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. 2021 Nov 19;6(48):32655–32662. doi: 10.1021/acsomega.1c03449

Portable and Intelligent Urine Glucose Analyzer Based on a CdTe QDs@GOx Aerogel Circular Array Sensor

Tao Hu 1, Wengen Li 1, Kangkai Xu 1, Ke Chen 1, Xiao Li 1,*, Hong Yi 1,*, Zhonghua Ni 1,*
PMCID: PMC8655949  PMID: 34901614

Abstract

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Diabetes is a public health problem characterized by hyperglycemia, high mortality, and morbidity. A simple, rapid, and sensitive glucose detection method for diabetes screening and health self-management of patients with diabetes is of great significance. Therefore, an attractive urine glucose (UG) analyzer with advantages of fastness, sensitivity, and portability was developed. A cadmium telluride quantum dots (CdTe QDs)@glucose oxidase (GOx) aerogel circular array sensor can emit visible red fluorescence when excited by a 365 nm ultraviolet light source inside the analyzer. When urine samples containing glucose were dropped onto the sensor, glucose was oxidized by GOx to produce hydrogen peroxide (H2O2), which quenched the red fluorescence of CdTe QDs. The fluorescence images of the sensor were obtained using a CCD camera, and the linear relationship between the glucose concentration and the gray value of the fluorescence image was established. The analyzer shows good sensitivity (LOD, 0.12 mM) with a wide linear range of 0.12–26 mM. Based on the linear relation, the software of the analyzer was written in the C++ language, which can automatically give the gray value of the image and the corresponding glucose concentration. The UG analyzer was used for the detection of a large number clinical samples and compared with a variety of UG test papers, which all showed good detection performance. The novel analyzer we proposed has an important significance in the screening of diabetes and the self-management of diabetic patients.

Introduction

Diabetes is a global disease; more than 400 million people have been tortured by diabetes since 2015, and the number of patients is still increasing. It is expected that the number will exceed 600 million by 2045.1,2 As a result, both the growth of medical expenditure and the decline in the quality of life are becoming serious challenges.3 Early diagnosis is of great significance for the management of diabetes and preventing or delaying the occurrence of diabetes complications.4 However, most patients with type 2 diabetes are asymptomatic, and more than 30% of patients with type 2 diabetes are not diagnosed until systemic complications occur.5 Therefore, screening for diabetes, especially in high-risk areas, is essential to reduce the negative effects of diabetes.

Until now, traditional methods of diabetes screening and monitoring include evaluation of fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), and FPG in combination with 2 h plasma glucose (2 h-PG) after a 75 g oral glucose tolerance test.6−9 However, due to low efficiency, a long time, and high cost, the application of these methods is limited.10 More importantly, frequent blood sampling leads to poor patient compliance, which is not conducive to diabetes screening and diabetic self-management. Therefore, a simple, user-friendly assistance approach with excellent sensitivity and selectivity is urgently needed.

The measurement of urine glucose (UG) appears to be an attractive choice. Current research shows that UG detection can reliably reflect the blood glucose concentration;11,12 the higher the UG concentration, the more the patient’s blood glucose exceeds the normal. Also, previous studies have shown that compared with blood self-monitoring, quantitative UG monitoring has similar effects in maintaining blood glucose control.13,14 The appearance of glucose in urine is an important indicator of many related diseases.15 UG detection has great advantages in early screening of diabetes, which avoids the pain of blood sampling needles and simplifies the testing process.

At present, various methods are used in UG detection, including electrochemical devices,16−18 surface-enhanced Raman scattering (SERS),19−21 colorimetric sensors,22−24 and so on. Glucose reacts with enzymes or enzyme-like substances to generate electrons to cause changes in current. Electrochemical workstations were used to capture the changes in current to determine UG concentrations in the electrochemical methods; in the SERS detection method, glucose causes the detection probe to agglomerate or change the surface structure, which changes the Raman intensity. Researchers use this Raman spectrum change to determine the UG concentration to be measured. In colorimetric detection, glucose produces H2O2 under the action of glucose oxidase, and hydrogen peroxide changes the color of the color probe; commonly used color probes are quantum dots (QDs),25,26 metal nanoparticles,27,28 TMB,29−31 etc. The above methods have been widely used in UG detection; these methods have a wider linear range, high sensitivity, and a low detection limit. However, they suffer from high cost, professional operation, complicated material synthesis, and modification processes. Moreover, most of these methods can only be performed in the laboratory. A universal, complete, and independent detection method is still vacant.

