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RNA sequencing from human neutrophils reveals distinct transcriptional differences associated with chronic inflammatory states

Overview of attention for article published in BMC Medical Genomics, August 2015
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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 (76th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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2 patents

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106 Mendeley
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Title
RNA sequencing from human neutrophils reveals distinct transcriptional differences associated with chronic inflammatory states
Published in
BMC Medical Genomics, August 2015
DOI 10.1186/s12920-015-0128-7
Pubmed ID
Authors

Kaiyu Jiang, Xiaoyun Sun, Yanmin Chen, Yufeng Shen, James N. Jarvis

Abstract

The transcriptional complexity of mammalian cells suggests that they have broad abilities to respond to specific environmental stimuli and physiologic contexts. These abilities were not apparent a priori from the structure of mammalian genomes, but have been identified through detailed transcriptome analyses. In this study, we examined the transcriptomes of cells of the innate immune system, human neutrophils, using RNA sequencing (RNAseq). We sequenced poly-A RNA from nine individual samples corresponding to specific phenotypes: three children with active, untreated juvenile idiopathic arthritis (JIA)(AD), three children with the same disease whose disease was inactive on medication (CRM), and three children with cystic fibrosis (CF). We demonstrate that transcriptomes of neutrophils, typically considered non-specific in their responses and functions, display considerable specificity in their transcriptional repertoires dependent on the pathologic context, and included genes, gene isoforms, and long non-coding RNA transcripts. Furthermore, despite the small sample numbers, these findings demonstrate the potential of RNAseq approaches to biomarker development in rheumatic diseases. These data demonstrate the capacity of cells previously considered non-specific in function to adapt their transcriptomes to specific biologic contexts. These data also provide insight into previously unrecognized pathological pathways and show considerable promise for elucidating disease and disease-state specific regulatory networks.

X Demographics

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The data shown below were collected from the profiles of 6 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 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
Sweden 1 <1%
Canada 1 <1%
Unknown 103 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 32%
Researcher 22 21%
Student > Bachelor 10 9%
Student > Doctoral Student 6 6%
Student > Master 6 6%
Other 15 14%
Unknown 13 12%
Readers by discipline Count As %
Immunology and Microbiology 22 21%
Agricultural and Biological Sciences 22 21%
Medicine and Dentistry 18 17%
Biochemistry, Genetics and Molecular Biology 13 12%
Neuroscience 3 3%
Other 12 11%
Unknown 16 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 30 July 2020.
All research outputs
#5,455,532
of 22,826,360 outputs
Outputs from BMC Medical Genomics
#244
of 1,223 outputs
Outputs of similar age
#63,629
of 267,486 outputs
Outputs of similar age from BMC Medical Genomics
#7
of 17 outputs
Altmetric has tracked 22,826,360 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,223 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 79% 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 267,486 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 76% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.