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Biological Tissue Imaging with a Position and Time Sensitive Pixelated Detector

Overview of attention for article published in Journal of the American Society for Mass Spectrometry, July 2012
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Title
Biological Tissue Imaging with a Position and Time Sensitive Pixelated Detector
Published in
Journal of the American Society for Mass Spectrometry, July 2012
DOI 10.1007/s13361-012-0444-5
Pubmed ID
Authors

Julia H. Jungmann, Donald F. Smith, Luke MacAleese, Ivo Klinkert, Jan Visser, Ron M. A. Heeren

Abstract

We demonstrate the capabilities of a highly parallel, active pixel detector for large-area, mass spectrometric imaging of biological tissue sections. A bare Timepix assembly (512 × 512 pixels) is combined with chevron microchannel plates on an ion microscope matrix-assisted laser desorption time-of-flight mass spectrometer (MALDI TOF-MS). The detector assembly registers position- and time-resolved images of multiple m/z species in every measurement frame. We prove the applicability of the detection system to biomolecular mass spectrometry imaging on biologically relevant samples by mass-resolved images from Timepix measurements of a peptide-grid benchmark sample and mouse testis tissue slices. Mass-spectral and localization information of analytes at physiologic concentrations are measured in MALDI-TOF-MS imaging experiments. We show a high spatial resolution (pixel size down to 740 × 740 nm(2) on the sample surface) and a spatial resolving power of 6 μm with a microscope mode laser field of view of 100-335 μm. Automated, large-area imaging is demonstrated and the Timepix' potential for fast, large-area image acquisition is highlighted.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
United States 1 3%
Belgium 1 3%
Unknown 33 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 31%
Researcher 6 17%
Student > Bachelor 4 11%
Other 3 8%
Professor 2 6%
Other 4 11%
Unknown 6 17%
Readers by discipline Count As %
Chemistry 11 31%
Agricultural and Biological Sciences 8 22%
Physics and Astronomy 3 8%
Biochemistry, Genetics and Molecular Biology 2 6%
Economics, Econometrics and Finance 1 3%
Other 3 8%
Unknown 8 22%