Urine Glucose Detection System and Its Detection Method

Abstract

The present application provides a urine glucose detection system and its detection method. The urine glucose detection system includes a test strip, a microfluidic measurement rod, and a detection terminal. The test strip includes a paper substrate and enzyme-copper hybrid nanoflowers, and the enzyme-copper hybrid nanoflowers are formed on the paper substrate based on an in-situ growth method. The microfluidic measurement rod is provided with a detection chamber, and the test strip is arranged in the detection chamber. The test strip is used to adsorb a urine sample to be tested to produce a colorimetric reaction. The detection terminal is used to capture an image of the test strip after the colorimetric reaction, and the detection terminal is also used to detect the urine glucose parameter of the urine sample to be tested according to the image. Forming enzyme-copper hybrid nanoflowers on the test strip based on the in-situ growth method can enhance the detection sensitivity. After the colorimetric reaction, the image is analyzed based on an algorithm to obtain the urine glucose parameter of the urine sample to be tested, realizing high-precision quantitative measurement. At the same time, the use of this system is relatively convenient, meeting the needs of home detection.

Description

Technical Field

[0001] This application belongs to the technical field of biomedical sensors. Specifically, it relates to a urine glucose detection system and its detection method. Background Art

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

[0003] Traditional urine glucose detection mainly relies on enzymatic or non-enzymatic colorimetric analysis, usually integrated into paper strips. These strips are widely adopted due to their low cost, ease of use, and rapid response. However, most commercial home urine glucose detections only provide qualitative or semi-quantitative results, only being able to roughly estimate glucose concentration and lacking precise measurement capabilities. The low sensitivity of these methods limits their effectiveness in early diabetes monitoring, especially when the glucose concentration is below 5 mmol / L, which may lead to delayed intervention. In contrast, laboratory-level 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 this application is: how to provide a urine glucose detection sensing device with high detection sensitivity, high accuracy, and meeting the convenience of home testing.

[0005] This application provides a urine glucose detection system, and the urine glucose detection system includes:

[0006] A test strip, the test strip includes a paper substrate and enzyme-copper hybrid nanoflowers, and the enzyme-copper hybrid nanoflowers are formed on the paper substrate based on an in-situ growth method;

[0007] A microfluidic measurement rod, the microfluidic measurement rod is provided with a detection chamber, the test strip is arranged in the detection chamber, and the test strip is used for adsorbing a urine sample to be detected to produce a colorimetric reaction;

[0008] A detection terminal, which is used to capture an image of the test strip after a colorimetric reaction, and the detection terminal is also used to detect the urine glucose parameter of the urine sample to be tested based on the image.

[0009] Optionally, the method for forming the enzyme-copper hybrid nanoflowers on the paper substrate based on the in-situ growth method includes:

[0010] Deposit an inorganic copper sulfate solution and an enzyme solution on the paper substrate in sequence to obtain enzyme-copper hybrid nanoflowers crosslinked to the paper fibers of the paper substrate.

[0011] Optionally, the enzyme solution contains glucose oxidase and horseradish peroxidase.

[0012] Optionally, the paper substrate includes a main body part and an adsorption end. The adsorption end is located at the edge of the main body part, and a part of the adsorption end extends outside the detection chamber for absorbing the urine sample to be tested.

[0013] Optionally, the microfluidic measurement rod is further provided with a microfluidic channel. The microfluidic channel is located at the edge of the detection chamber and communicates with the detection chamber. A part of the adsorption end is located inside the microfluidic channel and another part of the adsorption end extends outside the microfluidic channel.

[0014] Optionally, the test strip further includes a support layer. The paper substrate is attached to the support layer, and the support layer is detachably installed in the detection chamber.

[0015] Optionally, the method for the detection terminal to detect the urine glucose parameter of the urine sample to be tested based on the image includes:

[0016] The detection terminal extracts the RGB values of the image;

[0017] The detection terminal determines the glucose concentration of the urine sample to be tested according to the RGB values and a pre-stored RGB-glucose concentration regression curve.

[0018] Optionally, the microfluidic measurement rod is further provided with a colorimetric reference diagram, which includes several different sub-color diagrams, and each sub-color diagram corresponds to a different glucose concentration.

[0019] The present application also discloses a detection method for a urine glucose detection system. The detection method includes:

[0020] Use the test strip to adsorb the urine sample to be tested and perform a colorimetric reaction;

[0021] Use a detection terminal to capture an image of the test strip after the colorimetric reaction;

[0022] The detection terminal is used to detect the urine glucose parameter of the urine sample to be tested according to the image.

[0023] Optionally, the method for using the test strip to adsorb the urine sample to be tested includes:

[0024] Dip the adsorption end of the paper substrate into the urine sample to be tested, so that the whole test strip adsorbs the urine sample to be tested.

