Targeting Glycolysis in Macrophages Confers Protection Against Pancreatic Ductal Adenocarcinoma

Inflammation in the tumor microenvironment has been shown to promote disease progression in pancreatic ductal adenocarcinoma (PDAC); however, the role of macrophage metabolism in promoting inflammation is unclear. Using an orthotopic mouse model of PDAC, we demonstrate that macrophages from tumor-bearing mice exhibit elevated glycolysis. Macrophage-specific deletion of Glucose Transporter 1 (GLUT1) significantly reduced tumor burden, which was accompanied by increased Natural Killer and CD8+ T cell activity and suppression of the NLRP3-IL1β inflammasome axis. Administration of mice with a GLUT1-specific inhibitor reduced tumor burden, comparable with gemcitabine, the current standard-of-care. In addition, we observe that intra-tumoral macrophages from human PDAC patients exhibit a pronounced glycolytic signature, which reliably predicts poor survival. Our data support a key role for macrophage metabolism in tumor immunity, which could be exploited to improve patient outcomes.     

3-D-Skeleton-Based Head Detection and Tracking Using Range Images

Vision-based 3-D head detection and tracking systems have been studied in several applications like video surveillance, face-detection systems, and occupant posture analysis. In this paper, we present the development of a topology-based framework using a 3-D skeletal model for the robust detection and tracking of a vehicle occupant's head position from low-resolution range image data for a passive safety system. Unlike previous approaches to head detection, the proposed approach explores the topology information of a scene to detect the position of the head. Among the different available topology representations, the Reeb graph technique is chosen and is adapted to low-resolution 3-D range images. Invariance of the graph under rotations is achieved by using a Morse radial distance function. To cope with the particular challenges such as the noise and the large variations in the density of the data, a voxel neighborhood connectivity notion is proposed. A multiple-hypothesis tracker (MHT) with nearest-neighbor data association and Kalman filter prediction is applied on the endpoints of the Reeb graph to select and filter the correct head candidate out of Reeb graph endpoints. A systematic evaluation of the head detection framework is carried out on full-scale experimental 3-D range images and compared with the ground truth. It is shown that the Reeb graph topology algorithm developed herein allows the correct detection of the head of the occupant with only two head candidates as input to the MHT. Results of the experiments demonstrate that the proposed framework is robust under the large variations of the scene. The processing requirements of the proposed approach are discussed. It is shown that the number of operations is rather low and that real-time processing requirements can be met with the proposed method.     

Active filtering of physiological motion in robotized surgery using predictive control

This work presents a predictive-control approach to active mechanical filtering of complex, periodic motions of organs induced by respiration or heart beating in robotized surgery. Two different predictive-control schemes are proposed for the compensation of respiratory motions or cardiac motions. For respiratory motions, the periodic property of the disturbance has been included into the input-output model of the controlled system so as to have the robotic system learn and anticipate perturbation motions. A new cost function is proposed for the unconstrained generalized predictive controller (GPC), where reference tracking is decoupled from the rejection of predictable periodic motions. Cardiac motions are more complex, since they are the combination of two periodic nonharmonic components. An adaptive disturbance predictor is proposed which outputs future predicted disturbance values. These predicted values are used to anticipate the disturbance by using the predictive feature of a regular GPC. Experimental results are presented on a laboratory testbed and in vivo on pigs. They demonstrate the effectiveness of the two proposed methods to compensate complex physiological motion.