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Overview of the structure-based non-genomic effects of the nuclear receptor RXRα

Overview of attention for article published in Cellular & Molecular Biology Letters, August 2018
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Title
Overview of the structure-based non-genomic effects of the nuclear receptor RXRα
Published in
Cellular & Molecular Biology Letters, August 2018
DOI 10.1186/s11658-018-0103-3
Pubmed ID
Authors

Liqun Chen, Lingjuan Wu, Linyan Zhu, Yiyi Zhao

Abstract

The nuclear receptor RXRα (retinoid X receptor-α) is a transcription factor that regulates the expression of multiple genes. Its non-genomic function is largely related to its structure, polymeric forms and modification. Previous research revealed that some non-genomic activity of RXRα occurs via formation of heterodimers with Nur77. RXRα-Nur77 heterodimers translocate from the nucleus to the mitochondria in response to certain apoptotic stimuli and this activity correlates with cell apoptosis. More recent studies revealed a significant role for truncated RXRα (tRXRα), which interacts with the p85α subunit of the PI3K/AKT signaling pathway, leading to enhanced activation of AKT and promoting cell growth in vitro and in animals. We recently reported on a series of NSAID sulindac analogs that can bind to tRXRα through a unique binding mechanism. We also identified one analog, K-80003, which can inhibit cancer cell growth by inducing tRXRα to form a tetramer, thus disrupting p85α-tRXRα interaction. This review analyzes the non-genomic effects of RXRα in normal and tumor cells, and discusses the functional differences based on RXRα protein structure (structure source: the RCSB Protein Data Bank).

Twitter Demographics

The data shown below were collected from the profiles of 2 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 18%
Student > Master 2 12%
Student > Ph. D. Student 2 12%
Unspecified 1 6%
Professor 1 6%
Other 2 12%
Unknown 6 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 41%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Unspecified 1 6%
Agricultural and Biological Sciences 1 6%
Medicine and Dentistry 1 6%
Other 0 0%
Unknown 6 35%

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 11 August 2018.
All research outputs
#10,191,708
of 13,352,827 outputs
Outputs from Cellular & Molecular Biology Letters
#80
of 220 outputs
Outputs of similar age
#184,864
of 267,750 outputs
Outputs of similar age from Cellular & Molecular Biology Letters
#1
of 1 outputs
Altmetric has tracked 13,352,827 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 220 research outputs from this source. They receive a mean Attention Score of 2.1. This one has gotten more attention than average, scoring higher than 56% 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 267,750 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% 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