[0025] A urine glucose detection system and its detection method provided by the present application have the following technical effects:

[0026] Enzyme-copper hybrid nanoflowers are formed on the test strip based on the in-situ growth method, which can enhance the detection sensitivity. After the colorimetric reaction occurs, the detection terminal is used to take an image, and the image is analyzed based on an algorithm to obtain the urine glucose parameter of the urine sample to be tested, realizing high-precision quantitative measurement. At the same time, the use of this system is relatively convenient, meeting the needs of home detection. Description of the Drawings

[0027] Figure 1 It is the overall framework diagram of the urine glucose detection system according to one or more embodiments.

[0028] Figure 2 It is the assembly schematic diagram of the test strip and the microfluidic measuring rod according to one or more embodiments.

[0029] Figure 3 It is the exploded schematic diagram of the test strip according to one or more embodiments.

[0030] Figure 4 It is the schematic diagram of the detection mechanism and detection process of the urine glucose detection system according to one or more embodiments.

[0031] Figure 5 It is the physical diagram of the test strip and the microfluidic measuring rod according to one or more embodiments.

[0032] Figure 6 It is the fluid absorption comparison test diagram of different test strips according to one or more embodiments.

[0033] Figure 7 It is the schematic diagram of the design, manufacturing and assembly process of the test strip according to one or more embodiments.

[0034] Figure 8 It is the schematic diagram of the process of in-situ synthesizing enzyme-copper hybrid nanoflowers according to one or more embodiments.

[0035] Figure 9 It is the test result diagram of the sensitivity of glucose detection with different enzyme and chromogenic substrate concentrations according to one or more embodiments.

[0036] Figure 10 Structural and compositional characterization diagram of a test strip according to one or more embodiments.

[0037] Figure 11 Analysis performance evaluation result diagram of a test strip according to one or more embodiments in terms of reaction kinetics and sensitivity when detecting glucose.

[0038] Figure 12 Analysis performance evaluation result diagram of a test strip according to one or more embodiments in terms of stability and specificity when detecting glucose.

[0039] Figure 13 Schematic diagram of an image processing workflow according to one or more embodiments.

[0040] Figure 14 Schematic diagram of the workflow for the detection terminal to assist in glucose quantification according to one or more embodiments.

[0041] Figure 15 Schematic diagram of the recording and tracking module of the detection terminal according to one or more embodiments.

[0042] Figure 16 Schematic diagram of visual and quantitative glucose detection using a urine glucose detection system according to one or more embodiments.

[0043] Figure 17 Verification result diagram of glucose detection in urine samples using a urine glucose detection system according to one or more embodiments. Detailed implementation manners

[0044] In order to make the objectives, technical solutions and advantages of this application clearer, the following further elaborates on this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0045] Before describing each embodiment of this application in detail, first briefly describe the technical concept of this application: Currently, traditional urine glucose detection methods either use test strips for semi - quantitative rough testing or use complex laboratory - level POCT systems for testing, making it difficult to simultaneously achieve detection accuracy, high sensitivity, and the convenience of home testing. For this reason, this application provides a urine glucose detection system and its detection method. An enzyme - copper hybrid nanoflower is formed on the test strip based on an in - situ growth method, which can enhance the detection sensitivity. After a colorimetric reaction, an image is taken using a detection terminal, and the image is analyzed based on an algorithm to obtain the urine glucose parameters of the urine sample to be tested, achieving relatively high - precision quantitative measurement. At the same time, the use of this system is relatively convenient, meeting the needs of home testing. The following describes the specific principles of the urine glucose detection system and its detection method of this application in combination with more embodiments.

[0046] Specifically, as Figure 1 , Figure 2 and Figure 3 shown, the urine glucose detection system of the first embodiment includes a test strip 10, a microfluidic measurement rod 20, and a detection terminal 30. The test strip 10 includes a paper substrate and enzyme-copper hybrid nanoflowers, and the enzyme-copper hybrid nanoflowers are formed on the paper substrate based on an in-situ growth method; the microfluidic measurement rod 20 is provided with a detection chamber 21, the test strip 10 is disposed in the detection chamber 21, and the test strip 10 is used to adsorb a urine sample to be tested to produce a colorimetric reaction, and the detection terminal 30 is used to capture an image of the test strip 10 after the colorimetric reaction, and the detection terminal 30 is further used to detect the urine glucose parameter of the urine sample to be tested according to the image.

