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Polyelectrolyte multi-layer (PEM) coatings are prepared by alternative deposition of single polyelectrolyte monolayers on charged surfaces using the Layer-by-Layer (LbL) dip coating procedure. These are nanometre scaled coatings which allow fulfilling of different technical or biological requirements. The build-up process is based on selfassembly and self organization of polycations and polyanions on different substrates including complex geometrical structures and even closed volumes, forming homogeneous layer without defects. Depending on the proper selection of the applied polyelectrolytes, coatings with different stabilities can be prepared. Some of the coatings are stable and cannot be removed from the surface. Others are degradable and can be used as systems for controlled local drug delivery. Here we summarise the results of our experience in preparation of PEM coatings with different functionalities. PEM coatings can be used as controllable delivery system for siRNA polyplexes. They can be used to control the adhesion of different cell types on the surfaces and support e.g. the endothelialisation process on cardio-vascular medical devices as e.g. stents or reduce the immunological response of the tissue after implantation. We summarise results from physical characterisation of the coatings (e.g. film thickness, roughness, electrical charge and hydrophilicity) combined with in-vitro biological studies on adhesion of HUVEC cells.
A series of novel biomedical TPCUs with different percentages of hard segment and a silicone component in the soft segment were synthesized in a multi stage one-pot method. The kinetic profiles of the urethane formation in TPCU-based copolymer systems were monitored by rheological, in line FTIR spectroscopic (React IR) and real-time calorimetric (RC1) methods. This process-analytically monitored multi step synthesis was successfully used to optimize the production of medical-grade TPCU elastomers on preparative scale (in lots of several kg) with controlled molecular structure and mechanical properties. Various surface and bulk analytical methods as well as systematic studies of the mechanic response of the elastomer end-products towards compression and tensile loading were used to estimate the bio-stability of the prepared TPCUs in vitro after 3 months. The tests suggested that high bio-stability of all polyurethane formulations using accelerating in vitro test can be attributed to the synthetic design as well as to the specific techniques used for specimen preparation, namely: (1) the annealing for reducing residual polymer surface stress and preventing IES, (2) stabilization of the morphology by long time storage of the specimens after processing before being immersed in the test liquids, (3) purification by extraction to remove the shot chain oligomers which are the most susceptible to degradation. All mechanical tests were performed on cylindrical and circular disc specimens for modelling the thickness of the meniscus implants under application-relevant stress conditions.
We present an approach for segmenting individual cells and lamellipodia in epithelial cell clusters using fully convolutional neural networks. The method will set the basis for measuring cell cluster dynamics and expansion to improve the investigation of collective cell migration phenomena. The fully learning-based front-end avoids classical feature engineering, yet the network architecture needs to be designed carefully. Our network predicts how likely each pixel belongs to one of the classes and, thus, is able to segment the image. Besides characterizing segmentation performance, we discuss how the network will be further employed.
Surface topographies are often discussed as an important parameter influencing basic cell behavior. Whereas most in vitro studies deal with microstructures with sharp edges, smooth, curved microscale topographies might be more relevant concerning in-vivo situations. Addressing the lack of highly defined surfaces with varying curvature, we present a topography chip system with 3D curved features of varying spacing, curvature radii as well as varying overall dimensions of curved surfaces. The CurvChip is produced by low-cost photolithography with thermal reflow, subsequent (repetitive) PDMS molding and hot embossing. The platform facilitates the systematic in-vitro investigation of the impact of substrate curvature on cell types like epithelial, endothelial, smooth muscle cells, or stem cells. Such investigations will not only help to further understand the mechanism of curvature sensation but may also contribute to optimize cell-material interactions in the field of regenerative medicine.