University of North Florida
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Stuart Chalk, Ph.D.
Department of Chemistry
University of North Florida
Phone: 1-904-620-1938
Fax: 1-904-620-3535
Email: schalk@unf.edu
Website: @unf

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Javier Saurina

Abbrev:
Saurina, J.
Other Names:
Address:
Department of Analytical Chemistry, University of Barcelona, Diagonal 647, 08028 Barcelona, Spain
Phone:
+34-934034445
Fax:
+34-934021233

Citations 9

"Continuous Flow Derivatization System Coupled To Capillary Electrophoresis For The Determination Of Amino Acids"
J. Chromatogr. A 2002 Volume 976, Issue 1-2 Pages 55-64
Rosa M. Latorre, Javier Saurina and Santiago Hernández-Cassou

Abstract: A derivatization system coupled to capillary electrophoresis for the determination of amino acids using 1,2-naphthoquinone-4-sulfonate as a labeling agent is described. In this system, amino acids are derivatized on-line in a three-channel flow manifold for sample, reagent and buffer solutions. The reaction takes place in a PTFE coil heated at 80°C. The resulting solution, which contains the amino acid derivatives, is introduced into the electrophoretic system by means of an appropriate interface. Subsequently, amino acid derivatives are separated at 25 kV using a 40 mM sodium tetraborate aqueous solution with 30% (v/v) isopropanol solution as a running buffer. The electropherograms are monitored spectrophotometrically at 230 nm. The method has been applied to the determination of amino acids in feed samples and pharmaceutical preparations. A good concordance of the predicted values with those given by a standard amino acid analyzer is shown.

"Potentiometric Sensor Array For The Determination Of Lysine In Feed Samples Using Multivariate Calibration Methods"
Fresenius J. Anal. Chem. 2001 Volume 371, Issue 7 Pages 1001-1008
N. García-Villar, J. Saurina, S. Hernández-Cassou

Abstract: A potentiometric sensor array has been developed for the determination of lysine in feed samples. The sensor array consists of a lysine biosensor and seven ion-selective electrodes for NH4+, K+, Na+, Ca2+, Mg2+, Li+, and H+, all based on all-solid-state technology. The potentiometric lysine biosensor comprises a lysine oxidase membrane assembled on an NH4+ electrode. Because the selectivity of the lysine biosensor towards other cation species is not sufficient. there is severe interference with the potentiometric response. This poor selectivity can be circumvented mathematically by analysis of the richer information contained in the multi-sensor data. The sensor array takes advantage of the cross-selectivity of lysine for each electrode, which differs from the other species and quantification of lysine in complex feed sample extracts is accomplished with multivariate calibration methods, such as partial least-squares regression. The results obtained are in a reasonable agreement with those given by the standard method for amino acid analysis.

"PH-Gradient Spectrophotometric Data Files From Flow Injection And Continuous Flow Systems For Two- And Three-way Data Analysis"
Chemom. Intell. Lab. Syst. 2000 Volume 50, Issue 2 Pages 263-271
Javier Saurina, Santiago Hernández-Cassou, Anna Izquierdo-Ridorsa and Romà Tauler

Abstract: This paper describes a contribution to Chemometrics and Intelligent Laboratory Systems Elseviers data base of files. Mixtures of nucleosides and a pharmaceutical preparation composed of cytosine and inosine-5-monophosphate are analyzed using three different pH-gradient spectrophotometric flow injection and continuous flow systems. Results for one of the flow injection systems and for the continuous-flow system are reported for the first time in this paper. Resolution and quantitation of the constituents in the mixtures are given using a multivariate curve resolution method based on a constrained alternating least squares optimization.

"Determination Of Lysine In Pharmaceutical Samples Containing Endogenous Ammonium Ions By Using A Lysine Oxidase Biosensor Based On An All-solid-state Potentiometric Ammonium Electrode"
Biosens. Bioelectron. 1999 Volume 14, Issue 1 Pages 67-75
Javier Saurina, Santiago Hernández-Cassou, Salvador Alegret and Esteve Fàbregas

Abstract: A new potentiometric method is proposed to determine lysine in pharmaceutical samples. This method is based on a lysine biosensor consisting of a chemically immobilized lysine oxidase membrane attached to an all-solid-state ammonium electrode. Lysine is degraded in the sensor to release ammonium, which is detected by means of the ammonium electrode. The presence of endogenous ammonium in the samples interferes with these determinations, since the response measured corresponds to the sum of the ammonium generated enzymatically and that present in the sample. This is a general drawback for all biosensors based on the detection of ammonium. Study of samples containing both lysine and ammonium showed that concentration ranges exist in which a near-logarithmic relationship between potentials measured and lysine concentrations is found. Therefore, within these ranges, lysine can be determined by using the standard addition method, with the subsequent data treatment involving an iterative linearization procedure. Results obtained with the proposed potentiometric method are consistent with those given by the standard method for amino acid analysis.
Reactor

"Fast Determination Of PKa Values Of Reverse Transcriptase Inhibitor Drugs For AIDS Treatment By Using PH-gradient Flow-injection Analysis And Multivariate Curve Resolution"
Anal. Chim. Acta 2005 Volume 554, Issue 1-2 Pages 177-183
Antonio Checa, Víctor González Soto, Santiago Hernández-Cassou and Javier Saurina

Abstract: This paper aims at the characterization of acid-base properties of nucleoside analogs using a pH-gradient flow injection -diode array detector (FI-DAD) system and further data analysis with multivariate curve resolution. Drugs selected comprise nucleoside reverse transcriptase inhibitors (NRTIs) extensively used in AIDS treatment, including zidovudine (AZT), didanosine (ddl), stavudine (d4T) and zalcitabine (ddC). The FI system consists of a two-channel manifold in which the sample injection into an acid carrier is responsible of the generation of a pH gradient. A first step is focused on an accurate calibration of the pH-gradient shape inside the FI peak using nucleoside analogs of known pKa values as standard compounds. The pH gradient in the FI peak is estimated from the concentration profiles of standard compounds. In a second step, the pH-gradient profile is exploited for a rapid estimation of unknown pKa values of test drugs. Various approaches for calculating pKa values are evaluated using the peak front or peak tail gradient ranges. As a result, overall errors in pKa estimations are lower than 2.5%. © 2005 Elsevier B.V. All rights reserved.