[0047] Exemplarily, the paper substrate includes a main body portion 11 and an adsorption end 12. The adsorption end 12 is located at the edge of the main body portion 11, and a part of the adsorption end 12 extends outside the detection chamber 21 for absorbing the urine sample to be tested, so that the urine sample to be tested diffuses to the whole of the main body portion 11. The microfluidic measurement rod 20 is further provided with a microfluidic channel 22. The microfluidic channel 22 is located at the edge of the detection chamber 21 and communicates with the detection chamber 21. A part of the adsorption end 12 is located inside the microfluidic channel 22 and another part of the adsorption end 12 extends outside the microfluidic channel 22. The microfluidic measurement rod 20 with such a structure can enable the adsorption end 12 to extend into a test tube to adsorb the urine sample to be tested, without the need to use a pipette to transfer the sample, improving the convenience of detection use.

[0048] Furthermore, the test strip 10 further includes a support layer 13. The paper substrate is attached to the support layer 13, and the support layer 13 is detachably installed in the detection chamber 21. Exemplarily, the paper substrate and the support layer 13 can be connected by means of pasting, and the support layer 13 and the detection chamber 21 can be connected by means of pasting. On the one hand, the overall strength of the test strip 10 can be ensured through the support layer 13, and on the other hand, it is convenient to install the support layer 13 into the detection chamber 21 or detach it from the detection chamber 21 to replace a new test strip 10.

[0049] In one or more embodiments, the microfluidic measurement rod 20 is further provided with a colorimetric reference diagram 23. The colorimetric reference diagram 23 includes a number of different sub-color diagrams, and each sub-color diagram corresponds to a different glucose concentration. Exemplarily, the colorimetric reference diagram 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 diagram to roughly estimate the glucose level, and the user can directly compare the colorimetric reference diagram 23 to obtain an immediate visual reading.

[0050] In one or more embodiments, the method for forming enzyme-copper hybrid nanoflowers on a paper substrate based on an in-situ growth method includes: sequentially depositing an inorganic copper sulfate solution and an enzyme solution on the paper substrate to obtain enzyme-copper hybrid nanoflowers crosslinked to the paper fibers of the paper substrate. Exemplarily, the enzyme solution contains glucose oxidase and horseradish peroxidase.

[0051] Exemplarily, the detection mechanism and detection process of the urine glucose detection system are as Figure 4 shown. The enzyme-copper hybrid nanoflowers are composed of multifunctional enzyme copper hybrid nanoflowers (GO x &HRP@Cu3(PO4)2·3H2O) and are crosslinked in the cellulose matrix to ensure high enzyme stability, improve catalytic efficiency, and optimize the interaction of substrate active sites. The Cu3(PO4)2·3H2O nanosheets act as a structural scaffold to closely align glucose oxidase (GO x ) and horseradish peroxidase (HRP) to form a highly ordered hierarchical structure. This biocatalytic arrangement facilitates efficient electron transfer and substrate diffusion, thus optimizing substrate channels and reaction kinetics. As Figure 4 shown in B, the detection mechanism involves a catalytic cascade reaction: GO x catalyzes the oxidation of glucose to gluconic acid, while generating hydrogen peroxide (H2O2) as a byproduct. HRP then uses H2O2 to oxidize 3,3',5,5'-tetramethylbenzidine (TMB) to its oxidized form (ox-TMB), producing a visible blue colorimetric signal. The short-range effect in the enzyme-copper hybrid nanoflower structure not only enhances the reaction kinetics but also amplifies the colorimetric reaction by shortening the reaction time and enhancing the signal intensity. As Figure 4 shown, the step-by-step workflow for urine glucose detection using the dip-and-read detection method: The process includes pre-treating the urine sample with a TMB solution, dipping the test strip, and obtaining a colorimetric reaction, which can be analyzed visually or assisted by a detection terminal for quantification. 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. Additionally, pre-fixing the chromogenic substrate (e.g., embedded TMB) on the test strip can implement a one-step detection system, eliminating the need for manual pre-treatment and further simplifying user operation.

[0052] Among them, the actual operation of the urine glucose detection system follows a simple dip-and-read detection protocol, as Figure 4As shown in C, it specifically includes three steps: (i) Pretreat the urine sample with TMB solution, (ii) Immerse the test strip into the pretreated sample, and (iii) Observe the change in the colorimetric signal. It should be noted 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 diagram to obtain an immediate visual reading; or use the application on the detection terminal to capture the color intensity of the colorimetric signal to achieve a more accurate quantitative analysis of the glucose concentration.

[0053] In one or more embodiments, the method for the detection terminal to determine the urine glucose parameter of the urine sample to be tested according to the image detection includes: The detection terminal extracts the RGB values of the image; The detection terminal determines the glucose concentration of the urine sample to be tested according to the RGB values and the pre-stored RGB-glucose concentration regression curve. Exemplarily, the detection terminal can be a smart phone. Use the camera of the smart phone to take an image of the test strip after the colorimetric reaction, use the built-in detection algorithm of the smart phone to detect the image, and combine the RGB-glucose concentration regression curve to obtain the urine glucose parameter of the urine sample to be tested.

