A new method for rapid detection and evaluation of organ transplant donor kidney quality based on SERS technology

Abstract

The application relates to a new method for rapidly detecting and evaluating organ transplant donor kidney quality based on SERS technology, which comprises the following steps: a) SERS spectrum characteristics and imaging effects of related biomarkers in donor body fluid; b) respectively detecting the related biomarker levels of donor body fluid in different donor kidney quality groups; c) analyzing the relationship between the detection results and prognosis, and establishing a system for rapidly evaluating donor kidney quality by using SERS technology; and d) dynamically monitoring donor kidney quality. The application applies SERS technology to organ transplant donor kidney quality evaluation, takes the SERS spectrum technology with high sensitivity, strong specificity and fast detection speed as a tool, brings new ideas and means for a rapid evaluation scheme of donor kidney quality, is feasible, and has far-reaching clinical research significance.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of medical engineering cross-discipline, in particular, to a new method for evaluating the quality of organ transplantation donor kidney based on SERS technology. BACKGROUND

[0002] The transplantation field at home and abroad urgently needs a method that can accurately and timely evaluate the quality of donor kidney. Since China implemented the organ donation after citizen death in 2010, organ donation after citizen death (DD) has become the most important source of organ donation in China. Most of these donors have experienced a long warm ischemic time, leading to ischemia-reperfusion injury of organs; the donors are relatively older, prone to organ degenerative changes caused by old age; the donors stay in ICU for a long time, prone to nosocomial infection; the donors have unstable blood pressure, prone to drug-induced kidney injury after using pressor drugs; all the above factors can seriously affect the quality of DD donor kidney, and then lead to high incidence of delayed graft function (DGF) of transplanted kidney, postoperative graft failure and substantial increase in medical costs. Therefore, the donor kidney must be systematically, accurately and scientifically evaluated to reduce the incidence of postoperative DGF, reduce postoperative medical costs and improve the survival rate of transplanted kidney. Therefore, we urgently need to find a more rapid, accurate and safe method to evaluate the quality of donor kidney.

[0003] At present, experts in the field of transplantation at home and abroad are actively researching whether some biomarkers can be found in the body fluid of the donor, so as to more accurately and timely evaluate the quality of the donor kidney and predict the expected survival time of the transplanted kidney. By screening the serum of the donor before donation and comparing with the prognosis results of the recipients, currently, a number of biomarkers related to the quality of the donor kidney have been found, and a biological research platform for evaluating the quality of the donor kidney has been established in the UK National Biological Sample Bank. Kaisar M et al. combined the pathological puncture results, protein abundance analyzed by Label-Free Quantitation mass spectrometry (LFQ) and the prognosis results of patients, and considered that the biomarkers could be used as predictors of the quality of the donor kidney. However, the expression levels of these proteins are easily changed with the progression of the donor's condition. It takes about 90 minutes to detect proteins by LFQ mass spectrometry, which is faster than rapid paraffin section (2-3 hours) but slower than frozen section (about 40 minutes). Therefore, the use of LFQ mass spectrometry to detect biomarkers in the clinic puts higher requirements on the auxiliary departments of the transplantation center, and prolongs the cold ischemic time of the donor kidney. Therefore, in addition to finding more accurate biomarkers, better detection methods are needed, otherwise it will seriously limit its practice in the clinic.

[0004] In recent years, imaging technology has made great progress, and its application prospect in clinical practice is broad. With the development of molecular imaging, there are more and more choices. Surface enhanced Raman scattering (SERS) is an abnormal surface optical phenomenon that the Raman spectrum signal of the molecule adsorbed on the surface of the rough metal nano structure is significantly enhanced under laser irradiation. By using the field enhancement of the localized surface plasmon resonance (LSPR) of the metal nanoparticles, SERS can enhance the Raman scattering signal of biochemical molecules by 1014 times, thereby greatly enhancing its sensitivity, and thus has significant advantages in the fields of nucleic acid / protein detection and biological imaging. According to whether the Raman molecule is labeled, SERS technology can be divided into labeled and unlabeled: The labeled SERS technology has a large scattering cross section of the Raman molecule, a strong detection signal and high sensitivity, and has been widely used in the research of biological systems, especially living cell systems; The unlabeled SERS technology directly obtains the intrinsic spectral information of the analyte, and the advantage is that the rich SERS characteristic peaks are closely related to the molecular structure and orientation of the measured substance, and can more comprehensively and reliably reflect the characteristics of the analyte.

[0005] In summary, we can find that only the detection technology with clear and fast effect can be applied to rapid evaluation of the quality of the donor kidney, and truly serve the clinic. The present application intends to first explore the SERS spectral characteristics and imaging effect of the related biomarker proteins in serum or urine; before the organ is obtained, the related biomarker protein levels in the serum and urine of the donor are rapidly detected by using the SERS spectral technology, the differences and dynamic changes in the distribution of the biomarker proteins in the standard donor and the marginal donor are explored; the relationship between the biomarker and the prognosis is studied in combination with the prognosis of the transplanted kidney, and a system for rapidly evaluating the quality of the donor kidney by using the SERS technology is established; in combination with the repair technology of the donor kidney, the biomarker proteins in the preservation solution / irrigation solution are detected during the repair process, so as to monitor the repair effect of the kidney.

[0006] At present, there is no report on the method for rapidly detecting and evaluating the quality of the donor kidney for organ transplantation. SUMMARY

[0007] The first object of the present application is to provide a method for rapidly detecting and evaluating the quality of the donor kidney for organ transplantation in view of the deficiencies in the prior art.

[0008] The second object of the present application is to provide a system for rapidly evaluating the quality of the donor kidney.

