Colorimetric-fluorescent dual-mode array sensor based on heterocyclic azo derivative as well as preparation method and application of colorimetric-fluorescent dual-mode array sensor

Abstract

The invention discloses a colorimetric-fluorescent dual-mode array sensor based on heterocyclic azo derivatives as well as a construction method and application of the colorimetric-fluorescent dual-mode array sensor. The sensor is formed by compounding heterocyclic azo derivatives with different substitution sites and a colorimetric or fluorescent dye. The addition of the target analyte can cause the change of the RGB value or the fluorescence signal of the composite system, so that the recognition is realized. When in use, the fingerprint spectrum of each analyte is firstly established, and then the response spectrum of an unknown sample is matched with the standard spectrum to determine the type of the unknown sample. The array sensor has strong versatility, can realize 100% distinguishing of 12 polyhydroxy compounds, and has identification accuracy rates of 99.0% and 96.0% for 12 pathogenic bacteria in a buffer solution and a urine system. And high-efficiency detection and identification of a group of sensing elements in various types of samples are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of colorimetric-fluorescent dual-mode array sensors, and particularly to a colorimetric-fluorescent dual-mode array sensor based on heterocyclic azo derivatives, a construction method thereof, and an application thereof. Background Art

[0002] Flavonoids are a class of typical substances with polyhydroxy structures and are widely present in natural products. Due to the presence of multiple hydroxyl groups in their structures and high structural similarity, it poses challenges for their analysis and detection. Traditional detection methods such as high-performance liquid chromatography (HPLC), liquid chromatography-mass spectrometry (LC-MS), chemiluminescence analysis, and electrochemical methods, although having certain accuracy, have limitations such as cumbersome operation, high cost, and dependence on professional personnel, especially in terms of rapid and high-throughput detection.

[0003] The array sensing technology draws on the recognition mechanism of the animal taste system. Through a sensing array composed of multiple non-specific recognition units, it responds to the target substances in the sample to generate a characteristic "fingerprint spectrum". Compared with traditional methods, this technology is easy to operate, responds quickly, and can effectively distinguish polyhydroxy compounds with similar structures. Optical array sensors have become a research hotspot for the detection of polyhydroxy substances in recent years due to their visual output and good resolution ability.

[0004] Furthermore, the surfaces of bacteria are usually rich in biological macromolecules with polyhydroxy structures such as lipopolysaccharides, peptidoglycans, and glycoproteins, which makes the array sensor show potential in the field of microbial recognition. Especially in clinically common urinary tract infections, pathogenic bacteria (such as Escherichia coli, Enterococcus, etc.) have specific sugar structures on their surfaces, providing recognition targets. Currently, the diagnosis of urinary tract infections mainly relies on urine culture methods. Although the results are reliable, the detection period is long (24 - 48 hours), which is difficult to meet the needs of rapid diagnosis and treatment in outpatient clinics and primary medical care. Although molecular biology techniques such as PCR are rapid in detection, their equipment costs are high and the operations are complex, limiting their application in a wide range of clinical scenarios. And urinary tract infections often involve multi-drug resistant bacteria. If the types of pathogenic bacteria cannot be identified clearly within a short time, it is extremely easy to lead to treatment delays and increased drug resistance, especially in high-risk populations such as the elderly and pregnant women, which may induce serious complications.

[0005] Therefore, developing a pathogen recognition platform based on array sensing technology, with visual output, easy operation, and high sensitivity, can achieve rapid screening of pathogenic bacteria in urinary tract infections and provide support for precise antibacterial treatment, which has important clinical significance and application prospects. Summary of the Invention

[0006] Objective of the Invention: The objective of the present invention is to provide an array sensor, which can achieve colorimetric discrimination of polyhydroxy substances and fluorescence response detection of pathogenic bacteria causing urinary tract infections by respectively compounding a heterocyclic azo derivative with a colorimetric or fluorescent dye.