In this work, a portable UG analyzer was designed and manufactured. Its size is much smaller compared to medical instruments, which is very convenient to carry. Its core is the CdTe QDs@GOx aerogel circular array sensor. Through the fluorescence quenching reaction between glucose and the QDs@GOx aerogel, the linear relationship between the glucose concentration and the gray value of the fluorescence image is established. The linear range is 0–26 mM, and the detection limit is as low as 0.12 mM. The analysis software is written on the basis of this linear model; it can automatically read the gray value of the fluorescence picture and display the UG concentration, which greatly simplifies the data processing process. The UG analyzer was used for the detection of large clinical samples and showed good detection performance.

Results and Discussion

Detection Mechanism and Process

The detection principle and process are shown in Scheme 1. When UG solution is dropped onto the circular sensors, glucose produces H2O2 under the catalytic oxidation of GOx. H2O2 destroys the surface structure of CdTe QDs and quenches the fluorescence of QDs.34,35 Fluorescence changes in the sensors are captured by high-resolution industrial cameras and transmitted to the PC. The gray value of the picture is measured by the analysis software and calculated to show the glucose concentration. The whole process is very fast and efficient, and professional operation training is not needed.

Scheme 1. Detection Principle and Process.

Scheme 1

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Characteristics of the CdTe QD Aerogel

As described in the Experimental Section, CdTe QDs were synthesized by a simple one-step hydrothermal method. Figure 1a shows the fluorescence spectrum and ultraviolet (UV) spectrum of the synthesized CdTe QD aerogel. As shown in Figure 1a, the UV absorption peak wavelength of the prepared CdTe QDs is 580 nm, and the fluorescence emission peak wavelength is 610 nm, which is dazzling red under a UV lamp. Figure 1b is a scanning electron micrograph of the CdTe QD aerogel prepared by the freeze-drying method in the circular reaction area. The three-dimensional (3D) porous structure is clearly shown in Figure 1b; this 3D porous structure has a large specific surface area, which improves the reaction rate. Besides, the stabilizer of QDs is a polypeptide, which makes the 3D structure with good biocompatibility and provides a good site for the attachment of glucose oxidase, which improves the stability of the sensor.

Figure 1.

Figure 1

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(a) Fluorescence and UV spectra of CdTe QDs; (b) SEM images of CdTe-GOx aerogels in the reaction region.

Hardware Structure of the Portable UG Analyzer

The UG analyzer presents a closed box as a whole, which was made with 3D printing. The physical map can be seen in Figure S2. Since our analysis principle is fluorescence change, the completely enclosed structure can avoid the interference of ambient light and improve the stability and accuracy. The schematic diagram of the structure of the UG analyzer is shown in Figure 3. There is a sensor placement area on the base of the instrument. In order to excite the light intensity field uniformly, two UV light sources are symmetrically arranged on both sides of the placement area. The UV excitation wavelength is 365 nm. On the top of the instrument, an industrial camera is fixedly arranged, which is used to clearly capture the fluorescence image of the sensor and store and transmit it to the PC to perform software analysis and result readout. All subsequent experiments in this article are done using this instrument (Figure 2).

Figure 3.

Figure 3

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(a) Linear relationship between the change of fluorescence gray value and glucose concentration; (b) sensor fluorescence gradient image [from left to right: (a) 0 mM, (b) 0.085 mM, (c) 0.17 mM, (d) 0.34 mM, (e) 0.675 mM, (f) 1.35 mM, (g) 4.33 mM, (h) 10.8 mM, and (i) 26 mM].

Figure 2.

Figure 2

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Schematic diagram of the structure of the UG analyzer.

