TY - JOUR T1 - Chemometrics-assisted simultaneous voltammetric determination of ascorbic acid, uric acid, dopamine and nitrite: application of non-bilinear voltammetric data for exploiting first-order advantage. AU - Gholivand,Mohammad-Bagher, AU - Jalalvand,Ali R, AU - Goicoechea,Hector C, AU - Skov,Thomas, Y1 - 2013/11/27/ PY - 2013/07/25/received PY - 2013/11/07/revised PY - 2013/11/08/accepted PY - 2014/1/10/entrez PY - 2014/1/10/pubmed PY - 2014/9/3/medline KW - AA KW - AsLSSR KW - Ascorbic acid KW - BP-ANN KW - COW KW - CPR KW - DP KW - DWT-ANN KW - Dopamine KW - GA KW - GCE KW - LOO-CV KW - LS-SVM KW - LVs KW - Linear and non-linear multivariate calibration models KW - MC KW - MLR KW - MVC KW - NT KW - Nitrite KW - OSC KW - PDC KW - PLS-1 KW - PLY-PLS KW - PRESS KW - PRM KW - Q(2) KW - RBF-PLS KW - RCR KW - REP KW - RMC KW - RMSECV KW - RMSEP KW - SGS KW - SLD KW - SPA KW - SPL-PLS KW - SWV KW - Savitsky–Golay smoothing KW - Simultaneous determination KW - UA KW - Uric acid KW - WD KW - WT-ANN KW - ascorbic acid KW - asymmetric least squares splines regression KW - back propagation-artificial neural network KW - continuum power regression KW - correlation optimized warping KW - discrete wavelet transform-artificial neural network KW - dopamine KW - genetic algorithm KW - glassy carbon electrode KW - latent variables KW - least squares-support vector machines KW - leave one out cross-validation KW - mean centering KW - multiple linear regression KW - multivariate calibration KW - nitrite KW - orthogonal signal correction KW - partial least squares-1 KW - partial robust M-regression KW - percentage of data contamination KW - polynomial-partial least squares KW - prediction residual error sum of squares KW - rPCA KW - radial basis function-partial least squares KW - relative error of prediction KW - robust continuum regression KW - robust median centering KW - robust principal component analysis, MLP, multilayer perceptron KW - root mean square errors of prediction KW - root mean squared errors of cross-validation KW - simplex lattice design KW - spline-partial least squares KW - square wave voltammetry KW - successive projections algorithm KW - the square correlation coefficient of cross-validation KW - uric acid KW - wavelet denoising KW - wavelet transform-artificial neural network SP - 553 EP - 63 JF - Talanta JO - Talanta VL - 119 N2 - For the first time, several multivariate calibration (MVC) models including partial least squares-1 (PLS-1), continuum power regression (CPR), multiple linear regression-successive projections algorithm (MLR-SPA), robust continuum regression (RCR), partial robust M-regression (PRM), polynomial-PLS (PLY-PLS), spline-PLS (SPL-PLS), radial basis function-PLS (RBF-PLS), least squares-support vector machines (LS-SVM), wavelet transform-artificial neural network (WT-ANN), discrete wavelet transform-ANN (DWT-ANN), and back propagation-ANN (BP-ANN) have been constructed on the basis of non-bilinear first order square wave voltammetric (SWV) data for the simultaneous determination of ascorbic acid (AA), uric acid (UA), dopamine (DP) and nitrite (NT) at a glassy carbon electrode (GCE) to identify which technique offers the best predictions. The compositions of the calibration mixtures were selected according to a simplex lattice design (SLD) and validated with an external set of analytes' mixtures. An asymmetric least squares splines regression (AsLSSR) algorithm was applied for correcting the baselines. A correlation optimized warping (COW) algorithm was used to data alignment and lack of bilinearity was tackled by potential shift correction. The effects of several pre-processing techniques such as genetic algorithm (GA), orthogonal signal correction (OSC), mean centering (MC), robust median centering (RMC), wavelet denoising (WD), and Savitsky-Golay smoothing (SGS) on the predictive ability of the mentioned MVC models were examined. The best preprocessing technique was found for each model. According to the results obtained, the RBF-PLS was recommended to simultaneously assay the concentrations of AA, UA, DP and NT in human serum samples. SN - 1873-3573 UR - https://www.unboundmedicine.com/medline/citation/24401455/Chemometrics_assisted_simultaneous_voltammetric_determination_of_ascorbic_acid_uric_acid_dopamine_and_nitrite:_application_of_non_bilinear_voltammetric_data_for_exploiting_first_order_advantage_ DB - PRIME DP - Unbound Medicine ER -