[0007] Technical Solution: The present invention provides a colorimetric-fluorescent dual-mode array sensor based on a heterocyclic azo derivative. The colorimetric array sensor includes at least two different sensing units composed of a heterocyclic azo derivative and a colorimetric dye / fluorescent dye;

[0008] The general structural formula of the heterocyclic azo derivative is as follows:

[0009]

[0010] Wherein:

[0011] B is an organic precursor building block, including a five-membered aromatic ring or a six-membered aromatic ring; X- is a halogen anion.

[0012] Further, B in the heterocyclic azo derivative is selected from the following structures:

[0013]

[0014] Further, the colorimetric dyes include:

[0015]

[0016] Further, the fluorescent dyes include:

[0017]

[0018] Further, the heterocyclic azo derivative includes the following structures:

[0019]

[0020] Further, when the heterocyclic azo derivative and the colorimetric dye form a sensing unit, the concentration of the heterocyclic azo derivative is 50 - 200 μM, and the concentration of the colorimetric dye is 100 - 500 μM; when the heterocyclic azo derivative and the fluorescent dye form a sensing unit, the concentration of the heterocyclic azo derivative is 50 - 200 μM, and the concentration of the fluorescent dye is 1 - 50 μM.

[0021] The present invention also provides a construction method of the above colorimetric-fluorescent dual-mode array sensor, including the following steps:

[0022] (1) Using 4-aminopyridine as a raw material, preparing a diazo intermediate through a diazotization reaction;

[0023] (2) The diazo intermediate is subjected to quaternization reaction with phenylboronic acids at different substitution positions to prepare heterocyclic azo derivatives substituted with different boric acids;

[0024] (3) The heterocyclic azo derivative is mixed with a colorimetric dye / fluorescent dye to obtain the sensing unit.

[0025] Specifically, it includes the following steps:

[0026] (1) Using 4-aminopyridine as the raw material, deionized water as the solvent, sodium hypochlorite solution (active chlorine content 30.0%) is added dropwise under ice bath. After the addition is complete, stir at room temperature until the reaction ends. Ethyl acetate is added under stirring, the organic phase is extracted and collected, concentrated in vacuo, and subjected to column chromatography to obtain a yellow solid S;

[0027] (2) The yellow solid S and phenylboronic acids at different substitution positions in a fixed ratio (molar concentration ratio 1:3) are dissolved in N-methylpyrrolidone, stirred at 140 - 160 °C, cooled to room temperature after the reaction ends, the reaction solution is added dropwise to chloroform, a precipitate is formed, and filtered by suction. The filter cake is washed with chloroform and dried in vacuo to obtain a red solid, which is the heterocyclic azo derivative;

[0028] (3) The heterocyclic azo derivative is mixed with a colorimetric dye / fluorescent dye to obtain the sensing unit.

[0029] The present invention also provides the application of the above colorimetric-fluorescent dual-mode array sensor in the detection of flavonoids or bacteria. When detecting flavonoids, the colorimetric-fluorescent dual-mode array sensor used is composed of a heterocyclic azo derivative and a colorimetric dye; when detecting bacteria, the colorimetric-fluorescent dual-mode array sensor used is composed of a heterocyclic azo derivative and a fluorescent dye.

[0030] Specifically, when detecting flavonoids: (1) The colorimetric sensing element is mixed with a flavonoid standard, placed on a visual high-brightness detection surface light source, an image is collected using a mobile phone in a dark box, the RGB values are extracted, and the relative RGB change is calculated according to the formula (I - I0) / I0. The obtained two-dimensional array discrimination fingerprint map is used as a model. (2) The colorimetric sensing element and the sample to be detected containing flavonoids are mixed for detection and matched with the model to obtain the detection result. When detecting bacteria: (1) The sensing element is incubated with bacteria to measure the fluorescence intensity, the relative fluorescence intensity change is calculated according to the formula (I - I0) / I0, and the obtained two-dimensional array discrimination fingerprint map is used as a model. (2) The colorimetric sensing element and the sample to be detected containing bacteria are mixed and incubated for detection and matched with the model to obtain the detection result.

[0031] Furthermore, the flavonoids include naringenin, luteolin, apigenin, daidzein, quercetin, genistein, puerarin, naringin, rutin, neohesperidin, hesperidin, and methyl hesperidin.

