WO2011130938A1

WO2011130938A1 - Detection method for human plasma by surface enhanced raman spectroscopy combined with principal component analysis

Info

Publication number: WO2011130938A1
Application number: PCT/CN2010/074142
Authority: WO
Inventors: 冯尚源; 陈荣; 林居强; 陈冠楠; 李永增; 黄祖芳; 陈杰斯; 曾海山
Original assignee: 福建师范大学; 加拿大Bc癌研究中心
Priority date: 2010-04-19
Filing date: 2010-06-21
Publication date: 2011-10-27
Also published as: CN101806740B; CN101806740A

Abstract

A detection method for human plasma by surface enhanced Raman spectroscopy combined with principal component analysis is provided. The method includes the following steps: preparing silver colloid by deoxidization using hydroxylamine hydrochloride; mixing uniformly the silver colloid with a human plasma sample in physiological state in equal volumes and incubating the mixture for two hours at 4℃; exciting the human plasma sample by using the laser beams with different polarization states and performing surface enhanced Raman spectroscopy for the plasma; establishing the database of surface enhanced Raman spectra for the plasma; obtaining the scatter diagram distribution corresponding to the surface enhanced Raman spectra of plasma from different persons; and furthermore performing principal component analysis combined with linear discrimination analysis. The plasma of a patient suffering from cancer can be analyzed and distinguished from that of a healthy person by the method.

Description

Surface enhanced Raman spectroscopy combined with principal component analysis and detection method for human plasma

The invention relates to a human body plasma surface enhanced Raman spectroscopy combined with multivariate analysis and detection method, more specifically, the human blood is subjected to plasma centrifugation under aseptic conditions to obtain a human plasma solution under physiological conditions, and then through surface enhancement. Raman spectroscopy is used to detect plasma SERS signals and to perform statistical analysis using multivariate analysis techniques. It belongs to the field of biomedicine.

Background technique

Raman spectroscopy can provide the vibrational spectrum of molecules with fine structure information and characteristic fingerprints of molecules. Raman spectroscopy has become one of the important technologies for article identification and molecular detection. Raman spectroscopy is applied to life science research to analyze human tissue or cell structure or composition by detecting Raman spectra of biological macromolecules such as proteins, nucleic acids, lipids, etc. in human tissues or cells. Change has become a hot topic in related research fields. However, the conventional Raman spectrum has a weak signal and is susceptible to interference from autofluorescence. Therefore, it is necessary to enhance and amplify the Raman signal. Surface-enhanced Raman spectroscopy (SERS) is one of the commonly used means of enhancing Raman signals. This technology utilizes the effect of adsorption of molecules on the surface of certain rough metals (such as Au, Ag, Cu, Pt, etc.), increasing the Raman scattering intensity of these molecules by 10 ⁴ to 10 ¹⁴ times, and effectively inhibiting autofluorescence. signal. SERS technology has the characteristics of high spatial resolution, high sensitivity and rich information content, and has been widely used in the fields of material identification and molecular structure detection.

Chirality is a basic attribute of nature. In nature, many molecules often have two structural forms that are mirror images of each other but cannot completely overlap. These two forms of molecules are like human right and left hands. Molecules are called enantiomers or optical isomers. Life activities are closely related to the chirality of biomolecules. For example, more than 20 amino acids required in the human body are only glycine, which is not chiral, and others are chiral; for example: the specificity of the enzyme-catalyzed reaction reflects The requirements for molecular stereochemistry, many other processes are also infiltrated by the effects of molecular stereoscopic factors. When a biomolecule develops a lesion, the spatial three-dimensional structure of the biomolecule may undergo a slight change, further causing a change in the chirality of the biomolecule. Small changes in the spatial structure of the living molecules are difficult to detect with ordinary unpolarized lasers. The super-helical electromagnetic field generated by the circularly polarized laser can sensitively detect small changes in the chirality of biomolecules. Therefore, the use of circularly polarized laser to detect changes in the chirality of biological molecules is of great significance for revealing the mysteries of life and the information of lesions.

