Identification of plastic toys contaminated with volatile organic compounds using QCM gas sensor array.

In this paper, we propose a fast and easy-to-use analytical method to identify the children toys contaminated with potentially dangerous substances from the class of volatile organic compounds (VOCs). It is shown that the use of cross-sensitive gas sensor array based on piezoelectric sensors, modified with different sorbents, allows reliable recognition of items with the elevated levels of VOCs. Applying chemometric methods for processing of the sensor array data, it is possible to classify the toys into clean and hazardous ones with sensitivity and accuracy around 96%. Taking into account the simplicity of the suggested procedure, it appears to be an attractive option for cost-effective pre-screening of potentially dangerous plastic toys in comparison with the expensive and time-consuming chromatographic methods.

Three-point multivariate calibration models by correlation constrained MCR-ALS: A feasibility study for quantitative analysis of complex mixtures.

When it comes to address quantitative analysis in complex mixtures, Partial Least Squares (PLS) is often referred to as a standard first-order multivariate calibration method. The set of samples used to build the PLS regression model should ideally be large and representative to produce reliable predictions. In practice, however, the large number of calibration samples is not always affordable and the choice of these samples should be handled with care as it can significantly affect the accuracy of the predictive model. Correlation constrained multivariate curve resolution (CC-MCR) is an alternative regression method for first-order datasets where, unlike PLS, calibration and prediction stages are performed iteratively and optimized under constraints until the decomposition meets the convergence criterion. Both calibration and test samples are fitted into a unique bilinear model so that the number of calibration samples is no longer a critical issue. In this paper we demonstrate that under certain conditions CC-MCR models can provide for reasonable predictions in quantitative analysis of complex mixtures even when only three calibration samples are employed. The latter are defined as samples having the minimum, the maximum and the average concentration, providing for a simple and rapid strategy to build reliable calibration model. The feasibility of three-point multivariate calibration approach was assessed with several case studies featuring mixtures of different analytes in presence of interfering species. Satisfactory predictions with relative errors in the range 3-15% were achieved and good agreement with classical PLS models built from a larger set of calibration samples was observed.

Stepwise injection potentiometric determination of caffeine in saliva using single-drop microextraction combined with solvent exchange.

A flow potentiometric method for determination of caffeine in saliva is suggested. This task is important for non-invasive assessment of drug metabolizing system activity in hepatocytes. In the current study, stepwise injection analysis (SWIA) was successfully combined with single-drop liquid microextraction (SDLME) and solvent exchange procedure. The method is based on the caffeine SDLME with subsequent solvent evaporation and dissolution of analyte in sulfuric acid followed by potentiometric detection using poly(vinyl chloride) membrane electrode containing potassium tetrakis[3,5-bis(trifluoromethyl)phenyl]borate as electroactive component. SDLME was employed for elimination of interfering matrix effects of saliva and caffeine metabolites such as theophylline, theobromine and paraxanthine. A linear range of 10(-5)-10(-2)M was established for caffeine with detection limit at 6 × 10(-6)M. The sample throughput was 6 samples h(-1). The proposed method was successfully applied to the determination of caffeine in saliva and the analytical results agreed well with the results obtained with reference HPLC method.

Electronic tongue for microcystin screening in waters.

The potentiometric E-tongue system was employed for water toxicity estimation in terms of cyanobacterial microcystin toxins (MCs) detection. The data obtained from E-tongue were correlated to the MCs content detected by the standard chromatographic technique UHPLC-DAD (Ultra High Performance Liquid Chromatography with Diode Array Detector), as far as by the colorimetric enzymatic approach. The prediction of MCs released by toxic Microcystis aeruginosa strains was possible with Root Mean Squared Error of Validation (RMSEV) lower or very close to 1µg/L, the provisional guideline value of WHO for MCs content in potable waters. The application of E-tongue system opens up a new perspective offset for fast and inexpensive analysis in the field of environmental monitoring, offering also the possibility to distinguish toxin producing and non-toxic M. aeruginosa strains present in potable water.

[The choice of the targets and the search for their inhibitors by means of computer simulation for the development of innovative preparations to treat of chronic bacterial infections].

Persistence is a form of interaction of pathogenic bacteria with a host aimed to promote their long-term survivalby means of inactivation of the host's protective systems via modulation of intracellular signal pathways. Persistent forms of a pathogen are refractory to traditional antibiotic therapy and cause chronic infectious diseases. Directed search for protein targets and new antibacterial drugs using computer simulation and experimental testing for the development of innovative preparations to treat chronic bacterial infections appears to have good prospects as a method for the management of persistent infections. A stepwise strategy for realization of such approach is exemplified by the search of preparations against chlamydial infection.

Cross-sensitive rare-earth metal sensors based on bidentate neutral organophosphorus compounds and chlorinated cobalt dicarbollide.

A variety of new chemical sensors (ion selective electrodes) for determination of rare-earth (RE) and trivalent metal cations such as yttrium(III), lanthanum(III), praseodymium(III), neodymium(III) and europium(III) that are commonly present in aqueous radiological samples, e.g. in high-level liquid waste (HLW) and solutions from reprocessing spent nuclear fuel, have been developed and studied. The sensors are based on bidentate neutral organophosphorus compounds, such as methylene bridged diphosphine dioxides and carbamoylmethylphosphine oxides, which are efficient extractants, especially when used in conjunction with chlorinated cobalt dicarbollide, for recovery and concentration of the RE and actinide elements from acidic HLW derived from the nuclear fuel cycle. The sensors exhibit remarkable sensitivity to RE cations and indicate promise for HLW analysis.

Multicomponent analysis of fermentation growth media using the electronic tongue (ET).

A potentiometric electronic tongue (ET) consisting of eight cross-sensitive chemical sensors and a standard pH electrode has been applied for analysis of simulated fermentation solutions typical for fermentation processes with Aspergillus niger. The electronic tongue has been found capable of simultaneous determination of ammonium, citrate and oxalate in complex media with good precision (typical error within 8%). The system preserved high sensitivity to the targeted substances also in the presence of sodium azide, which is commonly used for suppressing microbial activity in real-world fermentation samples. Sensor performance was fast and reproducible which promises well for routine application of the electronic tongue for fermentation process monitoring.