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Employment of digital gene expression profiling to identify potential pathogenic and therapeutic targets of fulminant hepatic failure

Overview of attention for article published in Journal of Translational Medicine, January 2015
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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2 X users
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1 Wikipedia page

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10 Mendeley
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Title
Employment of digital gene expression profiling to identify potential pathogenic and therapeutic targets of fulminant hepatic failure
Published in
Journal of Translational Medicine, January 2015
DOI 10.1186/s12967-015-0380-9
Pubmed ID
Authors

En-Qiang Chen, Lang Bai, Dao-Yin Gong, Hong Tang

Abstract

BackgroundThe dysregulated cytokine metabolism and activity are crucial to the development of fulminant hepatic failure (FHF), and many different cytokines have been identified. However, the precise gene expression profile and their interactions association with FHF are yet to be further elucidated.MethodsIn this study, we detected the digital gene expression profile (DGEP) by high-throughput sequencing in normal and FHF mouse liver, and the candidate genes and potential targets for FHF therapy were verified. And the FHF mouse model was induced by D-Galactosamine (GalN)/lipopolysaccharide (LPS).ResultsTotally 12727 genes were detected, and 3551 differentially expressed genes (DEGs) were obtained from RNA-seq data in FHF mouse liver. In FHF mouse liver, many of those DEGs were identified as differentially expressed in metabolic process, biosynthetic process, response to stimulus and response to stress, etc. Similarly, pathway enrichment analysis in FHF mouse liver showed that many significantly DEGs were also enriched in metabolic pathways, apoptosis, chemokine signaling pathways, etc. Considering the important role of nuclear factor-kappa B (NF-¿B) in metabolic regulation and delicate balance between cell survival and death, several DEGs involved in NF-¿B pathway were selected for experimental validation. As compared to normal control, NF-¿Bp65 and its inhibitory protein I¿B¿ were both significantly increased, and NF-¿B targeted genes including tumor necrosis factor ¿(TNF¿), inducible nitric oxide synthase (iNOS), interleukin-1ß, chemokines CCL3 and CCL4 were also increased in hepatic tissues of FHF. In addition, after NF-¿B was successfully pre-blocked, there were significant alteration of hepatic pathological damage and mortality of FHF mouse model.ConclusionsThis study provides the globe gene expression profile of FHF mouse liver, and demonstrates the possibility of NF-¿B gene as a potential therapeutic target for FHF.

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The data shown below were collected from the profiles of 2 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 20%
Student > Bachelor 1 10%
Student > Ph. D. Student 1 10%
Professor 1 10%
Researcher 1 10%
Other 1 10%
Unknown 3 30%
Readers by discipline Count As %
Medicine and Dentistry 2 20%
Nursing and Health Professions 2 20%
Pharmacology, Toxicology and Pharmaceutical Science 1 10%
Psychology 1 10%
Engineering 1 10%
Other 0 0%
Unknown 3 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 04 May 2019.
All research outputs
#6,946,945
of 22,780,165 outputs
Outputs from Journal of Translational Medicine
#1,085
of 3,987 outputs
Outputs of similar age
#96,667
of 352,883 outputs
Outputs of similar age from Journal of Translational Medicine
#29
of 112 outputs
Altmetric has tracked 22,780,165 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 3,987 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 71% 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 352,883 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 112 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 70% of its contemporaries.