A fluorescent sensor array based on sulfur quantum dots and a preparation method and detection application thereof

Abstract

The application discloses a three-channel fluorescence sensor array based on sulfur quantum dots and a preparation method and detection application thereof. The sensor array is composed of three kinds of sulfur quantum dots, namely C-SQDs, PSS-SQDs and beta-SQDs. When target objects exist, the three kinds of sensing units generate differentiated fluorescence responses, forming a unique "fingerprint map". By using principal component analysis to analyze the response mode, the array can successfully distinguish between structurally similar baicalein, fiscetin, myricetin, quercetin and rutin in a concentration range of 8.0-56 muM. In addition, the array can also perform semi-quantitative analysis on a single flavone compound in a range of 4.0-56 muM, and the first principal component has a good linear relationship with the logarithm of the concentration of the target object.

Description

Technical Field

[0001] This invention belongs to the field of nano-fluorescent detection materials technology, and specifically relates to a fluorescence sensor array based on sulfur quantum dots, its preparation method and detection application. Background Technology

[0002] Flavonoids are a general term for a class of organic derivatives with 2-phenylchromone as the parent nucleus. Their structures often contain substituents such as hydroxyl, methoxy, alkyloxy, and isopentenyloxy groups. The presence of these auxochromes gives these compounds their yellow color. Flavonoids often exist in glycosidic or free states and possess various pharmacological effects, including antioxidant, neuroprotective, antitumor, antibacterial, and immunomodulatory properties. Common flavonoids include quercetin (Que), rutin (Rut), apigenin (Bai), myricetin (Myr), and flavonoid (Fis).

[0003] Common qualitative and quantitative detection methods for flavonoids include HPLC, capillary electrophoresis, ultraviolet absorption spectroscopy, fluorescence spectrometry, and mass spectrometry. HPLC can perform qualitative and quantitative analysis based on the retention time and peak area of ​​different flavonoids on a specific chromatographic column, but the analysis of a single sample is time-consuming. Capillary electrophoresis has limited sensitivity compared to other methods. In UV-Vis spectrophotometry, because flavonoids have similar chromophores and their maximum absorption wavelengths are similar, directly measuring the absorption spectrum yields inaccurate information. Specific reagents are often introduced to react with the flavonoids to detect them by observing changes in the absorption spectrum. Mass spectrometry has low specificity and is easily interfered with by other substances. In mass spectrometry, partially glycosylated flavonoids produce different fragment ions, which can be confused with unmodified compounds with similar structures. Compared to the previous methods, fluorescence spectrometry is widely favored due to its simplicity, speed, and high sensitivity.

[0004] Sulfur quantum dots (SQDs), as a class of inorganic nanomaterials with excellent fluorescence properties, possess advantages such as simple synthesis, low cost, and stable fluorescence performance, showing great potential for development in sensing, optoelectronic devices, and cell imaging. SQDs, with their surfaces modified by different ligands, possess abundant chemical functional groups, which can improve the selectivity of analytical detection based on the characteristics of the analytes, enabling quantitative and semi-quantitative analysis of various substances.

[0005] A fluorescence sensor array is a detection system composed of multiple different fluorescence sensing units. It comprehensively analyzes the changes in fluorescence signals generated by the sensing units of the analyte, creating a unique fingerprint spectrum. Subsequently, through mathematical modeling and data analysis, it can achieve the simultaneous detection and identification of multiple analytes in complex samples. Among these, PCA (Principal Component Analysis) is the most widely used multivariate dimensionality reduction statistical analysis method. The main purpose of PCA is to recombine numerous correlated variables into a new set of uncorrelated comprehensive variables through linear transformation; these comprehensive variables are called principal components. Fluorescence sensor arrays have advantages such as high sensitivity, high throughput, and rapid response, and have broad application prospects in environmental monitoring, food testing, and biomedical analysis. This method has been applied to the rapid classification and identification of various substances, including pesticides, ions, and explosives. Achieving rapid, high-throughput detection of flavonoids using fluorescence array sensing methods is of great significance. However, currently, there is no similar sensor array capable of achieving rapid detection of flavonoids. Summary of the Invention

[0006] The first objective of this invention is to provide a fluorescence sensor array based on sulfur quantum dots, the fluorescence sensor array comprising three independent sulfur quantum dots, C-SQDs, PSS-SQDs and β-SQDs; wherein the dispersant for the PSS-SQDs is sodium polystyrene sulfonate, the dispersant for the β-SQDs is β-cyclodextrin, and the dispersant for the C-SQDs is Na2S2O3·5H2O.

[0007] Furthermore, the synthesis method of the PSS-SQDs includes the following steps: S1. Dissolve sodium polystyrene sulfonate (PSS) in water, then add sublimed sulfur powder and dissolve it in ethylenediamine (EDA) to form a mixed solution; S2. Place the mixed solution in a sealed reaction vessel and heat it to react; S3. After cooling the solution obtained in S2, add hydrogen peroxide and stir. S4. The solution obtained in S3 is added dropwise to icy ethanol for precipitation and separation, and the resulting solid is dried to obtain the PSS-SQDs.

[0008] Furthermore, the amount of PSS added is 0.5-1.2g, the amount of sublimed sulfur added is 0.6-1.5g, the amount of EDA added is 6-12mL, and the amount of H2O2 added is 1-2mL.

[0009] Furthermore, the conditions for the heating reaction are: heating temperature of 140-190℃ and heating time of 5-9h.

[0010] Furthermore, the preparation method of the β-SQDs includes the following steps: Dissolve NaOH in ultrapure water. After cooling, add β-cyclodextrin (β-CD) and sublimed sulfur powder, bringing the solution to 80-120 mL. Sonicate for 10-20 min. Place the resulting suspension in a round-bottom flask and heat in a water bath at 70-85°C for 100-150 h. Stop the reaction when the solution gradually changes from brownish-red to pale yellow. Cool the solution to room temperature and dialyze for 24 h using a dialysis bag with a molecular cutoff of 1000 Da, changing the dialysate every 5-8 h. Finally, freeze-dry the dialysate for 24-30 h to obtain a pale yellow flocculent solid, which is β-SQDs.

