On-Chip Sonoporation-Based Flow Cytometric Magnetic Labeling.

Tracing magnetically labeled cells with magnetic resonance imaging (MRI) is an emerging and promising approach to uncover in vivo behaviors of cells in cell therapy. Today, existing methods for the magnetic labeling of cells are cumbersome and time-consuming, which has greatly limited the progress of such studies on cell therapy. Thus, in this study, using the flow cytometric loading technology, we develop a sonoporation-based microfluidic chip (i.e., a microfluidic chip integrated with ultrasound; MCU), to achieve the safe, instant, convenient, and continuous magnetic labeling of cells. For the MCU we designed, a suitable group of operating conditions for safely and efficiently loading superparamagnetic iron oxide (SPIO) nanoparticles into DC2.4 cells was identified experimentally. Under the identified operating conditions, the DC2.4 cells could be labeled in approximately 2 min with high viability (94%) and a high labeling quantity of SPIO nanoparticles (19 pg of iron per cell). In addition, the proliferative functions of the cells were also well maintained after labeling. Furthermore, the in vivo imaging ability of the DC2.4 cells labeled using the MCU was verified by injecting the labeled cells into the leg muscle of the C57BL/6 mice. The results show that the excellent imaging outcome can be continuously achieved for 7 days at a density of 106 cells/mL. This work can provide insight for the design of magnetic cell labeling devices and promote the MRI-based study of cell therapies.

Turning and Radius Deviation Correction for a Hexapod Walking Robot Based on an Ant-Inspired Sensory Strategy.

Abstract: In order to find a common approach to plan the turning of a bio-inspired hexapod robot, a locomotion strategy for turning and deviation correction of a hexapod walking robot based on the biological behavior and sensory strategy of ants. A series of experiments using ants were carried out where the gait and the movement form of ants was studied. Taking the results of the ant experiments as inspiration by imitating the behavior of ants during turning, an extended turning algorithm based on arbitrary gait was proposed. Furthermore, after the observation of the radius adjustment of ants during turning, a radius correction algorithm based on the arbitrary gait of the hexapod robot was raised. The radius correction surface function was generated by fitting the correction data, which made it possible for the robot to move in an outdoor environment without the positioning system and environment model. The proposed algorithm was verified on the hexapod robot experimental platform. The turning and radius correction experiment of the robot with several gaits were carried out. The results indicated that the robot could follow the ideal radius and maintain stability, and the proposed ant-inspired turning strategy could easily make free turns with an arbitrary gait.