation device 411 via a solution waste flow path 410. The extracellular vesicle isolation device 411 receives the culture supernatant at the culture supernatant inlet 102 and isolates extracellular vesicles from the culture supernatant. The isolation method is not particularly limited, and known techniques can be used. The extracellular vesicles are supplied to the Raman spectrometer 413 via a sample flow path 412. The wastewater generated in the extracellular vesicle isolation device 411 and the Raman spectrometer 413 is discarded in a wastewater storage container 414 via a solution waste flow path 420. The terminal 415, which serves as an analytical device and is responsible for device control, data analysis, and data storage, controls various valves, pumps, and devices, and stores and analyzes the Raman spectra obtained by the Raman spectrometer 413. Based on the monitoring results obtained by the terminal 415, the cell culture can be continued, stopped, or conditions can be changed. This decision can be made by an operator or by the analytical device according to preset criteria. ==Control flow by analyzer==

[0013] 2 is a schematic diagram of an example of a user interface displayed on the display device 109. FIG. 3 is a control flowchart of the control unit 111 of the evaluation system 101. First, the operator sets the evaluation conditions (301), for example, by inputting the cell state item 201 and cell type 202 to be evaluated. Preferably, the control unit 111 loads the analysis program stored in the storage unit 107 in accordance with the set evaluation conditions (302) and displays the analysis method 203 and the Raman signal 204 to be analyzed accordingly, but the operator may manually input the analysis method 203 and the Raman signal 204 to be analyzed. Next, the operator sets the measurement conditions (303), for example, by inputting the laser exposure time 205, laser power 206, Raman signal bandwidth 207 to be measured, and number of measurement data 208 when acquiring one spectrum. The control unit 111 supplies (304) the culture supernatant from the culture vessel 409 to the extracellular vesicle isolation device 411. Subsequently, the control unit 111 performs the following control. The extracellular vesicle isolation device 411 that obtained the culture supernatant isolates extracellular vesicles from the culture supernatant (305). The extracellular vesicle isolation device 411 sends the isolated extracellular vesicles to the Raman spectroscopy device 105. The Raman spectroscopy device 105 starts Raman spectroscopy analysis of the extracellular vesicles (306). When data on the number of measurements has been acquired (307), the Raman spectrometer 105 ends the measurement (308) and sends the measurement data to the analyzer 108, which receives the measurement data at the input unit 106 and analyzes it at the analyzer 110. The measurement data may be temporarily stored in the memory unit 107 before analysis. The analyzer 108 sends the results obtained by the analyzer 110 together with the measurement data to the display device 109, which displays the measurement data 209 and results 210 to the operator. The display device 109 may display the analysis results as a percentage of the cell state based on the classification of each measured Raman spectrum.

[0014] ==Cell status evaluation method== In the present invention, the cell state is evaluated based on the Raman spectrum of extracellular vesicles in the culture supernatant. The evaluation method is not particularly limited, but the following method is one example. In the present invention, the cell state can be exemplified by the cell differentiation stage, cell life / death, cell division stage, activation of specific signal transduction, gene introduction, and the like. For example, when the cell state represents the cell differentiation stage, the method for identifying the cell differentiation stage is not particularly limited, and examples include identification based on a specific number of days after the start of differentiation, identification based on the expression of a specific differentiation marker, or identification based on the adoption of a specific cell morphology. The direction of cell differentiation is not particularly limited, and may include differentiation into a specific germ layer such as endoderm, mesoderm, or ectoderm, or differentiation into a specific cell type such as neurons, fibroblasts, epithelial cells, or blood cells. The type of cell to be differentiated is not particularly limited, and examples include undifferentiated cells such as pluripotent stem cells such as iPS cells and ES cells, stem cells such as neural stem cells and mesenchymal stem cells, and progenitor cells such as neural progenitor cells and myeloid progenitor cells. Extracellular vesicles are isolated from cells whose cell state has been previously identified, and their Raman spectral data are used as training data to construct a cell state evaluation program using numerical analysis such as multivariate analysis, machine learning, and deep learning. Specifically, the training data may be the entire or partial waveform of the Raman spectrum, or a characteristic waveform portion. The Raman spectroscopic measurement method is not limited, and examples include spontaneous Raman scattering, surface-enhanced Raman scattering, and nonlinear Raman scattering.

