Department of Ophthalmology and Visual Sciences, University of Louisville, Louisville, Kentucky, USA.
Curr Eye Res. 2010 Sep;35(9):778-86. doi: 10.3109/02713683.2010.490895.
PURPOSE: Changes in the phase transition temperatures and conformation of human meibum lipid with age and meibomian gland dysfunction (MGD) have been quantified. Less than 1% of the infrared spectral range was used in the previous studies to demonstrate differences. In this study, the remaining 99% of the spectral frequencies were analyzed to gain insight into changes that occur in meibum with age. METHODS: Infrared spectra of meibum from 27 normal donors were acquired. Principal component analysis (PCA) was used to quantify the variance between the spectra. RESULTS: PCA was applied to a set of training spectra of human meibum to predict the age of meibum donors. The plot of predicted age versus actual age was linear, p < 0.001 with a slope of 1.00 and r = 0.909. This indicates that changes in constituents of the meibum spectra (eigenvectors) were due to age-related compositional differences. Eigenvector 1 accounted for 92% of the variance observed among all of the meibum spectra. The spectral features of the two major eigenvectors indicate that with increasing age, the meibum contains more wax, double bonds and terminal CH(3) groups, and is less ordered. The environment of the carbonyl band becomes less polar with increasing age. These results are similar to those obtained for human sebum. CONCLUSIONS: PCA is an excellent chemometric algorithm that may be used to characterize MGD and age-related changes in human meibum. The eigenvectors that define the variations in the spectra provide clues to the compositional changes that occur in meibum with age.
目的:已经量化了人睑脂相变温度和构象随年龄和睑板腺功能障碍(MGD)的变化。以前的研究中仅使用了红外光谱范围的不到 1%来证明差异。在这项研究中,分析了光谱的其余 99%频率,以深入了解随年龄变化的睑脂变化。
方法:获取了 27 名正常供体的睑脂红外光谱。主成分分析(PCA)用于量化光谱之间的方差。
结果:将 PCA 应用于一组人睑脂的训练光谱,以预测睑脂供体的年龄。预测年龄与实际年龄的图呈线性,p<0.001,斜率为 1.00,r=0.909。这表明睑脂光谱成分的变化(特征向量)是由于与年龄相关的组成差异。特征向量 1 占所有睑脂光谱观察到的方差的 92%。两个主要特征向量的光谱特征表明,随着年龄的增长,睑脂中含有更多的蜡、双键和末端 CH(3)基团,并且有序性降低。羰基带的环境随年龄的增长变得不那么极性。这些结果与人体皮脂获得的结果相似。
结论:PCA 是一种出色的化学计量算法,可用于表征 MGD 和人睑脂的年龄相关变化。定义光谱变化的特征向量提供了关于随年龄变化的睑脂中发生的组成变化的线索。
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