A proof of concept for a deep learning system that can aid embryologists in predicting blastocyst survival after thaw.

The ability to understand whether embryos survive the thaw process is crucial to transferring competent embryos that can lead to pregnancy. The objective of this study was to develop a proof of concept deep learning model capable of assisting embryologist assessment of survival of thawed blastocysts prior to embryo transfer. A deep learning model was developed using 652 labeled time-lapse videos of freeze-thaw blastocysts. The model was evaluated against and along embryologists on a test set of 99 freeze-thaw blastocysts, using images obtained at 0.5 h increments from 0 to 3 h post-thaw. The model achieved AUCs of 0.869 (95% CI 0.789, 0.934) and 0.807 (95% CI 0.717, 0.886) and the embryologists achieved average AUCs of 0.829 (95% CI 0.747, 0.896) and 0.850 (95% CI 0.773, 0.908) at 2 h and 3 h, respectively. Combining embryologist predictions with model predictions resulted in a significant increase in AUC of 0.051 (95% CI 0.021, 0.083) at 2 h, and an equivalent increase in AUC of 0.010 (95% CI -0.018, 0.037) at 3 h. This study suggests that a deep learning model can predict in vitro blastocyst survival after thaw in aneuploid embryos. After correlation with clinical outcomes of transferred embryos, this model may help embryologists ascertain which embryos may have failed to survive the thaw process and increase the likelihood of pregnancy by preventing the transfer of non-viable embryos.

Adult male mice conceived by in vitro fertilization exhibit increased glucocorticoid receptor expression in fat tissue.

Prenatal development is highly plastic and readily influenced by the environment. Adverse conditions have been shown to alter organ development and predispose offspring to chronic diseases, including diabetes and hypertension. Notably, it appears that the changes in glucocorticoid hormones or glucocorticoid receptor (GR) levels in peripheral tissues could play a role in the development of chronic diseases. We have previously demonstrated that in vitro fertilization (IVF) and preimplantation embryo culture is associated with growth alterations and glucose intolerance in mice. However, it is unknown if GR signaling is affected in adult IVF offspring. Here we show that GR expression is increased in inbred (C57Bl6/J) and outbred (CF-1× B6D2F1/J) blastocysts following in vitro culture and elevated levels are also present in the adipose tissue of adult male mice. Importantly, genes involved in lipolysis and triglyceride synthesis and responsive to GR were also increased in adipose tissue, indicating that increased GR activates downstream gene pathways. The promoter region of GR, previously reported to be epigenetically modified by perinatal manipulation, showed no changes in DNA methylation status. Our findings demonstrate that IVF results in a long-term change in GR gene expression in a sex- and tissue-specific manner. These changes in adipose tissues may well contribute to the metabolic phenotype in mice conceived by IVF.