Serum quality evaluation method based on surface enhanced Raman spectroscopy

Abstract

The invention discloses a method for evaluating serum quality based on surface enhanced Raman spectroscopy. The method comprises the following detection steps: 1) obtaining a normal serum sample, a hemolytic serum sample, a lipemia serum sample and a jaundice serum sample; 2) performing Raman spectrum scanning on the elargol enhanced serum sample; 3) discriminating the hemolysis, lipemia and jaundice samples by using principal component analysis and linear discriminant analysis, and determining the characteristic spectrums of hemolysis, lipemia and jaundice; the method comprises the following steps of (1) obtaining a serum characteristic spectrum signal, (2) determining a Cuff value of a corresponding abnormal specimen based on the serum characteristic spectrum, and establishing a fitting curve of key molecules influencing serum quality based on a characteristic peak, (5) carrying out Raman spectrum scanning on a to-be-detected serum sample, and (6) evaluating the serum quality according to the obtained Raman characteristic spectrum signal by utilizing the Cuff value of the characteristic spectrum peak determined in the earlier stage and the fitting curve.

Description

Technical Field

[0001] The present invention relates to the field of serum detection technology, and more specifically, to a method for evaluating serum quality based on surface enhanced Raman spectroscopy. Background Art

[0002] Serum samples are the most common and main samples in medical laboratories at present, and their quality seriously affects the accuracy of test results. Common interference factors such as hemolysis, lipemia, and jaundice often lead to unpredictable deviations in results, and even affect clinical diagnosis and treatment decisions. According to the accreditation requirements of ISO15189, pre-analysis quality control cannot be ignored, and medical laboratories need to identify and deal with unqualified samples in a timely manner. Therefore, rapid and accurate identification of the quality of serum samples is crucial for medical laboratories. At present, the judgment of serum quality is mainly based on naked eye observation and serum index (SI) based on absorbance. In recent years, the number of specimens in the laboratory has continued to increase. The conventional naked eye observation method is highly subjective, time-consuming, and cannot be standardized, which cannot meet the laboratory's rapid and accurate screening of unqualified samples; the SI based on absorbance is unsatisfactory in the accuracy of lipemia, and is restricted by instrument standards and costs. Therefore, it is urgent to develop a detection method that can quickly, accurately and economically determine serum quality. Summary of the invention

[0003] In view of the shortcomings of the prior art, the present invention provides a method for evaluating serum quality based on surface enhanced Raman spectroscopy, which can conveniently and quickly evaluate serum quality.

[0004] The present invention provides the following technical solution: a method for evaluating serum quality based on surface enhanced Raman spectroscopy, comprising the following detection steps: 1) Obtain normal serum samples, hemolytic serum samples, lipemic serum samples and icteric serum samples; 2) Perform Raman spectroscopy scans on serum samples enhanced with silver colloid to determine the characteristic Raman peaks of hemolytic, lipemic and icteric serum samples; 3) Use principal component analysis and linear discriminant analysis to distinguish hemolysis, lipemia and icterus samples and determine the characteristic spectra of hemolysis, lipemia and icterus; 4) Build a Raman spectral database of normal, hemolytic, lipemic and icteric samples, determine the cutoff value of the corresponding abnormal specimens based on the serum characteristic spectrum; and establish the fitting curve of the key molecules affecting serum quality based on the characteristic peaks; 5) Perform Raman spectroscopy scanning on the serum sample to be tested; 6) According to the obtained Raman characteristic spectrum signal, the quality of the serum is evaluated by using the previously determined characteristic spectrum peak Cutoff value and fitting curve.

[0005] Preferably, in step 2), the volume ratio of silver colloid to serum is (1-1.2):1.

[0006] Preferably, in step 2), the Raman spectrum acquisition parameters are: the excitation wavelength is 785 nm, the laser power is set to 20 mW, and the integration time is 5 s.

[0007] Preferably, in step 2), the preparation of silver colloid: prepare 0.1~0.5g / ml AgNO3 solution and stir; then, pour sodium hydroxide into hydroxylamine hydrochloride and mix well to obtain a mixed solution, wherein the volume ratio of sodium hydroxide to hydroxylamine hydrochloride is 1:(1~1.5); pour the mixed solution into the stirring AgNO3 solution to obtain a silver colloid precursor solution; centrifuge the prepared silver colloid precursor solution, remove the supernatant, and obtain silver colloid.

[0008] Preferably, in step 2), the characteristic Raman peak is located at 400 cm -1 -1800cm -1 Raman frequency shift range.

[0009] Preferably, in step 2), a Raman spectrum scan of the silver colloid-enhanced serum sample is performed using an incident laser light source with a wavelength of 785 nm to determine the characteristic Raman peaks of the hemolytic, lipemic and icteric serum samples.

[0010] Preferably, in step 4), the key molecules include hemoglobin, triglycerides and total bilirubin.

[0011] Preferably, in step 5), a Raman spectrum scan is performed on the serum sample to be tested using an incident laser light source with a wavelength of 785 nm.

