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Antibiotic perturbation of the murine gut microbiome enhances the adiposity, insulin resistance, and liver disease associated with high-fat diet

Overview of attention for article published in Genome Medicine, April 2016
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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 (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

blogs
1 blog
twitter
12 tweeters

Citations

dimensions_citation
135 Dimensions

Readers on

mendeley
248 Mendeley
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Title
Antibiotic perturbation of the murine gut microbiome enhances the adiposity, insulin resistance, and liver disease associated with high-fat diet
Published in
Genome Medicine, April 2016
DOI 10.1186/s13073-016-0297-9
Pubmed ID
Authors

Douglas Mahana, Chad M. Trent, Zachary D. Kurtz, Nicholas A. Bokulich, Thomas Battaglia, Jennifer Chung, Christian L. Müller, Huilin Li, Richard A. Bonneau, Martin J. Blaser

Abstract

Obesity, type 2 diabetes, and non-alcoholic fatty liver disease (NAFLD) are serious health concerns, especially in Western populations. Antibiotic exposure and high-fat diet (HFD) are important and modifiable factors that may contribute to these diseases. To investigate the relationship of antibiotic exposure with microbiome perturbations in a murine model of growth promotion, C57BL/6 mice received lifelong sub-therapeutic antibiotic treatment (STAT), or not (control), and were fed HFD starting at 13 weeks. To characterize microbiota changes caused by STAT, the V4 region of the 16S rRNA gene was examined from collected fecal samples and analyzed. In this model, which included HFD, STAT mice developed increased weight and fat mass compared to controls. Although results in males and females were not identical, insulin resistance and NAFLD were more severe in the STAT mice. Fecal microbiota from STAT mice were distinct from controls. Compared with controls, STAT exposure led to early conserved diet-independent microbiota changes indicative of an immature microbial community. Key taxa were identified as STAT-specific and several were found to be predictive of disease. Inferred network models showed topological shifts concurrent with growth promotion and suggest the presence of keystone species. These studies form the basis for new models of type 2 diabetes and NAFLD that involve microbiome perturbation.

Twitter Demographics

The data shown below were collected from the profiles of 12 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 248 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
Greece 1 <1%
Thailand 1 <1%
Brazil 1 <1%
Unknown 242 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 21%
Researcher 42 17%
Student > Master 36 15%
Student > Bachelor 31 13%
Professor > Associate Professor 10 4%
Other 34 14%
Unknown 44 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 52 21%
Biochemistry, Genetics and Molecular Biology 37 15%
Medicine and Dentistry 28 11%
Immunology and Microbiology 19 8%
Nursing and Health Professions 8 3%
Other 50 20%
Unknown 54 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 09 May 2016.
All research outputs
#2,417,813
of 22,865,319 outputs
Outputs from Genome Medicine
#562
of 1,443 outputs
Outputs of similar age
#41,002
of 299,013 outputs
Outputs of similar age from Genome Medicine
#20
of 35 outputs
Altmetric has tracked 22,865,319 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,443 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one has gotten more attention than average, scoring higher than 60% 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 299,013 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 86% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.