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A bioelectronic sensor based on canine olfactory nanovesicle– carbon nanotube hybrid structures for the fast assessment of food quality

Overview of attention for article published in Analyst, April 2012
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2 X users

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Title
A bioelectronic sensor based on canine olfactory nanovesicle– carbon nanotube hybrid structures for the fast assessment of food quality
Published in
Analyst, April 2012
DOI 10.1039/c2an16274a
Pubmed ID
Authors

Juhun Park, Jong Hyun Lim, Hye Jun Jin, Seon Namgung, Sang Hun Lee, Tai Hyun Park, Seunghun Hong

Abstract

We developed an olfactory-nanovesicle-fused carbon-nanotube-transistor biosensor (OCB) that mimics the responses of a canine nose for the sensitive and selective detection of hexanal, an indicator of the oxidation of food. OCBs allowed us to detect hexanal down to 1 fM concentration in real-time. Significantly, we demonstrated the detection of hexanal with an excellent selectivity capable of discriminating hexanal from analogous compounds such as pentanal, heptanal, and octanal. Furthermore, we successfully detected hexanal in spoiled milk without any pretreatment processes. Considering these results, our sensor platform should offer a new method for the assessment of food quality and contribute to the development of portable sensing devices.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 2 2%
United Kingdom 1 1%
Spain 1 1%
France 1 1%
Unknown 82 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 20%
Researcher 15 17%
Student > Master 11 13%
Student > Bachelor 11 13%
Student > Postgraduate 4 5%
Other 10 11%
Unknown 19 22%
Readers by discipline Count As %
Engineering 25 29%
Chemistry 11 13%
Agricultural and Biological Sciences 8 9%
Biochemistry, Genetics and Molecular Biology 7 8%
Physics and Astronomy 3 3%
Other 10 11%
Unknown 23 26%
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 20 June 2012.
All research outputs
#17,285,036
of 25,371,288 outputs
Outputs from Analyst
#4,117
of 6,119 outputs
Outputs of similar age
#113,242
of 174,046 outputs
Outputs of similar age from Analyst
#35
of 74 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,119 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 25th percentile – i.e., 25% 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 174,046 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.