Methods for Spatio-Temporal Analysis of Embryo Cleavage In Vitro

Automated or semiautomated time-lapse analysis of early stage embryo images during the cleavage stage can give insight into the timing of mitosis, regularity of both division timing and pattern, as well as cell lineage. Simultaneous monitoring of molecular processes enables the study of connections between genetic expression and cell physiology and development. The study of live embryos poses not only new requirements on the hardware and embryo-holding equipment but also indirectly on analytical software and data analysis as four-dimensional video sequencing of embryos easily creates high quantities of data. The ability to continuously film and automatically analyze growing embryos gives new insights into temporal embryo development by studying morphokinetics as well as morphology. Until recently, this was not possible unless by a tedious manual process. In recent years, several methods have been developed that enable this dynamic monitoring of live embryos. Here we describe three methods with variations in hardware and software analysis and give examples of the outcomes. Together, these methods open a window to new information in developmental embryology, as embryo division pattern and lineage are studied in vivo

Quantitative Phase Imaging for Label-Free Analysis of Cancer Cells—Focus on Digital Holographic Microscopy

To understand complex biological processes, scientists must gain insight into the function of individual living cells. In contrast to the imaging of fixed cells, where a single snapshot of the cell’s life is retrieved, live-cell imaging allows investigation of the dynamic processes underlying the function and morphology of cells. Label-free imaging of living cells is advantageous since it is used without fluorescent probes and maintains an appropriate environment for cellular behavior, otherwise leading to phototoxicity and photo bleaching. Quantitative phase imaging (QPI) is an ideal method for studying live cell dynamics by providing data from noninvasive monitoring over arbitrary time scales. The effect of drugs on migration, proliferation, and apoptosis of cancer cells are emerging fields suitable for QPI analysis. In this review, we provide a current insight into QPI applied to cancer research