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About this Attention Score

  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

patent
10 patents

Readers on

mendeley
46 Mendeley
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Article details
Title
One-pot bioinspired synthesis of all-inclusive protein–protein nanoflowers for point-of-care bioassay: detection of E. coli O157:H7 from milk
Published in
Nanoscale, January 2016
DOI 10.1039/c6nr06870g
Pubmed ID
Authors
Abstract

Protein-protein conjugates play a vital role in bioassays with their inherent functions of biological recognition and signal amplification. Herein, a one-pot green method for synthesis of all-inclusive protein-protein nanoflowers has been developed. The protein-protein nanoflowers integrate both essential functions of biological recognition and signal amplification, and they were used as ideal signal labels for the sensitive point-of-care detection of Escherichia coli O157:H7. Especially noteworthy, the prepared Con A-invertase-CaHPO4 hybrid nanoflowers simultaneously loaded sufficient invertase and enhanced the activity of the immobilized invertase, which fits well with the requirements of signal labels for bioassays. Due to the conversion of sucrose to glucose by invertase, Con A-invertase-CaHPO4 hybrid nanoflowers were successfully used for the reliable point-of-care detection of food pathogens by a personal glucose meter. The presented approach successfully resolved the bottleneck in preparing protein-protein conjugate-based signal labels for bioassays using enzyme-based signal amplification strategies, which holds great promise to develop on-demand protein-protein conjugates for a variety of applications extending from biosensors and biomedicine to energy, environmental monitoring and remediation.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 7 15%
Student > Ph. D. Student 6 13%
Other 3 7%
Professor 3 7%
Lecturer 2 4%
Other 6 13%
Unknown 19 41%
Readers by discipline
Readers by discipline Count As %
Chemistry 8 17%
Biochemistry, Genetics and Molecular Biology 4 9%
Chemical Engineering 3 7%
Engineering 3 7%
Agricultural and Biological Sciences 2 4%
Other 4 9%
Unknown 22 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 14 June 2022.
All research outputs
#6,542,369
of 30,202,275 outputs
Outputs from Nanoscale
#1,625
of 12,901 outputs
Outputs of similar age
#87,418
of 412,009 outputs
Outputs of similar age from Nanoscale
#127
of 781 outputs
Altmetric has tracked 30,202,275 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 12,901 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 84% of its peers.
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 412,009 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 781 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.