At present, domestic and foreign scholars use Raman spectroscopy to perform blood detection mainly by direct Raman detection of blood and plasma samples, but they have not achieved satisfactory results. The shortcoming of these studies is that the conventional Raman spectral signal is weak, self-body The fluorescence interference is strong, and the conventional laser Raman detection requires a large excitation light power and a long time, which is easy to damage the sample. The use of non-polarized laser, linearly polarized laser or circularly polarized laser as excitation light, silver-gel as a reinforcing matrix surface-enhanced Raman spectroscopy combined with principal component analysis for human plasma detection and analysis, has not been reported.

Summary of the invention

The object of the present invention is to provide a detection method using plasma surface enhanced Raman spectroscopy combined with principal component analysis for the current deficiencies and problems in blood Raman spectroscopy.

It firstly performs plasma centrifugation on human blood under aseptic conditions to obtain a human plasma solution under physiological conditions, and uses SERS detection means to detect surface enhanced Raman spectroscopy of human plasma.

The technical solution is adopted for the purpose of achieving the present invention as follows:

(1) extracting human blood and adding an anticoagulant to perform centrifugation under aseptic conditions to obtain a human plasma sample under physiological conditions, and preparing a silver sol by reduction with hydroxylamine hydrochloride;

(2) Silver sol and human plasma samples were uniformly mixed in an equal volume and incubated at 4 ° C for two hours for plasma surface enhanced Raman spectroscopy;

(3) Plasma surface enhanced Raman spectroscopy measurements can be performed using lasers of different polarization states to stimulate human plasma samples;

(4) Establish a plasma surface enhanced Raman spectroscopy database, and obtain the scatter plot distribution corresponding to the surface enhanced Raman spectra of different human plasmas by principal component analysis and T test.

According to the above steps, a plasma surface-enhanced Raman spectroscopy database was established. Principal component analysis and T-test were used to obtain the scatter plot distribution corresponding to the surface-enhanced Raman spectrum of normal human and diseased patients, and further analyzed and discriminated by LDA. Human and diseased patients' plasma.

The plasma surface enhanced Raman spectroscopy described in the step (2) is that a mixed solution of human plasma and silver gel is added to an aluminum sheet having a purity of 99.99% for surface enhanced Raman measurement, and the focus is 450-4000 cm- ¹ wave number. range.

Step (3) The lasers of different polarization states can be used for routine Raman spectroscopy analysis of human plasma samples, purified proteins, DNA, and RNA samples.

The laser of the different polarization states in the step (3) may be a non-polarized laser, a linearly polarized laser, a left-handed circularly polarized laser or a right-handed circularly polarized laser. Information about chiral changes in biomolecules can be obtained using circularly polarized laser excitation.

The plasma surface enhanced Raman spectroscopy database described in the step (4) is composed of plasma surface enhanced Raman spectroscopy data of different human bodies; before the plasma surface enhanced Raman spectroscopy database is established, the polymorphism of the SERS spectra of different human plasmas is first used. The fluorescence background is eliminated and the area normalization is performed to remove the influence of inconsistent experimental conditions such as fluctuations in excitation light power and aggregation.

The plasma substitute according to the present invention may be urine, serum, lymph, cerebrospinal fluid, urine, Saliva, tears, sweat, cell extracts, tissue homogenates, vaginal secretions or semen, can also be purified protein, DNA or RNA samples.

The pretreatment process of the plasma sample of the invention takes 2 hours and the detection time is only 10 seconds. Therefore, the activity of the biomolecule in the plasma is ensured during the measurement process, and the invention has the advantages of simple and rapid, and high reliability. And the SERS technology makes the sample obtain a strong Raman spectrum signal at a very low laser power, and the spectral signal repeatability is good, avoiding the carbonization and damage caused by the high power laser to the biological sample. Based on plasma surface enhanced Raman spectroscopy of different people, a plasma surface enhanced Raman spectroscopy database was established. Using PCA-LDA multivariate statistical analysis method, a new method for analyzing plasma surface enhanced Raman spectroscopy in normal human plasma and disease patients was provided. Methods.

