Urine sugar detection system and detection method thereof

Abstract

The invention provides a urine sugar detection system and a detection method thereof.The urine sugar detection system comprises detection test paper, a microfluid measurement rod and a detection terminal, the detection test paper comprises a paper substrate and enzyme-copper hybrid nanoflowers, the enzyme-copper hybrid nanoflowers are formed on the paper substrate based on an in-situ growth method, the microfluid measurement rod is provided with a detection chamber, and the detection chamber is provided with a detection probe; the detection test paper is arranged in the detection chamber and is used for adsorbing a to-be-detected urine sample to generate a colorimetric reaction, the detection terminal is used for shooting an image of the detection test paper after the colorimetric reaction is generated, and the detection terminal is also used for detecting urine sugar parameters of the to-be-detected urine sample according to the image. The enzyme-copper hybrid nanoflowers are formed on the test paper based on an in-situ growth method, the detection sensitivity can be enhanced, after a colorimetric reaction is generated, an image is analyzed based on an algorithm, the urine sugar parameter of a urine sample to be detected is obtained, high-precision quantitative measurement is achieved, meanwhile, the system is convenient to use, and the household detection requirement is met.

Description

Technical Field

[0001] The present application belongs to the technical field of biomedical sensors, and in particular, relates to a urine sugar detection system and a detection method thereof. Background Art

[0002] Urine glucose monitoring plays an important role in clinical diagnostics and home healthcare, providing a non-invasive method to detect metabolic imbalances. The presence of glucose in the urine (glycosuria) is often associated with diabetes, renal dysfunction, and other metabolic diseases. Although blood glucose monitoring remains the gold standard for diabetes management, urine glucose testing provides a convenient alternative for initial screening and long-term metabolic assessment. As the prevalence of diabetes and related diseases increases worldwide, the demand for simple, accurate, economical, and non-laboratory urine glucose sensors is increasing.

[0003] Traditional urine glucose testing mainly relies on enzymatic or non-enzymatic colorimetric analysis, usually integrated into paper test strips. These test strips are widely adopted due to their low cost, ease of use and rapid response. However, most commercial home urine glucose tests only provide qualitative or semi-quantitative results, which can only roughly estimate glucose concentrations and lack precise measurement capabilities. The low sensitivity of these methods limits their effectiveness in early diabetes monitoring, especially when glucose concentrations are below 5mmol / L, which may lead to delayed intervention. In contrast, laboratory-grade point-of-care testing (POCT) systems can provide higher sensitivity and quantitative accuracy, but require specialized equipment and personnel to operate, which makes their widespread implementation in home care settings difficult. Therefore, there is an urgent need to develop an innovative sensing platform that can meet the convenience of home testing while achieving laboratory-level detection sensitivity and accuracy. Summary of the invention

[0004] The technical problem solved by the present application is: how to provide a urine sugar detection sensor device with high detection sensitivity, high accuracy and convenience for home detection.

[0005] The present application provides a urine sugar detection system, the urine sugar detection system comprising: A test paper, the test paper comprising a paper substrate and an enzyme-copper hybrid nanoflower, wherein the enzyme-copper hybrid nanoflower is formed on the paper substrate based on an in-situ growth method; A microfluidic measuring stick, wherein the microfluidic measuring stick is provided with a detection chamber, the detection test paper is arranged in the detection chamber, and the detection test paper is used to absorb the urine sample to be tested to produce a colorimetric reaction; The detection terminal is used to capture an image of the test strip after a colorimetric reaction occurs, and the detection terminal is also used to detect and obtain urine sugar parameters of the urine sample to be tested based on the image.

[0006] Optionally, the method for forming the enzyme-copper hybrid nanoflower on the paper substrate based on an in-situ growth method includes: An inorganic copper sulfate solution and an enzyme solution are sequentially deposited on the paper substrate to obtain enzyme-copper hybrid nanoflowers of paper fibers cross-linked to the paper substrate.

[0007] Optionally, the enzyme solution contains glucose oxidase and horseradish peroxidase.

[0008] Optionally, the paper substrate comprises a main body and an adsorption end, wherein the adsorption end is located at an edge of the main body, and a portion of the adsorption end extends out of the detection chamber for absorbing the urine sample to be tested.

[0009] Optionally, the microfluidic measuring rod is further provided with a microfluidic channel, which is located at the edge of the detection chamber and connected to the detection chamber, a part of the adsorption end is located in the microfluidic channel and another part of the adsorption end extends out of the microfluidic channel.

[0010] Optionally, the test paper further comprises a support layer, the paper substrate is attached to the support layer, and the support layer is detachably mounted on the detection chamber.

[0011] Optionally, the method for the detection terminal to obtain the urine sugar parameter of the urine sample to be tested according to the image detection includes: The detection terminal extracts the RGB value of the image; The detection terminal determines the glucose concentration of the urine sample to be tested according to the RGB value and a pre-stored RGB-glucose concentration regression curve.

[0012] Optionally, the microfluidic measuring stick is further provided with a colorimetric reference diagram, wherein the colorimetric reference diagram includes a plurality of different sub-color diagrams, each sub-color diagram corresponding to a different glucose concentration.

[0013] The present application also discloses a detection method of a urine sugar detection system, the detection method comprising: Using the test paper to absorb the urine sample to be tested to perform a colorimetric reaction; Using a detection terminal to capture an image of the detection test paper after a colorimetric reaction occurs; The detection terminal is used to detect the urine sugar parameter of the urine sample to be tested based on the image.

