Method for detecting ascorbic acid in fruit based on colorimetric sensing microneedle patch

Abstract

The invention discloses a method for detecting ascorbic acid in fruits based on a colorimetric sensing microneedle patch. The method comprises the following steps: preparing Ni-Mn-CDs with obvious oxidation-like catalytic ability through a hydrothermal method, and further performing catalytic oxidation on TMB (Tetramethylbenzidine) by using dissolved oxygen to generate blue oxide (ox-TMB); ascorbic acid can be used for reducing ox-TMB into colorless TMB, and has specificity. Ni-Mn-CDs, ox-TMB and a methacrylated gelatin material are combined, and the colorimetric sensing microneedle patch capable of being used for detecting ascorbic acid in fruits is prepared. The method overcomes the defects that a traditional detection mode excessively depends on a large instrument, pretreatment steps are complex, cost is high, and field detection far away from a laboratory cannot be achieved. The input cost is reduced; meanwhile, efficient, rapid, in-situ and visual detection of ascorbic acid is realized.

Description

Technical Field

[0001] The invention belongs to the technical field of analytical chemistry, and in particular relates to a method for detecting ascorbic acid in fruits based on a colorimetric sensing microneedle patch. Background Art

[0002] Microneedle technology is a new type of non-destructive extraction technology developed in recent years. It uses minimally invasive methods to efficiently and quickly extract biomarkers in situ and realize material transfer. It is expected to revolutionize patient screening and disease diagnosis in organisms. Recent studies have shown that methacrylated hyaluronic acid microneedles with high hydrophilicity can extract enough skin interstitial fluid (ISF) in a short time without the help of additional devices, and then be used for offline analysis of metabolites such as glucose and cholesterol. Methacrylate-based gelatin microneedles can extract animal tissue fluid (ISF) in a short time and can effectively quantitatively detect glucose and vancomycin in ISF. The wearable epidermal system combining reverse ion introduction and microneedles can quickly capture and detect free DNA, an important biomarker of nasopharyngeal carcinoma. Colloidal crystal microneedle patches can monitor the changes in glucose content in mice with naked eyes. Cellulose acetate microneedles can be used for blood sugar level detection and insulin administration to treat hyperglycemia while efficiently extracting ISF. The porous silk protein microneedle array obtained by the water-based processing technology of silk protein collects liquid from the inside of the food through capillary action, and then transports the liquid to the identification signal printed on the back of the array, realizing the detection of pathogenic bacteria in food. The double-layer methacrylate hyaluronic acid microneedles prepared by the freeze spray method can effectively deliver insulin to the systemic circulation of mice to control blood sugar levels, and can also extract skin interstitial fluid for timely analysis of biomarkers. The hydrogel microneedles combined with the new non-aqueous direct compression tablets prepared a microneedle array containing a drug reservoir and effectively used for transdermal drug delivery. The ice microneedles prepared by forming a variety of soft materials and then freezing can deliver a variety of active substances through the skin, and can convert almost all microneedles containing water components from soft materials to hard materials, which can not only ensure satisfactory penetration, but also eliminate the limitation of material composition. These applications of microneedles concentrated on the human and animal bodies prove that microneedle technology is an efficient extraction technology. It is particularly noteworthy that some researchers have recently tried to apply microneedle technology to the extraction of substances in plants. DNA extraction microneedles prepared with polyvinyl alcohol (PVA) as the substrate can extract DNA suitable for amplification detection from different plant species within one minute. However, the subsequent detection of DNA molecular sequences still requires further assistance from instruments. Some researchers have designed an integrated microneedle-smartphone nucleic acid amplification platform for sampling and diagnosing a variety of plant pathogens within 30 minutes. At the same time, studies have shown that microneedle devices can pierce the waxy surface of plants and obtain impedance spectra with an average relative noise of 3.83% in an open-air environment. A series of MN designs have been reported based on different liquid sampling mechanisms (including diffusion, capillary action, osmosis, and pressure-driven convection). Summary of the invention

[0003] In order to improve the above technical problems, the present invention provides a colorimetric sensing microneedle patch for detecting ascorbic acid (AA) in fruits, which does not rely on the traditional method of extraction and then detection with laboratory equipment. The present invention uses gelatin-based microneedle (MN) patches to penetrate plant fruit tissues to extract ascorbic acid and other molecules without going through a series of cumbersome pretreatment steps. In addition, metal quantum dots with oxidase-like activity and TMB are added to the microneedles as ascorbic acid colorimetric materials to achieve naked eye detection of ascorbic acid.

[0004] To achieve the above-mentioned object of the invention, the technical solution of the present invention is as follows:

[0005] The present invention provides a microneedle patch, comprising active ingredients and auxiliary materials, wherein the active ingredients are nickel-manganese-doped carbon dots (Ni-Mn-CDs) and 3,3,5,5-tetramethylbenzidine (TMB).

[0006] According to an embodiment of the present invention, the auxiliary material is selected from methacrylated gelatin material.

[0007] According to an embodiment of the present invention, the microneedle patch is solid. Those skilled in the art should understand that when the microneedle patch is solid, the active ingredient is blended with the excipient to form the microneedle patch.

[0008] According to an embodiment of the present invention, the microneedle patch may be in any suitable shape, such as conical, cylindrical, pyramidal, rectangular, quadrangular pyramidal or any other geometric shape, preferably conical.

[0009] According to an embodiment of the present invention, the axial length of the microneedle patch can be 0.1mm to 1.5mm, preferably 0.2mm to 1.2mm, more preferably 0.6mm to 1.0mm, for example 0.1mm, 0.2mm, 0.3mm, 0.4mm, 0.5mm, 0.6mm, 0.7mm, 0.8mm, 0.9mm, 1.0mm, 1.1mm, 1.2mm, 1.3mm, 1.4mm or 1.5mm.

