Literature DB >> 28557135

Labor prediction based on the expression patterns of multiple genes related to cervical maturation in human term pregnancy.

Taiki Samejima1, Takeshi Nagamatsu1, Danny J Schust2, Takayuki Iriyama1, Seisuke Sayama1, Masaki Sonoda1, Atsushi Komatsu1, Kei Kawana3, Yutaka Osuga1, Tomoyuki Fujii1.   

Abstract

PROBLEM: This study explored the possibility of evaluating cervical maturation using swabbed cervical cell samples at term pregnancy, and aimed to develop a novel approach to predict labor onset. METHOD OF STUDY: Women with uncomplicated pregnancies (n=117 from 62 women at term pregnancy) were recruited. Messenger RNA expression levels of cervical cells for ten genes were quantified by qPCR. Principal component analysis (PCA) was conducted, and principal components that significantly contributed to the prediction of days to delivery were determined.
RESULTS: PCA demonstrated that 76% of the expression information from the ten genes can be represented by three principal components (PC1-3). By the multiple regression analysis, PC2 and Bishop score but not PC1 or PC3 were significant variables in the prediction of days to delivery.
CONCLUSION: These findings support the concurrent assessment of multiple gene activities in cervical cells as a promising approach to predict the initiation of labor.
© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  anti-inflammation; cervical maturation; principal component analysis; secretory leukocyte protease inhibitor

Mesh:

Year:  2017        PMID: 28557135     DOI: 10.1111/aji.12711

Source DB:  PubMed          Journal:  Am J Reprod Immunol        ISSN: 1046-7408            Impact factor:   3.886


  1 in total

1.  Metabonomics profile analysis in inflammation-induced preterm birth and the potential role of metabolites in regulating premature cervical ripening.

Authors:  Yan Yan; Zhuorong Gu; Baihe Li; Xirong Guo; Zhongxiao Zhang; Runjie Zhang; Zheng Bian; Jin Qiu
Journal:  Reprod Biol Endocrinol       Date:  2022-09-06       Impact factor: 4.982

  1 in total

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