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Current challenges facing the assessment of the allergenic capacity of food allergens in animal models

Overview of attention for article published in Clinical and Translational Allergy, June 2016
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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 (74th percentile)

Mentioned by

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9 tweeters
facebook
3 Facebook pages

Citations

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39 Dimensions

Readers on

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118 Mendeley
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Title
Current challenges facing the assessment of the allergenic capacity of food allergens in animal models
Published in
Clinical and Translational Allergy, June 2016
DOI 10.1186/s13601-016-0110-2
Pubmed ID
Authors

Katrine Lindholm Bøgh, Jolanda van Bilsen, Robert Głogowski, Iván López-Expósito, Grégory Bouchaud, Carine Blanchard, Marie Bodinier, Joost Smit, Raymond Pieters, Shanna Bastiaan-Net, Nicole de Wit, Eva Untersmayr, Karine Adel-Patient, Leon Knippels, Michelle M. Epstein, Mario Noti, Unni Cecilie Nygaard, Ian Kimber, Kitty Verhoeckx, Liam O’Mahony

Abstract

Food allergy is a major health problem of increasing concern. The insufficiency of protein sources for human nutrition in a world with a growing population is also a significant problem. The introduction of new protein sources into the diet, such as newly developed innovative foods or foods produced using new technologies and production processes, insects, algae, duckweed, or agricultural products from third countries, creates the opportunity for development of new food allergies, and this in turn has driven the need to develop test methods capable of characterizing the allergenic potential of novel food proteins. There is no doubt that robust and reliable animal models for the identification and characterization of food allergens would be valuable tools for safety assessment. However, although various animal models have been proposed for this purpose, to date, none have been formally validated as predictive and none are currently suitable to test the allergenic potential of new foods. Here, the design of various animal models are reviewed, including among others considerations of species and strain, diet, route of administration, dose and formulation of the test protein, relevant controls and endpoints measured.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters 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 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 <1%
Germany 1 <1%
France 1 <1%
Unknown 115 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 19%
Student > Ph. D. Student 22 19%
Student > Master 12 10%
Student > Bachelor 10 8%
Other 5 4%
Other 13 11%
Unknown 33 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 25%
Immunology and Microbiology 20 17%
Biochemistry, Genetics and Molecular Biology 10 8%
Medicine and Dentistry 6 5%
Pharmacology, Toxicology and Pharmaceutical Science 4 3%
Other 10 8%
Unknown 39 33%

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 30 December 2016.
All research outputs
#4,581,609
of 19,191,377 outputs
Outputs from Clinical and Translational Allergy
#247
of 558 outputs
Outputs of similar age
#68,549
of 272,774 outputs
Outputs of similar age from Clinical and Translational Allergy
#1
of 1 outputs
Altmetric has tracked 19,191,377 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 558 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one has gotten more attention than average, scoring higher than 55% 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 272,774 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them