光谱学与光谱分析 |
|
|
|
|
|
Research on the Autofluorescence Spectroscopy in Rats Doing Medium-Intensity Exercise |
REN Wen-jun1,4, XU Zheng-hong2, ZHANG Zhen-xi1*, YANG Xu-dong3, LI Zheng1 |
1. Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China 2. School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China 3. College of Medicine, Xi’an Jiaotong University, Xi’an 710061, China 4. Department of Physical Education, Xi’an Jiaotong University, Xi’an 710049,China |
|
|
Abstract The laser-inducted fluorescence spectrum technology (LIF) was used for the first time to study the autofluorescence spectral characteristics of the heart, kidney, liver, fat, foreleg muscle, hind leg soleus muscle and musculus gastrocnemius of the rat performing motion exercises. The wavelength of the excitation light used during the measurement was in the range of 250-650 nm and the emission wavelength was 300-700 nm. When comparing the three-dimensional fluorescence spectra of the control group with those of the four groups of different motion states, a specific fluorescence peak related to the motion and located in the area where the excitation wavelength was (340±10) nm and the emission wavelength was (460±10) nm was found mainly in the spectra of the soleus muscle. From this fluorescence peak, it is possible to determine that its corresponding fluorescent substance is NADH (nicotinamide adenine dinucleotide reduced). When comparing the fluorescence spectra of the four groups of different motion modes, it was found that the motion mode has a conspicuous relativity with the peak intensity. The results show that the energy metabolism of the soleus muscle of the rat in motion is stronger than that of the foreleg, soleus muscle and other visceras, and the autofluorescence spectral characteristics of NADH form one of the effective indexes for determining the muscular metabolism degree.
|
Received: 2008-06-28
Accepted: 2008-09-29
|
|
Corresponding Authors:
ZHANG Zhen-xi
E-mail: zxzhang@mail.xjtu.edu.cn
|
|
[1] LI Bu-hong, XIE Shu-sen(李步洪, 谢树森). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2005, 25(7): 1083. [2] A’Amar O, Guillemin F, Begorre H, eta l. Proc. of SPIE, 1997, 3197: 41. [3] XU Zheng-hong, ZHANG Zhen-xi, WANG Jing, et al(徐正红,张镇西,王 晶,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2007, 27(7): 1359. [4] LUO Qing-ming, GONG Hui, LIU Xian-de, et al(骆清铭, 龚 辉, 刘贤德, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 1997, 17(3): 105. [5] SHI Xiao-feng, MA Jun, MAO Wei-zheng,et al(史晓凤, 马 君, 毛伟征, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(2): 295. [6] Tuan Vo-Dinh. Biomedical Photonics Handbook. USA:CRC Press, 2003. [7] ZHANG Zhen-xi, YAO Cui-ping, XU Zheng-hong, et al(张镇西,姚翠萍,徐正红,等). Biomedical Photonics Now Technology and Application(生物医学光子学新技术及应用). Beijing:Science Press(北京:科学出版社),2008. 6. [8] LI Bu-hong, ZHANG Zhen-xi, XIE Shu-sen, et al(李步洪, 张镇西, 谢树森, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(7): 1310. [9] WANG Jing, ZHANG Zhen-xi, XU Zheng-hong, et al(王 晶,张镇西,徐正红,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2008, 28(3): 617. [10] Brooks G A. Medicine and Science in Sports and Exercise, 1985, 17(1): 22. [11] Chance B. Nature, 1959, 184: 195. [12] Schantz P G. Acta Physiolgica Scandinavica, 1986, 128:1(suppl. 558). [13] Sahlin K. Clinical Physiology, 1983, 3(5): 477. [14] Katz A, Edlund A, Sahlin K. Acta Physiolgica Scandinavica, 1987, 130(2): 193. [15] HONG Ping, ZHAO Peng, YANG Kui-sheng(洪 平,赵 鹏,杨奎生). Chin. J. Sports Med.(中国运动医学杂志), 2002, 21(3): 261. |
[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. |
|
|
|
|