[0014] Optionally, the method of using the test paper to absorb the urine sample to be tested includes: The adsorption end of the paper substrate is immersed in the urine sample to be tested, so that the entire test paper adsorbs the urine sample to be tested.

[0015] The present application provides a urine sugar detection system and a detection method thereof, which have the following technical effects: The enzyme-copper hybrid nanoflowers formed on the test strip based on the in situ growth method can enhance the detection sensitivity. After the colorimetric reaction occurs, the image is captured by the detection terminal, and the image is analyzed based on the algorithm to obtain the urine sugar parameters of the urine sample to be tested, thereby achieving quantitative measurement with high precision. At the same time, the system is relatively convenient to use and meets the needs of home testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is an overall framework diagram of a urine sugar detection system according to one or more embodiments.

[0017] Figure 2 Schematic diagram of the assembly of a test strip and a microfluidic measuring stick according to one or more embodiments.

[0018] Figure 3 Schematic diagram of an exploded view of a test strip according to one or more embodiments.

[0019] Figure 4 Schematic diagram of the detection mechanism and detection process of a urine sugar detection system according to one or more embodiments.

[0020] Figure 5 pictorial diagram of a test strip and a microfluidic measuring stick according to one or more embodiments.

[0021] Figure 6 FIG. 4 is a comparative test chart of fluid absorption of different test strips according to one or more embodiments.

[0022] Figure 7 The figure is a schematic diagram of the design, manufacture and assembly process of the test strip according to one or more embodiments.

[0023] Figure 8 Schematic diagram of the process of in situ synthesis of enzyme-copper hybrid nanoflowers according to one or more embodiments.

[0024] Fig. 9 Graph showing test results of the effects of enzyme and colorimetric substrate concentrations on glucose detection sensitivity according to one or more embodiments.

[0025] Fig.10 A diagram characterizing the structure and composition of a test strip according to one or more embodiments.

[0026] Fig.11 The figure is a result diagram of the analytical performance evaluation of the test strip in terms of reaction kinetics and sensitivity when detecting glucose according to one or more embodiments.

[0027] Fig.12The figure is a result diagram of evaluating the analytical performance of the test strip in terms of stability and specificity when detecting glucose according to one or more embodiments.

[0028] Fig.13 FIG. 4 is a schematic diagram of an image processing workflow according to one or more embodiments.

[0029] Fig.14 The figure is a schematic diagram of a workflow of detection terminal-assisted glucose quantification according to one or more embodiments.

[0030] Fig.15 A schematic diagram of a record tracking module of a detection terminal according to one or more embodiments.

[0031] Fig.16 Schematic diagram of visual and quantitative glucose detection using a urine glucose detection system according to one or more embodiments.

[0032] Fig.17 The figure is a diagram showing the verification results of glucose detection in a urine sample using a urine glucose detection system according to one or more embodiments. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0034] Before describing the various embodiments of the present application in detail, the technical concept of the present application is first briefly described: the current traditional urine sugar detection method is either to use test strips for semi-quantitative rough testing, or to use a laboratory-level POCT system with complex operation for testing, which makes it difficult to take into account detection accuracy, high sensitivity and convenience of home testing at the same time. To this end, the present application provides a urine sugar detection system and a detection method thereof, which forms enzyme-copper hybrid nanoflowers on the test strip based on an in situ growth method, which can enhance the detection sensitivity. After the colorimetric reaction occurs, the image is captured using a detection terminal, and the image is analyzed based on an algorithm to obtain the urine sugar parameters of the urine sample to be tested, thereby achieving quantitative measurement with higher precision. At the same time, the system is more convenient to use and meets the needs of home testing. The specific principles of the urine sugar detection system and the detection method thereof of the present application are described below in conjunction with more embodiments.

[0035] Specifically, Figure 1 , Figure 2 and Figure 3As shown, the urine sugar detection system of the first embodiment includes a test strip 10, a microfluidic measuring stick 20 and a detection terminal 30. The test strip 10 includes a paper substrate and an enzyme-copper hybrid nanoflower, and the enzyme-copper hybrid nanoflower is formed on the paper substrate based on an in-situ growth method; the microfluidic measuring stick 20 is provided with a detection chamber 21, the test strip 10 is arranged in the detection chamber 21, and the test strip 10 is used to adsorb the urine sample to be tested to produce a colorimetric reaction, the detection terminal 30 is used to capture the image of the test strip 10 after the colorimetric reaction is produced, and the detection terminal 30 is also used to obtain the urine sugar parameter of the urine sample to be tested according to the image detection.

[0036] Exemplarily, the paper substrate includes a main body 11 and an adsorption end 12, the adsorption end 12 is located at the edge of the main body 11, and a portion of the adsorption end 12 extends out of the detection chamber 21 for absorbing the urine sample to be tested, thereby allowing the urine sample to be tested to diffuse to the entire main body 11. The microfluidic measuring stick 20 is also provided with a microfluidic channel 22, which is located at the edge of the detection chamber 21 and connected to the detection chamber 21, a portion of the adsorption end 12 is located in the microfluidic channel 22 and another portion of the adsorption end 12 extends out of the microfluidic channel 22. The microfluidic measuring stick 20 of this structure allows the adsorption end 12 to extend into the test tube to adsorb the urine sample to be tested, without the need to use a pipette to transfer the sample, thereby improving the convenience of detection and use.

[0037] Furthermore, the test strip 10 also includes a support layer 13, the paper substrate is attached to the support layer 13, and the support layer 13 is detachably mounted on the detection chamber 21. Exemplarily, the paper substrate and the support layer 13 can be connected by pasting, and the support layer 13 and the detection chamber 21 can be connected by pasting. On the one hand, the overall strength of the test strip 10 can be ensured by the support layer 13, and on the other hand, it is convenient to install the support layer 13 to the detection chamber 21 or remove it from the detection chamber 21 to replace a new test strip 10.

