This study demonstrates the feasibility of using nanoshells in vivo as a new contrast-enhancing agent for photoacoustic tomography. Deep penetrating near-infrared light was employed to image the in vivo distribution of poly(ethylene glycol)-coated nanoshells circulating in the vasculature of a rat brain. The images, captured after three sequential administrations of nanoshells, present a gradual enhancement of the optical absorption in the brain vessels by up to 63%. Subsequent clearance of the nanoshells from the blood was imaged for ∼6 h after the administrations.

Background The angiotensin‐receptor neprilysin inhibitor (ARNI) sacubitril/valsartan was shown to be superior to the angiotensin‐converting enzyme inhibitor enalapril in terms of reducing cardiovascular mortality in the PARADIGM‐HF (Prospective Comparison of ARNI with angiotensin‐converting enzyme inhibitor to Determine Impact on Global Mortality and Morbidity in Heart Failure) study. However, the impact of ARNI on cardiac reverse remodeling (CRR) has not been established. Methods and Results We conducted a meta‐analysis to compare the effects of ARNI versus angiotensin‐converting enzyme inhibitors or angiotensin receptor blockers on CRR indices. We searched databases for studies published between 2010 and 2019 that reported CRR indices following ARNI administration. Effect size was expressed as mean difference (MD) with 95% CIs. Twenty studies enrolling 10 175 patients were included. ARNI improved functional capacity in patients with heart failure (HF) and a reduced ejection fraction (EF), including increasing New York Heart Association functional class (MD −0.79, 95% CI −0.86, −0.71) and 6‐minute walking distance (MD 27.62 m, 95% CI 15.76, 39.48). ARNI outperformed angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers in terms of CRR indices, with striking changes in left ventricular EF, diameter, and volume. However, there were no significant improvements in indices except left ventricular mass index (MD −3.25 g/m 2 , 95% CI −3.78, −2.72) and left atrial volume (MD −7.20 mL, 95% CI −14.11, −0.29) in HF patients with preserved EF treated with ARNI. Improvements in CRR indices were observed at 3 months and became more significant with longer follow‐up to 12 months. The regression equation for the relationship between left ventricular EF and end‐diastolic dimension was y=0.041+0.071x+0.045x 2 +0.006x 3 . Conclusions ARNI distinctly improved left ventricular size and hypertrophy compared with angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers in HF with reduced EF patients, even after short‐term follow‐up. Patients appeared to benefit more in terms of CRR treated with ARNI as early as possible and for at least 3 months. Further large sample trials are required to determine the effects of ARNI on CRR in HF with preserved EF patients.

SUMMARYVirtual network (VN) embedding is a major challenge in network virtualization. In this paper, we aim to increase the acceptance ratio of VNs and the revenue of infrastructure providers by optimizing VN embedding costs. We first establish two models for VN embedding: an integer linear programming model for a substrate network that does not support path splitting and a mixed integer programming model when path splitting is supported. Then we propose a unified enhanced particle swarm optimization‐based VN embedding algorithm, called VNE‐UEPSO, to solve these two models irrespective of the support for path splitting. In VNE‐UEPSO, the parameters and operations of the particles are well redefined according to the VN embedding context. To reduce the time complexity of the link mapping stage, we use shortest path algorithm for link mapping when path splitting is unsupported and propose greedy k‐shortest paths algorithm for the other case. Furthermore, a large to large and small to small preferred node mapping strategy is proposed to achieve better convergence and load balance of the substrate network. The simulation results show that our algorithm significantly outperforms previous approaches in terms of the VN acceptance ratio and long‐term average revenue. Copyright © 2012 John Wiley & Sons, Ltd.

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