[0010] According to an embodiment of the present invention, the diameter of the bottom circumscribed circle of the microneedle patch may be 0.1 mm to 0.8 mm, preferably 0.2 mm to 0.5 mm, for example 0.1 mm, 0.2 mm, 0.3 mm, 0.4 mm, 0.5 mm, 0.6 mm, 0.7 mm, 0.8 mm.

[0011] According to an embodiment of the present invention, the raw materials for preparing the microneedle patch include nickel manganese doped carbon dots (Ni-Mn-CDs), 3,3,5,5-tetramethylbenzidine (TMB) and auxiliary materials in terms of mass percentage. For example, the mass percentages of the nickel manganese doped carbon dots (Ni-Mn-CDs), 3,3,5,5-tetramethylbenzidine (TMB) and auxiliary materials are (5-15%): (2-8%): (77-93%), exemplified by 10%: 5%: 85%.

[0012] The present invention also provides a method for preparing the microneedle, comprising the following steps:

[0013] (1) dissolving nickel-manganese-doped carbon dots (Ni-Mn-CDs) in solvent s1 to obtain a mixture a1;

[0014] (2) dissolving 3,3,5,5-tetramethylbenzidine (TMB) in solvent s2 to obtain a mixture a2;

[0015] (3) mixing the mixture a1 of step (1) and the mixture a2 of step (2) to obtain a mixture a3;

[0016] (4) mixing the mixture a3 of step (3) with auxiliary materials to obtain a mixture a4;

[0017] (5) Drying and shaping the mixture a4 in step (4) in a microneedle mold and then demoulding the mold to obtain the microneedle patch.

[0018] According to an embodiment of the present invention, the solvents s1 and s2 are the same or different and are independently selected from water or alcohol.

[0019] According to an embodiment of the present invention, based on the mass of the mixture a4, the mass percentage content of the nickel-manganese doped carbon dots (Ni—Mn—CDs) is 5-15%, and 10% is exemplary.

[0020] According to an embodiment of the present invention, based on the mass of the mixture a4, the mass percentage content of 3,3,5,5-tetramethylbenzidine (TMB) is 2-8%, and exemplarily 5%.

[0021] According to an embodiment of the present invention, based on the mass of the mixture a4, the mass percentage content of the auxiliary material is 77-93%, and 85% is exemplary.

[0022] According to an embodiment of the present invention, the method for preparing the microneedle patch further comprises adding an acetic acid buffer solution to the mixture a3. For example, the volume ratio of the mixture a3 to the acetic acid buffer solution may be 1:(1:10), exemplified by 1:1, 1:5.67, 1:10. For another example, the pH of the acetic acid buffer solution is 4.

[0023] According to an embodiment of the present invention, the method for preparing the microneedle patch, in step (5), further comprises adding a photoinitiator to the mixture a4. Preferably, the photoinitiator is, for example, Irgacure 2959.

[0024] According to an embodiment of the present invention, based on the mass of the mixture a4, the mass percentage content of the photoinitiator is 0.01-0.1%, and exemplarily 0.05%.

[0025] According to an embodiment of the present invention, the concentration of the mixture a1 is 1 to 10 mg ml -1 , exemplified by 5 mg ml -1 .

[0026] According to an embodiment of the present invention, the concentration of the mixture a2 is 1-20 mM, exemplarily 10 mM.

[0027] According to an embodiment of the present invention, the nickel-manganese doped carbon dots (Ni-Mn-CDs) are prepared from raw materials including citric acid, a nickel source, a manganese source, ethylenediamine, and water through a hydrothermal reaction.

[0028] In an exemplary embodiment of the present invention, the reaction ratio of citric acid, nickel source, manganese source, ethylenediamine, and water is 0.5%: 0.25%: 0.25%: 0.5%: 98.5%.

[0029] In one embodiment of the present invention, the nickel source is selected from nickel chloride hexahydrate.

[0030] In one embodiment of the present invention, the manganese source is selected from manganese chloride tetrahydrate.

[0031] In one embodiment of the present invention, the temperature of the hydrothermal reaction is 160-200° C., exemplarily 180° C.; the time of the hydrothermal reaction is 6-24 hours, exemplarily 10 hours.

[0032] In one embodiment of the present invention, the method for preparing nickel manganese doped carbon dots (Ni-Mn-CDs) further comprises purifying and drying the reaction solution to obtain nickel manganese doped carbon dots (Ni-Mn-CDs) solid powder. For example, the cooled reaction solution is filtered through a water filter membrane (0.22 μm), the supernatant is collected, and freeze-dried to obtain nickel manganese doped carbon dots (Ni-Mn-CDs) solid powder.

[0033] According to an embodiment of the present invention, the methacrylated gelatin material is prepared by reacting gelatin with methacrylic anhydride. Preferably, the reaction molar ratio of gelatin to methacrylic anhydride is 1:(1-2), exemplarily 1:1.5.

[0034] In one embodiment of the present invention, the preparation of the methacrylated gelatin material is carried out in a solvent system. For example, gelatin is dissolved in a DPBS buffer solution and then mixed with methacrylic anhydride for reaction. For another example, the amount ratio of gelatin to DPBS buffer solution is 1g:(5-20)ml, exemplified by 1g:10ml.

[0035] In one embodiment of the present invention, the reaction temperature is 40-60°C, exemplarily 50°C; the reaction time is 2-4 hours, exemplarily 3 hours.

[0036] In one embodiment of the present invention, the preparation of the methacrylic gelatin material further comprises purifying and drying the reaction solution to obtain the methacrylic gelatin material. For example, after the reaction solution returns to room temperature, the reaction solution is dialyzed in a DPBS buffer solution (12-14 kDa), and then freeze-dried to obtain a methacrylic gelatin material prepolymer. For another example, the dialysis time is 1 to 10 days, exemplarily 7 days; the dialysis temperature is 40 to 60°C, exemplarily 50°C.

