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Metabolic fingerprints of human primary endothelial and fibroblast cells

Overview of attention for article published in Metabolomics, April 2016
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Metabolic fingerprints of human primary endothelial and fibroblast cells
Published in
Metabolomics, April 2016
DOI 10.1007/s11306-016-1024-7
Pubmed ID
Authors

Polona Žigon, Katjuša Mrak-Poljšak, Katja Lakota, Matic Terčelj, Saša Čučnik, Matija Tomsic, Snezna Sodin-Semrl

Abstract

Human primary cells originating from different locations within the body could differ greatly in their metabolic phenotypes, influencing both how they act during physiological/pathological processes and how susceptible/resistant they are to a variety of disease risk factors. A novel way to monitor cellular metabolism is through cell energetics assays, so we explored this approach with human primary cell types, as models of sclerotic disorders. In order to better understand pathophysiological processes at the cellular level, our goals were to measure metabolic pathway activities of endothelial cells and fibroblasts, and determine their metabolic phenotype profiles. Biolog Phenotype MicroArray™ technology was used for the first time to characterize metabolic phenotypes of diverse primary cells. These colorimetric assays enable detection of utilization of 367 specific biochemical substrates by human endothelial cells from the coronary artery (HCAEC), umbilical vein (HUVEC) and normal, healthy lung fibroblasts (NHLF). Adenosine, inosine, d-mannose and dextrin were strongly utilized by all three cell types, comparable to glucose. Substrates metabolized solely by HCAEC were mannan, pectin, gelatin and prevalently tricarballylic acid. HUVEC did not show any uniquely metabolized substrates whereas NHLF exhibited strong utilization of sugars and carboxylic acids along with amino acids and peptides. Taken together, we show for the first time that this simple energetics assay platform enables metabolic characterization of primary cells and that each of the three human cell types examined gives a unique and distinguishable profile.

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The data shown below were collected from the profiles of 3 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 4%
Unknown 27 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 18%
Student > Bachelor 5 18%
Student > Master 5 18%
Student > Doctoral Student 2 7%
Professor 2 7%
Other 6 21%
Unknown 3 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 29%
Biochemistry, Genetics and Molecular Biology 5 18%
Medicine and Dentistry 3 11%
Neuroscience 2 7%
Social Sciences 1 4%
Other 3 11%
Unknown 6 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 October 2018.
All research outputs
#13,379,977
of 22,889,074 outputs
Outputs from Metabolomics
#655
of 1,296 outputs
Outputs of similar age
#145,588
of 301,023 outputs
Outputs of similar age from Metabolomics
#24
of 47 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,296 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 49th percentile – i.e., 49% 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 301,023 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.