Multivariate analysis to separate the signal given by cross-reactants in immunoassay with sample matrix dilution

摘要: This paper describes a new approach to achieve selectivity in an immunoassay by separating the signals given two cross-reactive compounds present simultaneously complex sample matrix. The method is based on sequential dilution of containing mixture analytes, spiking each diluted with reference compound, and detection enzyme-linked immunosorbent assay (ELISA). obtained multivariate response was used for individual calibrations cross-reactants using principal component analysis (PCA) partial least squares regression (PLSR) data modeling. calibration models showed that signal separation due analytes 2,4-dinitrophenol (2,4-DNP) 4-nitrophenol (4-NP) possible prediction concentration error 1.4 μM 72 μM, respectively.