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Endogenous expression mapping of malignant melanoma by mass spectrometry imaging

Overview of attention for article published in Clinical and Translational Medicine, August 2018
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Title
Endogenous expression mapping of malignant melanoma by mass spectrometry imaging
Published in
Clinical and Translational Medicine, August 2018
DOI 10.1186/s40169-018-0201-x
Pubmed ID
Authors

Yutaka Sugihara, Daniel Rivas, Johan Malm, Marcell Szasz, HoJeong Kwon, Bo Baldetorp, Håkan Olsson, Christian Ingvar, Melinda Rezeli, Thomas E. Fehniger, György Marko-Varga

Abstract

Currently, only a limited number of molecular biomarkers for malignant melanoma exist. This is the case for both diagnosing the disease, staging, and efficiently measuring the response to therapy by tracing the progression of disease development and drug impact. There is a great need to identify novel landmarks of disease progression and alterations. Matrix-assisted laser desorption ionisation mass spectrometry imaging (MALDI-MSI) has been developed within our group to study drug localisation within micro-environmental tissue compartments. Here, we expand further on this technology development and introduce for the first time melanoma tumour tissues to map metabolite localisation utilising high resolution mass spectrometry. MALDI-MSI can measure and localise the distribution pattern of a number of small molecule metabolites within tissue compartments of tumours isolated from melanoma patients. Data on direct measurements of metabolite identities attained at the local sites in tissue compartments has not been readily available as a measure of a clinical index for most cancer diseases. The current development on the mapping of endogenous molecular expression melanoma tumours by mass spectrometry imaging focuses on the establishment of a cancer tissue preparation process whereby a matrix crystal formation is homogenously built on the tissue surface, providing uniform molecular mapping. We apply this micro-preparation technology to disease presentation by mapping the molecular signatures from patient tumour sections. We have automated the process with a micro-technological dispensing platform. This provides the basis for thin film generation of the cancer patient tissues prior to imaging screening. Compartmentalisation of the tumour regions are displayed within the image analysis interfaced with histopathological grading and characterisation. This enables site localisation within the tumour with image mapping to disease target areas such as melanoma cells, macrophages, and lymphocytes.

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 23%
Researcher 5 23%
Student > Master 3 14%
Student > Bachelor 2 9%
Other 1 5%
Other 0 0%
Unknown 6 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 14%
Medicine and Dentistry 3 14%
Chemistry 3 14%
Pharmacology, Toxicology and Pharmaceutical Science 2 9%
Immunology and Microbiology 1 5%
Other 3 14%
Unknown 7 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 September 2018.
All research outputs
#16,728,456
of 25,385,509 outputs
Outputs from Clinical and Translational Medicine
#527
of 1,060 outputs
Outputs of similar age
#208,817
of 340,721 outputs
Outputs of similar age from Clinical and Translational Medicine
#7
of 10 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,060 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 340,721 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.