[0032] Furthermore, the bacteria include Klebsiella pneumoniae (K. pneumoniae), Morganella morganii (M. morganii), Staphylococcus aureus (S. aureus), Enterococcus faecium (E. faecium), Escherichia coli (E. coli), Staphylococcus haemolyticus (S. haemolyticus), Klebsiella oxytoca (K. oxytoca), Pseudomonas aeruginosa (P. aeruginosa), Bacillus cereus (B. cereus), Staphylococcus lugdunensis (S. lugdunensis), Staphylococcus capitis (S. capitis), and Enterococcus faecalis (E. faecalis).

[0033] Beneficial effects: Compared with the prior art, the present invention has the following remarkable advantages: The sensing element structure of the array sensor of the present invention is simple and can be prepared without complex synthesis processes; the analytes are visually analyzed through colorimetric reactions, enabling accurate identification of 12 flavonoids. At the same time, it has a sensitive bacterial fluorescence response and can identify 12 urinary tract infection pathogenic bacteria, possessing the advantage of multiple uses of a set of sensing elements. Description of the Drawings

[0034] Figure 1 It is the absorption curve spectrum after the colorimetric array sensor composed of ON-L and ON-J respectively with cresol red and brilliant yellow is mixed with flavonoid (daidzein). Among them, L is ON-L, J is ON-J, dye1 is cresol red, and dye2 is brilliant yellow;

[0035] Figure 2 It is the RGB response signal of the colorimetric array sensor to 12 flavonoids in water;

[0036] Figure 3 It is the visualization graph (LDA) of the rapid identification of 12 flavonoids by the colorimetric array sensor in water;

[0037] Figure 4 It is the fluorescence titration curve of the heterocyclic azo compound and the fluorescent dye composite;

[0038] Figure 5 It is the fluorescence response signal of the fluorescence array sensor to 12 bacteria in the buffer solution

[0039] Figure 6 It is the visualization graph (LDA) of the fluorescence array sensor to 12 bacteria in the buffer solution;

[0040] Figure 7are the fluorescence response signals of the fluorescence array sensor to 12 kinds of bacteria in urine;

[0041] Figure 8 is the visualization map (LDA) of the fluorescence array sensor to 12 kinds of bacteria in urine. Detailed implementation manners

[0042] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0043] Example 1. Synthesis of water-soluble heterocyclic azo derivatives

[0044] The synthesis route is as follows:

[0045]

[0046] It includes the following steps:

[0047] (1) Add compound 1 (3 g, 1.30 mmol) into a 100 mL round-bottom flask, dissolve it with deionized water, and dropwise add sodium hypochlorite (active chlorine content is 13.0%) in an ice bath. After the reaction is completed, extract with ethyl acetate three times, combine the organic phases, concentrate under vacuum, and perform column chromatography with PE:EA = 1:1. Obtain yellow solid compound 2 (1.64 g), yield: 88%. 1 H NMR (400 MHz, Chloroform-d) δ8.89 - 8.84 (m, 1H), 7.77 - 7.72 (m, 1H).

[0048] (2.1) Add compound 2 (300 mg, 0.178 mmol) and 3 (1.2 g, 0.568 mmol) into a 50 mL eggplant-shaped flask, add 7.0 mL of N,N-dimethylformamide (DMF), heat to 100 °C and stir for 48 h. After the reaction is completed, cool to room temperature, rotary evaporate to remove most of the organic solvents, drop the reaction solution into chloroform, precipitate, filter by suction, wash the filter cake with chloroform, and dry the filter cake under vacuum to obtain yellow solid ON-L (132 mg), yield 75.0%. 1 HNMR (300 MHz, Deuterium Oxide) δ8.25 - 8.16 (m, 1H), 7.63 (dd, J = 7.2, 1.7 Hz, 1H), 7.55 - 7.36 (m, 2H), 7.08 (s, 1H), 5.57 (s, 1H).