Optimization of Analytical Instruments

In order to get the fastest response time, the optimal detection time is explored. 10 μL of 10.8 mM glucose solution was dropped into the circular reaction area of the sensor. Fluorescence images are obtained at regular intervals and analyzed for gray values. The relationship between the gray value of the fluorescence image and the reaction time is obtained, as shown in Figure S3. The concentration of quantum dots was diluted 2.5,5,10 and 15 times, respectively. Glucose solutions of 4.33, 10.8, and 26 mM were dropped onto the sensors prepared with different concentrations of QDs. After 5 min of reaction, the fluorescence image of the reaction area was taken and calculated in the gray scale. As shown in Figure S4, with the reaction progressing, the fluorescent gray value of the reaction zone gradually decreases. When the reaction time reaches 5 min, the gray value tends to be stable. In order to improve the sensitivity of the sensor and the need for rapid detection, 5 min was determined as the best reaction time.

Different concentrations of QDs will affect the QDs fluorescence quenching. The gray value change rate of different QD concentrations is calculated, as shown in Table S1. When the QD stock solution is diluted 10 times, the rate of change of the gray value caused by 4.33 and 10.8 mM glucose is the largest, reaching 54.57 and 72.01%, respectively, and the rate of change of the gray value caused by 26 mM is not far from other concentrations. This means that when diluted 10 times, the QD probe has the greatest detection sensitivity and the most sensitive response to changes in glucose concentration. Therefore, comprehensively, the dilution of 10 is determined as the optimal concentration of the QD solution.

Establishment of the Glucose Detection Curve

Different concentrations of UG solutions are dropped onto the circular reaction area of the sensor. After 5 min of reaction, the fluorescence image of the reaction area is captured by the camera; the result is shown in Figure 3b. It can be observed from the figure that when the glucose concentration gradually increases, the red fluorescence in the reaction area gradually decreases. By comparing and analyzing the relationship between glucose concentration and the gray value, a linear curve of glucose concentration detection is established, as shown in Figure 3a. It can be seen from Figure 3a that from 0.085 to 26 mM, there is a good linear relationship between I/I0 and glucose concentration, and the correlation coefficient is 0.9933 (the gray value of the blank sample is defined as I0, and the gray value of the reaction area with different glucose concentrations is defined as I). The linear equation is (glucose concentration is defined as C)

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The limit of detection (LOD) is 0.12 mM.

Software Interface and the Operation Process

The software interface diagram based on the OPENCV library is shown in Figure 4. The interface is simple and intuitive. “Read” is used to read the fluorescence picture of the sensor transmitted by the camera. After the image is read, it will be displayed in the center of the interface, and the fluorescence changes of the sensor can be observed visually by the naked eye. This provides the qualitative judgment basis. When “Get CCNC” is clicked, the data bar on either side of the interface quickly displays the gray values for each circular area and the corresponding glucose concentration, and precise quantitative results are measured. The whole operation interface is very user-friendly, and users who do not need special training can operate. This enhances the utility potential of the portable diabetes meter. The logic flow of the software is shown in Figure 5 below. Since the position of the paper-based sensor in the UG analyzer is fixed, the detection area was selected by the software directly based on the fixed coordinates, the copyTo() function was used to cut and enlarge it and display it in the software interface, and then the cvtColor() function (using the CV_BGR2GRAY parameter) was used to convert the color picture into a grayscale picture, which is convenient to directly obtain the grayscale value of the pixel. The getcct() function is written to calculate the gray value of the detection area and calculate the UG concentration.

Figure 4.

Figure 4

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Software interface of the analyzer.

Figure 5.

Figure 5

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Logic flow chart of UG analysis software.

Selectivity and Stability

The selectivity of the sensor was studied. 10.8 mM glucose, sucrose, fructose, maltose, lactose, and urea as well as 0.45 mM uric acid and 0.6 mM ascorbic acid are configured. The concentrations of uric acid and ascorbic acid are the upper limits of urine in healthy humans. 10 μL of various test solutions is dropped onto the circular reaction area of the sensor, and the resulting fluorescence gray value is analyzed. The results are shown in Figure 6a; as can be seen in Figure 6a, glucose can cause severe fluorescence quenching of the sensor, and other substances have basically no effect on fluorescence quenching. The excellent selectivity of the sensor is verified.

