SPR detection system and verification method

Abstract

The invention relates to the technical field of biological detection, in particular to an SPR (Surface Plasmon Resonance) detection system and a verification method. In order to improve the detection effect of the existing SPR detection platform, the invention provides a verification method of an SPR detection system, which comprises the following steps: carrying out SPR detection on a standard sample or / and a control sample, collecting verification spectral data and reference spectral data, calculating to obtain a corresponding differential spectral curve, and carrying out smooth noise reduction treatment on the differential spectral curve to obtain a final detection result. Fitting processing is carried out on the smooth spectrum curve to obtain fitting slopes and correlation coefficients, interference data are eliminated, the remaining fitting slopes are sorted to obtain a sorted spectrum curve, and a wave crest corresponding to the maximum slope and a wave trough corresponding to the minimum slope are determined; the sequencing spectrum curve is subjected to regional integration treatment to obtain a concentration characteristic value related to the concentration of the standard sample, and the detection accuracy and the detection efficiency can be improved when the SPR detection system is detected by adopting the detection method of the SPR detection system disclosed by the invention.

Description

Technical Field

[0001] The present invention relates to the field of biological detection technology, and in particular to an SPR detection system and a detection method. Background Art

[0002] Surface Plasmon Resonance (SPR) is a physical optical phenomenon that occurs at the interface between metal films and dielectrics and is widely used in sensing, especially in the field of biosensing.

[0003] When the dielectric-metal interface of an SPR sensor receives incident light, an evanescent wave (or evanescent wave) forms in the metal film that forms the dielectric-metal interface. This evanescent wave resonates with the surface plasmon waves present in the metal film, causing the intensity of the reflected light detected by the SPR sensor to be significantly weakened, and its phase to change significantly. Therefore, in the signal detected by the SPR sensor, when a sharp resonant absorption peak is generated in the intensity spectrum of the reflected or projected light due to a sharp decrease in light intensity, and the phase of the radiated or projected light also jumps, the corresponding incident light angle or wavelength is called the resonance angle or resonant wavelength. Because the signal detected by the SPR sensor (referred to as the SPR signal) is very sensitive to changes in the properties of the solution to be tested on the surface of the metal film, the SPR sensor is used to detect the intensity or phase spectrum of the reflected or projected light to obtain information such as the refractive index, concentration, and kinetic parameters of the biochemical reaction of the solution to be tested, thereby achieving the purpose of biochemical detection.

[0004] When using SPR sensing technology for biochemical detection, the detection limit of the detection platform using SPR sensing technology is usually reduced by improving the signal-to-noise ratio and correcting the signal offset, thereby improving the SPR detection performance.

[0005] Currently, the industry has developed a variety of SPR signal processing methods, such as centroid detection, polynomial fitting, dynamic baseline compensation, linear analysis, Radon transform, local parameter regression, global response method, characteristic peak shift, fixed peak spectral difference of differential spectrum, and standard differential response method. Among them, centroid detection, polynomial fitting, dynamic baseline compensation, linear analysis, Radon transform, local parameter regression, and global response method are mainly used to reduce noise and obtain higher resolution resonance detection; characteristic peak shift and fixed peak spectral difference of differential spectrum are mainly used to characterize changes in refractive index. Among these SPR signal processing methods, most SPR signal processing methods only use a portion of each spectrum in the SPR signal and simplify this portion of the spectrum into a single parameter, resulting in the discarding of a lot of useful data in the SPR signal, affecting the accuracy of SPR signal analysis and processing. The global response method proposed by Mandira Das et al. and the standard differential response method proposed by ME et al., however, include all information reflected in the SPR signal in the analysis and processing scope, weakening the expression of truly effective information and affecting the accuracy of SPR signal analysis and processing. This shows that, before conducting detection, using the existing SPR signal processing method to calibrate the detection platform will, to a certain extent, limit the performance of the detection platform and affect the detection effect of the detection platform. Summary of the Invention

[0006] In order to improve the detection effect of the existing SPR detection platform, the present invention proposes a detection method of the SPR detection system, which comprises the following steps:

[0007] S1. Use the detection light wave Diw with a wavelength λ value range of [p, q] to perform SPR detection on m standard samples or / and control samples with different concentrations, collect the test spectrum data and reference spectrum data, and obtain the corresponding test spectrum curve and reference spectrum curve And calculate the corresponding differential spectrum curve and

[0008] in,

[0009] C j Represents the jth standard sample A among m standard samples with different concentrations j The concentration of , j is a positive integer and 1≤j≤m,

[0010] λ i represents the i-th wavelength value of the wavelength λ of the detection light wave Diw among the n wavelength values ​​selected sequentially within the value range [p, q], where i is a positive integer and 1≤i≤n;

[0011] Represents the standard sample Aj The corresponding differential spectrum curve;

[0012] Represents the standard sample A j Corresponding test spectrum curve The wavelength value λ i The corresponding test optical density value;

[0013] OD ref (λ i ) represents the corresponding reference spectrum curve when there is a control sample The wavelength value λ i The corresponding reference optical density value;

[0014] Indicates the reference spectrum curve corresponding to the absence of a control sample The wavelength value λ i The corresponding reference optical density value;

[0015] S2, the differential spectrum curve Perform smooth noise reduction processing to obtain the corresponding smooth spectrum curve and

[0016] Among them, f smooth () is the noise reduction algorithm;

[0017] S3, smoothing the spectrum curve Perform fitting processing to obtain the smooth spectrum curve The fitted slope of and the correlation coefficient R 2 (λ i ), remove the data that is less than the set threshold The wavelength value and fitting slope corresponding to the correlation coefficient of , sort the remaining n1' (1≤n1'<n) fitting slopes to obtain a new fitting slope sequence And according to the new fitted slope sequence Get the corresponding new wavelength sequence λ 1' ,λ 2' ,…,λ i' ,…,λ n1' and the corresponding smoothed spectral density value sequence Thus, the standard sample A j Corresponding sorting spectrum curve and And according to the new fitting slope sequence The maximum fitting slope and the minimum fitting slope determine the sorting spectrum curve the peaks and troughs in

[0018] S4, sorting the spectrum curve Perform regional integration processing to obtain the same j The concentration C j Related concentration characteristic values

[0019] In the test method of the SPR detection system of the present invention, the differential spectrum curve is smoothed and denoised to reduce the influence of noise fluctuations on the test accuracy; the smooth spectrum curve obtained by the smooth denoising is fitted and sorted to facilitate the acquisition of the peaks and troughs in the corresponding sorted spectrum curve, to achieve automatic peak finding and improve the test efficiency; the sorted spectrum curve obtained by the fitting and sorting is subjected to regional integration processing to avoid the drawbacks of only focusing on the overall effect and being insensitive to locally important spectral data or only selecting peak and trough data and ignoring other potentially useful information, thereby improving the test accuracy. Therefore, after the SPR detection system is tested by the test method of the SPR detection system of the present invention, for the same detection chip, when the SPR detection system is used to test the test sample of unknown concentration, the concentration characteristic value can be directly calculated by regional integration using the sorted spectrum curve obtained by the previous test. Then, the concentration of the test sample with unknown concentration can be quantitatively obtained, which can not only improve the detection accuracy of the SPR detection system, but also improve the detection efficiency and reduce the detection cost.