[0009] In order to achieve the above first object, the technical scheme adopted by the present application is:

[0010] A new method for rapidly detecting and evaluating the quality of the donor kidney for organ transplantation based on SERS technology, comprising the following steps:

[0011] a) SERS spectrum characteristics and imaging effect of the related biomarker in the body fluid of the donor;

[0012] b) detecting the level of the related biomarker in the body fluid of the donor in different groups of kidney quality respectively;

[0013] c) analyzing the relationship between the detection result and the prognosis;

[0014] d) dynamically monitoring the kidney quality of the donor

[0015] More preferably, the SERS detection and imaging method of the related biomarker in the body fluid of the donor comprises the following steps:

[0016] a1) determining the protein related to the evaluation of the kidney quality of the donor;

[0017] a2) separating / synthesizing the related protein in vitro, and exploring the influence law of the SERS detection result under the laser wavelength, excitation power and integration time;

[0018] a3) optimizing the detection method of each protein, and obtaining the SERS spectrum characteristics thereof as a calibration.

[0019] More preferably, the related protein in the step a) comprises SLPI, IL-18, CH3L1 and L-FABP.

[0020] More preferably, the level of the related biomarker is detected by using the SERS spectrum technology and the label-free quantitative mass spectrometry respectively, and the sensitivity, specificity, detection time, cost-effectiveness and feasibility of the two detection schemes are compared.

[0021] More preferably, the analysis of the relationship between the detection result and the prognosis is to observe the difference in the distribution of the biomarkers in the standard donor and the marginal donor, and to analyze the related independent risk factors by regression analysis, so as to determine the prediction value of each biomarker in the evaluation of the kidney quality of the donor.

[0022] More preferably, the dynamic monitoring of the kidney quality of the donor in the step d) is to monitor the dynamic change of the biomarker protein in the preservation solution / irrigation solution by using the SERS technology during the repair process, so as to monitor the effect of the repair of the kidney.

[0023] To achieve the above-mentioned second object, the technical scheme adopted by the present application is:

[0024] The system for rapidly evaluating the kidney quality of the donor, which is composed of the method as described in any of the above, wherein the evaluation of the kidney quality of the donor is performed by monitoring the dynamic change of the biomarker in the serum of the living donor and the DD donor (including the SCD and the ECD) at different time points by using the SERS technology.

[0025] The present application has the advantages of:

[0026] 1. The present application takes the clinical demand of "lack of effective, reliable and fast method for evaluating the quality of kidney supply" as the breakthrough point, uses the SERS spectrum technology with high sensitivity, strong specificity and fast detection speed as the tool, brings new ideas and means for the rapid evaluation of the quality of kidney supply, has strong feasibility and has far-reaching clinical research significance.

[0027] 2. The SERS characteristic peak signal of the related biomarker protein is used to detect the expression level thereof in serum and urine, the quality of kidney supply is prompted from the molecular level, the detection time is shortened from several hours to several minutes, which is beneficial to rapidly judging the quality of kidney supply and the functional change thereof, the SERS detection technology has higher specificity, has the "fingerprint" atlas effect on the detection of macromolecular substances such as proteins, and excludes the interference of other macromolecules. Through the proposal of the new method, the quality of kidney supply can be accurately, specifically and rapidly detected and evaluated. BRIEF DESCRIPTION OF DRAWINGS

[0028] The present application is a method for evaluating the quality of kidney supply. Figure 1 The present application is a method for evaluating the quality of kidney supply.

[0029] The present application is a method for evaluating the quality of kidney supply. Figure 2 The present application is a method for evaluating the quality of kidney supply.

[0030] The present application is a method for evaluating the quality of kidney supply. Figure 3 The present application is a method for evaluating the quality of kidney supply. -1 Corresponding to SLPI. And IL-18 has no obvious band at 1000 cm -1 ).

[0031] The present application is a method for evaluating the quality of kidney supply. Figure 4 (a) UV-Vis absorption spectra of Au NPs, BP nanosheets, BP / Au nanohybrid; photographs of Au NPs (left) and BP / Au nanohybrid (right); (b) hydrodynamic size distribution of BP / Au nanohybrid determined by DLS (0, 24 h); (c) TEM image of Au NPs; (d) TEM image of BP nanosheets; (e-f) TEM images of BP / Au nanohybrid at different magnifications.

[0032] The present application is a method for evaluating the quality of kidney supply. Figure 5 (a) average SERS spectra of R6G with a concentration of 10 -2 mM using Au NPs and BP / Au nanohybrid as enhancement substrates (spectra placed in parallel); (b) SERS intensity quantification of R6G characteristic bands enhanced by Au NPs and BP / Au nanohybrid, respectively.

[0033] The present application is a method for evaluating the quality of kidney supply. Figure 6(a) BP / Au nanohybrid and (b) isolated material were numerically simulated by using finite-difference time-domain method. (Excitation wavelength: 638 nm, mesh setting: 1 nm, boundary condition: PML, BP nanosheet thickness: 5 nm, gold nanoparticle to BP nanosheet relationship: tangent).

[0034] Figure 2 Figure 7 To verify the uniformity and repeatability of BP / Au nanohybrid. (a) SERS spectra of 80 R6G with concentration of 10 -2 mM. (b) SERS strip spectra of 80 R6G collected along y axis, (c) histogram statistics of SERS intensity at 1512 cm -1 from 80 spectra (d) SERS spectra of 50 10 -2 mM R6G; (e, f) scatter plot and histogram statistics of SERS intensity at 1512 cm -1 from 50 individual spectra.

[0035] Figure 3 Figure 8 To: (a) detect SLPI in buffer (SERS spectra with concentration dependence, SLPI concentration range from 2 to 2 x 10 -8 mg / mL); (b) band intensity plot at 1000 cm -1 as a function of SLPI concentration. (c) detect IL-18 using BP / Au nanohybrid (SERS spectra with concentration dependence, IL-18 concentration range from 2 to 2 x 10 -8 mg / mL); (d) band intensity at 950 cm -1 as a function of IL-18 concentration.

[0036] Figure 4 Figure 9 To: (a) detect SERS spectra of SLPI with concentration dependence in buffer solution containing 10% fetal bovine serum (SLPI concentration range from 2 to 2 x 10 -8 mg / mL); (b) band intensity plot at 1000 cm -1 as a function of SLPI concentration. (c) detect SERS spectra of IL-18 with concentration dependence in buffer solution containing 10% fetal bovine serum (concentration range from 2 to 2 x 10 -8 mg / mL). (d) band intensity plot at 950 cm -1 as a function of IL-18 concentration.

