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Inflammatory Aetiology of Human Myometrial Activation Tested Using Directed Graphs
Author(s) -
Andrew Bisits,
Roger Smith,
Sam Mesiano,
George Yeo,
Kenneth Kwek,
David A. MacIntyre,
Eng Cheng Chan
Publication year - 2005
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.0010019
Subject(s) - lisrel , oxytocin receptor , myometrium , oxytocin , event (particle physics) , event study , biology , structural equation modeling , medicine , endocrinology , bioinformatics , uterus , computer science , machine learning , physics , quantum mechanics , paleontology , context (archaeology)
There are three main hypotheses for the activation of the human uterus at labour: functional progesterone withdrawal, inflammatory stimulation, and oxytocin receptor activation. To test these alternatives we have taken information and data from the literature to develop causal pathway models for the activation of human myometrium. The data provided quantitative RT-PCR results on key genes from samples taken before and during labour. Principal component analysis showed that pre-labour samples form a homogenous group compared to those during labour. We therefore modelled the alternative causal pathways in non-laboring samples using directed graphs and statistically compared the likelihood of the different models using structural equations and D-separation approaches. Using the computer program LISREL, inflammatory activation as a primary event was highly consistent with the data (p = 0.925), progesterone withdrawal, as a primary event, is plausible (p = 0.499), yet comparatively unlikely, oxytocin receptor mediated initiation is less compatible with the data (p = 0.091). DGraph, a software program that creates directed graphs, produced similar results (p= 0.684, p= 0.280, and p = 0.04, respectively). This outcome supports an inflammatory aetiology for human labour. Our results demonstrate the value of directed graphs in determining the likelihood of causal relationships in biology in situations where experiments are not possible.

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