[0020] Preferably, in step S2, a moving average algorithm is used as a noise reduction algorithm to reduce the noise of the differential spectrum curve. Perform smooth noise reduction processing to obtain the corresponding smooth spectrum curve and

[0021]

[0022] in,

[0023] Indicates that the standard sample A is detected by the detection light wave Diw. j The wavelength value λ obtained by SPR detection i The corresponding differential optical density value,

[0024] r represents the difference spectrum curve using the moving average algorithm The average number of points used in smoothing and noise reduction processing, r is an integer and r≥1;

[0025] Indicates that the standard sample A is detected by the detection light wave Diw. j The wavelength value λ obtained by SPR detection is i The adjacent r wavelength values ​​λ i+1 ,λ i+2 ,…,λi+r One-to-one corresponding differential optical density values.

[0026] In this way, the moving average algorithm is used as the noise reduction algorithm to smooth and reduce the noise of the differential spectrum curve. By incorporating the surrounding spectral data to calculate the average value, the noise points can be effectively erased, the fluctuation of single-point data can be reduced, and the verification accuracy can be improved.

[0027] Preferably, in step S3, the smoothed spectrum curve When performing the fitting process, the standard sample A j The concentration C j As the independent variable, the standard sample A j The test spectrum curve of The wavelength value λ of the detection light wave Diw i The corresponding smoothed optical density value As the dependent variable, a linear function is established with the wavelength value λ i The corresponding fitting equation is

[0028] in,

[0029] Indicates the standard sample A j The corresponding fitting constant value.

[0030] In this way, linear fitting is adopted, the fitting function is simple, and the fitting is convenient and fast.

[0031] Preferably, the remaining n1' (1≤n1'<n) fitting slopes are sorted in descending order to obtain the sorted spectrum curve

[0032] In this way, the remaining fitting slopes are sorted in descending order, which facilitates the rapid determination of the sorted spectral curve during the verification process. The peaks and troughs in the wave can be detected to improve the verification efficiency.

[0033] Furthermore, the threshold value is set is 0.95. Thus, using the correlation coefficient R 2 (λ i ) setting threshold Eliminate interfering data and improve verification accuracy.

[0034] Preferably, in step S4, the sorting spectrum curve is selected The first N wavelength data and the last M wavelength data are processed by regional integration, and

[0035]

[0036] in,

[0037] N represents the integral range of the peak area,

[0038] M represents the integral range of the trough area,

[0039] I represents the sorting spectrum curve Medium and minimum fitting slope That is, the wavelength value λ corresponding to the trough I The sort number,

[0040] W represents the weight parameter of the peak area, and W=(w0, w1, ..., w N ),

[0041] V represents the weight parameter of the trough area, and V=(v I-M ,…,v I-1 、v I ).

[0042] In this way, when performing regional integration processing on the sorted spectral curve, the weight of the wavelength data used for integration can be adjusted as needed to further improve the verification accuracy.

[0043] In addition, the present invention also proposes an SPR detection system, which is detected by any of the above-mentioned SPR detection system detection methods to obtain the same SPR as the standard sample A. j The concentration C j Related concentration characteristic values

[0044] After the SPR detection system of the present invention is tested by the above-mentioned test method, when the sample to be tested of unknown concentration is tested, the concentration characteristic value can be directly obtained by performing regional integral calculation using the sorted spectrum curve obtained by the test. Furthermore, the concentration of the test sample with unknown concentration can be quantitatively obtained, thereby improving the detection accuracy and detection efficiency of the SPR detection system and reducing the detection cost.

[0045] Preferably, the SPR detection system includes an SPR detection plate, which includes an orifice plate and an SPR chip, wherein the orifice plate is provided with a plurality of through holes, the SPR chip is arranged on one side of the orifice plate and affixed to the bottom of the through holes, and the SPR chip cooperates with the through holes to form a detection hole. Such an SPR detection plate has a simple structure and is easy to manufacture.

[0046] Furthermore, the SPR detection plate is provided with 96 detection wells arranged in a matrix. In this way, the SPR detection plate is provided with multiple detection wells, which facilitates the use of unused detection wells during the detection to detect samples of unknown concentration after the detection, thereby avoiding data interference during the detection, which affects the detection effect of the SPR detection system of the present invention.

[0047] Preferably, the SPR detection system includes a bandwidth light source, a detector and a control computer, and the bandwidth light source is connected to the control computer by a light source control line, and the output end of the bandwidth light source is provided with a guide optical fiber; the detector is connected to the control computer by a signal collection line, and the output head of the detector and the guide optical fiber is relatively arranged on both sides of the detection position for placing the SPR detection plate. Such an SPR detection system is simple in structure and easy to build; in use, it is only necessary to replace the SPR detection plate to detect different types of test samples, and it has a wide range of applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 Schematic diagram of the structure of the SPR detection system of the present invention;

[0049] Figure 2 Flowchart of the assay method of the SPR detection system of the present invention;

[0050] Figure 3 Schematic diagram of the spectrum obtained by the SPR detection system of the present invention for SPR detection of sucrose solution, wherein (a) is a schematic diagram of the test spectrum, and (b) is a schematic diagram of the difference spectrum;

[0051] Figure 4 Schematic diagram of the smoothed spectra obtained by SPR detection of sucrose solution using the detection method of the SPR detection system of the present invention, wherein (a) is a schematic diagram of the smoothed spectrum when the average number of points is 1, (b) is a schematic diagram of the smoothed spectrum when the average number of points is 3, (c) is a schematic diagram of the smoothed spectrum when the average number of points is 5, and (d) is a schematic diagram of the smoothed spectrum when the average number of points is 7;

[0052] Figure 5 Schematic diagram of the regional integral standard response curve obtained by performing SPR detection on a sucrose solution by the SPR detection system of the present invention and a schematic diagram of the dual-wavelength standard response curve for comparison;

[0053] Figure 6 This is a trend diagram of the translational sliding signal-to-noise ratio when the SPR detection system of the present invention detects a sucrose solution;

[0054] Figure 7 Schematic diagram of the spectrum obtained by the SPR detection system of the present invention for SPR detection of a protein solution, wherein (a) is a schematic diagram of the reference spectrum and the test spectrum, and (b) is a schematic diagram of the difference spectrum;

[0055] Figure 8 Schematic diagram of a smoothed spectrum obtained by performing SPR detection on a protein solution using the detection method of the SPR detection system of the present invention;

[0056] Figure 9 Schematic diagram of fitting results obtained by fitting the smoothed spectral curve obtained by SPR detection of a protein solution using the assay method of the SPR detection system of the present invention at wavelengths of 594 nm, 590 nm, 570 nm, and 566 nm;

[0057] Figure 10 Schematic diagram comparing the regional integrated standard response and the 594nm single wavelength curve obtained by performing SPR detection on a protein solution using the detection method of the SPR detection system of the present invention;

[0058] Figure 11 Schematic diagram of the fitting peak search results obtained by detecting eight groups of SARS-CoV-2N protein solutions with different concentrations using SPR detection plates manufactured in three different batches using the assay method of the SPR detection system of the present invention. DETAILED DESCRIPTION

[0059] Next, combine Figures 1 to 11 The SPR detection system and the detection method of the present invention are described in detail in the following embodiments.

