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Sample preparation and data interpretation procedures for the examination of xenobiotic compounds in skin by indirect imaging MALDI-MS
Authors:Brendan Prideaux   Sally J. Atkinson   Vikki A. Carolan   Jacqueline Morton  Malcolm R. Clench  
Affiliation:aBiomedical Research Centre, Sheffield Hallam University, Howard Street, Sheffield S1 1WB, United Kingdom;bHealth and Safety Laboratory, Harpur Hill, Buxton, Derbyshire SK17 9NJ, United Kingdom
Abstract:Aspects of the indirect examination of xenobiotic distribution on the surface of and within skin sections by imaging matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) have been examined. A solvent assisted blotting technique previously developed for the examination of the absorption of agrochemicals into leaves has been examined for the analysis of the distribution of hydrocortisone on the surface of skin. It was found that by careful control of the extraction and blotting procedure an 80-fold sensitivity improvement could by obtained over dry blotting with only 10% lateral diffusion of the image. However, in contrast it was found that the use of a hydrophobic blotting membrane was more suitable for the examination of the transdermal absorption of the pesticide chlorpyrifos.The potential of incorporating a derivatisation step into the solvent assisted blotting procedure was investigated by blotting isocyanate treated skin onto a methanol soaked blotting membrane. This served the dual purpose of derivatising the isocyanate to a stable substituted urea derivative and extracting it from the skin. Preliminary data indicate that this approach may have some merit for field sampling for such compound and clearly derivatisation also offers the potential for sensitivity enhancements.Finally, the use of principal components analysis with an ion species specific normalisation procedure is proposed to identify regions of drug treated skin where the ion abundance of the compound of interest is low.
Keywords:Imaging MALDI   Skin   Indirect imaging   Principal component analysis
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