[0015] When using Raman spectra of extracellular vesicles isolated from the culture supernatant of iPS cells and cells differentiated therefrom, the results were 713±10, 830±10, 858±10, 885±10, 895±10, 919±10, 942±10, 997±10, 1040±10, 1065±10, 1107±10, 1133±10, 1175±10, 1299±10, 1372±10, 1420±10, 1443±10, 1739±10, 2663±10, 2730±10, 2850±10, 2887±10, 2936±10, and 2964±10 cm -1 At least one Raman spectrum in a wavelength region selected from the group consisting of:

[0016] Then, Raman spectral data is obtained for the cell whose state is to be evaluated, and Raman spectral analysis is performed in the same manner as for the training data, and the data is entered into the cell state evaluation program, thereby enabling the cell state of the cell to be evaluated. [Example]

[0017] [Example 1] This example demonstrates that the Raman spectral pattern of extracellular vesicles changes during the differentiation of stem cells. Specifically, iPS cell line 201B7 was used and cultured for 12 days to induce differentiation into dopaminergic neural progenitor cells, and the changes in the Raman spectra of extracellular vesicles were evaluated. The conditions for differentiation into dopaminergic neural progenitor cells were as follows (Stem Cell Reports, vol. 2 (2014), pp. 337-350). First, feeder-free iPS cells cultured in StemFit media (Ajinomoto Co.) were treated with TrypLE select for 10 minutes and then dissociated into single cells. Next, 4 × 10 iPS cells were plated onto a 6-well plate coated with LM511-E8. 5 Thin The cells were seeded at a density of 1000 cells / mL and cultured for 4 days until they reached confluence. The medium was then changed to differentiation medium containing GMEM supplemented with 8% KSR, 0.1 mM MEM non-essential amino acids (Invitrogen), sodium pyruvate (Sigma-Aldrich), and 0.1 mM 2-mercaptoethanol, and differentiation induction was initiated. To further induce neural differentiation, LDN193189 (STEMGENT) and A83-01 (Wako) were added to the medium (J. Neurosci. Res., vol. 89 (2011), pp. 117-126).

[0018] The iPS cells were cultured in three wells of a six-well plate to induce differentiation of dopaminergic neural progenitor cells. Culture supernatants were collected from the iPS cells on the day of differentiation induction, and on days 8 (mid-differentiation) and 12 (late differentiation) after differentiation induction. The isolated extracellular vesicle fraction was subjected to Raman spectroscopy using the phosphatidylserine affinity method (Sci Rep., vol. 6 (2016), pp. 33935). For Raman spectrum analysis, the wavenumbers around the signals shown in Figure 5 were 881.0, 883.1, 885.1, 887.2, 889.2, 891.3, 893.3, 895.4, 897.4, 899.5, 909.7, 911.7, 913.8, 915.8, 917.8, 919.9, 921.9, 924.0, 926.0, 928.0, 930.1, 932.1, 934.2, 936.2, 938.2, 940.3, and 942. 3,944.3, 946.4, 948.4, 950.4, 952.5, 986.9, 989.0, 991.0, 993.0, 995.0, 997.1, 999.1, 1001.1, 1003.1, 1005.1, 1007.2, 1029.3, 1031.4, 1033.4, 1035.4, 1037.4, 1039.4, 1041.4, 1043.4, 1045.4, 1047.5, 1049.5, 1055.5, 1057.5, 1059.5 ,1061.5,1063.5,1065.5,1067.5,1069.5,1071.5,1073.5,1075.5,1097.5,1099.5,1101.5,1103.5,1105.5,1107.5,1109.5,1111.5,1113.5,1115.5,1117.5,1123.5,1125.5,1127.5,1129.5,1131.4,1133.4,1135.4,1137.4,1139.4,11 41.4, 1143.4, 1165.2, 1167.2, 1169.2, 1171.1, 1173.1, 1175.1, 1177.1, 1179.1, 1181.0, 1183.0, 1185.0, 1289.1, 1291.1, 1293.0, 1295.0, 1296.9, 1298.9, 1300.8, 1302.8, 1304.7, 1306.7, 1308.6, 1310.6, 1363.0, 1364.9, 1366.8, 1368.8, 1370.7, 1372.6, 1374.6, 1376.5, 1378.4, 1380.4, 1382.3, 1409.3, 1411.2, 1413.1, 1415.0, 1417.0, 1418.9, 1420.8, 1422.7, 1424.6, 1426.6, 1428.5, 1430.4, 1432.3, 1434.2, 1436.2, 1438.1, 1440.0, 1441 .9,1443.8,1445.7,1447.7,1449.6,1451.5,1453.4,1729.9,1731.8,1733.6,1735.5,1737.3,1739.2,1741.0,1742.9,1744.7,1746.6,1748.4,1750.3,2653.3,2654.9,2656.5,2658.2,2659.8,2661.5,266 3.1,2664.7,2666.4,2668.0,2669.7,2671.3,2672.9,2720.2,2721.9,2723.5,2725.1,2726.7,2728.4,2730.0,2731.6,2733.2,2734.9,2736.5,2738.1,2739.7,2839.6,2841.2,2842.8,2844.4,2846.0,28 47.6, 2849.2, 2850.8,, 2852.4, 2854.0, 2855.6, 2857.2, 2858.8, 2860.4, 2876.3, 2877.9, 2879.5, 2881.1, 2882.7, 2884.3, 2885.9, 2887.4, 2889.0, 2890.6, 2892.2, 2893.8, 2895.4, 2897.0, 2925.5, 2927.1. ,2928.7,2930.2,2931.8,2933.4,2935.0,2936.6,2938.1,2939.7,2941.3,2942.9,2944.4,2946.0,2952.3,29 53.9,2955.5,2957.1,2958.6,2960.2,2961.8,2963.3,2964.9,2966.5,2968.1,2969.6,2971.2,2972.8,2974.4 cm -1 was used. Of the three culture wells, measurement data from two wells was used as training data, and one well was used as test data. Using the training data, data features were extracted by independent component analysis, and a classifier was created using logistic regression. In the independent component analysis, the data dimensions were compressed to three dimensions. The dimensions of the independent component analysis used in the classifier and the hyperparameters of the logistic regression were optimized using 10-fold cross validation. As a result of the optimization, the number of dimensions of the independent component analysis used in the classifier was reduced to two. Figure 6 shows a scatter plot of the results of the independent component analysis of all measured spectral data. As shown in the graph in Figure 6, the spectral data were separated for the mid- and late stages of differentiation induction into iPS cells and dopaminergic neural progenitor cells. The analysis was performed using scikit-learn (0.23.1), a Python machine learning library. When the test data was evaluated using the created classifier, the classification accuracy F-measure of the data was 86%. This is what happened. Thus, the composition of extracellular vesicles changes depending on the differentiation state of the cells, and this change is reflected in the Raman spectrum of the extracellular vesicles.

