Literature DB >> 10918368

Analysis of urinary nucleosides. I. Optimisation of high performance liquid chromatography/electrospray mass spectrometry.

E Dudley1, S El-Sharkawi, D E Games, R P Newton.   

Abstract

In order to optimise the analysis of urinary nucleosides by high performance liquid chromatography/mass spectrometry (HPLC/MS), the HPLC separation of these compounds was performed at different 'flow rates' and 0.2mL/min was found to give both a better separation and ionisation. The ionisation conditions were optimised to give the best intensity of the molecules quasi-molecular ions. The ion distribution profile and ionisation in both positive and negative mode were examined and the detection of the protonated molecule in positive mode chosen for further analysis. The limits of detection of the method developed are reported and representative LC/MS and LC/MS/MS spectra shown. Typical urinary nucleoside chromatograms are presented. Copyright 2000 John Wiley & Sons, Ltd.

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Year:  2000        PMID: 10918368     DOI: 10.1002/1097-0231(20000730)14:14<1200::AID-RCM10>3.0.CO;2-I

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


  6 in total

1.  A nano-chip-LC/MSn based strategy for characterization of modified nucleosides using reduced porous graphitic carbon as a stationary phase.

Authors:  Anders Michael Bernth Giessing; Lincoln Greyson Scott; Finn Kirpekar
Journal:  J Am Soc Mass Spectrom       Date:  2011-04-15       Impact factor: 3.109

2.  MALDI-TOF MS analysis of urinary nucleosides.

Authors:  Bernd Kammerer; Antje Frickenschmidt; Christoph H Gleiter; Stefan Laufer; Hartmut Liebich
Journal:  J Am Soc Mass Spectrom       Date:  2005-04-20       Impact factor: 3.109

Review 3.  The state-of-the-art determination of urinary nucleosides using chromatographic techniques "hyphenated" with advanced bioinformatic methods.

Authors:  Wiktoria Struck; Małgorzata Waszczuk-Jankowska; Roman Kaliszan; Michał J Markuszewski
Journal:  Anal Bioanal Chem       Date:  2011-02-27       Impact factor: 4.142

4.  Quantification of mRNA cap-modifications by means of LC-QqQ-MS.

Authors:  Nils Muthmann; Petr Špaček; Dennis Reichert; Melissa van Dülmen; Andrea Rentmeister
Journal:  Methods       Date:  2021-05-28       Impact factor: 4.647

5.  Prediction of breast cancer by profiling of urinary RNA metabolites using Support Vector Machine-based feature selection.

Authors:  Carsten Henneges; Dino Bullinger; Richard Fux; Natascha Friese; Harald Seeger; Hans Neubauer; Stefan Laufer; Christoph H Gleiter; Matthias Schwab; Andreas Zell; Bernd Kammerer
Journal:  BMC Cancer       Date:  2009-04-05       Impact factor: 4.430

6.  Metabolic signature of breast cancer cell line MCF-7: profiling of modified nucleosides via LC-IT MS coupling.

Authors:  Dino Bullinger; Hans Neubauer; Tanja Fehm; Stefan Laufer; Christoph H Gleiter; Bernd Kammerer
Journal:  BMC Biochem       Date:  2007-11-29       Impact factor: 4.059

  6 in total

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