Optimization and characterization of a biosensor assembly for detection of <Emphasis Type="Italic">Salmonella</Emphasis> Typhimurium

The performance of biosensors depends directly on the strategies adopted during their development. In this paper, a fast and sensitive biosensor for Salmonella Typhimurium detection was assembled by using optimization studies in separate stages. The pre-treatment assays, biomolecular immobilization (primary antibody and protein A concentrations), and analytical response (hydroquinone and hydrogen peroxide concentrations) were optimized via voltammetric methods. In the biosensor assembly, a gold surface was modified via the self-assembled monolayer technique (SAM) using cysteamine thiol and protein A for immobilization of anti-Salmonella antibody. The analytical response of the biosensor was obtained through the use of a secondary antibody labeled with a peroxidase enzyme, and the signal was evaluated by applying the chronoamperometry technique. The biosensor was characterized by infrared spectroscopy and cyclic voltammetry. Optimization of protein A and primary antibody concentrations enabled higher analytical signals of 7.5 and 75 mg mL^?1, respectively, to be achieved. The hydroquinone and H₂O₂ concentrations selected were 3 and 300 mM, respectively. The biosensor developed attained a very low detection limit of 10 CFU mL^?1 and a fast response with a final detection time of 125 min. These results indicate that this biosensor is very promising for the food safety and emergency response applications.     

Computational chemistry approach for the early detection of drug-induced idiosyncratic liver toxicity

Idiosyncratic drug toxicity (IDT), considered as a toxic host-dependent event, with an apparent lack of dose response relationship, is usually not predictable from early phases of clinical trials, representing a particularly confounding complication in drug development. Albeit a rare event (usually <1/5000), IDT is often life threatening and is one of the major reasons new drugs never reach the market or are withdrawn post marketing. Computational methodologies, like the computer-based approach proposed in the present study, can play an important role in addressing IDT in early drug discovery. We report for the first time a systematic evaluation of classification models to predict idiosyncratic hepatotoxicity based on linear discriminant analysis (LDA), artificial neural networks (ANN), and machine learning algorithms (OneR) in conjunction with a 3D molecular structure representation and feature selection methods. These modeling techniques (LDA, feature selection to prevent over-fitting and multicollinearity, ANN to capture nonlinear relationships in the data, as well as the simple OneR classifier) were found to produce QSTR models with satisfactory internal cross-validation statistics and predictivity on an external subset of chemicals. More specifically, the models reached values of accuracy/sensitivity/specificity over 84%/78%/90%, respectively in the training series along with predictivity values ranging from ca. 78 to 86% of correctly classified drugs. An LDA-based desirability analysis was carried out in order to select the levels of the predictor variables needed to trigger the more desirable drug, i.e. the drug with lower potential for idiosyncratic hepatotoxicity. Finally, two external test sets were used to evaluate the ability of the models in discriminating toxic from nontoxic structurally and pharmacologically related drugs and the ability of the best model (LDA) in detecting potential idiosyncratic hepatotoxic drugs, respectively. The computational approach proposed here can be considered as a useful tool in early IDT prognosis.     

Selective synthesis of 4-thiomethyl-1,3-dioxolan-2-ones under microwave irradiation using an environmentally benign KF/Al2O3/PEG-400 system

Research on Chemical Intermediates - We describe a simple and rapid method for selective synthesis of 4-thiomethyl-1,3-dioxolan-2-ones promoted by KF/Al2O3 using PEG-400 as solvent under microwave...     

Mixture-mixture design for the fingerprint optimization of chromatographic mobile phases and extraction solutions for Camellia sinensis

A composite simplex centroid-simplex centroid mixture design is proposed for simultaneously optimizing two mixture systems. The complementary model is formed by multiplying special cubic models for the two systems. The design was applied to the simultaneous optimization of both mobile phase chromatographic mixtures and extraction mixtures for the Camellia sinensis Chinese tea plant. The extraction mixtures investigated contained varying proportions of ethyl acetate, ethanol and dichloromethane while the mobile phase was made up of varying proportions of methanol, acetonitrile and a methanol-acetonitrile-water (MAW) 15%:15%:70% mixture. The experiments were block randomized corresponding to a split-plot error structure to minimize laboratory work and reduce environmental impact. Coefficients of an initial saturated model were obtained using Scheffe-type equations. A cumulative probability graph was used to determine an approximate reduced model. The split-plot error structure was then introduced into the reduced model by applying generalized least square equations with variance components calculated using the restricted maximum likelihood approach. A model was developed to calculate the number of peaks observed with the chromatographic detector at 210 nm. A 20-term model contained essentially all the statistical information of the initial model and had a root mean square calibration error of 1.38. The model was used to predict the number of peaks eluted in chromatograms obtained from extraction solutions that correspond to axial points of the simplex centroid design. The significant model coefficients are interpreted in terms of interacting linear, quadratic and cubic effects of the mobile phase and extraction solution components.     

