A novel technique for selective NF-kappa B inhibition in Kupffer cells: contrary effects in fulminant hepatitis and ischaemia-reperfusion.

Background and aims: The transcription factor nuclear factor kappa B (NF-kB) has risen as a promising target for anti-inflammatory therapeutics. In the liver, however, NFkB inhibition mediates both damaging and protective effects. The outcome is deemed to depend on the liver cell type addressed. Recent gene knock-out studies focused on the role of NF-kB in hepatocytes, whereas the role of NF-kB in Kupffer cells has not yet been investigated in vivo. Here we present a novel approach, which may be suitable for clinical application, to selectively target NF-kB in Kupffer cells and analyse the effects in experimental models of liver injury. Methods: NF-kB inhibiting decoy oligodeoxynucleotides were loaded upon gelatin nanoparticles (D-NPs) and their in vivo distribution was determined by confocal microscopy. Liver damage, NF-kB activity, cytokine levels and apoptotic protein expression were evaluated after lipopolysaccharide (LPS), D-galactosamine (GalN)/LPS, or concanavalin A (ConA) challenge and partial warm ischaemia and subsequent reperfusion, respectively. Results: D-NPs were selectively taken up by Kupffer cells and inhibited NF-kB activation. Inhibition of NF-kB in Kupffer cells improved survival and reduced liver injury after GalN/LPS as well as after ConA challenge. While anti-apoptotic protein expression in liver tissue was not reduced, pro-apoptotic players such as cJun N-terminal kinase (JNK) were inhibited. In contrast, selective inhibition of NF-kB augmented reperfusion injury. Conclusions: NF-kB inhibiting decoy oligodeoxynucleotide- loaded gelatin nanoparticles is a novel tool to selectively inhibit NF-kB activation in Kupffer cells in vivo. Thus, liver injury can be reduced in experimental fulminant hepatitis, but increased at ischaemia–reperfusion

A Column Generation Approach for Optimized Routing and Coordination of a UAV Fleet

Unmanned Aerial Vecicles (UAVs) in civil and military applications are becoming increasingly popular. Various platform types have already shown their great potential in missions that require rapid surveillance capabilities or logistic support. Large scale incidents require the deployment of several platforms with various capabilities. In this case, coordinated use will lead to more efficient use of the given resources. Problems to resolve resemble known optimization problems from the field of vehicle routing or scheduling. The problem considered in this work includes a given team of homogenous UAVs and a set of target locations with certain requests that need to be served. It is modeled as a variant of the Vehicle Routing Problem (VRP) that is known to be NP hard, i.e. until now no algorithm is known that can solve the problem in polynomial run-time. In this paper, the problem is formulated using a path flow formulation and a column generation algorithm has been implemented and tested to solve simulated realtime instances of the problem in suitable time