[0037] Figure 5 Figure 10 Average SERS spectra of mixed biomarker samples A, B and C.

[0038] Figure 6Figure 11 Schematic diagram of SERS detection for AKI biomarkers.

[0039] Figure 1 Figure 12 (a) UV-vis absorption spectrum. (b) Particle size distribution of gold colloid. (c, d) TEM images of Au@Ag NPs and GO / Au@Ag NPs.

[0040] Figure 2 Figure 13 Figure 2 -5 Average SERS spectra of 10

[0041] Figure 3 Figure 14 (a) SERS spectra of all pixels in the mapping result. (b) SERS intensity histogram waveband at 1654 cm -1 RSD of 9.13% for the intensity of 1654 cm -1

[0042] Figure 4 Figure 15 SERS spectra of CH3L1 (a) and L-FABP (b) standard solutions at 8 concentrations.

[0043] Figure 5 Figure 16 Linear relationship of CH3L1 standard solution. The relationship between SERS characteristic peak intensity at 997 cm -1 and CH3L1 concentration is shown in linear coordinates (a) and logarithmic coordinates (b).

[0044] Figure 6 Figure 17 Linear relationship of L-FABP standard solution. The relationship between SERS characteristic peak intensity at 1161 cm -1 and L-FABP concentration is shown in linear coordinates (a) and logarithmic coordinates (b).

[0045] Figure 7 Figure 18 SERS spectra in CH3L1 (a) and L-FABP (b) serum samples at 8 concentrations.

[0046] Figure 8 Figure 19 Linear relationship of CH3L1 serum sample. The relationship between SERS characteristic peak intensity at 997 cm -1 and CH3L1 concentration is shown in linear coordinates (a) and logarithmic coordinates (b).

[0047] Figure 9 Figure 20 Linear relationship of L-FABP serum sample. The relationship between SERS characteristic peak intensity at 1161 cm -1 and L-FABP concentration is shown in linear coordinates (a) and logarithmic coordinates (b).​

[0048] Appendix Figure 21 Mean SERS spectrum of mixed serum samples (leftmost shaded: CH3L1 at 997 cm⁻¹) -1 Characteristic peaks at 1161, 1254, and 1321 cm⁻¹; three remaining shaded areas: L-FABP at 1161, 1254, and 1321 cm⁻¹. -1 (characteristic peak at the location). Detailed Implementation

[0049] This invention leverages the high sensitivity and specificity of SERS spectroscopy for detecting biomolecules, exploring the SERS spectral characteristics and imaging effects of relevant biomarkers in body fluids. Before organ retrieval, SERS spectroscopy is used to rapidly detect the levels of relevant biomarkers in donor body fluids, investigating the differences and dynamic changes in their distribution between standard and marginal donors. In conjunction with the prognosis of transplanted kidneys, the relationship between biomarkers and prognosis is studied, establishing a system for rapidly assessing donor kidney quality using SERS technology. Furthermore, in conjunction with donor kidney repair technology, biomarker proteins in preservation / irrigation fluids are detected during the repair process to monitor the effectiveness of kidney repair. The experimental content and experimental technical roadmap of this invention are detailed in the appendix. Figure 1 and attached Figure 2 .

[0050] The present invention will be further described below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the description of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

[0051] Example 1: Detection of SLPI and IL-18 using a SERS method based on BP / Au nanohybrids

[0052] 1. Experimental Equipment

[0053] 1.1 Materials

[0054] SLPI and IL-18 were provided by Changhai Hospital and their purity was analyzed by Wuhan Seville Biotechnology Co., Ltd. (>85%).

[0055] 1.2 Instruments

[0056] UV-Vis absorption spectra were recorded using Evolution 350 UV-vis (Thermo Scientific, China). The surface morphology and size of the prepared BP / Au nanohybrids were characterized by high-resolution transmission electron microscopy (JEM-2100F, JEOL, Japan) at an accelerating voltage of 200 kV. The size distribution was measured by dynamic light scattering experiments (Zetasizer, Nano-ZS90, Malvern, UK). SERS spectra were recorded by a microscope Raman spectrometer (XploRAPLUS, HORIBA) with an incident laser wavelength of 638 nm and a 10x objective lens.

[0057] 2. Experimental procedures

[0058] 2.1 SERS spectral characteristics and imaging effects of relevant biomarkers in donor body fluids

[0059] Through literature retrieval, the proteins related to the evaluation of the quality of the donor kidney (CH3L1, SLPI, IL-18, CH3L1, L-FABP) were identified, the related proteins were isolated / synthesized in vitro, the influence law of the SERS detection results under different detection conditions (changing the laser wavelength, excitation power, integration time) was explored, the detection method for detecting each protein was optimized, and the SERS spectral characteristics were obtained as a calibration.

[0060] 2.2 Detection of the levels of relevant biomarkers in the body fluids of donors in different groups of kidney quality

[0061] 2.2.1 Retrospective analysis of 650 cases of recipients who received kidney transplantation in our center according to the grouping of kidney quality

[0062] According to the quality and acquisition method of the donor kidney, they were divided into living donor (LD), standard criteria donor (SCD) and expanded criteria donor (ECD). The inclusion criteria were: a the specimens in the sample bank were not missing; b the increase or not of eGFR was mainly used as the judgment to enter the ECD group; c if two kidneys came from the same donor, they could be included in the ECD group only if DGF occurred at the same time; d if the eGFR of the donor kidney was good, but DGF occurred, it could not be included in the ECD group; e if it was clear that DGF occurred due to recipient factors, but the postoperative eGFR was normal, it could be included in the SCD group. According to the grouping, the corresponding donor serum and urine specimens were obtained from the sample bank.

[0063] 2.2.2 Detection of the levels of biomarkers in different groups

[0064] The SERS spectrum technique and the label-free quantitative mass spectrometry were used to detect the related proteins in serum and urine of the three groups, and the sensitivity, specificity, detection time, cost-effectiveness and feasibility of the two detection schemes were compared.