[0011] Furthermore, the amount of β-cyclodextrin added is 5.3-8.0g, and the amount of sublimed sulfur powder added is 2.2g-3.5g.

[0012] Furthermore, the water bath heating conditions are 70-85℃ for 100-150 hours.

[0013] Furthermore, the preparation method of the C-SQDs includes the following steps: This invention also provides a method for preparing the aforementioned sulfur quantum dot-based fluorescent sensor array, comprising the following steps: preparing three sulfur quantum dot sensing solutions in test tubes respectively: S1. Add 1200 μL of PBS buffer (0.10 M, pH 6.0) to a test tube, then add 800 μL of 0.50 mg / mL C-SQDs and mix well. S2. Add 1983 μL of PBS buffer (0.10 M, pH 7.5) to a test tube, then add 17 μL of 1.0 mg / mL PSS-SQDs and mix well. S3. Add 1800 μL of PBS buffer (0.10 M, pH 7.0) to a test tube, then add 200 μL of 1.0 mg / mL β-SQDs and mix well.

[0014] The present invention also provides the application of the sulfur quantum dot-based fluorescent sensor array in the detection of flavonoids.

[0015] Furthermore, the flavonoid compound is selected from at least one of baicalin, Fis, Myristicin, Quercetin, and Rut.

[0016] Furthermore, the sulfur quantum dot-based fluorescent sensor array can perform qualitative or semi-quantitative detection of flavonoids.

[0017] The present invention also provides a method for detecting flavonoids using the sulfur quantum dot-based fluorescence sensor array, comprising the following steps: S1. Prepare a series of solutions of various concentrations for each flavonoid standard. React each concentration and each flavonoid standard solution with three different SQDs sensing solutions. After incubation for 15 minutes, measure the fluorescence intensity of each mixture at the optimal excitation / emission wavelength using a fluorescence spectrophotometer. Record the fluorescence intensity after adding the flavonoid compound. F and the initial fluorescence intensity when not added F 0 ; S2. For each measurement, calculate the normalized fluorescence response signal: ( FF 0 ) / F 0 Ultimately, each specific type and concentration of flavonoid compound sample will yield 3 data points, corresponding to the response values ​​of 3 sensor channels, and the data of all samples will be arranged into a matrix. S3. Use Origin2021b to perform PCA analysis on the obtained data matrix, check the variance contribution rate of each principal component, select the first two PC1 and PC2 as principal components, use PC1 as the x-axis and PC2 as the y-axis, and plot the score of each sample on a two-dimensional graph, which is the PCA model of flavonoid compound standards. S4. When it is necessary to detect an unknown sample, process the sample according to the same steps, measure its fluorescence response in the three sensing channels, and calculate ( FF 0 ) / F 0 The three values ​​are input into the established PCA model to calculate the projection coordinates of the unknown sample on the PCA score map; the projection point is observed to determine which standard cluster it falls near, thereby identifying the type qualitatively; and a semi-quantitative estimate is made by analyzing the relationship between the location and the concentration gradient of the standard.

[0018] Beneficial technical effects of the present invention: (1) The three-channel sulfur quantum dot (SQDs) fluorescence sensor array constructed in this invention can generate a unique "fluorescent fingerprint" based on the differential fluorescence response of different flavonoids interacting with three SQDs. Through principal component analysis (PCA), these five structurally similar flavonoids can be clearly distinguished in the concentration range of 8.0-56 μM, with a correct classification rate of 100% (HCA verification), which solves the problem of insufficient selectivity of traditional single detection methods when distinguishing structural analogs.

[0019] (2) This sensor array can be used not only for qualitative differentiation but also for concentration detection of single flavonoids. Within the concentration range of 4.0-56 μM, the array shows significant responses to different concentrations of the same flavonoid, and the first principal component in its PCA score plot exhibits a good linear relationship with the logarithm of the flavonoid concentration (R0). 2 >0.99), thus achieving semi-quantitative and even quantitative analysis of the target analyte.

[0020] (3) Given that flavonoids often exist in mixed forms in actual samples, this array has been successfully applied to distinguish between binary and ternary flavonoid mixtures. Even under different mixing ratios (with a constant total concentration of 40 μM), the array can clearly cluster mixed samples with different compositions on the PCA score map, demonstrating its analytical potential for complex component samples.

[0021] (4) The sensor array was applied to the spiked detection of human serum samples. The results showed that it could accurately identify and classify single flavonoids and their binary and ternary mixtures added to the serum, proving the accuracy and practicality of the method in the detection of actual biological samples. Attached Figure Description

[0022] Figure 1 TEM images of (a) PSS-SQDs and (b) β-SQDs; particle size distribution of (c) PSS-SQDs and (d) β-SQDs.

[0023] Figure 2 (a) TEM image of C-SQDs; (b) Particle size distribution of C-SQDs.

[0024] Figure 3 FT-IR spectra of PSS-SQDs (a) and β-SQDs (b).

[0025] Figure 4 (a) FT-IR spectra of Na2S2O3·5H2O, PEG-400 and C-SQDs; (b) XPS full spectrum of C-SQDs; (c) S 2p high-resolution XPS spectrum of C-SQDs.

[0026] Figure 5 (a) XPS full spectra of PSS-SQDs and (c) β-SQDs; (b) high-resolution S2p XPS spectra of PSS-SQDs and (d) β-SQDs.

[0027] Figure 6(a) Absorption spectrum of PSS-SQDs; (b) Fluorescence emission spectrum of PSS-SQDs in aqueous solution under different wavelengths of excitation; (c) Optimal excitation and emission spectrum of PSS-SQDs; (d) Absorption spectrum of β-SQDs; (e) Fluorescence emission spectrum of β-SQDs in aqueous solution under different wavelengths of excitation; (f) Optimal excitation and emission spectrum of β-SQDs.

[0028] Figure 7 (a) Absorption spectrum of C-SQDs; (b) Fluorescence excitation and emission spectra of C-SQDs; (c) Fluorescence spectra under different excitations; (d) Effect of UV irradiation time on the stability of C-SQDs solution.

