Xueqian Wang

It has been suggested that a vascular-like cell has multipotent regenerative and mesenchymal lineage relationships. The identity of this stem/progenitor cell has remained elusive. We report here that adult central nervous system (CNS) capillaries contain a distinct population of microvascular cells, the pericyte that are nestin/NG2 positive and in response to basic fibroblast growth factor (bFGF) differentiate into cells of neural lineage. In their microvascular location, pericytes express nestin and NG2 proteoglycan. In serum containing media primary (0 to 7 day old) CNS pericytes are nestin positive, NG2 positive, alpha smooth muscle actin (alphaSMA) positive, and do not bind the endothelial cell specific griffonia symplicifolia agglutinin (GSA). In serum containing media, pericytes do not undergo neurogenesis but are induced to express alphaSMA. In bFGF containing media without serum, CNS pericytes form small clusters and multicellular spheres. Differentiated spheres expressed neuronal and glial cell markers. After disruption and serial dilution, differentiated spheres were capable of self-renewal. When differentiated spheres were disrupted and cultured in the presence of serum, multiple adherent cell populations were identified by dual and triple immunocytochemistry. Cells expressing markers characteristic of pericytes, neurons, and glial cells were generated. Many of the cells exhibited dual expression of differentiation markers. With prolonged culture fully differentiated cells of neural lineage were present. Results indicate that adult CNS microvascular pericytes have neural stem cell capability.

Abstract Tactile sensing technology is crucial for soft grippers. Soft grippers equipped with intelligent tactile sensing systems based on various sensors can interact safely with the unstructured environments and obtain precise properties of objects (e.g., size and shape). It is essential to develop state‐of‐the‐art sensing technologies for soft grippers to handle different grasping tasks. In this review, the development of tactile sensing techniques for robotic hands is first introduced. Then, the principles and structures of different types of sensors normally adopted in soft grippers, including capacitive tactile sensors, piezoresistive tactile sensors, piezoelectric tactile sensors, fiber Bragg grating (FBG) sensors, vision‐based tactile sensors, triboelectric tactile sensors, and other advanced sensors developed recently are briefly presented. Furthermore, sensing modalities and methodologies for soft grippers are also described in aspects of force measurement, perception of object properties, slip detection, and fusion of perception. The application scenarios of soft grippers are also summarized based on these advanced sensing technologies. Finally, the challenges of tactile sensing technologies for soft grippers that need to be tackled are discussed and perspectives in addressing these challenges are pointed out.