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Plusa, B.

Publications and source records attributed to Plusa, B..

2 recordsLinked to original sources

Stage-sensitive potential of isolated rabbit ICM to differentiate into extraembryonic lineages

In the course of mammalian development initial state of totipotency must be lost to allow acquisition of specific cell fates. The first differentiation event results in the formation of trophectoderm (TE) and the inner cell mass (ICM). In the mouse embryo the cell fate of these two compartments is set quickly after formation of a blastocyst. However, recent reports suggest that plasticity of these two lineages might be extended in species other than the mouse. Here we investigated how the cellular plasticity of early mammalian embryos relates to developmental time scale and changes in gene expression using rabbit isolated ICMs. We studied the dynamics of rabbit blastocyst formation using time-lapse imaging and identified GATA3 as an early marker of rabbit TE and CDX2 as a marker of fully formed TE. We then analysed developmental potential of rabbit ICMs isolated by immunosurgery and subsequently cultured in vitro. ICMs originating from early- to mid-blastocyst stage embryos are able to re-form a blastocyst-like structure, with a functional TE, and an ICM containing both SOX2-positive epiblast cells and SOX17-positive primitive endoderm cells. We further observed that rabbit ICMs isolated from later blastocyst stages lose the ability for TE specification, instead forming a halo-like cavity with an outer layer of SOX17-positive cells. Our data indicate that in mammalian embryos the potential for TE differentiation gives way to formation of a different type of extraembryonic epithelial layer, suggesting potential common mechanism of pluripotency restriction between eutherian mammals.

developmental biology↗

Deep learning pipeline reveals key moments in human embryonic development predictive of live birth in IVF

Demand for IVF treatment is growing, however success rates remain low partly due to difficulty in selecting the best embryo to be transferred. Current manual assessments are subjective and may not take advantage of the most informative moments in embryo development. Here, we apply convolutional neural networks (CNNs) to identify key windows in preimplantation human development that can be linked to embryo viability and are therefore suitable for the early grading of IVF embryos. We show how machine learning models trained at these developmental time-points can be used to refine overall embryo viability assessment. Exploiting the well-known capabilities of transfer learning, we illustrate the performance of CNN models for very limited data sets, paving the way for the use on a clinic-by-clinic basis, catering for local data heterogeneity.

developmental biology↗