[0038] In one or more embodiments, the microfluidic measuring stick 20 is also provided with a colorimetric reference image 23, which includes a plurality of different sub-color images, each of which corresponds to a different glucose concentration. Exemplarily, the colorimetric reference image 23 provides a glucose concentration gradient from 0 to 0.75 mmol / L. After the test strip 10 produces a colorimetric reaction, the test strip image can be compared with each sub-color image to roughly estimate the glucose level. The user can directly compare the colorimetric reference image 23 to obtain an instant visual reading.

[0039] In one or more embodiments, the method of forming enzyme-copper hybrid nanoflowers on a paper substrate based on an in-situ growth method includes: depositing an inorganic copper sulfate solution and an enzyme solution on the paper substrate in sequence to obtain enzyme-copper hybrid nanoflowers cross-linked to paper fibers of the paper substrate. Exemplarily, the enzyme solution contains glucose oxidase and horseradish peroxidase.

[0040] Exemplarily, the detection mechanism and detection process of the urine sugar detection system are as follows: Figure 4 As shown, the enzyme-copper hybrid nanoflower is composed of multifunctional enzyme copper hybrid nanoflower (GO x &HRP@Cu3(PO4)2·3H2O) and cross-linked in a cellulose matrix to ensure high enzyme stability, improve catalytic efficiency, and optimize substrate active site interactions. The Cu3(PO4)2·3H2O nanopetals act as a structural scaffold to enable glucose oxidase (GO x ) and horseradish peroxidase (HRP) are closely aligned to form a highly ordered hierarchical structure. This biocatalytic arrangement facilitates efficient electron transfer and substrate diffusion, thereby optimizing substrate channeling and reaction kinetics. Figure 4 As shown in B, the detection mechanism involves a catalytic cascade reaction: GO x It catalyzes the oxidation of glucose to gluconic acid, while generating hydrogen peroxide (H2O2) as a byproduct. HRP then utilizes H2O2 to oxidize 3,3',5,5'-tetramethylbenzidine (TMB) to its oxidized form (ox-TMB), producing a visible blue colorimetric signal. The proximity effect in the enzyme-copper hybrid nanoflower structure not only improves the reaction kinetics, but also amplifies the colorimetric reaction by shortening the reaction time and enhancing the signal intensity. Figure 4 As shown, a step-by-step workflow for urine glucose detection using an immersion test method is shown: the process includes pre-treating the urine sample with a TMB solution, immersing the test strip, and obtaining a colorimetric reaction, which can be analyzed visually or quantitatively assisted by a detection terminal. In other embodiments, in addition to TMB colorimetric detection, other chromogenic substrates (such as ABTS or OPD) can be used to achieve different color outputs or improve signal stability. In addition, the chromogenic substrate (e.g., embedded TMB) can be pre-fixed on the test strip to achieve a one-step detection system, eliminating the need for manual pretreatment and further simplifying user operations.

[0041] Among them, the actual operation of the urine sugar detection system follows a simple immersion detection protocol, such as Figure 4As shown in Figure 3, the device includes three steps: (i) pre-treating the urine sample with TMB solution, (ii) immersing the test strip in the pre-treated sample, and (iii) observing the change in the colorimetric signal. It is worth noting that the device provides a dual-mode detection method, combining visual interpretation and quantitative analysis assisted by the detection terminal. Users can directly compare the colorimetric reference chart to obtain an instant visual readout; or use the application of the detection terminal to capture the color intensity of the colorimetric signal to achieve more accurate quantitative analysis of glucose concentration.

[0042] In one or more embodiments, the method for the detection terminal to obtain the urine glucose parameters of the urine sample to be tested based on the image detection includes: the detection terminal extracts the RGB value of the image; the detection terminal determines the glucose concentration of the urine sample to be tested based on the RGB value and the pre-stored RGB-glucose concentration regression curve. Exemplarily, the detection terminal can be a smart phone, and the camera of the smart phone is used to capture the image of the test strip after the colorimetric reaction is generated, and the image is detected using the detection algorithm built into the smart phone, and the urine glucose parameters of the urine sample to be tested are obtained in combination with the RGB-glucose concentration regression curve.

[0043] In one or more embodiments, the detection method of the urine sugar detection system includes: using the detection test paper to absorb the urine sample to be tested and perform a colorimetric reaction; using the detection terminal to capture an image of the detection test paper after the colorimetric reaction occurs; using the detection terminal to obtain the urine sugar parameter of the urine sample to be tested based on the image detection. The adsorption end of the paper substrate is immersed in the urine sample to be tested so that the detection test paper as a whole absorbs the urine sample to be tested.

[0044] The above describes the basic contents of the urine sugar detection system and the detection method. The following describes the working principle, usage method and the effects produced by the urine sugar detection system in more detail with reference to specific examples and experimental processes.

[0045] In one or more embodiments, Figure 5 As shown, the microfluidic measuring stick 20 is in a U-shape, and the bend of the microfluidic measuring stick 20 can be used as a holding point for the operator when performing the test. Its ergonomically slender U-shaped body is made of durable polylactic acid (PLA) 3D printing material to ensure comfort and practicality, and is intended to provide a compact, user-friendly and reliable urine glucose colorimetric detection platform. Exemplarily, the skeleton structure of the microfluidic measuring stick 20 has an outwardly protruding head, and the detection chamber 21 is located at the head to optimize liquid contact. For example, the dimensions of the microfluidic measuring stick 20 are 40 mm wide, 80 mm high, and 1.5 mm thick to ensure durability and the convenience of one-handed operation.

