Precise dosage of the imprinted H19 and Igf2 genes is critical for normal embryonic development, especially related to the cardiac-placental axis.

A time-course of single nuclei RNA-seq of the mouse placenta identifies trophoblast subtypes and the genes, signaling events, and transcriptional networks important for their differentiation, maintenance, and function.

Active uptake and metabolism of maternal vitamin D by the placenta determine fetal exposure to vitamin D and how vitamin D regulates the placental transcriptome, which is also determined by its underlying epigenetic landscape, and proteome.

The short-lived tammar wallaby placenta expresses genes resembling eutherian placentas, establishing marsupials as "placental mammals", further, dynamic lactation allows marsupials to compensate for short placentation by expressing key placental genes in the mammary gland.

The role of placental aging and metabolic stress in driving labor onset is demonstrated, with a novel mouse model of preterm labor in which injection of a prolyl hydroxylase inhibitor stabilizes placental hypoxia-inducible factor 1 and significantly shortens gestational length.

Epigenomic and transcriptomic analysis reveals that paternal obesity influences sperm histone H3 lysine 4 tri-methylation enrichment and placenta gene expression, which in turn negatively impact its development and function in a manner that may contribute to metabolic disease in offspring.

VAR2CSA, the leading candidate antigen for a placental malaria vaccine, displays epitopes targeted by naturally acquired broadly neutralizing antibodies of African multigravidae.

Zika virus infection induces the gasdermin E-mediated pyroptosis in placental cells through TNF-α-caspase-8-caspase-3 signaling pathway, which contributes to adverse fetal outcomes in pregnant mouse model.

Full spectrum flow cytometry reveals a high degree of placental mesenchymal cell heterogeneity, which is lost with culture, highlighting the importance of detailed ex vivo phenotyping to optimise the use of these cells in downstream applications.

Machine learning identified six protective antibody features and showed for the first time that serological markers can predict protection from placental-malaria, which is important for evaluation and development of vaccines.