The invention has the advantages of using a non-polarized laser, a linearly polarized laser and a circularly polarized laser as excitation light for surface enhanced Raman spectroscopy, and can obtain high quality plasma surface enhanced Raman signal, which can be obtained in different human plasma molecules. Information on the changes in chirality of biomolecules. The scatter plot distribution corresponding to the surface-enhanced Raman spectroscopy of different human plasmas was obtained by principal component analysis. It provides important reference for the rapid and non-destructive detection of plasma-enhanced Raman spectroscopy in different human plasmas.

DRAWINGS

Figure 1 is a graph showing the average surface-enhanced Raman spectrum of Group A plasma measured by the present invention;

Figure 2 is a graph showing the average surface-enhanced Raman spectrum of Group B plasma measured by the present invention;

FIG 3 of the present invention is used to calculate the parameters _ai, 04, a ₈ required first, fourth and eighth main component spectra;

Figure 4 is a distribution diagram of the scattered surface of the group A plasma and group B plasma surface enhanced Raman spectroscopy PCA drawn by PC1 and PC4. The black circle in the figure represents the surface enhanced Raman spectrum of group A human plasma, and the black triangle tip represents Plasma surface enhanced Raman spectroscopy of group B;

Figure 5 is a distribution diagram of the scattered surface of the group A plasma and the B group plasma surface enhanced Raman spectrum PCA drawn by PC1 and PC8. The black circle in the figure represents the surface enhanced Raman spectrum of the group A human plasma, and the black triangle tip represents Plasma surface enhanced Raman spectroscopy of group B;

Figure 6. is a comparison of the average SERS spectra of the first human plasma under the excitation of unpolarized laser, left-handed circularly polarized laser and right-handed circularly polarized laser;

Figure 7. is a comparison of the average SERS spectra of the second person's plasma under the excitation of unpolarized laser, left-handed circularly polarized laser and right-handed circularly polarized laser;

Figure 8. A posteriori probability distribution of plasma SERS spectra from 33 normal and 32 gastric cancer patients after PCA-LDA analysis. The P value corresponding to the discriminant line is equal to 0.5.

detailed description The invention is described below in terms of specific implementation details:

(1) Pretreatment of silver sol and pretreatment of plasma samples

4.5 ml of sodium hydroxide solution (0.1 mol) was added to 5 ml of hydroxylamine hydrochloride solution (0.06 mol), and then the mixture was quickly added to 90 ml of silver nitrate solution (0.01 lmol), and uniformly stirred until uniform milk was obtained. Gray solution. Centrifuge at 10,000 rpm for 10 minutes, layer the silver gel, discard the supernatant, and remove the concentrated silver sol. Store at room temperature in the dark.

Under sterile conditions, the blood of different people's overnight fastness was taken from 7:00 to -8 in the morning, and EDTA was added to prevent blood from coagulating and centrifugation (2000 rpm) for 15 minutes. The upper serum was discarded and the lower plasma was taken as a sample. Two different sets of human plasma samples (combined as Group A and Group B) were obtained by this method. Use a pipette to remove each sample of plasma from Group A 200 μl into a sterile sterile tube. A 200 μ 各 each of the previously prepared centrifuged silver sols was added to the test tube by a pipette, and the volume ratio of plasma to silver sol was 1:1. The mixed solution was thoroughly stirred to mix the plasma with the silver sol as uniformly as possible to prepare a plasma-silver sol mixed solution of the sputum group. Pipette each sample of 200 μl from the Group B using a pipette into a sterile sterile tube. The pipette was used to add 200 μl of the previously prepared centrifuged silver sol to the test tube, and the volume ratio of plasma to silver sol was 1:1. The mixed solution was thoroughly stirred, and the plasma and the silver sol were mixed as uniformly as possible to prepare a plasma-silver sol mixed solution of the sputum group. All the mixed solutions prepared were placed in a refrigerator set at 4 ° C for two hours.

