Developing a Portable Autofluorescence Detection System and Its Application in Biological Samples

被引:0
|
作者
Zhou, Jiaxing [1 ]
Li, Yunfei [1 ]
Zhang, Jinfeng [1 ]
Cai, Fuhong [1 ]
机构
[1] Hainan Univ, Sch Biomed Engn, Sanya 572000, Peoples R China
关键词
fluorescence monitoring; advanced glycation end-products (AGEs); portable detection system; diabetes management; GLYCATION END-PRODUCTS; SKIN AUTOFLUORESCENCE; RISK; AGES; HEMOGLOBIN;
D O I
10.3390/s24113351
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Advanced glycation end-products (AGEs) are complex compounds closely associated with several chronic diseases, especially diabetes mellitus (DM). Current methods for detecting AGEs are not suitable for screening large populations, or for long-term monitoring. This paper introduces a portable autofluorescence detection system that measures the concentration of AGEs in the skin based on the fluorescence characteristics of AGEs in biological tissues. The system employs a 395 nm laser LED to excite the fluorescence of AGEs, and uses a photodetector to capture the fluorescence intensity. A model correlating fluorescence intensity with AGEs concentration facilitates the detection of AGEs levels. To account for the variation in optical properties of different individuals' skin, the system includes a 520 nm light source for calibration. The system features a compact design, measuring only 60 mm x 50 mm x 20 mm, and is equipped with a miniature STM32 module for control and a battery for extended operation, making it easy for subjects to wear. To validate the system's effectiveness, it was tested on 14 volunteers to examine the correlation between AGEs and glycated hemoglobin, revealing a correlation coefficient of 0.49. Additionally, long-term monitoring of AGEs' fluorescence and blood sugar levels showed a correlation trend exceeding 0.95, indicating that AGEs reflect changes in blood sugar levels to some extent. Further, by constructing a multivariate predictive model, the study also found that AGEs levels are correlated with age, BMI, gender, and a physical activity index, providing new insights for predicting AGEs content and blood sugar levels. This research supports the early diagnosis and treatment of chronic diseases such as diabetes, and offers a potentially useful tool for future clinical applications.
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页数:11
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