Cells sense and respond to the rigidity of their microenvironment by altering their morphology and migration behavior. To examine this response, hydrogels with a range of moduli or mechanical gradients have been developed. Here, we show that edge effects inherent in hydrogels supported on rigid substrates also influence cell behavior. A Matrigel hydrogel was supported on a rigid glass substrate, an interface which computational techniques revealed to yield relative stiffening close to the rigid substrate support. To explore the influence of these gradients in 3D, hydrogels of varying Matrigel content were synthesized and the morphology, spreading, actin organization, and migration of glioblastoma multiforme (GBM) tumor cells were examined at the lowest (<50 µm) and highest (>500 µm) gel positions. GBMs adopted bipolar morphologies, displayed actin stress fiber formation, and evidenced fast, mesenchymal migration close to the substrate, whereas away from the interface, they adopted more rounded or ellipsoid morphologies, displayed poor actin architecture, and evidenced slow migration with some amoeboid characteristics. Mechanical gradients produced via edge effects could be observed with other hydrogels and substrates and permit observation of responses to multiple mechanical environments in a single hydrogel. Thus, hydrogel-support edge effects could be used to explore mechanosensitivity in a single 3D hydrogel system and should be considered in 3D hydrogel cell culture systems.

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Over the last 15 years, research on canid cognition has revealed that domestic dogs possess a surprising array of complex sociocognitive skills pointing to the possibility that the domestication process might have uniquely altered their brains; however, we know very little about how evolutionary processes (natural or artificial) might have modified underlying neural structure to support species‐specific behaviors. Evaluating the degree of cortical folding (i.e., gyrification) within canids may prove useful, as this parameter is linked to functional variation of the cerebral cortex. Using quantitative magnetic resonance imaging to investigate the impact of domestication on the canine cortical surface, we compared the gyrification index (GI) in 19 carnivore species, including six wild canid and 13 domestic dog individuals. We also explored correlations between global and local GI with brain mass, cortical thickness, white and gray matter volume and surface area. Our results indicated that GI values for domestic dogs are largely consistent with what would be expected for a canid of their given brain mass, although more variable than that observed in wild canids. We also found that GI in canids is positively correlated with cortical surface area, cortical thickness and total cortical gray matter volumes. While we found no evidence of global differences in GI between domestic and wild canids, certain regional differences in gyrification were observed.

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With their high degree of specificity and investigator control, in vitro disease models provide a natural complement to in vivo models. Especially in organs such as the brain, where anatomical limitations make in vivo experiments challenging, in vitro models have been increasingly used to mimic disease pathology. However, brain mimetic models may not fully replicate the mechanical environment in vivo, which has been shown to influence a variety of cell behaviors. Specifically, many disease models consider only the linear elastic modulus of brain, which describes the stiffness of a material with the assumption that mechanical behavior is independent of loading rate. Here, we characterized porcine brain tissue using a modified stress relaxation test, and across a panel of viscoelastic models, showed that stiffness depends on loading rate. As such, the linear elastic modulus does not accurately reflect the viscoelastic properties of native brain. Among viscoelastic models, the Maxwell model was selected for further analysis because of its simplicity and excellent curve fit (R 2 = 0.99 ± 0.0006). Thus, mechanical response of native brain and hydrogel mimetic models was analyzed using the Maxwell model and the linear elastic model to evaluate the effects of strain rate, time post mortem, region, tissue type (i.e., bulk brain vs white matter), and in brain mimetic models, hydrogel composition, on observed mechanical properties. In comparing the Maxwell and linear elastic models, linear elastic modulus is consistently lower than the Maxwell elastic modulus across all brain regions. Additionally, the Maxwell model is sensitive to changes in viscosity and small changes in elasticity, demonstrating improved fidelity. These findings demonstrate the insufficiency of linear elastic modulus as a primary mechanical characterization for brain mimetic materials and provide quantitative information toward the future design of materials that more closely mimic mechanical features of brain.

In this study, we sought to characterize functional signaling domains by applying the multiresolution properties of the continuous wavelet transform to fluorescence resonance energy transfer (FRET) microscopic images of plasma membranes. A genetically encoded FRET reporter of protein kinase C (PKC)-dependent phosphorylation was expressed in COS1 cells. Differences between wavelet coefficient matrices revealed several heterogeneous domains (typically ranging from 1 to 5 microm), reflecting the dynamic balance between PKC and phosphatase activity during stimulation with phorbol-12,13-dibutyrate or acetylcholine. The balance in these domains was not necessarily reflected in the overall plasma membrane changes, and observed heterogeneity was absent when cells were exposed to a phosphatase or PKC inhibitor. Prolonged exposure to phorbol-12,13-dibutyrate and acetylcholine yielded more homogeneous FRET distribution in plasma membranes. The proposed wavelet-based image analysis provides, for the first time, a basis and a means of detecting and quantifying dynamic changes in functional signaling domains, and may find broader application in studying fine aspects of cellular signaling by various imaging reporters.

Advances in smart materials and electronics have enabled compliant sensing systems mimicking nature. In structural health monitoring (SHM) applications, the technology still lacks accuracy in tracking measurements over large geometries. Herein we report a facile fabrication for a compliant sensor based on an elastomeric capacitive sensor technology, augmented with a scalable surface texture inspired by various grid geometries. Texture designs are selected to direct, and therefore improve, the strain sensing capabilities and thus the sensor's gauge factor. We showcase selected designs based on an a detailed engineering analysis. The selected surface patterns are investigated under increasing strain targets and strain frequency sweeps. Results confirm that a stretchable thermoplastic composite sensor with a textured pattern embossed into the hyper-elastic matrix yields approximately 30% increase in the gauge factor and 35% in signal accuracy, great linearity up to 30% strain, and overall signal stability to empower SHM applications.

Recent advances in hyperelastic materials and self-sensing sensor designs have enabled the creation of dense compliant sensor networks for the cost-effective monitoring of structures. The authors have proposed a sensing skin based on soft polymer composites by developing soft elastomeric capacitor (SEC) technology that transduces geometric variations into a measurable change in capacitance. A limitation of the technology is in its low gauge factor and lack of sensing directionality. In this paper, we propose a corrugated SEC through surface texture, which provides improvements in its performance by significantly decreasing its transverse Poisson’s ratio, and thus improving its sensing directionality and gauge factor. We investigate patterns inspired by auxetic structures for enhanced unidirectional strain monitoring. Numerical models are constructed and validated to evaluate the performance of textured SECs, and to study their performance at monitoring strain on animal skin. Results show that the auxetic patterns can yield a significant increase in the overall gauge factor and decrease the stress experienced by the animal skin, with the re-entrant hexagonal honeycomb pattern outperforming all of the other patterns.