(II) Surface enhanced Raman spectroscopy to detect sample processes

The mixed plasma-silver sol mixture was transferred to a 99.99% aluminum sample stage with a pipette, dried naturally, and the sample was detected by Raman spectroscopy. The excitation light used was an unpolarized laser or a linearly polarized laser. Left-handed circularly polarized laser or right-handed circularly polarized laser, focusing on the detection of 450_4000cm- ¹ wavenumber range, to obtain surface enhanced Raman spectrum of plasma. Set the measurement parameters: integration time 10s, excitation wavelength 785 calendar, excitation light power 5mw.

(3) Principal component analysis of surface enhanced Raman spectroscopy of different human plasma

Principal component analysis of different plasmas requires the establishment of a plasma surface enhanced Raman spectroscopy database. Before establishing the spectral database model, the surface-enhanced Raman spectroscopy of plasma should be normalized to remove the influence of inconsistent experimental conditions such as excitation light power fluctuation and aggregation difference. In the establishment of the database, taking into account some individual differences between different people, in order to ensure statistical, it is necessary to collect a sufficient number of surface-enhanced Raman spectral data of different human plasma. The plasma surface enhanced Raman spectroscopy database consists of plasma surface enhanced Raman spectroscopy data from different human bodies. Based on the establishment of the database, PCA analysis is used to obtain the score corresponding to each principal component (PC score), and then the Independent-Sample T test in SPSS is used to select the three PCA scores with the most significant differences to further draw. Scatter plot distribution of plasma surface enhanced Raman spectra of different groups in group A and group B. The first step in establishing a plasma SERS database is to normalize the spectrum. Since the information in the spectrum mainly comes from the relative intensity of each peak, the absolute intensity of the peak is related to the fluctuation and aggregation of the laser power, and normalization can eliminate this effect. The present invention normalizes the method by normalizing the spectral lines by the integrated area. The second step in building the model is to plot the average spectrum of Group A and the average spectrum of Group B that make up the database. The average spectral calculation formula is:

< _r (v)>=l3⁄4r _m (v), where r ) is the average spectrum. For the sake of convenience, we use the subscript m to mark different spectra, using nm=l

The targets i and j represent wave numbers.

Next, using the standard algorithm of principal component analysis, the main element spectrum describing the spectral variation characteristics is established. First, calculate the covariance matrix of each wave number after normalization, 艮

^ij =∑ -^—[r _m Υ < r(v _t ) >] · ( _; . Y < r( _Vj )>J ≤ ,7≤ N

... -l ^l calculates the eigenvalues and eigenvectors of the matrix. Since only a few eigenvalues ranked first in the order of magnitude have higher values than noise, the latter can be ignored because they are weaker than noise. Therefore we only take the first 20 eigenvalues { Λ, 2... ₂ . } and its corresponding eigenvector { ^(v), ^^).... P ₂ . f)} constitute the main element spectrum. Due to the orthogonal normality of the eigenvectors, the linear decomposition of the main element spectrum can be performed on the calibration spectrum, ie: a _n = [r(vi )- < r(T) >] - Ρ _η (ν, ) , 1 < « < 20

i=lr(v) =< r(v) > a _n P _n (v) . where r ) is the normalized spectrum, α „ is the expansion coefficient (score). { P„ f )} The basic set of rendezvous, Zhang Cheng into a new space, called the main element space, this space can be obtained from the previous matrix ^ ' spatial change. After the above changes, each spectrum is mapped to a point in the main element space.

The following is the specific calculation process for applying PCA analysis:

(1) First, different human plasma SERS spectra were fitted using a polynomial to eliminate the fluorescent background;

(2) normalizing the SERS spectra of different human plasmas that have eliminated the fluorescent background;

(3) Using SPSS software to perform PCA on different human plasma SERS spectra processed by (1) and (2)

Analysis

(4) Using the T test to obtain the three most significant differences in PCA scores and plot the scatter plot distribution; After repeated experiments, under the excitation of non-polarized laser light, the present invention confirmed by the T test that the three main components of the main component 1, the main component 4, and the main component 8 after PCA analysis have significant differences. We further draw a scatter plot of principal component 1 and principal component 4, principal component 1 and principal component 8.