[0054] In one or more embodiments, the detection method of the urine glucose detection system includes: Use the test strip to adsorb the urine sample to be tested and perform a colorimetric reaction; Use the detection terminal to take an image of the test strip after the colorimetric reaction; Use the detection terminal to determine the urine glucose parameter of the urine sample to be tested according to the image detection. Immerse the adsorption end of the paper substrate into the urine sample to be tested so that the entire test strip adsorbs the urine sample to be tested.

[0055] The basic content of the urine glucose detection system and the detection method has been described above. Next, the working principle, usage method and the effects produced by the urine glucose detection system will be described in more detail in combination with specific examples and experimental processes.

[0056] In one or more embodiments, as Figure 5 shown, the shape of the microfluidic measuring rod 20 is U-shaped. The bent part of the microfluidic measuring rod 20 can be used as a holding point for the operator during detection. Its ergonomic slender U-shaped body is made of durable polylactic acid (PLA) 3D printing material, ensuring comfort and practicality, aiming to provide a compact, user-friendly and reliable urine glucose colorimetric detection platform. Exemplarily, the skeleton structure of the microfluidic measuring rod 20 has a protruding head, and the detection chamber 21 is located at this head to optimize liquid contact. For example, the size of the microfluidic measuring rod 20 is 40 mm wide, 80 mm high, and 1.5 mm thick to ensure durability and the convenience of single-handed operation.

[0057] In one example, the detection chamber 21 is a square detection chamber (with a length and width of 5.6 mm × 5.6 mm and a depth of 1 mm) to accommodate a test strip made of Whatman grade 1 filter paper as the paper substrate. Filter paper is selected as the substrate for enzyme immobilization due to its high absorbency and stable liquid flow characteristics. The support layer 13 material consists of a 5.6 mm × 5.6 mm PET polyester film, which is bonded with 3M 467MP tape (thickness 0.01 mm) to stabilize the test strip, prevent liquid leakage, and provide protection against environmental pollution. It should be noted that the adsorption end 12 (1.7 mm × 1.5 mm) enhances the direct contact with the urine sample to be tested, thereby improving the liquid absorption efficiency and optimizing the accuracy of the colorimetric reaction.

[0058] To ensure the test strip has high fluid absorption capacity during the dipping detection process, two different test strips were designed and evaluated to optimize the flow rate after liquid contact. One test strip uses a square PET support layer (without external protrusions), while the other test strip's PET support layer includes external protrusions for supporting the adsorption end 12 of the test strip. Figure 6 Table 1 shows the schematic diagrams of different test strips and the comparative analysis of fluid transport performance. The experimental results show that the test strip with a square support layer (SL) exhibits a higher flow rate (average flow rate = 0.433 mm / s, RSD = 6.24%) and lower variability in repeated tests, while the test strip with external protrusions (EL) exhibits a lower flow rate (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 its excellent fluid transport consistency and performance. As shown in the following table, the comparative results of the fluid transport efficiency of the two different test strips are presented.

[0059]

[0060] Table 1

[0061] Exemplarily, the microfluidic measurement rod 20 was designed using Fusion 360 CAD software, and an STL model was generated. This 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. Additionally, based on the initial calibration images of the microfluidic measurement rod 20 in the glucose concentration range of 0 to 0.75 mmol / L, a colorimetric reference map was developed and calibrated.

[0062] Specifically, as Figure 7As shown, the disposable test strip is made of Whatman grade 1 filter paper, precisely cut into a square of 7.3 mm × 7.3 mm to ensure uniformity and reproducibility. Each paper substrate contains two regions: (1) an adsorption end 12 of 1.5 mm × 1.7 mm for controlling sample absorption; (2) a main body part 11 of 5.6 mm × 5.6 mm as the main detection region where the enzyme-catalyzed colorimetric reaction occurs. The paper substrate is laminated on 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 cutting of the support layer 13 is completed using a Universal Laser System (VLS3.50 software) and high precision is achieved through optimized vector pattern settings.

[0063] As Figure 8 shown, the in-situ growth method process involves two-step sequential solution deposition. First, 2.5 μL of 120 mmol / L CuSO4 solution is 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 x and 0.1 mg / mL horseradish peroxidase HRP, dissolved in 0.07 mol / L KH2PO4 buffer, pH 7.4) is pipetted to provide the organic components required for the formation of hybrid nanoflowers. The test strip is dried at room temperature for 10 minutes to allow the copper ions to react with the enzyme and promote the formation of hybrid nanoflowers. Finally, the functionalized test strip is stored in a sealed container at 4°C to maintain enzyme activity for subsequent testing.

