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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Van de Plas, Raf Yang, Junhai Spraggins, Jeffrey Caprioli, Richard M. |
| Description | Country affiliation: Netherlands Author Affiliation: Van de Plas R ( 1] Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA. [2] Department of Biochemistry, Vanderbilt University, Nashville, Tennessee, USA. [3] Delft Center for Systems and Control, Delft University of Technology, Delft, the Netherlands.); Yang J ( 1] Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA. [2] Department of Biochemistry, Vanderbilt University, Nashville, Tennessee, USA.); Spraggins J ( 1] Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA. [2] Department of Biochemistry, Vanderbilt University, Nashville, Tennessee, USA.); Caprioli RM ( 1] Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA. [2] Department of Biochemistry, Vanderbilt University, Nashville, Tennessee, USA. [3] Department of Chemistry, Vanderbilt University, Nashville, Tennessee, USA. [4] Department of Pharmacology, Vanderbilt Universi) |
| Abstract | We describe a predictive imaging modality created by 'fusing' two distinct technologies: imaging mass spectrometry (IMS) and microscopy. IMS-generated molecular maps, rich in chemical information but having coarse spatial resolution, are combined with optical microscopy maps, which have relatively low chemical specificity but high spatial information. The resulting images combine the advantages of both technologies, enabling prediction of a molecular distribution both at high spatial resolution and with high chemical specificity. Multivariate regression is used to model variables in one technology, using variables from the other technology. We demonstrate the potential of image fusion through several applications: (i) 'sharpening' of IMS images, which uses microscopy measurements to predict ion distributions at a spatial resolution that exceeds that of measured ion images by ten times or more; (ii) prediction of ion distributions in tissue areas that were not measured by IMS; and (iii) enrichment of biological signals and attenuation of instrumental artifacts, revealing insights not easily extracted from either microscopy or IMS individually. |
| File Format | HTM / HTML |
| ISSN | 15487091 |
| e-ISSN | 15487105 |
| DOI | 10.1038/nmeth.3296 |
| Journal | Nature Methods |
| Issue Number | 4 |
| Volume Number | 12 |
| Language | English |
| Publisher | Nature Publishing Group |
| Publisher Date | 2015-04-01 |
| Publisher Place | United States |
| Access Restriction | Open |
| Subject Keyword | Discipline Clinical Laboratory Techniques Image Processing, Computer-assisted Mass Spectrometry Microscopy Animals Brain Ultrastructure Instrumentation Mice Research Support, N.i.h., Extramural |
| Content Type | Text |
| Resource Type | Article |
| Subject | Cell Biology Biochemistry Molecular Biology Biotechnology |
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