Perineural invasion (PNI) is the underestimated metastatic pathway and has been widely recognized as a negative prognostic factor in many human cancers. L1CAM is one of members of the immunoglobulin-like cell adhesion molecule (CAM) family, which play a role in neural development. Moreover, a new role of L1CAM outside the nervous system has been revealed. Overexpression of L1CAM was involved in the tumor progression and LN metastasis in various malignancies. In the present study, presence of PNI and L1CAM expression were examined to define their prognostic values in OSCC. In addition, association of L1CAM expression with presence of PNI was assessed to define the value as a candidate molecule supporting the diagnosis of PNI. We found that presence of PNI significantly correlated with LN metastasis and advanced clinical stage. L1CAM expression also significantly correlated with differentiation, lymph node metastasis, advanced clinical stage, as well as presence of PNI. Our results suggest that L1CAM seems to play a role in tumor progression, possibly through the PNI-related mechanism and could be a molecular marker for supporting the presence of PNI and predicting clinical outcome in OSCC.

This study presents a precise relative navigation algorithm using both laser and Global Positioning System (GPS) measurements in real time. The measurement model of the navigation algorithm between two spacecraft is comprised of relative distances measured by laser instruments and single differences of GPS pseudo-range measurements in spherical coordinates. Based on the measurement model, the Extended Kalman Filter (EKF) is applied to smooth the pseudo-range measurements and to obtain the relative navigation solution. While the navigation algorithm using only laser measurements might become inaccurate because of the limited accuracy of spacecraft attitude estimation when the distance between spacecraft is rather large, the proposed approach is able to provide an accurate solution even in such cases by employing the smoothed GPS pseudo-range measurements. Numerical simulations demonstrate that the errors of the proposed algorithm are reduced by more than about 12% compared to those of an algorithm using only laser measurements, as the accuracy of angular measurements is greater than 0.001° at relative distances greater than 30 km.