[0060] like Figure 1 As shown, the SPR detection system of the present invention includes an SPR detection plate 1, a broadband light source 2, a detector 3 and a control computer 4. Among them, the SPR detection plate 1 includes an orifice plate 11 and an SPR chip 12, the orifice plate 11 is provided with a plurality of through holes 111, and the SPR chip 12 is arranged on one side of the orifice plate 11 and affixed to the bottom of the through hole 111 to cooperate with the through hole 111 to form a detection hole. Preferably, 96 detection holes are arranged on the SPR detection plate 1, and the 96 detection holes are arranged in a matrix. Preferably, the SPR chip includes a PET substrate, a metasurface structure and a metal film, the metasurface is provided on the PET substrate, and the metal film is coated on the metasurface. When performing the detection, the detection light wave irradiated on the SPR chip can excite the plasma resonance on the surface of the metal film. Preferably, the broadband light source 2 is connected to the control computer 4 via a light source control line 5 to output the detection light wave according to the control signal issued by the control computer 4; the output end of the broadband light source 2 is provided with a guide optical fiber 6 to guide the detection light wave output by the broadband light source 2. Preferably, the detector 3 is connected to the control computer 4 via a signal collection line 7 to transmit the spectral data collected by the detection to the control computer 4 to form a spectral curve. Preferably, the output head 61 of the guide optical fiber 6 and the detector 3 are arranged opposite to each other on both sides of the detection position where the SPR detection plate 1 is placed, so that the detection light wave is output from the output head 61 of the guide optical fiber 6 and irradiated onto the SPR detection plate 1 located at the detection position, and at the same time, the detector 3 collects the spectral data passing through the detection hole on the SPR detection plate 1 in real time.

[0061] When using the SPR detection system of the present invention to detect a test sample to be detected, the spectral scanning range is first determined, and the broadband light source is caused to perform spectral scanning within the specified wavelength range to output detection light waves. The detector records the light intensity of each transmission spectrum output from the broadband light source and after passing through the SPR chip on the corresponding SPR detection board, and obtains a curve of intensity variation with light wavelength, namely the SPR spectral profile curve of the detection area.

[0062] The assay method of the SPR detection system of the present invention specifically comprises the following steps:

[0063] First, SPR detection is performed on standard samples and / or control samples of known concentration using a detection light wave Diw with a wavelength λ ranging from [p, q]. The corresponding calibration spectral data and reference spectral data are collected to obtain the corresponding calibration spectral curve and reference spectral curve. The differential spectral curve corresponding to the calibration spectral curve is then calculated. To ensure calibration accuracy, at least three standard samples of different concentrations must be selected.

[0064] When implementing the SPR detection system assay method of the present invention, a corresponding control sample can be selected based on the specific composition of the standard sample to obtain reference data. For example, when the standard sample is a carbohydrate solution, water is generally used as the control sample; when the standard sample is a protein solution, no separate control sample is required.

[0065] Select m portions of standard samples A1, A2, ..., A with different concentrations. j ,…,A m , the m parts of standard samples A1, A2, ..., A j ,…,A m The concentrations are C1, C2, ..., C j ,…,C m , m is a positive integer and m≥3. From the wavelength of the detection light wave Diw λ Select n wavelength values ​​λ1, λ2, ..., λ in the value range [p, q] in turn i ,…,λ n , and p≤λ1<λ2<…<λ i <…<λ n ≤q, where λ i Indicates the n wavelength values ​​λ1, λ2, ..., λ selected from the detection light wave Diw in the value range [p, q] i ,…,λ n The i-th wavelength value in , i is a positive integer and 1≤i≤n.

[0066] The SPR detection of the standard sample A1 with the concentration of C1 is performed using the detection light wave Diw, and the wavelength values ​​λ1, λ2, ..., λ i ,…,λn The corresponding optical density values ​​are used as the test optical density values ​​and recorded as Thus, the calibration spectrum curve corresponding to the standard sample A1 is obtained and The SPR detection of the standard sample A2 with a concentration of C2 is performed using the detection light wave Diw, and the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The corresponding optical density values ​​are taken as the test optical density values ​​and recorded as Thus, the calibration spectrum curve corresponding to the standard sample A2 is obtained and By analogy, the detection light wave Diw is used to detect the concentration of C j Standard sample A j Perform SPR detection and collect the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The corresponding optical density values ​​are taken as the test optical density values ​​and recorded as Thus, we can obtain the same j Corresponding test spectrum curve and Using the detection light wave Diw to detect the concentration of C m Standard sample A m Perform SPR detection and collect the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The corresponding optical density values ​​are taken as the test optical density values ​​and recorded as Thus, we can obtain the same m Corresponding test spectrum curve and

[0067] When standard samples A1, A2, ..., A j ,…,A m When the solution is a sugar solution, water is used as a control sample, and the detection light wave Diw is used to perform SPR detection on the control sample, i.e., water, and collect the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The corresponding optical density values ​​are taken as reference optical density values ​​and recorded as OD ref (λ1), OD ref (λ2), ..., OD ref (λ i ),……、OD ref (λ n ), thereby obtaining the corresponding reference spectrum curve and

[0068] When the standard sample is a protein solution, the SPR detection is performed on the standard sample using the detection light wave Diw, and the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The corresponding optical density values ​​are taken as reference optical density values ​​and recorded as OD ref (λ1), OD ref (λ2), ..., OD ref (λ i ),……、OD ref (λ n ), thereby obtaining the corresponding reference spectrum curve and With concentration as C j Standard sample A j For example, the reference spectrum curve obtained after detection is and

[0069] Based on the collected calibration spectrum data and reference spectrum data, the difference between the calibration optical density value and the reference optical density value corresponding to the same wavelength value, that is, the differential optical density value, can be calculated one by one, thereby obtaining the differential spectrum curve corresponding to the calibration spectrum curve and the reference spectrum curve.

[0070] When standard samples A1, A2, ..., A j ,…,A m When it is a protein solution, the specific calculation method is as follows:

[0071] For the standard sample A1, due to the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The one-to-one corresponding differential optical density values ​​are The differential spectrum curve corresponding to the standard sample A1 can be obtained Due to the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The corresponding reference optical density values ​​are: Therefore

[0072]

[0073] Therefore, the differential spectrum curve corresponding to the standard sample A1 with a concentration of C1 is

[0074] For the standard sample A2, due to the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The one-to-one corresponding differential optical density values ​​are The differential spectrum curve corresponding to the standard sample A2 can be obtained Due to the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The corresponding reference optical density values ​​are: Therefore

[0075]

[0076] Therefore, the differential spectrum curve corresponding to the standard sample A2 with a concentration of C2 is

[0077] And so on:

[0078] For standard sample A j , and the wavelength values ​​λ1, λ2, ..., λ of the detection light wave Diw i ,…,λ n The one-to-one corresponding differential optical density values ​​are and the wavelength values ​​λ1, λ2, ..., λ of the detection light wave Diw i ,…,λ n The corresponding reference optical density values ​​are: With a concentration of C j Standard sample A j The corresponding differential spectrum curve is Right now,

[0079] For standard sample A m , and the wavelength values ​​λ1, λ2, ..., λ of the detection light wave Diw i ,…,λ n The one-to-one corresponding differential optical density values ​​are and the wavelength values ​​λ1, λ2, ..., λ of the detection light wave Diw i ,…,λ n The corresponding reference optical density values ​​are: With a concentration of C m Standard sample A m The corresponding differential spectrum curve Right now,

[0080] When standard samples A1, A2, ..., A j ,…,A m When it is a sugar solution, the control sample is water. The specific calculation method is as follows:

[0081] For the control sample water, the detection light wave Diw is used to perform SPR detection on the control sample water, and the wavelength values ​​λ1, λ2, ..., λ i ,…,λn The corresponding reference optical density values ​​are recorded as OD ref (λ1), OD ref (λ2), ..., OD ref (λ i ),……、OD ref (λ n ).