[0019] [Example 2] This example demonstrates that the Raman spectral pattern derived from extracellular vesicles changes even in a differentiation induction system different from that used in Example 1. Specifically, iPS cell line 201B7 was used and cultured to induce differentiation into ectoderm and mesoderm, and changes in the Raman spectrum of extracellular vesicles were evaluated. Differentiation induction into both germ layers was performed using the STEMdiff Trilineage Differentiation Kit (R).

[0020] Differentiation induction culture of iPS cells into ectoderm and mesoderm was performed in two wells of a 6-well plate, and the culture supernatant of iPS cells on the start day of differentiation induction and the culture supernatant on the final day of differentiation induction for each germ layer were collected, and the extracellular vesicles isolated from them were subjected to Raman spectroscopy. Raman spectral analysis was performed in the same manner as in Example 1. Figure 7 shows all the spectral data of iPS cells, ectoderm, and mesoderm. FIG. 10 is a scatter plot of the results of independent component analysis. As shown in the graph in Figure 7, the spectral data for iPS cells and both germ layers tended to separate. Of the two cultured wells, one was used as training data and the other as test data, and the classification accuracy evaluated in the same manner as in Example 1 was 87%. As described above, even in a differentiation induction system different from that of Example 1, the differentiation state of cells can be determined by labeling extracellular vesicles. It can be evaluated by mann spectroscopy.

[0021] [Example 3] In this example, we demonstrate that deviation from the undifferentiated state of stem cells alters the Raman spectra of extracellular vesicles. Specifically, in a culture for expanding iPS cell line 201B7, iPS cells were cultured under standard culture conditions, as well as under conditions in which basic fibroblast growth factor (FGF2), necessary for maintaining the undifferentiated state of iPS cells, was removed from the medium (hereinafter referred to as deviation conditions) to deviate from the undifferentiated state. Both conditions were performed in three wells of a six-well plate. In the deviation conditions, iPS cells were seeded as in Example 1, and on day 3, the medium was replaced with one from which FGF2 had been removed. For both culture conditions, cells and culture supernatants were collected on day 7 after the start of culture. Expression levels of the cell undifferentiation marker Nanog were evaluated by quantitative RT-PCR, and the expression levels under the deviation conditions were significantly lower than those under the standard conditions. Furthermore, Raman spectroscopy and Raman spectral analysis were performed as in Example 1. Figure 8 shows the total spectra under both culture conditions. FIG. 10 is a scatter plot of the results of independent component analysis of torque data. As shown in the graph in Figure 8, the spectral data showed a tendency to separate for each culture condition. The classification accuracy, evaluated in the same manner as in Examples 1 and 2, was 85%. In this way, the undifferentiated state of stem cells can be evaluated using Raman spectra derived from extracellular vesicles. [Explanation of symbols]

