CN116930143A - SERS probe Cu 2 Preparation method of O@Ag and method for establishing breast cancer cell parting model based on O@Ag - Google Patents

SERS probe Cu 2 Preparation method of O@Ag and method for establishing breast cancer cell parting model based on O@Ag Download PDF

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CN116930143A
CN116930143A CN202310508203.0A CN202310508203A CN116930143A CN 116930143 A CN116930143 A CN 116930143A CN 202310508203 A CN202310508203 A CN 202310508203A CN 116930143 A CN116930143 A CN 116930143A
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breast cancer
cancer cell
sers
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copper
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吴爱国
谢育娇
林杰
任勇
徐磊
张晨光
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Ningbo Institute of Material Technology and Engineering of CAS
Cixi Institute of Biomedical Engineering CIBE of CAS
University of Nottingham Ningbo China
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Ningbo Institute of Material Technology and Engineering of CAS
Cixi Institute of Biomedical Engineering CIBE of CAS
University of Nottingham Ningbo China
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Abstract

The invention belongs to the technical field of accurate diagnosis of breast cancer, and particularly relates to a SERS probe Cu 2 Preparation method of O@Ag and method for establishing breast cancer cell parting model based on O@Ag. SERS probe Cu constructed by the invention 2 O@Ag has the characteristics of high sensitivity and good stability. The SERS probe Cu 2 O@Ag can be combined with the breast cancer cell subtype under the condition of no mark, so that Raman spectrum data of the breast cancer cell subtype is obtained, a breast cancer cell subtype model is established through data processing, and the marker-free identification and judgment of the breast cancer cell subtype are realized.

Description

SERS probe Cu 2 Preparation method of O@Ag and method for establishing breast cancer cell parting model based on O@Ag
Technical Field
The invention belongs to the technical field of accurate diagnosis of breast cancer, and particularly relates to a SERS probe Cu 2 Preparation method of O@Ag and method for establishing breast cancer cell parting model based on O@Ag.
Background
The selection of clinical treatment strategies is greatly affected by different breast cancer cell subtypes, and the accurate identification of the breast cancer cell subtypes is important for the survival rate of breast cancer patients. Traditional methods of cell subtype identification are limited by complex procedures, lengthy processing times and high economic costs. In addition, breast cancer cannot be accurately detected by tumor markers in clinical samples, unlike lung cancer, colorectal cancer, prostate cancer, and the like, which have specific tumor markers. Therefore, it is important to develop new methods with accurate identification and efficient detection of breast cancer cell subtypes. Surface Enhanced Raman Spectroscopy (SERS) has received great attention in the field of cancer diagnosis due to its advantages of ultra-high sensitivity, good reproducibility and selectivity, and the like. By constructing a reliable label-free SERS probe, the abundant spectral information of the cell subtype can be obtained, so that accurate analysis is realized, and important reference is provided for breast cancer diagnosis. Conventional SERS substrates are comprised primarily of noble metals and semiconductors, but both have certain limitations. Noble metal substrates, such as gold, silver, etc., exhibit high signal sensitivity, but signal uniformity is difficult to ensure due to the presence of "hot spot" effects; the semiconductor substrate has good detection uniformity and selectivity, but the signal enhancement degree is not comparable with that of noble metals. Therefore, exploring a reliable composite SERS substrate, and jointly utilizing noble metal and semiconductor materials, obtaining a high-efficiency SERS substrate with high sensitivity, stability and selectivity is an important strategy for realizing accurate tumor cell analysis.
Disclosure of Invention
The invention aims to provide a SERS probe Cu 2 Preparation method of O@Ag and SERS probe Cu 2 O@Ag, SERS probe-based Cu 2 Method for establishing breast cancer cell parting model by O@Ag, breast cancer cell parting model and SERS probe Cu 2 The application of O@Ag in detecting breast cancer cell subtypes.