[0012] In summary, the present invention determines the Cutoff value of the corresponding abnormal specimen based on the serum characteristic spectrum, and establishes the fitting curve of the key molecules (hemoglobin, triglycerides, and total bilirubin) that affect the serum quality based on the characteristic peaks; according to the obtained Raman characteristic spectrum signal of the serum sample to be tested, the Cutoff value of the characteristic spectrum peak determined in the early stage and the fitting curve are used to evaluate the quality of the serum, which can conveniently and quickly evaluate the quality of the serum. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a detection schematic diagram; Normalized mean SERS spectra of normal control (n=48), hemolytic (n=60), lipemic (n=41), and icteric serum; the green line indicates the difference between the control group and other groups; the Raman shift with the largest difference between the hemolytic group and the control group is 723cm -1 , 1133 cm -1 The Raman shift with the largest difference in characteristic peaks between the lipemia group and the control group was 636 cm -1, 928cm -1 The Raman shift with the largest difference between the characteristic peaks of the jaundice group and the control group was 863 cm -1 , 1424cm -1 , 1615cm -1 .

[0014] Figure 2 shows the intra-batch precision determination: The same serum sample was tested repeatedly under the same experimental conditions. It can be seen from the figure that the characteristic peaks of the serum sample spectrum are very obvious and have good consistency. The serum solution is calculated to be at 636cm -1 、723cm -1 and 1615cm -1 The relative standard deviations of the Raman characteristic peak intensities at were 4.56%, 4.62% and 4.77% RSD respectively.

[0015] Figure 3 is the principal component analysis of serum SERS data Two-dimensional scatter plots of PCA scores of (a) healthy control group and hemolysis group, (b) healthy control group and lipidemia group, (c) healthy control group and jaundice group; red points represent the control group, and blue points represent the hemolysis or lipidemia or jaundice group.

[0016] Figure 4 To compare different serum spectra according to PC1 (a) and (b) draw the corresponding ROC curves; The areas under the ROC curve (AUC) were 0.9805, 0.9922 and 0.9678, respectively.

[0017] Figure 5 The characteristic peaks of hemolysis, lipemia and icteric serum samples and the hemoglobin, triglyceride and bilirubin concentrations of standard serum were analyzed by regression analysis. The results showed that: based on 723cm -1 、636cm -1 、1615cm -1 The intensity of characteristic spectral peaks can effectively determine the severity of hemolysis, lipemia and jaundice in serum samples. DETAILED DESCRIPTION

[0018] The present invention will be further described with reference to the accompanying drawings.

[0019] like Figures 1 to 5 As shown, a method for rapid assessment of serum quality based on surface enhanced Raman spectroscopy includes the following detection steps: (1) Sample collection: serum samples with abnormal hemolysis index, abnormal lipidemia index, or abnormal icterus index were collected, and serum samples with normal serum indexes were collected as control samples; (2) Preparation of silver colloid: 0.0340 g of AgNO3 was dissolved in 90 ml of ultrapure water, and the mixture was stirred at 800 rpm on a magnetic stirrer for 10 min. Then, 9 ml of sodium hydroxide was poured into 10 ml of hydroxylamine hydrochloride and mixed. The mixture was poured into the stirring AgNO3 solution and stirred for 10 min. The prepared silver colloid was transferred to a centrifuge tube and centrifuged at 8000 rpm for 10 min. 49 / 50 of the supernatant was discarded, and the concentrated silver colloid was concentrated 50 times and then mixed for later use. (3) Sample testing: Drop 10 μl of concentrated silver colloid on an aluminum groove substrate, then drop 10 μl of serum on it, and mix by pipetting several times, taking care to avoid generating bubbles; collect the spectrum using a Raman spectrometer.