[0065] 2.3 Analysis of the relationship between the detection results and prognosis

[0066] Through detection, combined with the prognosis of the transplanted kidney, the differences in the distribution of these biomarkers in standard donors and marginal donors were observed, and the relevant independent risk factors were analyzed by regression analysis. Further, the predictive value of each biomarker in the evaluation of the quality of the donor kidney under the detection conditions of the SERS spectrum technique was determined, and a system for rapidly evaluating the quality of the donor kidney using SERS technology was established.

[0067] 3. Experimental method

[0068] 3.1 Synthesis of SERS substrate

[0069] 3.1.1 Synthesis of gold nanoparticles (Au NPs)

[0070] 20 mL of deionized water was added to a conical flask, and continuous stirring was used to heat it to boiling. Then, 600 μL of 1% HAuCl4 was added to 1.2 mL of 1% trisodium citrate solution, and after stirring, it was kept boiling for 18 min. Then, the heating was stopped, and the mixture was continuously stirred until it cooled to room temperature. The obtained sample was stored in the refrigerator (4°C).

[0071] 3.1.2 Synthesis of black phosphorus / gold (BP / Au) nanohybrids

[0072] The BP / gold nanohybrids were synthesized by in situ reduction method. 600 μL of HAuCl4 (1 wt%) was added to 20 mL of boiling water, 80 μL of 4 mg / mL BP nanosheet solution was first ultrasonically oscillated for 5 min, and then added dropwise every 3 seconds. Then, 1.2 mL of trisodium citrate solution (1 wt%) was added, and stirred for 2 h. Finally, the product was obtained by centrifugation at 9000 rpm for 20 min. The obtained product was dispersed in deionized water and stored in the dark at 4°C.

[0073] 3.2 SERS-based detection

[0074] 5 μL of SLPI and IL-18 solutions with different concentrations were added to 5 μL of BP / Au nanohybrids. SERS spectra were obtained under excitation at 638 nm. For each sample, SERS spectra from 10 random positions were measured to obtain the average spectrum.

[0075] 4 Data analysis

[0076] SERS spectra were collected by a micro-Raman spectrometer (LabRAM Xplora Plus, HORIBA Scientific, France) at 638 nm excitation. The scattered light in the sample was collected with a 10x objective. All spectra were recorded between 400-1800 cm -1 with a resolution of 1 cm -1 .

[0077] The obtained Raman and SERS spectra were smoothed, denoised and baseline corrected using the software LabSpec 6. The optimized SERS spectra were analyzed to analyze the correlation between the characteristic peak intensity and the concentration of the analyte. The logarithm of the Raman characteristic peak intensity of the AKI biomarkers CH3L1 and L-FABP was linearly related to the logarithm of the concentration of CH3L1 and L-FABP in the sample. When the concentration range of the sample is large, the linear relationship between the logarithm of the peak intensity (log I) and the logarithm of the sample concentration (log C) is usually used. The average intensity is the average value obtained by 8 repeated measurements. The linear relationship is evaluated by R2, and the detection of CH3L1 and L-FABP in serum samples is used to verify the prediction accuracy of the established linear calibration model. The calculation of the limit of detection (LOD) is defined as 3 times the instrument background signal value produced by the matrix blank (S / N = 3).

[0078] 5 Experimental results

[0079] 5.1 Characteristics of Au NPs and BP / Au nanohybrids

[0080] Au NPs were prepared according to the above method, and then absorption and transmission electron microscopy (TEM) measurements were performed. As shown in FIG. 1, (a) in the absorption spectrum of Au NPs, there is a clear absorption band peaking at 520 nm, which is derived from the surface plasmon resonance (SPR) of Au NPs. Figure 4 (b) in the TEM image, the Au NPs are spherical monodisperse, and the average size is 27 nm. Figure 4 (c) in the TEM image results show that the Au NPs are spherical monodisperse, and the average size is 27 nm. BP / Au nanohybrids were synthesized by in-situ reduction method, in which BP nanosheets were used as carrier materials, and HAuCl4 was used as the precursor of Au and sodium citrate as the reducing agent. Figure 4(a) shows that pure BP nanosheets have no obvious adsorption band, while BP / Au nanohybrids have an obvious SPR band at 545 nm, which is related to the loading of AuNPs on the BP nanosheets. Compared with AuNPs, the SPR band of the nanohybrids shows obvious red shift and broadening. This indicates that the AuNPs on the BP nanosheets are slightly stacked with each other, which is conducive to the generation of multiple hot spots, thereby improving the SERS sensitivity of biosensing. Transmission electron microscopy images further confirm the construction of the BP / Au nanohybrids. The BP nanosheets have a typical sheet structure with a lateral size of 600 nm -1 μm, as shown in Figure 4 (d). After the in-situ reduction process, the BP nanosheets are observed to be attached with spherical AuNPs, as shown in Figure 4 (e) and (f). The AuNPs are densely located on the surface of the BP nanosheets, with a relatively uniform size and an average diameter of about 30 nm. At the same time, the coverage range of the AuNPs on the surface of the BP nanosheets is limited within the range of the BP nanosheets, and no AuNPs are observed outside. The AuNPs on the BP nanosheets have the same size as the AuNPs. This indicates that the AuNPs can be effectively assembled on the BP nanosheets. In addition, the BP / Au nanohybrids need to maintain their structural and property stability for subsequent detection. As shown in Figure 4 (b), the hydrodynamic diameter is detected by dynamic light scattering (DLS), and the fluid dynamic size of the nanohybrids has no obvious change, indicating that the nanohybrids have almost no aggregation and maintain their morphology for at least 24 h. Therefore, the BP / Au nanohybrids have good colloidal stability.