One object of the invention is achieved by the following technical scheme: SERS probe Cu 2 The preparation method of O@Ag comprises the following steps:
s1, adding polyvinylpyrrolidone (PVP) into copper salt solution, then adding sodium hydroxide solution, stirring to generate copper hydroxide, then adding first reducing agent solution, heating for reaction to obtain Cu 2 O；
S2, cu obtained in the step S1 2 O is prepared into suspension, a second reducing agent solution is added, and after stirring, a silver salt solution is added for reaction, thus obtaining Cu 2 O@Ag。
Preferably, in the above preparation method, the SERS probe Cu 2 Cu in O@Ag 2 The morphology of O is octahedron and or hexahedron.
Preferably, in the above preparation method, when Cu 2 When the morphology of O is octahedron, the molecular weight of polyvinylpyrrolidone is 30000-60000, and the molar ratio of polyvinylpyrrolidone to copper salt is 1: (5-80); when Cu is 2 When the morphology of O is hexahedron, the molecular weight of polyvinylpyrrolidone is 200000 ～ 1500000, and the molar ratio of polyvinylpyrrolidone to copper salt is 1: (120-600). In this document, the values in brackets include the end points.
Preferably, in the above preparation method, the SERS probe Cu 2 The mass fraction of Ag in the O@Ag is 1-10%. Preferably, in the above preparation method, the copper salt is one or more of copper chloride, copper nitrate, copper sulfate and copper acetate.
Preferably, in the above preparation method, the first reducing agent is one or more of ascorbic acid, glucose and hydroxylamine.
Preferably, the above preparationIn the method, the second reducing agent is sodium citrate and NaBH 4 One or more of hydrazine hydrate and ascorbic acid.
Preferably, in the above preparation method, the molar ratio of the copper salt to the first reducing agent is 1: (2-100).
Preferably, in the above preparation method, the molar ratio of silver salt to the second reducing agent is 1: (2-100).
Preferably, in the preparation method, the heating reaction temperature in the step S1 is 40-70 ℃ and the time is 4-6 h.
Preferably, in the above preparation method, the reaction of step S2 is carried out at 0 to 50℃for 0.1 to 10 hours.
The second object of the invention is achieved by the following technical scheme: SERS probe Cu 2 O@Ag, the SERS probe Cu 2 O@Ag is prepared by the following steps:
s1, adding polyvinylpyrrolidone into copper salt solution, then adding sodium hydroxide solution, stirring to generate copper hydroxide, then adding first reducing agent solution, heating for reaction to obtain Cu 2 O；
S2, cu obtained in the step S1 2 O is prepared into suspension, a second reducing agent solution is added, and after stirring, a silver salt solution is added for reaction, thus obtaining Cu 2 O@Ag。
Preferably, the SERS probe Cu 2 In O@Ag, ag is coated on Cu 2 O surface.
The third object of the present invention is achieved by the following technical scheme: SERS (surface enhanced Raman Scattering) -based probe Cu 2 A method for establishing a breast cancer cell typing model by o@ag, comprising the following steps:
(1) Culturing different breast cancer cell subtypes;
(2) Addition of SERS probes Cu in different breast cancer cell subtypes 2 Co-culturing O@Ag to obtain Raman spectrum data of different breast cancer cell subtypes;
(3) And performing machine learning-assisted Linear Discriminant Analysis (LDA) on the Raman spectrum data, performing dimension reduction processing and feature extraction, and then selecting more than 80% of features occupying the Raman spectrum data to establish a breast cancer cell parting model.
Preferably, the SERS probe Cu 2 Cu in O@Ag 2 The morphology of O is octahedron and or hexahedron.
Further preferably, the SERS probe Cu 2 Cu in O@Ag 2 O has the shape of an octahedron. Cu of octahedral morphology 2 The O@Ag has better SERS stability and sensitivity, and is more beneficial to improving the accuracy of the breast cancer cell parting model.