The above non-polarized laser light may be replaced by a linearly polarized laser, a left-handed circularly polarized laser or a right-handed circularly polarized laser.

The present inventors have found that for the study of plasma SERS spectra of gastric cancer patients and healthy people, the discrimination effect by left-handed circularly polarized laser excitation is better than that of linearly polarized lasers and non-polarized lasers.

(iv) Plasma SERS database The specific steps for PCA analysis are as follows:

1. Prepare a silver sol-plasma mixed solution according to step (1) for different human plasmas;

2. Plasma surface enhanced Raman spectroscopy was measured according to step (2); plasma spectra of not less than 30 samples were measured for Group A and Group B, respectively.

3. Normalize the area of each plasma SERS spectrum.

4. For the plasma SERS spectra in the spectral database, each principal component score is calculated using the PCA standard algorithm. .

5. The main components using the T test to calculate the most significant differences are PC1, PC4, and PC8.

6. Surface-Enhanced Raman Spectroscopy of Different Human Plasmas The distribution of the dot map of PCA is the measurement result of the present invention. (5) Principal component analysis and linear discriminant analysis (PCA-LDA) for surface-enhanced Raman spectroscopy of plasma in normal and diseased patients

Linear Discriminant Analysis (LDA) is also known as Fisher Linear Discriminant (Fisher Linear Discriminant,

FLD), its purpose is to extract the most discriminative low-dimensional features from the high-dimensional feature space. These features can help to gather all the samples of the same category, and the different categories of samples are separated as much as possible. between samples largest class scatter S within the sample, and wherein the ratio of class _B dispersion of _W S. The intra-class dispersion matrix is to find the intra-class average for each class of training samples, and then subtract the mean of each class from each sample. The definition of the dispersion matrix S _B between the sample classes and the dispersion matrix S _w in the sample class is as follows: S _B = - μ) - μ) ^τ

S _w =∑ ∑(X _K - μ, Χ _K - μ, ) where c is the number of categories, is the prior probability, is the mean of the α-type samples, and is a sample belonging to the i-th class.

The projection line obtained by the PCA method makes the projected sample unrepeatable, and the projection line obtained by the LDA method makes the projected sample still have good separability. After projection, the samples of different categories in the low-dimensional space should be separated as much as possible. At the same time, it is hoped that the internal samples of each category are as dense as possible. That is, the larger the dispersion between the sample classes, the better, and the dispersion within the sample class. The smaller the better. Therefore, if S is attached to a non-singular matrix, the optimal projection direction W is The orthogonal feature vectors with the largest ratio of the determinant between the sample class dispersion matrix and the sample class internal dispersion matrix are obtained. Therefore, the best mapping function, the Fisher criterion, is defined as:

W ^T S _B W

W = arg max

\w ^T s _w w

Both LDA and PCA reduce the dimension by finding the feature vector. In the process of solving the problem, LDA grasps the discriminant feature of the sample, and PCA captures the description feature of the sample. We can see that LDA and PCA have their own strengths and disadvantages. They have different statistical characteristics and are suitable for different specific situations. Therefore, it is very necessary to combine LDA and PCA algorithms.

The following is the calculation process of the PCA-LDA algorithm:

(1) Firstly, the plasma SERS spectrum of normal healthy people and the plasma SERS spectrum of cancer patients are fitted by polynomial to eliminate the fluorescent background;

(2) Normalize the area of the SERS spectra of healthy people who have eliminated the fluorescent background and cancer;

(3) PCS analysis of plasma SERS spectra of healthy people treated with (1) and (2) and cancer patients using SPSS software;

(4) Based on this, using the Independent-Sample T test in SPSS, select the three PCA scores with the most significant differences for further LDA analysis;

(5) Calculate the posterior probability P using the nearest neighbor criterion, P is greater than 0.5 for normal healthy people, P is less than 0.5

For cancer patients, the diagnosis can be completed.