[0064] To achieve optimal glucose detection performance, the urine glucose detection system optimized the concentrations of GO x , HRP and the chromogenic substrate (TMB) to improve the catalytic efficiency and reduce background noise. Figure 9 A in Figure 9 shows the effect of increasing the GOx concentration on the colorimetric response, Figure 9 B in Figure 9 shows the evaluation of the role of HRP in the catalytic colorimetric reaction, x and C in x shows the determination of the optimal amount of the chromogenic substrate for the maximum signal intensity. The error bars represent the standard deviation (SD) of n = 3 independent measurements. As x shown in A of Figure 9As shown in B of, during the optimization of HRP activity, at a fixed GO 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. As x shown in C of, for the optimization of the chromogenic substrate, the TMB concentration was optimized in the range of 0.05 - 1.0 mg / mL, and the color signal was the strongest at 0.5 mg / mL. Further increasing the TMB concentration did not significantly enhance the color change but might increase the background noise. Therefore, 0.5 mg / mL was determined as the optimal TMB concentration. Figure 9 Furthermore, the surface morphology and elemental composition of the test strips were analyzed using a scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDS) through a PHENOM XL (Phenom World) instrument. The crystal structure analysis was completed using a Bruker AXS D8 Discover (TXS) through X-ray diffraction (XRD). In addition, X-ray photoelectron spectroscopy (XPS) analysis was performed using a Thermo Scientific ESCALAB 250Xi to evaluate the elemental composition and oxidation state.

[0065] Specifically, as

[0066] shown, where Figure 10 A, B, and C of represent the pure paper strip, Cu3(PO4)2·3H2O deposited on the paper strip, and GO immobilized on the paper strip Figure 10 &HRP@Cu3(PO4)2·3H2O nanoflowers, respectively; the SEM images of x D and E of represent the EDS elemental mappings of Cu3(PO4)2·3H2O and GO Figure 10 &HRP@Cu3(PO4)2·3H2O nanoflowers, showing the spatial distribution of Cu, P, O, and enzyme-related elements. x F of represents the XRD pattern of Cu3(PO4)2·3H2O and GO Figure 10 &HRP@Cu3(PO4)2·3H2O nanoflowers, confirming the crystal structure of the nanoflowers and the successful enzyme immobilization. SEM analysis: The pure paper test strip showed a porous fiber network ( x A of), which was beneficial for the immobilization of nanomaterials. After loading Cu3(PO4)2·3H2O, a disordered microstructure with a particle size of 2.8 - 4 μm was formed ( Figure 10 B of). With the addition of GO Figure 10 x ​With the further addition of HRP, the nanoflowers formed uniform spherical structures with a size of approximately 5 - 5.3 μm ( Figure 10 C), and the star-shaped nanosheets contributed to enhancing the enzyme stability and catalytic efficiency. EDS elemental mapping: Cu, P, and O were uniformly distributed in the Cu3(PO4)2·3H2O structure ( Figure 10 D). After loading GO x and HRP, elements such as C, N, and S appeared ( Figure 10 E), confirming the successful immobilization of the enzyme. Further, the XRD pattern ( Figure 10 F): It was confirmed that the Cu3(PO4)2·3H2O crystal phase was complete and matched the ICDD standard card.

[0067] As Figure 11 A shows, the Michaelis - Menten kinetic curve shows a time - dependent colorimetric reaction (ΔR) with respect to glucose concentration (0–0.5 mmol L -¹ ). As Figure 11 B shows, the Lineweaver - Burk plot derived from the kinetic data for determining V max and K m . As Figure 11 C shows, the glucose detection curve (0–2 mmol L -¹ ) describing the relationship between the ΔRGB signal and glucose concentration, with a boxed linear detection range; as Figure 11 D shows, 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. As Figure 11 shown, XPS analysis: As Figure 11 A shows, the XPS survey spectrum confirmed the presence of Cu, O, N, C, and P, verifying the success of enzyme immobilization. As Figure 11 B shows, the Cu 2p spectrum shows peaks corresponding to Cu 2+ and Cu + oxidation states, indicating the presence of mixed copper valence, which can affect the catalytic activity. As Figure 11 C shows, the C 1s spectrum reveals deconvoluted peaks of C - C, C - N, C=O, and C - O, highlighting the organic functional groups integrated by the enzyme. As Figure 11 D shows, the N 1s spectrum shows peaks of C - N / N - H and N - C=O, further confirming the incorporation of the enzyme through nitrogen - related functional groups.

