Quantify permeability using on-a-chip models in high-throughput applications.

Traditionally, to quantify permeability of a biological barrier, the initial slope is used, based on the assumption of sink condition (concentration of the donor is constant, and the receiver increases less than 10%). With on-a-chip barrier models, this assumption fails in cell-free or leaky conditions, which requires the use of the exact solution. To encounter a time delay from performing the assay and acquiring the data, we present a protocol with the exact equation modified to incorporate a time offset.

Non-invasive single-cell biomechanical analysis using live-imaging datasets.

The physiological state of a cell is governed by a multitude of processes and can be described by a combination of mechanical, spatial and temporal properties. Quantifying cell dynamics at multiple scales is essential for comprehensive studies of cellular function, and remains a challenge for traditional end-point assays. We introduce an efficient, non-invasive computational tool that takes time-lapse images as input to automatically detect, segment and analyze unlabeled live cells; the program then outputs kinematic cellular shape and migration parameters, while simultaneously measuring cellular stiffness and viscosity. We demonstrate the capabilities of the program by testing it on human mesenchymal stem cells (huMSCs) induced to differentiate towards the osteoblastic (huOB) lineage, and T-lymphocyte cells (T cells) of naïve and stimulated phenotypes. The program detected relative cellular stiffness differences in huMSCs and huOBs that were comparable to those obtained with studies that utilize atomic force microscopy; it further distinguished naïve from stimulated T cells, based on characteristics necessary to invoke an immune response. In summary, we introduce an integrated tool to decipher spatiotemporal and intracellular dynamics of cells, providing a new and alternative approach for cell characterization.