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A dynamical systems model of progesterone receptor interactions with inflammation in human parturition

Overview of attention for article published in BMC Systems Biology, August 2016
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Title
A dynamical systems model of progesterone receptor interactions with inflammation in human parturition
Published in
BMC Systems Biology, August 2016
DOI 10.1186/s12918-016-0320-1
Pubmed ID
Authors

Douglas Brubaker, Alethea Barbaro, Mark R. Chance, Sam Mesiano

Abstract

Progesterone promotes uterine relaxation and is essential for the maintenance of pregnancy. Withdrawal of progesterone activity and increased inflammation within the uterine tissues are key triggers for parturition. Progesterone actions in myometrial cells are mediated by two progesterone receptor (PR) isoforms, PR-A and PR-B, that function as ligand-activated transcription factors. PR-B mediates relaxatory actions of progesterone, in part, by decreasing myometrial cell responsiveness to pro-inflammatory stimuli. These same pro-inflammatory stimuli promote the expression of PR-A which inhibits the anti-inflammatory activity of PR-B. Competitive interaction between the progesterone receptors then augments myometrial responsiveness to pro-inflammatory stimuli. The interaction between PR-B transcriptional activity and inflammation in the pregnancy myometrium is examined using a dynamical systems model in which quiescence and labor are represented as phase-space equilibrium points. Our model shows that PR-B transcriptional activity and the inflammatory load determine the stability of the quiescent and laboring phenotypes. The model is tested using published transcriptome datasets describing the mRNA abundances in the myometrium before and after the onset of labor at term. Surrogate transcripts were selected to reflect PR-B transcriptional activity and inflammation status. The model coupling PR-B activity and inflammation predicts contractile status (i.e., laboring or quiescent) with high precision and recall and outperforms uncoupled single and two-gene classifiers. Linear stability analysis shows that phase space bifurcations exist in our model that may reflect the phenotypic states of the pregnancy uterus. The model describes a possible tipping point for the transition of the quiescent to the contractile laboring phenotype. Our model describes the functional interaction between the PR-A:PR-B hypothesis and tissue level inflammation in the pregnancy uterus and is a first step in more sophisticated dynamical systems modeling of human partition. The model explains observed biochemical dynamics and as such will be useful for the development of a range of systems-based models using emerging data to predict preterm birth and identify strategies for its prevention.

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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 18%
Student > Bachelor 4 14%
Student > Postgraduate 3 11%
Professor 3 11%
Student > Master 3 11%
Other 7 25%
Unknown 3 11%
Readers by discipline Count As %
Medicine and Dentistry 7 25%
Agricultural and Biological Sciences 4 14%
Immunology and Microbiology 2 7%
Engineering 2 7%
Neuroscience 2 7%
Other 5 18%
Unknown 6 21%

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 22 August 2016.
All research outputs
#6,267,906
of 8,261,086 outputs
Outputs from BMC Systems Biology
#621
of 850 outputs
Outputs of similar age
#180,670
of 253,947 outputs
Outputs of similar age from BMC Systems Biology
#27
of 40 outputs
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