[0068] Furthermore, for the colorimetric glucose test using the hybrid nanoflower-functionalized paper strip, the sample was pretreated with 0.5 mg / mL of TMB as the chromogenic substrate. Specifically, 2.5 μL of a 10 mg / mL TMB stock solution (prepared in DMSO) was added to every 50 μL of the sample. After pretreatment, 2.5 μL of the treated sample was added dropwise to the test strip, and the change in the colorimetric signal was recorded. To achieve a pipette-free dipping detection method, a 200 μL disposable plastic dropper was used for sample preparation (as shown in C of Figure 4 ). For each test, the dropper was filled and transferred to an empty container, and then one drop of a 10 mg / mL TMB solution (prepared in DMSO) was added. Then, the fully assembled detection system was immersed in the TMB-treated solution until the adsorption end of the extended tip of the test strip was completely submerged, and then taken out. The colorimetric reaction results were recorded by capturing images before and 3 minutes after immersion.

[0069] The test strips were evaluated for their analytical performance in terms of reaction kinetics, sensitivity, stability, and specificity. All experiments were conducted under controlled conditions to ensure reproducibility.

[0070] (1) Reaction kinetics: Glucose solutions with concentrations ranging from 0 to 0.5 mmol / L were prepared and pretreated with TMB. 2.5 μL aliquots of each concentration were introduced onto the test strip, and a 5-minute video was recorded using a smartphone. Video frames of 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 against time to determine the signal stabilization point and record the response time. As shown in A and B of Figure 11 , the color signal stabilized within 2.5 - 5 minutes, and the calculated Km = 0.15 mmol / L, indicating that the sensor has a high affinity for glucose.

[0071] (2) Sensitivity assessment: Glucose solutions with concentrations from 0 to 2 mmol / L were prepared, and 2.5 μL of each sample was added dropwise to the test strip. Images were captured before and 3 minutes after sample application. The experiment was repeated three times, and RGB values were extracted. The change in the colorimetric signal (ΔR, ΔG, ΔB) was plotted against the glucose concentration to evaluate sensitivity. The most stable and responsive channel was selected for further quantification, and the linear detection range was determined. The limit of detection (LOD) was calculated using the following formula: LOD = 3σ / S, where σ is the standard deviation of the blank (after 3 repeated measurements), and S is the slope of the linear calibration curve. As shown in C and D of Figure 11 , good linearity was shown in the range of 0 - 0.75 mmol / L (R ² = 0.9925), and the calculated LOD = 0.017 mmol / L, which is better than most existing colorimetric sensors.

[0072] (3)Stability assessment: As Figure 12 in A, the pH-dependent stability study focuses on the optimal pH conditions for sensor performance; as Figure 12 in B, the long-term stability assessment demonstrates that the enzyme activity is retained over time. The stability of the test strip is evaluated within the pH range of 3.7 to 8.5. A 0.25 mmol / L glucose solution is prepared and the colorimetric response is 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, the freshly HNF-functionalized strips are stored at 4 °C and evaluated over six weeks. The colorimetric reaction is measured weekly using a 0.25 mmol / L glucose solution to assess the long-term storage stability. As Figure 12 shown in A and B of, the sensor remains stable over a wide pH range of 3.7–7.5 and retains more than 70% of the enzyme activity after six weeks.

[0073] (4)Specificity assessment: As Figure 12 in C, the specificity assessment for a single interferent, comparing the responses to glucose and common urine contaminants; as Figure 12 in D, the interference analysis in mixed samples, evaluating the sensor performance in complex matrices, and the error bars represent the standard deviation (SD) of n = 3 independent measurements. The specificity of the test strip is evaluated by testing potential interfering substances, including uric acid (equimolar concentration), fructose, galactose, xylose, lactose, maltose, and sucrose (five times the glucose concentration), as well as NaCl, KCl, creatinine, and urea (ten times the glucose concentration). Each solution (2.5 μL) is added separately to the strip and the colorimetric reaction is recorded. In addition, a 0.25 mmol / L glucose solution is 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 interferences, the method is considered to have good specificity. As Figure 12 shown in C and D of, it has high selectivity for common urine interferents (such as NaCl, KCl, urea, creatinine, and uric acid).

[0074] Image acquisition and RGB analysis workflow. In colorimetric analysis, images are taken under consistent imaging conditions. The smartphone is firmly mounted on a phone holder and kept in a fixed horizontal orientation (as Figure 13 shown). The camera captures images from a top-down perspective, ensuring a constant distance to minimize errors due to angle or position changes. All images are taken under controlled lighting conditions, directly illuminated by a designated laboratory light source that is fixed in place to ensure reproducibility. To eliminate external light fluctuations, the imaging setup remains unchanged throughout the experiment.

[0075] Image processing involves cropping an image after a colorimetric glucose reaction to isolate the relevant color regions. To optimize the cropping strategy, three different methods were evaluated: peripheral cropping, middle cropping, and central cropping. Peripheral cropping includes the entire test strip, capturing both the reaction area and non-reaction area. Middle cropping focuses on the main color regions while excluding bright or uneven regions at the edges, thus ensuring a balanced selection area. Central cropping isolates only a small portion at the center of the reaction zone, prioritizing the most uniform color regions. The best 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 method for effectively processing images in glucose detection.

