Search

Yanfen Cui,1,* Caiyuan Zhang,1,* Ran Luo,1 Huanhuan Liu,1 Zhongyang Zhang,1 Tianyong Xu,2 Yong Zhang,2 Dengbin Wang11Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, 2MR Advanced Application and Research Center, GE Healthcare China, Shanghai, People’s Republic of China *These authors contributed equally to this workPurpose: Arginine-glycine-aspartic acid (RGD)-based nanoprobes allow specific imaging of integrin αvβ3, a protein overexpressed during angiogenesis. Therefore, this study applied a novel RGD-coupled, polyacrylic acid (PAA)-coated ultrasmall superparamagnetic iron oxide (USPIO) (referred to as RGD-PAA-USPIO) in order to detect tumor angiogenesis and assess the early response to antiangiogenic treatment in human nasopharyngeal carcinoma (NPC) xenograft model by magnetic resonance imaging (MRI).Materials and methods: The binding specificity of RGD-PAA-USPIO with human umbilical vein endothelial cells (HUVECs) was confirmed by Prussian blue staining and transmission electron microscopy in vitro. The tumor targeting of RGD-PAA-USPIO was evaluated in the NPC xenograft model. Later, mice bearing NPC underwent MRI at baseline and after 4 and 14 days of consecutive treatment with Endostar or phosphate-buffered saline (n=10 per group).Results: The specific uptake of the RGD-PAA-USPIO nanoparticles was mainly dependent on the interaction between RGD and integrin αvβ3 of HUVECs. The tumor targeting of RGD-PAA-USPIO was observed in the NPC xenograft model. Moreover, the T2 relaxation time of mice in the Endostar-treated group decreased significantly compared with those in the control group both on days 4 and 14, consistent with the immunofluorescence results of CD31 and CD61 (P

In this paper, we present a review of the current research status of multi-relational fusion and systematically summarize the multiple relationships among different measurement entities and entities in the scientific literature. Further, we propose a multi-relational extraction and relational fusion approach to thematic identification. We divide the relationships for topic recognition into three types—basic, enhancing, and supplement—that can be formed by integrating co-occurrence, citation, and co-authorship relationships. Finally, as an empirical analysis, we use the PathSelClus algorithm to realize topic clustering based on multivariate relation fusion. Empirical analysis confirms that multivariate relational fusion can effectively improve the effectiveness of topic clustering.

Automatic neural architecture design has shown its potential in discovering powerful neural network architectures. Existing methods, no matter based on reinforcement learning or evolutionary algorithms (EA), conduct architecture search in a discrete space, which is highly inefficient. In this paper, we propose a simple and efficient method to automatic neural architecture design based on continuous optimization. We call this new approach neural architecture optimization (NAO). There are three key components in our proposed approach: (1) An encoder embeds/maps neural network architectures into a continuous space. (2) A predictor takes the continuous representation of a network as input and predicts its accuracy. (3) A decoder maps a continuous representation of a network back to its architecture. The performance predictor and the encoder enable us to perform gradient based optimization in the continuous space to find the embedding of a new architecture with potentially better accuracy. Such a better embedding is then decoded to a network by the decoder. Experiments show that the architecture discovered by our method is very competitive for image classification task on CIFAR-10 and language modeling task on PTB, outperforming or on par with the best results of previous architecture search methods with a significantly reduction of computational resources. Specifically we obtain 1.93% test set error rate for CIFAR-10 image classification task and 56.0 test set perplexity of PTB language modeling task. Furthermore, combined with the recent proposed weight sharing mechanism, we discover powerful architecture on CIFAR-10 (with error rate 2.93%) and on PTB (with test set perplexity 56.6), with very limited computational resources (less than 10 GPU hours) for both tasks., Comment: NeurIPS 2018. Code available at: https://github.com/renqianluo/NAO

Xiaoping Li,1–3,* Chi Cai,3,* Rong Luo,4 Rongjian Jiang,1 Jie Zeng,1 Yijia Tang,1 Yang Chen,1 Michael Fu,5 Tao He,1 Wei Hua31Department of Cardiology, Hospital of the University of Electronic Science and Technology of China, Sichuan Provincial People’s Hospital, Chengdu, Sichuan, 2School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, 3Department of Clinical Electrophysiology, Fuwai Hospital and Cardiovascular Institute, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 4Key Laboratory of Thermoregulation and Inflammation of Sichuan Higher Education Institutes, Chengdu Medical College, Chengdu, Sichuan, People’s Republic of China; 5Department of Medicine, Sahlgrenska University Hospital/Östra Hospital, Gothenburg, Sweden*These authors contributed equally tothisworkObjective: Recent studies have shown that sex and age are associated with outcomes in patients with cardiomyopathy. The purpose of this study was to determine the all-cause mortality of dilated cardiomyopathy (DCM) by age and sex.Methods and results: The patients were divided into non-elderly (age

Hepatocellular carcinoma(HCC) is serious condition associated with a high morbidity and mortality. Therefore is an urgent need to develop novel noninvasive techniques for early diagnosis, particularly for patients with AFP-negative [AFP(-)] HCC. In this study, iTRAQ-MALDI-MS/MS was used to identify differentially expressed proteins in AFP(-) HBV-related HCC compared with non-cancerous hepatitis B virus (HBV) and healthy controls subjects.Serum was obtained from 18 patients with AFP(-) HBV-related HCC, 18 matched patients with HBV without HCC and 18 healthy control subjects. High abundance proteins were removed from serum and the differentially expressed proteins from the three groups were screened out using iTRAQ-MALDI-MS/MS. The Gene Ontology (GO) function and the interaction networks of differentially expressed proteins were then analyzed. A total of 24 expressed differential proteins associated with AFP(-) HBV-related HCC were screened out, 15 proteins were up-regulated and 9 down-regulated. The most common molecular function of the 24 differentially expressed proteins was enzyme inhibition. Interaction network of the 24 differentially expressed proteins showed that 14 proteins (C5, KNG1, FN1, LRG1, HRG, SERPINC1, CRP, APOB, SAA1, APCS, C4BPA, CFI, CFB and GSN) were central to the functional network. The expression levels of the GSN protein were down-regulated in AFP(-) HBV-related HCC subjects compared with healthy controls and the HBV group (p

This thesis aims at developing efficient methods for control of large-scale systems by employing state-of-the-art control methods and optimization techniques. This thesis is divided into two parts. In the first part, we address dynamic traffic routing for urban transportation networks. In the second part, we address multi-agent model predictive control of a class of hybrid systems with limiting information sharing and subject to global hard constraints.