A two-dimensional microarray of ten thousand (100100) chondrocyte-spheroids was successfully constructed with a 100-µm spacing on a micropatterned gold electrodes that were coated with poly(ethylene glycol) (PEG) hydrogels. The PEGylated surface as a cytophobic region was regulated by controlling the gel structure through photolithography. In this way, a PEG hydrogel was modulated enough to inhibit outgrowth of chondrocytes from cell adhering region in the horizontal direction. These structural control of PEG hydrogel was critical for inducing formation of three-dimensional chondrocyte condensations (spheroids) within 24 hours. We report noninvasive monitoring of the cellular functional change at the cell membrane using a chondrocyte-based field effect transistor (FET), which is based on detection of extracellular potential change induced as a result of the interaction between extracellular matrix (ECM) protein secreted from spheroid and substrate at the cell membrane. The interface potential change at the cell membrane/gate insulator interface can be monitored during the uptake of substrate without any labeling materials. Our findings on the time course of the interface potential would provide important information to understand the uptake kinetics for cellular differentiation.

We describe a technique for the registration of three dimensional (3D) knee femur surface points from MR image data sets; it is a technique that can track local cartilage thickness changes over time. In the first coarse registration step, we use the direction vectors of the volume given by the cloud of points of the MR image to correct for different knee joint positions and orientations in the MR scanner. In the second fine registration step, we propose a global search algorithm that simultaneously determines the optimal transformation parameters and point correspondences through searching a six dimensional space of Euclidean motion vectors (translation and rotation). The present algorithm is grounded on a mathematical theory - Lipschitz optimization. Compared with the other three registration approaches (ICP, EM-ICP, and genetic algorithms), the proposed method achieved the highest registration accuracy on both animal and clinical data.