[0076] Among them, RGB analysis was performed using a self-developed smartphone application, which was built using TypeScript, WXML, and CSS in the WeChat integrated development environment (IDE). Initially, RGB values were extracted through a Python script, and the optimized workflow was then integrated into the application to simplify the analysis. To ensure reproducibility, all image acquisitions were carried out under consistent experimental conditions, including fixed camera settings, constant focal length, and standardized analysis regions.

[0077] Exemplarily, the smartphone application (App) was developed using TypeScript, WXML, and CSS in the WeChat integrated development environment (IDE) on the 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 application has cross-platform compatibility and can run seamlessly on iOS and Android devices. The IDE supports front-end page design using WXML, style setting using CSS, and implementation of backend logic using TypeScript (a superset of JavaScript). The WXML template is used to build the user interface, including image upload / take button, real-time preview panel, and result display module. CSS is used to implement dynamic styles and responsive layouts. TypeScript is responsible for managing user interactions, integrating device APIs (such as camera access and gallery retrieval), and facilitating communication with the image processing module.

[0078] The application includes the following functional modules: Calibration module (such as the calibration interface shown in Figure 14 ): The user uploads an image of a standard solution, and the system generates a regression curve. Detection module (such as the detection interface shown in Figure 14 ): Automatically calculates the glucose concentration, avoiding human errors. Recording module (such asFigure 15 as shown): Saving historical data to support long-term health monitoring.

[0079] Furthermore, the assembly of the urine glucose detection system involves integrating the test strip into a 3D-printed microfluidic measurement rod. To ensure correct alignment and optimize contact with the urine sample, the test strip is accurately placed in a designated chamber. Calibration of the urine glucose detection system is performed using standard glucose solutions with known concentrations (0 to 1 mmol / L). Colorimetric responses are recorded by taking images before and 3 minutes after immersion. As previously described, the average red channel value is extracted using Python, and the corresponding change in the colorimetric signal is plotted as a function of glucose concentration. The range within which the colorimetric signal shows a strong linear correlation with glucose concentration is determined as the linear detection range of the urine glucose detection system and is used to generate a calibration curve. To enable visual color recognition, images of the linear colorimetric reaction are printed onto stickers as a colorimetric reference chart on the device. Additionally, a smartphone application is used to reconstruct the calibration curve generated from the colorimetric glucose reaction images and to determine the glucose level in actual urine samples. To evaluate the performance of the sensor in visual and quantitative glucose detection, three glucose solutions were prepared, including blank controls (0, 0.25, and 0.75 mmol / L). The colorimetric response of the sensor was compared with a reference color card by visual inspection to estimate the glucose concentration, and further confirmed using the smartphone application. Sample preparation and measurement follow the above pipette-free immersion detection method, ensuring ease of operation and user-friendliness.

[0080] Specifically, as Figure 16 shown, linear detection range: The sensor exhibits a significant linear relationship within the glucose concentration range of 0–1 mmol L -¹ (as shown in A). The red channel shows the most significant signal change, consistent with the results of independent strip analysis. The calibration curve ( Figure 16 as shown in B) shows a high correlation coefficient (R Figure 16 ) within the range of 0–0.75 mmol L -¹ = 0.994), confirming the high precision and reliability of quantitative glucose detection. Visual reading: The colorimetric strip ( ² as shown in C) provides a semi-quantitative estimate, allowing users to directly compare color intensities. The red marked area of the reference strip directly corresponds to the color intensity generated in the detection chamber, making it suitable for non-professional users. Smartphone-assisted quantitative analysis: Image processing is performed through a smartphone application to automatically quantify color changes ( Figure 16 as shown in D). The calibration parameters generated by the smartphone are consistent with the analysis results of the Python script, demonstrating the reliability of quantitative analysis. The results show a strong correlation between visual estimation and smartphone-assisted analysis ( Figure 16 as shown in Figure 16E). User-friendliness and applicability: All measurements are completed by the pipette-free Dip-and-Detect method, simplifying the operation steps. This design is suitable for low-resource settings and non-professional users. The modular design of the urine glucose detection system can be adapted for other biomarker detections, demonstrating its potential in personalized diagnostics and telemedicine. Through these experimental results, the Hybrid μDip sensor has demonstrated its practicality in non-invasive glucose detection and provides broad application prospects for future multi-biomarker detection and telemedicine.

[0081] Urine sample collection and detection protocol: This study has been approved by the Institutional Review Board (IRB) of Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences, with the approval number SIAT-IRB-250115-H0954. All procedures involving human participants were conducted in accordance with the ethical standards laid down in the Declaration of Helsinki and informed consent was obtained from all volunteers prior to the study. Urine samples from five volunteers were collected and screened for glucose content using the gold standard method. A glucose standard curve (0–0.5 mM) was prepared by incubating glucose solutions with 0.5 mg / mL GO x in PBS (pH 7.4) at 37 °C for 25 minutes. The 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).