[0029] Figure 8 Fluorescence spectra of (a) C-SQDs, (b) PSS-SQDs and (c) β-SQDs before and after the addition of 28 μM Que, Rut, Myr, Fis and Bai, respectively.

[0030] Figure 9 (a) Fingerprint of flavonoids; (b) Two-dimensional PCA score map; (c) SQDs heatmap; (d) HCA cluster analysis map (the concentration of flavonoids is 28 μM).

[0031] Figure 10 Fluorescence intensity changes in PBS buffer at different pH values: (a) C-SQDs, (b) PSS-SQDs, and (c) β-SQDs.

[0032] Figure 11 The effect of reaction time after the addition of Que on the fluorescence intensity of (a) C-SQDs, (b) PSS-SQDs and (c) β-SQDs.

[0033] Figure 12 Two-dimensional PCA score plots of SQDs fluorescence sensor arrays with different concentrations of flavonoids.

[0034] Figure 13 (a) Quantitative analysis of different concentrations of Bai (4.0-56 μM) Two-dimensional PCA score plot (b) Linear fitting of PC1 and logarithm of Bai concentration.

[0035] Figure 14 (a) Quantitative analysis of different concentrations of FIS (4.0-56 μM) Two-dimensional PCA score plot (b) Linear fitting of PC1 and the logarithm of FIS concentration.

[0036] Figure 15 (a) Quantitative analysis of Myr at different concentrations (4.0-56 μM) Two-dimensional PCA score plot (b) Linear fitting of PC1 and the logarithm of Myr concentration.

[0037] Figure 16 (a) Quantitative analysis of different concentrations of Que (4.0-56 μM) Two-dimensional PCA score plot (b) Linear fitting of PC1 and logarithm of Que concentration.

[0038] Figure 17 (a) Quantitative analysis of Rut at different concentrations (4.0-56 μM) Two-dimensional PCA score plot (b) Linear fitting of PC1 and the logarithm of Rut concentration.

[0039] Figure 18 Two-dimensional PCA score plots of fluorescence sensor arrays with different molar ratios of Que, Myr, and Rut (total concentration of 40 μM).

[0040] Figure 19 Absorption plots of C-SQDs before and after the addition of (a) Bai, (b) Fis, (c) Myr, (d) Que and (e) Rut.

[0041] Figure 20 Absorption plots of PSS-SQDs before and after the addition of (a) Bai, (b) FIS, (c) Myr, (d) Que and (e) Rut.

[0042] Figure 21 Absorption plots of β-SQDs before and after addition to (a) Bai, (b) Fis, (c) Myr, (d) Que and (e) Rut.

[0043] Figure 22 Fluorescence spectra of C-SQDs and absorption spectra of (a) Bai, (b) Fis, (c) My, (d) Que and (e) Rut.

[0044] Figure 23 Fluorescence spectra of PSS-SQDs and absorption spectra of (a) Bai, (b) Fis, (c) Myr, (d) Que and (e) Rut.

[0045] Figure 24 Fluorescence spectra of β-SQDs and absorption spectra of (a) Bai, (b) Fis, (c) Myr, (d) Que and (e) Rut.

[0046] Figure 25 Fluorescence lifetime decay curves of (a) C-SQDs, (b) PSS-SQDs and (c) β-SQDs before and after the addition of Bai, Fis, Myr, Que and Rut.

[0047] Figure 26 (a) Fluorescence emission spectra of C-SQDs before and after the addition of Fis; (b) Optimal excitation and emission wavelengths of Fis.

[0048] Figure 27 Two-dimensional PCA score plots of the fluorescence sensing arrays of Bai, Fis, Myr, Que, and Rut in serum samples.

[0049] Figure 28. Two-dimensional PCA score plot of fluorescence sensor arrays with different molar ratios of Que, Myr and Rut (total concentration of 40 μM) in serum samples. Detailed Implementation

[0050] The Na₂S₂O₃·5H₂O, PEG-400, S, NaOH, and dimethyl sulfoxide (DMSO) used in the experiment were purchased from Aladdin Reagent Co., Ltd. (Shanghai, China). KCl, NaCl, PSS, β-CD, NaH₂PO₄·2H₂O, and Na₂HPO₄·12H₂O were purchased from InnoChem Co., Ltd. (Beijing, China). EDA was purchased from Hangzhou Zhongli Chemical Co., Ltd. 30% H₂O₂ was purchased from Hangzhou Metso Biotechnology Co., Ltd. Que, Myr, Lut, Fis, and baicalein standards were purchased from Chengdu Must Bio-technology Co., Ltd.

[0051] Example 1: Synthesis of C-SQDs 4 g of Na₂S₂O₃·5H₂O was dissolved in 25 mL of ultrapure water, followed by the addition of 2 mL of PEG-400. After complete mixing, the mixture was sonicated for 15 min. The solution was then transferred to a polytetrafluoroethylene reactor and reacted at 140 °C for 10 h. Subsequently, the resulting pale yellow solution was dialyzed (molecular weight cutoff of 2000 kDa) for 12 h. Finally, the obtained solution was freeze-dried, and the resulting solid was stored at 4 °C for later use.

[0052] Example 2 Synthesis of PSS-SQDs First, 0.7 g of PSS was dissolved in water in a 100 mL beaker, followed by the addition of 1.0 g of sublimed sulfur dissolved in 10 mL of EDA. Once the mixture was fully dissolved, it was transferred to a 50 mL reactor and heated in an electrically heated drying oven at 160 °C for 6 hours. After cooling to room temperature, 1 mL of H₂O₂ was slowly added dropwise while stirring. After standing, an orange-yellow solution was obtained. This solution was then slowly added dropwise to ice-cold ethanol to precipitate and separate the precipitate. Finally, the precipitate obtained after centrifugation was dried in a vacuum drying oven at 50 °C for 12 hours. The resulting solid was PSS-SQDs powder, which was stored at 4 °C for later use.

