Localized ultrasonic stimulation using a piezoelectric micromachined ultrasound transducer array for selective neural differentiation of magnetic cell-based robots

Abstract

Targeted stem cell delivery utilizing a magnetic actuation system is an emerging technology in stem cell engineering that efficiently targets stem cells in specific areas in vitro. However, integrating precise magnetic control systems with selective neural differentiation has not yet been widely considered for building successful neural networks. Challenges arise in creating targeted functional neuronal networks, largely due to difficulties in simultaneously controlling the positions of stem cells and selectively stimulating their differentiation. These challenges often result in suboptimal differentiation rates and abnormalities in transplanted neural stem cells. In contrast, ultrasound stimulation has superior tissue penetration and focusing capability, and represents a promising noninvasive neural stimulation technique capable of modulating neural activity and promoting selective differentiation into neuronal stem cells. In this study, we introduce a method for targeted neural differentiation using localized ultrasonic stimulation with a piezoelectric micromachined ultrasound transducer (pMUT) array. Differentiation was assessed quantitatively by monitoring neurite outgrowth as the ultrasound intensity was increased. The neurite length of cells ultrasonically stimulated for 40 min was found to have increased, compared to the non-stimulated group (119.9 +/- 34.3 mu m vs. 63.2 +/- 17.3 mu m, respectively). Targeted differentiation was confirmed by measuring neurite lengths, where selective ultrasound stimulation induced differentiation in cells that were precisely delivered via an electromagnetic system. Magnetic cell-based robots reaching the area of localized ultrasound stimulation were confirmed to have enhanced differentiation. This research demonstrated the potential of the combination of precise stem cell delivery with selective neural differentiation to establish functional neural networks.