[0046] In one example, the detection chamber 21 is a square detection chamber (length and width of 5.6mm×5.6mm, depth of 1mm) to accommodate a test paper made of Whatman grade 1 filter paper as a paper substrate. Filter paper is selected as the substrate for enzyme immobilization, taking advantage of its high absorbency and stable liquid flow properties. The support layer 13 material is made of 5.6mm×5.6mm PET polyester film and bonded with 3M 467MP tape (thickness 0.01mm) to stabilize the test paper, prevent liquid leakage, and provide protection from environmental pollution. It is worth noting that the adsorption end 12 (1.7mm×1.5mm) enhances direct contact with the urine sample to be tested, thereby improving the liquid absorption efficiency and optimizing the accuracy of the colorimetric reaction.

[0047] To ensure that the test strips had efficient fluid absorption during immersion testing, two different test strips were designed and evaluated to optimize the flow rate after liquid contact. One test strip used a square PET support layer (without external protrusions), while the other test strip had a PET support layer that included external protrusions to support the adsorption end of the test strip12. Figure 6 Schematic diagrams of different test strips and comparative analysis of fluid transfer performance are shown in Table 1. The experimental results show that the test strip with a square support layer (SL) exhibited higher flow rates (average flow rate = 0.433 mm / s, RSD = 6.24%) and lower variability in repeated tests, while the test strip with external protrusions (EL) exhibited lower flow rates (average flow rate = 0.039 mm / s, RSD = 20.51%). Based on these results, the test strip with a square support layer (SL) was adopted as the final implementation because of their excellent fluid transfer consistency and performance. As shown in the following table, the comparative results of the fluid transfer efficiency of two different test strips are shown.

[0048]

[0049] Table 1

[0050] Exemplarily, the microfluidic measuring stick 20 was designed using Fusion 360 CAD software, and an STL model was generated. The model was processed by Bambu Studio (V1.10.89) and printed on a Bambu Lab P1S 3D printer using a 0.2 mm nozzle and white PLA Basic Bambu material. In addition, a colorimetric reference chart was developed and calibrated based on the initial calibration images of the microfluidic measuring stick 20 in the range of 0 to 0.75 mmol / L glucose concentration.

[0051] Specifically, if Figure 7As shown, the disposable test strips are made of Whatman grade 1 filter paper, precisely cut into 7.3 mm × 7.3 mm squares to ensure uniformity and repeatability. Each paper substrate contains two areas: (1) a 1.5 mm × 1.7 mm adsorption end 12 for controlled sample absorption; (2) a 5.6 mm × 5.6 mm body 11, which serves as the main detection area where the enzyme-catalyzed colorimetric reaction occurs. The paper substrate is laminated to a 5.6 mm thick support layer 13 (PET plastic sheet) using 3M tape to provide structural support and prevent enzyme leakage during the functionalization process. The process of cutting the support layer 13 is completed using a Universal Laser System (VLS3.50 software) and high precision is achieved through optimized vector pattern settings.

[0052] like Figure 8 As shown in Figure 1, the in situ growth method involves two steps of sequential solution deposition. First, 2.5 µL of 120 mmol / L CuSO4 solution was pipetted onto the paper substrate to initiate the formation of the inorganic framework. Subsequently, 2.5 µL of enzyme solution (containing 1 mg / mL glucose oxidase GO) was pipetted onto the paper substrate. x and 0.1 mg / mL horseradish peroxidase HRP, dissolved in 0.07 mol / L KH2PO4 buffer, pH 7.4) to provide the organic components required for the formation of hybrid nanoflowers. The test strips were dried at room temperature for 10 minutes to allow copper ions to react with the enzyme and promote the formation of hybrid nanoflowers. Finally, the functionalized test strips were stored in a sealed container at 4 ° C to maintain enzyme activity for subsequent testing.

[0053] To achieve the best performance in glucose detection, the urine glucose detection system optimizes GO x , HRP, and chromogenic substrate (TMB) to increase catalytic efficiency and reduce background noise. Fig. 9 A shows the effect of increasing GOx concentration on the colorimetric response. Fig. 9 B in the figure shows the evaluation of the role of HRP in catalyzing the colorimetric reaction. Fig. 9 C shows the optimal amount of chromogenic substrate to determine the maximum signal intensity, and the error bars represent the standard deviation (SD) of n = 3 independent measurements. Fig. 9 As shown in A, in GO x During the activity optimization process, when GO x When the concentration increased from 0.1 mg / mL to 1.0 mg / mL, the colorimetric signal (ΔR) increased significantly, indicating enhanced catalytic activity. When the concentration exceeded 1.0 mg / mL, the signal tended to saturate, which may be due to the aggregation of enzyme molecules, which restricted the diffusion of substrates. Therefore, 1.0 mg / mL was determined to be the optimal GO x Concentration. Fig. 9B shows the process of optimizing HRP activity. x At the concentration (1.0 mg / mL), when the HRP concentration increased from 0.0 mg / mL to 0.1 mg / mL, the color signal increased significantly, indicating that HRP catalyzed the oxidation of TMB. When the concentration exceeded 0.1 mg / mL, the signal did not change significantly, indicating that the catalytic activity had reached saturation. Therefore, 0.1 mg / mL was selected as the optimal HRP concentration. Fig. 9 As shown in C, the optimization of the chromogenic substrate, TMB concentration was optimized in the range of 0.05–1.0 mg / mL, and the color signal was strongest at 0.5 mg / mL. Further increasing the TMB concentration will not significantly enhance the color change, but may increase the background noise. Therefore, 0.5 mg / mL was determined to be the optimal TMB concentration.

