Calibration of the complex matrix effects on the sampling of polycyclic aromatic hydrocarbons in milk samples using solid phase microextraction

Solid phase microextraction (SPME), a simple, fast and promising sampling technique, has been widely used for complex sample analysis. However, complex matrices could modify the absorption property of coatings as well as the uptake kinetics of analytes, eventually biasing the quantification results. In the current study, we demonstrated the feasibility of a developed calibration method for the analysis of polycyclic aromatic hydrocarbons (PAHs) in complex milk samples. Effects of the complex matrices on the SPME sampling process and the sampling conditions were investigated. Results showed that short exposure time (pre-equilibrium SPME, PE-SPME) could increase the lifetime of coatings, and the complex matrices in milk samples could significantly influence the sampling kinetics of SPME. In addition, the optimized sampling time, temperature and dilution factor for PAHs were 10 min, 85 °C and 20, respectively. The obtained LODs and LOQs of all the PAHs were 0.1–0.8 ng/mL and 1.4–4.7 ng/mL, respectively. Furthermore, the accuracy of the proposed PE-SPME method for milk sampling was validated by the recoveries of the studied compounds in two concentration levels, which ranged from 75% to 110% for all the compounds. Finally, the proposed method was applied to the screening of PAHs in milk samples.     

A note on random walks with absorbing barriers and sequential Monte Carlo methods

In this article, we consider importance sampling (IS) and sequential Monte Carlo (SMC) methods in the context of one-dimensional random walks with absorbing barriers. In particular, we develop a very precise variance analysis for several IS and SMC procedures. We take advantage of some explicit spectral formulae available for these models to derive sharp and explicit estimates; this provides stability properties of the associated normalized Feynman–Kac semigroups. Our analysis allows one to compare the variance of SMC and IS techniques for these models. The work in this article is one of the few to consider an in-depth analysis of an SMC method for a particular model-type as well as variance comparison of SMC algorithms.     

Physicochemical and Graph Theoretical Descriptors in Developmental Toxicity SAR: A Comparative Study

Abstract

Chemical insults to the developing fetus can lead to growth retardation, malformation, death, and functional deficits. The present study seeks to determine if physicochemical and/or graph theoretical parameters can be used to determine a structure-activity relationship (SAR) for developmental toxicity, and if consistency is observed among the selected features. The biological data utilized consists of a diverse series of compounds evaluated within the Chernoff-Kavlock in vivo mouse assay. Physicochemical parameters calculated correspond to electronic, steric, and transport properties. Graph theoretical parameters calculated include the simple, valence, and kappa indices. Both sets of parameters were independently applied to derive SARs in order to compare the quality of the respective models. Multiple random sampling, without replacement, was utilized to obtain ten training/test partitions. Models were built by linear discriminant analysis, decision trees, and neural networks respectively. Comparisons on identical sets of data were carried out to determine if any of the model building procedures had a significant advantage in terms of predictive performance. Furthermore, comparison of the features selected within and across the model building processes led to the determination of model consistency. Our results indicate that consistent features related to developmental toxicity are observed and that both physicochemical and graph theoretical parameters have equal utility.     

Electrochemical Detection of TNT at Cobalt Phthalocyanine Mediated Screen‐Printed Electrodes and Application to Detection of Airborne Vapours

We describe the use of cobalt phthalocyanine as a mediator to improve the sensitivity for the electrochemical detection of TNT. Commercial screen‐printed electrodes containing cobalt phthalocyanine were employed for determination of TNT. Improved sensitivities compared to screen‐printed carbon electrodes without phthalocyanine were observed, current response for cyclic voltammetric measurements at modified electrodes being at least double that of unmodified electrodes. A synergistic effect between oxygen and TNT reduction was also observed. Correlation between TNT concentrations and sensor output was observed between 0–200 µM TNT. Initial proof‐of‐concept experiments combining electrochemical determinations, with the use of an air‐sampling cyclone, are also reported.     

