| 光谱学与光谱分析 |
|
|
|
|
|
| Design of Advanced Glycation Endproducts Fluorescence Spectrum Detecting System |
| XU Liang-yuan1, 2, ZHU Ling1, ZHANG Long1, YU Feng3, LIU Yong1, ZHANG Gong4, WU Lu-sheng1 |
1. Anhui Institute of Optics and Fine Mechanics，Chinese Academy of Sciences，Hefei 230031，China
2. Engineering College，Anhui Agricultural University，Hefei 230036，China
3. The Affiliated Provincial Hosptial of Anhui Medical University, Hefei 230001, China
4. University of Winnipeg，Manitoba，R3T6A5，Canada |
|
|
|
|
Abstract The method of making use of the technique of fluorescence spectrum to detect advanced glycation endproducts is discussed in the present pape. The emphasis is on the principle and structure of the fluorescence spectrum detecting system．In the end, the authors made use of the system to detect the excitation spectrum at the wavelengths of 365nm, 370nm, 375nm, 380nm and 385nm, respectively, and the authors found that 375nm is the best excitation wavelength. At the same time, the emission spectrum was also detected on the skin of nondiabetic people and patients with diabetes respectively. The result of the experiment indicates that there is a difference distinctly at about 450nm between them, and has proved the feasibility of the system. The detecting system does not need collecting blood sample, is a noninvasive detection technology, and avoids pain and infection to the patients. The process of detection is very rapid and convenient, and the repetitiveness is well. The patient can benefit from it to forecast and diagnose the state of illness such as diabetes, decrepitude and oxidative stress etc conveniently.
|
|
Received: 2008-07-16
Accepted: 2008-10-18
|
|
|
|
Corresponding Authors:
XU Liang-yuan
E-mail: xlyjwh@126.com
|
|
[1] SUN Mian-en, DU Guan-hua(孙缅恩, 杜冠华). Chinese Pharmacological Bulletin(中国药理学通报), 2002, 18(3): 246.
[2] WEN Wen(文 雯). Journal of Mathematical Medicine(数理医药学杂志), 2005, 18(6): 611.
[3] LI Xing-chuan, GUO Zuo-da, LIN Da-quan(李星川, 郭祚达, 林大全). China Measurement Technology(中国测试技术), 2005, 31(1): 120.
[4] YAN Ji-xiang, ZHANG Yan, LI Jia-ze(阎吉祥, 张 雁, 李家泽). Optical Technique(光学技术), 1999, 5: 51.
[5] WEN Shang-sheng(文尚胜). Optical Technique(光学技术), 2003, 29(5): 587.
[6] HUANG Bao-hua, CHEN Rong, ZENG Hai-shan, et al(黄宝华, 陈 荣, 曾海山, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2007, 27(1): 95.
[7] Thome J, Munch G, MUlier R, et al. Life Sci., 1996, 59: 679.
[8] Wu I T, Tu M C, Zhung P. J. Clin. Lab. Anal., 1996, 10: 21.
[9] Münch G, Keis R, Wessels A, et al. Eur. J. Clin. Chem. Clin. Biochem, 1997, 35(9): 669.