[0053] Example 3 Synthesis of β-SQDs 8.0 g of NaOH was dissolved in 50 mL of ultrapure water in a 500 mL beaker. After the solution cooled, 7.4 g of β-CD and 2.8 g of sublimed sulfur powder were added, and the solution was brought to a final volume of 100 mL. The mixture was then sonicated for 15 min. The resulting suspension was then placed in a round-bottom flask and heated in a water bath at 75 °C for 120 h. The reaction was stopped when the solution gradually changed from brownish-red to pale yellow. After the solution cooled to room temperature, it was dialyzed for 24 h using a dialysis bag with a molecular cutoff of 1000 Da, with the dialysate changed every 8 h. Finally, the dialysate was freeze-dried for 24 h to obtain a pale yellow flocculent solid, which is β-SQDs. The obtained solid was stored at 4 °C for later use.

[0054] (1) Characterization of SQDs The TEM images of PSS-SQDs and β-SQDs are as follows: Figure 1 As shown in (a) and 1(b), it can be seen that the two types of quantum dots are uniformly spherical in the aqueous phase, and their particle size distribution histograms are as follows: Figure 1 As shown in (c) and 1(d), their average particle sizes are 2.10±0.42 nm and 2.21±0.49 nm, respectively. This indicates the successful synthesis of the two SQDs. The morphology and size distribution of C-SQDs were analyzed by TEM, and the results are shown in […]. Figure 2 As can be seen, C-SQDs are spherical, see Figure 2 (a) and it is uniformly distributed in aqueous solution. Particle size analysis of C-SQDs in the TEM image shows an average particle size of 2.74 ± 0.23 nm. Figure 2 (b).

[0055] The surface functional group properties of two types of SQDs were studied using FT-IR spectroscopy. The FT-IR spectra of PSS-SQDs are shown below. Figure 3 As shown in (a). At 3442cm -1 The broad absorption at 2931 cm⁻¹ is due to the stretching vibrations of -OH and NH. -1 The stretching vibration peak of CH is at 1649 cm⁻¹. -1 The peaks at 1506 cm⁻¹ represent the bending vibrations of CH and CONH, indicating that the solvent EDA also coats the surface of PSS-SQDs, providing them with excellent water solubility and offering amino groups. The S=O peak is located at 1506 cm⁻¹. -1 At this location, SNS is located at 825cm. -1 SO is located at 609cm -1 The location of the PSS and EDA indicates that they are both covered on the surface of PSS-SQDs and may be linked to SQDs through amino and hydroxyl groups. Figure 3 (b) shows the FT-IR spectra of β-SQDs. (At 3439 cm⁻¹) -1The broad absorption band at 2950 cm⁻¹ indicates the stretching vibration of -OH. -1 The characteristic peak of the stretching vibration of CH is located at 1630 cm⁻¹. -1 Corresponding to the bending vibration of -CH, 1150cm -1 The corresponding point corresponds to the CO stretching vibration on the β-CD. Infrared spectroscopy of the β-CD shows that it is attached to the surface of the SQDs. Furthermore, at 990 cm⁻¹... -1 S=O and 620cm -1 The formation of SO bonds at the site also proves the successful synthesis of β-SQDs.

[0056] Figure 5 (a) shows the full XPS spectrum of PSS-SQDs. It can be seen that PSS-SQDs mainly contain five elements: O, C, S, and N. C originates from PSS and EDA molecules, N mainly comes from PSS molecules, and O mainly originates from the oxidation of S on the surface of PSS-SQDs. To further investigate the form of S in these quantum dots, its S2p ​​high-resolution fine XPS spectrum was measured (…). Figure 5 (b) Among them, the absorption peak at 166.58 eV is mainly attributed to SO2. 2- (2p) 3 / 2 The characteristic peak at 167.68 eV is mainly attributed to SO3. 2- (2p) 2 / 3 ) or SO2 2- (2p) 1 / 2 The characteristic peak at 168.48 eV is related to SO3. 2- (2p) 3 / 2 Correspondingly, the absorption peak at 169.88 eV can be attributed to SO4. 2- (2p) 1 / 2 The above results indicate that the surface of PSS-SQDs is mainly composed of SO2. 2- SO3 2- and SO4 2- It exists in the form of. Figure 5 (c) is the XPS total spectrum of β-SQDs, showing that the main elements present are S, O, and C. C mainly originates from β-CD, while O originates from the surface oxidation of SQDs and β-CD. The high-resolution fine spectrum of S 2p in β-SQDs is shown below. Figure 5 As shown in d, its characteristic peak at 163.25 eV can be attributed to S. x 2- The characteristic peak at 168.48 eV can be attributed to SO3. 2- (2p) 2 / 3 The characteristic peak at 169.58 eV can be attributed to SO4. 2- It can be seen that the main form of S is S. x 2-SO3 2- and SO4 2- Subsequently, FT-IR spectral analysis was performed on the C-SQDs, from... Figure 4 (a) It can be found that C-SQDs and PEG-400 have relatively similar FT-IR spectra. Their FT-IR spectra at 3400 cm⁻¹ are similar. -1 1650cm -1 The peaks at 2875 cm⁻¹ correspond to the stretching and bending vibrations of OH, respectively. -1 and 1462cm -1 The peak at 1137 cm⁻¹ corresponds to the stretching vibration of CH. -1 The peaks correspond to the vibrations of COH, and these functional groups are characteristic peaks of PEG-400, indicating that PEG-400 has successfully adhered to the surface of C-SQDs. Furthermore, the FT-IR spectrum of C-SQDs shows peaks located at 671 cm⁻¹. -1 The sharp peak at this point is consistent with the characteristic absorption peak of the SO group, which is consistent with the characteristic functional group of SQDs, further proving the successful synthesis of C-SQDs.

