Strategies to optimise machine learning classification performance when using biomechanical features.

Building prediction models using biomechanical features is challenging because such models may require large sample sizes. However, collecting biomechanical data on large sample sizes is logistically very challenging. This study aims to investigate if modern machine learning algorithms can help overcome the issue of limited sample sizes on developing prediction models.

Continuous microfluidic flow-through protocol for selective and image-activated electroporation of single cells.

Electroporation of cells is a widely-used tool to transport molecules such as proteins or nucleic acids into cells or to extract cellular material. However, bulk methods for electroporation do not offer the possibility to selectively porate subpopulations or single cells in heterogeneous cell samples. To achieve this, either presorting or complex single-cell technologies are required currently.

High-precision, low-complexity, high-resolution microscopy-based cell sorting.

Continuous flow cell sorting based on image analysis is a powerful concept that exploits spatially-resolved features in cells, such as subcellular protein localisation or cell and organelle morphology, to isolate highly specialised cell types that were previously inaccessible to biomedical research, biotechnology, and medicine. Recently, sorting protocols have been proposed that achieve impressive throughput by combining ultra-high flow rates with sophisticated imaging and data processing protocols. However, moderate image quality and high complex experimental setups still prevent the full potential of image-activated cell sorting from being a general-purpose tool.

Combining dielectrophoresis and computer vision for precise and fully automated single-cell handling and analysis.

With the advent of single-cell technologies comes the necessity for efficient protocols to process single cells. We combine dielectrophoresis with open source computer vision programming to automatically control the trajectories of single cells inside a microfluidic device. Using real-time image analysis, individual cells are automatically selected, isolated and spatially arranged.

Micropatterned Thermoresponsive Cell Culture Substrates for Dynamically Controlling Neurite Outgrowth and Neuronal Connectivity in Vitro.

In vitro cultured neuronal networks with defined connectivity are required to improve neuronal cell culture models. However, most protocols for their formation do not provide sufficient control of the direction and timing of neurite outgrowth with simultaneous access for analytical tools such as immunocytochemistry or patch-clamp recordings. Here, we present a proof-of-concept for the dynamic (i.