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Towards an Integrative Understanding of Diet–Host–Gut Microbiome Interactions

Overview of attention for article published in Frontiers in immunology, May 2017
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  • 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 (95th percentile)

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Title
Towards an Integrative Understanding of Diet–Host–Gut Microbiome Interactions
Published in
Frontiers in immunology, May 2017
DOI 10.3389/fimmu.2017.00538
Pubmed ID
Authors

Mark N. Read, Andrew J. Holmes

Abstract

Over the last 20 years, a sizeable body of research has linked the microbiome and host diet to a remarkable diversity of diseases. Yet, unifying principles of microbiome assembly or function, at levels required to rationally manipulate a specific individual's microbiome to their benefit, have not emerged. A key driver of both community composition and activity is the host diet, but diet-microbiome interactions cannot be characterized without consideration of host-diet interactions such as appetite and digestion. This becomes even more complex if health outcomes are to be explored, as microbes engage in multiple interactions and feedback pathways with the host. Here, we review these interactions and set forth the need to build conceptual models of the diet-microbiome-host axes that draw out the key principles governing this system's dynamics. We highlight how "units of response," characterizations of similarly behaving microbes, do not correlate consistently with microbial sequence relatedness, raising a challenge for relating high-throughput data sets to conceptual models. Furthermore, they are question-specific; responses to resource environment may be captured at higher taxonomic levels, but capturing microbial products that depend on networks of different interacting populations, such as short-chain fatty acid production through anaerobic fermentation, can require consideration of the entire community. We posit that integrative approaches to teasing apart diet-microbe-host interactions will help bridge between experimental data sets and conceptual models and will be of value in formulating predictive models.

X Demographics

X Demographics

The data shown below were collected from the profiles of 42 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 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 <1%
Unknown 122 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 20%
Student > Ph. D. Student 21 17%
Student > Master 13 11%
Student > Doctoral Student 8 7%
Student > Bachelor 8 7%
Other 23 19%
Unknown 26 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 28%
Biochemistry, Genetics and Molecular Biology 18 15%
Medicine and Dentistry 17 14%
Immunology and Microbiology 4 3%
Nursing and Health Professions 3 2%
Other 16 13%
Unknown 31 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 30. 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 July 2017.
All research outputs
#1,297,682
of 25,382,440 outputs
Outputs from Frontiers in immunology
#1,127
of 31,531 outputs
Outputs of similar age
#25,275
of 324,786 outputs
Outputs of similar age from Frontiers in immunology
#19
of 389 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 31,531 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done particularly well, scoring higher than 96% 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 324,786 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 389 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.