[0057] XPS analysis was also performed on C-SQDs. Figure 4 The full spectrum of (b) shows three peaks at 168 eV, 286 eV and 533 eV, indicating that it is mainly composed of S, C and O elements. Figure 4 (c) is the high-resolution energy spectrum of S 2p in SQDs. As can be seen from the figure, the peak at 161.2 eV corresponds to S 2- The peaks at 162.6 eV, 163.3 eV, and 164.7 eV are the three characteristic peaks of elemental S, while the peak at the binding energy of 166.3 eV corresponds to SO2. 2- (2p) 2 / 3 The peak at 167.65 eV corresponds to SO3. 2- (2p) 2 / 3 ) or SO2 2- (2p) 1 / 2 Furthermore, the peak value of 168.9 eV corresponds to SO3. 2- (2p) 1 / 2 This result indicates that the synthesized C-SQDs have abundant sulfite groups on their surface, suggesting good water solubility.

[0058] (2) Optical properties of PSS-SQDs and β-SQDs Figure 7 (a) shows the UV-Vis spectrum of C-SQDs. The figure shows that C-SQDs have two absorption peaks at 330 nm and 400 nm, indicating that S... x 2-The presence of [certain substances] was further investigated. The fluorescence spectra of C-SQDs were then examined. Figure 7 (b) shows that the optimal excitation wavelength for C-SQDs is 340 nm and the maximum emission wavelength is 460 nm. Figure 7 (c) shows that when the excitation wavelength is shifted from 320 nm to 370 nm, the fluorescence of C-SQDs exhibits a redshift from the optimal emission wavelength of 455 nm to 515 nm, indicating that C-SQDs have wavelength-dependent photoluminescence properties. Figure 7 (d) indicates that the C-SQDs solution exhibited relatively stable luminescence under continuous UV irradiation for 0-60 min. With quinine sulfate as a reference, the relative PLQY of C-SQDs was 0.043.

[0059] The absorption spectrum of PSS-SQDs aqueous solution is as follows: Figure 6 As shown in (a), it can be seen that it has a relatively broad absorption band at 312 nm and a weak absorption peak at 410 nm. This is mainly due to S8 2- and S4 2- The presence of these two characteristic peaks indicates that sublimed sulfur dissolves and forms S. x 2- The reaction process was then investigated. Subsequently, its fluorescence properties were examined. Figure 6 (b) shows the fluorescence emission spectra of PSS-SQDs at different excitation wavelengths. It can be seen that the fluorescence of PSS-SQDs is wavelength-dependent, which is mainly related to the non-uniform particle size of PSS-SQDs. Figure 6 (c) indicates that the optimal excitation and emission wavelengths are 344 nm and 434 nm, respectively. Under these conditions, with quinine sulfate as a reference, the relative PLQY of PSS-SQDs was measured to be 0.18.

[0060] The absorption spectrum of β-SQDs aqueous solution is as follows: Figure 6 As shown in (d), a broad absorption peak can be observed at 340 nm, which is mainly attributed to S8. 2- The presence of this indicates that sublimed sulfur dissolves to form S. x 2- The reaction process, S x 2- It can be oxidized to thiosulfate by dissolved oxygen in water. Subsequently, it is characterized by fluorescence. Figure 6 (e) It can be seen that the fluorescence of β-SQDs also has an excitation wavelength dependence, which is mainly related to the non-uniform particle size of β-SQDs. Figure 6 (f) shows that the optimal excitation wavelength for β-SQDs is 315 nm and the optimal emission wavelength is 428 nm. Under these conditions, with quinine sulfate as a reference, the relative PLQY of β-SQDs was measured to be 0.021.

[0061] Example 4: Construction of a sulfur quantum dot fluorescence sensing array for flavonoids To effectively construct a SQDs fluorescent probe sensing array for identifying flavonoids, the fluorescence response behavior of three probes to different flavonoids was first investigated. Different flavonoids interact differently with the probes, resulting in different fluorescence responses. The fluorescence changes of three SQDs to five different flavonoids were first studied. After adding different types of the same concentration (28 μM) of Que, Rut, Fis, Myr, and Bai, the three SQDs exhibited different fluorescence responses, as shown in the results below. Figure 8 As shown, the fluorescence intensity of the three SQDs decreased after the addition of the same concentration of flavonoids, but the magnitude of the decrease varied.

[0062] The change in relative fluorescence intensity of each fluorescence sensing unit after the addition of flavonoids is expressed as ( ). FF 0 ) / F 0 It means that, among them F 0 and F The values ​​represent the fluorescence intensity of the fluorescent probe solutions with and without flavonoids, respectively. The numerical values ​​of the relative fluorescence intensity changes serve as the basis for describing the characteristic spectra of five flavonoids: Que, Rut, Myr, Fis, and Bai. Figure 9 As shown in (a), the addition of different flavonoids to three fluorescent probes resulted in different changes in their characteristic spectra, forming a "fingerprint" of five flavonoids. A linear discriminant analysis was performed on the eigenvectors corresponding to the first two factors to obtain a two-dimensional coordinate graph of the fluorescence changes of the fluorescent sensor array for different flavonoids. PCA analysis of this fingerprint spectrum yielded the following results: Figure 9 As shown in (b), the five flavonoids are clearly distinguishable, indicating that the interaction between the five flavonoids and the three SQDs fluorescent probes affects the fluorescence intensity of the SQDs. To more intuitively illustrate the response of flavonoids to SQDs, a heatmap analysis was further performed on the results. Figure 9 c). As can be seen from the figure, each flavonoid compound can produce a characteristic fingerprint and color, which is significantly different from other flavonoid compounds, indicating that the fluorescence sensing array constructed in this chapter has a certain feasibility in distinguishing the five flavonoid compounds.

[0063] To verify the accuracy of PCA analysis, the data was processed using HCA. The Chebyshev distance between two points is defined as the maximum difference between their coordinate values. Taking the coordinates (a1, b1) and (a2, b2) as an example, their Chebyshev distance is Max(|a2-a1|, |b2-b1|). Figure 9 (d) shows the HCA cluster analysis of five flavonoids constructed using Chebyshev distance. Each sample was repeated five times, and it can be seen that types with high similarity among the data were merged together. 100% of the flavonoid samples were correctly classified. The correct differentiation of HCA demonstrates the accuracy and superiority of the fluorescence sensor array with three SQDs as sensing units in distinguishing and identifying flavonoids.