[10] McCance D R, Dyer D G, Dunn J A, et al. J. Clin. Invest, 1993, 91(6): 2470. |
| [1] |
LEI Hong-jun1, YANG Guang1, PAN Hong-wei1*, WANG Yi-fei1, YI Jun2, WANG Ke-ke2, WANG Guo-hao2, TONG Wen-bin1, SHI Li-li1. Influence of Hydrochemical Ions on Three-Dimensional Fluorescence
Spectrum of Dissolved Organic Matter in the Water Environment
and the Proposed Classification Pretreatment Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 134-140. |
| [2] |
GU Yi-lu1, 2，PEI Jing-cheng1, 2*，ZHANG Yu-hui1, 2，YIN Xi-yan1, 2，YU Min-da1, 2, LAI Xiao-jing1, 2. Gemological and Spectral Characterization of Yellowish Green Apatite From Mexico[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 181-187. |
| [3] |
HAN Xue1, 2, LIU Hai1, 2, LIU Jia-wei3, WU Ming-kai1, 2*. Rapid Identification of Inorganic Elements in Understory Soils in
Different Regions of Guizhou Province by X-Ray
Fluorescence Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 225-229. |
| [4] |
WANG Hong-jian1, YU Hai-ye1, GAO Shan-yun1, LI Jin-quan1, LIU Guo-hong1, YU Yue1, LI Xiao-kai1, ZHANG Lei1, ZHANG Xin1, LU Ri-feng2, SUI Yuan-yuan1*. A Model for Predicting Early Spot Disease of Maize Based on Fluorescence Spectral Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3710-3718. |
| [5] |
CHENG Hui-zhu1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, MA Qian1, 2, ZHAO Yan-chun1, 2. Genetic Algorithm Optimized BP Neural Network for Quantitative
Analysis of Soil Heavy Metals in XRF[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3742-3746. |
| [6] |
SONG Yi-ming1, 2, SHEN Jian1, 2, LIU Chuan-yang1, 2, XIONG Qiu-ran1, 2, CHENG Cheng1, 2, CHAI Yi-di2, WANG Shi-feng2，WU Jing1, 2*. Fluorescence Quantum Yield and Fluorescence Lifetime of Indole, 3-Methylindole and L-Tryptophan[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3758-3762. |
| [7] |
YANG Ke-li1, 2, PENG Jiao-yu1, 2, DONG Ya-ping1, 2*, LIU Xin1, 2, LI Wu1, 3, LIU Hai-ning1, 3. Spectroscopic Characterization of Dissolved Organic Matter Isolated From Solar Pond[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3775-3780. |
| [8] |
LI Xiao-li1, WANG Yi-min2*, DENG Sai-wen2, WANG Yi-ya2, LI Song2, BAI Jin-feng1. Application of X-Ray Fluorescence Spectrometry in Geological and
Mineral Analysis for 60 Years[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 2989-2998. |
| [9] |
XUE Fang-jia, YU Jie*, YIN Hang, XIA Qi-yu, SHI Jie-gen, HOU Di-bo, HUANG Ping-jie, ZHANG Guang-xin. A Time Series Double Threshold Method for Pollution Events Detection in Drinking Water Using Three-Dimensional Fluorescence Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3081-3088. |
| [10] |
MA Qian1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, CHENG Hui-zhu1, 2, ZHAO Yan-chun1, 2. Research on Classification of Heavy Metal Pb in Honeysuckle Based on XRF and Transfer Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2729-2733. |
| [11] |
JIA Yu-ge1, YANG Ming-xing1, 2*, YOU Bo-ya1, YU Ke-ye1. Gemological and Spectroscopic Identification Characteristics of Frozen Jelly-Filled Turquoise and Its Raw Material[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2974-2982. |
| [12] |
YANG Xin1, 2, XIA Min1, 2, YE Yin1, 2*, WANG Jing1, 2. Spatiotemporal Distribution Characteristics of Dissolved Organic Matter Spectrum in the Agricultural Watershed of Dianbu River[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2983-2988. |
| [13] |
CHEN Wen-jing, XU Nuo, JIAO Zhao-hang, YOU Jia-hua, WANG He, QI Dong-li, FENG Yu*. Study on the Diagnosis of Breast Cancer by Fluorescence Spectrometry Based on Machine Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2407-2412. |
| [14] |
ZHU Yan-ping1, CUI Chuan-jin1*, CHENG Peng-fei1, 2, PAN Jin-yan1, SU Hao1, 2, ZHANG Yi1. Measurement of Oil Pollutants by Three-Dimensional Fluorescence
Spectroscopy Combined With BP Neural Network and SWATLD[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2467-2475. |
| [15] |
LIU Xian-yu1, YANG Jiu-chang1, 2, TU Cai1, XU Ya-fen1, XU Chang3, CHEN Quan-li2*. Study on Spectral Characteristics of Scheelite From Xuebaoding, Pingwu County, Sichuan Province, China[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2550-2556. |
|
|
|
|
