Ariana P. Pagani

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

The 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 desirable properties, the technique can handle incomplete calibration information, i.e., when only certain analyte concentrations are known in the training set. It can also cope with analyte spectral changes from sample to sample, due to its latent variable structure. In this work, U-PLS/RBL has been successfully applied to experimental fluorescence excitation-emission matrix data aimed at the quantitation of analytes in complex samples: these were the antibiotic tetracycline and the anti-inflammatory salicylate, in both cases in the presence of human serum, where significant analyte-background interactions occur. The interactions of the analyte with the serum proteins modify their spectral fluorescence properties, making it necessary to employ training sets of samples where the biological background is present, possibly causing analyte spectral changes from sample to sample. The predictive ability of the studied model has been compared with that of parallel factor analysis (PARAFAC), as regards test samples containing different sera, and also other pharmaceuticals which could act as potential interferents.

Second-order advantage from kinetic-spectroscopic data matrices in the presence of extreme spectral overlapping: A multivariate curve resolution—Alternating least-squares approach

Multivariate curve resolution coupled to alternating least-squares (MCR-ALS) has been employed to model kinetic-spectroscopic second-order data, with focus on the achievement of the important second-order advantage, under conditions of extreme spectral overlapping among sample components. A series of simulated examples shows that MCR-ALS can conveniently handle the studied analytical problem unlike other second-order multivariate calibration algorithms, provided matrix augmentation is implemented in the spectral mode instead of in the usual kinetic mode. The approach has also been applied to three experimental examples, which involve the determination of: (1) the antiparkinsonian carbidopa (analyte) in the presence of levodopa as a potential interferent, both reacting with cerium (IV) to produce the fluorescent species cerium (III) with different kinetics; (2) Fe(II) (analyte) in the presence of the interferent Zn(II), both catalyzing the oxidation of methyl orange with potassium bromate; and (3) tartrazine (analyte) in the presence of the interferent brilliant blue, both oxidized with potassium bromate, with the interferent leading to a product with an absorption spectrum very similar to tartrazine. The results indicate good analytical performance towards the analytes, despite the intense spectral overlapping and the presence of unexpected constituents in the test samples.

Simultaneous Multivariate Spectrophotometric Analysis of Binary and Ternary Mixtures of Sulfamethoxazole, Trimethoprim and Phenazopyridine in Tablets

ABSTRACT The use of multivariate spectrophotometric calibration is reported for the analysis of tablets containing the antibiotics sulfamethoxazole and trimethoprim, and a combination of the former two drugs with the analgesic phenazopyridine. The resolution of these mixtures has been accomplished without prior separation, derivatisation or use of nonaqueous solvents, with the aid of partial least-squares (PLS-1) regression analysis of electronic absorption spectral data. The analytes have been simultaneously determined with high accuracy and precision, and with no interference from tablet excipients.

Simultaneous multivariate spectrophotometric analysis of ear drops containing a ternary mixture of antipyrine, sulfathiazole, and rivanol

The use of multivariate calibration is reported for the analysis of ear drops, which contain the anti-inflammatory antipyrine, the antibiotic sulfathiazole and the analgesic rivanol. The components are present in a 10 : 10 : 1 ratio, and are all dissolved in glycerin. The resolution of this mixture has been accomplished without prior separation or derivatization, with the aid of partial least-squares (PLS-1) regression analysis of electronic absorption spectral data. A sensor selection method based on the minimization of the cross-validation square error for each component was performed in order to optimize the method. The analytes have been simultaneously determined with accuracy and precision, even for the minor component rivanol which is present in a 1 : 10 ratio with respect to both sulfathiazole and antypirine. Estimated limits of detection are: antypirine, 0.3 mg L−1, sulfathiazole, 0.1 mg L−1 and rivanol, 0.1 mg L−1.

Determination of the minor component bromhexine in cotrimoxazole-containing tablets by absorption spectrophotometry and partial least-squares (PLS-1) multivariate calibration.

The mucolitic bromhexine [N-(2-amino-3,5-dibromobenzyl)-N-methylcyclohexylamine] has been determined in cotrimoxazole-containing tablets by partial least-squares (PLS-1) multivariate of spectrophotometric calibration data in the spectral range 310-350 nm. In the studied commercial tablets, cotrimoxazole is present in large excess (ca. 100:1 in weight) with respect to bromhexine, and a high degree of spectral overlapping exists among bromhexine and cotrimoxazole components. However, the obtained recoveries are reasonably good with the presently discussed technique.

Second-order multivariate models for the processing of standard-addition synchronous fluorescence-pH data. Application to the analysis of salicylic acid and its major metabolite in human urine.

In the present work, we describe the determination of salicylic acid and its major metabolite, salicyluric acid, in spiked human urine samples, using synchronous fluorescence spectra measured in a flow-injection system with a double pH gradient. Because the fluorescent urine background constitutes a potentially interfering signal, it becomes necessary to achieve the second-order advantage. Moreover, due to significant changes in the signal of the analytes in the presence of the urine matrix, mainly for salicyluric acid, standard addition was required in order to obtain appropriate quantifications. Several second-order multivariate calibration models were evaluated for this purpose: PARAFAC and MCR-ALS in two different modes, and PLS/RBL.

Analytical approach for the simultaneous determination of quinolones in edible animal products. Modeling pH–modulated fluorescence excitation–emission matrices four–way arrays

This paper describes a novel procedure for the simultaneous determination of four quinolones pipemidic acid, enoxacin, marbofloxacin and enrofloxacin in different edible animal tissues. It is based on third-order data excitation-emission fluorescence matrices modulated by pH gradient, generated in situ through the hydrolysis of glucono delta-lactone. To overcome the strongly overlapped spectra within the analytes, and also with the highly complex tissue matrix, we have used the multivariate calibration procedure unfolded partial least-squares coupled to residual trilinearization (U-PLS/RTL). The method has been validated by application to bovine kidney, chicken and porcine meat samples, fortified at concentration levels between 70 and 600 µg kg-1 corresponding to values near the maximum residue level (MRL) regulated by the European Community. Good recoveries were obtained for all analytes, with values between 80% and 113%, depending on the quinolone and the matrix.