NO- and haem-independent activation of soluble guanylyl cyclase: molecular basis and cardiovascular implications of a new pharmacological principle

1. Soluble guanylyl cyclase (sGC) is the only proven receptor for the ubiquitous biological messenger nitric oxide (NO) and is intimately involved in many signal transduction pathways, most notably in regulating vascular tone and platelet function. sGC is a heterodimeric (α/ß) protein that converts GTP to cyclic GMP; NO binds to its prosthetic haem group. Here, we report the discovery of a novel sGC activating compound, its interaction with a previously unrecognized regulatory site and its therapeutic implications. 2. Through a high-throughput screen we identified BAY 58-2667, an amino dicarboxylic acid which potently activates sGC in an NO-independent manner. In contrast to NO, YC-1 and BAY 41-2272, the sGC stimulators described recently, BAY 58-2667 activates the enzyme even after it has been oxidized by the sGC inhibitor ODQ or rendered haem deficient. 3. Binding studies with radiolabelled BAY 58-2667 show a high affinity site on the enzyme. 4. Using photoaffinity labelling studies we identified the amino acids 371 (α-subunit) and 231 – 310 (ß-subunit) as target regions for BAY 58-2667. 5. sGC activation by BAY 58-2667 results in an antiplatelet activity both in vitro and in vivo and a potent vasorelaxation which is not influenced by nitrate tolerance. 6. BAY 58-2667 shows a potent antihypertensive effect in conscious spontaneously hypertensive rats. In anaesthetized dogs the hemodynamic effects of BAY 58-2667 and GTN are very similar on the arterial and venous system. 7. This novel type of sGC activator is a valuable research tool and may offer a new approach for treating cardiovascular diseases

IoT networks 3D deployment using hybrid many-objective optimization algorithms

International audienceWhen resolving many-objective problems, multi-objective optimization algorithms encounter several difficulties degrading their performances. These difficulties may concern the exponential execution time, the effectiveness of the mutation and recombination operators or finding the tradeoff between diversity and convergence. In this paper, the issue of 3D redeploying in indoor the connected objects (or nodes) in the Internet of Things collection networks (formerly known as wireless sensor nodes) is investigated. The aim is to determine the ideal locations of the objects to be added to enhance an initial deployment while satisfying antagonist objectives and constraints. In this regard, a first proposed contribution aim to introduce an hybrid model that includes many-objective optimization algorithms relying on decomposition (MOEA/D, MOEA/DD) and reference points (Two_Arch2, NSGA-III) while using two strategies for introducing the preferences (PI-EMO-PC) and the dimensionality reduction (MVU-PCA). This hybridization aims to combine the algorithms advantages for resolving the many-objective issues. The second contribution concerns prototyping and deploying real connected objects which allows assessing the performance of the proposed hybrid scheme on a real world environment. The obtained experimental and numerical results show the efficiency of the suggested hybridization scheme against the original algorithms