Evaluation of partial least-squares with second-order advantage for the multi-way spectroscopic analysis of complex biological samples in the presence of analyte-background interactions.

MARÍA J. CULZONI, HÉCTOR C. GOICOECHEA, ARIANA P. PAGANI, MIGUEL A. CABEZÓN, ALEJANDRO C.

ANALYST

Año: 2006 vol. 131 p. 718 - 723

0003-2654

AbstractThe combination of unfolded partial least-squares (U-PLS) with residual bilinearization (RBL)has not been properly exploited to process experimental second-order spectroscopic information,although it is able to achieve the important second-order advantage. Among other desirableproperties, the technique can handle incomplete calibration information, i.e., when only certainanalyte concentrations are known in the training set. It can also cope with analyte spectralchanges from sample to sample, due to its latent variable structure. In this work, U-PLS/RBL hasbeen successfully applied to experimental fluorescence excitation–emission matrix data aimed atthe quantitation of analytes in complex samples: these were the antibiotic tetracycline and theanti-inflammatory salicylate, in both cases in the presence of human serum, where significantanalyte–background interactions occur. The interactions of the analyte with the serum proteinsmodify their spectral fluorescence properties, making it necessary to employ training sets ofsamples where the biological background is present, possibly causing analyte spectral changesfrom sample to sample. The predictive ability of the studied model has been compared with thatof parallel factor analysis (PARAFAC), as regards test samples containing different sera, and alsoother pharmaceuticals which could act as potential interferents.