"Flow Injection Differential Potentiometric Determination Of Lysine By Using A Lysine Biosensor"
Anal. Chim. Acta 2003 Volume 477, Issue 2 Pages 315-324
N. García-Villar, J. Saurina and S. Hernández-Cassou

Abstract: This paper describes a method for the determination of lysine based on a flow injection (FI) differential potentiometry system. The flow injection manifold is composed of a support electrolyte solution channel and a water channel acting as a carrier into which the sample solution is injected. The lysine biosensor was consisted of lysine oxidase chemically immobilized on a nylon membrane and attached to an all-solid-state ammonium electrode. A circular ammonium electrode was used as a reference. Hence, the possible interference of endogenous ammonium can be partly corrected by differential potentiometry. In order to increase the sensitivity of the response, the reaction was kinetically developed following a stopped-flow method. As a result, the sensitivity increased from 20 to 40 mV per decade when comparing the FI and the stopped-flow values. Furthermore, the peak-to-peak stopped-flow signals generated can be used as a more selective analytical response for lysine. The quantification of lysine in mixture samples containing small amounts of ammonium can be achieved with an acceptable accuracy, with prediction errors lower than 4%. However, when the ammonium concentration exceeded the lysine concentration, multivariate calibration with non-linear partial least squares (PLS) regression was needed to improve the lysine quantification, with an overall prediction error around 10%.

"Spectrophotometric Determination Of PK(a) Values Based On A PH Gradient Flow Injection System"
Anal. Chim. Acta 2000 Volume 408, Issue 1-2 Pages 135-143
Javier Saurina, Santiago Hernández-Cassou, Romà Tauler and Anna Izquierdo-Ridorsa

Abstract: This paper describes a pH gradient flow injection method for fast spectrophotometric determination of acidity constants. The flow injection system consists of a three-channel manifold in which the sample bolus is injected between acidic and basic zones. Therefore, the front of the flow injection peak is made acidic while the tail of the peak is alkalinized, and consequently, a pH gradient from acidic to basic medium is generated along the flow injection peak in an easy and reproducible way. The whole procedure is composed of two steps; first, the in situ determination of the pH gradient profile by using a standard compound with a known pK(a) value, and second, this pH gradient profile is used to calculate the pK(a) of an unknown compound. An alternating least squares multivariate curve resolution method is used in both steps to resolve the concentration profiles of the acidic and basic species in the standard and in the unknown samples which are the basis of the calculations. The method is tested using several nucleic acid components. An additional advantage of the proposed method is that no pH experimental measurement is needed for the fast determination of pK(a) values. Results obtained using the proposed procedure are consistent with those listed in the literature.
Acidity, constants Nucleic acids Water Spectrophotometry pH gradient Titrations Multivariate calibration

"Flow-injection Determination Of Amine Contaminants In Cyclamate Samples Based On Temperature For Controlling Selectivity"
Analyst 2004 Volume 129, Issue 5 Pages 468-474
avier Saurina, Leah Hlabangana, Daniel García-Milla and Santiago Hernández-Cassou

Abstract: This paper describes a flow-injection (FI) method for the simultaneous determination of aniline and cyclohexylamine impurities in cyclamate products. The method consists of the derivatization of amines with 1,2-naphthoquinone-4- sulfonate under selective and non-selective conditions. Here, the selectivity is achieved by working at 20°C, at which only aniline reacts, whilst higher temperatures (80°C) lead to a non-selective reaction of the two analytes. The FI manifold is composed of two flow cells for the spectrophotometric detection of derivatives at 480 nm. Experimental conditions have been optimized by factorial design and multicriteria making approach. Quantification is accomplished by differential analysis of the analyte contributions in the double peaks generated when the sample reaches cell 1 and cell 2. Results obtained with the proposed method are in satisfactory agreement with those provided by the standard method for the analysis of cyclamate samples.

"A Comparison Of Chemometric Methods For The Flow Injection Simultaneous Spectrophotometric Determination Of Aniline And Cyclohexylamine"
Analyst 1999 Volume 124, Issue 5 Pages 745-749
Javier Saurina and Santiago Hernández-Cassou

Abstract: A flow injection spectrophotometric method for the simultaneous determination of aniline and cyclohexylamine using multivariate calibration methods is proposed. The method is based on the reaction of these amines with 1,2-naphthoquinone-4-sulfonate, yielding spectrophotometrically active derivatives. The data analyzed with multivariate calibration methods consisted of the spectra registered in the range 290-590 nm at the maximum of the flow injection peak. Although the spectrum of each derivative was characteristic, overlapping occurred and no selective wavelengths were found. The predictive abilities of principal component regression and partial least-squares regression (PLS), non-linear PLS, locally weighted regression(LWR) and artificial neural networks were examined for the determination of aniline and cyclohexylamine in sample mixtures. The accuracy for cyclohexylamine and aniline quantifications in unknown mixtures was optimum with LWR, providing overall prediction errors of 3.4 and 5.6%, respectively.