[0082] For the standard sample A1, due to the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The one-to-one corresponding differential optical density values ​​are Obtain the differential spectrum curve corresponding to the standard sample A1 Due to the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The corresponding reference optical density values ​​are OD ref (λ1), OD ref (λ2), ..., OD ref (λ i ),……、OD ref (λ n ), so

[0083]

[0084] Therefore, the differential spectrum curve corresponding to the standard sample A1 with a concentration of C1 is

[0085] For the standard sample A2, due to the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The one-to-one corresponding differential optical density values ​​are Obtain the differential spectrum curve corresponding to the standard sample A2 Due to the wavelength values ​​λ1, λ2, ..., λ i ,…,λ n The corresponding reference optical density values ​​are OD ref (λ1), OD ref (λ2), ..., OD ref (λ i ),……、OD ref (λ n ), so

[0086]

[0087] Therefore, the differential spectrum curve corresponding to the standard sample A2 with a concentration of C2 is

[0088] And so on:

[0089] For standard sample A j , and the wavelength values ​​λ1, λ2, ..., λ of the detection light wave Diw i ,…,λ n The one-to-one corresponding differential optical density values ​​are and the wavelength values ​​λ1, λ2, ..., λ of the detection light wave Diw i ,…,λ n The corresponding reference optical density values ​​are OD ref (λ1), OD ref (λ2), ..., OD ref (λ i ),……、OD ref (λ n ), so, with a concentration of C j Standard sample A j The corresponding differential spectrum curve Right now,

[0090] For standard sample A m , and the wavelength values ​​λ1, λ2, ..., λ of the detection light wave Diw i ,…,λ n The one-to-one corresponding differential optical density values ​​are and the wavelength values ​​λ1, λ2, ..., λ of the detection light wave Diw i ,…,λ n The corresponding reference optical density values ​​are OD ref (λ1), OD ref (λ2), ..., OD ref (λ i ),……、OD ref (λ n ), so, with a concentration of C m Standard sample A m The corresponding differential spectrum curve Right now,

[0091] In summary, when the differential spectrum curve is calculated using the collected test spectrum data and reference spectrum data, the calculation formula is as follows:

[0092]

[0093] in,

[0094] C j Represents m standard samples with different concentrations A1, A2, ..., A j ,…,Am The jth standard sample A j The concentration of , j is a positive integer, and 1≤j≤m, m≥3;

[0095] λ i Indicates the n wavelength values ​​λ1, λ2, ..., λ selected from the detection light wave Diw in the value range [p, q]. i ,…,λ n The i-th wavelength value in , i is a positive integer and 1≤i≤n;

[0096] Indicates standard sample A j The corresponding differential spectrum curve;

[0097] Indicates standard sample A j Corresponding test spectrum curve The wavelength value λ i The corresponding test optical density value;

[0098] OD ref (λ i ) represents the corresponding reference spectrum curve when there is a control sample The wavelength value λ i The corresponding reference optical density value;

[0099] Indicates the reference spectrum curve corresponding to the absence of a control sample The wavelength value λ i The corresponding reference optical density value.

[0100] Next, the differential spectrum curve is smoothed and denoised to obtain a smoothed spectrum curve corresponding to the differential spectrum curve.

[0101] Specifically, the standard sample A j The corresponding differential spectrum curve As an example, the noise reduction algorithm f smo oth () for the differential spectrum curve Perform smoothing and noise reduction to obtain the differential spectrum curve The corresponding smooth spectral curve and

[0102] Using moving average algorithm as noise reduction algorithm smo oth ()Difference spectrum curve When performing smoothing and noise reduction, first extract the wavelength value λ i The adjacent r wavelength values ​​λ i+1 ,λ i+2 ,…,λ i+r One-to-one differential optical density values Then calculate the r differential optical density values and wavelength λ i The corresponding differential optical density value The average value of the wavelength λ i The corresponding smoothed optical density value and

[0103]

[0104] Thus, we can obtain the same j The corresponding smooth spectral curve and Therefore

[0105]

[0106] in,

[0107] Indicates the use of detection light wave Diw to measure the standard sample A j The wavelength value λ obtained by SPR detection i The corresponding differential optical density value;

[0108] r represents the average number of points used when smoothing and denoising the differential spectrum curve using the moving average algorithm. r is an integer and r≥1;

[0109] Indicates the use of detection light wave Diw to measure the standard sample A j The wavelength value λ obtained by SPR detection is i The adjacent r wavelength values ​​λ i+1 ,λ i+2 ,…,λ i+r One-to-one corresponding differential optical density values.

[0110] When using the moving average algorithm as a noise reduction algorithm to smooth the differential spectrum curve, the number of average points r can be set as needed, which is the same as the wavelength value λ. i The value of the number r of differential optical density values ​​corresponding to adjacent wavelength values.

[0111] In addition, when implementing the present invention, Bezier curves or other noise reduction methods may be used to perform smoothing and noise reduction processing on the differential spectrum curve.

[0112] Then, the smooth spectrum curve is fitted to obtain the fitting slope and correlation coefficient of the smooth spectrum curve, and the peaks smaller than the set threshold are eliminated. The fitting slope corresponding to the correlation coefficient is sorted, and the remaining fitting slopes are sorted to obtain a new fitting slope sequence. According to the new fitting slope sequence, the corresponding new wavelength sequence and the corresponding smoothed spectral density value sequence are obtained, thereby obtaining the corresponding sorted spectral curve, and the peaks and troughs in the sorted spectral curve are determined according to the maximum fitting slope and the minimum fitting slope in the new fitting slope sequence.

[0113] In the specific implementation of the present invention, the spectral data of the smoothed spectral curve corresponding to the standard sample is first fitted to obtain the fitting slope and correlation coefficient of the smoothed spectral curve; then, the best response wavelength sorting algorithm is used to sort the fitting slope after removing noise to obtain the corresponding sorted spectral curve. The specific operation is as follows:

[0114] For the wavelength value λ1, the standard samples A1, A2, ..., A j ,…,A m The concentrations of C1, C2, ..., C j ,…,C m As the independent variable, with the standard samples A1, A2, ..., A j ,…,A m The corresponding smooth spectral curve The smoothed optical density value corresponding to the wavelength value λ1 As the dependent variable, As the fitting slope corresponding to the wavelength value λ1, As a constant corresponding to the wavelength value λ1, a fitting equation corresponding to the wavelength value λ1 is established using a linear function, as follows:

[0115]

[0116] According to the above fitting equation, the fitting slope corresponding to the wavelength value λ1 is obtained. and constant values

[0117] The standard samples A1, A2, ..., A j ,…,A m The concentration values ​​C1, C2, ..., C j ,…,C m Substitute them into the corresponding fitting equations in turn to calculate the smoothed optical density prediction value corresponding to the wavelength value λ1 The details are as follows:

[0118]

