Voltammetric Sensor for Sodium Nitroprusside Determination in Biological Fluids Using Films of Poly‐L‐Lysine

Sodium nitroprusside (NP), a commercial vasodilator, can be pre‐concentrated on vitreous carbon electrode modified by films of 97.5%: 2.5% poly‐L ‐lysine (PLL): glutaraldehyde (GA). This coating gives acceptable anion exchange properties whilst giving the required improvement of adhesion to the glassy carbon electrode surface. Linear response range and detection limit on nitroprusside in B‐R buffer pH 4.0, were 1×10^?6 to 2×10^?5 mol L^?1 and 1×10^?7 mol L^?1, respectively. The repeatability of the proposed sensor, evaluated in term of relative standard deviation, was measured as 4.1% for 10 experiments. The voltammetric sensor was directly applied to determination of nitroprusside in human plasma and urine samples and the average recovery for these samples was around 95–97% without any pre treatment.     

Genetic‐Algorithm‐Based Wavelength Selection in Multicomponent Spectrophotometric Determination by PLS: Application on Ascorbic Acid and Uric Acid Mixture

Genetic algorithm (GA) is a suitable method for selecting wavelengths for partial least squares (PLS) calibration of mixtures with almost identical spectra without loss of prediction capacity using the spectrophotometric method. In this study, the concentration model is based on absorption spectra in the range of 200‐320 nm for 25 different mixtures of ascorbic acid (AA) and uric acid (UA). The calibration curve was linear over the concentration range of 1‐15 and 2‐16 μg mL^?1 for ascorbic acid and uric acid, respectively. The root mean square deviation (RMSD) for ascorbic acid and uric acid with GA and without GA were 0.3071 and 0.3006, 0.3971 and 0.7063, respectively. The proposed method was successfully applied to the simultaneous determination of both analytes in human serum and urine samples.     

Octadecylsilane/Nylon‐6 composite as a thin‐film microextraction sorbent for the determination of bisphenol A in water samples

We report on the fabrication of a thin‐film composite for the extraction of bisphenol A from aqueous solutions. Nylon‐6, C₁₈ particles, and polyethylene glycol were used to prepare the thin film sorbent. Bisphenol A was used as a model compound to evaluate the extraction efficiency of the sorbent. High‐performance liquid chromatography with UV detection was used for the analysis. The extraction yield of the sorbent was compared with other thin films fabricated using different sorbents including nanoclay, LiChrolut EN, and multiwalled carbon nanotubes. Experimental parameters affecting the extraction performance (extraction time, desorption condition, sample stirring, and ionic strength of the sample solution) were investigated. The detection limit and the dynamic range of the method were 0.05 and 0.15–50 μg/L, respectively. The relative standard deviation of the method at two concentration levels (0.5 and 20 μg/L) was less than 7.2%. Finally, a polycarbonate baby bottle, river water, and wastewater samples were analyzed by the method.     

Construction and Performance Characterization of Ion‐Selective Electrodes for Potentiometric Determination of Paroxetine Hydrochloride in Pharmaceutical Preparations and Biological Fluids

Three types of ion‐selective electrodes: PVC membrane, modified carbon paste (CPE), and coated graphite electrodes (CGE) have been constructed for determining paroxetine hydrochloride (Prx). The electrodes are based on the ion pair of paroxetine with sodium tetraphenylborate (NaTPB) using dibutyl phthalate as plasticizing solvent. Fast, stable and potentiometric response was obtained over the concentration range of 1.1×10^?5–1×10^?2 mol L^?1 with low detection limit of 6.9×10^?6 mol L^?1 and slope of a 56.7±0.3mV decade^?1 for PVC membrane electrode, the concentration range of 2×10^?5–1×10^?2 mol L^?1 with low detection limit of 1.2×10^?5 mol L^?1 and slope of a 57.7±0.6 mV decade^?1 for CPE, and the concentration range of 2×10^?5–1×10^?2 mol L^?1 with low detection limit of 8.9×10^?6 mol L^?1 and slope of a 56.1±0.1 mV decade^?1 for CGE. The proposed electrodes display good selectivity for paroxetine with respect to a number of common inorganic and organic species. The electrodes were successfully applied to the potentiometric determination of paroxetine hydrochloride in its pure state, its pharmaceutical preparation, human urine and plasma.     