[0020] (4) Raman spectrum acquisition parameters: excitation wavelength is 785nm, laser power is set to 20mW, integration time is 5s, laser mode is laser automatic, spectrum is obtained and data is saved; (5) Preprocessing of Raman spectral data: The interpolated sample data is subjected to windowed moving polynomial least squares smoothing and adaptive iterative penalized least squares method to remove the fluorescence background, first-order derivative operation is performed to remove the interference of noise and fluorescence background, and maximum value normalization is performed to remove the influence of inconsistent experimental conditions such as excitation light power fluctuations and aggregation differences, ensuring the unified benchmarking of spectra collected at different integration times; (6) Construction of Raman spectroscopy discrimination model: Based on the preprocessed sample data, the discrimination model of hemolysis, lipemia and jaundice was established using PCA (principal component analysis) and LDA (linear discriminant analysis) algorithms to determine the feasibility of surface Raman spectroscopy in the discrimination of hemolysis, lipemia and jaundice; (7) The Raman spectra of different hemolytic, lipemic and icteric serum samples were analyzed to obtain the corresponding Raman characteristic peaks: the most significant Raman shift of the hemolytic sample peak difference was 723 cm -1 ; The Raman shift of lipemia sample is 636cm -1 ; The Raman shift of the characteristic peak of jaundice is 1615cm -1; The biggest interfering factor for hemolytic samples is the release of free hemoglobin, the biggest interfering factor for lipemic samples is triglycerides, and the biggest interfering factor for icteric samples is bilirubin; Correlation and regression analysis were performed based on the characteristic peaks of hemolytic, lipemic and icteric serum samples and the hemoglobin, triglyceride and bilirubin concentrations of standard serum; Based on hemoglobin hemolytic serum: Y1 = 0.0004x - 0.3169, R2 = 0.983, p<0.001; lipemic serum: Y2=5E-05x + 0.41, R2 = 0.9536, p<0.001; icteric samples: Y3= 0.0004x - 0.3169, R2 = 0.983, p<0.001 (X1 represents 723cm -1 Characteristic peak intensity; X1 represents 723cm -1 Characteristic peak intensity; X2 represents 636cm -1 Characteristic peak intensity; X3 represents 1615cm -1 Characteristic peak intensity); the results show that: based on 723cm -1 、636cm -1 、1615cm -1 The intensity of characteristic spectral peaks can effectively determine the severity of hemolysis, lipemia and jaundice in serum samples; (8) Normal samples, samples with different degrees of hemolysis, lipemia and icterus were collected to construct the corresponding surface-enhanced Raman spectroscopy database; the Raman spectroscopy database and hemolysis (723 cm -1 )、lipidemia(636cm -1 ) and jaundice (1615cm -1 The cut-off values ​​of the intensity of the characteristic peaks of hemolysis, lipemia and icterus specimens were determined by the receiver operating characteristic (ROC) curve method. (9) Further clinical samples were collected, and the Raman spectral data of hemolysis, lipemia, and jaundice were used as the test set. The test set was discriminated and verified based on the cut-off value of the determined abnormal serum specimens. Confusion matrix and receiver operating characteristic curve were used for verification.

[0021] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for evaluating serum quality based on surface enhanced Raman spectroscopy, characterized by: comprising the following Testing steps: 1) Obtain normal serum samples, hemolytic serum samples, lipemic serum samples and icteric serum samples; 2) Perform Raman spectroscopy scans on serum samples enhanced with silver colloid to determine the characteristic Raman peaks of hemolytic, lipemic and icteric serum samples; 3) Use principal component analysis and linear discriminant analysis to distinguish hemolysis, lipemia and icterus samples and determine the characteristic spectra of hemolysis, lipemia and icterus; 4) Build a Raman spectral database of normal, hemolytic, lipemic and icteric samples, and determine the cutoff value of the corresponding abnormal specimens based on the serum characteristic spectrum; Based on the characteristic peaks, the fitting curves of key molecules affecting serum quality were established; 5) Perform Raman spectroscopy scanning on the serum sample to be tested; 6) According to the obtained Raman characteristic spectrum signal, the quality of the serum is evaluated by using the previously determined characteristic spectrum peak Cutoff value and fitting curve.

2. The method for evaluating serum quality based on surface enhanced Raman spectroscopy according to claim 1, characterized in that: In step 2), the volume ratio of silver colloid to serum is (1~1.2):

1.

3. The method for evaluating serum quality based on surface enhanced Raman spectroscopy according to claim 1 or 2, characterized in that: In step 2), the Raman spectrum acquisition parameters are: the excitation wavelength is 785 nm, the laser power is set to 20 mW, and the integration time is 5 s.

4. The method for evaluating serum quality based on surface enhanced Raman spectroscopy according to claim 3, characterized in that: In step 2), the preparation of silver colloid: prepare 0.1~0.5g / ml AgNO3 solution and stir; then, pour sodium hydroxide into hydroxylamine hydrochloride and mix well to obtain a mixed solution, wherein the volume ratio of sodium hydroxide to hydroxylamine hydrochloride is 1: (1~1.5); pour the mixed solution into the stirring AgNO3 solution to obtain a silver colloid precursor solution; centrifuge the prepared silver colloid precursor solution, remove the supernatant, and obtain silver colloid.

5. The method for evaluating serum quality based on surface enhanced Raman spectroscopy according to claim 4, characterized in that: In step 2), the characteristic Raman peak is located at 400 cm -1 -1800cm -1 Raman frequency shift range.

6. The method for evaluating serum quality based on surface enhanced Raman spectroscopy according to claim 5, characterized in that: In step 2), a Raman spectrum scan of the silver colloid-enhanced serum sample is performed using an incident laser light source with a wavelength of 785 nm to determine the characteristic Raman peaks of the hemolytic, lipemic and icteric serum samples.

7. The method for evaluating serum quality based on surface enhanced Raman spectroscopy according to claim 6, characterized in that: In step 4), key molecules include hemoglobin, triglycerides and total bilirubin.

8. The method for evaluating serum quality based on surface enhanced Raman spectroscopy according to claim 7, characterized in that: In step 5), a Raman spectrum scan is performed on the serum sample to be tested using an incident laser light source with a wavelength of 785 nm.

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