Planar in vitro models have been invaluable tools to identify the mechanical basis of wound closure. Although these models may recapitulate closure dynamics of epithelial cell sheets, they fail to capture how a wounded fibrous tissue rebuilds its 3D architecture. Here we develop a 3D biomimetic model for soft tissue repair and demonstrate that fibroblasts ensconced in a collagen matrix rapidly close microsurgically induced defects within 24 h. Traction force microscopy and time-lapse imaging reveal that closure of gaps begins with contractility-mediated whole-tissue deformations. Subsequently, tangentially migrating fibroblasts along the wound edge tow and assemble a progressively thickening fibronectin template inside the gap that provide the substrate for cells to complete closure. Unlike previously reported mechanisms based on lamellipodial protrusions and purse-string contraction, our data reveal a mode of stromal closure in which coordination of tissue-scale deformations, matrix assembly and cell migration act together to restore 3D tissue architecture.

The use of a single energy source for both manipulating micromachines and triggering their functionalities will result in highly integrated devices and simplify the design of the controlling platform. Here, we demonstrate this concept employing magnetoelectric Janus particle-based micromachines, which are fabricated by coating SiO₂ microspheres with a CoFe₂O₄–BaTiO₃ bilayer composite. While the inner magnetic CoFe₂O₄ layer enables the micromachines to be maneuvered using low magnitude rotating magnetic fields, the magnetoelectric bilayer composite provides the ability to remotely generate electric charges upon the application of a time-varying magnetic field. To demonstrate the capabilities of these micromachines, noble metals such as Au, Ag and Pt are magnetoelectrochemically reduced from their corresponding precursor salts and form nanoparticles on the surface of the micromachines. Magnetoelectric micromachines are promising devices for their use as metal scavengers, cell stimulators and electric field-assisted drug delivery agents.

Human-robot collaboration is gaining more and more interest in industrial settings, as collaborative robots are considered safe and robot actions can be programmed easily by, for example, physical interaction. Despite this, robot programming mostly focuses on automated robot motions and interactive tasks or coordination between human and robot still requires additional developments. For example, the selection of which tasks or actions a robot should do next might not be known beforehand or might change at the last moment. Within a human-robot collaborative setting, the coordination of complex shared tasks, is therefore more suited to a human, where a robot would act upon requested commands.In this work we explore the utilization of commands to coordinate a shared task between a human and a robot, in a shared work space. Based on a known set of higher-level actions (e.g., pick-and-placement, hand-over, kitting) and the commands that trigger them, both a speech-based and graphical command-based interface are developed to investigate its use. While speech-based interaction might be more intuitive for coordination, in industrial settings background sounds and noise might hinder its capabilities. The graphical command-based interface circumvents this, while still demonstrating the capabilities of coordination. The developed architecture follows a knowledge-based approach, where the actions available to the robot are checked at runtime whether they suit the task and the current state of the world. Experimental results on industrially relevant assembly, kitting and hand-over tasks in a laboratory setting demonstrate that graphical command-based and speech-based coordination with high-level commands is effective for collaboration between a human and a robot.