Establishment and Validation of Computational Model for MT1-MMP Dependent ECM Degradation and Intervention Strategies

MT1-MMP is a potent invasion-promoting membrane protease employed by aggressive cancer cells. MT1-MMP localizes preferentially at membrane protrusions called invadopodia where it plays a central role in degradation of the surrounding extracellular matrix (ECM). Previous reports suggested a role for a continuous supply of MT1-MMP in ECM degradation. However, the turnover rate of MT1-MMP and the extent to which the turnover contributes to the ECM degradation at invadopodia have not been clarified. To approach this problem, we first performed FRAP (Fluorescence Recovery after Photobleaching) experiments with fluorescence-tagged MT1-MMP focusing on a single invadopodium and found very rapid recovery in FRAP signals, approximated by double-exponential plots with time constants of 26 s and 259 s. The recovery depended primarily on vesicle transport, but negligibly on lateral diffusion. Next we constructed a computational model employing the observed kinetics of the FRAP experiments. The simulations successfully reproduced our FRAP experiments. Next we inhibited the vesicle transport both experimentally, and in simulation. Addition of drugs inhibiting vesicle transport blocked ECM degradation experimentally, and the simulation showed no appreciable ECM degradation under conditions inhibiting vesicle transport. In addition, the degree of the reduction in ECM degradation depended on the degree of the reduction in the MT1-MMP turnover. Thus, our experiments and simulations have established the role of the rapid turnover of MT1-MMP in ECM degradation at invadopodia. Furthermore, our simulations suggested synergetic contributions of proteolytic activity and the MT1-MMP turnover to ECM degradation because there was a nonlinear and marked reduction in ECM degradation if both factors were reduced simultaneously. Thus our computational model provides a new in silico tool to design and evaluate intervention strategies in cancer cell invasion

Model-based Gaze Estimation with Transparent Markers on Large Screens

Several technical issues that affect eye-tracking have arisen concomitantly with the steadily increasing sizes of personal displays recently. One such issue is the loss of the illumination reflection of the near-infrared light-emitting diodes used as reference points around the edge of the display. Another issue is that reference identification is required for practical usage. Therefore, this paper proposes gaze estimation with transparent markers for large display environments to solve these problems. The transparent markers can be distributed on the screen, and a unique ID is assigned to each marker using linear polarization angles. The reference is detected using a polarization camera through the reflection on the cornea. The results of experiments conducted using a 50-inch display indicate that the proposed method can estimate the point-of-gaze to within 2.1 degrees of error. We confirmed that on-screen markers in sizable displays could be effectively used as references instead of illumination sources