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Separation of enantiomers remains a challenge owing to their identical physical and chemical properties in an achiral environment, and research on specialized separation techniques such as multidimensional achiral-chiral liquid chromatography continues to resolve individual enantiomers in complex samples. Recent advances in application of multidimensional liquid chromatography applied to chiral analysis are reviewed. For this reason, benefits of achiral-chiral coupling are shown, with emphasis in applications on biological and pharmaceutical fields as well as pesticide analysis. A description of standard instrumental setup in both heart-cut and comprehensive multidimensional liquid chromatography is shown. The most broadly used chiral stationary phases for multidimensional liquid chromatography are summarized. An extensive overview of different interface designs applied to complex samples is presented.

Changes in free amino acids content and its potential racemization in ready-to-eat foods treated with E-beam irradiation between 1 and 8 kGy for sanitation purposes were studied. A simple heart cut two-dimensional high performance liquid chromatographic method (LC-LC) for the simultaneous enantiomeric determination of three pairs of amino acids used as markers (tyrosine, phenylalanine, and tryptophan) is presented. The proposed method involves the use of two chromatographs in an LC-LC achiral-chiral coupling. Amino acids and their decomposition products were firstly separated in a primary column (C(18)) using a mixture of ammonium acetate buffer (20 mM, pH 6) (94%) and methanol (6%) as the mobile phase. Then, a portion of each peak was transferred by heart cutting through a switching valve to a teicoplanin-chiral column. Methanol (90%)/water (10%) was used as the mobile phase. Ultraviolet detection was at 260 nm. Detection limits were between 0.16 and 3 mg L(-1) for each enantiomer. Recoveries were in the range 79-98%. The LC-LC method combined with the proposed sample extraction procedure is suitable for complex samples; it involves an online cleanup, and it prevents degradation of protein, racemization of L-enantiomers, and degradation of tryptophan. Under these conditions, D-amino acids were not found in any of the analyzed samples at detection levels of the proposed method.

The present work reports the distribution of pollutants in the Madrid city and province from 22 monitoring stations during 2010 to 2017. Statistical tools were used to interpret and model air pollution data. The data include the annual average concentrations of nitrogen oxides, ozone, and particulate matter (PM10), collected in Madrid and its suburbs, which is one of the largest metropolitan places in Europe, and its air quality has not been studied sufficiently. A mapping of the distribution of these pollutants was done, in order to reveal the relationship between them and also with the demography of the region. The multivariate analysis employing correlation analysis, principal component analysis (PCA), and cluster analysis (CA) resulted in establishing a correlation between different pollutants. The results obtained allowed classification of different monitoring stations on the basis of each of the four pollutants, revealing information about their sources and mechanisms, visualizing their spatial distribution, and monitoring their levels according to the average annual limits established in the legislation. The elaboration of contour maps by the geostatistical method, ordinary kriging, also supported the interpretation derived from the multivariate analysis demonstrating the levels of NO2 exceeding the annual limit in the centre, south, and east of the Madrid province.