[0119] according to Calculate the standard samples A1, A2, ..., A J ,…,A M The corresponding smooth spectral curve The average value of the smoothed spectral density difOD corresponding to the wavelength value λ1 ave (λ1), and

[0120] According to the standard samples A1, A2, ..., A j ,…,A m The corresponding smooth spectral curve The average smoothed optical density difOD corresponding to the wavelength value λ1 ave (λ1) and smoothed optical density prediction Calculate the average smoothed optical density difOD corresponding to the wavelength value λ1 ave (λ1) and smoothed optical density prediction The correlation coefficient R 2 (λ1), and

[0121]

[0122] For the wavelength value λ2, the standard samples A1, A2, ..., A j ,…,A m The concentrations of C1, C2, ..., C j ,…,C m As the independent variable, with the standard samples A1, A2, ..., A j ,…,A m The corresponding smooth spectral curve The smoothed optical density value corresponding to the wavelength value λ2 As the dependent variable, As the fitting slope corresponding to the wavelength value λ2, As a constant corresponding to the wavelength value λ2, a fitting equation corresponding to the wavelength value λ2 is established using a linear function, as follows:

[0123]

[0124] According to the above fitting equation, the fitting slope corresponding to the wavelength value λ2 is obtained. and constant values

[0125] The standard samples A1, A2, ..., A j ,…,A m The concentration values ​​C1, C2, ..., C j ,…,C m Substitute them into the corresponding fitting equations in turn to calculate the smoothed optical density prediction value corresponding to the wavelength value λ2 The details are as follows:

[0126]

[0127] according to Calculate the standard samples A1, A2, ..., A j ,…,A m The corresponding smooth spectral curve The average value of the smoothed spectral density difOD corresponding to the wavelength value λ2 ave (λ2), and

[0128] According to the standard samples A1, A2, ..., A j ,…,A m The corresponding smooth spectral curve The average smoothed optical density difOD corresponding to the wavelength value λ2 ave (λ2) and smoothed optical density prediction Calculate the average smoothed optical density difOD corresponding to the wavelength value λ2 ave (λ2) and smoothed optical density prediction The correlation coefficient R 2 (λ2), and

[0129]

[0130] And so on:

[0131] For the wavelength λ i , calculated and the wavelength value λ i The corresponding fitting slope and constant values Calculate the difference between the standard samples A1, A2, ..., A J ,…,A M The corresponding smooth spectral curve The wavelength value λ i The corresponding smoothed spectral density average difOD ave (λ i ),and Calculate the wavelength value λ i The corresponding smoothed optical density average difOD ave (λ i ) and smoothed optical density predictions The correlation coefficient R 2 (λ i ),and

[0132]

[0133] For the wavelength λ n , calculated and the wavelength value λ n The corresponding fitting slope and the fitting constant value Calculate the standard samples A1, A2, ..., A j ,…,A m The corresponding smooth spectral curve The wavelength value λ n The corresponding smoothed spectral density average difOD ave (λ n ),and Calculate the wavelength value λ n The corresponding smoothed optical density average difOD ave (λ n ) and smoothed optical density predictions The correlation coefficient R 2 (λ n ),and

[0134]

[0135] For the smooth spectrum curve corresponding to standard sample A1 The calculated correlation coefficient R 2 (λ1), R 2 (λ2),…,R 2 (λ i ),…,R 2 (λ n ) and set thresholds Compare and remove the values ​​whose values ​​are less than the set threshold The wavelength value and fitting slope corresponding to the correlation coefficient are arranged in descending order for the remaining n1' (1≤n1'<n) fitting slopes to form a new fitting slope sequence And get the corresponding new wavelength sequence λ 1' ,λ 2' ,…,λ i' ,…,λ n1' and smoothed optical density value series According to the new fitted slope sequence and the corresponding wavelength sequence λ 1' ,λ 2' ,…,λ i' ,…,λ n1' and smoothed optical density value series The sorting spectrum curve corresponding to the standard sample A1 can be obtained and Among them, with the wavelength value λ 1' The corresponding fitting slope is the maximum slope, that is, the sorting spectrum curve corresponding to the standard sample A1 The peak and wavelength value λ in 1' Corresponding to the wavelength value λ n1' The corresponding fitting slope is the minimum slope, that is, the sorting spectrum curve corresponding to the standard sample A1 The trough and wavelength value λ in n1' For example, when n=10 and the correlation coefficient R 2 (λ1), R 2 (λ2),…,R 2 (λ i ),…,R 2 (λ 10 ) in the four correlation coefficients R 2 (λ2), R 2 (λ5), R 2 (λ7), R 2 (λ8) are all less than the set threshold When the correlation coefficient R 2 (λ2), R 2 (λ5), R 2 (λ7), R 2 (λ8) One-to-one correspondence between wavelength values ​​λ2, λ5, λ7, λ8 and fitting slope And fit the slopes of the remaining 6 Arrange in descending order to obtain a new fitting slope sequence and the corresponding new wavelength sequence λ 1' ,λ 2' ,λ 3' ,λ 4' ,λ 5' ,λ 6' and smoothed optical density value series Thus, the sorting spectrum curve corresponding to the standard sample A1 is obtained and Then the sorting spectrum curve corresponding to the standard sample A1 is obtained The fitting slope and wavelength values ​​corresponding to the peak in are and λ 1' The fitting slope and wavelength values ​​corresponding to the trough are and λ 6' , that is, to achieve the sorting spectrum curve corresponding to the standard sample A1 The goal of peak search.

[0136] For the smooth spectrum curve corresponding to standard sample A2 The calculated correlation coefficient R 2 (λ1), R 2 (λ2),…,R 2 (λ i ),…,R 2 (λ n ) and set thresholds Compare and remove the values ​​whose values ​​are less than the set threshold The wavelength value and fitting slope corresponding to the correlation coefficient of the remaining n1' (1≤n1'<n) fitting slopes are arranged in descending order to form a new fitting slope sequence And get the corresponding new wavelength sequence λ 1' ,λ 2' ,…,λ i' ,…,λ n1' and smoothed spectral density value series According to the new fitted slope sequence and the corresponding wavelength sequence λ 1' ,λ 2' ,…,λ i' ,…,λ n1' and smoothed spectral density value series The sorting spectrum curve corresponding to the standard sample A2 can be obtained and Among them, with the wavelength value λ 1' The corresponding fitting slope is the maximum slope, that is, the sorting spectrum curve corresponding to the standard sample A2 The peak and wavelength value λ in 1' Corresponding to the wavelength value λ n1' The corresponding fitting slope is the minimum slope, that is, the sorting spectrum curve corresponding to the standard sample A2 The trough and wavelength value λ in n1' That is, the sorting spectrum curve corresponding to the standard sample A2 The fitting slope and wavelength values ​​corresponding to the peak in are and λ 1' The fitting slope and wavelength values ​​corresponding to the trough are and λ n1' , that is, to achieve the sorting spectrum curve corresponding to the standard sample A2 The goal of peak search.

