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Modeling hormonal and inflammatory contributions to preterm and term labor using uterine temporal transcriptomics

Overview of attention for article published in BMC Medicine, June 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

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1 blog
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17 X users

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73 Mendeley
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Title
Modeling hormonal and inflammatory contributions to preterm and term labor using uterine temporal transcriptomics
Published in
BMC Medicine, June 2016
DOI 10.1186/s12916-016-0632-4
Pubmed ID
Authors

Roberta Migale, David A. MacIntyre, Stefano Cacciatore, Yun S. Lee, Henrik Hagberg, Bronwen R. Herbert, Mark R. Johnson, Donald Peebles, Simon N. Waddington, Phillip R. Bennett

Abstract

Preterm birth is now recognized as the primary cause of infant mortality worldwide. Interplay between hormonal and inflammatory signaling in the uterus modulates the onset of contractions; however, the relative contribution of each remains unclear. In this study we aimed to characterize temporal transcriptome changes in the uterus preceding term labor and preterm labor (PTL) induced by progesterone withdrawal or inflammation in the mouse and compare these findings with human data. Myometrium was collected at multiple time points during gestation and labor from three murine models of parturition: (1) term gestation; (2) PTL induced by RU486; and (3) PTL induced by lipopolysaccharide (LPS). RNA was extracted and cDNA libraries were prepared and sequenced using the Illumina HiSeq 2000 system. Resulting RNA-Seq data were analyzed using multivariate modeling approaches as well as pathway and causal network analyses and compared against human myometrial transcriptome data. We identified a core set of temporal myometrial gene changes associated with term labor and PTL in the mouse induced by either inflammation or progesterone withdrawal. Progesterone withdrawal initiated labor without inflammatory gene activation, yet LPS activation of uterine inflammation was sufficient to override the repressive effects of progesterone and induce a laboring phenotype. Comparison of human and mouse uterine transcriptomic datasets revealed that human labor more closely resembles inflammation-induced PTL in the mouse. Labor in the mouse can be achieved through inflammatory gene activation yet these changes are not a requisite for labor itself. Human labor more closely resembles LPS-induced PTL in the mouse, supporting an essential role for inflammatory mediators in human "functional progesterone withdrawal." This improved understanding of inflammatory and progesterone influence on the uterine transcriptome has important implications for the development of PTL prevention strategies.

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X Demographics

The data shown below were collected from the profiles of 17 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 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 73 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 18%
Student > Master 12 16%
Researcher 9 12%
Student > Doctoral Student 6 8%
Student > Postgraduate 4 5%
Other 17 23%
Unknown 12 16%
Readers by discipline Count As %
Medicine and Dentistry 17 23%
Biochemistry, Genetics and Molecular Biology 13 18%
Agricultural and Biological Sciences 7 10%
Immunology and Microbiology 5 7%
Pharmacology, Toxicology and Pharmaceutical Science 3 4%
Other 11 15%
Unknown 17 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 01 August 2016.
All research outputs
#1,862,963
of 23,310,485 outputs
Outputs from BMC Medicine
#1,256
of 3,508 outputs
Outputs of similar age
#35,858
of 354,315 outputs
Outputs of similar age from BMC Medicine
#21
of 41 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,508 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.7. This one has gotten more attention than average, scoring higher than 64% 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 354,315 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 89% of its contemporaries.
We're also able to compare this research output to 41 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 51% of its contemporaries.