Preferably, the different breast cancer cell subtypes include four types: luminel type a, luminel type B, HER2 positive and triple negative.
Luminel type a is ER and/or PR positive, HER2 negative; luminel type B is ER and/or PR positive, HER2 positive; HER2 positive type is both ER and PR negative, HER2 positive; the triple negative type was ER, PR, HER2 negative.
Preferably, in the step (2), a silicon slice is placed in a cell culture dish, then different cultured breast cancer cell subtypes are passaged to the silicon slice in the cell culture dish, after 2-50 hours of culture, SERS probe Cu is added 2 O@Ag aqueous suspension is co-cultured for 2-10 hours. SERS probe Cu 2 The O@Ag aqueous suspension is SERS probe Cu 2 O@Ag is formed by dispersing in water.
Preferably, the Raman spectrum has a spectral range of 600-1800cm -1 。
The linear discriminant analysis assisted by machine learning is to edit program codes in a computer programming language, and construct a classification model comprising spectral data dimension reduction, feature extraction, training and testing, thereby realizing label-free identification and judgment of breast cancer cell subtypes.
Preferably, features occupying more than 80% of the Raman spectrum data (more than 80% of the linear discriminant feature values) are selected for linear discriminant analysis, and the established breast cancer cell parting model can reach the accuracy of 85% and more.
Preferably, after the breast cancer cell typing model is established, the detection efficacy of the breast cancer cell typing model is further estimated through an ROC curve.
The area under the curve (AUC) of the ROC curve can be used for evaluation, the AUC ranges from 0 to 1, and the closer the AUC value is to 1, the better the model efficacy of breast cancer cells.
The fourth object of the present invention is achieved by the following technical scheme: a breast cancer cell parting model which is established by the method.
The fifth object of the present invention is achieved by the following technical scheme: SERS probe Cu 2 The application of O@Ag in detecting breast cancer cell subtypes.
Preferably, the application comprises the steps of: after preparing the isolated tumor tissue into cell suspension, adding SERS probe Cu 2 And incubating O@Ag, detecting to obtain Raman spectrum data, and judging the breast cancer cell subtype of the tumor tissue according to the breast cancer cell subtype.
Compared with the prior art, the invention has the following beneficial effects:
1. the preparation method of the invention successfully prepares and obtains octahedral Cu by regulating and controlling the molecular weight and the addition amount of polyvinylpyrrolidone 2 O@Ag or hexahedral Cu 2 O@Ag；
2. The preparation method of the invention can effectively regulate and control Cu 2 The silver content in O@Ag is beneficial to ensuring the sensitivity and selectivity of the SERS substrate;
3. cu provided by the invention 2 O@Ag has excellent SERS stability and sensitivity, wherein octahedral Cu 2 O@Ag relative to hexahedral Cu 2 The O@Ag has better SERS detection performance, and is more beneficial to improving the accuracy of the breast cancer cell parting model;
4. cu provided by the invention 2 O@Ag can be combined with the breast cancer cell subtype under the condition of no mark, so that Raman spectrum data of the breast cancer cell subtype is obtained, a breast cancer cell subtype model is established through data processing, and the mark-free identification and judgment of the breast cancer cell subtype are realized;
5. cu using SERS probes 2 O@Ag, and then according to the established breast cancer cell parting model, can effectively identify the breast cancer tumor cell subtype, and is beneficial to the selection of clinical treatment schemesAlternatively, there is great potential in early screening and prognostic assessment of breast cancer.