[0037] According to an embodiment of the present invention, in step (5), the microneedle mold may be a PDMS microneedle mold. As an example, the microneedle array arrangement is (4-60)×(4-60).

[0038] According to an embodiment of the present invention, step (5) further comprises subjecting the mold after adding the photoinitiator to vacuum treatment. For example, the mold after adding the photoinitiator is placed in a vacuum (600 mm hg) chamber for 20 minutes.

[0039] According to an embodiment of the present invention, step (5) further comprises irradiating the vacuum-treated mold with ultraviolet light. For example, the ultraviolet light intensity is 600 mW cm -2 ; For example, the ultraviolet light exposure time is 60 to 500 seconds, and 200 seconds is an example.

[0040] According to an embodiment of the present invention, in step (5), drying and shaping can be carried out at room temperature or under temperature-controlled conditions in an oven.

[0041] The present invention also provides application of the microneedle patch in detecting ascorbic acid in fruits.

[0042] According to an embodiment of the present invention, the fruit may be, for example, one of apple, mango, nectarine, pear, kiwi and the like.

[0043] A method for detecting ascorbic acid in fruit comprises inserting the above-mentioned microneedle patch into the fruit, then taking it out, photographing the microneedle patch with a smart phone after the color is stable, measuring the color value through the sample picture and constructing the relationship between the color value and the ascorbic acid concentration, indicating the ascorbic acid concentration in the fruit.

[0044] In the present invention, the algorithm for measuring the color value through the sample image and constructing the relationship between the color value and the ascorbic acid concentration is as follows:

[0045] In the work of measuring color values ​​through sample images, building the relationship between color values ​​and concentration, and further predicting concentration, we found that changes in concentration will cause large fluctuations in color, so when processing images, we did not perform grayscale processing on the images. Due to factors such as lighting, temperature, and shooting angle, white spots that are significantly different from the surrounding area are likely to appear in the captured images, or dark spots due to factors such as uneven raw materials, so noise reduction is required before fitting the model.

[0046] 1. Noise reduction

[0047] Different from traditional noise reduction, since concentration is more sensitive to color, multi-step processing is required. The specific processing steps are as follows:

[0048] 1.1 Get the recognition area

[0049] Select a sample area with relatively uniform color on the image, which is called the reference area. This step can be achieved by sliding the identification area in the APP. After that, the APP will automatically obtain the pixel value of the identification area, expressed in RGB format, where RGB represents red, green and blue respectively, and the value range is an integer from 0 to 255 (because the pixel value is represented by the three primary colors R, G, B numerically, and this algorithm is mainly based on color recognition, so the pixel value, color value and RGB are not distinguished in the following text). The screen width is 360 pixels and the identification area is 60*60 pixels.

[0050] 1.2 Sampling

[0051] According to the number of sampling points set by SETTINGS, the pixels in the recognition area are evenly sampled, and the sampling points are used instead of the recognition points in the recognition area to improve the efficiency of subsequent calculations.

[0052] 1.3 Calculate similar modes (also called close modes)

[0053] In order to better represent the main color in an area, we introduce:

[0054] If |a1 - a2| < a0, then a1 and a2 are similar to each other. When the set of similar numbers of an forms the largest similar set in the original set A, the set of similar numbers of an is called the similar mode in the set (note: the similar mode is a set, not a specific number), and a0 is the corresponding allowable error. In color recognition, there are three primary color sets of R, G, and B. Therefore, formula (1) needs to be satisfied to show that color a and color b are similar.

[0055]

[0056] Among them, r a , g a , b a are the RGB values of color a, and r b , g b , b b are the RGB values of color b. r 0 , g 0 , b 0 are the corresponding allowable errors.

[0057] According to formula (1), the similar mode RGBsimilar of the pixel points in this area can be obtained by using the traversal algorithm.

[0058] 1.4 Calculate (area) reference color value

[0059] The R, G, and B values of each element of the similar mode obtained in 1.3 are all close. Therefore, the average value of each primary color is used as the reference color value RGB in this area sign . That is:

[0060]

[0061] Among them, r sign , g sign , b sign are the RGB values of the reference color of this area, RGB similar ·r, RGB similar ·g, RGB similar ·b are the R, G, and B color sets of RGB similar respectively.

[0062] 1.5 Calculate the global similar mode

[0063] The RGB sign calculated in 1.4 can well represent the situation of the main color in this area. However, due to the uneven distribution of the sample concentration, even if a relatively uniform area is selected artificially, certain errors are likely to occur. Therefore, the global similar mode is introduced. If

[0064]

[0065] Among them, r a ,g a ,b a is the RGB value of color a. 0 ,g 0 ,b 0 is the corresponding allowable error, indicating that color a is the regional color reference value RGBs ign When the similar color set is the largest, the set is called the global similarity mode of the reference points in the region. In this step, the pixels obtained are not limited to the reference region, but the entire screen.

[0066] According to formula (3), the traversal algorithm can be used to obtain the similarity mode RGB of the pixels on the screen. global-similar

[0067] 1.6 Calculate global reference sample points

[0068] This step is similar to 1.4. The global reference sample point RGB global-sign The R, G, and B values ​​of are the average values ​​of the R, G, and B sets in RGBglobal-similar.

[0069] 2. Fitting

[0070] Use the power (1 to 4) of the R, G, and B values ​​of the sample global reference color as independent variables, and use the least squares method based on the gradient descent method for fitting (this part is a combination of the least squares method for fitting multivariate straight lines and the least squares method for fitting univariate curves), that is:

[0071] Y=R+R^2+R^3+R^4+G+G^2+G^3+G^4+B+B^2+B^3+B^4+K

[0072] Among them, K is the intercept.