[0022] 101: Evaluation device 102:Culture supernatant introduction part 103: Extracellular vesicle isolation device 104:Solution discharge device 105: Raman spectrometer 106: Input section 107: Storage section 108:Analysis equipment 109:Display device 110:Analysis Department 111: Control unit 201: Evaluation items 202: Target cell type 203: Analysis method 204: Analysis signal 205: Exposure time 206: Power 207: Measurement bandwidth 208: Number of measurements 209: Measurement Raman spectrum 210: Analysis results of cell state 401:Culture solution storage container 402: Pressure regulation channel 403: Fresh air filter 404: Solution supply channel 405: Valve 406: Gas supply channel 407: Gas Cylinder 408: Pump 409:Culture container 410: Solution waste flow path 411: Extracellular vesicle isolation device 412: Sample flow path 413: Raman spectrometer 414: Drainage storage container 415: Terminal

Claims

1. An evaluation system for evaluating a state of a cell, comprising: A Raman spectrometer for performing Raman spectroscopic analysis on extracellular vesicles contained in the culture supernatant of the cells; an analyzer for evaluating a state of the cells based on the Raman spectrum obtained by the Raman spectroscopic analysis; and the cell is a pluripotent stem cell, a dopaminergic neural progenitor cell, an ectoderm, or a mesoderm; the state of the cell is a differentiation stage of the cell, An evaluation system that evaluates the state of the cell using a classifier created based on a pair of the Raman spectrum and data on the state of the cell corresponding to the Raman spectrum.

2. The extracellular vesicles are exosomes. The evaluation system of claim 1 .

3. In the Raman spectrum, 713 ± 10, 830 ± 10, 858 ± 10, 885 ± 10, 895 ± 10, 919 ± 10, 942 ± 10, 997 ± 10, 1040 ± 10, 1065 ± 10, 1107 ± 10, 1133 ± 10, 1175 ± 10, 1299 ± 10, 1372 ± 10, 1420 ± 10, 1443 ± 10, 1739 ± 10, 2663 ± 10, 2730 ± 10, 2850 ± 10, 2887 ± 10, 2936 ± 10, 2964 ± 10 cm -1 The state of the cell is evaluated based on the measurement results in at least one range selected from the group consisting of: The evaluation system according to claim 1 or 2.

4. 4. The evaluation system according to claim 1, further comprising a display device.

5. An automatic culture system comprising the evaluation system according to any one of claims 1 to 4 and an automatic culture device for culturing the cells.

6. An evaluation method for evaluating a cell state, comprising: Performing Raman spectroscopy on the extracellular vesicles isolated from the culture supernatant of the cells; evaluating the state of the cells based on the Raman spectrum obtained by the Raman spectroscopic analysis; Including, the cell is a pluripotent stem cell, a dopaminergic neural progenitor cell, an ectoderm, or a mesoderm; the state of the cell is a differentiation stage of the cell, An evaluation method for evaluating the state of the cell using a classifier created based on a pair of the Raman spectrum and data on the state of the cell corresponding to the Raman spectrum.

7. The extracellular vesicles are exosomes. The evaluation method according to claim 6.

8. In the Raman spectrum, 713 ± 10, 830 ± 10, 858 ± 10, 885 ± 10, 895 ± 10, 919 ± 10, 942 ± 10, 997 ± 10, 1040 ± 10, 1065 ± 10, 1107 ± 10, 1133 ± 10, 1175 ± 10, 1299 ± 10, 1372 ± 10, 1420 ± 10, 1443 ± 10, 1739 ± 10, 2663 ± 10, 2730 ± 10, 2850 ± 10, 2887 ± 10, 2936 ± 10, 2964 ± 10 cm -1 The state of the cell is evaluated based on the measurement results in at least one range selected from the group consisting of The evaluation method according to claim 6 or 7.

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