The behaviour of an organism often reflects a strategy for coping with its environment. Such behaviour in higher organisms can often be reduced to a few stereotyped modes of movement due to physiological limitations, but finding such modes in amoeboid cells is more difficult as they lack these constraints. Here, we examine cell shape and movement in starved Dictyostelium amoebae during migration toward a chemoattractant in a microfluidic chamber. We show that the incredible variety in amoeboid shape across a population can be reduced to a few modes of variation. Interestingly, cells use distinct modes depending on the applied chemical gradient, with specific cell shapes associated with shallow, difficult-to-sense gradients. Modelling and drug treatment reveals that these behaviours are intrinsically linked with accurate sensing at the physical limit. Since similar behaviours are observed in a diverse range of cell types, we propose that cell shape and behaviour are conserved traits.

In industrial settings, X-ray computed tomography scans are a common tool for inspection of objects. Often the object can not be imaged using standard circular or helical trajectories because of constraints in space or time. Compared to medical applications the variance in size and materials is much larger. Adapting the acquisition trajectory to the object is beneficial and sometimes inevitable. There are currently no sophisticated methods for this adoption. Typically the operator places the object according to his best knowledge. We propose a detectability index based optimization algorithm which determines the scan trajectory on the basis of a CAD-model of the object. The detectability index is computed solely from simulated projections for multiple user defined features. By adapting the features the algorithm is adapted to different imaging tasks. Performance of simulated and measured data was qualitatively and quantitatively assessed.The results illustrate that our algorithm not only allows more accurate detection of features, but also delivers images with high overall quality in comparison to standard trajectory reconstructions. This work enables to reduce the number of projections and in consequence scan time by introducing an optimization algorithm to compose an object specific trajectory.X-ray Computed Tomography (CT) is a widely used tool for inspection in industrial settings, in particular for nondestructive testing (NDT). It is used, for example, for dimensional metrology and defect detection. Apart from the non-existing radiation exposure issue, CT in NDT has several differences when compared to medical CT, such as large variations in object-size and attenuation. One common major issue is the importance of reduced scan times. This facilitates the expansion of industrial CT application from the laboratory to the factory with a full test coverage in the production line.Currently, industrial CT almost exclusively uses standard circular or helical trajectories in combination with filtered backprojection (FBP) reconstruction algorithms. The increased availability of high performance computing hardware, for example GPUs 1,2 , facilitates the revival of iterative reconstruction algorithms, which inherently support arbitrary trajectories. To exploit the flexibility of iterative reconstruction methods, it makes sense to move towards trajectories that include "valuable" acquisition poses (position and orientation of the source/detector arrangement, often also called projections) and exclude "less valuable" acquisition poses. In Varga et al. 3 it was demonstrated that not all acquisition poses have the same value for the reconstructed image. For example, for reconstruction of an edge at least one X-ray has to be tangential to the edge 4 . Furthermore, image quality can be severely reduced by artifacts due to beam-hardening and high attenuation materials. Typically it is not possible to avoid such artifacts completely, but one can choose a trajectory in such a way that the region of interest is not (or less) aff...

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Living cells interact with their immediate environment by exerting mechanical forces, which regulate important cell functions. Elucidation of such force patterns yields deep insights into the physics of life. Here we present a top-down nanostructured, ultraflexible nanowire array biosensor capable of probing cell-induced forces. Its universal building block, an inverted conical semiconductor nanowire, greatly enhances both the functionality and the sensitivity of the device. In contrast to existing cellular force sensing architectures, microscopy is performed on the nanowire heads while cells deflecting the nanowires are confined within the array. This separation between the optical path and the cells under investigation excludes optical distortions caused by cell-induced refraction, which can give rise to feigned displacements on the 100 nm scale. The undistorted nanowire displacements are converted into cellular forces via the nanowire spring constant. The resulting distortion-free cellular force transducer realizes a high-resolution and label-free biosenor based on optical microscopy. Its performance is demonstrated in a proof-of-principle experiment with living Dictyostelium discoideum cells migrating through the nanowire array. Cell-induced forces are probed with a resolution of 50 piconewton, while the most flexible nanowires promise to enter the 100 femtonewton realm.

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MAPK inhibitors (MAPKi) show outstanding clinical response rates in melanoma patients harbouring BRAF mutations, but resistance is common. The ability of melanoma cells to switch from melanocytic to mesenchymal phenotypes appears to be associated with therapeutic resistance. High‐throughput, subcellular proteome analyses and RNAseq on two panels of primary melanoma cells that were either sensitive or resistant to MAPKi revealed that only 15 proteins were sufficient to distinguish between these phenotypes. The two proteins with the highest discriminatory power were PTRF and IGFBP7, which were both highly upregulated in the mesenchymal‐resistant cells. Proteomic analysis of CRISPR/Cas‐derived PTRF knockouts revealed targets involved in lysosomal activation, endocytosis, pH regulation, EMT, TGFβ signalling and cell migration and adhesion, as well as a significantly reduced invasive index and ability to form spheres in 3D culture. Overexpression of PTRF led to MAPKi resistance, increased cell adhesion and sphere formation. In addition, immunohistochemistry of patient samples showed that PTRF expression levels were a significant biomarker of poor progression‐free survival, and IGFBP7 levels in patient sera were shown to be higher after relapse.

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