[0073] The reason why we use powers of 1 to 4 is that according to the Weierstrass approximation theorem, we can use Y = ∑a_n X^n to represent any function curve when n tends to infinity. However, as n increases, the influence of the a_n X^n term will gradually decrease. Generally, when it reaches 4, it can represent a not-too-complex fitting curve. According to the Weierstrass approximation theorem, for any continuous function f(x), there exists a polynomial sequence {Pn(x)} on a bounded closed interval [a,b], such that when n tends to infinity, the polynomial sequence Pn(x) gradually approaches the function f(x). In other words, we can find a series of polynomial functions that are infinitely close to a given continuous function.

[0074] This theorem ensures that no matter how complex a continuous function is, it can be approximated by a polynomial function by properly choosing the order of the polynomial.

[0075] Specifically, for a continuous function f(x), we can represent it using the sum of polynomials:

[0076] f(x)=a 0 +a 1 x+a 2 x 2 +...+anx n +...

[0077] where a 0 ,a 1 ,a 2 ,... are the polynomial coefficients, and n is the order of the polynomial. By increasing the order of the polynomial, we can approximate the original function more accurately.

[0078] Beneficial effects of the present invention:

[0079] The present invention is based on the biocompatibility and non-toxicity of methacryloyl gelatin (GelMA) and its swelling properties, and is expected to be used for the extraction of plant juice. Microneedles can penetrate the wax layer of the plant body to achieve non-destructive extraction of substances in the plant body. However, the detection in the middle and late stages of the prior art still relies on large traditional analytical instruments in the laboratory, which cannot achieve real-time in-situ detection of field plants, and thus cannot achieve precision farming.

[0080] As the most direct detection method, colorimetry can achieve in-situ detection with the naked eye. It gets rid of the dependence on large instruments on the basis of reducing input costs and is very suitable for fields far away from laboratories. The recent development of nanomaterials has once again promoted the further development of colorimetry. The use of nanomaterials such as nanoenzymes, polydiacetylene, colloidal crystals, quantum dots and the selective color development of the test objects can achieve naked eye detection of a variety of substances. For example, Fe-NC single-atom nanozymes can detect the activity of galactose peroxidase; thiol-functionalized polydiacetylene films can be used for naked eye detection of ethylene; titanium dioxide microspheres have been proven to be contactless, high-performance, ultrafast and stable optical humidity colorimetric sensors; cadmium telluride quantum dots can be used to detect the residues of organophosphorus pesticides. These studies have shown that the color development reaction of nanomaterials has very high sensitivity and selectivity, and can achieve naked eye detection. In view of this:

[0081] The present invention prepares Ni-Mn-CDs with obvious oxidation-like catalytic ability by a hydrothermal method, and further uses dissolved oxygen to catalyze and oxidize TMB to generate blue oxide (ox-TMB). Ascorbic acid can reduce ox-TMB to colorless TMB, and has specificity. Ni-Mn-CDs, ox-TMB and methacrylated gelatin materials are combined to prepare a colorimetric sensing microneedle patch for detecting ascorbic acid in fruits. The method of the present invention avoids the shortcomings of traditional detection methods that are overly dependent on large instruments, complex pretreatment steps, high costs, and cannot achieve on-site detection far from the laboratory. While reducing input costs, efficient, rapid, in-situ, and visual ascorbic acid detection is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 Middle a is the preparation process of ascorbic acid microneedles for visual detection; Figure 1 b, c, and d are scanning electron microscope images of the microneedles; Figure 1 Middle e is an optical microscope image of the microneedle.

[0083] Figure 2 A is the maximum absorption wavelength (243 nm) of ascorbic acid at a concentration of 5 μg / mL in 1% hydrochloric acid solution; Figure 2 In B, there is a standard curve of ascorbic acid (0.0-50.0 μg / mL).

[0084] Figure 3 A in the middle is a flow chart of ascorbic acid detection using visualized microneedles; Figure 3 Middle B is the top view and side view of the microneedle patch and the color images on different fruits; Figure 3 Middle C is a bar graph comparing the ascorbic acid content in fruits measured by colorimetric microneedle and UV spectrophotometry; Figure 3 D in the middle is the consistency result diagram of the ascorbic acid content in mango determined by the colorimetric microneedle method and the UV spectrophotometry.

[0085] Figure 4 A in the middle is the consistency result diagram of the ascorbic acid content in nectarine determined by the colorimetric microneedle method and the UV spectrophotometry; Figure 4 Middle B is: the consistency result diagram of the ascorbic acid content in apples determined by the colorimetric microneedle method and the UV spectrophotometry; Figure 4 Middle C is the consistency result diagram of the ascorbic acid content in pears determined by the colorimetric microneedle method and the UV spectrophotometry; Figure 4 D in the middle is the consistency result diagram of the ascorbic acid content in kiwi fruit determined by the colorimetric microneedle method and the UV spectrophotometry. DETAILED DESCRIPTION

[0086] The technical scheme of the present invention will be further described in detail below in conjunction with specific embodiments. It should be understood that the following embodiments are only exemplary descriptions and explanations of the present invention and should not be construed as limiting the scope of protection of the present invention. All technologies implemented based on the above content of the present invention are included in the scope that the present invention is intended to protect.

[0087] Unless otherwise specified, the raw materials and reagents used in the following examples are commercially available or can be prepared by known methods.

[0088] In the present invention, the preparation process of GelMA MN patch is as follows: Figure 1 As shown in A. The patch was prepared by a micromolding method, in which the GelMA prepolymer was poured into a pre-designed PDMS mold by a reduced pressure method (600 mm hg), and the mold dimensions were: the axial length of the microneedle was 800 μm, the bottom diameter was 225 μm, the distance between the two needle tips was 650 μm, the number of arrays in the mold was 20*20 holes, and the size of the entire microneedle patch was 16 mm*16 mm.