After PCA combined with LDA analysis and calculation, the present invention determines that the best straight line for discriminating between the cancer patient and the normal human plasma surface enhanced Raman spectrum is the posterior probability P = 0.5. At this point, the equation actually defines a two-dimensional coordinate plane consisting of the posterior probability and the number of samples. This line effectively separates the plasma point set distribution of cancer patients from the normal human plasma point set distribution. This line is equal to a threshold set, which is the criterion.

Using the above criteria, the present invention has a sensitivity and specificity of more than 90% for plasma spectral discrimination in the surface enhanced Raman spectroscopy database.

All data and values of the present invention are measured by actual measurements, and the identification of plasma is objectively given by surface-enhanced Raman spectroscopy data, independent of the subjective judgment of the observer. Plasma sample preparation can be completed in 2 hours and the spectral measurement time can be controlled in two minutes. Principal component analysis of the spectrum can be obtained in 10 minutes. Therefore, human plasma surface enhanced Raman spectroscopy combined with principal component analysis has a very broad application prospect in the field of biomedicine.

The invention is further described below by several specific examples of the invention, but the invention is not limited thereto.

Example 1 The overnight fasting blood of two different groups of people between 7 and 8 o'clock in the morning was taken, and EDTA was added to prevent blood coagulation and centrifugation (2000 rpm) for 15 minutes. The upper serum was discarded and the lower plasma was taken as a sample. The first group of human plasma was a total of 33, and was grouped as group A. A total of 43 plasma samples from the second group were grouped into Group B. 200 μ 血浆 of each sample was removed from the group A using a pipette and added to the sterile-sterilized test tube. A 200 μ 各 each of the previously prepared centrifuged silver sols was added to the test tube by a pipette, and the volume ratio of plasma to silver sol was 1:1. The mixed solution was thoroughly stirred, and the plasma and the silver sol were mixed as uniformly as possible to prepare a plasma-silver sol mixed solution of the sputum group. Pipette each sample of 200 μl from the Group B using a pipette and add to the sterile-sterilized test tube. The pipette was used to add 200 μ 各 each of the previously prepared centrifuged silver sols to a test tube, and the volume ratio of plasma to silver sol was 1:1. The mixed solution was thoroughly stirred, and the plasma and the silver sol were mixed as uniformly as possible to prepare a plasma-silver sol mixed solution of the sputum group. All the mixed solutions prepared were placed in a refrigerator set at 4 ° C for two hours.

The mixed plasma-silver sol mixture was transferred to a purity sample of 99.99% aluminum by a pipette, and dried naturally. The sample was detected by a confocal Raman spectrometer, and the range of 450_4000 cm- ¹ wave was detected to obtain plasma. Surface enhanced Raman spectroscopy. Set the measurement parameters: The integration time is 10s, the excitation wavelength is 785nm, and the excitation light power is 5mw. The excitation light used to measure the SERS spectrum is an unpolarized laser.

Before establishing a plasma surface-enhanced Raman spectroscopy database, the surface-enhanced Raman spectroscopy of plasma should be normalized to remove the effects of inconsistent experimental conditions such as fluctuations in excitation light power and aggregation. Based on the database, the average spectrum of Group A in the database (as shown in Figure 1) and the average spectrum of Group B (as shown in Figure 2) are plotted. Principal component analysis is used to obtain the score corresponding to each principal component (PC score), and then use the Independent-Sample T test in SPSS to select the three most significant differences in PCA scores, namely PC1, PC4 and PC8, to further draw. The scatter plot distribution of plasma surface enhanced Raman spectra of group A and group B was obtained. Figure 3 is a first, fourth and eighth principal component spectrum, Figure 4 is a scatter plot distribution of PC1 and PC4, and Figure 5 is a scatter plot of PC1 and PC8.