[0054] Furthermore, the surface morphology and elemental composition of the test strips were analyzed using scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) using a PHENOM XL (Phenom World) instrument. Crystal structure analysis was completed by X-ray diffraction (XRD) using a Bruker AXS D8 Discover (TXS). In addition, X-ray photoelectron spectroscopy (XPS) analysis was performed using a Thermo Scientific ESCALAB 250Xi to evaluate the elemental composition and oxidation state.

[0055] Specifically, Fig.10 As shown, Fig.10 A, B, and C represent pure paper strips, Cu3(PO4)2·3H2O deposited on the paper strips, and GO fixed on the paper strips, respectively. x &SEM image of HRP@Cu3(PO4)2·3H2O nanoflowers; Fig.10 D and E represent Cu3(PO4)2·3H2O and GO, respectively. x &EDS elemental mapping of HRP@Cu3(PO4)2·3H2O nanoflowers, showing the spatial distribution of Cu, P, O, and enzyme-related elements. Fig.10 F represents Cu3(PO4)2·3H2O and GO x &XRD pattern of HRP@Cu3(PO4)2·3H2O nanoflowers, confirming the crystal structure of nanoflowers and successful enzyme immobilization. SEM analysis: Pure paper test strips show a porous fiber network ( Fig.10 A), which is conducive to the immobilization of nanomaterials. After loading Cu3(PO4)2·3H2O, a disordered microstructure with a particle size of 2.8-4μm is formed ( Fig.10 B). With GO xWith the further addition of HRP, the nanoflowers formed uniform spherical structures with a size of approximately 5-5.3 μm ( Fig.10 C), star-shaped nanosheets help enhance the stability and catalytic efficiency of the enzyme. EDS element mapping: Cu, P and O are evenly distributed in the Cu3(PO4)2·3H2O structure ( Fig.10 D). Load GO x After HRP, elements such as C, N and S appeared ( Fig.10 E), confirming the successful immobilization of the enzyme. Further, the XRD pattern ( Fig.10 F): Confirm that the Cu3(PO4)2·3H2O crystal phase is intact and matches the ICDD standard card.

[0056] like Fig.11 A, Michaelis-Menten kinetic curves showing the effect of glucose concentration (0–0.5 mmol L -¹ ) time-dependent colorimetric reaction (ΔR). Fig.11 B, derived from kinetic data, is used to determine V max and K m Lineweaver-Burk diagram. Fig.11 C, Glucose detection curve describing the relationship between ΔRGB signal and glucose concentration (0–2 mmol L -¹ ), with a box linear detection range; such as Fig.11 D, Linear regression analysis confirmed a strong correlation between ΔR and glucose concentration, and the error bars represent the standard deviation (SD) of n = 3 independent measurements. Fig.11 As shown, XPS analysis: Fig.11 As shown in Figure A, the XPS survey spectrum confirmed the presence of Cu, O, N, C, and P, verifying the successful immobilization of the enzyme. Fig.11 As shown in B, the Cu 2p spectrum shows that it corresponds to Cu 2+ and Cu + The peaks of the oxidation states indicate the presence of mixed copper valence, which can affect the catalytic activity. Fig.11 As shown in Figure 2, the C 1s spectrum reveals deconvoluted peaks of CC, CN, C=O, and CO, highlighting the organic functional groups integrated into the enzyme. Fig.11 As shown in D, the N 1s spectrum shows peaks of CN / NH and NC=O, further confirming that the enzyme is incorporated through nitrogen-related functional groups.

[0057] Further, for the colorimetric glucose test using hybrid nanoflower functionalized paper strips, the samples were pretreated with 0.5 mg / mL TMB as a chromogenic substrate. Specifically, 2.5 μL of 10 mg / mL TMB stock solution (prepared in DMSO) was added to each 50 μL sample. After pretreatment, 2.5 μL of treated sample was added dropwise to the test strip, and the change in colorimetric signal was recorded. In order to achieve an immersion detection method without a pipette, a 200 µL disposable plastic dropper was used for sample preparation (e.g. Figure 4 C). For each test, the dropper was filled and transferred to an empty container, and then one drop of 10 mg / mL TMB solution (prepared in DMSO) was added. The fully assembled detection system was then immersed in the TMB-treated solution until the adsorption end of the extended tip of the detection strip was completely immersed and then removed. The colorimetric reaction results were recorded by capturing images before and after 3 minutes of immersion.

[0058] The test strips were evaluated in terms of analytical performance including reaction kinetics, sensitivity, stability and specificity, and all experiments were performed under controlled conditions to ensure reproducibility.

[0059] (1) Reaction kinetics: Glucose solutions with concentrations ranging from 0 to 0.5 mmol / L were prepared and pretreated with TMB. A 2.5 µL aliquot of each concentration was introduced onto the test strip and a 5-minute video was recorded using a smartphone. Video frames for each concentration were extracted at 30-second intervals and RGB values ​​were retrieved using a Python script. The change in red intensity (ΔR) was plotted over time to determine the signal stabilization point and record the response time. Fig.11 As shown in A and B, the color signal is stable within 2.5-5 minutes, and the calculated Km=0.15mmol / L indicates that the sensor has a high affinity for glucose.

