Multi-way partial least-squares and residual bi-linearization for the direct determination of monohydroxy-polycyclic aromatic hydrocarbons on octadecyl membranes via room-temperature fluorescence excitation emission matrices

Abstract

Multi-way partial least-squares (N-PLS) is combined to the residual bi-linearization procedure (RBL) for the direct analysis of metabolites of polycyclic aromatic hydrocarbons in urine samples. Metabolite analysis is carried out via a two-step experimental procedure based on solid-phase extraction and room temperature fluorescence spectroscopy. Excitation-emission matrices are recorded from octadecyl (C18) membranes that serve as solid substrates for sample extraction and spectroscopic measurements. Excellent metabolite recoveries were obtained in all cases, which varied from 96.2±1.35% (9-hydroxyphenanthrene) to 99.7±0.49% (3-hydroxybenzo[a]pyrene). Background correction of extraction membranes is carried out with a new alternating least-squares (ALS) procedure adapted to second order data. The performance of N-PLS/RBL is compared to the well-established multivariate curve resolution-alternating least-squares (MCR-ALS) algorithm. Both algorithms provided similar analytical figures of merit, including their ability to handle unknown interference in urine samples. With only 10mL of sample, the limits of detection varied between 0.06–0.08ngmL−1 (1-hydroxypyrene) and 0.016–0.018ngmL−1 (2-hydroxyfluorene). When compared to previously reported univariate calibration data, the limits of detection via N-PLS/RBL and MCR-ALS are approximately one order of magnitude higher. This was somehow expected due to the effect of unexpected components in multivariate figures of merit, i.e. a more realistic approach to the analysis of metabolites in human urine samples.