In vitro fertilization-conceived murine embryos show evidence of oxidative and metabolic stress with alteration in lactic acid metabolism.

Reproductive fluids help the correct establishment of some epigenetic marks and gene expression in preimplantation pig embryos.

A well-trained deep learning neural network can outperform and can potentially assist expertly trained embryologists in selecting embryos based on their implantation potential, even amongst high-quality euploid blastocyst embryos.

Preimplantation screening of embryos using polygenic risk scores may substantially reduce risk for a given complex disease, but this effect depends on several quantifiable factors and raises significant ethical issues.

Genetic analyses in mice identifies Rlim in the spermatogenic cell lineage as a regulator of cytoplasmic reduction during spermiogenesis.

The fertilizing potential of sperm correlates with their ability to induce viral-like fusion of somatic cells expressing JUNO.

The inclusion of the patient couple's clinical features along with blastocyst images increases live birth prediction accuracy.

A theoretical framework predicts that using polygenic screening to select embryos against traits that depend on many genes has few benefits.

Zona pellucida requires ZP4 protein to efficiently protect the developing embryo during in vivo pre-implantation development.

Seminal fluid harbours the as yet unknown mechanism that facilitates rapid adjustment of sperm velocity in response to changing sperm competition risk.