Drawings
FIG. 1 is an octahedral Cu prepared in example 1 2 O particle scanning electron microscope and hexahedral Cu prepared in example 2 2 O particle scanning electron microscope images; wherein FIG. 1A is octahedral Cu prepared in example 1 2 O particle Scanning Electron Microscope (SEM) image, FIG. 1B shows hexahedral Cu prepared in example 2 2 O particle scanning electron microscope images;
FIG. 2 shows octahedral Cu prepared in example 1 2 O@Ag particle scanning electron microscope image and hexahedral Cu prepared in example 2 2 O@Ag particle scanning electron microscope; wherein FIG. 2A is octahedral Cu prepared in example 1 2 FIG. 2B is a scanning electron microscope image of O@Ag particles, showing hexahedral Cu prepared in example 2 2 O@Ag particle scanning electron microscope;
FIG. 3 shows the silver content of example 5 for a single Cu 2 High-resolution transmission electron microscope and energy spectrogram of elemental analysis of O@Ag particles, wherein 3A:0.5mL AgNO 3 Octahedral Cu prepared in amount 2 O@Ag，3B：1mL AgNO 3 Octahedral Cu prepared in amount 2 O@Ag，3C：1.5mL AgNO 3 Octahedral Cu prepared in amount 2 O@Ag；
FIG. 4 shows octahedral and hexahedral Cu in example 6 2 SERS detection performance of o@ag on 4NTP, where a: octahedral Cu 2 Detection limit of O@Ag-4NTP, 4B: octahedral Cu 2 O@Ag-4NTP(10 -5 M), 10 point spectrum, 4C: hexahedral Cu 2 Detection limit of O@Ag-4NTP, 4D: hexahedral Cu 2 O@Ag-4NTP(10 -5 M) 10 point spectrum;
FIG. 5 is an octahedral Cu of example 7 2 Raman spectrum data of four human breast cancer cells MCF-7, MDA-MB-231, SK-BR-3 and BT474 are processed by O@Ag, and the results of cell classification and corresponding ROC curves are obtained.
Detailed Description
The technical solution of the present invention will be further described by means of specific examples and drawings, it being understood that the specific examples described herein are only for aiding in understanding the present invention and are not intended to be limiting. And the drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure. Unless otherwise indicated, all materials used in the examples of the present invention are those commonly used in the art, and all methods used in the examples are those commonly used in the art.
Example 1
7.5g PVP (Mw=40000) was dissolved in 100mL of 0.01mol/L CuCl 2 -2H 2 O aqueous solution; then, naOH aqueous solution (10.0 mL,2.0 mol/L) was slowly added to the above solution, and the color was changed from pale blue to pale black; after stirring for 1 hour, an aqueous ascorbic acid solution (10.0 mL,2.0 mol/L) was further added dropwise to the mixed solution, the whole process was kept under stable stirring (700 rpm), and heated in a water bath at 50℃for 3 hours; centrifuging the obtained precipitate, and repeatedly washing with deionized water and absolute ethyl alcohol to remove residual polymer and inorganic ions; the resulting ethanol suspension was dried in an oven at 50℃for 3 hours to give Cu 2 O, the scanning electron microscope of which is shown in FIG. 1A, shows that the obtained Cu 2 The O shape is octahedron.
4.5mg of octahedral Cu was taken 2 The O powder is firstly dispersed in 3mL of absolute ethyl alcohol by ultrasonic to obtain Cu 2 O suspension, dissolving the above suspension in a mixture of ethanol/deionized water (20 mL/80 mL) with vigorous stirring; then aqueous sodium citrate (1.2 mL,30 mM) and fresh NaBH 4 The aqueous solution (1 mL,100 mM) was successively added dropwise to Cu 2 O in solution; after stirring for 5 minutes, agNO was added 3 The solution (1 mL,10 mM) was slowly added dropwise to the stirred mixture, the color of the solution turned pale yellow, indicating the formation of small Ag nanoparticles; after reacting for 2 hours at room temperature, centrifuging the reaction solution, and washing with deionized water and ethanol; finally, the collected particles (Cu 2 O@ag) was suspended in ethanol for further use and characterization.
FIG. 2A is a Cu film obtained in example 1 2 Scanning electron microscope images of O@Ag particles show that the Ag particles are successfully coated on octahedral Cu 2 O particle surface.