[0089] The microstructure of a single microneedle patch is shown in Figure 1 As shown in (be) (the initial concentration of GelMA is 20%). Both the top view and the side view show a conical MN structure. The magnified image shows that the height and bottom diameter of the microneedle are approximately 800 μm and 225 μm, respectively. Figure 1 Middle (e) is an optical microscope image of the GelMA MN patch, showing a 20*20 evenly arranged MN array fixed on a 16mm*16mm patch, which is used to extract sufficient plant sol for later analysis.

[0090] The techniques commonly used to make nanoparticles of different shapes and sizes include: photolithography, laser cutting, 3D printing, etc. In the present invention, we purchased a customized polydimethylsiloxane (PDMS) mold from Taobao.com Laike Mold Company in advance to make MN patches. The polymer MN patch has a breaking force of up to 1N / needle, which is sufficient to insert into skin and plant tissue without breaking. The microneedle module prepared by the present invention has a height of 800μm, which is the optimal length for penetrating the plant wax layer.

[0091] In the following embodiments of the present invention, the method for detecting ascorbic acid in fruits by ultraviolet spectrophotometry comprises the following steps:

[0092] 1) Determination of ascorbic acid standard curve: Accurately weigh 24.00 mg of ascorbic acid standard, dissolve it in 1% hydrochloric acid solution, and prepare an ascorbic acid mother solution with a concentration of 100 μg / mL. Using 1% hydrochloric acid solution as a blank, perform ultraviolet absorption spectrum scanning in the wavelength range of 200-600 nm, and the maximum absorption wavelength of 1% hydrochloric acid solution of ascorbic acid is measured to be 243 nm ( Figure 2(A).

[0093] 2) Prepare a series of ascorbic acid standard solutions with concentrations of 0.0 μg / mL, 10.0 μg / mL, 20.0 μg / mL, 30.0 μg / mL, 40.0 μg / mL, and 50.0 μg / mL, select a wavelength of 243 nm, measure the absorbance of the ascorbic acid solution, and prepare a standard curve ( Figure 2 As can be seen from the figure, there is a good linear relationship between the ascorbic acid concentration and the absorbance in the range of 0.0 to 50.0 μg / mL (the linear equation is: A = 0.05033C + 0.05751, R = 0.9916, where A is the absorbance value and C is the concentration of the ascorbic acid solution (μg / mL)). This curve can be used to calculate the ascorbic acid content in the fruit sample solution.

[0094] 3) Determination of ascorbic acid content in fruits: Five kinds of fresh fruits (mango, apple, pear, nectarine, kiwi) were washed twice with tap water to remove sludge, then rinsed twice with ultrapure water, and dried on the surface; 5.0000g of pulp tissue was accurately weighed, placed in a juicer, 100mL of 1% hydrochloric acid solution was added, and juice was squeezed for 5 minutes; centrifuged, the supernatant was filtered for standby use; 1% hydrochloric acid solution was used as a blank, and the absorbance of the supernatant was measured at a wavelength of 243nm, and the absorbance was substituted into the standard curve to calculate the ascorbic acid concentration of the five kinds of fruits.

[0095] Example 1

[0096] The preparation method of the colorimetric sensing microneedle patch comprises the following steps:

[0097] (1) Preparation of ascorbic acid colorimetric material: Add 0.1g citric acid, 0.05g nickel chloride hexahydrate, 0.05g manganese chloride tetrahydrate, 1ml ethylenediamine, and 20ml ultrapure water to a hydrothermal kettle. After stirring for 10 minutes, place the hydrothermal kettle in an oven at 180°C and heat for 10 hours. The cooled reaction solution is filtered through a water filter membrane (0.22um), the supernatant is collected, and freeze-dried to obtain a yellow nickel-manganese-doped carbon dot (Ni-Mn-CDs) solid powder. The Ni-Mn-CDs solid powder is prepared into 5mgml with ultrapure water. -1 Prepare a 10 mM solution of 3,3,5,5-tetramethylbenzidine (TMB) powder with anhydrous ethanol. Add 0.1 ml of 5 mg / ml TMB to a 10 ml beaker. -1 The Ni-Mn-CDs aqueous solution, 0.2 ml of 10 mM TMB solution, and 1.7 ml of acetic acid-sodium acetate buffer solution (pH=4) were set aside for later use.

[0098] (2) Preparation of methacryloyl gelatin material: 10 g of gelatin was dissolved in 100 ml of DPBS and stirred continuously at 60°C for 1 hour. 16 ml of methacrylic anhydride was slowly added dropwise to the solution and stirred vigorously at 50°C for 3 hours. After the reaction returned to room temperature, the reaction solution was dialyzed in a 50°C DPBS buffer solution (12-14 kDa) for 7 days. The GelMA prepolymer was obtained after freeze-drying and stored in a refrigerator at 4°C before use.

[0099] (3) Preparation of colorimetric sensing microneedle patch: Weigh 2 g of the GelMA prepolymer prepared in step (2) and add it to the solution in step (1), heat to 50°C, and stir rapidly for 3 hours until completely dissolved. Adjust the temperature to 60°C, add 10 mg of photoinitiator (Irgacure 2959), stir rapidly for 2 hours to dissolve, and set the solution aside for later use. Inject the solution into the PDMS mold, let it stand under vacuum for 20 minutes, absorb the solution containing bubbles, and heat the concentrated solution in an oven at 35°C for 5 hours. Repeat the above process once. Place the filled mold under a UV lamp (365-402nm 30Mw / cm 2 ) for 200 s to achieve the curing effect, and then dried in a room temperature oven for 24 h to obtain a microneedle device (GelMA MN patch).

