Literature DB >> 21145556

Fluorescence detection by intensity changes for high-performance thin-layer chromatography separation of lipids using automated multiple development.

Vicente L Cebolla1, Carmen Jarne, Pilar Domingo, Andrés Domínguez, Aránzazu Delgado-Camón, Rosa Garriga, Javier Galbán, Luis Membrado, Eva M Gálvez, Fernando P Cossío.   

Abstract

Changes in emission of berberine cation, induced by non-covalent interactions with lipids on silica gel plates, can be used for detecting and quantifying lipids using fluorescence scanning densitometry in HPTLC analysis. This procedure, referred to as fluorescence detection by intensity changes (FDIC) has been used here in combination with automated multiple development (HPTLC/AMD), a gradient-based separation HPTLC technique, for separating, detecting and quantifying lipids from different families. Three different HPTLC/AMD gradient schemes have been developed for separating: neutral lipid families and steryl glycosides; different sphingolipids; and sphingosine-sphinganine mixtures. Fluorescent molar responses of studied lipids, and differences in response among different lipid families have been rationalized in the light of a previously proposed model of FDIC response, which is based on ion-induced dipole interactions between the fluorophore and the analyte. Likewise, computational calculations using molecular mechanics have also been a complementary useful tool to explain high FDIC responses of cholesteryl and steryl-derivatives, and moderate responses of sphingolipids. An explanation for the high FDIC response of cholesterol, whose limit of detection (LOD) is 5 ng, has been proposed. Advantages and limitations of FDIC application have also been discussed.
Copyright © 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 21145556     DOI: 10.1016/j.chroma.2010.11.033

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  1 in total

1.  Sphingolipid serum profiling in vitamin D deficient and dyslipidemic obese dimorphic adults.

Authors:  Nasser M Al-Daghri; Enrica Torretta; Pietro Barbacini; Hannah Asare; Cristian Ricci; Daniele Capitanio; Franca Rosa Guerini; Shaun B Sabico; Majed S Alokail; Mario Clerici; Cecilia Gelfi
Journal:  Sci Rep       Date:  2019-11-13       Impact factor: 4.379

  1 in total

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