[0081] 5.2 SERS performance of BP / Au nanohybrids

[0082] R6G is used to detect the SERS performance of the BP / Au nanohybrids. First, the SERS signal of R6G (10 -2 mM) is obtained by using lasers with wavelengths of 638 nm and 785 nm, and the results show that both the 638 nm and 785 nm bands are feasible. In subsequent experiments, 638 nm is selected for SERS measurement. Then, a comparative study is conducted on the SERS activity of AuNPs and BP / Au nanohybrids. Both the AuNPs and the BP / Au nanohybrids have no obvious SERS background, and the gold content is adjusted to be consistent. AuNPs and BP / Au nanohybrids are used as substrates for R6G detection. Fig. Figure 5 (a) shows the SERS spectra of R6G at a concentration of 10 -2 mM, which are enhanced by AuNPs and BP / Au nanohybrids, respectively. The SERS signal of R6G at 609 cm -1The characteristic SERS bands at 1582 cm -1 and 1512 cm -1 correspond to in-plane C-C stretching. The SERS intensities of the three characteristic bands are shown in Fig. Figure 5 (b). Compared with Au NPs, the Raman signal of R6G was amplified more than 2-fold by BP / Au nanohybrids, due to the existence of a large number of hot spots in the gap of Au NPs on BP nanosheets. The potential mechanism of hot spot benefiting Raman amplification was verified by numerical simulation of the electromagnetic field distribution of Au NPs and BP / Au nanohybrids using the finite-difference time-domain method.

[0083] As shown in Fig. Figure 6 Compared with Au NPs, BP / Au nanohybrids provided a stronger electric field in the nanoscale gap between Au NPs through interparticle plasmonic coupling. Due to the fact that a large number of Au NPs were densely deposited on BP nanosheets, a high density of hot spots was generated, and the sensitivity of future analysis was accordingly improved.

[0084] The uniformity and repeatability of the SERS signal were then verified. Fig. Figure 7 (a) shows 80 spectra detected from randomly selected positions on one single sample, Fig. Figure 7 (b) is the SERS code collected from the 80 spectra, and it can be seen that the SERS signal is quite consistent. Fig. Figure 7 (c) plots the intensities of the characteristic SERS band at 1512 cm -1 , to evaluate the fluctuation of the signal. The relative standard deviation (RSD) value of this band was 9.7%, indicating that BP / Au nanohybrids are a homogeneous substrate.

[0085] To verify the repeatability, 5 batches of substrates were prepared under the same experimental conditions, and 50 SERS spectra were collected on these substrates as shown in Fig. Figure 7 (d). The intensities of the SERS band at 1512 cm -1 are shown in Figs. Figure 7 (e) and (f), which fluctuate slightly, with an RSD of 13.85%, which is within an acceptable range (<20%).

[0086] 5.3 Detection results of SLPI and IL-18

[0087] SLPI and IL-18 were detected using the prepared BP / Au nanohybrids. The concentration range of the SLPI and IL-18 solutions was 2-2 x 10 -8mg / mL, then mixed with nanohybrids. Due to the high affinity of BP nanosheets for biomolecules, SLPI and IL-18 can be effectively absorbed by the nanohybrids, resulting in a strong SERS signal. (See attached...) Figure 8 As shown in Table 1, a series of SERS spectra corresponding to different SLPI and IL-18 concentrations show an increasing trend with increasing concentration. The main SERS bands are shown in Table 1.

[0088] Table 1. Raman characteristic peaks in biomarker solutions

[0089] Peak Assignment 933 C-H bending / v(C-C) / C-COO 950 C-H bending / v(C-H) / v(C-CH3) 1000 Phe v12 / v(CH2) 1064 C-N stretch 1100 v(C-N) / v(C-C) / v(C-N) 1162 vas(CCN), Tyr / Phe-w(NH3) 1256 amide III / delta (C-Ca-H) 1305 w(CH2) 1323 delta(CH) / Trp / CH2 1421 Gly-v(C-H) / Cys-delta(CH2) 1495 Phe, Tyr 1534 Trp W3 / Gly, Leu δ (NH3+)

[0090] To quantitatively analyze SLPI, at 1000 cm⁻¹ -1 The intensity of the band at that point should be expressed as Phe v12 and ρCH2. (See attached image.) Figure 9 As shown in (b), SERS intensity and SLPI concentration are in the range of 2 to 2 × 10⁻⁶. -8 The BP / Au nanoparticles showed a good linear relationship with the target concentration (mg / mL). The linear regression equation is shown in Table 2, with a correlation coefficient (r) of 0.99. The calculated limit of detection (LOD) for the BP / Au nanoparticle hybrid was 1.53 × 10⁻⁶ mg / mL. -8 mg / mL. As a control, the SERS detection concentration using Au NPs only reached 2 × 10 mg / mL. -6 The concentration of BP / Au nanohybrids is significantly lower than that of AuNPs, reaching mg / mL. Therefore, compared to AuNPs, the use of BP / Au nanohybrids improves the sensitivity of SLPI detection by two orders of magnitude. Furthermore, our SERS-based detection method is more sensitive than ELISA. (See attached image.) Figure 9 (d) and Table 2 also show that BP / Au nanohybrids can detect different concentrations of IL-18, and the SERS intensity has a good linear dependence on the IL-18 concentration, with a LOD of 0.23 × 10⁻⁶. -8 mg / mL, and the detection sensitivity is also higher.

[0091] Table 2. Linear relationship between SERS detection of biomarkers SLPI and IL-18

[0092] Peak 1000 cm -1 ]] 950 cm -1 ]] Equation lg(y) = 3.275 + 0.189 lg(x) lg(y) = 4.056 + 0.252 lg(x) Pearson’s correlation coefficient 0.991 0.991 R square (COD) 0.982 0.983 LOD 1.53 x 10 -8 mg / mL 0.23 x 10 -8 mg / mL

[0093] 5.4 Detection results of SLPI and IL-18 in real samples

[0094] Different concentrations of SLPI and IL-18 were mixed in fetal bovine serum (10% FBS) and then exposed to BP / Au nanohybrids. (See attached image) Figure 10 (a) shows the concentration-dependent calibration curve for SLPI detection. It can be seen that at 1000 cm⁻¹... -1The SERS intensity increased with increasing SLPI concentration, maintaining a linear relationship with a correlation coefficient of 0.979. Similarly, the results for serum IL-18 were similar, with SERS intensity at 950 cm⁻¹. -1 The concentration of SLPI showed a linear relationship with that of IL-18, with a correlation coefficient of 0.992. The correlation coefficient of the serum assay was slightly lower than that of the buffer solution alone, which may be related to the interference of multiple proteins in serum. However, it can be concluded that the SERS-based detection method is still applicable to real biological environments. Recovery experiments were then performed using serum samples mixed with SLPI and IL-18, respectively. (See attached...) Figure 10 The calibration curves in the dataset allow for the calculation of SLPI and IL-18 concentrations using the SERS signal intensity. The detection method achieves an accuracy of 87.95%–97.05% in real samples, demonstrating its feasibility in biological environments and exhibiting high accuracy and sensitivity.