[0060] (2) Sensitivity assessment: Prepare glucose solutions ranging from 0 to 2 mmol / L, and add 2.5 µL of each sample dropwise to the test strip. Capture images before and 3 minutes after sample application. Repeat the experiment three times, and extract RGB values. Plot the changes in colorimetric signals (ΔR, ΔG, ΔB) versus glucose concentration to evaluate sensitivity. Select the most stable and sensitive channel for further quantification, and determine the linear detection range. Calculate the limit of detection (LOD) using the following formula: LOD = 3σ / S, where σ is the standard deviation of the blank (after repeated measurements 3 times) and S is the slope of the linear calibration curve. Fig.11 As shown in C and D, it shows good linearity in the range of 0–0.75 mmol / L (R ² =0.9925), the calculated LOD = 0.017mmol / L, which is better than most existing colorimetric sensors.

[0061] (3) Stability assessment: Fig.12 A, pH-dependent stability studies focus on the optimal pH conditions for sensor performance; e.g. Fig.12 B. Long-term stability assessment demonstrated retention of enzyme activity over time. The stability of the test strips was evaluated over a pH range of 3.7 to 8.5. A 0.25 mmol / L glucose solution was prepared and the colorimetric response was tested in acetate buffer (pH 3.7–5.6) and phosphate buffer (pH 6.0–8.5) to determine the optimal pH range. In addition, fresh HNF functionalized paper strips were stored at 4°C and evaluated over a six-week period. The colorimetric response was measured weekly using a 0.25 mmol / L glucose solution to assess long-term storage stability. Fig.12 As shown in A and B, the sensor remained stable over a wide pH range of 3.7–7.5 and retained more than 70% of the enzyme activity after six weeks.

[0062] (4) Specificity assessment: Fig.12 C, specificity evaluation for individual interferents, comparing responses to glucose and common urine contaminants; e.g. Fig.12 D, Interference analysis in mixed samples, evaluating sensor performance in complex matrices, error bars represent the standard deviation (SD) of n=3 independent measurements. The specificity of the test strip was evaluated by testing potential interfering substances, including uric acid (equimolar concentration), fructose, galactose, xylose, lactose, maltose, and sucrose (five times the concentration of glucose), as well as NaCl, KCl, creatinine, and urea (ten times the concentration of glucose). Each solution (2.5 μL) was added to the paper strip separately, and the colorimetric reaction was recorded. In addition, a 0.25 mmol / L glucose solution was mixed with each interfering substance and tested to evaluate the signal change. If the ΔR value of glucose is significantly different from the R value of the interfering substance and remains consistent in the presence of mixed interference, the method is considered to have good specificity. Fig.12 As shown in Figures C and D, it is highly selective for common urine interferents such as NaCl, KCl, urea, creatinine, and uric acid.

[0063] Image acquisition and RGB analysis workflow,In colorimetric analysis, images are captured under consistent imaging conditions.,The smartphone is firmly mounted on a phone holder and maintained in a fixed horizontal,direction (e.g. Fig.13 ). The camera captured images from a top-down perspective, ensuring a constant distance to minimize errors due to angle or position changes. All images were taken under controlled lighting conditions, directly illuminated by a specified laboratory light source that was fixed in place to ensure reproducibility. To eliminate external light fluctuations, the imaging setup remained constant throughout the experiment.

[0064] Image processing involves cropping the image after a colorimetric glucose reaction to isolate the color region of interest. To optimize the cropping strategy, three different approaches were evaluated: peripheral cropping, middle cropping, and central cropping. Peripheral cropping includes the entire test strip, capturing both reactive and non-reactive areas. Middle cropping focuses on the primary color region while excluding bright or non-uniform areas at the edges, thereby ensuring balanced selection. Central cropping isolates only a small portion in the center of the reaction zone, prioritizing the most uniform color region. The optimal cropping method was selected based on maximizing the signal-to-noise ratio (SNR) to ensure accurate and consistent colorimetric analysis. This evaluation established an evidence-based approach for effective image processing in glucose testing.

[0065] RGB analysis was performed using a self-developed smartphone application built using TypeScript, WXML, and CSS in the WeChat (WeiXin) integrated development environment (IDE). Initially, RGB values ​​were extracted using a Python script, and the optimized workflow was subsequently integrated into the application to simplify analysis. To ensure reproducibility, all image acquisitions were performed under consistent experimental conditions, including fixed camera settings, constant focal length, and standardized analysis areas.

[0066] Exemplarily, a smartphone application (App) was developed in the WeChat (WeiXin) integrated development environment (IDE) using TypeScript, WXML, and CSS on a Windows 11 operating system. The IDE was hosted on a 13th-generation HP Omen laptop equipped with an Intel Core i9 processor, 32GB DDR5 RAM, and an NVIDIA RTX 4060 GPU (8GB VRAM). The App has cross-platform compatibility and can run seamlessly on both iOS and Android devices. The IDE supports front-end page design using WXML, styling using CSS, and back-end logic implemented using TypeScript (a superset of JavaScript). WXML templates are used to build the user interface, including image upload / shoot buttons, live preview panels, and result display modules. CSS is used to implement dynamic styling and responsive layouts. TypeScript is responsible for managing user interactions, integrating device APIs (such as camera access and gallery retrieval), and facilitating communication with image processing modules.

[0067] The application includes the following functional modules: calibration module (such as Fig.14 The calibration interface shown in the figure is as follows: The user uploads an image of the standard solution and the system generates a regression curve. Fig.14 The detection interface shown in the figure): automatically calculates the glucose concentration to avoid human errors. Recording module (such as Fig.15 Shown): Save historical data to support long-term health monitoring.

