University of Freiburg

About: University of Freiburg is a education organization based out in Freiburg, Baden-Württemberg, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 41992 authors who have published 77296 publications receiving 2896269 citations. The organization is also known as: alberto-ludoviciana & Albert-Ludwigs-Universität Freiburg.

Guidelines for the use and interpretation of assays for monitoring cell death in higher eukaryotes

Abstract: Cell death is essential for a plethora of physiological processes, and its deregulation characterizes numerous human diseases Thus, the in-depth investigation of cell death and its mechanisms constitutes a formidable challenge for fundamental and applied biomedical research, and has tremendous implications for the development of novel therapeutic strategies It is, therefore, of utmost importance to standardize the experimental procedures that identify dying and dead cells in cell cultures and/or in tissues, from model organisms and/or humans, in healthy and/or pathological scenarios Thus far, dozens of methods have been proposed to quantify cell death-related parameters However, no guidelines exist regarding their use and interpretation, and nobody has thoroughly annotated the experimental settings for which each of these techniques is most appropriate Here, we provide a nonexhaustive comparison of methods to detect cell death with apoptotic or nonapoptotic morphologies, their advantages and pitfalls These guidelines are intended for investigators who study cell death, as well as for reviewers who need to constructively critique scientific reports that deal with cellular demise Given the difficulties in determining the exact number of cells that have passed the point-of-no-return of the signaling cascades leading to cell death, we emphasize the importance of performing multiple, methodologically unrelated assays to quantify dying and dead cells

Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters

Abstract: Recently, Rao-Blackwellized particle filters (RBPF) have been introduced as an effective means to solve the simultaneous localization and mapping problem. This approach uses a particle filter in which each particle carries an individual map of the environment. Accordingly, a key question is how to reduce the number of particles. In this paper, we present adaptive techniques for reducing this number in a RBPF for learning grid maps. We propose an approach to compute an accurate proposal distribution, taking into account not only the movement of the robot, but also the most recent observation. This drastically decreases the uncertainty about the robot's pose in the prediction step of the filter. Furthermore, we present an approach to selectively carry out resampling operations, which seriously reduces the problem of particle depletion. Experimental results carried out with real mobile robots in large-scale indoor, as well as outdoor, environments illustrate the advantages of our methods over previous approaches

G 2 o: A general framework for graph optimization

Abstract: Many popular problems in robotics and computer vision including various types of simultaneous localization and mapping (SLAM) or bundle adjustment (BA) can be phrased as least squares optimization of an error function that can be represented by a graph. This paper describes the general structure of such problems and presents g2o, an open-source C++ framework for optimizing graph-based nonlinear error functions. Our system has been designed to be easily extensible to a wide range of problems and a new problem typically can be specified in a few lines of code. The current implementation provides solutions to several variants of SLAM and BA. We provide evaluations on a wide range of real-world and simulated datasets. The results demonstrate that while being general g2o offers a performance comparable to implementations of state-of-the-art approaches for the specific problems.

Angiotensin-converting enzyme 2 protects from severe acute lung failure

Abstract: Acute respiratory distress syndrome (ARDS), the most severe form of acute lung injury, is a devastating clinical syndrome with a high mortality rate (30-60%) (refs 1-3). Predisposing factors for ARDS are diverse and include sepsis, aspiration, pneumonias and infections with the severe acute respiratory syndrome (SARS) coronavirus. At present, there are no effective drugs for improving the clinical outcome of ARDS. Angiotensin-converting enzyme (ACE) and ACE2 are homologues with different key functions in the renin-angiotensin system. ACE cleaves angiotensin I to generate angiotensin II, whereas ACE2 inactivates angiotensin II and is a negative regulator of the system. ACE2 has also recently been identified as a potential SARS virus receptor and is expressed in lungs. Here we report that ACE2 and the angiotensin II type 2 receptor (AT2) protect mice from severe acute lung injury induced by acid aspiration or sepsis. However, other components of the renin-angiotensin system, including ACE, angiotensin II and the angiotensin II type 1a receptor (AT1a), promote disease pathogenesis, induce lung oedemas and impair lung function. We show that mice deficient for Ace show markedly improved disease, and also that recombinant ACE2 can protect mice from severe acute lung injury. Our data identify a critical function for ACE2 in acute lung injury, pointing to a possible therapy for a syndrome affecting millions of people worldwide every year.