[0064] (1) Optimization of experimental conditions To better distinguish multiple flavonoids simultaneously, the pH of the sensing system was adjusted. Figure 10 ) and reaction time ( Figure 11 ) Perform condition optimization. Figure 10 (a) It can be seen that when the pH increases from 3.0 to 9.0, the fluorescence intensity of the prepared C-SQDs does not change much, and the fluorescence intensity is the highest at pH 6.5. Figure 10 (b) It can be seen that PSS-SQDs are also relatively stable in the pH range of 3.0-9.0, with the maximum fluorescence intensity occurring at pH 7.5. Finally, the effect of pH changes on β-SQDs was measured. Figure 10 c) It can be seen that its fluorescence intensity is basically stable in the pH range of 3.0-9.0, and its relative maximum value occurs at pH 7.0. Therefore, the optimal detection pH values ​​for C-SQDs, PSS-SQDs and β-SQDs are set to pH 6.0, pH 7.5 and pH 7.0, respectively.

[0065] Subsequently, taking Que as an example, the reaction binding time of flavonoids with three SQDs was optimized. For example... Figure 11 As shown, after adding Que, the three SQDs and their reactions were rapid, all reaching reaction equilibrium within 5.0 min. Therefore, the optimal reaction time is 5.0 min.

[0066] Example 5: Response of SQDs sensor array to different types of flavonoids In a fluorescence sensor array using three different SQDs as sensing units, the fluorescence intensity changes of each sensing unit were measured after adding different concentrations (8.0 μM, 12 μM, 20 μM, 28 μM, 36 μM, 44 μM, 52 μM, and 56 μM) of five flavonoids: Que, Rut, Myr, Fis, and Bai. The measurements were repeated five times, resulting in a 3 (3 SQDs) × 5 (5 flavonoids) × 5 (5 replicates) matrix. The (F0-F) / F0 ratio was analyzed using Origin 2021b software using PCA. Linear discriminant analysis was performed on the eigenvectors corresponding to the first two factors. The results are as follows: Figure 12 As shown in the diagram, the first principal component accounts for 51.6%-64.3% of the matrix, while the second principal component accounts for approximately 30.0%-39.6%. The five flavonoid compounds can be well distinguished within a concentration range of 8.0-56 μM, and the positions of the detection results in the two-dimensional coordinate system remain relatively stable after five repeated detections, indicating the high stability of this fluorescence sensor array.

[0067] Example 6: Response of SQDs fluorescence sensor array to the same type of flavonoid compound at different concentrations PCA fluorescence array analysis was performed on Bai, FIS, Myr, Que, and Rut at different concentrations within the range of 4.0–56 μM. First, fluorescence array sensing analysis was performed on Bai, and the PCA score of Bai is shown in the figure below. Figure 13 As shown in (a), PC1 accounts for 98.9% of the sample. Different concentrations of Bai are all identified by this sensor array, with samples of the same concentration clustering together, while Bai of different concentrations separate into different clusters. This indicates that the sensor array has high sensitivity, achieving sensitive detection even at a low concentration of 4.0 μM. Further research shows that the concentrations of PC1 and Bai exhibit a good logarithmic relationship in the range of 4.0–56 μM. Figure 13 As shown in (b), its linear equation is y = 2.85 × (Log C) bai -3.81 (R) 2 =0.998).

[0068] Subsequently, two-dimensional array sensing analysis was also performed on four flavonoids—Fis, Myr, Que, and Rut—in the range of 4.0–56 μM. Their PCA score plots are shown below. Figure 14 (a) Figure 15 (a) Figure 16 (a) and Figure 17(a) Analysis of the PCA score plot shows that the PC1 percentage is between 99.4% and 99.8%, and different concentrations of flavonoids have different distribution ranges. Furthermore, samples of the same concentration cluster together, indicating that the fluorescence sensor array has good recognition performance for the same flavonoid at different concentrations. Further research shows that as the concentration of flavonoids increases, the concentration distribution is not random, but rather exhibits a regular left-to-right arrangement from low to high. Linear fitting of PC1 with the logarithm of concentration was also performed on different concentrations of Fis, Myr, Que, and Rut (4.0 μM, 8.0 μM, 16 μM, 24 μM, 32 μM, 40 μM, 48 μM, and 56 μM), and the results are as follows. Figure 14 (b) Figure 15 (b) Figure 16 (b) and Figure 17 As shown in (b), their linear relationships are y = 2.59 × (Log C) Fis -3.46 (R) 2 =0.990), y=2.85×(Log C Myr -3.82 (R) 2 =0.995), y=2.86×(Log C Que -3.84 (R) 2 =0.998) and y=2.85×(Log C) Rut -3.81 (R) 2 =0.998), these results further demonstrate that the constructed SQDs fluorescence sensor array has good distinguishing and recognition capabilities for the five flavonoid compounds.

[0069] Example 7: Response of SQDs sensor array to binary and ternary flavonoid mixtures In real-world samples, flavonoids often exist as mixtures. Therefore, qualitative and semi-quantitative determination of binary or ternary mixtures is of significant practical importance. Three representative flavonoids, Que, Myr, and Rut, were selected and mixed in pairs at a total concentration of 40 μM with different molar ratios: 0:40, 5:35, 10:30, 15:25, 20:20, 30:10, 35:5, and 40:0. The fluorescence change (F0-F) / F0 was measured, followed by PCA analysis. Figure 18 The PCA two-dimensional score plot (ac) shows that when any two flavonoids of different concentration ratios of Que, Myr and Rut are mixed together, they can aggregate into different groups at a concentration of 40 μM.

[0070] Subsequently, Que, Myr, and Rut were mixed in ternary ratios of 0:40:0, 5:10:25, 10:25:5, 10:5:25, and 25:5:10. The fluorescence response of the three fluorescent probes to these mixtures was measured, and the changes in relative fluorescence intensity were then analyzed by PCA. The results are as follows: Figure 18 As shown in the two-dimensional score plot of the ternary mixture in (d), the mixed samples with different molar ratios can be clearly distinguished, and the correlation with PC1 is 94.6%. The above experimental results fully demonstrate that the C-SQDs / PSS-SQDs / β-SQDs sensing array also has good recognition ability for binary and ternary flavonoid mixtures.

