Endoscopic submucosal dissection with a novel high viscosity injection solution (LiftUp) in an ex vivo model: a prospective randomized study

Introduction  Endoscopic submucosal dissection (ESD) is increasingly being used in the western world. Submucosal injectates are an essential tool for the ESD procedure. In this study, we evaluated a novel copolymer injectate (LiftUp, Ovesco, Tübingen Germany) in an established ESD model (EASIE-R) in comparison to existing submucosal injectables. Materials and methods  We conducted a prospective, randomized ex vivo study performing ESD with three injectates: LiftUp, hydroxyethyl starch (HAES 6 %) and normal saline solution (NaCl 0.9 %). A total of 60 artificial lesions, each 3 × 3 cm in size, were resected in an ex vivo porcine model, utilizing one of the three studied injectates (n = 20 ESDs per injectate). Study parameters were: en bloc resection rate, perforation rate, lifting property, time of injection, injectate volume, general ESD procedure time, and overall procedure time. Results  All 60 lesions were successfully resected using the standard ESD technique. LiftUp had no procedure related perforations, one perforation occurred in the HAES group, and two perforations in the NaCl group ( P  > 0.05). Furthermore, adequate lifting was achieved in 16/20 (80 %) using LiftUp, 6/20 (30 %) in the HAES group and 6/20 (30 %) in the NaCl group ( P  < 0.0002). En bloc resection was achieved in 19 (95 %) with LiftUp, in 20 (100 %) with HAES, and in 16 (80 %) with NaCl. General ESD procedure time and overall procedure time were not different among the three groups. Conclusion  LiftUp appears to be a safe alternative to established fluids for ESD. It had a significantly improved lifting effect and required significantly less injected volume compared to well-established lifting solutions

Cellular Automata Applications in Shortest Path Problem

Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201