The Interplay between NF-kappaB and E2F1 Coordinately Regulates Inflammation and Metabolism in Human Cardiac Cells

Pyruvate dehydrogenase kinase 4 (PDK4) inhibition by nuclear factor-κB (NF-κB) is related to a shift towards increased glycolysis during cardiac pathological processes such as cardiac hypertrophy and heart failure. The transcription factors estrogen-related receptor-α (ERRα) and peroxisome proliferator-activated receptor (PPAR) regulate PDK4 expression through the potent transcriptional coactivator PPARγ coactivator-1α (PGC-1α). NF-κB activation in AC16 cardiac cells inhibit ERRα and PPARβ/δ transcriptional activity, resulting in reduced PGC-1α and PDK4 expression, and an enhanced glucose oxidation rate. However, addition of the NF-κB inhibitor parthenolide to these cells prevents the downregulation of PDK4 expression but not ERRα and PPARβ/δ DNA binding activity, thus suggesting that additional transcription factors are regulating PDK4. Interestingly, a recent study has demonstrated that the transcription factor E2F1, which is crucial for cell cycle control, may regulate PDK4 expression. Given that NF-κB may antagonize the transcriptional activity of E2F1 in cardiac myocytes, we sought to study whether inflammatory processes driven by NF-κB can downregulate PDK4 expression in human cardiac AC16 cells through E2F1 inhibition. Protein coimmunoprecipitation indicated that PDK4 downregulation entailed enhanced physical interaction between the p65 subunit of NF-κB and E2F1. Chromatin immunoprecipitation analyses demonstrated that p65 translocation into the nucleus prevented the recruitment of E2F1 to the PDK4 promoter and its subsequent E2F1-dependent gene transcription. Interestingly, the NF-κB inhibitor parthenolide prevented the inhibition of E2F1, while E2F1 overexpression reduced interleukin expression in stimulated cardiac cells. Based on these findings, we propose that NF-κB acts as a molecular switch that regulates E2F1-dependent PDK4 gene transcription.

Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed

Visual SLAM for underwater vehicles using video velocity log and natural landmarks

A visual SLAM system has been implemented and optimised for real-time deployment on an AUV equipped with calibrated stereo cameras. The system incorporates a novel approach to landmark description in which landmarks are local sub maps that consist of a cloud of 3D points and their associated SIFT/SURF descriptors. Landmarks are also sparsely distributed which simplifies and accelerates data association and map updates. In addition to landmark-based localisation the system utilises visual odometry to estimate the pose of the vehicle in 6 degrees of freedom by identifying temporal matches between consecutive local sub maps and computing the motion. Both the extended Kalman filter and unscented Kalman filter have been considered for filtering the observations. The output of the filter is also smoothed using the Rauch-Tung-Striebel (RTS) method to obtain a better alignment of the sequence of local sub maps and to deliver a large-scale 3D acquisition of the surveyed area. Synthetic experiments have been performed using a simulation environment in which ray tracing is used to generate synthetic images for the stereo system