[0049] (2.2) Compound 2 (300 mg, 0.178 mmol) and 4 (1.2 g, 0.568 mmol) were added into a 50 mL eggplant-shaped flask, 7.0 mL of N,N-dimethylformamide (DMF) was added, and the temperature was raised to 100 °C and stirred for reaction for 48 h. After the reaction was completed, it was cooled to room temperature, and most of the organic solvents were removed by rotary evaporation. The reaction solution was added dropwise to chloroform, a precipitate was formed, filtered by suction, the filter cake was washed with chloroform, and the filter cake was dried in vacuo to obtain a yellow solid ON-J (120 mg), with a yield of 70.0%. 1 HNMR (300 MHz, Deuterium Oxide) δ 8.25 - 8.16 (m, 1H), 7.63 (dd, J = 7.2, 1.7 Hz, 0H), 7.55 - 7.36 (m, 2H), 7.08 (s, 1H), 5.57 (s, 1H).

[0050] (2.3) Compound 2 (300 mg, 0.178 mmol) and 5 (1.2 g, 0.568 mmol) were added into a 50 mL eggplant-shaped flask, 7.0 mL of N,N-dimethylformamide (DMF) was added, and the temperature was raised to 100 °C and stirred for reaction for 48 h. After the reaction was completed, it was cooled to room temperature, and most of the organic solvents were removed by rotary evaporation. The reaction solution was added dropwise to chloroform, a precipitate was formed, filtered by suction, the filter cake was washed with chloroform, and the filter cake was dried in vacuo to obtain a yellow solid ON-D (110 mg), with a yield of 60.0%. 1 HNMR (400 MHz, Methanol-d4) δ 8.52 (d, J = 7.1 Hz, 1H), 8.40 - 8.31 (m, 1H), 7.74 (d, J = 42.9 Hz, 1H), 7.52 - 7.37 (m, 1H), 7.24 - 7.20 (m, 1H), 5.52 (s, 1H).

[0051] Example 2, Construction and Use of Colorimetric Array Sensor

[0052] ON-L, ON-J and ON-D prepared in Example 1 were respectively dissolved in DMSO to prepare a 1 mM stock solution for standby, and diluted with deionized water to a final concentration of 100 μM. Cresol Red and Brilliant Yellow, the colorimetric dyes, were respectively solubilized with DMSO and diluted with deionized water to a final concentration of 250 μM, and the two were mixed in equal ratio as the sensing unit.

[0053] The method for differentiating different types of flavonoids is as follows: Take 100 μL each of the colorimetric sensing unit and the flavonoid detection sample (the information of flavonoid types is shown in Table 1) and add them to a 96-well plate, and incubate for 10 seconds. Place it on a visual high-brightness detection surface light source, collect images using a mobile phone in a dark box, extract the RGB values, and use the intensity change of the relative RGB data as the detection signal (I - I0) / I0 to obtain the color change values under different RGB channels (Table 2). Taking H4 as an example, under different combinations of cresol red and brilliant yellow in ON-L, ON-J, and ON-D, the addition of H4 causes changes in the absorption curve, proving that the addition of flavonoids causes changes in the ultraviolet absorption of the system ( Figure 1 A - F). Each flavonoid is repeated 4 times as the training set. A total of 36 signal channels are obtained, and 8 signal channels are retained after screening according to the fluorescence corresponding signal ±0.2.

[0054] Table 1. Flavonoid types

[0055]

[0056]

[0057] Table 2. RGB response changes of the colorimetric array sensor to 12 flavonoids

[0058]

[0059]

[0060] Example 3. Analysis and processing of colorimetric array sensor data

[0061] The preparation of the colorimetric array sensor is the same as that in Example 4. Use the statistical analysis software SYSTAT 13 to process and analyze the RGB values, convert the RGB value response mode into a canonical mode using linear discriminant analysis, classify the data matrix, and obtain the two-dimensional array discrimination fingerprint map of the flavonoids contained in the test solution ( Figure 2 ), to achieve visual recognition ( Figure 3 ); The Jackknifed Classification Matrix shows that the accuracy of the array sensor for differentiating flavonoids is 100% (Table 3).

