Cellular senescence, a driver of aging and age-related diseases, is a stable state found in metabolically active cells characterized by irreversible cell growth arrest and dramatic changes in metabolism, gene expression and secretome profile. Endogenous regeneration efficacy of mesenchymal stem cells (MSCs) could be attenuated due to senescence. MSCs can be modulated by not only biochemical signals but also by physical cues such as substrate topography. To provide a cell culture substrate that can prevent MSC senescence over an extended period of in vitro cultivation, here, the cell- and immunocompatible poly(ether imide) (PEI) substrate was used. Two distinct levels of roughness were created on the bottom surfaces of PEI inserts via injection molding: Low-R (similar to the thickness of attached single MSC, Rq: 3.9 ± 0.2 µm) and High-R (larger than single MSC thickness. Rq: 22.7 ± 0.8 µm). Cell expansion, lysosomal enzymatic activity, apoptosis and paracrine effects of senescent MSCs were examined by cell counting, detection of senescence-associated β-galactosidase (SA β-gal), Caspase 3/7, and CFSE labeling. MSCs showed high cell viability and similar spindle-shaped morphology on all investigated surfaces. Cells on Low-R presented the highest expansion (80000 ± 1805 cells), as compared to cells on smooth PEI and High-R. The low apoptosis level (0.08 vs 0.12 from smooth PEI) and senescence ratio (35% vs. 54% from smooth PEI) were observed in MSCs cultured on Low-R. The secretome from Low-R effectively prevents senescence and supports the proliferation of neighboring cells (1.5-fold faster) as compared to the smooth PEI secretome. In summary, the Low-R PEI provided a superior surface environment for MSCs, which promoted proliferation, inhibited apoptosis and senescence, and effectively influenced the proliferation of neighboring cells via their paracrine effect. Such microroughness can be considered as a key parameter for improving the therapeutic potential of endogenous regeneration, anti-organismal aging and anti-age-related pathologies via directly promoting cell growth and modulating paracrine effects of the senescence associated secretome.

Electrical discharge machining (EDM) is a method capable of modifying the microstructure of metal surfaces. Here, we present a predictive computer supported model of the roughness generated on the surface by this process. EDM is a stochastic process, in which charge generated between a metallic substrate and an electrode creates impacts, and thus is suitable for modeling through iterative simulations. The resulting virtual, modified surface structures were evaluated for roughness. Curvatures were analyzed using Abbott-Firestone curves. Three radii of impacts (10, 20, 30 μm) and two values for the depth to radius ratio (0.1, 0.3) were used as input parameters to compute a total of six simulations. It was found that the roughness parameters followed an inverse exponential trend as a function of impact number, and that the strongly concave curvatures reached equilibrium at an earlier impact number for lower depth to radius ratios.

Recent advances in simultaneous localization and mapping permit robots to autonomously explore enclosed environments and, subsequently, navigate to selected positions within them. But, for many tasks, it is more useful to immediately navigate to goals in unexplored environments, without a map. This is possible if a human director can describe the ideal route to the robot using grounded symbols that both parties can perceive directly.

In this paper, a mobile robot is autonomously navigated to many locations in a cluttered laboratory environment by a variety of routes. A series of topological navigation instructions are provided in advance by the director, in a form that can be expressed verbally and translates easily to software representation. The instructions are based on the perception of spatial affordances available to the robot, namely nearby junctions and edges in a pruned Generalized Voronoi Diagram. The operator can generate the instructions by viewing or imagining the environment without any measurements. Only three to five instructions are needed to navigate anywhere in our laboratory. The instructions contain only topology. No spatial measurements or environmental data such as landmarks are provided to the robot.