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Quantitative prediction of shrimp disease incidence via the profiles of gut eukaryotic microbiota

Overview of attention for article published in Applied Microbiology and Biotechnology, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

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54 Mendeley
Title
Quantitative prediction of shrimp disease incidence via the profiles of gut eukaryotic microbiota
Published in
Applied Microbiology and Biotechnology, March 2018
DOI 10.1007/s00253-018-8874-z
Pubmed ID
Authors

Jinbo Xiong, Weina Yu, Wenfang Dai, Jinjie Zhang, Qiongfen Qiu, Changrong Ou

Abstract

One common notion is emerging that gut eukaryotes are commensal or beneficial, rather than detrimental. To date, however, surprisingly few studies have been taken to discern the factors that govern the assembly of gut eukaryotes, despite growing interest in the dysbiosis of gut microbiota-disease relationship. Herein, we firstly explored how the gut eukaryotic microbiotas were assembled over shrimp postlarval to adult stages and a disease progression. The gut eukaryotic communities changed markedly as healthy shrimp aged, and converged toward an adult-microbiota configuration. However, the adult-like stability was distorted by disease exacerbation. A null model untangled that the deterministic processes that governed the gut eukaryotic assembly tended to be more important over healthy shrimp development, whereas this trend was inverted as the disease progressed. After ruling out the baseline of gut eukaryotes over shrimp ages, we identified disease-discriminatory taxa (species level afforded the highest accuracy of prediction) that characteristic of shrimp health status. The profiles of these taxa contributed an overall 92.4% accuracy in predicting shrimp health status. Notably, this model can accurately diagnose the onset of shrimp disease. Interspecies interaction analysis depicted how the disease-discriminatory taxa interacted with one another in sustaining shrimp health. Taken together, our findings offer novel insights into the underlying ecological processes that govern the assembly of gut eukaryotes over shrimp postlarval to adult stages and a disease progression. Intriguingly, the established model can quantitatively and accurately predict the incidences of shrimp disease.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 17%
Student > Ph. D. Student 7 13%
Student > Master 7 13%
Student > Bachelor 5 9%
Student > Postgraduate 4 7%
Other 7 13%
Unknown 15 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 33%
Biochemistry, Genetics and Molecular Biology 6 11%
Medicine and Dentistry 3 6%
Immunology and Microbiology 3 6%
Environmental Science 1 2%
Other 4 7%
Unknown 19 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 22 September 2018.
All research outputs
#3,964,151
of 24,119,703 outputs
Outputs from Applied Microbiology and Biotechnology
#946
of 8,034 outputs
Outputs of similar age
#75,252
of 334,796 outputs
Outputs of similar age from Applied Microbiology and Biotechnology
#22
of 144 outputs
Altmetric has tracked 24,119,703 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,034 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 88% 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 334,796 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 77% of its contemporaries.
We're also able to compare this research output to 144 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.