[0071] Exploring the sensing mechanism This invention explores the sensing response mechanisms of three quantum dots (SQDs) to different flavonoid compounds. First, the effects of mixing each quantum dot with different flavonoid compounds were calculated. K sv and k q The results are shown in Table 4-1. It can be seen that each group... k q The values ​​are all much smaller than (10) 10 M -1 s -1 (Molecular diffusion rate constant), thus ruling out the possibility of dynamic quenching. Subsequently, it was determined whether the addition of flavonoids caused changes in the absorption spectra of different SQDs. Figure 19 It can be seen that no new absorption peaks appeared after the five flavonoids were mixed with C-SQDs, and the mechanism may be IFE or FRET. Figure 20 The shift in the absorption peak of PSS-SQDs and five different flavonoids suggests that, in addition to IFE, SQE may also be involved in its mechanism of action. Figure 21 The UV absorption spectra of β-SQDs after the addition of different flavonoids show that the absorption peaks changed after the addition of Bai, FIS, and Myr, which is considered to be the combined effect of IFE and SQE. However, no new absorption peaks appeared after the addition of Que and Rut, indicating that the quenching mechanism of these two flavonoids may be IFE.

[0072] Table 1. K values ​​of flavonoids that induce fluorescence quenching in SQDs sv , τ0 and k q value

[0073] Subsequently, the absorption spectra of five flavonoids (Bai, Fis, Myr, Que, and Rut) and the fluorescence excitation and emission spectra of three SQDs (SQDs, PSS-SQDs, and β-SQDs) were measured respectively. Figure 22 , 23 As can be seen from Figures 2 and 24, the absorption peaks of flavonoids can overlap with the excitation peaks of the three SQDs. Therefore, it is inferred that their fluorescence quenching may be due to IFE or FRET.

[0074] Finally, the fluorescence decay curves of the three SQDs before and after the addition of flavonoids were measured and their fluorescence lifetimes were fitted. Figure 25 As shown in (a), the fluorescence lifetime of C-SQDs is 1.35 (0.07 ns). After adding Bai, Fis, Myr, Que and Rut, the fluorescence lifetimes are 1.31 (0.06 ns), 1.32 (0.06 ns), 1.29 (0.08 ns), 1.30 (0.03 ns) and 1.34 (0.07 ns), respectively. The fluorescence lifetime change rate is less than 4.5%. Figure 25 (b) The fluorescence lifetimes of PSS-SQDs before and after mixing with five flavonoid compounds, namely Bai, Fis, Myr, Que and Rut, are 5.65 (0.10 ns), 5.49 (0.08 ns), 5.46 (0.12 ns), 5.40 (0.13 ns), 5.61 (0.09 ns) and 5.50 (0.11 ns), respectively, with a fluorescence lifetime change rate of less than 3.5%. Figure 25 (c) The fluorescence lifetime of β-SQDs is 5.03 (0.14 ns). When mixed with Bai, Fis, Myr, Que, and Rut, the lifetime is slightly shortened, specifically 5.03 (0.11 ns), 4.89 (0.09 ns), 4.93 (0.07 ns), 5.00 (0.10 ns), and 4.99 (0.12 ns), with a fluorescence lifetime change rate of less than 2.8%. It can be seen that the fluorescence lifetime of the three SQDs remains basically unchanged after the addition of flavonoids. Therefore, it can be determined that their fluorescence quenching is mainly attributed to IFE.

[0075] The addition of Fis to C-SQDs actually increased the fluorescence intensity of the system. Figure 26 a). This is mainly due to the inherent fluorescence properties of Fis. The optimal excitation wavelength of Fis is 370 nm, and the emission wavelength is 509 nm. Figure 26 (b) Since its emission wavelength is close to that of C-SQDs, it exhibits enhanced fluorescence.

[0076] Example 8: Detection of actual samples Based on the above results, this fluorescence sensor array can identify flavonoids in aqueous samples. To further verify its practical feasibility, its recognition effect in serum samples was investigated. Equal concentrations (36 μM) of Bai, FIS, Myr, Que, and Rut solutions were added to serum, and the relative fluorescence intensity changes sensed by the SQDs array were detected. The PCA two-dimensional score map was then obtained. Figure 27 As shown, the addition of these five flavonoids to the SQDs array resulted in five distinct categories of relative fluorescence intensity changes. Furthermore, the actual sample and the measured standard PCA spectrum showed significant overlap. Moreover, there was no overlap between the five different flavonoids. These results validated the accuracy and practicality of the fluorescence sensor array, demonstrating its ability to accurately identify and correctly classify the five flavonoids (Bai, Fis, Myr, Que, and Rut) in serum samples.

[0077] Based on this, the classification of binary or ternary mixtures of Myr, Que, and Rut with different molar ratios at a total molar concentration of 40 μM was also determined in serum samples, and the results are shown in Figure 28. It can be seen that the binary or ternary flavonoid mixtures with different molar ratios are clearly distinguishable without overlapping parts, further demonstrating that the constructed fluorescence sensor array can effectively distinguish flavonoid mixtures with different ratios in serum.

[0078] In summary, this invention constructs a three-channel SQDs fluorescence sensor array for identifying and detecting flavonoids. Based on the differences in fluorescence changes caused by the varying fluorescence responses of different flavonoids to the three SQDs, fluorescence-specific identification fingerprints for Bai, Fis, Myr, Que, and Rut were established. PCA analysis of the relative fluorescence intensity changes of the sensor array revealed that within the range of 8.0-56 μM, the constructed fluorescence sensor array can effectively distinguish and identify these five flavonoids, clearly demonstrating the differences in results produced by different flavonoids. Simultaneously, the SQDs fluorescence sensor array can also identify different concentrations of a single flavonoid within the concentration range of 4.0 μM-56 μM. The PC1 percentage in its PCA analysis is consistently above 98%, and a good linear relationship is established with the logarithm of the flavonoid concentration, enabling quantitative analysis. Furthermore, this fluorescence sensor array can also effectively distinguish binary or ternary mixtures of Myr, Que, and Rut. Further research indicates that SQDs, PSS-SQDs, and β-SQDs are based on IFE for the sensing and identification of flavonoids. Finally, the constructed fluorescence sensor array can also achieve qualitative identification and detection of single flavonoids and binary and ternary mixtures in human serum samples, providing a new, rapid, and accurate identification method for the effective identification and detection of flavonoids with subtle differences.

