Department of Chemistry, Faculty of Sciences, University of Tehran, P.O. Box, 14155-6455, Tehran, Iran.
Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, 08034, Barcelona, Catalonia, Spain.
Anal Chim Acta. 2020 May 29;1113:52-65. doi: 10.1016/j.aca.2020.03.057. Epub 2020 Apr 1.
The application of the recently developed area correlation constraint in Multivariate CurveResolution-Alternating Least Squares (MCR-ALS) for the quantitative determination of analyte mixtures is shown. The feasibility of the proposed constraint is tested firstly for the calibration and quantitation of PAHs mixtures in their synthetic mixtures (validation samples) and in river water samples dissolved organic matter (DOM) using EEM fluorescent three-way data. In this case, MCR-ALS results obtained with the proposed area correlation constraint are comparable with the results obtained with methods based on the fulfillment of the trilinear model, like PARAFAC and MCR-ALS with the trilinearity constraint. Secondly, the possibility of applying this new area correlation constraint is extended to the analytical determination of lipid mixtures in synthetic and cell culture samples by LC-MS, where the trilinear model does not hold. The applicability of the proposed area correlation constraint is assessed, and it is proposed as a general tool for the quantitative determination of unknown mixtures of analytes in complex natural samples with severe profile overlapping and unknown composition, whatever the data structure is.
本文展示了最近开发的区域相关约束在多元曲线分辨交替最小二乘法（MCR-ALS）中对分析物混合物定量测定的应用。首先，我们使用 EEM 荧光三向数据，在合成混合物（验证样本）和河水中溶解有机物（DOM）中对 PAHs 混合物的校准和定量，对所提出的约束的可行性进行了测试。在这种情况下，使用所提出的区域相关约束得到的 MCR-ALS 结果与基于满足三线性模型的方法（如 PARAFAC 和带有三线性约束的 MCR-ALS）得到的结果相当。其次，将这种新的区域相关约束的可能性扩展到通过 LC-MS 对合成和细胞培养样品中脂质混合物的分析测定，其中三线性模型不成立。评估了所提出的区域相关约束的适用性，并将其作为一种通用工具，用于在严重轮廓重叠和未知组成的复杂天然样品中对未知分析物混合物进行定量测定，无论数据结构如何。