[0062] Table 3 Jackknifed Classification Matrix

[0063]

[0064] Example 4. Differentiation of flavonoids by colorimetric array sensor

[0065] Twelve unknown flavonoid samples were tested according to the above steps, with 2 replicates for each flavonoid as the prediction set. The relative RGB value changes were recorded. Linear discriminant analysis was then used to verify the ability of the model constructed in Example 2 to test unknown samples. The accuracy of the unknown sample prediction was calculated to be 87.5%, achieving the distinction and detection of different flavonoids (Table 4).

[0066] Table 4 Discrimination of 24 blind test samples by colorimetric array sensor

[0067]

[0068] Example 5: System construction and use of fluorescence array sensor

[0069] Dissolve the prepared ON-L, ON-J and ON-D in DMSO to prepare 1 mM stock solution. Set aside.

[0070] The pretreatment method of bacteria is: inoculate the bacterial mother liquid on agar solid culture medium by plate streak method, and culture it in a constant temperature incubator at 37°C overnight. When the bacteria grow to the stable period, select a single colony with good growth condition, place it in MH liquid culture medium, and culture it in a constant temperature shaker at 37°C overnight. After the cultured bacteria are washed with physiological saline several times, they are diluted with buffer solution (pH = 4.4, the buffer solution is prepared by 0.2 mol / L disodium hydrogen phosphate and 0.1 mol / L citric acid, pH = 9.3, the buffer solution is prepared by 0.1 mol / L sodium carbonate and 0.1 mol / L sodium bicarbonate) to OD 600 =0.01, and two bacterial samples with different pH values were prepared. The bacterial species information is shown in Table 5, among which those without strain numbers were provided by the Laboratory Department of Zhongda Hospital Affiliated to Southeast University.

[0071] The method for distinguishing different types of bacteria is to combine the prepared ON-L, ON-J and ON-D with the fluorescent dye ES or MS, and obtain the quenching curves under different concentration ratios to determine the optimal composite ratio of the two. The standard is to quench the fluorescence to 30.0% of the initial value ( Figure 4 100 μL of each of the complex (ON-L, ON-J and ON-D concentrations were 100 μM; the concentration of the fluorescent dye was 10 μM) and bacteria were added to a 96-well plate. The final OD of the bacteria was 600= 0.005. There were 6 replicates for each type of bacterium. Fluorescence intensities at 480 nm were collected at excitation wavelengths of 368 nm (ES) and 358 nm (MS), and the relative fluorescence intensity change (I - I0) / I0 was used as the detection signal. Composite solutions of bacteria and the fluorescence array sensor were used to construct 12 signal channels at different pH values (pH = 4.4 and 9.3) (2 fluorescent dyes, 3 heterocyclic azo compounds, and 2 different pH conditions; the corresponding information for the channels is shown in Table 8). Different sensor units had different fluorescence responses to the bacteria (Tables 6 and 7).

[0072] Table 5. Bacterial species

[0073]

[0074] Table 6. Fluorescence changes of the fluorescence array sensor for 12 types of bacteria in water

[0075]

[0076]

[0077]

[0078] Table 7. Fluorescence responses of the fluorescence array sensor for 12 types of bacteria in water

[0079]

[0080]

[0081]

[0082] Table 8 Different channel combinations

[0083] Channel Channel ES-LpH = 4.4 CH1 MS-LpH = 4.4 CH7 ES-LpH = 9.3 CH2 MS-LpH = 9.3 CH8 ES-JpH = 4.4 CH3 MS-JpH = 4.4 CH9 ES-JpH = 9.3 CH4 MS-JpH = 9.3 CH10 ES-DpH = 4.4 CH5 MS-DpH = 4.4 CH11 ES-DpH = 9.3 CH6 MS-DpH = 9.3 CH12

[0084] Example 6. Analysis and processing of fluorescence array sensor data

[0085] Statistical analysis software SYSTAT (version 13.0) was used to process and analyze the fluorescence correlation data. The fluorescence response patterns were converted into canonical patterns using linear discriminant analysis (LDA), and the tolerance was set to 0.001. The Mahalanobis distance from each individual pattern to the centroid of each group was calculated in the multi-dimensional space, and the assignment of all species was based on the shortest Mahalanobis distance. The relative fluorescence intensity change was as Figure 5 shown. Through the LDA graph ( Figure 6)It can be seen that in the buffer solution, even if there are many different types of bacteria with low concentrations, different categories of bacteria can ultimately be distinguished. The Jackknifed Classification Matrix shows that the accuracy rate of the array sensor in distinguishing bacteria in the buffer solution is 99.0% (Table 9).