[0100] Example 2

[0101] The colorimetric microneedle patch prepared in Example 1 was used in conjunction with a smartphone APP to detect the content of ascorbic acid (AA) in mango. Figure 3 As shown in B and D, this microneedle patch can show blue after being inserted into mango to absorb juice. Then, through the image analysis module of the smartphone APP, the ascorbic acid content in mango can be quantitatively detected. We used the image analysis module in the smartphone APP to establish a model corresponding to the color and concentration of 1000nM-30000nM. After the microneedle patch extracts fruit juice, it will show different shades of blue due to different AA concentrations. After taking photos and sampling with the mobile phone APP, the corresponding concentration value will be obtained through the software's own algorithm and data processing.

[0102] Among them, the image analysis module in the smartphone APP realizes the quantitative detection of ascorbic acid concentration in fruits. The algorithm for measuring the color value of the sample image and constructing the relationship between the color value and the ascorbic acid concentration is as follows:

[0103] In the work of measuring color values through sample images, establishing the relationship between color values and concentration, and further predicting concentration, we found that changes in concentration can cause significant fluctuations in color. Therefore, during image processing, the images were not grayscale processed. Due to factors such as lighting, temperature, and shooting angle, white spots with significant differences from the surrounding area are likely to appear in the captured images, or dark spots may be generated due to uneven raw materials, etc. Therefore, noise reduction work needs to be carried out before fitting the model.

[0104] 1. Noise Reduction

[0105] Different from traditional noise reduction, since concentration is sensitive to color, multiple steps of processing are required. The specific processing steps are as follows:

[0106] 1.1 Obtain the recognition area

[0107] Select a sample area with relatively uniform color on the image. This area is called the reference area. This step can be achieved by sliding the recognition area in the APP. After that, the APP will automatically obtain the pixel values of the recognition area, represented in RGB format, where RGB represent red, green, and blue respectively, and the numerical range is an integer from 0 to 255 (since pixel values are numerically represented by the three primary colors R, G, B, and this algorithm mainly focuses on color recognition, so pixel values, color values, and RGB are not distinguished in the following text). The screen width is 360 pixels, and the recognition area is 60 * 60 pixels.

[0108] 1.2 Sampling

[0109] According to the number of sampling points set in SETTINGS, evenly sample the pixels within the recognition area, and use the sampling points to replace the recognition points within the recognition area to improve the calculation efficiency of subsequent steps.

[0110] 1.3 Calculate the similar mode (also called the相近众数)

[0111] To better represent the main color within an area, the following is introduced:

[0112] If |a1 - a2| < a0, then a1 and a2 are similar to each other. When the similar number set of an is the largest similar set in the original set A, the similar number set of an is called the similar mode in the set (note: the similar mode is a set, not a specific number), and a0 is the corresponding allowable error. In color recognition, there are three primary color sets of R, G, and B. Therefore, the formula (1) needs to be satisfied to show that color a and color b are similar.

[0113]

[0114] Among them, r a , g a , b ais the RGB value of color a, r b ,g b ,b b is the RGB value of color b. 0 ,g 0 ,b 0 is the corresponding allowable error.

[0115] According to formula (1), the traversal algorithm can be used to obtain the similarity mode RGBsimilar of the pixels in the area.

[0116] 1.4 Calculate (regional) reference color value

[0117] The R, G, and B values ​​of each element of the similar mode obtained in 1.3 are similar, so the average of each primary color is used as the reference color value RGB in this area. sign .Right now:

[0118]

[0119] Among them, r sign ,g sign ,b sign The RGB value of the reference color of the area. similar r, RGB similar g. RGB similar b is RGB respectively similar The R, G, B color set.

[0120] 1.5 Calculating the global similarity mode

[0121] RGB calculated in 1.4 sign It can well represent the main color in the area, but due to the uneven distribution of sample concentration, even if a relatively uniform area is artificially selected, it is easy to cause certain errors. For this reason, the global similarity mode is introduced.

[0122]

[0123] Among them, r a ,g a ,b a is the RGB value of color a. 0 ,g 0 ,b 0 is the corresponding allowable error, indicating that color a is the regional color reference value RGBs ign When the similar color set is the largest, the set is called the global similarity mode of the reference points in the region. In this step, the pixels obtained are not limited to the reference region, but the entire screen.

[0124] According to formula (3), the traversal algorithm can be used to obtain the similarity mode RGB of the pixels on the screen. global-similar

[0125] 1.6 Calculate global reference sample points

[0126] This step is similar to 1.4. The global reference sample point RGB global-sign The R, G, and B values ​​of are the average values ​​of the R, G, and B sets in RGBglobal-similar.

[0127] 2. Fitting

[0128] Use the power (1 to 4) of the R, G, and B values ​​of the sample global reference color as independent variables, and use the least squares method based on the gradient descent method for fitting (this part is a combination of the least squares method for fitting multivariate straight lines and the least squares method for fitting univariate curves), that is:

[0129] Y=R+R^2+R^3+R^4+G+G^2+G^3+G^4+B+B^2+B^3+B^4+K

[0130] Among them, K is the intercept.

[0131] The reason why we use powers of 1 to 4 is that according to the Weierstrass approximation theorem, we can use Y = ∑a_n X^n to represent any function curve when n tends to infinity. However, as n increases, the influence of the a_n X^n term will gradually decrease. Generally, when it reaches 4, it can represent a not-too-complex fitting curve. According to the Weierstrass approximation theorem, for any continuous function f(x), there exists a polynomial sequence {Pn(x)} on a bounded closed interval [a,b], such that when n tends to infinity, the polynomial sequence Pn(x) gradually approaches the function f(x). In other words, we can find a series of polynomial functions that are infinitely close to a given continuous function.

[0132] This theorem ensures that no matter how complex a continuous function is, it can be approximated by a polynomial function by properly choosing the order of the polynomial.

[0133] Specifically, for a continuous function f(x), we can represent it using the sum of polynomials:

[0134] f(x)=a 0 +a 1 x+a 2 x 2 +...+anx n +...

[0135] where a 0 ,a 1,a 2 ,... are the polynomial coefficients, and n is the order of the polynomial. By increasing the order of the polynomial, we can approximate the original function more accurately.

