Rijksuniversiteit Groningen

A method and system for determining biocompatibility ("BC") of a biological sample ("S") with a solid test material ("M"). A testing apparatus (100) comprises a material region (10R) containing the solid test material ("M"); and a sample region (20R) containing the biological sample ("S") comprising biological cells ("Sc") into which nanocrystals ("NC") with color centers ("CC") have been introduced. A liquid medium ("L") fluidly connects the material region (10R) with the sample region (20R) and carries dissolvable components ("Mc") from the solid test material ("M") into contact with the biological cells ("Sc"). Optical measurements are performed on the biological sample ("S") to determine a time-dependent spin state of the color centers ("CC") of the respective nanocrystals ("NC") as local indicators of a biological response ("Br") of the biological cells ("Sc") to the dissolvable components ("Mc"). The biocompatibility ("BC") is determined based on the optical measurements.

A method is provided herein for training a neural network to automatically reconstruct a three-dimensional bone model from MRI-scan data. The method that is performed for a plurality of human body part samples comprises preparing (S1M, S1C) a respective pair of an MRI-scan comprising MRI-scan data (M) and a CT-scan with CT-scan data (C). Ground truth bone segmentation data (Cs) is provided (S2C) for one or more regions of interest in the CT-scan. The ground truth bone segmentation data (Cs) is linked (S4C) with the CT-scan data to obtain enriched CT-scan data (Cl). The MRI-scan data is fused (S5) with the enriched CT-scan data (Cl) to obtain enriched MRI-scan data (Fa, Fb) including ground truth bone segmentation data. Then with the neural network to be trained tentative enriched MRI-scan data (Ft) is estimated (S7) from the MRI-scan data. The tentative enriched MRI-scan data (Ft) comprises the MRI-scan data and tentative bone segmentation data. A loss is computed(S8) that is indicative for a deviation between the tentative bone segmentation data and the ground truth bone segmentation data and backpropagated (S9). The trained neural network (20) obtained with the method is suitable for computing bone segmentation data from MRI-scan data.

The invention relates to a bicelle entity comprising a bicelle structure with a rim and first and second amphiphilic compounds, the first having a longer hydrophobic chain, and at least one extension configured to bind a DNA origami envelope or its extension. It further relates to a DNA origami envelope adapted for such binding and to a complex formed by their assembly. A kit comprising the bicelle entity and the DNA origami envelope is also provided. The invention additionally concerns a hybrid pore device incorporating the complex with a solid-state pore. Methods are disclosed for manufacturing the complex by assembling the bicelle entity and DNA origami envelope, and for producing the hybrid pore device by integrating the complex with the solid-state pore.

The invention provides a method for manufacturing a memristor system for a neuromorphic device, including: -providing a first substrate; -depositing an epitaxial buffer layer on the first substrate; -epitaxially depositing at least one memristor device layer, in particular a semiconductor oxide layer, on the buffer layer; -removing the buffer layer, in particular by dissolving and/or etching the buffer layer, to provide a freestanding memristor device layer; -manufacturing a memristor device cell structure in/from the memristor device layer; -providing a second substrate; - forming a first electrode structure on the second substrate; -joining the freestanding memristor device layer onto the first electrode structure of the second substrate; and -forming a second electrode structure on the memristor device cell structure.

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