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Mapping surface charge density of lipid bilayers by quantitative surface conductivity microscopy

Overview of attention for article published in Nature Communications, August 2016
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Title
Mapping surface charge density of lipid bilayers by quantitative surface conductivity microscopy
Published in
Nature Communications, August 2016
DOI 10.1038/ncomms12447
Pubmed ID
Authors

Lasse Hyldgaard Klausen, Thomas Fuhs, Mingdong Dong

Abstract

Local surface charge density of lipid membranes influences membrane-protein interactions leading to distinct functions in all living cells, and it is a vital parameter in understanding membrane-binding mechanisms, liposome design and drug delivery. Despite the significance, no method has so far been capable of mapping surface charge densities under physiologically relevant conditions. Here, we use a scanning nanopipette setup (scanning ion-conductance microscope) combined with a novel algorithm to investigate the surface conductivity near supported lipid bilayers, and we present a new approach, quantitative surface conductivity microscopy (QSCM), capable of mapping surface charge density with high-quantitative precision and nanoscale resolution. The method is validated through an extensive theoretical analysis of the ionic current at the nanopipette tip, and we demonstrate the capacity of QSCM by mapping the surface charge density of model cationic, anionic and zwitterionic lipids with results accurately matching theoretical values.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 171 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Denmark 1 <1%
Unknown 169 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 46 27%
Researcher 27 16%
Student > Master 23 13%
Student > Doctoral Student 11 6%
Professor > Associate Professor 9 5%
Other 22 13%
Unknown 33 19%
Readers by discipline Count As %
Chemistry 32 19%
Engineering 27 16%
Biochemistry, Genetics and Molecular Biology 18 11%
Physics and Astronomy 12 7%
Materials Science 10 6%
Other 30 18%
Unknown 42 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 26 August 2016.
All research outputs
#15,381,871
of 22,884,315 outputs
Outputs from Nature Communications
#42,132
of 47,135 outputs
Outputs of similar age
#216,032
of 338,621 outputs
Outputs of similar age from Nature Communications
#759
of 864 outputs
Altmetric has tracked 22,884,315 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 47,135 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.8. This one is in the 8th percentile – i.e., 8% 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 338,621 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 864 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.