[0137] And so on:

[0138] For standard sample A j The corresponding smooth spectral curve The calculated correlation coefficient R 2 (λ1), R 2 (λ2),…,R 2 (λ i ),…,R 2 (λ n ) and set thresholds Compare and remove the values ​​whose values ​​are less than the set threshold The wavelength value and fitting slope corresponding to the correlation coefficient are arranged in descending order for the remaining n1' (1≤n1'<n) fitting slopes to form a new fitting slope sequence And get the corresponding new wavelength sequence λ 1' ,λ 2' ,…,λ i' ,…,λ n1' and smoothed spectral density value series According to the new fitted slope sequence and the corresponding wavelength sequence λ 1' ,λ 2' ,…,λ i' ,…,λ n1' and smoothed optical density value series Available with standard sample A j Corresponding sorting spectrum curve Among them, with the wavelength value λ 1' The corresponding fitting slope is the maximum slope, that is, the slope with the standard sample A j Corresponding sorting spectrum curve The peak and wavelength value λ in 1' Corresponding to the wavelength value λ n1' The corresponding fitting slope is the minimum slope, that is, the slope of the standard sample A j Corresponding sorting spectrum curve The trough and wavelength value λ in n1' That is, with the standard sample A j Corresponding sorting spectrum curve The fitting slope and wavelength values ​​corresponding to the peak in are and λ 1' The fitting slope and wavelength values ​​corresponding to the trough are and λ n1' , that is, to achieve the same j Corresponding sorting spectrum curve The goal of peak search.

[0139] For standard sample A m The corresponding smooth spectral curve The calculated correlation coefficient R 2 (λ1), R 2 (λ2),…,R 2 (λ i ),…,R 2 (λ n ) and set thresholds Compare and remove the values ​​whose values ​​are less than the set threshold The wavelength value and fitting slope corresponding to the correlation coefficient are arranged in descending order for the remaining n1' (1≤n1'<n) fitting slopes to form a new fitting slope sequence And get the corresponding new wavelength sequence λ 1' ,λ 2' ,…,λ i' ,…,λ n1' and smoothed spectral density value series According to the new fitted slope sequence and the corresponding wavelength sequence λ 1′ ,λ 2′ ,…,λ i′ ,…,λ n1′ and smoothed optical density value series Available with standard sample A m Corresponding sorting spectrum curve Among them, with the wavelength value λ 1' The corresponding fitting slope is the maximum slope, that is, the slope with the standard sample A m Corresponding sorting spectrum curve The peak and wavelength value λ in 1' Corresponding to the wavelength value λ n1' The corresponding fitting slope is the minimum slope, that is, the slope of the standard sample A m Corresponding sorting spectrum curve The trough and wavelength value λ in n1' That is, with the standard sample A m Corresponding sorting spectrum curve The fitting slope and wavelength values ​​corresponding to the peak in are and λ 1' The fitting slope and wavelength values ​​corresponding to the trough are k Cm (λ n1' ) and λ n1' , that is, to achieve the same m Corresponding sorting spectrum curve The goal of peak search.

[0140] When implementing the present invention, the threshold is set The value of can be set according to actual needs, usually set to 0.95; when sorting the remaining fitting slopes, they can also be arranged in ascending order.

[0141] In summary, according to the spectral data of the smooth spectrum curve corresponding to the standard sample, the smooth spectrum curve is fitted, and the relationship between the smooth optical density value corresponding to each wavelength value and the concentration of the standard sample can be calculated, thereby fitting the fitting slope and correlation coefficient corresponding to each wavelength value in the smooth spectrum curve; comparing the correlation coefficient and the set threshold To eliminate the The wavelength value and fitting slope corresponding to the correlation coefficient are obtained, and the remaining fitting slopes are sorted to form a new fitting slope sequence, and the corresponding new wavelength sequence and smoothed spectral density value sequence are obtained according to the new fitting slope sequence, so as to obtain the sorted spectral curve corresponding to the standard sample, and then the peaks and troughs in the sorted spectral curve can be determined according to the new fitting slope sequence, that is, the goal of finding the peak of the sorted spectral curve is achieved.

[0142] With concentration as C j Standard sample A j For example, the specific processing process is as follows:

[0143] According to the standard sample A j The corresponding smooth spectral curve The spectral data of the standard sample A j Corresponding spectral curve Perform fitting processing to calculate each wavelength value λ i (p<λ i <q, and i = [1, n]) corresponding to the smoothed optical density value and standard sample A j The concentration C j The relationship between Each wavelength value λ i (p<λ i <q, and i = [1, n]) corresponding to the fitting slope and the correlation coefficient R 2 (λ i ). Comparison of correlation coefficients R 2 (λ i ) and set thresholds when When the correlation coefficient R is eliminated 2 (λ i ) corresponds to the wavelength value λ i and the fitted slope when When the correlation coefficient R 2 (λ i ) corresponds to the wavelength value λ i and the fitted slope Sort the remaining n1' (1≤n1'<n) fitting slopes to form a new fitting slope sequence And get the corresponding new wavelength sequence λ 1' ,λ 2' ,…,λ i' ,…,λ n1' and the corresponding smoothed spectral density value sequence According to the new fitted slope sequence and the corresponding wavelength sequence λ 1′ ,λ 2′ ,…,λ i′ ,…,λ n1′ and smoothed spectral density value series Available with standard sample A j Corresponding sorting spectrum curve and The above fitting sorting operation is expressed mathematically as follows:

[0144]

[0145] in,

[0146] f fit () represents the fitting function,

[0147] f sort () indicates a sorting operation.

[0148] Finally, the sorting spectrum curve is subjected to regional integration processing to obtain a concentration characteristic value related to the concentration of the standard sample corresponding to the sorting spectrum curve.

[0149] Specifically, the obtained samples are arranged in descending order with the standard sample A j Corresponding sorting spectrum curve As an example, select the sorting spectrum curve The first N wavelength data and the last M wavelength data, that is, the first N wavelength data are close to the sorted spectrum curve The wavelength data of the peak area in the middle, the last M wavelength data are close to the sorted spectrum curve The wavelength data of the trough area in the trough area is processed by regional integration of the selected wavelength data to obtain the sorted spectrum curve. Corresponding standard sample A j The concentration C j Related concentration characteristic values and

[0150]

[0151] in,

[0152] N represents the integral range of the peak area,

[0153] M represents the integral range of the trough area,

[0154] I represents the sorting spectrum curve Medium and minimum fitting slope That is, the wavelength value λ corresponding to the trough I The sort number,

[0155] W represents the weight parameter of the peak area, and W=(w0, w1, ..., w N ),

[0156] V represents the weight parameter of the trough area, and V=(v I-M ,…,v I-1 、v I ).

[0157] When performing SPR detection on a test sample of unknown concentration using the SPR detection system of the present invention, the concentration of the test sample of unknown concentration can be quantitatively determined directly based on the concentration characteristic value related to the concentration of the standard sample obtained by the detection method of the SPR detection system of the present invention.

[0158] When implementing the assay method of the SPR detection system of the present invention, the values ​​of the weight parameters W and V can be adjusted as needed. For example, when the wavelength values ​​of the three groups of wavelengths with the largest and smallest fitting slopes are 590 nm, 592 nm, and 588 nm and 570 nm, 572 nm, and 574 nm, respectively, the weight parameters corresponding to the three groups of wavelengths with the largest and smallest fitting slopes can be set to 1, 1.2, and 1.3, respectively.