[0095] In summary, BP / Au nanohybrids can be used to simultaneously and quantitatively detect SLPI and IL-18.

[0096] Example 2: Detection of CH3L1 and L-FABP using a SERS method based on GO / Au@Ag NPs

[0097] 1. Experimental Equipment

[0098] 1.1 Materials

[0099] CH3L1 (2 mg / mL) and L-FABP (1.2 mg / mL) were provided by Changhai Hospital and their purity was analyzed by Wuhan Seville Biotechnology Co., Ltd. (>85%).

[0100] 1.2 Instruments

[0101] Same as Example 1

[0102] 2. Experimental Procedures and Methods

[0103] 2.1 Synthesis of graphene oxide / gold and silver core-shell nanoparticles (GO / Au@Ag NPs)

[0104] The preparation of Au-Ag core-shell nanostructures (Au@Ag NPs) can be divided into two steps. First, AuNPs were prepared by sodium citrate dihydrate mediated reduction of HAuCl4.3H2O. 306 μL of HAuCl4.4H2O (10% w / w) was dissolved in 99.694 mL of deionized water and heated to boiling. Then, 10 ml of sodium citrate dihydrate (1% w / w) was added to the boiling mixture. Heating was continued for 15 minutes until it turned wine red, and it was cooled to room temperature. Then, Ag was coated on the surface of AuNPs by reduction of silver nitrate by D(+)-glucose. 6 mL of gold NPs were centrifuged at a speed of 9500 r / min for 35 min. The supernatant was removed, and the precipitate was diluted back to 6 mL, 54 mL of deionized water was added, and it was stirred and heated to 60°C. 500 μL of 0.08 M D(+) glucose solution and 140 μL of 0.1 M AgNO3 were added to the solution, and 200 μL of 1 M sodium hydroxide solution was added. Heating was continued for 30 minutes until the solution turned orange yellow, and it was cooled to room temperature and stored in the dark for one week for later use.

[0105] Then 10 mL of aqueous solution of graphene oxide (0.01 mg / mL) was added to 30 ml of Au@Ag NPs colloid, ultrasonicated for 3 minutes, and continuously stirred for 2 hours until complete mixing.

[0106] 2.2 Preparation of CH3L1 and L-FABP standard solutions and SERS detection

[0107] CH3L1 and L-FABP standard solutions were prepared for SERS determination. According to previous studies, in healthy population, when the urine CH3L1 value is lower than 0.2 ng / mL, it is usually not detected, so 5 ng / mL is generally used as the baseline. The baseline of L-FABP is generally 10.1 ng / mL, and the biomarker concentration of patients with acute kidney injury is usually higher than the baseline level.

[0108] The initial concentrations of CH3L1 and L-FABP were 2 mg / mL and 1.2 mg / mL, respectively, and then diluted with Tris-HCL to obtain CH3L1 standard samples with concentrations of 2 x 10 -1 ,2 x 10 -2 ,2 x 10 -3 ,2 x 10 -4 ,2 x 10 -5 ,2 x 10 -6 ,2 x 10 -7 ,2 x 10 -8 mg / mL and L-FABP standard samples with concentrations of 1.2 x 10 -1 ,1.2 x 10 -2 ,1.2 x 10 -3 ,1.2 x 10 -4 ,1.2 x 10-5 1.2 x 10 -6 1.2 x 10 -7 1.2 x 10 -8 mg / mL L-FABP standard sample. 2 μL GO / Au@Ag nanocomposites were dropped on the glass slide, and then 2 μL standard sample was dropped, followed by SERS detection. Eight SERS spectra were measured from random positions to obtain the average spectrum.

[0109] 2.3 Real sample pretreatment and SERS detection

[0110] Fetal bovine serum (FBS) was diluted with Tris-HCL (dilution ratio 1:9), and then different concentrations of CH3L1 and L-FABP were added respectively. The concentration of CH3L1 serum sample was 2 x 10 -1 2 x 10 -2 2 x 10 -3 2 x 10 -4 2 x 10 -5 2 x 10 -6 2 x 10 -7 2 x 10 -8 mg / mL, and the concentration of L-FABP serum sample was 1.2 x 10 -1 1.2 x 10 -2 1.2 x 10 -3 1.2 x 10 -4 1.2 x 10 -5 1.2 x 10 -6 1.2 x 10 -7 1.2 x 10 -8 mg / mL. CH3L1 and L-FABP were mixed to obtain three different concentrations of mixed serum samples to simultaneously determine CH3L1 and L-FABP. The concentration of CH3L1 in the mixed sample was 1 x 10 -1 1 x 10 -4 and 1 x 10 -7 mg / mL, and the concentration of L-FABP was 0.6 x 10 -1 0.6 x 10 -4 and 0.6 x 10 -7 mg / mL (denoted as sample 10 -1 mg / mL, 10 -4 mg / mL, 10 -7 mg / mL).

[0111] The SERS detection method of serum sample was referred to the foregoing ( Figure 11 ). Each spectrum was also obtained by averaging the spectra measured from 8 random positions.

[0112] 3. Data Collection and Analysis

[0113] SERS spectra were collected using a micro Raman spectrometer (LabRAM XploraPlus, HORIBA Scientific, France) under 638 nm excitation. Scattered light from the sample was acquired using a 10x objective lens. All spectra were recorded in the range of 400–1800 cm⁻¹. -1 Between, with a resolution of 1cm -1 .

