Achieving second order advantage with multi-way partial least squares and residual bi-linearization with total synchronous fluorescence data of monohydroxy-polycyclic aromatic hydrocarbons in urine samples.

An attractive approach to handle matrix interference in samples of unknown composition is to generate second- or higher-order data formats and process them with appropriate chemometric algorithms. Several strategies exist to generate high-order data in fluorescence spectroscopy, including wavelength time matrices, excitation-emission matrices and time-resolved excitation-emission matrices. This article tackles a different aspect of generating high-order fluorescence data as it focuses on total synchronous fluorescence spectroscopy. This approach refers to recording synchronous fluorescence spectra at various wavelength offsets. Analogous to the concept of an excitation-emission data format, total synchronous data arrays fit into the category of second-order data. The main difference between them is the non-bilinear behavior of synchronous fluorescence data. Synchronous spectral profiles change with the wavelength offset used for sample excitation. The work presented here reports the first application of total synchronous fluorescence spectroscopy to the analysis of monohydroxy-polycyclic aromatic hydrocarbons in urine samples of unknown composition. Matrix interference is appropriately handled by processing the data either with unfolded-partial least squares and multi-way partial least squares, both followed by residual bi-linearization.

[1]  Jiamo Fu,et al.  Quantification of several monohydroxylated metabolites of polycyclic aromatic hydrocarbons in urine by high-performance liquid chromatography with fluorescence detection , 2005, Analytical and bioanalytical chemistry.

[2]  Héctor C. Goicoechea,et al.  Total synchronous fluorescence spectroscopic data modeled with first- and second-order algorithms for the determination of doxorubicin in human plasma , 2013, Analytical and Bioanalytical Chemistry.

[3]  Franco Allegrini,et al.  Analytical figures of merit for partial least-squares coupled to residual multilinearization. , 2012, Analytical chemistry.

[4]  D. Hood,et al.  Bioavailability and Risk Assessment of Orally Ingested Polycyclic Aromatic Hydrocarbons , 2004, International journal of toxicology.

[5]  P T Henderson,et al.  1-Hydroxypyrene in human urine after exposure to coal tar and a coal tar derived product , 1985, International archives of occupational and environmental health.

[6]  A. Campiglia,et al.  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. , 2012, Analytica chimica acta.

[7]  Ján Mikulás Lisý,et al.  Multiple straight-line least-squares analysis with uncertainties in all variables , 1990, Comput. Chem..

[8]  D. Patterson,et al.  Determination of selected monohydroxy metabolites of 2-, 3- and 4-ring polycyclic aromatic hydrocarbons in urine by solid-phase microextraction and isotope dilution gas chromatography-mass spectrometry. , 2002, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[9]  Andres D Campiglia,et al.  Four-way data coupled to parallel factor model applied to environmental analysis: determination of 2,3,7,8-tetrachloro-dibenzo-para-dioxin in highly contaminated waters by solid-liquid extraction laser-excited time-resolved Shpol'skii spectroscopy. , 2005, Analytical chemistry.

[10]  Alejandro C. Olivieri,et al.  A combined artificial neural network/residual bilinearization approach for obtaining the second‐order advantage from three‐way non‐linear data , 2005 .

[11]  P. Garrigues,et al.  Detection of 1-hydroxypyrene in urine by direct fluorometric analysis on a solid sorbing phase. Validation and application of the method to biological monitoring of PAH-exposed persons , 2003, Analytical and bioanalytical chemistry.

[12]  M. Bergamini,et al.  Voltammetric sensor for amoxicillin determination in human urine using polyglutamic acid/glutaraldehyde film , 2008 .

[13]  Ronei J. Poppi,et al.  Second- and third-order multivariate calibration: data, algorithms and applications , 2007 .

[14]  Ralf Otterpohl,et al.  Comparison of analytical and theoretical pharmaceutical concentrations in human urine in Germany. , 2008, Water research.

[15]  S. Wold,et al.  Multi‐way principal components‐and PLS‐analysis , 1987 .

[16]  J. Miller,et al.  Statistics and chemometrics for analytical chemistry , 2005 .

[17]  R. Anzion,et al.  Biological monitoring of polycyclic aromatic hydrocarbons. Metabolites in urine. , 1986, Scandinavian journal of work, environment & health.

[18]  K. Peltonen,et al.  Urinary hydroxy-metabolites of naphthalene, phenanthrene and pyrene as markers of exposure to diesel exhaust , 2004, International archives of occupational and environmental health.

[19]  Hai-Long Wu,et al.  MVC2: A MATLAB graphical interface toolbox for second-order multivariate calibration , 2009 .

[20]  N. Rothman,et al.  Detection of metabolites of polycyclic aromatic hydrocarbons in human urine. , 1993, Carcinogenesis.

[21]  M. A. Herrador,et al.  Intra-laboratory testing of method accuracy from recovery assays. , 1999, Talanta.

[22]  G. M. Escandar,et al.  First- and second-order multivariate calibration applied to biological samples: determination of anti-inflammatories in serum and urine , 2002, Analytical and bioanalytical chemistry.

[23]  Yong-Sheng Wang,et al.  Synchronous fluorescence determination of urinary 1-hydroxypyrene, beta-naphthol and 9-hydroxyphenanthrene based on the sensitizing effect of beta-cyclodextrin. , 2009, Analytica chimica acta.

[24]  Andres D Campiglia,et al.  Four-way modeling of 4.2 K time-resolved excitation emission fluorescence data for the quantitation of polycyclic aromatic hydrocarbons in soil samples. , 2012, Talanta.

[25]  Keshav Kumar,et al.  Simultaneous quantification of dilute aqueous solutions of certain polycyclic aromatic hydrocarbons (PAHs) with significant fluorescent spectral overlap using total synchronous fluorescence spectroscopy (TSFS) and N-PLS, unfolded-PLS and MCR-ALS analysis , 2011 .

[26]  E. V. Thomas,et al.  Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information , 1988 .

[27]  N. M. Faber,et al.  Uncertainty estimation and figures of merit for multivariate calibration (IUPAC Technical Report) , 2006 .

[28]  N. Rothman,et al.  Polycyclic Aromatic Hydrocarbon Biomarkers of Internal Exposure in U.S. Army Soldiers Serving in Kuwait in 1991 , 1999 .

[29]  Andres D Campiglia,et al.  Direct quantification of monohydroxy-polycyclic aromatic hydrocarbons in synthetic urine samples via solid-phase extraction-room-temperature fluorescence excitation-emission matrix spectroscopy. , 2008, Analytical biochemistry.

[30]  A. Helander,et al.  Unreliable alcohol testing in a shipping safety programme. , 2009, Forensic science international.

[31]  Roger Gibson,et al.  Urinary biomarkers of exposure to jet fuel (JP-8). , 2003, Environmental health perspectives.

[32]  F. X. Rius,et al.  Univariate regression models with errors in both axes , 1995 .

[33]  T. Vo‐Dinh,et al.  Multicomponent analysis by synchronous luminescence spectrometry. , 1978, Analytical chemistry.

[34]  B. Kowalski,et al.  Theory of analytical chemistry , 1994 .

[35]  M. M. Krahn,et al.  Analytical methods for determining metabolites of polycyclic aromatic hydrocarbon (PAH) pollutants in fish bile: A review. , 2010, Environmental toxicology and pharmacology.

[36]  Lovisa C. Romanoff,et al.  Automated solid-phase extraction method for measuring urinary polycyclic aromatic hydrocarbon metabolites in human biomonitoring using isotope-dilution gas chromatography high-resolution mass spectrometry. , 2006, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.