Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, Georgia, United States of America ; College of Pharmacy, Korea University, Sejong City, Korea.
PLoS One. 2013 Aug 21;8(8):e69000. doi: 10.1371/journal.pone.0069000. eCollection 2013.
The concept of multifractality is currently used to describe self-similar and complex scaling properties observed in numerous biological signals. Fractals are geometric objects or dynamic variations which exhibit some degree of similarity (irregularity) to the original object in a wide range of scales. This approach determines irregularity of biologic signal as an indicator of adaptability, the capability to respond to unpredictable stress, and health. In the present work, we propose the application of multifractal analysis of wavelet-transformed proton nuclear magnetic resonance ((1)H NMR) spectra of plasma to determine nutritional insufficiency. For validation of this method on (1)H NMR signal of human plasma, standard deviation from classical statistical approach and Hurst exponent (H), left slope and partition function from multifractal analysis were extracted from (1)H NMR spectra to test whether multifractal indices could discriminate healthy subjects from unhealthy, intensive care unit patients. After validation, the multifractal approach was applied to spectra of plasma from a modified crossover study of sulfur amino acid insufficiency and tested for associations with blood lipids. The results showed that standard deviation and H, but not left slope, were significantly different for sulfur amino acid sufficiency and insufficiency. Quadratic discriminant analysis of H, left slope and the partition function showed 78% overall classification accuracy according to sulfur amino acid status. Triglycerides and apolipoprotein C3 were significantly correlated with a multifractal model containing H, left slope, and standard deviation, and cholesterol and high-sensitivity C-reactive protein were significantly correlated to H. In conclusion, multifractal analysis of (1)H NMR spectra provides a new approach to characterize nutritional status.
多重分形的概念目前被用于描述在许多生物信号中观察到的自相似和复杂的标度属性。分形是几何对象或动态变化，在广泛的尺度上表现出与原始对象一定程度的相似性（不规则性）。这种方法将生物信号的不规则性确定为适应性的指标，即对不可预测的压力做出反应的能力和健康状况。在本工作中，我们提出了应用小波变换质子磁共振（1H NMR）谱的多重分形分析来确定营养不足。为了验证这种方法在人血浆 1H NMR 信号上的有效性，从经典统计方法中提取了标准偏差和 Hurst 指数（H），从多重分形分析中提取了左斜率和分形函数，以检验多重分形指数是否能够区分健康受试者和不健康的重症监护病房患者。验证后，将多重分形方法应用于硫氨基酸不足的交叉研究的血浆光谱，并测试其与血脂的相关性。结果表明，在硫氨基酸充足和不足时，标准偏差和 H 但不是左斜率有显著差异。H、左斜率和分形函数的二次判别分析根据硫氨基酸状态显示出 78%的总体分类准确性。甘油三酯和载脂蛋白 C3 与包含 H、左斜率和标准偏差的多重分形模型显著相关，胆固醇和高敏 C 反应蛋白与 H 显著相关。总之，1H NMR 光谱的多重分形分析为描述营养状况提供了一种新方法。
