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LF-NMR and multivariate data analysis: compression of data to classify hydrogel contact lenses

机译:LF-NMR和多变量数据分析:数据压缩以对水凝胶隐形眼镜分类

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摘要

Hydrogel contact lenses swollen in viscoelastic artificial tears solution have been studied, measuring transversal relaxation times of water molecules using LF-NMR techniques. Data were processed by classical multiexponential fitting, by principal component analysis and by SLICING, a multi-way analysis method. The reason for using multivariate data analysis was not to obtain a better fitting, but rather more effective data description. The single-sample relaxation curves were projected in a space spanned by the loading curves, and in this space it was simpler to compare data. In particular, it contributed to the description of the variability of motion characteristics of the water molecule 'families' contained in the studied samples. Applying multivariate techniques, we were able to group lenses with different Equilibrium Water Content (EWC) and with the same water content but different compositions. Accordingly, we were able to point out that, if the lenses are swollen first in physiological solution and then in viscoelastic artificial tears solution, hydration characteristics remained unchanged in all the studied samples, except for 38% EWC lenses.
机译:已经研究了在粘弹性人工泪液中溶胀的水凝胶隐形眼镜,使用LF-NMR技术测量水分子的横向弛豫时间。通过经典的多指数拟合,主成分分析和多方分析方法SLICING对数据进行处理。使用多元数据分析的原因不是为了获得更好的拟合,而是更有效的数据描述。单样本松弛曲线投影在由加载曲线跨越的空间中,在该空间中比较数据更为简单。特别是,它有助于描述所研究样品中所含水分子“家族”的运动特征的变异性。应用多元技术,我们能够对具有不同平衡水含量(EWC)且具有相同水含量但组成不同的镜片进行分组。因此,我们能够指出,如果先将镜片在生理溶液中然后在粘弹性人工泪液中溶胀,则除38%EWC镜片外,所有研究样品的水合特性均保持不变。

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