Example 2
Example 2 differs from example 1 in that example 2 incorporates 4.5g PVP (mw=1,300,000), the remainder being the same as example 1.
Prepared Cu 2 O scanning electron microscope image is shown in FIG. 1B, and it can be seen that Cu is obtained 2 The O shape is hexahedron.
FIG. 2B is a scanning electron microscope image of the Cu2O@Ag particles prepared in example 2, and it can be seen that the Ag particles were successfully coated on hexahedral Cu 2 O particle surface.
Example 3
15g PVP (Mw=58000) was dissolved in 100mL of 0.02mol/L CuCl 2 -2H 2 O aqueous solution; then, naOH aqueous solution (10.0 mL,4.0 mol/L) was slowly added to the above solution, and the color was changed from pale blue to pale black; after stirring for 2 hours, an aqueous ascorbic acid solution (10.0 mL,4.0 mol/L) was further added dropwise to the mixed solution, the whole process was kept under stable stirring (700 rpm), and heated in a water bath at 60℃for 4 hours; centrifuging the obtained precipitate, and repeatedly washing with deionized water and absolute ethyl alcohol to remove residual polymer and inorganic ions; the resulting ethanol suspension was dried in an oven at 60℃for 3 hours to give Cu 2 O, as known from a scanning electron microscope (not shown), cu is obtained 2 The O shape is octahedron.
6mg of octahedral Cu is taken 2 The O powder is firstly dispersed in 6mL of absolute ethyl alcohol by ultrasonic to obtain Cu 2 O suspension, dissolving the above suspension in a mixture of ethanol/deionized water (20 mL/80 mL) with vigorous stirring; then aqueous sodium citrate (2 mL,40 mM) and fresh NaBH 4 The aqueous solution (0.8 mL,100 mM) was successively added dropwise to Cu 2 O in solution; after stirring for 10 minutes, agNO was added 3 Solution (3 ml,10 mm) was slowly added drop-wise to the stirred mixture, the color of the solution turned pale yellow, indicating the formation of small Ag nanoparticles; after 3 hours of reaction at room temperature, centrifuging the reaction solution, and washing with deionized water and ethanol; finally, the collected particles (Cu 2 O@ag) was suspended in ethanol.
Example 4
1g PVP(mw=220,000) in 200ml of 0.01mol/L CuCl 2 -2H 2 O aqueous solution; then, naOH aqueous solution (20.0 mL,2.0 mol/L) was slowly added to the above solution, and the color was changed from pale blue to pale black; after stirring for 1 hour, an aqueous ascorbic acid solution (30.0 mL,2.0 mol/L) was further added dropwise to the mixed solution, the whole process was kept under stable stirring (800 rpm), and heated in a water bath at 55℃for 5 hours; centrifuging the obtained precipitate, and repeatedly washing with deionized water and absolute ethyl alcohol to remove residual polymer and inorganic ions; the resulting ethanol suspension was dried in an oven at 55deg.C for 3 hours to give Cu 2 O, as known from a scanning electron microscope (not shown), cu is obtained 2 The O shape is hexahedron.
7mg hexahedral Cu is taken 2 The O powder is firstly dispersed in 5mL absolute ethanol by ultrasonic to obtain Cu 2 O suspension, dissolving the above suspension in a mixture of ethanol/deionized water (30 mL/70 mL) with vigorous stirring; then aqueous sodium citrate (2 mL,30 mM) and fresh NaBH 4 The aqueous solution (2 mL,100 mM) was successively added dropwise to Cu 2 O in solution; after stirring for 7 minutes, agNO was added 3 The solution (2 ml,20 mm) was slowly added dropwise to the stirred mixture, the color of the solution turned pale yellow, indicating the formation of small Ag nanoparticles; after 3 hours of reaction at room temperature, centrifuging the reaction solution, and washing with deionized water and ethanol; finally, the collected particles (Cu 2 O@ag) was suspended in ethanol for further use and characterization.
