期刊
JOURNAL OF CHROMATOGRAPHY A
卷 1217, 期 25, 页码 3946-3954出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2010.01.033
关键词
MALDI; SIMS; DESI; Imaging mass spectrometry; Molecular histology
资金
- Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO)
- Netherlands Proteomics Centre
- Computis Program, 6th European Framework Program for Research and Technological Development (FP6) [LSHG-CT-2005-5181194]
Mass spectrometric imaging allows the investigation of the spatial distribution of molecules at complex surfaces. The combination of molecular speciation with local analysis renders a chemical microscope that can be used for the direct biomolecular characterization of histological tissue surfaces. MS based imaging advantageously allows label-free detection and mapping of a wide-range of biological compounds whose presence or absence can be the direct result of disease pathology. Successful detection of the analytes of interest at the desired spatial resolution requires careful attention to several steps in the mass spectrometry imaging protocol. This review will describe and discuss a selected number of crucial developments in ionization, instrumentation, and application of this innovative technology. The focus of this review is on the latest developments in imaging MS. Selected biological applications are employed to illustrate some of the novel features discussed. Two commonly used MS imaging techniques, secondary ion mass spectrometric (SIMS) imaging and matrix-assisted laser desorption ionization (MALDI) mass spectrometric imaging, center this review. New instrumental developments are discussed that extend spatial resolution, mass resolving power, mass accuracy, tandem-MS capabilities, and offer new gas-phase separation capabilities for both imaging techniques. It will be shown how the success of MS imaging is crucially dependent on sample preparation protocols as they dictate the nature and mass range of detected biomolecules that can be imaged. Finally, developments in data analysis strategies for large imaging datasets will be briefly discussed. (C) 2010 Elsevier B.V. All rights reserved.
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