[0086] Table 9 Jackknifed Classification Matrix

[0087]

[0088]

[0089] Example 7. Discrimination of unknown bacterial samples by the fluorescence array sensor

[0090] Twelve bacterial samples were tested according to the above steps, and the relative fluorescence intensity changes were recorded with 4 replicates for each. Then, linear discriminant analysis was used to verify the ability of the model constructed in Example 5 to test unknown samples for discriminating bacteria, and the discrimination accuracy rate was 87.5% (Tables 10 and 11).

[0091] Table 10 Discrimination of 48 unknown samples by the fluorescence array sensor in the buffer solution

[0092]

[0093]

[0094] Table 10 Discrimination of 48 blind test samples by the fluorescence array sensor

[0095]

[0096]

[0097] Example 8. Discrimination of bacterial samples in urine by the fluorescence array sensor

[0098] The method for differentiating different types of bacteria in urine is as follows: The testing method is similar to that of Example 5, where the testing system is an artificial urine environment (i.e., replacing the diluted bacteria with buffer solution with artificial urine), and the relative fluorescence intensity change (I - I0) / I0 is used as the detection signal. The composite solution of bacteria and the fluorescence array sensor constructs 12 signal channels (2 fluorescent dyes, 3 heterocyclic azo compounds, and 2 different pH conditions) at different pH values (pH = 4.4 and 9.3). Different sensor units have different fluorescence responses to bacteria (Tables 12 and 13). The Jackknifed Classification Matrix shows that the accuracy rate of the array sensor in differentiating bacteria in the buffer solution is 96.0% (Table 14). The signal channel information is the same as Table 8.

[0099] Table 12 Fluorescence changes of the fluorescence array sensor for 12 kinds of bacteria in urine

[0100]

[0101]

[0102] Table 13 Fluorescence responses of the fluorescence array sensor for 12 kinds of bacteria in urine

[0103]

[0104]

[0105]

[0106] Table 14 Jackknifed Classification Matrix

[0107]

[0108] Example 9. Differentiation of unknown bacterial samples in urine by the fluorescence array sensor

[0109] Test 12 kinds of bacterial samples according to the above steps, with 4 replicates for each, and record the relative fluorescence intensity change. Then, use linear discriminant analysis, and the accuracy rate of differentiating unknown samples is 79.1% (Tables 15 and 16).

[0110] Table 15 Differentiation of the fluorescence array sensor for 48 blind test samples

[0111]

[0112]

[0113] Table 16 Differentiation test of the fluorescence array sensor for 48 unknown samples in urine

[0114]

[0115]

[0116] In the present invention, a heterocyclic azo derivative is combined with a colorimetric sensing element or a fluorescence sensing element to form different sensing mixtures, which are used for visual identification of different polyhydroxy substances and fluorescence detection of common pathogenic bacteria causing urinary tract infections. Different kinds of flavonoids (final concentration 500 μM) are added to the colorimetric array sensor, and each kind is tested 4 times to obtain a data model of 4 (number of repetitions) × 12 (analytes) × 8 (channels). The data is analyzed and processed by a machine learning algorithm. The fluorescence array sensor has an accuracy of 100% for 12 kinds of flavonoids, and the accuracy for differentiating flavonoids in water for unknown samples is 87.5%. Different kinds of bacteria (final concentration OD 600 = 0.005) are added to the fluorescence array sensor, and each kind is tested 6 times to obtain a data model of 6 (number of repetitions) × 12 (bacteria) × 12 (channels). The data is analyzed and processed by a machine learning algorithm. The fluorescence array sensor has accuracies of 99.0% and 96.0% for 12 kinds of bacteria in buffer solution and urine system respectively, and the accuracies for unknown samples in buffer solution and urine system are 87.5% and 79.1% respectively. The present invention provides a multi-purpose dual-mode array sensor, which is simple to construct, easy to operate, and has a rapid reaction. It can visually distinguish a variety of polyhydroxy substances and detect pathogenic bacteria causing urinary tract infections.

