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Abstract Biological processes are inherently dynamic, necessitating biomaterial platforms capable of spatiotemporal control over cellular organization and matrix stiffness for accurate study of tissue development, wound healing, and disease. However, most in vitro platforms remain static. In this study, a dynamic biomaterial platform comprising a stiffening hydrogel is introduced and achieved through a stepwise approach of addition followed by light‐mediated crosslinking, integrated with an elastomeric substrate featuring strain‐responsive lamellar surface patterns. Employing this platform, the response of human induced pluripotent stem cell‐derived cardiomyocytes (hIPSC‐CMs) is investigated to dynamic stiffening from healthy to fibrotic tissue stiffness. The results demonstrate that culturing hIPSC‐CMs on physiologically relevant healthy stiffness significantly enhances their function, as evidenced by increased sarcomere fraction, wider sarcomere width, significantly higher connexin‐43 content, and elevated cell beating frequency compared to cells cultured on fibrotic matrix. Conversely, dynamic matrix stiffening negatively impacts hIPSC‐CM function, with earlier stiffening events exerting a more pronounced hindering effect. These findings provide valuable insights into material‐based approaches for addressing existing challenges in hIPSC‐CM maturation and have broader implications across various tissue models, including muscle, tendon, nerve, and cornea, where both cellular alignment and matrix stiffening play pivotal roles in tissue development and regeneration.
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Cellular plasticity model for self-organized phenotypes in multi-cellular robots
Abstract Robotic systems often struggle to adapt to dynamic, unstructured environments due to top-down design constraints based on human assumptions. Inspired by biological morphogenesis, this study introduces a cellular plasticity model based on Turing patterns, enabling multi-cellular robots to self-organize their cell phenotypes in response to environmental stimuli. The model leverages reaction-diffusion dynamics to capture key cellular plasticity phenomena observed in muscle cells, neurons, and stem cells. Analytical analysis explores equilibrium points, stability, and conditions for emergent Turing patterns, while simulations examine parametric influences on system behavior. Physical experiments with the Loopy platform demonstrate that its cells dynamically self-organize mechanical properties in response to behavioral and environmental demands. This response enables Loopy to achieve similar performance to empirically optimized static parameters in obstacle-free environments and outperform the static configuration in an environment with limited space. This work advances morphogenetic robotics, presenting a scalable framework for decentralized, dynamic adaptation in unmodeled environments.
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- Award ID(s):
- 2223793
- PAR ID:
- 10625633
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- npj Robotics
- Volume:
- 3
- Issue:
- 1
- ISSN:
- 2731-4278
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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