[0082] For each glucose concentration, 80 μL of the glucose-GO x reaction solution was added to the TMB-HRP mixture and incubated at 37 °C for 20 minutes, 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. Then 0.5 mg / mL GO x was added and incubated at 37 °C for 25 minutes. 80 μL of the reaction mixture was mixed with the TMB-HRP substrate solution, incubated at 37 °C for 20 minutes, and cooled in an ice-water bath. The absorbance at 652 nm was recorded and the glucose concentration was calculated using the standard curve equation, taking into account the dilution factor and applying the Beer-Lambert law for accurate measurement.

[0083] For urine samples containing detectable glucose, further testing is performed using a urine glucose detection system. In the urine glucose detection system test, 200 μL of urine sample is collected using a disposable dropper, pre-mixed with one drop of TMB solution, and analyzed using a pipette-free immersion detection method. The fully assembled sensor is immersed in the solution, ensuring that the protruding end of the strip is completely submerged. After 3 minutes, a preliminary visual glucose estimation is made using a reference color bar, and at the same time, the colorimetric reaction is quantitatively measured using a smartphone. The color signals before and after 3 minutes are recorded for analysis. When performing statistical analysis, the data is expressed as mean ± standard deviation (SD), and the error bars represent the standard deviation of the mean. The sample size (n) for each analysis is stated in the legend. Most experiments are conducted in triplicate, and data analysis is performed using Microsoft Excel.

[0084] Specifically, the test results for real urine samples are as follows. As Figure 17 shown, visual detection: The color chart shows the color changes corresponding to the glucose concentration in 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, indicating 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 for low-concentration urine glucose is increased by 224%. At high concentrations, the sensitivity is increased by 97% - 63%.

[0085] Through the above series of experiments and real urine tests, the feasibility of the urine glucose detection system is systematically demonstrated. The main findings include: (1) Optimization of the enzyme and TMB concentrations significantly improves the detection sensitivity; (2) Comprehensive material characterization using SEM, EDS, XRD, and XPS confirms the successful formation and structure of the hybrid nanoflowers; (3) The sensor has high sensitivity, stability, and specificity, and is very suitable for urine glucose monitoring; (4) The smartphone-based analysis system improves the convenience of detection and enables real-time and user-friendly glucose quantification. (5) Real urine tests show excellent performance, and the results are consistent with standard laboratory methods.

[0086] Furthermore, as shown in Table 2, the lowest detection limit (LOD) of the urine glucose detection system of the present application is 0.017 mmol / L, which is far better than that of existing commercial urine glucose test strips, whose detection limits are usually 2.2 mmol / L and above. This urine glucose detection system also has semi-quantitative and quantitative analysis modes, providing a more accurate and convenient urine glucose detection method for household users.

[0087]

[0088] Table 2

[0089] According to the test results, the main technical advantages of the urine glucose detection system of the present application are as follows: (1) Ultra-high sensitivity: The lowest detection limit is 0.017 mmol / L, which can detect trace glucose and is far superior to existing household urine glucose test strips. (2) Quantitative accuracy: The detection terminal application program is combined with RGB color analysis to provide real-time quantitative detection, avoiding inaccurate semi-quantitative estimation. (3) Enhanced specificity: It can resist common interferents (such as uric acid, fructose, galactose, etc.) and maintain high selectivity in complex urine matrices. (4) Long-term stability: It maintains more than 80% activity after 3 weeks of storage and 70% activity after 6 weeks of storage, ensuring continuous testing. (5) Wider pH stability: It maintains high performance within the pH range of 3.7 to 7.5, which is consistent with physiological urine conditions.

[0090] The specific implementation manners of the present application have been 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 defined by the claims and their equivalents, and these modifications and improvements should also be within the protection scope of the present application.

Claims

1. A urine sugar detection system, characterized in that: The urine sugar detection system comprises: A test strip, the test strip comprising a paper substrate and an enzyme-copper hybrid nanoflower, the enzyme-copper hybrid nanoflower being formed on the paper substrate based on an in-situ growth method, comprising: sequentially depositing an inorganic copper sulfate solution and an enzyme solution on the paper substrate to obtain an enzyme-copper hybrid nanoflower cross-linked to paper fibers of the paper substrate, the enzyme solution containing glucose oxidase and horseradish peroxidase; the paper substrate comprising a main body and an adsorption end, the adsorption end being located at the edge of the main body, and a portion of the adsorption end extending out of the detection chamber for absorbing a urine sample to be tested; 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 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.

3. The urine sugar detection system according to claim 2, 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.

4. 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.

5. 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.

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