Claims

1. A fluorescence sensor array based on sulfur quantum dots, characterized in that: The fluorescence sensor array includes three independent sulfur quantum dots: C-SQDs, PSS-SQDs, and β-SQDs. The dispersant for PSS-SQDs is sodium polystyrene sulfonate, the dispersant for β-SQDs is β-cyclodextrin, and the dispersant for C-SQDs is Na2S2O3·5H2O.

2. The sulfur quantum dot-based fluorescence sensor array according to claim 1, characterized in that: The method for synthesizing PSS-SQDs includes the following steps: S1. Dissolve sodium polystyrene sulfonate (PSS) in water, then add sublimed sulfur powder and dissolve it in ethylenediamine (EDA) to form a mixed solution; S2. Place the mixed solution in a sealed reaction vessel and heat it to react; S3. After cooling the solution obtained in S2, add hydrogen peroxide and stir. S4. The solution obtained in S3 is added dropwise to icy ethanol for precipitation and separation, and the resulting solid is dried to obtain the PSS-SQDs.

3. The sulfur quantum dot-based fluorescence sensor array according to claim 2, characterized in that: The amount of PSS added is 0.5-1.2g, the amount of sublimed sulfur added is 0.6-1.5g, the amount of EDA added is 6-12mL, and the amount of H2O2 added is 1-2mL.

4. The sulfur quantum dot-based fluorescence sensor array according to claim 2, characterized in that: The conditions for the heating reaction are: heating temperature of 140-190℃ and heating time of 5-9h.

5. The sulfur quantum dot-based fluorescence sensor array according to claim 1, characterized in that: The preparation method of the β-SQDs includes the following steps: Dissolve NaOH in ultrapure water. After cooling, add β-cyclodextrin (β-CD) and sublimed sulfur powder, bringing the solution to 80-120 mL. Sonicate for 10-20 min. Place the resulting suspension in a round-bottom flask and heat in a water bath at 70-85°C for 100-150 h. Stop the reaction when the solution gradually changes from brownish-red to pale yellow. Cool the solution to room temperature and dialyze for 24 h using a dialysis bag with a molecular cutoff of 1000 Da, changing the dialysate every 5-8 h. Finally, freeze-dry the dialysate for 24-30 h to obtain a pale yellow flocculent solid, which is β-SQDs.

6. The sulfur quantum dot-based fluorescence sensor array according to claim 5, characterized in that: The amount of β-cyclodextrin added is 5.3-8.0g, the amount of sublimed sulfur powder added is 2.2-3.5g, and the water bath heating conditions are 70-85℃ for 100-150h.

7. A method for fabricating a sulfur quantum dot-based fluorescent sensor array as described in any one of claims 1-6, characterized in that: The steps include: preparing three different sulfur quantum dot sensing solutions in test tubes respectively: S1. Add 1200 μL of PBS buffer (0.10 M, pH 6.0) to a test tube, then add 800 μL of 0.50 mg / mL C-SQDs and mix well. S2. Add 1983 μL of PBS buffer (0.10 M, pH 7.5) to a test tube, then add 17 μL of 1.0 mg / mL PSS-SQDs and mix well. S3. Add 1800 μL of PBS buffer (0.10 M, pH 7.0) to a test tube, then add 200 μL of 1.0 mg / mL β-SQDs and mix well.

8. The application of a sulfur quantum dot-based fluorescent sensor array as described in any one of claims 1-6 in the detection of flavonoids, characterized in that: The flavonoids are selected from at least one of baicalin, ficus-indole, myricetin, quercetin, and rutin.

9. The application of a sulfur quantum dot-based fluorescence sensor array as described in claim 8 in the detection of flavonoids, characterized in that: The sulfur quantum dot-based fluorescence sensor array can perform qualitative or semi-quantitative detection of flavonoids, which are used for non-disease diagnosis and treatment.

10. A method for detecting flavonoids using a sulfur quantum dot-based fluorescent sensor array as described in any one of claims 1-6, characterized in that: Includes the following steps: S1. Prepare a series of solutions of various concentrations for each flavonoid compound standard; react each concentration and each flavonoid standard solution with three SQDs sensing solutions, incubate for 15 minutes, and then use a fluorescence spectrophotometer to measure the fluorescence intensity of the solutions at the optimal excitation / emission wavelength, recording the fluorescence intensity after the addition of the flavonoid compound. F and the initial fluorescence intensity when not added F 0 ; S2. For each measurement, calculate the normalized fluorescence response signal: ( F - F 0 ) / F 0 Ultimately, each specific type and concentration of flavonoid compound sample will yield 3 data points, corresponding to the response values ​​of 3 sensor channels, and the data of all samples will be arranged into a matrix. S3. Use Origin2021b to perform PCA analysis on the obtained data matrix, check the variance contribution rate of each principal component, select the first two PC1 and PC2 as principal components, use PC1 as the x-axis and PC2 as the y-axis, and plot the score of each sample on a two-dimensional graph, which is the PCA model of flavonoid compound standards. S4. When it is necessary to detect an unknown sample, process the sample according to the same steps, measure its fluorescence response in the three sensing channels, and calculate ( F - F 0 ) / F 0 The three values ​​are input into the established PCA model to calculate the projection coordinates of the unknown sample on the PCA score map; the projection point is observed to determine which standard cluster it falls near, thereby identifying the type qualitatively; and a semi-quantitative estimate is made by analyzing the relationship between the location and the concentration gradient of the standard.

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