Sensitive Determination of 2‐Methoxyestradiol in Pharmaceutical Preparations and Biological Fluids by KMnO4‐Na2SO3 Chemiluminescence System

A simple and novel flow‐injection chemiluminescence (FI‐CL) method was established for the determination of 2‐Methoxyestradiol (2‐ME) in pharmaceutical preparations and biological fluids. The method was based on the significant enhancement of the CL from the KMnO₄‐Na₂SO₃ reaction by 2‐ME in acidic medium. Under optimized conditions, the CL intensity was correlated linearly with concentration of 2‐ME in the range of 5.0 × 10^?8‐5.0 × 10^?6 M (r = 0.9995). The detection limit (3σ) of 2‐ME was 7.5 × 10^?9 M and the relative standard deviation was 0.8% at 5.0 × 10^?7 M 2‐ME (n = 8). The proposed method was successfully applied for the flow‐injection CL determination of 2‐ME in pharmaceutical preparations and biological fluids with the recoveries from 92.4 to 106.8%. The possible CL reaction mechanism was also discussed briefly.     

Partial least‐squares discriminant analysis optimized by particle swarm optimization: application to 1H nuclear magnetic resonance analysis of lung cancer metabonomics

The complexity of metabolic profiles makes chemometric tools indispensable for extracting the most significant information. Partial least‐squares discriminant analysis (PLS‐DA) acts as one of the most effective strategies for data analysis in metabonomics. However, its actual efficacy in metabonomics is often weakened by the high similarity of metabolic profiles, which contain excessive variables. To rectify this situation, particle swarm optimization (PSO) was introduced to improve PLS‐DA by simultaneously selecting the optimal sample and variable subsets, the appropriate variable weights, and the best number of latent variables (SVWL) in PLS‐DA, forming a new algorithm named PSO‐SVWL‐PLSDA. Combined with ¹H nuclear magnetic resonance‐based metabonomics, PSO‐SVWL‐PLSDA was applied to recognize the patients with lung cancer from the healthy controls. PLS‐DA was also investigated as a comparison. Relatively to the recognition rates of 86% and 65%, which were yielded by PLS‐DA, respectively, for the training and test sets, those of 98.3% and 90% were offered by PSO‐SVWL‐PLSDA. Moreover, several most discriminative metabolites were identified by PSO‐SVWL‐PLSDA to aid the diagnosis of lung cancer, including lactate, glucose (α‐glucose and β‐glucose), threonine, valine, taurine, trimethylamine, glutamine, glycoprotein, proline, and lipid. Copyright © 2015 John Wiley & Sons, Ltd.     

Man‐Tailored Biomimetic Sensor of Molecularly Imprinted Materials for the Potentiometric Measurement of Rivastigmine in Tablets and Biological Fluids and Employing the Taguchi Optimization Methodology to Optimize the MIP‐Based Membranes

This work proposes a novel biomimetic sensor for the potentiometric transduction of rivastigmine based on molecularly imprinted polymer (MIP). Using the Taguchi method, this study analyzed the optimum conditions for preparing the MIP‐based membranes. The rank order of each controllable factor was also determined. MIP‐based membranes exhibited a Nernstian response (30.7±1.1 mV decade^?1) in a concentration range from 1.0×10^?5 to 1.0×10^?2 mol L^?1 with a LOD of 6.3×10^?6 mol L^?1. The sensor was successfully applied to the determination of rivastigmine concentrations in human serum, plasma, urine, rat brain and tablets.     

A useful approach for the differentiation of wines according to geographical origin based on global volatile patterns

In this study, the feasibility of solid‐phase extraction combined with gas chromatography and mass spectrometry in tandem with partial least squares discriminant analysis was evaluated as a useful strategy to differentiate wines according to geographical origin (Azores, Canary and Madeira Islands) and types (white, red and fortified wine) based on their global volatile patterns. For this purpose, 34 monovarietal wines from these three wine grape‐growing regions were investigated, combining the high throughput extraction efficiency of the solid‐phase extraction procedure with the separation and identification ability. The partial least squares discriminant analysis results suggested that Madeira wines could be clearly discriminated from Azores and Canary wines. Madeira wines are mainly characterized by 2‐ethylhexan‐1‐ol, 3,5,5‐trimethylhexan‐1‐ol, ethyl 2‐methylbutanoate, ethyl dl ‐2‐hydroxycaproate, decanoic acid, 3‐methylbutanoic acid, and (E)‐whiskey lactone, whereas 3‐ethoxypropan‐1‐ol, 1‐octen‐3‐ol, (Z)‐3‐hexenyl butanoate, 4‐(methylthio)‐1‐butanol, ethyl 3‐hydroxybutanoate, isoamyl lactate, 4‐methylphenol, γ‐octalactone and 4‐(methylthio)‐1‐butanol, are mainly associated with Azores and Canary wines. The data obtained in this study revealed that solid‐phase extraction combined with gas chromatography and quadrupole mass spectrometry data and partial least squares discriminant analysis provides a suitable tool to discriminate wines, both in terms of geographical origin as well as wine type and vintage.     