[0159] Verification Example 1:

[0160] 60uL (microliter) of water is added to holes 1 to 5 on the SPR detection plate with 96 through holes as a control sample, and the SPR detection plate is immediately placed between the output head of the guide optical fiber and the detector, and the control computer controls the bandwidth light source to emit a detection light wave Diw with a wavelength range of 400-800nm ​​(nanometers) and irradiate the SPR detection plate through the output head of the guide optical fiber, and the detector is used to detect and collect the reference spectrum data and transmit it to the control computer and form a reference spectrum in the control computer, which includes a reference spectrum curve

[0161] Remove the control samples from wells 1 to 5 on the SPR detection plate, and sequentially inject 5 groups of sucrose solutions with different concentrations as standard samples A1, A2, A3, A4, and A5, wherein the concentration C1 of standard sample A1 is 0%, the concentration C2 of standard sample A2 is 2%, the concentration C3 of standard sample A3 is 4%, the concentration C4 of standard sample A4 is 8%, and the concentration C5 of standard sample A5 is 16%. Use the detection light wave Diw with a wavelength range of 400-800nm ​​(nanometers) to perform SPR detection on the 5 groups of standard samples A1, A2, A3, A4, and A5 respectively, use the detector to collect the verification spectrum data, transmit it to the control computer, and generate the following in the control computer. Figure 3 (a) shows the test spectrum, and the test spectrum includes 5 test spectrum curves corresponding to 5 groups of standard samples A1, A2, A3, A4, and A5.

[0162] By using the test method of the SPR detection system of the present invention, the test spectrum and the reference spectrum are differentially processed to obtain the following: Figure 3 (b) shows the differential spectrum, and the differential spectrum includes 5 differential spectrum curves corresponding to the 5 groups of standard samples A1, A2, A3, A4, and A5. The corresponding smoothed spectrum can be obtained by smoothing and denoising the differential spectrum using the translation sliding algorithm. The smoothed spectrum includes 5 smoothed spectrum curves corresponding to the 5 standard samples A1, A2, A3, A4, and A5. When the number of average points is 1, 3, 5 and 7, the four smoothed spectra obtained are as follows: Figure 4 As shown; for the smooth spectrum curve Perform fitting processing to obtain the fitting slope, obtain the fitting slope and correlation coefficient corresponding to each wavelength value in the smoothed spectral curve, and eliminate the values ​​less than the set threshold. The wavelength values ​​and fitting slopes corresponding to the correlation coefficients are obtained, and the remaining fitting slopes are sorted in descending order to obtain a new fitting slope sequence, and the corresponding new wavelength sequence and smoothed spectral density value sequence are obtained according to the new fitting slope sequence, thereby obtaining 5 sorted spectral curves corresponding to the standard samples A1, A2, A3, A4, and A5. The sorting spectrum curve is determined based on the maximum fitting slope in the new fitting slope sequence. The sorting spectrum curve is determined based on the minimum fitting slope in the new fitting slope sequence. The trough on the sorting spectrum curve Perform regional integration processing to obtain the concentration characteristic values ​​related to the concentrations C1, C2, C3, C4, and C5 of the five groups of sucrose solutions A1, A2, A3, A4, and A5. And according to the concentration characteristic value The concentrations C1, C2, C3, C4, and C5 of the corresponding sucrose solutions A1, A2, A3, A4, and A5 can be established as follows: Figure 5 The area integral standard response curve and response formula y shown MAAWI =0.294x+0.060, where y MAAWI Indicates the concentration characteristic value related to the concentration of the standard sample in the regional integral standard response curve, that is, y MAAWI =C OD , x represents the concentration of sucrose solution. At the same time, as a comparison, Figure 5 The double wavelength standard response curve and response formula y are also shown, which are constructed with the wavelength value of 585nm corresponding to the peak and the wavelength value of 570nm corresponding to the trough. D2Ps =0.070x+0.030, where y D2PsI Indicates the concentration characteristic value related to the concentration of the standard sample in the dual-wavelength standard response curve, that is, y D2PsI =C OD , x represents the concentration of sucrose solution.

[0163] In this embodiment, the moving smoothed signal-to-noise ratio (SNR) changes when the average number of points is 1, 3, 5, and 7, respectively. Figure 6 As shown, when the average number of points is 1, the signal-to-noise ratio level L SNR =3.089; when the average number of points is 7, the signal-to-noise ratio level L SNR =3.788. Since a higher signal-to-noise ratio indicates a higher signal-to-noise ratio for the data processed by the smoothing and noise reduction, the number of average points used in the smoothing and noise reduction process can be adjusted as needed during the implementation of the present invention to reduce noise data, that is, to reduce interference data, thereby improving the accuracy of the test.

[0164] Since the characteristic concentration value C OD The concentration of the sucrose solution can be quantitatively calculated. Therefore, after the SPR detection system of the present invention is used to perform SPR detection on a sucrose solution of unknown concentration and obtain the corresponding differential spectrum curve, the response formula y can be used. MAAWI =0.294x+0.060 and concentration characteristic value C OD Quantitatively determine the concentration x of a sucrose solution of unknown concentration.

[0165] In addition, when implementing the present invention, different sensors, detectors and standard samples are used, and the response curves and response formulas established may be slightly different.

[0166] Verification Example 2:

[0167] First, the SPR detection plate was surface functionalized. Specifically, the SPR detection plate with 96 through-holes was cleaned and the SARS-CoV-2N protein was diluted with PBS buffer to prepare a coating solution. 5 μL of the coating solution was injected into each detection well of the SPR detection plate and incubated on the surface of the SPR detection plate for 12 hours. After 12 hours, 100 μL of 5% BSA was injected into each detection well of the SPR detection plate for 30 minutes.

[0168] Next, clean the SPR detection plate and inject 60uL of 8 groups of SARS-CoV-2N protein solutions of different concentrations into the eight detection wells on the SPR detection plate, and the concentrations of the 8 groups of SARS-CoV-2N protein solutions are 0ug / mL, 0.03125ug / mL, 0.0625ug / mL, 0.125ug / mL, 0.25ug / mL, 0.5ug / mL, 1ug / mL and 2ug / mL, respectively. The SPR detection plate is placed between the output head of the guide optical fiber in the SPR detection system and the detector, and the SARS-CoV-2N protein solution injected into the detection well is immediately detected with a detection light wave Diw with a wavelength range of 400-800nm, so that the detector collects reference spectrum data to form the following Figure 7 (a) shows the reference spectrum, which includes 8 reference spectrum curves. After 15 minutes, the SARS-CoV-2N protein solution injected into the detection hole is detected again using the detection light wave Diw so that the detector can collect the verification spectrum data, forming the following Figure 7 (a) shows the test spectrum, which includes 8 test spectrum curves.

