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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comparison Between the Fecal Bacterial Microbiota of Healthy and Diarrheic Captive Musk Deer
|
|---|---|
| Published in |
Frontiers in Microbiology, March 2018
|
| DOI | 10.3389/fmicb.2018.00300 |
| Pubmed ID | |
| Authors |
Yimeng Li, Xiaolong Hu, Shuang Yang, Juntong Zhou, Lei Qi, Xiaoning Sun, Mengyuan Fan, Shanghua Xu, Muha Cha, Meishan Zhang, Shaobi Lin, Shuqiang Liu, Defu Hu |
| Abstract |
Diarrhea constitutes one of the most common diseases affecting the survival of captive musk deer and is usually caused by an imbalance in intestinal microbiota. Currently, research regarding the structure and function of intestinal microbiota in diarrheic musk deer is lacking. Therefore, in the present study, high-throughput 16S-rRNA gene sequencing was used to analyze the intestinal microbiota in feces of healthy captive musk deer (HMD) (n= 8) and musk deer with mild (MMD) (n= 8), and severe (n= 5) (SMD) diarrhea to compare the difference in intestinal microbiota of musk deer under various physiological conditions. The results showed that the diversity of HMD fecal microbiota was significantly higher than that of the two diarrhea samples. β Diversity results indicated that there were extremely significant differences in bacterial communities between the HMD sample and the MMD and SMD samples. However, no significant difference was found between the two diarrhea samples. LefSe analysis showed that the degree of intestinal physiological dysfunction in musk deer was correlated with the types of major pathogens. The main pathogen in the MMD group isEscherichia-Shigella, whereasFusobacteriumis the main pathogen in the SMD group. PICRUSt functional profile prediction indicated that the intestinal microbiota disorder could also lead to changes in the abundance of genes in metabolic pathways of the immune system. Altogether, this study provides a theoretical basis for the exploration of treatments for diarrhea in captive musk deer, which is of considerable significance to the implementation of the musk deer release into the wild program. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 70 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 23% |
| Student > Ph. D. Student | 11 | 16% |
| Student > Bachelor | 6 | 9% |
| Student > Master | 5 | 7% |
| Professor | 4 | 6% |
| Other | 9 | 13% |
| Unknown | 19 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 21% |
| Immunology and Microbiology | 8 | 11% |
| Biochemistry, Genetics and Molecular Biology | 6 | 9% |
| Environmental Science | 4 | 6% |
| Engineering | 3 | 4% |
| Other | 10 | 14% |
| Unknown | 24 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 20 March 2018.
All research outputs
#17,934,709
of 23,028,364 outputs
Outputs from Frontiers in Microbiology
#17,434
of 25,154 outputs
Outputs of similar age
#241,106
of 331,406 outputs
Outputs of similar age from Frontiers in Microbiology
#443
of 588 outputs
Altmetric has tracked 23,028,364 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 25,154 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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 331,406 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 588 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.