Spectroscopic and electrochemical studies of cocaine–opioid interactions

The drugs of abuse cocaine (C), heroin (H), and morphine (M) have been studied to enable understanding of the occurrence of cocaine–opioid interactions at a molecular level. Electrochemical, Raman, and NMR studies of the free drugs and their mixtures were used to study drug–drug interactions. The results were analyzed using data obtained from quantum-mechanical calculations. For the cocaine–morphine mixture (C–MH), formation of a binary complex was detected; this involved the 3-phenolic group and the heterocyclic oxygen of morphine and the carbonyl oxygen and the methyl protons of cocaine’s methyl ester group. NMR studies conducted simultaneously also revealed C–MH binding geometry consistent with theoretical predictions and with electrochemical and vibrational spectroscopy results. These results provide evidence for the occurrence of a cocaine–morphine interaction, both in the solid state and in solution, particularly for the hydrochloride form. A slight interaction, in solution, was also detected by NMR for the cocaine–heroin mixture. Figure "Schematic representation of the proposed model for cocaine:morphine salt interaction"     

Progress in direct solid sampling analysis using line source and high-resolution continuum source electrothermal atomic absorption spectrometry

The literature about direct solid sample analysis of the past 10–15 years using electrothermal atomic absorption spectrometry has been reviewed. It was found that in the vast majority of publications aqueous standards were reported as having been used for calibration after careful program optimization. This means the frequently expressed claim that certified reference materials with a matrix composition and analyte content close to that of the sample have to be used for calibration in solid sample analysis is not confirmed in the more recent literature. There are obviously limitations, and there are examples in the literature where even calibration with certified reference materials did not lead to accurate results. In these cases the problem is typically associated with spectral interferences that cannot be corrected properly by the systems available for conventional line source atomic absorption spectrometry, including Zeeman-effect background correction. Using high-resolution continuum source atomic absorption spectrometry, spectral interferences become visible owing to the display of the spectral environment at both sides of the analytical line at high resolution, which makes program optimization straightforward. Any spectrally continuous background absorption is eliminated automatically, and even rapidly changing background absorption does not cause any artifacts, as measurement and correction of background absorption are truly simultaneous. Any kind of fine-structured background can be eliminated by “subtracting” reference spectra using a least-squares algorithm. Aqueous standards are used for calibration in all published applications of high-resolution continuum source atomic absorption spectrometry to direct solid sample analysis. This contribution is based on a presentation given at the Colloquium for Analytical Atomic Spectroscopy (CANAS ‘07) held March 18–21, 2007 in Constance, Germany.     

Electrochemical and spectroscopic characterisation of amphetamine-like drugs: application to the screening of 3,4-methylenedioxymethamphetamine (MDMA) and its synthetic precursors

A complete physicochemical characterisation of MDMA and its synthetic precursors MDA, 3,4-methylenedioxybenzaldehyde (piperonal) and 3,4-methylenedioxy-β-methyl-β-nitrostyrene was carried out through voltammetric assays and Raman spectroscopy combined with theoretical (DFT) calculations. The former provided important analytical redox data, concluding that the oxidative mechanism of the N-demethylation of MDMA involves the removal of an electron from the amino-nitrogen atom, leading to the formation of a primary amine and an aldehyde. The vibrational spectroscopic experiments enable to afford a rapid and reliable detection of this type of compounds, since they yield characteristic spectral patterns that lead to an unequivocal identification.Moreover, the rational synthesis of the drug of abuse 3,4-methylenedioxymethamphetamine (MDMA or “ecstasy”) from one of its most relevant precursors 3,4-methylene-dioxyamphetamine (MDA), is reported. In addition, several approaches for the N-methylation of MDA, a limiting synthetic step, were attempted and the overall yields compared.     

Magnetic interactions in the monoclinic ludwigite Cu FeO BO

The system Cu₂FeO₂BO₃ is an oxyborate belonging to the family of the ludwigites. In this paper we present AC susceptibility, magnetization measurements and M?ssbauer spectroscopy on this material which allows for a complete characterization of its complex magnetic behavior. We find an hierarchy of interactions which clearly defines three regimes with decreasing temperature. These are associated with, the freezing of the Fe moments, the antiferromagnetic ordering of the Cu sub-lattice and finally the coupling between both systems. Received 25 September 1998     

Determination of silver in geological samples using high-resolution continuum source electrothermal atomic absorption spectrometry and direct solid sampling

A DNA biosensor was constructed by immobilizing DNA on a glassy carbon (GC) electrode modified with multiwall carbon nanotubes (MWNTs) dispersed in Nafion (DNA/MWNTs/GCE). The DNA-modified electrode exhibited two well-defined oxidation peaks corresponding to the guanine and adenine residues of DNA, respectively. The effects of the adsorption potential, DNA concentration and quantity of MWNTs used for DNA immobilization were investigated, as were the effects of buffer, pH and scan rate on the voltammetric behavior of DNA. Phenol, m-cresol and catechol showed noticeable inhibition towards the response of the electrode due to their interactions with DNA. These findings were used to design biosensors with linear response to these phenolic pollutants.     

Exploratory analysis and inductively coupled plasma optical emission spectrometry (ICP OES) applied in the determination of metals in soft drinks

A 2³ factorial design and a CCD (Central Composite Design) were employed to optimize the operational conditions for determining Al, Ba, Ca, Cd, Cr, Cu, K, Mg, Na, Ni, Pb, Sn and Zn in soft drink samples by inductively coupled plasma optical emission spectrometry (ICP OES). Satisfactory parameters of merit were obtained (Plasma stability, linearity, SBR, BEC, LOD and LOQ). The accuracy was evaluated by means of a recovery study. Thirty five soft drink samples were analyzed. The results obtained were used in an exploratory analysis, in which principal component analysis and cluster analysis were applied in order to differentiate the several soft drink classes. Adequate LOQ values were obtained for all elements (0.34 μg L^− 1 for Ca to 88.7 μg L^− 1 for Mg) and the recovery study results ranged between 80 and 100%. Cluster analysis revealed four sample classes characterized by flavor and other characteristics, such as being light, diet, low calorie or regular beverages. A model with 4 PCs was obtained by means of a principal component analysis, which explained 99.8% of the total variance.