Example 2

The overnight fasting blood of two different people between 7:00 and 8:00 in the morning was taken, and EDTA was added to prevent blood clotting and centrifugation (2000 rpm) for 15 minutes. The upper serum was discarded and the lower plasma was taken as a sample. The sample plasma 200 μl was removed from the first plasma sample using a pipette and added to the sterile-sterilized test tube. A 200 μ 各 each of the previously prepared centrifuged silver sols was added to the test tube by a pipette, and the volume ratio of plasma to silver sol was 1:1. The mixed solution was thoroughly stirred to mix the plasma with the silver sol as uniformly as possible to prepare a first plasma-silver sol mixed solution. A 200 μl sample of each of the sample plasma was removed from the second human plasma using a pipette and added to the sterile-sterilized test tube. Then, 200 μ ΐ each of the previously prepared centrifuged silver sols was added to the test tube by a pipette, and the volume ratio of plasma to silver sol was 1:1. The mixed solution was thoroughly stirred, and the plasma and the silver sol were mixed as uniformly as possible to prepare a control silver sol-plasma mixed solution. All mixed solutions prepared Incubate for two hours in a refrigerator set at 4 °C.

The mixed silver sol-plasma mixture was transferred to a purity sample of 99.99% aluminum by a pipette, dried naturally, and the sample was detected by a confocal Raman spectrometer. The excitation light used to measure the SERS spectrum was used separately. Unpolarized laser, left-handed circularly polarized laser and right-handed circularly polarized laser. Focus on detecting the range of 450_1730cm- ¹ wavenumber to obtain surface enhanced Raman spectra of plasma. Set the measurement parameters: The integration time is 10s, the excitation wavelength is 785nm, and the excitation light power is 5mw. The test obtained two sets of data as shown in Figure 6 and Figure 7. From the average SERS comparison of the excitation light of the two individuals in different polarization states, especially in the comparison of the shaded band range, it can be seen that the use of circularly polarized light excitation can obtain more information about the molecular chiral changes than the unpolarized light excitation. . It is shown that the use of circularly polarized laser to detect changes in the chirality of biomolecules is of great significance for revealing the mysteries of life and the information of lesions.

Example 3

During the morning between 7 and -8 in the morning, two groups of people with different health conditions were given fasting blood overnight. EDTA was added to prevent blood clotting and centrifugation (2000 rpm) for 15 minutes. The upper serum was discarded and the lower plasma was taken as a sample. The first group of normal healthy people had a total of 33 plasma samples, which were grouped into group A. A total of 32 patients with gastric cancer in the second group were enrolled in group B. They were removed from group A using a pipette and 200 μl of each sample was added to the sterile-sterilized test tube. A 200 μ 各 each of the previously prepared core silver sols was added to the test tube by a pipette, and the volume ratio of plasma to silver sol was 1:1. The mixed solution was thoroughly stirred, and the plasma and the silver sol were mixed as uniformly as possible to prepare a plasma-silver sol mixed solution of the sputum group. Pipette each sample of each plasma 200 μl from the group B using a pipette into a sterile-sterilized test tube. The previously prepared centrifuged silver sol was added to the test tube with a pipette of 200 μM each, and the volume ratio of plasma to silver sol was 1:1. The mixed solution was thoroughly stirred, and the plasma and the silver sol were mixed as uniformly as possible to prepare a plasma-silver sol mixed solution of the sputum group. All the mixed solutions prepared were placed in a refrigerator set at 4 ° C for two hours.

The mixed plasma-silver sol mixture was transferred to a purity sample of 99.99% aluminum by a pipette, and dried naturally. The sample was detected by a confocal Raman spectrometer, and the range of 450_4000 cm- ¹ wave was detected to obtain plasma. Surface enhanced Raman spectroscopy. Set the measurement parameters: The integration time is 10s, the excitation light wavelength is 785nm laser, and the excitation light power is 5mw. The excitation light used to measure the SERS spectrum is a left-handed circularly polarized laser.

