Triarylphosphine-Coordinated Bipyridyl Ru(II) Complexes Induce Mitochondrial Dysfunction.

While cancer cells rely heavily upon glycolysis to meet their energetic needs, reducing the importance of mitochondrial oxidative respiration processes, more recent studies have shown that their mitochondria still play an active role in the bioenergetics of metastases. This feature, in combination with the regulatory role of mitochondria in cell death, has made this organelle an attractive anticancer target. Here, we report the synthesis and biological characterization of triarylphosphine-containing bipyridyl ruthenium (Ru(II)) compounds and found distinct differences as a function of the substituents on the bipyridine and phosphine ligands.

A monoadduct generating Ru(ii) complex induces ribosome biogenesis stress and is a molecular mimic of phenanthriplatin.

Ruthenium complexes are often investigated as potential replacements for platinum-based chemotherapeutics in hopes of identifying systems with improved tolerability and reduced susceptibility to cellular resistance mechanisms. Inspired by phenanthriplatin, a non-traditional platinum agent that contains only one labile ligand, monofunctional ruthenium polypyridyl agents have been developed, but until now, few demonstrated promising anticancer activity. Here we introduce a potent new scaffold, based on [Ru(tpy)(dip)Cl]Cl (tpy = 2,2':6',2''-terpyridine and dip = 4,7-diphenyl-1,10-phenanthroline) in pursuit of effective Ru(ii)-based monofunctional agents.

Superhuman cell death detection with biomarker-optimized neural networks.

Cellular events underlying neurodegenerative disease may be captured by longitudinal live microscopy of neurons. While the advent of robot-assisted microscopy has helped scale such efforts to high-throughput regimes with the statistical power to detect transient events, time-intensive human annotation is required. We addressed this fundamental limitation with biomarker-optimized convolutional neural networks (BO-CNNs): interpretable computer vision models trained directly on biosensor activity.

Genetically encoded cell-death indicators (GEDI) to detect an early irreversible commitment to neurodegeneration.

Cell death is a critical process that occurs normally in health and disease. However, its study is limited due to available technologies that only detect very late stages in the process or specific death mechanisms. Here, we report the development of a family of fluorescent biosensors called genetically encoded death indicators (GEDIs).

Automated four-dimensional long term imaging enables single cell tracking within organotypic brain slices to study neurodevelopment and degeneration.

Current approaches for dynamic profiling of single cells rely on dissociated cultures, which lack important biological features existing in tissues. Organotypic slice cultures preserve aspects of structural and synaptic organisation within the brain and are amenable to microscopy, but established techniques are not well adapted for high throughput or longitudinal single cell analysis. Here we developed a custom-built, automated confocal imaging platform, with improved organotypic slice culture and maintenance.