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KMID : 0370220050490010074
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Yakhak Hoeji
2005 Volume.49 No. 1 p.74 ~ p.79
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Pattern Recognition Using NMR Spectral Data for Metabonomic Analysis of Urine Samples from Experimental Animals
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주현진/Joo HJ
조정환/Cho JH
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Abstract
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Metabonomic analysis has been recognized as a powerful approach for characterizing metabolic changes in biofluids due to toxicity disease process or environmental influences. To investigate the possibility of relating metabolic changes with ¹H-NMR spectra, urine samples from Sprague-Dawley rats treated with various dietary restrictions or toxic substances (nicotine) were analysed using ¹H-NMR spectroscopy and pattern recognition techniques. Dietary restrictions-given to male rats were normal diet and high fat diet and fasting. The nicotine urine samples were collected from SD rats administered with nicotine (25 mg/kg) at the various time intervals. ¹H-NMR spectra of all urine samples were acquired at 400 MHz on a VARIAN spectrometer. To establish the presence of any intrinsic class-related patterns or clusters in each NMR data, methods of PCA (principal component analysis) and soft independent modeling of class analogy (SIMCA) analysis were used, and the results from these analyses were compared to each other, In all cases of dietary conditions and nicotine treatment, SIMCA analysis gave better results for the discrimination of NMR spectra of urine samples than PCA.
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KEYWORD
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