[0117] Advantages of this specific embodiment: The preparation method of the array sensor is simple, low in cost, and high in sensitivity, and can be used for timely detection. In addition, the sensor can accurately distinguish a variety of polyhydroxy substances and bacteria, has a relatively high accuracy for differentiating unknown samples and good reproducibility, and has high clinical application potential.

Claims

1. A colorimetric-fluorescent dual-mode array sensor based on heterocyclic azo derivatives, characterized in that, The colorimetric array sensor includes at least two different sensing units composed of heterocyclic azo derivatives and colorimetric dyes / fluorescent dyes; The structural general formula of the heterocyclic azo derivative is as follows: Wherein: B is an organic precursor building block, including a five-membered aromatic ring or a six-membered aromatic ring; X- is a halogen anion.

2. The colorimetric-fluorescent dual-mode array sensor according to claim 1, wherein B in the heterocyclic azo derivative is selected from the following structures:

3. The colorimetric-fluorescent dual-mode array sensor according to claim 1, wherein The colorimetric dyes include:

4. The colorimetric-fluorescent dual-mode array sensor according to claim 1, wherein The fluorescent dyes include:

5. The colorimetric-fluorescent dual-mode array sensor according to claim 1, wherein The heterocyclic azo derivative includes the following structure:

6. The colorimetric-fluorescent dual-mode array sensor according to any one of claims 1 to 5, characterized in that, When the heterocyclic azo derivative and the colorimetric dye form a sensing unit, the concentration of the heterocyclic azo derivative is 50 - 200 μM, and the concentration of the colorimetric dye is 100 - 500 μM; when the heterocyclic azo derivative and the fluorescent dye form a sensing unit, the concentration of the heterocyclic azo derivative is 50 - 200 μM, and the concentration of the fluorescent dye is 1 - 50 μM.

7. Method for constructing a colorimetric-fluorescent dual-mode array sensor according to any one of claims 1-6, characterized in that, It includes the following steps: (1) Using 4-aminopyridine as a raw material, a diazo intermediate is prepared through a diazotization reaction; (2) The diazo intermediate is subjected to a quaternization reaction with phenylboronic acid at different substitution positions to prepare heterocyclic azo derivatives with different boric acid substitutions; (3) The heterocyclic azo derivative is mixed with the colorimetric dye / fluorescent dye to obtain the sensing unit.

8. Use of the colorimetric-fluorescent dual-mode array sensor according to any one of claims 1-6 in the detection of flavonoids or bacteria, characterized in that, When detecting flavonoids, the colorimetric-fluorescent dual-mode array sensor used is composed of a heterocyclic azo derivative and a colorimetric dye; when detecting bacteria, the colorimetric-fluorescent dual-mode array sensor used is composed of a heterocyclic azo derivative and a fluorescent dye.

9. The application according to claim 8, wherein The flavonoids include naringenin, luteolin, apigenin, daidzein, quercetin, genistein, puerarin, naringin, rutin, neohesperidin, hesperidin, methyl hesperidin.

10. The application according to claim 8, wherein The bacteria include Klebsiella pneumoniae (K. pneumoniae), Morganella morganii (M. morganii), Staphylococcus aureus (S. aureus), Enterococcus faecium (E. faecium), Escherichia coli (E. coli), Staphylococcus haemolyticus (S. haemolyticus), Klebsiella oxytoca (K. oxytoca), Pseudomonas aeruginosa (P. aeruginosa), Bacillus cereus (B. cereus), Staphylococcus lugdunensis (S. lugdunensis), Staphylococcus capitis (S. capitis), Enterococcus faecalis (E. faecalis).

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