Leveraging bioengineering to assess cellular functions and communication within human fetal membranes

DR-Net: dual-rotation network with feature map enhancement for medical image segmentation

To obtain more semantic information with small samples for medical image segmentation, this paper proposes a simple and efficient dual-rotation network (DR-Net) that strengthens the quality of both local and global feature maps. The key steps of the DR-Net algorithm are as follows (as shown in Fig. 1). First, the number of channels in each layer is divided into four equal portions. Then, different rotation strategies are used to obtain a rotation feature map in multiple directions for each subimage. Then, the multiscale volume product and dilated convolution are used to learn the local and global features of feature maps. Finally, the residual strategy and integration strategy are used to fuse the generated feature maps. Experimental results demonstrate that the DR-Net method can obtain higher segmentation accuracy on both the CHAOS and BraTS data sets compared to the state-of-the-art methods.

Bioengineered Microphysiological Placental Models: Towards Improving Understanding of Pregnancy Health and Disease

Driven by a lack of appropriate human placenta models, recent years have seen the introduction of bioengineered in vitro models to better understand placental health and disease. Thus far, the focus has been on the maternal-foetal barrier. However, there are many other physiologically and pathologically significant aspects of the placenta that would benefit from state-of-the-art bioengineered models, in particular, integrating advanced culture systems with contemporary biological concepts such as organoids. This critical review defines and discusses the key parameters required for the development of physiologically relevant in vitro models of the placenta. Specifically, it highlights the importance of cell type, mechanical forces, and culture microenvironment towards the use of physiologically relevant models to improve the understanding of human placental function and dysfunction.