Example 5
SERS probe Cu 2 In O@Ag, the contents of different silver are regulated and controlled
4.5mg of octahedral Cu was taken 2 The O powder is firstly dispersed in 3mL of absolute ethyl alcohol by ultrasonic to obtain Cu 2 O suspension, dissolving the above suspension in a mixture of ethanol/deionized water (20 mL/80 mL) with vigorous stirring; then aqueous sodium citrate (1.2 mL,30 mM) and fresh NaBH 4 The aqueous solution (1 mL,100 mM) was successively added dropwise to Cu 2 O in solution; after stirring for 5 minutes, different volumes (0.5, 1,1.5 mL) of AgNO can be added 3 Solution (10 mM) was slowly added dropwise with stirringAfter reacting for 2 hours at room temperature in the mixed mixture, centrifuging the reaction solution, and washing with deionized water and ethanol; collecting Cu to obtain 2 O@Ag particles.
FIG. 3 is a graph showing the control of silver content for a single Cu 2 The high-resolution transmission electron microscope and the energy spectrum of the O@Ag particle for elemental analysis show that as the silver nitrate dosage is increased from 0.5mL to 1mL and 1.5mL, the silver content is increased from 2.75% to 4.93% and 6.96% respectively. Therefore, the preparation method can regulate and control the silver content to a certain extent, and is beneficial to ensuring the sensitivity and the selectivity of the SERS probe.
Example 6
Octahedral and hexahedral Cu 2 SERS detection performance of O@Ag on 4-nitrophenol (4 NTP)
To illustrate Cu 2 SERS performance of o@ag raman signal molecule 4NTP powder was dissolved in ethanol and diluted at different concentrations. The resulting solution was immersed in Cu of example 1 and example 2 in the dark 2 O@Ag ethanol suspension for 8 hours to form Cu 2 O@Ag-4NTP; afterwards, the mixture was centrifuged to remove excess 4NTP; then, after drying at room temperature, the resulting suspension was dropped on a clean silicon wafer (5×5 mm) with a micropipette for raman detection; SERS spectra were collected by confocal microscopy raman spectroscopy at 532nm excitation light. FIG. 4 shows octahedral Cu 2 The LOD value of the detection 4NTP of the O@Ag serving as the SERS substrate reaches 10 -15 The lowest concentration of mol/L, hexahedral Cu 2 O@Ag is also detectable as low as 10 -14 mol/L4 NTP. To verify the repeatability of SERS spectra, cu was tested 2 O@Ag-4NTP at 10 -5 Raman spectra of mol/L show that 10 spectra are in 1080cm of characteristic peak -1 And 1572cm -1 The composition shows good stability. In addition, through calculation, cu 2 SERS enhancement factor of O@Ag to 4NTP detection reaches 10 14 . The above results indicate that Cu 2 O@Ag has good SERS stability and sensitivity, and octahedral Cu 2 O@Ag performs better at the detection limit.
Example 7
Embodiments with better Performance1 octahedral Cu 2 O@Ag is used for establishing a breast cancer cell parting model, and specifically comprises the following steps:
four different breast cancer cells were selected based on the expression discrimination of ER, PR, HER2 receptor: SK-BR-3 (HER 2 positive type, ER) - ，PR - ，HER2 + ) BT474 (Luminal B type, ER) + ，PR + ，HER2 + ) MCF-7 (Luminal A type, ER) + ，PR + ，HER2 - ) And MDA-MB-231 (triple negative, ER) - ，PR - ，HER2 - ) In vitro culture and detection were performed. Complete medium used for MCF-7 and MDA-MB-231 cells contained 90% DMEM, 10% FBS and 1% P/S, SK-BR-3 cells were cultured using 90% McCoy' S5A basal medium, 10% FBS and 1% P/S, and complete medium used for BT474 cells contained 10. Mu.g/mL insulin, 2mmol/L glutamine, 20% FBS and 1% P/S RPMI-1640. All cells were exposed to 5% CO at 37℃ 2 Culturing in an incubator.