[0136] Wash the mango with tap water twice to remove the sludge, rinse it with ultrapure water twice, and dry the surface moisture; accurately weigh 5.0000g of pulp tissue, place it in a juicer, add 100mL of 1% hydrochloric acid solution, and squeeze the juice for 5 minutes; centrifuge, take the supernatant and filter it for use; use 1% hydrochloric acid solution as a blank, measure the absorbance at a wavelength of 243nm, substitute it into the standard curve, and calculate the ascorbic acid concentration in mango as 1632nM (n=5); use the microneedle patch prepared in Example 1 of the present invention to measure the ascorbic acid concentration in mango as 1729nM (n=5). Comparing the two methods, it is found that the two methods have good correlation, with a correlation coefficient of 0.97 and an average confidence interval of 95%.

[0137] Example 3

[0138] The colorimetric microneedle patch prepared in Example 1 was used in conjunction with a smartphone APP to detect the ascorbic acid content in nectarines. Figure 3 B, C and Figure 4 As shown in A, the microneedle patch will display blue after being inserted into the nectarine to absorb the juice. Then, the ascorbic acid content in the nectarine can be quantitatively detected by taking photos and analyzing the images through a smartphone APP that has successfully self-modeled.

[0139] The nectarine was washed twice with tap water to remove the sludge, then rinsed twice with ultrapure water, and the surface moisture was dried; 5.0000g of pulp tissue was accurately weighed, placed in a juicer, 100mL of 1% hydrochloric acid solution was added, and the juice was squeezed for 5 minutes; centrifuged, the supernatant was filtered for standby use; 1% hydrochloric acid solution was used as a blank, the absorbance was measured at a wavelength of 243nm, and the standard curve was substituted to calculate the ascorbic acid concentration in the nectarine as 2820nM (n=5), and the ascorbic acid concentration in the nectarine was measured using the microneedle patch prepared in Example 1 of the present invention as 3020nM (n=5). The two methods were compared and found to have good correlation, with a correlation coefficient of 0.98 and an average confidence interval of 95%.

[0140] Example 4

[0141] The colorimetric microneedle patch prepared in Example 1 was used in conjunction with a smartphone APP to detect the ascorbic acid content in apples. Figure 3 B, C and Figure 4 As shown in B, the microneedle patch will display blue after being inserted into the apple to absorb juice. The ascorbic acid content in the apple can be quantitatively detected by taking photos and analyzing the images through a smartphone APP that has successfully self-modeled.

[0142] The apples were washed twice with tap water to remove the sludge, then rinsed twice with ultrapure water, and the surface moisture was dried; 5.0000g of pulp tissue was accurately weighed, placed in a juicer, 100mL of 1% hydrochloric acid solution was added, and the juice was squeezed for 5 minutes; centrifuged, the supernatant was filtered for standby use; 1% hydrochloric acid solution was used as a blank, the absorbance was measured at a wavelength of 243nm, and the standard curve was substituted to calculate the ascorbic acid concentration of the apples as 3310nM (n=5), and the ascorbic acid concentration in the apples measured by the microneedle patch prepared in Example 1 of the present invention was 3517nM (n=5). The two methods were compared and found to have good correlation, with a correlation coefficient of 0.95 and an average confidence interval of 95%.

[0143] Example 5

[0144] The colorimetric microneedle patch prepared in Example 1 was used in conjunction with a smartphone APP to detect the ascorbic acid content in pears. Figure 3 B, C and Figure 4 As shown in C, the microneedle patch can show blue after being inserted into the pear to absorb juice. Then, the self-modeled smartphone APP can be used to take photos and samples, and the image analysis can be used to quantitatively detect the content of ascorbic acid in the pear. The pear was washed with tap water twice to remove the sludge, then rinsed with ultrapure water twice, and the surface moisture was dried; 5.00g of pulp tissue was accurately weighed, placed in a juicer, 100mL of 1% hydrochloric acid solution was added, and the juice was squeezed for 5 minutes; centrifuged, the supernatant was filtered and used for standby; 1% hydrochloric acid solution was used as a blank, the absorbance was measured at a wavelength of 243nm, and the standard curve was substituted to calculate the ascorbic acid concentration in the pear as 3740nM (n=5). The ascorbic acid concentration in the pear was measured using the microneedle patch prepared in Example 1 of the present invention as 4008nM (n=5). The two methods were compared and found to be well correlated, with a correlation coefficient of 0.96 and an average confidence interval of 85%.

[0145] Example 6

[0146] The colorimetric microneedle patch prepared in Example 1 was used in conjunction with a smartphone APP to detect the ascorbic acid content in kiwifruit. As shown in Figures 3B, C and 4D, the microneedle patch can display blue after being inserted into the kiwifruit to absorb juice. The ascorbic acid content in the kiwifruit can be quantitatively detected by taking photos and analyzing the images through the smartphone APP that has successfully self-modeled.

[0147] The kiwi fruit was washed twice with tap water to remove the sludge, then rinsed twice with ultrapure water, and the surface moisture was dried; 5.0000g of pulp tissue was accurately weighed, placed in a juicer, 100mL of 1% hydrochloric acid solution was added, and the juice was squeezed for 5 minutes; centrifuged, the supernatant was filtered for standby use; 1% hydrochloric acid solution was used as a blank, the absorbance was measured at a wavelength of 243nm, and the standard curve was substituted to calculate the ascorbic acid concentration in the kiwi fruit as 23820nM (n=5), and the ascorbic acid concentration in the kiwi fruit was measured using the microneedle patch prepared in Example 1 of the present invention as 24076nM (n=5). The two methods were compared and found to have good correlation, with a correlation coefficient of 0.91 and an average confidence interval of 85%.