Quantitative determination and evaluation of Paris polyphylla var. yunnanensis with different harvesting times using UPLC‐UV‐MS and FT‐IR spectroscopy in combination with partial least squares discriminant analysis

A rapid method was developed and validated by ultra‐performance liquid chromatography–triple quadrupole mass spectroscopy with ultraviolet detection (UPLC‐UV‐MS) for simultaneous determination of paris saponin I, paris saponin II, paris saponin VI and paris saponin VII. Partial least squares discriminant analysis (PLS‐DA) based on UPLC and Fourier transform infrared (FT‐IR) spectroscopy was employed to evaluate Paris polyphylla var. yunnanensis (PPY) at different harvesting times. Quantitative determination implied that the various contents of bioactive compounds with different harvesting times may lead to different pharmacological effects; the average content of total saponins for PPY harvested at 8 years was higher than that from other samples. The PLS‐DA of FT‐IR spectra had a better performance than that of UPLC for discrimination of PPY from different harvesting times.     

Accurate discrimination of Gastrodia elata from different geographical origins using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis

Gastrodia elata from different geographical origins varies in quality and pharmacological activity. This study focused on the classification and identification of Gastrodia elata from six producing areas using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis. Before recognition analysis, a principal component analysis was applied to ascertain the discrimination possibility with high‐performance liquid chromatography fingerprints. And then, boosting partial least‐squares discriminant analysis and conventional partial least‐squares discriminant analysis were applied in this study. Experimental results indicated that the adaptive iteratively reweighted penalized least‐squares algorithm could eliminate the baseline drift of high‐performance liquid chromatography chromatograms effectively. And compared with partial least‐squares discriminant analysis, the total recognition rates using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis for the calibration sets and prediction sets were improved from 94 to 100% and 86 to 97%, respectively. In conclusion, high‐performance liquid chromatography combined with boosting partial least‐squares discriminant analysis, which has such advantages as effective, specific, accurate, non‐polluting, has an edge for discrimination of traditional Chinese medicine from different geographical origins. And the proposed methodology is a useful tool to classify and identify Gastrodia elata from different geographical origins.     

Boosting partial least‐squares discriminant analysis with application to near infrared spectroscopic tea variety discrimination

In the present study, boosting has been combined with partial least‐squares discriminant analysis (PLS‐DA) to develop a new pattern recognition method called boosting partial least‐squares discriminant analysis (BPLS‐DA). BPLS‐DA is implemented by firstly constructing a series of PLS‐DA models on the various weighted versions of the original calibration set and then combining the predictions from the constructed PLS‐DA models to obtain the integrative results by weighted majority vote. Coupled with near infrared (NIR) spectroscopy, BPLS‐DA has been applied to discriminate different kinds of tea varieties. As comparisons to BPLS‐DA, the conventional principal component analysis, linear discriminant analysis (LDA), and PLS‐DA have also been investigated. Experimental results have shown that the inter‐variety difference can be accurately and rapidly distinguished via NIR spectroscopy coupled with BPLS‐DA. Moreover, the introduction of boosting drastically enhances the performance of an individual PLS‐DA, and BPLS‐DA is a well‐performed pattern recognition technique superior to LDA. Copyright © 2012 John Wiley & Sons, Ltd.     

A new method of comparing 2D-PAGE maps based on the computation of Zernike moments and multivariate statistical tools

The aim of this work was to obtain the correct classification of a set of two-dimensional polyacrylamide gel electrophoresis map images using the Zernike moments as discriminant variables. For each 2D-PAGE image, the Zernike moments were computed up to a maximum p order of 100. Partial least squares discriminant analysis with variable selection, based on a backward elimination algorithm, was applied to the moments calculated in order to select those that provided the lowest error in cross-validation. The new method was tested on four datasets: (1) samples belonging to neuroblastoma; (2) samples of human lymphoma; (3) samples from pancreatic cancer cells (two cell lines of control and drug-treated cancer cells); (4) samples from colon cancer cells (total lysates and nuclei treated or untreated with a histone deacetylase inhibitor). The results demonstrate that the Zernike moments can be successfully applied for fast classification purposes. The final aim is to build models that can be used to achieve rapid diagnosis of these illnesses.     

