Comparison of Efficacy and Safety Between First and Second Generation Drug-Eluting Stents in Patients with Stable Coronary Artery Disease: A Single-Center Retrospective Study

Background: Lots of trials demonstrate that second-generation drug-eluting stents (G2-DES), with their improved properties, offer significantly superior efficacy and safety profiles compared to first generation DES (G1-DES) for patients with coronary artery disease (CAD) receiving percutaneous coronary intervention (PCI). This study aimed to verify the advantage of G2-DES over G1-DES in Chinese patients with stable CAD (SCAD). Methods: For this retrospective observational analysis, 2709 SCAD patients with either G1-DES (n = 863) or G2-DES (n = 1846) were enrolled consecutively throughout 2013. Propensity score matching (PSM) was applied to control differing baseline factors. Two-year outcomes, including major adverse coronary events as well as individual events, including target vessel-related myocardial infarction, target lesion revascularization (TLR), target vessel revascularization, and cardiogenic death were evaluated. Results: The incidence of revascularization between G1- and G2-DES showed a trend of significant difference with a threshold P - value (8.6% vs. 6.7%, χ2 = 2.995, P = 0.084). G2-DES significantly improved TLR-free survival compared to G1-DES (96.6% vs. 97.9%, P = 0.049) and revascularization-free survival curve showed a trend of improvement of G2-DES (92.0% vs. 93.8%, P = 0.082). These differences diminished after PSM. Multivariate Cox proportional hazard regression analysis showed a trend for G1-associated increase in revascularization (hazard ratio: 1.28, 95% confidence interval: 0.95-1.72, P = 0.099) while no significance was found after PSM. Other endpoints showed no significant differences after multivariate adjustment regardless of PSM. Conclusions: G1-DES showed the same safety as G2-DES in this large Chinese cohort of real-world patients. However, G2-DES improved TLR-free survival of SCAD patients 2 years after PCI. The advantage was influenced by baseline clinical factors. G1-DES was associated with a trend of increase in revascularization risk and was not an independent predictor of worse medium-term prognosis compared with G2-DES

Laboratory observation of ion acceleration via reflection off laser-produced magnetized collisionless shocks

Fermi acceleration by collisionless shocks is believed to be the primary mechanism to produce high energy charged particles in the Universe,where charged particles gain energy successively from multiple reflections off the shock front.Here,we present the first direct experimental evidence of ion energization from reflection off a supercritical quasi perpendicular collisionless shock,an essential component of Fermi acceleration in a laser produced magnetized plasma. We observed a quasi monoenergetic ion beam with 2,4 times the shock velocity in the upstream flow using time of flight method. Our related kinetic simulations reproduced the energy gain and showed that these ions were first reflected and then accelerated mainly by the motional electric field associated with the shock. This mechanism can also explain the quasi monoenergetic fast ion component observed in the Earth's bow shock

Distributed evolutionary algorithms and their models: A survey of the state-of-the-art

The increasing complexity of real-world optimization problems raises new challenges to evolutionary computation. Responding to these challenges, distributed evolutionary computation has received considerable attention over the past decade. This article provides a comprehensive survey of the state-of-the-art distributed evolutionary algorithms and models, which have been classified into two groups according to their task division mechanism. Population-distributed models are presented with master-slave, island, cellular, hierarchical, and pool architectures, which parallelize an evolution task at population, individual, or operation levels. Dimension-distributed models include coevolution and multi-agent models, which focus on dimension reduction. Insights into the models, such as synchronization, homogeneity, communication, topology, speedup, advantages and disadvantages are also presented and discussed. The study of these models helps guide future development of different and/or improved algorithms. Also highlighted are recent hotspots in this area, including the cloud and MapReduce-based implementations, GPU and CUDA-based implementations, distributed evolutionary multiobjective optimization, and real-world applications. Further, a number of future research directions have been discussed, with a conclusion that the development of distributed evolutionary computation will continue to flourish