Determination of adrenolytic drugs by SPME-LC-MS.
ABSTRACT Five adrenolytic drugs have been analyzed by liquid chromatography-mass spectrometry (LC-MS). Samples were prepared by solid-phase microextraction (SPME) using polypyrrole fibers coated on stainless steel support as an adsorbent for the drugs. Adsorption efficiencies were 95% and were close for all the drugs investigated. Relative standard deviations (RSD), calculated for samples prepared in standard solutions, were in the range 2.5-13%, however RSD values for the drugs in human plasma were 2.5-4.5%. Using LC-MS the limit of detection (LOD) and the limit of quantification (LOQ) were in the ranges 0.11-0.18 and 0.39-0.54 ng mL(-1), respectively, for the five drugs.
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ABSTRACT: The human population continues to grow exponentially in the fast developing and most populated countries, whereas in Western Europe it is getting older and older each year. This inevitably raises the demand for better and more efficient medical services without increasing the economic burden in the same proportion. To meet these requirements, improvement of medical diagnosis is certainly a key aspect to consider. Therefore, we need powerful analytical methodologies able to go deeper and further in the characterization of human metabolism and identification of disease biomarkers and endogenous molecules in body fluids and tissues. The ultimate goal is to have a reliable and early medical diagnosis, mitigating the disease complications as much as possible. Microextraction techniques (METs) represent a key step in these analytical methodologies by providing samples in the suitable volumes and purification levels necessary for the characterization of the target analytes. In this aspect, solid-phase microextraction (SPME) and, more recently, microextraction by packed sorbent (MEPS), are powerful sample preparation techniques, characterized by their reduced time of analysis, low solvent consumption, and broad application. Moreover, as miniaturized techniques, they can be easily automatized to have a high-throughput performance in the clinical environment. In this review, we explore some of the most interesting MEPS and SPME applications, focusing on recent trends and applications to medical diagnostic, particularly the in vivo and near real time applications.Analytical and Bioanalytical Chemistry 01/2014; 406(8). DOI:10.1007/s00216-013-7527-4 · 3.58 Impact Factor
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ABSTRACT: Polymeric polypyrrole and polythiophene solid phase microextraction (SPME) coatings were prepared using electropolymerization with a linear sweep voltammetry technique. Physicochemical properties were measured using different methods, in particular small angle X-ray scattering and scanning electron microscopy. By using innovative approaches for pore size measurement, we were able to calculate a maximum of the pore size range from 80 to 90 nm. Additionally, film thicknesses measured from 90 to 150 μm. Using scanning electron microscopy, we describe the characteristics of polymer growth on the support surface.Monatshefte fuer Chemie/Chemical Monthly 01/2014; 145(3):527-531. DOI:10.1007/s00706-013-1115-3 · 1.35 Impact Factor
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ABSTRACT: Multiple headspace solid-phase microextraction (SPME) has proved high efficiency in analysis of volatile compounds in complex samples. Fibers used in multiple headspace SPME must provide a logarithm relationship between peak areas and extraction times. The aim of this work was to investigate the potential of a carbon nanotube doped-polymeric ionic liquid (PILs) fiber for multiple headspace SPME of 2-naphthol in fruit samples, using gas chromatography (GC) for analysis. Based on theory of multiple headspace SPME, β parameters of fruit and aqueous samples were obtained and used for quantitation. The interference effects of sample matrix on proposed multiple headspace SPME method were investigated and compared with that of headspace SPME by determination of significant differences (P) of peak areas. It showed high independence from matrix effects. The proposed multiple headspace SPME-GC method also exhibited high repeatability (relative standard deviation of 2.56%) and recoveries (81.9-110%) for the analysis of real samples.Talanta 06/2014; 123:18–24. DOI:10.1016/j.talanta.2014.01.030 · 3.51 Impact Factor