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Natural Selection of Human Embryos: Decidualizing Endometrial Stromal Cells Serve as Sensors of Embryo Quality upon Implantation

Overview of attention for article published in PLOS ONE, April 2010
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Title
Natural Selection of Human Embryos: Decidualizing Endometrial Stromal Cells Serve as Sensors of Embryo Quality upon Implantation
Published in
PLOS ONE, April 2010
DOI 10.1371/journal.pone.0010258
Pubmed ID
Authors

Gijs Teklenburg, Madhuri Salker, Mariam Molokhia, Stuart Lavery, Geoffrey Trew, Tepchongchit Aojanepong, Helen J. Mardon, Amali U. Lokugamage, Raj Rai, Christian Landles, Bernard A. J. Roelen, Siobhan Quenby, Ewart W. Kuijk, Annemieke Kavelaars, Cobi J. Heijnen, Lesley Regan, Jan J. Brosens, Nick S. Macklon

Abstract

Pregnancy is widely viewed as dependent upon an intimate dialogue, mediated by locally secreted factors between a developmentally competent embryo and a receptive endometrium. Reproductive success in humans is however limited, largely because of the high prevalence of chromosomally abnormal preimplantation embryos. Moreover, the transient period of endometrial receptivity in humans uniquely coincides with differentiation of endometrial stromal cells (ESCs) into highly specialized decidual cells, which in the absence of pregnancy invariably triggers menstruation. The role of cyclic decidualization of the endometrium in the implantation process and the nature of the decidual cytokines and growth factors that mediate the crosstalk with the embryo are unknown.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 238 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 <1%
United States 2 <1%
Argentina 2 <1%
Australia 1 <1%
United Kingdom 1 <1%
Russia 1 <1%
Poland 1 <1%
Unknown 228 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 47 20%
Student > Bachelor 30 13%
Student > Master 25 11%
Researcher 24 10%
Professor 12 5%
Other 38 16%
Unknown 62 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 62 26%
Medicine and Dentistry 40 17%
Biochemistry, Genetics and Molecular Biology 30 13%
Social Sciences 6 3%
Nursing and Health Professions 4 2%
Other 26 11%
Unknown 70 29%