Study of the Molecular Mobility in Polymers with the Thermally Stimulated Recovery Technique—A Review

Thermally stimulated recovery (TSR) is a non‐conventional mechanical spectroscopy technique that allows to analyse in detail the relaxation processes of polymeric systems in the low frequency region. This work reviews the main aspects and potentialities of this technique. The different kinds of TSR experiments that can be performed, global and thermal sampling (TS) experiments, are described and illustrated with several examples. Also, the different methods for the determination of the thermokinetic parameters (activation energy and pre‐exponential factor) of the thermal sampling (TS) procedure are explained and compared. In this context, the compensation phenomenon, which always appears in TSR results when the studies are performed in the glass transition region of a given system, is discussed. Examples of the application of this technique to different polymeric systems during the last 20 years are provided. An emphasis will be made on the analysis of the effect of crystallinity degree and crosslink density on the TSR response. A comparison between the results (characteristic times and activation energies) obtained by different techniques, namely TSR, dynamic mechanical analysis (DMA), and differential scanning calorimetry (DSC), is made.     

Solid phase microextraction fills the gap in tissue sampling protocols

Metabolomics and biomarkers discovery are an integral part of bioanalysis. However, untargeted tissue analysis remains as the bottleneck of such studies due to the invasiveness of sample collection, as well as the laborious and time-consuming sample preparation protocols. In the current study, technology integrating in vivo sampling, sample preparation and global extraction of metabolites – solid phase microextraction was presented and evaluated during liver and lung transplantation in pig model. Sampling approaches, including selection of the probe, transportation, storage conditions and analyte coverage were discussed. The applicability of the method for metabolomics studies was demonstrated during lung transplantation experiments.     

Determination of Pd,Rh, Pt,Au in road dust by electrothermal vaporization inductively coupled plasma mass spectrometry with slurry sampling

Inductively coupled plasma mass spectrometry coupled with ultrasonic slurry sampling electrothermal vaporization (USS-ETV-ICP-MS) has been applied to determine Pd, Rh, Pt and Au in 0.5% m/v slurries of several road dust samples. 2% m/v ammonium pyrrolidine dithiocarbamate (APDC) was used as the modifier to enhance the ion count. The influence of instrument operating conditions, slurry preparation and interferences on the ion count was reported. This method has been applied to the determination of Pd, Rh, Pt and Au in BCR 723 Road Dust and NIST SRM 2709 San Joaquin Soil reference materials and two road dust samples collected locally. The analysis results of the standard reference materials agreed with the certified values. Precision between sample replicates was better than 10% for all the determinations. The method detection limits estimated from standard addition curves were 0.9, 0.4, 0.6 and 0.4 ng g⁻¹ for Pd, Rh, Pt and Au, respectively, in original dust samples.     

FIPSDock: A new molecular docking technique driven by fully informed swarm optimization algorithm

The accurate prediction of protein–ligand binding is of great importance for rational drug design. We present herein a novel docking algorithm called as FIPSDock, which implements a variant of the Fully Informed Particle Swarm (FIPS) optimization method and adopts the newly developed energy function of AutoDock 4.20 suite for solving flexible protein–ligand docking problems. The search ability and docking accuracy of FIPSDock were first evaluated by multiple cognate docking experiments. In a benchmarking test for 77 protein/ligand complex structures derived from GOLD benchmark set, FIPSDock has obtained a successful predicting rate of 93.5% and outperformed a few docking programs including particle swarm optimization (PSO)@AutoDock, SODOCK, AutoDock, DOCK, Glide, GOLD, FlexX, Surflex, and MolDock. More importantly, FIPSDock was evaluated against PSO@AutoDock, SODOCK, and AutoDock 4.20 suite by cross‐docking experiments of 74 protein–ligand complexes among eight protein targets (CDK2, ESR1, F2, MAPK14, MMP8, MMP13, PDE4B, and PDE5A) derived from Sutherland‐crossdock‐set. Remarkably, FIPSDock is superior to PSO@AutoDock, SODOCK, and AutoDock in seven out of eight cross‐docking experiments. The results reveal that FIPS algorithm might be more suitable than the conventional genetic algorithm‐based algorithms in dealing with highly flexible docking problems. © 2012 Wiley Periodicals, Inc.