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To Supplement or Not to Supplement: A Metabolic Network Framework for Human Nutritional Supplements

Overview of attention for article published in PLOS ONE, August 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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28 X users
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4 Facebook pages
reddit
1 Redditor

Citations

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15 Dimensions

Readers on

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59 Mendeley
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2 CiteULike
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Title
To Supplement or Not to Supplement: A Metabolic Network Framework for Human Nutritional Supplements
Published in
PLOS ONE, August 2013
DOI 10.1371/journal.pone.0068751
Pubmed ID
Authors

Christopher D. Nogiec, Simon Kasif

Abstract

Flux balance analysis and constraint based modeling have been successfully used in the past to elucidate the metabolism of single cellular organisms. However, limited work has been done with multicellular organisms and even less with humans. The focus of this paper is to present a novel use of this technique by investigating human nutrition, a challenging field of study. Specifically, we present a steady state constraint based model of skeletal muscle tissue to investigate amino acid supplementation's effect on protein synthesis. We implement several in silico supplementation strategies to study whether amino acid supplementation might be beneficial for increasing muscle contractile protein synthesis. Concurrent with published data on amino acid supplementation's effect on protein synthesis in a post resistance exercise state, our results suggest that increasing bioavailability of methionine, arginine, and the branched-chain amino acids can increase the flux of contractile protein synthesis. The study also suggests that a common commercial supplement, glutamine, is not an effective supplement in the context of increasing protein synthesis and thus, muscle mass. Similar to any study in a model organism, the computational modeling of this research has some limitations. Thus, this paper introduces the prospect of using systems biology as a framework to formally investigate how supplementation and nutrition can affect human metabolism and physiology.

X Demographics

X Demographics

The data shown below were collected from the profiles of 28 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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Greece 1 2%
Peru 1 2%
Singapore 1 2%
Unknown 56 95%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 13 22%
Student > Ph. D. Student 10 17%
Student > Master 7 12%
Researcher 6 10%
Lecturer 4 7%
Other 13 22%
Unknown 6 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 31%
Sports and Recreations 10 17%
Biochemistry, Genetics and Molecular Biology 8 14%
Medicine and Dentistry 8 14%
Engineering 2 3%
Other 4 7%
Unknown 9 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 07 November 2016.
All research outputs
#2,004,147
of 25,853,983 outputs
Outputs from PLOS ONE
#24,342
of 225,411 outputs
Outputs of similar age
#16,522
of 209,970 outputs
Outputs of similar age from PLOS ONE
#593
of 4,878 outputs
Altmetric has tracked 25,853,983 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 225,411 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.9. This one has done well, scoring higher than 89% 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 209,970 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 4,878 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.