Octahedral Cu of example 1 2 Centrifuging the ethanol suspension of O@Ag at 10000rpm to remove the organic reagent; the precipitate was dried at 50 ℃ and resuspended in water for further use. Placing clean silicon wafer (10×10mm) in cell culture dish for cell attachment and Raman detection, culturing the four breast cancer cells in culture dish for 24 hr, adding Cu 2 O@Ag aqueous suspension and co-cultivation for 4 hours. After washing with PBS, a laser light of 532nm was used as excitation source, which was detected by confocal micro-Raman spectroscopy.
LDA is a powerful machine learning technique for classifying according to the characteristics of a sample. In the application of raman spectroscopy, LDA can distinguish between different classes of cells by analyzing the dataset and extracting features. At 600-1800cm for each breast cancer cell -1 100 SERS spectrums in the spectrum range are taken as analysis objects, and the data are divided into a training set and a testing set by adopting a scikit-learn method and a train_test_split () algorithm with the aid of machine learning. Wherein 70 SERS spectrums of each breast cancer cell are used as a training set, after the dimensionality reduction treatment is carried out, a plurality of main features are extracted according to Raman spectrum data, and linear distinguishing features are selectedValues of 86.65% (characteristic of 86.65% of raman spectrum data) and 99.99% gave two-dimensional and three-dimensional discriminant analysis results (calculated and output using Python 3.6 programming language), respectively, to establish a breast cancer cell typing model with an accuracy of 85% (see fig. 5B and 5C, respectively). And taking 30 SERS spectrums of each breast cancer cell as a test set, and using the test set to verify the accuracy of the established breast cancer cell parting model, wherein the accuracy can reach 85% when the linear discrimination characteristic value is 86.65% and 99.99%. The test set has 120 pieces of data, and the predicted results of 0-21 pieces of data at 99.99% of the linear discriminant feature value are shown in the following table 1. As can be seen from FIG. 5, octahedral Cu 2 O@Ag can effectively distinguish four breast cancer cells.
TABLE 1
In linear discriminant analysis based on machine learning, model evaluation is very important. One common method of evaluating a model is to use ROC curves (subject work characteristics). ROC curves are a method of evaluating classifier performance by plotting the relationship between True Positive Rate (TPR) and False Positive Rate (FPR). In the ROC curve, the horizontal axis represents FPR, i.e., false positive rate, and the vertical axis represents TPR, i.e., true positive rate. The shape of the ROC curve is determined by the values of TPR and FPR at different thresholds. In machine learning based linear discriminant analysis, ROC curves can be used to evaluate the classification effect of a model on positive and negative examples. For example, in medicine, ROC curves may be used to evaluate the effect of a model classifying between a tumor patient and a healthy person, and if the model is able to correctly distinguish a tumor patient from a healthy person, and has a lower FPR and a higher TPR, the ROC curve should show a pattern near the upper left corner. In addition, the ROC curve can calculate its Area Under (AUC), which represents the overall quality of the model performance. AUC ranges from 0 to 1, with the model performing better the closer the value is to 1. Thus, ROC curves can be a useful method of machine learning model evaluation.
In the present application, the efficacy of the model was verified by using ROC curve, which is shown in fig. 5D, and the area under the curve AUC is more than 95%, which indicates that the linear discriminant analysis result is reliable.
The various aspects, embodiments, features of the invention are to be considered as illustrative in all respects and not restrictive, the scope of the invention being indicated only by the appended claims. Other embodiments, modifications, and uses will be apparent to those skilled in the art without departing from the spirit and scope of the claimed invention.
In the preparation method of the invention, the sequence of each step is not limited to the listed sequence, and the sequential change of each step is also within the protection scope of the invention without the inventive labor for the person skilled in the art. Furthermore, two or more steps or actions may be performed simultaneously.
