Study of blood collection and sample preparation for analysis of vitamin D and its metabolites by liquid chromatography–tandem mass spectrometry

The analysis of vitamin D status, with special emphasis on 25-hydroxyvitamin D and 1,25-dihydroxyvitamin D, is gaining interest in clinical studies due to the classical and non-classical effects attributed to this prohormone. In this research, the influence of the two steps preceding determination (viz. sample collection and preparation) on the quantitative analysis of vitamin D and its more important metabolites has been studied. Two preparation approaches, deproteination and solid-phase extraction (SPE), have been evaluated in terms of sensitivity to delimit their application, thus establishing that detection of 1,25-dihydroxyvitamin D cannot be addressed by protein precipitation. Concerning sample collection, serum and plasma reported high accuracy (above 83.3%) for vitamin D and metabolites, while precision, expressed as relative standard deviation, was below 12.9% for all analytes in both samples. Statistical analysis revealed that serum and plasma provided similar physiological levels for vitamin D₃, 24,25-dihydroxyvitamin D₃ and 25-hydroxyvitamin D₃, while significantly different levels were obtained for 1,25-dihydroxyvitamin D₃, always higher in plasma than in serum. Sample collection and treatment have proved to be significant in the analysis of vitamin D and its relevant metabolites.     

Evolution of dispersive liquid–liquid microextraction method

Dispersive liquid–liquid microextraction (DLLME) has become a very popular environmentally benign sample-preparation technique, because it is fast, inexpensive, easy to operate with a high enrichment factor and consumes low volume of organic solvent. DLLME is a modified solvent extraction method in which acceptor-to-donor phase ratio is greatly reduced compared with other methods. In this review, in order to encourage further development of DLLME, its combination with different analytical techniques such as gas chromatography (GC), high-performance liquid chromatography (HPLC), inductively coupled plasma-optical emission spectrometry (ICP-OES) and electrothermal atomic absorption spectrometry (ET AAS) will be discussed. Also, its applications in conjunction with different extraction techniques such as solid-phase extraction (SPE), solidification of floating organic drop (SFO) and supercritical fluid extraction (SFE) are summarized. This review focuses on the extra steps in sample preparation for application of DLLME in different matrixes such as food, biological fluids and solid samples. Further, the recent developments in DLLME are presented. DLLME does have some limitations, which will also be discussed in detail. Finally, an outlook on the future of the technique will be given.     

Extending the working calibration ranges of four hexachlorocyclohexane isomers in gas chromatography-electron capture detector by radial basis function neural network

A radial basis function neural network (RBFNN) method was developed for the first time to model the nonlinear calibration curves of four hexachlorocyclohexane (HCH) isomers, aiming to extend their working calibration ranges in gas chromatography-electron capture detector (GC-ECD). Other 14 methods, including seven parametric curve fitting methods, two nonparametric curve fitting methods, and five other artificial neural network (ANN) methods, were also developed and compared. Only the RBFNN method, with logarithm-transform and normalization operation on the calibration data, was able to model the nonlinear calibration curves of the four HCH isomers adequately. The RBFNN method accurately predicted the concentrations of HCH isomers within and out of the linear ranges in certified test samples. Furthermore, no significant difference (p > 0.05) was found between the results of HCH isomers concentrations in water samples calculated with RBFNN method and ordinary least squares (OLS) method (R² > 0.9990). Conclusively, the working calibration ranges of the four HCH isomers were extended from 0.08-60 ng/ml to 0.08-1000 ng/ml without sacrificing accuracy and precision by means of RBFNN. The outstanding nonlinear modeling capability of RBFNN, along with its universal applicability to various problems as a “soft” modeling method, should make the method an appealing alternative to traditional modeling methods in the calibration analyses of various systems besides the GC-ECD.     

Sample preparation methods for subsequent determination of metals and non-metals in crude oil—A review

In this review sample preparation strategies used for crude oil digestion in last ten years are discussed focusing on further metals and non-metals determination. One of the main challenges of proposed methods has been to overcome the difficulty to bring crude oil samples into solution, which should be compatible with analytical techniques used for element determination. On this aspect, this review summarizes the sample preparation methods for metals and non metals determination in crude oil including those based on wet digestion, combustion, emulsification, extraction, sample dilution with organic solvents, among others. Conventional methods related to wet digestion with concentrated acids or combustion are also covered, with special emphasis to closed systems. Trends in sample digestion, such as microwave-assisted digestion using diluted acids combined with high-efficiency decomposition systems are discussed. On the other hand, strategies based on sample dilution in organic solvents and procedures recommended for speciation analysis are reported as well as the use of direct analysis in view of the recent importance for crude oil field. A compilation concerning sample preparation for crude oil provided by official methods as well as certified reference materials available for accuracy evaluation is also presented and discussed.