Preparative mass‐spectrometry profiling of minor concentrated metabolites in Salicornia gaudichaudiana Moq by high‐speed countercurrent chromatography and off‐line electrospray mass‐spectrometry injection

Salicornia species have just been introduced to the European market as a vegetable named ‘samphire’, ‘green asparagus’, or ‘sea asparagus’. Due to its increasing attention, and associated value, minor compounds of Salicornia gaudichaudiana Moq were investigated. The use of countercurrent chromatography and mass spectrometry enabled the search for known, as well as potentially novel natural products. Their identification was achieved based on molecular weights and mass‐spectrometric fragmentation data. Low detection limits enabled the visualization of all compounds with their identification in almost real time close to the preparative countercurrent chromatography experiment. A list of known natural products from Salicornia genus guided the identification process of compounds occurring in Salicornia gaudichaudiana Moq by tandem mass spectrometry fragment comparison. The natural product classes were divided into four groups: chlorogenic acid derivatives; flavonoid derivatives; pentacyclic triterpenoid saponins; and other compounds.     

Essential oil and fractions isolated of Laurel to control adults and larvae of cattle ticks

Abstract

This study, was to evaluate the acaricidal effect of the essential oil (EO) and fractions (FR) obtained from Laurus nobilis leaves on Rhipicephalus (Boophilus) microplus. Eight fractions were obtained, however FR1: sabinene (37.83%), β-pinene (13.50%), 1,8-cineole (12.66%), α-pinene (12.56%) and FR8: α-terpineol (79.19%) were highlighted as to the larvicidal potential when submitted by Larval Packet Test. The EO was tested by the Adult Immersion Test, at concentrations of 200.00; 100.00 and 50.00?µL/mL caused mortality of engorged females, egg mass reduction and hatching inhibition. Two fractions are shown to be efficient in controlling larvae FR8 (LC₅₀?=?0.13?µL/mL, LC₉₉?=?0.51?µL/mL) and FR1 (LC₅₀?=?0.20?µL/mL, LC₉₉?=?0.56?µL/mL). The fractionation of EO was determinant to elucidate which compounds were responsible for the larvicidal potential. This study opens new perspectives to direct new bioassays with the compounds obtained in the fractionation, since they present high potential on cattle tick larvae.     

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.     

Molecular dynamics simulations on the local order of liquid and amorphous ZnTe

Molecular dynamics studies of structural and dynamical correlations of molten and vitreous states under several conditions of density and temperature were performed. We use an effective recently proposed interatomic potential, consisting of two- and three-body covalent interactions which has successfully described the structural, dynamical, and structural phase transformation induced by pressure in ZnTe [D. S. Borges and J. P. Rino, Phys. Rev. B 72, 014107 (2005)]. The two-body term of the interaction potential consists of Coulomb interaction resulting from charge transfer, steric repulsion due to atomic sizes, charge-dipole interaction to include the effect of electronic polarizability of anions, and dipole-dipole (van der Waals) interactions. The three-body covalent term is a modification of the Stillinger-Weber potential. Molecular dynamics simulations in isobaric-isenthalpic ensemble have been performed for systems amounting to 4096 and 64 000 particles. Starting from a crystalline zinc-blende (ZB) structure, the system is initially heated until a very homogeneous liquid is obtained. The vitreous zinc telluride phase is attained by cooling the liquid at sufficiently fast cooling rates, while slower cooling rates lead to a disordered ZB crystalline structure. Two- and three-body correlations for the liquid and vitreous phases are analyzed through pair distribution functions, static structure factors, and bond angle distributions. In particular, the neutron static structure factor for the liquid phase is in very good agreement with both the reported experimental data and first-principles simulations.     

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...     

Capillary electrochromatography and nano‐liquid chromatography coupled to nano‐electrospray ionization interface for the separation and identification of estrogenic compounds

Nano‐LC and CEC were coupled to MS through a nanospray or a pressurized liquid‐junction interface for the simultaneous separation and determination of 11 estrogenic compounds. Different stationary phases, that is, phenyl, C18, and C18 bidentate silica hydrate, were studied. For both techniques, the phenyl stationary phase was the best option, considering separation efficiency, selectivity, and resolution. Under the optimized conditions, the baseline separation of the target compounds (including estradiol and zearalanol epimers) was achieved in less than 20 min in nano‐LC‐MS and less than 13 min in CEC‐MS. Molecular imprinted polymer SPE was used for extracting the target compounds from mineral water samples with the analysis of nano‐LC‐MS. The whole molecular imprinted polymer SPE nano‐LC‐MS method was validated through a recovery study at two levels of concentration. Sensitivity was improved by on‐column focusing technique obtaining LODs in the range 1.4–55.4 ng/L.     

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.