[0114] The obtained Raman and SERS spectra were smoothed, denoised, and baseline corrected using LabSpec6 software. The optimized SERS spectra were analyzed to examine the correlation between characteristic peak intensities and analyte concentrations. A linear relationship was established between the logarithm of the Raman characteristic peak intensities of the AKI biomarkers CH3L1 and L-FABP and the logarithm of their concentrations in the sample. When the sample concentration range is large, a linear relationship between the logarithm of the peak intensity (log I) and the logarithm of the sample concentration (log C) is typically used. The average intensity was obtained from eight repeated measurements. The linear relationship is expressed using R0. 2 An evaluation was conducted, and CH3L1 and L-FABP were detected in serum samples to verify the predictive accuracy of the established linear calibration model. The limit of detection (LOD) was calculated as three times the instrument background signal value generated by the matrix blank (S / N=3).

[0115] To verify the repeatability of the SERS signal, 10 -2 mM Rhodamine B (RB) solution was mixed with GO / Au@Ag NPs in a 1:1 ratio, and then the 50 μm × 50 μm (step size 10 μm) interval plot of the mixed solution was detected and the SERS spectrum of the analysis was recorded.

[0116] 4 Results and Discussion

[0117] 4.1 Characterization of GO / Au@AgNPs

[0118] After preparation, GO / Au@Ag NPs were detected using ultraviolet-visible (UV-Vis) spectroscopy, transmission electron microscopy, and dynamic light scattering. GO / Au@Ag NPs were detected using an Evolution 350 UV-Vis spectrometer (Thermo Scientific, China). Figure 12 As shown in figure a, there is a peak at 411 nm, and at 520 nm, corresponding to the silver shell and gold core, which is consistent with the UV-VIS absorption peaks of Ag and Au. Its size distribution was obtained through dynamic light scattering experiments (Zetasizer, Nano-ZS90, Malvern, UK). Figure 12bshows that the size of GO / Au@Ag NPs is relatively uniform. The surface morphology and size of GO / Au@Ag NPs were observed by JEM-2100F (JEOL, Japan) high-resolution transmission electron microscopy (TEM) at an accelerating voltage of 200 kV. According to the TEM image in Figure 12 , the average size of GO / Au@Ag NPs is 24 nm. The core-shell structure is shown in Figure 12 c. As shown in Figure 12 d, the nanoparticles are uniformly distributed on the graphene oxide. The results show that GO / Au@Ag NPs are uniform and consistent.

[0119] The SERS performance of GO / Au@Ag hybrid and Au@Ag composite nanoparticles was compared. According to the absorbance of gold nanoparticles, the gold content of the two hybrids was adjusted to be the same. Then, GO / Au@Ag nanoparticles and Au@Ag nanoparticles were used as SERS substrates, respectively, to detect 10 -2 mM Rhodamine B (RB). The SERS signal enhanced by GO / Au@Ag nanoparticles is significantly better than that of Au@Ag nanoparticles, as shown in Figure 13 .

[0120] In addition, in order to verify the stability of GO / Au@Ag NPs in SERS, we mapped 10 -2 mM RB, and the characteristic peak intensity was 1645 cm -1 to generate a SERS mapping image. The experiment was performed on a 50 μm x 50 μm area on a glass slide. As shown in Figure 14 .B, there is no significant difference in the SERS intensity of the pixel points with a relative standard deviation (RSD) of 9.13%. In summary, the SERS performance of GO / Au@Ag NPs has good stability and uniformity.

[0121] 4.2 SERS measurement and analysis of CH3L1 and L-FABP standard solutions

[0122] As shown in Figure 15 , the SERS measurement standard sample, CH3L1 (2 x 10 -1 to 2 x 10 -8 mg / mL, corresponding to a concentration of 3.38 x 10 -6 to 3.37 x 10 -13 M), and L-FABP (1.2 x 10 -1 to 1.2 x 10 -8 mg / mL, corresponding to 2.93 x 10 -6 to 2.93 x 10 - 13M). Based on the SERS intensity at specific characteristic peaks, the quantitative detection function of this method was verified.

[0123] In CH3L1 and L-FABP standard samples, the characteristic peaks of CH3L1 at 997 cm -1 and L-FABP at 1161, 1254 and 1321 cm -1 respectively can be clearly observed, even at the lowest concentration of 2 x 10 -8 mg / mL and 1.2 x 10 -8 mg / mL. The characteristic peak distribution of CH3L1 and L-FABP is shown in Table 3. With the increase of biomarker concentration, GO / Au@Ag NPs caused different degrees of Raman signal enhancement. This is due to the formation of hot spots between GO / Au@Ag NPs, indicating that the hot spot response SERS signal is extremely sensitive to the detection of biomarkers.

[0124] Table 3. Distribution of SERS spectral peaks of CH3L1 and L-FABP

[0125]

[0126] There are several characteristic peaks that can be used for quantitative analysis. For CH3L1, the logarithm (log I) of the intensity at 997 cm -1 shows an ideal linear relationship with the entire measured concentration range (log C), 2 x 10 -1 to 2 x 10 -8 mg / mL (corresponding to 3.38 x 10 -6 to 3.38 x 10 -13 M), as shown in Figure 16 . For L-FABP, the log I at the characteristic peaks 1161, 1254 and 1321 cm -1 shows a linear relationship with the log C in the entire concentration range, 1.2 x 10 -1 to 1.2 x 10 -8 mg / mL (2.93 x 10 -6 to 2.93 x 10 -13 M), with the highest R2at 1161 cm -1 .According to these results, the limit of detection (LOD) of CH3L1 and L-FABP was calculated to be 1.21 x 10 -8 mg / mL and 0.62 x 10 -8 mg / mL using the 3σ / s method. Figure 17 is 1161 cm -1Linear fitting results between the intensity of the characteristic peaks and the concentration. Values and errors in (a) and (b) are the average intensity and standard deviation calculated from 8 independent measurements. Linear fitting equations of the four characteristic peaks are shown in Table 4.