[0068] Further, the assembly of the urine glucose detection system involved integrating the test strip into a 3D-printed microfluidic measuring stick. To ensure proper alignment and optimize contact with the urine sample, the test strip was accurately placed in the designated chamber. The calibration of the urine glucose detection system was performed using standard glucose solutions of known concentrations (0 to 1 mmol / L). The colorimetric response was recorded by taking images before and 3 minutes after immersion. As previously described, the red mean channel value was extracted using Python, and the corresponding changes in the colorimetric signal were plotted as a function of glucose concentration. The range in which the colorimetric signal was strongly linearly correlated with the glucose concentration was determined as the linear detection range of the urine glucose detection system and used to generate a calibration curve. To achieve visual color recognition, an image of the linear colorimetric response was printed onto a sticker as a colorimetric reference map on the device. In addition, a smartphone application was used to reconstruct the calibration curve generated by the colorimetric glucose response image and used to determine the glucose level in the actual urine sample. To evaluate the performance of the sensor in visual and quantitative glucose detection, three glucose solutions were prepared, including a blank control (0, 0.25, and 0.75 mmol / L). The colorimetric response of the sensor was compared to a reference color chart by visual inspection to estimate the glucose concentration and further confirmed using a smartphone app. Sample preparation and measurement followed the aforementioned pipette-free immersion detection method, ensuring ease of operation and user-friendliness.

[0069] Specifically, Fig.16 As shown, the linear detection range of the sensor is 0–1mmol L -¹ There is a significant linear relationship within the glucose concentration range ( Fig.16 The red channel showed the most significant signal change, which is consistent with the results of independent paper strip analysis. Calibration curve ( Fig.16 B) shows 0–0.75 mmol L -¹ High correlation coefficient (R ² =0.994), confirming the high accuracy and reliability of quantitative glucose detection. Visual readout: Colorimetric strips ( Fig.16 C) provides a semi-quantitative estimate, allowing the user to directly compare color intensities. The red marked area of ​​the reference bar corresponds directly to the color intensity produced by the detection chamber, making it suitable for non-expert users. Smartphone-assisted quantitative analysis: Image processing via a smartphone app to automatically quantify color changes ( Fig.16 The calibration parameters generated by the smartphone were consistent with the analysis results of the Python script, demonstrating the reliability of the quantitative analysis. The results showed a strong correlation between the visual estimation and the smartphone-assisted analysis ( Fig.16E). User-friendliness and applicability: All measurements were completed by the pipette-free Dip-and-Detect method, simplifying the operation steps. This design is suitable for low-resource environments and non-professional users. The modular design of the urine glucose detection system can be adapted to other biomarker detection, demonstrating its potential in personalized diagnosis and telemedicine. Through these experimental results, the Hybrid μDip sensor demonstrated its practicality in non-invasive glucose detection and provided broad application prospects for future multi-marker detection and telemedicine.

[0070] Urine sample collection and testing protocol: This study has been approved by the Ethics Committee (IRB) of Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences, with approval number SIAT-IRB-250115-H0954. All procedures involving human participants were performed in accordance with the ethical standards set forth in the Declaration of Helsinki, and informed consent was obtained from all volunteers before the study. Urine samples from five volunteers were collected and screened for glucose content using the gold standard method. Glucose solution was mixed with 0.5 mg / mL GO at 37 °C for 24 h. x A glucose standard curve (0–0.5 mM) was prepared by incubation in PBS (pH 7.4) for 25 min. TMB-HRP substrate solution was prepared by mixing 50 μL of 10 mmol / L TMB, 10 μL of 10 mg / mL HRP, and 860 μL of 0.2 M acetate buffer (pH 4.0).

[0071] For each glucose concentration, add 80 μL of glucose-GO to the TMB-HRP mixture. x The reaction solution was incubated at 37°C for 20 minutes and then cooled in an ice water bath for 10 minutes. The absorbance was recorded at 652 nm and a linear regression equation was generated for quantitative analysis. For urine sample analysis, each sample was centrifuged at 12000 rpm for 10 minutes and the supernatant was collected. 0.5 mg / mL GO was then added x , and incubate at 37°C for 25 minutes. Take 80 μL of the reaction mixture and mix it with TMB-HRP substrate solution, incubate at 37°C for 20 minutes, and cool in an ice-water bath. Record the absorbance at 652 nm and calculate the glucose concentration using the standard curve equation, taking into account the dilution factor and applying the Beer-Lambert law for accurate measurement.

[0072] For urine samples containing detectable glucose, they were further tested using the Urine Glucose Detection System. In the Urine Glucose Detection System test, 200 μL of urine samples were collected using a disposable dropper, premixed with a drop of TMB solution, and analyzed using a pipette-free immersion detection method. The fully assembled sensor was immersed in the solution, ensuring that the extended end of the paper strip was completely immersed. After 3 minutes, a preliminary visual glucose estimate was made using a reference color strip, while the colorimetric reaction was quantitatively measured using a smartphone. The color signal before and after 3 minutes was recorded for analysis. When performing statistical analysis, data are presented as mean ± standard deviation (SD), and error bars represent the standard deviation of the mean. The sample size (n) for each analysis is stated in the figure legend. Most experiments were performed in triplicate, and data analysis was performed using Microsoft Excel.

[0073] Specifically, the test results of the real urine samples are as follows. Fig.17 As shown, visual detection: The color chart shows the color change corresponding to the glucose concentration in the urine. Smartphone quantitative detection: The results based on the smartphone application are consistent with the visual readings. Comparison with the gold standard method: The Pearson correlation coefficient R=0.99324 shows that there is a high degree of consistency between the urine glucose detection system and the gold standard results. Enhanced detection sensitivity: Compared with the gold standard method, the sensitivity of low concentration urine glucose is improved by 224%. At high concentrations, the sensitivity is improved by 97%-63%.