Syntheses,Characterizations, and Crystal Structures of β‐Diketiminato Compounds of Pentafluorophenyl Group 12 Derivatives,HC{[C(Me)N(C6H3‐2, 6‐i‐Pr2)]2}MC6F5 (M = Zn,Cd)

The reactions of H₂C[C(Me)N(C₆H₃‐2, 6‐i‐Pr₂)]₂ ((DPP)₂NacNacH) and Zn(C₆F₅)₂ · 2 EtCN or Cd(C₆F₅)₂ · 2 MeCN in a molar ratio of approximately 1:1 selectively gave the derivatives (DPP)₂NacNacMC₆F₅ (M = Zn, Cd) in excellent yields. No reaction was observed between (DPP)₂NacNacH and Hg(C₆F₅)₂ under similar conditions. Reactions with Hg(C₆F₅)OCOMe yielded the products of dismutation, Hg(C₆F₅)₂ and Hg(OCOMe)₂. (DPP)₂NacNacZnC₆F₅ crystallises as a 1:1 adduct with THF with two independent molecules per unit cell (triclinic, P1 (no. 2)). The zinc atom is tetrahedrally surrounded by the chelating ligand, the pentafluorophenyl group and one THF molecule. A similar situation is found in the 1:1 adduct of (DPP)₂NacNacCdC₆F₅ and DMF (monoclinic, P2₁/n (no. 14)), while in the donor‐free compound (CDCl₃ and H₂O co‐crystallize) the cadmium atom is nearly ideally trigonal planar co‐ordinated (orthorhombic, Pbnm (no. 62)).     

Chemometrics‐enhanced laser‐induced thermal emission detection of PETN and other explosives on various substrates

Infrared emissions (IREs) of samples of pentaerythritol tetranitrate (PETN) deposited as contamination residues on various substrates were measured to generate models for the detection and discrimination of the important nitrate ester from the emissions of the substrates. Mid‐infrared emissions were generated by heating the samples remotely using laser‐induced thermal emission (LITE). Chemometrics multivariate analysis techniques such as principal component analysis (PCA), soft independent modeling by class analogy (SIMCA), partial least squares‐discriminant analysis (PLS‐DA), support vector machines (SVMs), and neural network (NN) were employed to generate the models for the classification and discrimination of PETN IREs from substrate thermal emissions. PCA exhibited less variability for the LITE spectra of PETN/substrates. SIMCA was able to predict only 44.7% of all samples, while SVM proved to be the most effective statistical analysis routine, with a discrimination performance of 95%. PLS‐DA and NN achieved prediction accuracies of 94% and 88%, respectively. High sensitivity and specificity values were achieved for five of the seven substrates investigated. Copyright © 2015 John Wiley & Sons, Ltd.     

High‐throughput kinetic analysis of acrylate and thiol‐ene photopolymerization using temperature and exposure time gradients

In this work, a high‐throughput technique for evaluating photopolymers is developed to enable simultaneous measurement of the effects of temperature in combination with exposure time. Temperature and exposure time gradients were produced in orthogonal directions on a single sample, and subsequently sampled using Fourier transform infrared (FTIR) spectroscopy. The technique developed here allows for photopolymerization kinetics to be analyzed rapidly over a large range of industrially relevant temperatures, giving insight into the role temperature and the polymer's glass transition temperature have in dictating the photopolymerization kinetics. In the 70/30 wt % hexyl acrylate and hexanediol diacrylate system, conversion in samples below the glass transition temperature (T_G) was 66 ± 2% after 12 s, significantly lower than the 93 ± 4% conversion at 12 s for samples polymerized at temperatures above the T_G. In addition, a thiol‐ene system was analyzed to study the effect of temperature on the ene homopolymerization in allyl ether monomers, which leads to incomplete thiol conversion in stoichiometrically balanced systems. At a 60% thiol conversion, the allyl ether‐ene conversion at all temperatures is 65 ± 3% irrespective of initial formulation temperature, indicative of the homopolymerization behavior being nearly independent of temperature. © 2008 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 46: 1502–1509, 2008     

New Validated Potentiometric Determination of Vasodilator Pentoxifylline in its Pharmaceutical Formulations and Biological Fluids

The construction and performance characteristics of pentoxifylline selective electrodes were developed. Two types of electrodes: plastic membrane I and coated wire II were constructed based on the incorporation of pentoxifylline with phosphotungstic acid (PTA). The influence of membrane composition, kind of plasticizer, pH of the test solution, soaking time, and foreign ions on the electrodes was investigated. The electrodes showed a Nernstain response with a mean calibration graph slope of 56.77 ± 0.19 and 55.76 ± 0.71 mV decade^‐1 at 25 °C for electrode I and II respectively, over pentoxifylline concentration range from 1.0 × 10^‐5‐1.0 × 10^‐2 and 9.0 × 10^‐6‐1.0 × 10^‐2 mol L^‐1, with detection limits 4.89 × 10^‐6 and 3.90 × 10^‐6 mol L^‐1 for electrode I and II, respectively. The pH range of the constructed electrodes was 4‐6. Interferences from common cations, alkaloids, sugars, amino acids and drug excipients were reported. The results obtained by the proposed electrodes were also applied successfully to the determination of the drug in its pharmaceutical preparations and biological fluids.     

