Multivariate analysis to separate the signal given by cross-reactants in immunoassay with sample matrix dilution.
This paper describes a new approach to achieve selectivity in an immunoassay by separating the signals given by two cross-reactive compounds present simultaneously in a complex sample matrix. The method is based on the sequential dilution of the sample containing a mixture of the two analytes, spiking each diluted sample with a reference compound, and the detection by enzyme-linked immunosorbent assay (ELISA). The obtained multivariate response was used for the individual calibrations of the assay for each of the two cross-reactants simultaneously by using principal component analysis (PCA) and partial least squares regression (PLSR) data modeling. The calibration models showed that the signal separation due the analytes 2,4-dinitrophenol (2,4-DNP) and 4-nitrophenol (4-NP) was possible with a prediction concentration error of 1.4 microM and 72 microM, respectively.
Nistor
Catalin
C
Department of Analytical Chemistry, Lund University, P.O. Box 124, 221 00 Lund, Sweden.
Christensen
Jakob
J
Ocio
Natalia
N
Nørgaard
Lars
L
Emnéus
Jenny
J
D019297:2,4-Dinitrophenol / Q000032:analysis* / Q000737:chemistry; D000818:Animals; D002138:Calibration; D003429:Cross Reactions; D004797:Enzyme-Linked Immunosorbent Assay; D016018:Least-Squares Analysis; D008892:Milk / Q000737:chemistry*; D015999:Multivariate Analysis; D009596:Nitrophenols / Q000032:analysis* / Q000737:chemistry; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
D009596:Nitrophenols; D019297:2,4-Dinitrophenol; C024836:4-nitrophenol