Before establishing the plasma surface enhanced Raman spectroscopy database, the surface-enhanced Raman spectroscopy of plasma should be normalized to remove the influence of inconsistent experimental conditions such as fluctuations in excitation light power and aggregation. Based on the establishment of the database, the principal component analysis is used to obtain the score corresponding to each principal component (PC score), and then the Independent-Sample T test in SPSS is used to select the three PCA scores with the most significant difference, namely PC1. PC5 and PC13, further use LDA analysis to obtain the posterior probability P value corresponding to each sample, and further draw the scatter plot distribution and discriminant line of posterior probability, as shown in Figure 8, the black circle in the figure represents Normal healthy human plasma, black triangle tip represents gastric cancer Patient plasma. The discriminant line equation is P=0.5, and the P value distributed above the discriminant line is greater than 0.5 for a normal healthy person. The P value below the discriminant line is less than 0.5 for the gastric cancer patient's plasma. The sensitivity of plasma discrimination for gastric cancer patients was 90.7%, and the specificity was 97%.

Claims

Claim

A method for surface enhanced Raman spectroscopy combined with principal component analysis of human plasma, characterized in that the method consists of the following three steps:

(3) Establish a plasma surface-enhanced Raman spectroscopy database, and obtain the scatter plot distribution corresponding to the surface-enhanced Raman spectra of different human plasmas by principal component analysis and T-test.

2 . The method for detecting surface Raman spectroscopy combined with principal component analysis of human plasma according to claim 1 , wherein: according to the step, establishing a plasma surface enhanced Raman spectrum database of normal humans and disease patients, using a principal component. Analytical and T-tests were used to obtain the scatter plot distribution corresponding to the surface-enhanced Raman spectrum of the plasma of normal people and disease patients, and further analyzed and discriminated by LDA to distinguish the plasma of normal people and disease patients.

3. The method of claim 1, wherein the plasma surface enhanced Raman spectroscopy is to measure human plasma and silver sol. The surface was subjected to surface-enhanced Raman spectroscopy on an aluminum sheet having a purity of 99.99%, and a range of 450-4000 cm- ¹ wave number was mainly detected.

4. The method of claim 1, wherein the plasma surface enhanced Raman spectrum database is enhanced by plasma surface of different human bodies. Raman spectroscopy detects data composition.

The method for detecting surface-enhanced Raman spectroscopy combined with principal component analysis of human plasma according to claim 1 or 3, characterized in that: prior to the establishment of the plasma surface enhanced Raman spectroscopy database, different human plasma SERS is performed. The spectra were polynomial fitted to eliminate the fluorescent background and normalize the area.

6. A method for laser-excited detection of surface enhanced Raman spectroscopy combined with different polarization states of human plasma, characterized in that: the specific steps are as follows:

(1) extracting human blood and adding an anticoagulant to perform centrifugation under aseptic conditions to obtain a human plasma sample under physiological conditions, and preparing a silver sol by reduction with hydroxylamine hydrochloride; (2) Silver sol and human plasma samples were uniformly mixed in an equal volume and incubated at 4 ° C for two hours for plasma surface enhanced Raman spectroscopy;

(3) Plasma surface enhanced Raman spectroscopy uses lasers of different polarization states to excite human plasma samples;

(4) Establish a plasma surface enhanced Raman spectroscopy database, and obtain the scatter plot distribution corresponding to the surface enhanced Raman spectra of different human plasmas by principal component analysis.

7. The method of claim 6, wherein the human plasma surface enhanced Raman spectroscopy combined with different polarization state laser excitation detection methods is characterized in that: according to the steps, establishing a plasma surface enhanced Raman spectrum database of normal humans and disease patients, using a principal component Analytical and T-tests were used to obtain the scatter plot distribution corresponding to the surface-enhanced Raman spectrum of the plasma of normal people and disease patients, and further analyzed and discriminated by LDA to distinguish the plasma of normal people and disease patients.

8 . The method of claim 6 , wherein the different polarization states of the laser are non-polarized laser, linearly polarized laser, left-handed circularly polarized laser or Right-handed circularly polarized laser.

9. The method of claim 6, wherein the different polarization states of the laser are used to sample human plasma samples, purified proteins, DNA or RNA samples. Perform conventional Raman spectroscopy analysis.

10 . The method according to claim 6 , wherein the plasma substitute is urine, serum, lymph, cerebrospinal fluid, saliva, or the like. Tears, sweat, cell extracts, tissue homogenates, vaginal secretions or semen can also be purified protein, DNA or RNA samples.