Segmentation of cellular ultrastructures on sparsely labeled 3D electron microscopy images using deep learning.

Focused ion beam-scanning electron microscopy (FIB-SEM) images can provide a detailed view of the cellular ultrastructure of tumor cells. A deeper understanding of their organization and interactions can shed light on cancer mechanisms and progression. However, the bottleneck in the analysis is the delineation of the cellular structures to enable quantitative measurements and analysis.

A workflow for visualizing human cancer biopsies using large-format electron microscopy.

Recent developments in large format electron microscopy have enabled generation of images that provide detailed ultrastructural information on normal and diseased cells and tissues. Analyses of these images increase our understanding of cellular organization and interactions and disease-related changes therein. In this manuscript, we describe a workflow for two-dimensional (2D) and three-dimensional (3D) imaging, including both optical and scanning electron microscopy (SEM) methods, that allow pathologists and cancer biology researchers to identify areas of interest from human cancer biopsies.

Effective reduction of non-specific binding of blood cells in a microfluidic chip for isolation of rare cancer cells.

The high purity of target cells enriched from blood samples plays an important role in the clinical detection of diseases. However, non-specific binding of blood cells in the isolated cell samples can complicate downstream molecular and genetic analysis. In this work, we report a simple solution to non-specific binding of blood cells by modifying the surface of microchips with a multilayer nanofilm, with the outmost layer containing both PEG brushes for reducing blood cell adhesion and antibodies for enriching target cells.