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Synthesis of Molecularly Imprinted Polymer Nanoparticles for α‑Casein Detection Using Surface Plasmon Resonance as a Milk Allergen Sensor

Overview of attention for article published in ACS Sensors, January 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

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5 X users
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113 Mendeley
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Title
Synthesis of Molecularly Imprinted Polymer Nanoparticles for α‑Casein Detection Using Surface Plasmon Resonance as a Milk Allergen Sensor
Published in
ACS Sensors, January 2018
DOI 10.1021/acssensors.7b00850
Pubmed ID
Authors

Jon Ashley, Yunus Shukor, Roberta D’Aurelio, Linda Trinh, Thomas L. Rodgers, Jeff Temblay, Mike Pleasants, Ibtisam E. Tothill

Abstract

Food recalls due to undeclared allergens or contamination are costly to the food manufacturing industry worldwide. As the industry strives for better manufacturing efficiencies over a diverse range of food products, there is a need for the development of new analytical techniques to improve monitoring the presence of unintended food allergens during the food manufacturing process. In particular, the monitoring of wash samples from cleaning in place systems (CIP), used in the cleaning of food processing equipment, would allow for the effective removal of allergen containing ingredients in between food batches. Casein proteins constitute the biggest group of proteins in milk and hence are the most commonly milk protein allergen in food ingredients. As such, these proteins could present an ideal analyte for cleaning validation. In this work, molecularly imprinted polymer-nanoparticles (nanoMIPs) with high affinity towards bovine α-casein were synthesized using solid-phase imprinting method. The nanoMIPs were then characterized and incorporated into label free surface plasmon resonance (SPR) based sensor. The nanoMIPs demonstrated good binding affinity and selectivity towards α-casein (KD ~10 x 10-9 M). This simple affinity sensor demonstrated the quantitative detection of α-casein achieving a detection limit of 127 ± 97.6 ng ml-1 (0.127 ppm) which is far superior to existing commercially available ELISA kits. Recoveries from spiked CIP waste water samples were within the acceptable range (87-120%). The reported sensor could allow food manufacturers to adequately monitor and manage food allergen risk in food processing environments while insuring that the food produced is safe for the consumer.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 113 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 19%
Researcher 14 12%
Student > Master 13 12%
Student > Doctoral Student 5 4%
Student > Bachelor 5 4%
Other 17 15%
Unknown 38 34%
Readers by discipline Count As %
Chemistry 21 19%
Agricultural and Biological Sciences 16 14%
Engineering 8 7%
Biochemistry, Genetics and Molecular Biology 5 4%
Unspecified 3 3%
Other 12 11%
Unknown 48 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 29 December 2021.
All research outputs
#5,407,105
of 25,382,440 outputs
Outputs from ACS Sensors
#462
of 2,530 outputs
Outputs of similar age
#110,752
of 449,669 outputs
Outputs of similar age from ACS Sensors
#18
of 92 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,530 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one has done well, scoring higher than 81% 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 449,669 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 75% of its contemporaries.
We're also able to compare this research output to 92 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.