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Landscape of transcription and long non-coding RNAs reveals new insights into the inflammatory and fibrotic response following ventilator-induced lung injury

Overview of attention for article published in Respiratory Research, June 2018
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5 tweeters

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Title
Landscape of transcription and long non-coding RNAs reveals new insights into the inflammatory and fibrotic response following ventilator-induced lung injury
Published in
Respiratory Research, June 2018
DOI 10.1186/s12931-018-0822-z
Pubmed ID
Authors

Lu Wang, Nannan Zhang, Yi Zhang, Jingen Xia, Qingyuan Zhan, Chen Wang

Abstract

Mechanical ventilation can cause ventilator-induced lung injury (VILI) and lung fibrosis; however, the underlying mechanisms are still not fully understood. RNA sequencing is a powerful means for detecting vitally important protein-coding transcripts and long non-coding RNAs (lncRNAs) on a genome-wide scale, which may be helpful for reducing this knowledge gap. Ninety C57BL/6 mice were subjected to either high tidal volume ventilation or sham operation, and then mice with ventilation were randomly allocated to periods of recovery for 0, 1, 3, 5, 7, 14, 21, or 28 days. Lung histopathology, wet-to-dry weight ratio, hydroxyproline concentration, and transforming growth factor beta 1 (TGF-β1) levels were determined to evaluate the progression of inflammation and fibrosis. To compare sham-operated lungs, and 0- and 7-day post-ventilated lungs, RNA sequencing was used to elucidate the expression patterns, biological processes, and functional pathways involved in inflammation and fibrosis. A well-defined fibrotic response was most pronounced on day 7 post-ventilation. Pairwise comparisons among the sham and VILI groups showed a total of 1297 differentially expressed transcripts (DETs). Gene Ontology analysis determined that the stimulus response and immune response were the most important factors involved in inflammation and fibrosis, respectively. Kyoto Encyclopedia of Genes and Genomes analysis revealed that mechanistic target of rapamycin (mTOR), Janus kinase-signal transducer and activator of transcription (JAK/STAT), and cyclic adenosine monophosphate (cAMP) signaling were implicated in early inflammation; whereas TGF-β, hypoxia inducible factor-1 (HIF-1), Toll-like receptor (TLR), and kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathways were significantly involved in subsequent fibrosis. Additionally, 332 DE lncRNAs were identified and enriched in the processes of cellular and biological regulation. These lncRNAs may potentially regulate fibrosis through signaling pathways such as wingless/integrase-1 (Wnt), HIF-1, and TLR. This is the first transcriptome study to reveal all of the transcript expression patterns and critical pathways involved in the VILI fibrotic process based on the early inflammatory state, and to show the important DE lncRNAs regulated in inflammation and fibrosis. Together, the results of this study provide novel perspectives into the potential molecular mechanisms underlying VILI and subsequent fibrosis.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 25%
Other 2 17%
Student > Bachelor 1 8%
Student > Ph. D. Student 1 8%
Student > Postgraduate 1 8%
Other 0 0%
Unknown 4 33%
Readers by discipline Count As %
Medicine and Dentistry 7 58%
Nursing and Health Professions 1 8%
Immunology and Microbiology 1 8%
Computer Science 1 8%
Unknown 2 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 23 June 2018.
All research outputs
#8,604,987
of 14,995,047 outputs
Outputs from Respiratory Research
#1,068
of 1,864 outputs
Outputs of similar age
#136,462
of 274,645 outputs
Outputs of similar age from Respiratory Research
#1
of 1 outputs
Altmetric has tracked 14,995,047 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,864 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 38th percentile – i.e., 38% 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 274,645 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them