Figure 6.

Figure 6

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(a) Sensor selectivity; (b) sensor stability. The detection of real clinical samples.

The stability of the sensor was also studied. The sensor is placed in a plastic box, and the air is evacuated using a vacuum machine. Then, the plastic box containing the sensor is placed in a refrigerator at −20 °C. The glucose solutions of 0 and 10.8 mM are dropped onto the sensor every 15 days, and the fluorescence gray value is analyzed and compared. The results are shown in Figure 6b; as can be seen in Figure 6b, within 45 days, the gray value of the sensor fluorescence remained basically unchanged, which meets the requirements of industrial and clinical use.

In order to verify the reliability of the UG analyzer for the detection of different urine samples, 208 clinical samples were detected in cooperation with Nanjing Zhongda Hospital. In order to stabilize the pH value of the samples, all urine samples were diluted 10 times with phosphate buffered saline (PBS) buffer with a pH of 7.4. The measurement results are compared with those of medical instruments (Uretest-500B Automatic Urine Chemistry Analyzer of URIT). Table 1 shows the measurement results and comparison of the two instruments. In contrast, we have a good recovery rate and a higher positive detection rate, which mean that we have not missed any possible suspected positive cases, which is of great significance for the early screening of diabetes.

Table 1. Comparison of Test Results of Two Instruments.

UG gradient Uretest-500B ours recovery (%)
–(0–5.6 mM) 52 49 94.23
+(5.6–14 mM) 38 40 105.26
++(14–28 mM) 46 38 82.61
≥+++(≥28 mM) 72 81 112.5
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In addition, five commonly used UG test papers were purchased from the market for comparison tests with our instruments. The sample results tested using medical instruments were used as a standard control group. The comparative test result is shown in Figure 7; it can be seen intuitively from the stacking graph that our test results are closest to the standard values, and the proportions of each concentration gradient are roughly equal.

Figure 7.

Figure 7

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UG test paper comparison test stacking chart.

In order to quantitatively indicate the accuracy difference between various UG test papers, the standard deviation of each UG test paper and the standard control group was calculated. The calculation results are shown in Table 2. From the comparison of specific values, we can see that the standard deviation of the instrument we developed is the smallest. From the above multi-sample test and comparison, it can be seen that the UG analyzer developed by us has reliable accuracy and stability and has the value of clinical practical use.

Table 2. Comparison of Standard Deviation Values of UG Test Papers.

standard deviation ACCU ANJIAN GAOERBAO URIT AVE ours
standard 27.50 76.58 57.83 28.98 28.53 14.07
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Conclusions

Herein, based on the CdTe QDs@GOx aerogel circular array sensor, we designed and manufactured a portable, highly sensitive, and selective UG analyzer. The linear range is 0–26 mM, and the detection limit is as low as 0.12 mM. User-friendly and easy-to-use analysis software has also been developed to circumvent the responsible data post-processing process and improve detection efficiency and capabilities. In the detection of a large number of clinical samples and comparison with a variety of UG test paper tests, the analyzer has demonstrated good detection performance. Our work provides an important approach for diabetes screening, early treatment, and patient self-health management.

Experimental Section

Materials

All chemicals were of analytical grade. 2.5 cadmium chloride hydrate (CdCl2·2.5H2O) (Alfa Aesar), sodium borohydride (NaBH4) (Alfa Aesar), l-glutathione (L-GSH) (Alfa Aesar), sodium tellurate (Na2TeO3) (Alfa Aesar), sodium hydroxide (NaOH) (Chengdu KESHI Company), PBS buffer (Biosharp, 10 mM), isopropanol (C3H8O) (Chengdu KESHI Company), polyimide (Beijing Yinuokai Technology Co., Ltd.), ethanol (C2H6O) (Sinopharm Reagent), and polydimethylsiloxane (Dow Corning Corp., USA) were the chemicals purchased. Ultrapure water (≥18 MΩ·cm2) was prepared using a Millipore water purification system.