[0148] The above is an explanation of the embodiments of the present invention. However, the present invention is not limited to the above embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A microneedle patch, characterized in that: The microneedle patch comprises active ingredients and auxiliary materials, wherein the active ingredients are nickel-manganese-doped carbon dots (Ni-Mn-CDs) and 3,3,5,5-tetramethylbenzidine (TMB).

2. The microneedle patch according to claim 1, characterized in that The auxiliary material is selected from methacrylated gelatin material. Preferably, the microneedle patch is solid. Preferably, the microneedle patch can be in any suitable shape, such as conical, cylindrical, pyramidal, rectangular, quadrangular pyramidal or any other geometric shape, preferably conical. Preferably, the axial length of the microneedle patch may be 0.1 mm to 1.5 mm, preferably 0.2 mm to 1.2 mm, and more preferably 0.6 mm to 1.0 mm. Preferably, the diameter of the bottom circumscribed circle of the microneedle patch may be 0.1 mm to 0.8 mm, preferably 0.2 mm to 0.5 mm.

3. The microneedle patch according to claim 1 or 2, characterized in that: In terms of mass percentage, the raw materials for preparing the microneedle patch include nickel-manganese-doped carbon dots (Ni-Mn-CDs), 3,3,5,5-tetramethylbenzidine (TMB) and auxiliary materials. For example, the mass percentages of the nickel-manganese-doped carbon dots (Ni-Mn-CDs), 3,3,5,5-tetramethylbenzidine (TMB) and auxiliary materials are (5-15%): (2-8%): (77-93%).

4. The method for preparing the microneedle patch according to any one of claims 1 to 3, characterized in that: The preparation method comprises the following steps: (1) dissolving nickel-manganese-doped carbon dots (Ni-Mn-CDs) in solvent s1 to obtain a mixture a1; (2) dissolving 3,3,5,5-tetramethylbenzidine (TMB) in solvent s2 to obtain a mixture a2; (3) mixing the mixture a1 of step (1) and the mixture a2 of step (2) to obtain a mixture a3; (4) mixing the mixture a3 of step (3) with auxiliary materials to obtain a mixture a4; (5) Drying and shaping the mixture a4 in step (4) in a microneedle mold and then demoulding the mold to obtain the microneedle patch.

5. The method according to claim 4, characterized in that The solvents s1 and s2 are the same or different and are independently selected from water or alcohol. Preferably, based on the mass of the mixture a4, the mass percentage content of the nickel-manganese doped carbon dots (Ni—Mn—CDs) is 5-15%. Preferably, based on the mass of the mixture a4, the mass percentage content of 3,3,5,5-tetramethylbenzidine (TMB) is 2-8%. Preferably, based on the mass of the mixture a4, the mass percentage content of the auxiliary material is 77-93%. Preferably, the method for preparing the microneedle patch further comprises adding an acetate buffer solution to the mixture a3. For example, the volume ratio of the mixture a3 to the acetate buffer solution may be 1:(1:10). Preferably, the method for preparing the microneedle patch, in step (5), further comprises adding a photoinitiator to the mixture a4. Preferably, the photoinitiator is, for example, Irgacure 2959. Preferably, based on the mass of the mixture a4, the mass percentage content of the photoinitiator is 0.01-0.1%. Preferably, the concentration of the mixture a1 is 1 to 10 mg ml -1 . Preferably, the concentration of the mixture a2 is 1-20 mM.

6. The method according to claim 4, characterized in that The nickel-manganese doped carbon dots (Ni-Mn-CDs) are prepared from raw materials including citric acid, a nickel source, a manganese source, ethylenediamine and water through a hydrothermal reaction. Preferably, the nickel source is selected from nickel chloride hexahydrate. Preferably, the manganese source is selected from manganese chloride tetrahydrate. Preferably, the temperature of the hydrothermal reaction is 160-200° C., exemplarily 180° C.; the time of the hydrothermal reaction is 6-24 hours, exemplarily 10 hours. Preferably, the method for preparing nickel manganese doped carbon dots (Ni—Mn-CDs) further comprises purifying and drying the reaction solution to obtain nickel manganese doped carbon dots (Ni—Mn-CDs) solid powder. Preferably, the methacrylated gelatin material is prepared by reacting gelatin with methacrylic anhydride. Preferably, the reaction molar ratio of gelatin to methacrylic anhydride is 1:(1-2). Preferably, the preparation of the methacrylated gelatin material is carried out in a solvent system. For example, gelatin is dissolved in a DPBS buffer solution and then mixed with methacrylic anhydride for reaction. For another example, the usage ratio of gelatin to DPBS buffer solution is 1 g: (5-20) ml. Preferably, the reaction temperature is 40-60° C.; and the reaction time is 2-4 hours.

7. The method according to claim 4, characterized in that In step (5), the microneedle mold may be a PDMS microneedle mold. Preferably, the microneedle array is arranged in an array of (4-60)×(4-60). Preferably, step (5) further comprises subjecting the mold to vacuum treatment after the photoinitiator is added. Preferably, step (5) further comprises subjecting the vacuum-treated mold to ultraviolet light exposure, for example, for a period of 60 to 500 seconds.

8. Use of the microneedle patch according to any one of claims 1 to 3 and / or the microneedle patch prepared by the preparation method according to any one of claims 4 to 7 in detecting ascorbic acid in fruits.

9. The use according to claim 8, characterized in that The fruit may be, for example, one of apple, mango, nectarine, pear, kiwi and the like.

10. A method for detecting ascorbic acid in fruit, characterized in that: The method comprises inserting the microneedle patch described in any one of claims 1 to 3 and / or the microneedle patch prepared by the preparation method described in any one of claims 4 to 7 into a fruit, then taking it out, photographing the microneedle patch with a smart phone after the color stabilizes, measuring the color value through the sample picture and constructing a relationship between the color value and the ascorbic acid concentration, thereby indicating the ascorbic acid concentration in the fruit.

Images