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Dextran coated silver nanoparticles — Chemical sensor for selective cysteine detection

Overview of attention for article published in Colloids & Surfaces B: Biointerfaces, December 2017
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Citations

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44 Mendeley
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Title
Dextran coated silver nanoparticles — Chemical sensor for selective cysteine detection
Published in
Colloids & Surfaces B: Biointerfaces, December 2017
DOI 10.1016/j.colsurfb.2017.09.031
Pubmed ID
Authors

Slađana Davidović, Vesna Lazić, Ivana Vukoje, Jelena Papan, S.Phillip Anhrenkiel, Suzana Dimitrijević, Jovan M. Nedeljković

Abstract

A simple, fast and non-costly method for selective cysteine (Cys) detection, based on optical changes of silver colloids, is developed. For that purpose, stable colloids consisting of silver nanoparticles (Ag NPs) coated with polysaccharide dextran (Dex), isolated from bacterium species Leuconostoc mesenteroides T3, were prepared. The synthesized samples were thoroughly characterized including absorption and FTIR spectroscopy, as well as transmission electron microscopy and X-ray diffraction analysis. The silver colloids display high sensitivity and selectivity towards Cys detection in aqueous solutions. The Ag NPs coated with Dex provide possibility to detect Cys among a dozen amino acids and its detection limit was found to be 12.0μM. The sensing mechanism - red shift of optical absorption - is discussed in terms of the agglomeration of Ag NPs due to formation of hydrogen bonds between Cys molecules attached to different Ag NPs.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 30%
Student > Bachelor 5 11%
Researcher 4 9%
Student > Master 3 7%
Professor > Associate Professor 3 7%
Other 7 16%
Unknown 9 20%
Readers by discipline Count As %
Chemistry 6 14%
Agricultural and Biological Sciences 5 11%
Biochemistry, Genetics and Molecular Biology 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Engineering 2 5%
Other 8 18%
Unknown 17 39%

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 16 September 2017.
All research outputs
#9,808,203
of 12,278,153 outputs
Outputs from Colloids & Surfaces B: Biointerfaces
#1,004
of 1,599 outputs
Outputs of similar age
#175,037
of 238,656 outputs
Outputs of similar age from Colloids & Surfaces B: Biointerfaces
#18
of 50 outputs
Altmetric has tracked 12,278,153 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,599 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 23rd percentile – i.e., 23% 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 238,656 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.