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The automation of cryo-focused ion beam milling enables previously unfeasible cryo-electron tomography projects.

A robot capable of automatically obtaining blind whole cell patch clamp recordings from multiple neurons simultaneously guides four interacting electrodes in a coordinated fashion, avoiding mechanical coupling in the brain.

Automated liquid handling, whole mount staining, and clearing allow unbiased 3D quantitation of cell markers in human neural organoids with diameters of up to 1 mm at the single-cell level.

Development of a fully automated pain scale using machine learning tools in computational neuroethology and creation of new software, reveals a robust circuit-dissection compatible platform for objective pain measurement.

A computational method based on optimal transport enables state-of-the-art alignment between untargeted metabolomic studies and is evaluated on cord blood and cancer datasets.

An algorithm for analysing brain connectivity data identifies cell types and connections in simple (C. elegans) and complex (mouse) nervous systems, and can even resolve structure and connectivity in a man-made microprocessor.

A novel micropositioning approach allows remote-controlled, micrometer-resolution actuation of many densely packed, arbitrarily shaped probes with a device whose size and weight scale much more efficiently with probe count compared to current methods.

In an investigation into the effects of drugs on proteins, an active machine learning algorithm chose which sets of experiments to perform and was able to learn an accurate model of the effects after doing only a fraction of the experiments.

Software is introduced for the rapid and comprehensive quantification of sarcomere-containing myofibrils and their precursors in cardiac myocytes, aiding in the advancement of cardiovascular cell biology investigations.