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Cited by 317

The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.

The Human Endometrium as a Sensor of Embryo Quality1

Macklon, Nick S., Brosens, Jan J.·2014·Biology of Reproduction

Abstract

Human reproduction is characterized by a high degree of embryo wastage, which is largely ascribed to a high prevalence of embryo aneuploidy. It is proposed that maternal strategies have evolved that prevent inappropriate investment in invasive, but poorly viable embryos. Key to this is the emerging concept of the endometrium as biosensor, first identified in human in vitro embryo/decidualized stromal cell coculture systems and recently confirmed in an in vivo mouse model. In this review, the growing supporting experimental evidence for the biosensor component of decidualized endometrium is outlined, and recent insights into the nature of the embryo-derived signal detected by the endometrium and the biological processes by which this signal is thought to be converted into a go or no-go endometrial response are described. Finally, the clinical implications of this new paradigm of the choosy uterus are addressed.

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Metadata

Authors
Macklon, N. S., & Brosens, J. J.
Venue
Biology of Reproduction
Published
2014-10-01
Volume
91
Issue
4
Pages
98-98
ISSN
  • 0006-3363 (ISSN-L)
  • 1529-7268
OpenAlex
W2117371378
Cited by
317
References
43
FWCI
6.48
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Human Endometrium as a Sensor of Embryo Quality1. https://app.cochat.ai/papers/10.1095/biolreprod.114.122846
The paper
Macklon, N. S., & Brosens, J. J. (2014). The Human Endometrium as a Sensor of Embryo Quality1. Biology of Reproduction. https://doi.org/10.1095/biolreprod.114.122846

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.