[0074] Through the above series of experiments and actual urine tests, the feasibility of the urine glucose detection system was systematically demonstrated, and the main findings include: (1) The optimization of enzyme and TMB concentrations significantly improved the detection sensitivity; (2) Comprehensive material characterization using SEM, EDS, XRD and XPS confirmed the successful formation and structure of hybrid nanoflowers; (3) The sensor has high sensitivity, stability and specificity, which is very suitable for urine glucose monitoring; (4) The smartphone-based analysis system improves the convenience of detection and realizes real-time and user-friendly glucose quantification. (5) Real urine tests show excellent performance and the results are consistent with standard laboratory methods.

[0075] Furthermore, as shown in Table 2, the minimum detection limit (LOD) of the urine sugar detection system of the present application is 0.017 mmol / L, which is much better than the existing commercial urine sugar detection test strips, the detection limit of which is usually 2.2 mmol / L and above. The urine sugar detection system has both semi-quantitative and quantitative analysis modes, providing home users with a more accurate and convenient urine sugar detection method.

[0076]

[0077] Table 2

[0078] According to the test results, the main technical advantages of the urine glucose detection system of this application are: (1) Ultra-high sensitivity: The minimum detection limit is 0.017mmol / L, which can detect trace amounts of glucose, far superior to existing home urine glucose test strips. (2) Quantitative accuracy: The detection terminal application is combined with RGB color analysis to provide real-time quantitative detection, avoiding inaccurate semi-quantitative estimates. (3) Enhanced specificity: Able to resist common interferents (such as uric acid, fructose, galactose, etc.) and maintain high selectivity in complex urine matrices. (4) Long-term stability: Maintain more than 80% activity after 3 weeks of storage and 70% activity after 6 weeks, ensuring continuous testing. (5) Wider pH stability: Maintain high performance in the pH range of 3.7 to 7.5, consistent with physiological urine conditions.

[0079] The specific implementation methods of the present application are described in detail above. Although some embodiments have been shown and described, those skilled in the art should understand that these embodiments can be modified and improved without departing from the principles and spirit of the present application whose scope is defined by the claims and their equivalents. These modifications and improvements should also be within the scope of protection of the present application.

Claims

1. A urine sugar detection system, characterized in that: The urine sugar detection system comprises: A test paper, the test paper comprising a paper substrate and an enzyme-copper hybrid nanoflower, wherein the enzyme-copper hybrid nanoflower is formed on the paper substrate based on an in-situ growth method; A microfluidic measuring stick, wherein the microfluidic measuring stick is provided with a detection chamber, the detection test paper is arranged in the detection chamber, and the detection test paper is used to absorb the urine sample to be tested to produce a colorimetric reaction; The detection terminal is used to capture an image of the test strip after a colorimetric reaction occurs, and the detection terminal is also used to detect and obtain urine sugar parameters of the urine sample to be tested based on the image.

2. The urine sugar detection system according to claim 1, characterized in that: The method for forming the enzyme-copper hybrid nanoflower on the paper substrate based on an in-situ growth method comprises: An inorganic copper sulfate solution and an enzyme solution are sequentially deposited on the paper substrate to obtain enzyme-copper hybrid nanoflowers of paper fibers cross-linked to the paper substrate.

3. The urine sugar detection system according to claim 2, characterized in that: The enzyme solution contains glucose oxidase and horseradish peroxidase.

4. The urine sugar detection system according to claim 1, characterized in that: The paper substrate comprises a main body and an adsorption end, wherein the adsorption end is located at the edge of the main body, and a portion of the adsorption end extends out of the detection chamber for absorbing the urine sample to be detected.

5. The urine sugar detection system according to claim 4, characterized in that: The microfluidic measuring rod is also provided with a microfluidic channel, which is located at the edge of the detection chamber and connected to the detection chamber, a part of the adsorption end is located in the microfluidic channel and another part of the adsorption end extends out of the microfluidic channel.

6. The urine sugar detection system according to claim 4, characterized in that: The test paper further comprises a support layer, the paper substrate is attached to the support layer, and the support layer is detachably mounted on the detection chamber.

7. The urine sugar detection system according to claim 1, characterized in that: The method for the detection terminal to obtain the urine sugar parameter of the urine sample to be tested according to the image detection includes: The detection terminal extracts the RGB value of the image; The detection terminal determines the glucose concentration of the urine sample to be tested according to the RGB value and a pre-stored RGB-glucose concentration regression curve.

8. The urine sugar detection system according to claim 1, characterized in that: The microfluidic measuring stick is also provided with a colorimetric reference diagram, which includes a plurality of different sub-color diagrams, each of which corresponds to a different glucose concentration.

9. A detection method of a urine sugar detection system according to any one of claims 1 to 8, characterized in that: The detection method comprises: Using the test paper to absorb the urine sample to be tested to perform a colorimetric reaction; Using a detection terminal to capture an image of the detection test paper after a colorimetric reaction occurs; The detection terminal is used to detect the urine sugar parameter of the urine sample to be tested based on the image.

10. The detection method of the urine sugar detection system according to claim 9, characterized in that: The method of using the test paper to absorb the urine sample to be tested includes: The adsorption end of the paper substrate is immersed in the urine sample to be tested, so that the entire test paper adsorbs the urine sample to be tested.

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