[0169] Then, based on the test spectrum and the reference spectrum, we can get the following Figure 7 (b) shows the differential spectrum, and the differential spectrum includes 8 differential spectrum curves; after smoothing and denoising the differential spectrum, the corresponding Figure 8 The smooth spectrum shown in the figure includes 8 smooth spectrum curves. The smooth spectrum curves in the smooth spectrum are fitted to obtain the fitting slope and correlation coefficient corresponding to each wavelength value in the smooth spectrum curve. The values ​​of the correlation coefficients less than the set threshold are eliminated. The wavelength values ​​and fitting slopes corresponding to the correlation coefficients are obtained, and the remaining fitting slopes are sorted to obtain a new fitting slope sequence, and the corresponding new wavelength sequence and smoothed spectral density value sequence are obtained according to the new fitting slope sequence, thereby obtaining 8 sorted spectral curves corresponding to 8 groups of SARS-CoV-2N protein solutions, and the peak on the sorted spectral curve is determined according to the maximum fitting slope in the new fitting slope sequence, and the trough on the sorted spectral curve is determined according to the minimum fitting slope in the new fitting slope sequence, and the fitting results at wavelengths of 594nm, 590nm, 572nm and 570nm are as follows: Figure 9 As shown in the figure; according to the relevant parameters determined by fitting, after eliminating the corresponding fitting slope and wavelength values, the sorting spectrum curve is regionally integrated to obtain the concentration characteristic value C related to the concentration of the 8 groups of SARS-CoV-2N protein solutions. OD , and according to each concentration characteristic value C OD The concentration of the corresponding SARS-CoV-2N protein solution can be established as Figure 10 The area-integrated standard response curve and response formula are shown.

[0170] After the SPR detection system of the present invention is tested through the above steps, the SPR detection system of the present invention is used to perform SPR detection on a SARS-CoV-2N protein solution of unknown concentration to obtain the corresponding differential spectrum curve and calculate the corresponding concentration characteristic value C OD , so that the concentration of the SARS-CoV-2N protein solution of unknown concentration can be quantitatively obtained using the response formula.

[0171] In addition, the above 8 groups of SARS-CoV-2N protein solutions with concentrations of 0ug / mL, 0.03125ug / mL, 0.0625ug / mL, 0.125ug / mL, 0.25ug / mL, 0.5ug / mL, 1ug / mL and 2ug / mL were used as standard samples to calibrate the SPR detection systems of three SPR detection plates equipped with SPR chips manufactured in different batches. The fitting peak search results are as follows: Figure 11 As shown in the figure, when the SPR detection system of the present invention uses SPR chips from different batches, errors in the manufacturing process of the SPR chips will cause the maximum response wavelength to shift. Compared with the corresponding 5 groups of data before the peak and 5 groups of data before the trough, the fitting peak-finding method used in the detection method of the SPR detection system of the present invention more accurately determines the peaks and troughs in the detection spectrum data.

Claims

1. A method for detecting an SPR detection system, characterized in that: The verification method comprises the following steps: S1. Use the detection light wave Diw with a wavelength λ value range of [p, q] to perform SPR detection on m standard samples or / and control samples with different concentrations, collect the test spectrum data and reference spectrum data, and obtain the corresponding test spectrum curve and reference spectrum curve , and calculate the corresponding differential spectrum curve and in, C j Represents the jth standard sample A among m standard samples with different concentrations j The concentration of , j is a positive integer and 1≤j≤m, λ i represents the i-th wavelength value of the wavelength λ of the detection light wave Diw among the n wavelength values ​​selected sequentially within the value range [p, q], where i is a positive integer and 1≤i≤n; Represents the standard sample A j The corresponding differential spectrum curve; Represents the standard sample A j Corresponding test spectrum curve The wavelength value λ i The corresponding test optical density value; OD ref (λ i ) represents the corresponding reference spectrum curve when there is a control sample The wavelength value λ i The corresponding reference optical density value; Indicates the reference spectrum curve corresponding to the absence of a control sample The wavelength value λ i The corresponding reference optical density value; S2, the differential spectrum curve Perform smooth noise reduction processing to obtain the corresponding smooth spectrum curve and Among them, f smooth ( ) is the noise reduction algorithm; S3, smoothing the spectrum curve Perform fitting processing to obtain the smooth spectrum curve The fitted slope of and the correlation coefficient R 2 (λ i ), remove the data that is less than the set threshold The wavelength value and fitting slope corresponding to the correlation coefficient of , sort the remaining n1' (1≤n1'<n) fitting slopes to obtain a new fitting slope sequence And according to the new fitted slope sequence Get the corresponding new wavelength sequence λ 1' ,λ 2' ,…,λ i' ,…,λ n1' and the corresponding smoothed spectral density value sequence Thus, the standard sample A j Corresponding sorting spectrum curve and And according to the new fitting slope sequence The maximum fitting slope and the minimum fitting slope determine the sorting spectrum curve the peaks and troughs in S4, sorting the spectrum curve Perform regional integration processing to obtain the same j The concentration C j Related concentration characteristic values 2. The method for detecting an SPR detection system according to claim 1, wherein In step S2, a moving average algorithm is used as a noise reduction algorithm to reduce the difference spectrum curve. Perform smooth noise reduction processing to obtain the corresponding smooth spectrum curve and in, Indicates that the standard sample A is detected by the detection light wave Diw. j The wavelength value λ obtained by SPR detection i The corresponding differential optical density value, r represents the difference spectrum curve using the moving average algorithm The average number of points used in smoothing and noise reduction processing, r is an integer and r≥1; Indicates that the standard sample A is detected by the detection light wave Diw. j The wavelength value λ obtained by SPR detection is i The adjacent r wavelength values ​​λ i+1 ,λ i+2 ,…,λ i+r One-to-one corresponding differential optical density values.

3. The method for detecting an SPR detection system according to claim 1 or 2, wherein: In step S3, the smoothed spectrum curve When performing the fitting process, the standard sample A j The concentration C j As the independent variable, the standard sample A j The test spectrum curve of The wavelength value λ of the detection light wave Diw i The corresponding smoothed optical density value As the dependent variable, a linear function is established with the wavelength value λ i The corresponding fitting equation is in, Indicates the standard sample A j The corresponding fitting constant value.

4. The method for detecting the SPR detection system according to claim 3, wherein Then the remaining n1' (1≤n1'<n) fitting slopes are sorted in descending order to obtain the sorted spectrum curve 5. The method for detecting the SPR detection system according to claim 4, wherein The set threshold is 0.

95.

6. The method for detecting the SPR detection system according to claim 3, wherein: In step S4, the sorting spectrum curve is selected The first N wavelength data and the last M wavelength data are processed by regional integration, and in, N represents the integral range of the peak area, M represents the integral range of the trough area, I represents the sorting spectrum curve Medium and minimum fitting slope That is, the wavelength value λ corresponding to the trough I The sort number, W represents the weight parameter of the peak area, and W=(w0, w1, ..., w N ), V represents the weight parameter of the trough area, and V=(v I-M ,…,v I-1 、v I ).

7. An SPR detection system, characterized in that The SPR detection system is tested by the SPR detection method according to any one of claims 1 to 6, and the result is the same as that of the standard sample A. j The concentration C j Related concentration characteristic values 8. The SPR detection system according to claim 7, characterized in that The SPR detection system includes an SPR detection plate, which includes a well plate and an SPR chip. The well plate is provided with a plurality of through holes. The SPR chip is arranged on one side of the well plate and adheres to the bottom of the through holes. The SPR chip cooperates with the through holes to form a detection hole.

9. The SPR detection system according to claim 8, characterized in that 96 detection holes are arranged on the SPR detection plate, and the detection holes are arranged in a matrix.

10. The SPR detection system according to any one of claims 7 to 9, characterized in that The SPR detection system includes a bandwidth light source, a detector and a control computer. The bandwidth light source is connected to the control computer via a light source control line, and a guide optical fiber is provided at the output end of the bandwidth light source; the detector is connected to the control computer via a signal collection line, and the output heads of the detector and the guide optical fiber are arranged opposite to each other on both sides of the detection position for placing the SPR detection plate.

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