Finally, it should be noted that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention's embodiments. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions in a similar manner, and need not and cannot fully practice all of the embodiments. While these obvious variations and modifications, which come within the spirit of the invention, are within the scope of the invention, they are to be construed as being without departing from the spirit of the invention.

Claims (10)

1. SERS probe Cu 2 The preparation method of O@Ag is characterized by comprising the following steps of:
s1, adding polyvinylpyrrolidone into copper salt solution, then adding sodium hydroxide solution, stirring to generate copper hydroxide, then adding first reducing agent solution, heating for reaction to obtain Cu 2 O；
S2, willCu obtained in step S1 2 O is prepared into suspension, a second reducing agent solution is added, and after stirring, a silver salt solution is added for reaction, thus obtaining Cu 2 O@Ag。
2. The method of claim 1, wherein the SERS probe Cu 2 Cu in O@Ag 2 The morphology of O is octahedron and or hexahedron.
3. The preparation method according to claim 1 or 2, wherein when Cu 2 When the morphology of O is octahedron, the molecular weight of polyvinylpyrrolidone is 30000-60000, and the molar ratio of polyvinylpyrrolidone to copper salt is 1: (5-80); when Cu is 2 When the morphology of O is hexahedron, the molecular weight of polyvinylpyrrolidone is 200000 ～ 1500000, and the molar ratio of polyvinylpyrrolidone to copper salt is 1: (120-600).
4. The method of claim 1, wherein the SERS probe Cu 2 The mass fraction of Ag in the O@Ag is 1-10%.
5. The preparation method according to claim 1, wherein the copper salt is one or more of copper chloride, copper nitrate, copper sulfate, and copper acetate;
and/or, the first reducing agent is one or more of ascorbic acid, glucose and hydroxylamine;
and/or, the second reducing agent is sodium citrate, naBH 4 One or more of hydrazine hydrate and ascorbic acid;
and/or the molar ratio of copper salt to first reducing agent is 1: (2-100);
and/or, the molar ratio of silver salt to second reducing agent is 1: (2-100);
and/or, the heating reaction temperature in the step S1 is 40-70 ℃ and the time is 4-6 h;
and/or, the reaction in the step S2 is carried out at the temperature of 0-50 ℃ for 0.1-10 h.
6. SERS probe Cu 2 O@Ag, characterized in that the SERS probe Cu 2 O@Ag is prepared by the following steps:
s1, adding polyvinylpyrrolidone into copper salt solution, then adding sodium hydroxide solution, stirring to generate copper hydroxide, then adding first reducing agent solution, heating for reaction to obtain Cu 2 O；
S2, cu obtained in the step S1 2 O is prepared into suspension, a second reducing agent solution is added, and after stirring, a silver salt solution is added for reaction, thus obtaining Cu 2 O@Ag。
7. SERS (surface enhanced Raman Scattering) -based probe Cu 2 A method for establishing a breast cancer cell parting model by O@Ag, which is characterized by comprising the following steps of:
(1) Culturing different breast cancer cell subtypes;
(2) Addition of SERS probes Cu in different breast cancer cell subtypes 2 Co-culturing O@Ag to obtain Raman spectrum data of different breast cancer cell subtypes;
(3) And performing machine learning-assisted linear discriminant analysis on the Raman spectrum data, performing dimension reduction treatment and feature extraction, and then selecting features occupying more than 80% of the Raman spectrum data to establish a breast cancer cell parting model.
8. The method of claim 7, wherein after establishing the breast cancer cell typing model, the efficacy of the breast cancer cell typing model is further evaluated by ROC curve.
9. A breast cancer cell parting model, characterized in that it is established by the method of claim 7.
10. SERS probe Cu 2 The application of O@Ag in detecting breast cancer cell subtypes.
CN202310508203.0A 2023-05-08 2023-05-08 SERS probe Cu 2 Preparation method of O@Ag and method for establishing breast cancer cell parting model based on O@Ag Pending CN116930143A (en)

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