High‐throughput determination of fungicides in grapes using thin‐film microextraction coupled with liquid chromatography–tandem mass spectrometry

A high‐throughput and environmentally friendly method based on 96‐well plate thin‐film microextraction was established to determine 14 fungicides in grapes and grape juice using liquid chromatography–tandem mass spectrometry. The thin‐film microextraction optimized method consisted of 60 min of extraction at pH 6.0 with the addition of sodium chloride (2–5%). Acetonitrile/water in the ratio of 8:2 was used for desorption analytes for 60 min. Evaluation of different extractive phases showed that polyacrylonitrile–polystyrene–divinylbenzene was the optimum coating. The linearity of the method was good in the range of 0.01–0.5 μg/mL for 14 fungicides with determination coefficients (R²) from 0.990 to 0.999, which indicated good linearity for both the grape juice and grape matrixes. The limit of detection was in the range of 0.002–0.01 μg/mL. The limit of quantitation was in the range of 0.01 mg/kg according to the minimum fortified level. The average absolute recoveries of the 14 fungicides ranged from 75.0 to 118.3%. The intraday relative standard deviation (n = 4) and interday relative standard deviation (n = 4) were 5.6–13.0% and 1.6–6.4%, respectively. This study showed that this method can be used for analyzing 96 samples in parallel, and the sample preparation time was approximately 2.0 min per sample. In addition, this approach offers a green and low‐cost sample pretreatment technique for future analyses.     

Metabolomics of meat exudate: Its potential to evaluate beef meat conservation and aging

In this study we analyzed the exudate of beef to evaluate its potential as non invasive sampling for nuclear magnetic resonance (NMR) based metabolomic analysis of meat samples. Exudate, as the natural juice from raw meat, is an easy to obtain matrix that it is usually collected in small amounts in commercial meat packages. Although meat exudate could provide complete and homogeneous metabolic information about the whole meat piece, this sample has been poorly studied. Exudates from 48 beef samples of different breeds, cattle and storage times have been studied by ¹H NMR spectroscopy. The liquid exudate spectra were compared with those obtained by High Resolution Magic Angle Spinning (HRMAS) of the original meat pieces. The close correlation found between both spectra (>95% of coincident peaks in both registers; Spearman correlation coefficient = 0.945) lead us to propose the exudate as an excellent alternative analytical matrix with a view to apply meat metabolomics. 60 metabolites could be identified through the analysis of mono and bidimensional exudate spectra, 23 of them for the first time in NMR meat studies. The application of chemometric tools to analyze exudate dataset has revealed significant metabolite variations associated with meat aging. Hence, NMR based metabolomics have made it possible both to classify meat samples according to their storage time through Principal Component Analysis (PCA), and to predict that storage time through Partial Least Squares (PLS) regression.     

A Biomimetic Potentiometric Sensor Using Molecularly Imprinted Polymer for the Cetirizine Assay in Tablets and Biological Fluids

Despite the increasing number of applications of molecularly imprinted polymers (MIPs) in analytical chemistry, the construction of a biomimetic potentiometric sensor remains still challenging. In this work, a biomimetic potentiometric sensor, based on a non‐covalent imprinted polymer was fabricated for the recognition and determination of cetirizine. The MIP was synthesized by precipitation polymerization, using cetirizine dihydrochloride as a template molecule, methacrylic acid (MAA) as a functional monomer and ethylene glycol dimethacrylate (EGDMA) as a cross linking agent. The sensor showed high selectivity and a sensitive response to the template in aqueous system. The MIP‐modified electrode exhibited Nernstian response (28.0±0.9 mV/decade) in a wide concentration range of 1.0×10^?6 to 1.0×10^?2 M with a lower detection limit of 7.0×10^?7 M. The electrode has response time of ca. 20 s, high performance, high sensitivity, and good long term stability (more than 5 months). The method was satisfactory and used to the cetirizine assay in tablets and biological fluids.