[0127] Table 4. Linear fitting results between the intensity of the characteristic peaks and the concentration of CH3L1 and L-FABP standard solutions at 997, 1161, 1254 and 1321 cm-1. -1

[0128]

[0129] To quantify CH3L1 and L-FABP, the band intensity of vs(C-C) and phenylalanine at 997 cm-1 -1 and the band intensity of C-H bending and tyrosine at 1161 cm-1 -1 were extracted, respectively, to represent the trend of them. These two characteristic peaks are relatively obvious and easy to distinguish, and the biomarkers can be detected at very low concentrations (2 x 10 -8 mg / mL, 1.2 x 10 -8 mg / mL), and the linear range is 2 x 10 -1 to 2 x 10 -8 mg / mL and 1.2 x 10 -1 to 1.2 x 10 -8 mg / mL.

[0130] 4.3 SERS determination and analysis of CH3L1 and L-FABP in serum samples

[0131] To determine whether the SERS method can be used for the determination of CH3L1 and L-FABP in real complex environments, the two biomarkers were detected in fetal bovine serum (FBS) solution. The SERS spectra of serum samples have similar variation trends as CH3L1 and L-FABP standard solutions Figure 18 ). Similar to the standard solutions, satisfactory linear fitting was obtained at the characteristic peaks 997 and 1161 cm-1 -1 , respectively.

[0132] At the characteristic peak value 997 cm-1 of CH3L1, the SERS spectral intensity has a good linear relationship with the concentration from 2 x 10 -1 to 2 x 10 -8 mg / mL, and the linear relationship between log C and log I is shown in Figure 19 . For L-FABP serum samples, at the characteristic peak 1161 cm-1 -1 , the SERS spectral intensity is 1.2 x 10 -1 to 1.2 x 10 -8 ​mg / mL, a good linear relationship with sample concentration was observed, as shown in Figure 20 Table 5. Linear fitting equations of four characteristic peaks of CH3L1 and L-FABP serum samples

[0133] Table 5. Linear fitting equations of four characteristic peaks of CH3L1 and L-FABP serum samples -1

[0134]

[0135] The results of serum samples were consistent with standard samples, and the lowest detection concentrations of CH3L1 and L-FABP in serum samples were 2 x 10 -8 mg / mL and 1.2 x 10 -8 mg / mL, respectively. The detection limit of this method was significantly lower than the baseline of CH3L1 and L-FABP, so the biomarkers in real samples could be qualitatively and quantitatively analyzed by this method, providing a reference value for the screening and early diagnosis of acute kidney injury.

[0136] To further evaluate the application of this scheme in real samples, we performed a verification experiment on a new set of CH3L1 serum samples and L-FABP serum samples. The spectral intensity at 997 and 1161 cm -1 was detected, and the linear regression model was substituted, and the concentration of each sample was calculated and compared with the true value (Table 6). The verification results were all within the acceptable range of 96.83% to 106.58%, indicating that this method has great application potential in real samples.

[0137] Table 6. Determination of CH3L1 and L-FABP in serum

[0138]

[0139] 4.4 Simultaneous detection of CH3L1 and L-FABP

[0140] Three serum concentration samples (mixed sample concentrations of 10 -1 , 10 -4 , and 10 -7 mg / mL) were mixed with CH3L1 and L-FABP, and the SERS results are shown in Figure 21 In the mixed solution, the main SERS peaks still exist. The representative characteristic peaks are 997, 1161, 1254, and 1321 cm -1 ​It is easy to observe and can be used to identify the content of CH3L1 and L-FABP in a mixture. The characteristic peak intensity of SERS increases with increasing biomarker concentration. Therefore, it is feasible to quantitatively determine the content of a single biomarker in complex samples containing multiple biomarkers.

[0141] In summary, the GO / Au@AgNPs-based SERS method is a reliable and ultrasensitive biomarker detection method that can be used to detect extremely low concentrations of CH3L1 and L-FABP, demonstrating feasibility in real-world, complex biological environments. The entire detection process is convenient, time-saving, and economical, and both gold-based and silver-based substrates exhibit good biocompatibility. Therefore, this method holds broad promise for various medical and biotechnological applications.

[0142] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several improvements and additions without departing from the method of the present invention, and these improvements and additions should also be considered within the scope of protection of the present invention.

Claims

1. A method for rapidly detecting and assessing the quality of donor kidneys for organ transplantation based on SERS technology, comprising the following steps: a) Methods for detecting and imaging relevant biomarkers in donor body fluids; b) Detect the levels of relevant biomarkers in donor body fluids from different donor kidney quality groups; c) Analyze the relationship between test results and prognosis; d) Dynamically monitor the quality of donor kidneys; Its features are, The SERS detection and imaging method for relevant biomarkers in donor bodily fluids described in step a) is characterized by comprising the following steps: a1) Identify proteins relevant to donor kidney quality assessment; a2) In vitro isolation / synthesis of related proteins to investigate the influence of laser wavelength, excitation power and integration time on SERS detection results; a3) Optimize the detection methods for each protein and obtain their SERS spectral characteristics for calibration. The relevant biomarkers mentioned are BP / Au nanohybrids for detecting SLPI and IL-18 and GO / Au@AgNPs for detecting CH3L1 and L-FABP. The relationship between the test results and prognosis in step c) is determined by observing the differences in the distribution of these biomarkers among standard and marginal donors, and by regression analysis of relevant independent risk factors, thereby clarifying the predictive value of each biomarker in assessing donor kidney quality.

2. The method according to claim 1, characterized in that, The relevant proteins in step a1) include: SLPI, IL-18, CH3L1 and L-FABP.

3. The method according to claim 1, characterized in that, In step b), the levels of relevant biomarkers were detected in serum and urine of the three groups using SERS spectroscopy and label-free quantitative mass spectrometry, respectively. The sensitivity, specificity, detection time, cost-effectiveness and feasibility of the two detection methods were compared.

4. The method according to claim 1, characterized in that, In step d), dynamic monitoring of donor kidney quality involves using SERS technology to monitor the dynamic changes of biomarker proteins in the preservation / irrigation fluid during the repair process, thereby monitoring the effectiveness of kidney repair.

5. The system for rapidly assessing donor kidney quality according to any one of claims 1-4, characterized in that, The assessment of donor kidney quality is achieved by monitoring the dynamic changes of biomarkers in the serum of both living donors and DD donors at different time points, including SCD and ECD, using SERS spectroscopy.

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