Synthesis of Cadmium Telluride QDs (CdTe QDs)

The red-emission CdTe QDs were synthesized based on the reported method.32,33 A 100 mL beaker was dried with nitrogen, and 55 mL of ultrapure water was added to it. 0.1028 g of CdCl2·2.5H2O and 0.1844 g of L-GSH were weighed and added to the beaker; a Teflon A25 magnetic stirrer was added to the beaker, and NaOH solution with a concentration of 0.5 mM was prepared. The pH value of the mixed solution in the beaker was detected using a Mettler pH meter. The solution was continuously stirred with a magnetic stirrer, and NaOH solution was added in drops to adjust the pH value to 10.5. Then, 0.0222 g of Na2TeO3 and 0.0038 g of NaBH4 were added to the mixed solution successively and stirred for 30 min; after the completion of the mixing, the solution was placed in a flask and was heated in an oil bath at 110 °C for 6 h. After heating, 10 mL of ethylene glycol was added to the solution and the CdTe QD solution was obtained by centrifugation at 5000 rpm for 6 min.

Preparation of the CdTe QDs@GOx Aerogel Circular Array Sensor

The PDMS prepolymer and cross-linker were mixed in a weighing boat at a mass ratio of 10:1; the mixture was stirred for 5 min and then was put in a vacuum storage system to evacuate until the bubbles were removed. The polyimide film was flattened on the glass slide, and the excess was cut off; then, the glass slide was placed on the spin coating platform of the spin coater, and 4 g of the PDMS mixed reagent was poured on it, spin coating at 900 rpm for 55 s. After the spin coating was completed, the glass slide was placed in an oven at 80 °C for 1 h; a laser processing machine was used to process the cured composite film into the desired shape. The basic dimensions of the PDMS film are 50 cm long and 22 cm wide (details can be seen in Figure S1). After the processing is completed, the composite film is placed in ethanol for ultrasonic cleaning for 5 min and then placed on a dust-free paper to dry naturally. The dried composite film PDMS is put with the face up with the glass slide into the plasma cleaner for bonding. After the bonding is completed, it is placed in a 120 °C oven for 3 h to enhance the bonding strength. The dried chips were placed with the face up in a plasma cleaner for 2 min to make the chip reaction section hydrophilic; then, 10 μL of CdTe-GOx solution (the GOX concentration is 25 mM) was added dropwise to each round reaction section. The chips were freezed at −20 °C for 12 h. After the freezing is completed, it is placed in a freeze dryer and dried for 3 h. After taking out, a circular array sensor is obtained.

Establishment of the UG Linear Curve

Glucose was added to 2 mL of urine from healthy volunteers to get the final concentrations of 0, 0.085, 0.17, 0.34, 0.675, 1.35, 4.33, 10.8, and 26 mM. 10 μL of glucose solution of the abovementioned concentrations was dropped onto the circular array sensor. 5 min later, the change in the fluorescence color of the chip was captured by a high-resolution industrial camera under the 365 nm UV-LED of the analyzer and a linear curve for glucose detection was established.

Acknowledgments

This work was supported by the National Key Scientific Instrument and Equipment Development Project (grant no. 51627808), the National Natural Science Foundation of China (grant nos. 51605088 and 51505083), the Natural Science Foundation of Jiangsu Province (grant no. BK20170667), and the National Key R&D Program of China (grant no. 2016YFC1305700).

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.1c03449.

  • Sensor dimensions; UG analyzer display; response time optimization; concentration optimization of quantum dots; and fluorescence attednuation of glucose solution measured by various sensors (PDF)

Author Contributions

H.Y., Z.N., and X.L. provided funding and equipment support for this topic. T.H. and K.C. planned and directed experiments. K.X. and W.L. designed and implemented experiments. T.H. and K.X. wrote and revised the paper.

The authors declare no competing financial interest.

Supplementary Material

ao1c03449_si_001.pdf (336.9KB, pdf)

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