Blockchain Data Mining With Graph Learning: A Survey.

Blockchain data mining has the potential to reveal the operational status and behavioral patterns of anonymous participants in blockchain systems, thus providing valuable insights into system operation and participant behavior. However, traditional blockchain analysis methods suffer from the problems of being unable to handle the data due to its large volume and complex structure. With powerful computing and analysis capabilities, graph learning can solve the current problems through handling each node's features and linkage relationships separately and exploring the implicit properties of data from a graph perspective. This paper systematically reviews the blockchain data mining tasks based on graph learning approaches. First, we investigate the blockchain data acquisition method, integrate the currently available data analysis tools, and divide the sampling method into rule-based and cluster-based techniques. Second, we classify the graph construction into transaction-based blockchain and account-based methods, and comprehensively analyze the existing blockchain feature extraction methods. Third, we compare the existing graph learning algorithms on blockchain and classify them into traditional machine learning-based, graph representation-based, and graph deep learning-based methods. Finally, we propose future research directions and open issues which are promising to address.

[Corrigendum] Carvacrol may alleviate vascular inflammation in diabetic db/db mice.

Following the publication of the above article, the authors contacted the Editorial Office to explain that they made a couple of inadvertent errors in the assembly of the data panels showing the results of immunohistochemical experiments in Fig. 5K on p. 983 (the 'TLR4' experiments); essentially, the data panels selected for the '10 mg/mg Carvacrol' and '5 mg/kg Carvacrol' experiments were copied across from those shown for the 'NF­κB' experiments in the row above (Fig. 5I). The revised version of Fig. 5, showing the correct data for the'10 mg/mg Carvacrol' and '5 mg/kg Carvacrol' experiments in Fig. 5K, is shown on the next page. The authors can confirm that the errors associated with this figure did not have any significant impact on either the results or the conclusions reported in this study, and all the authors agree with the publication of this Corrigendum. The authors are grateful to the Editor of International Journal of Molecular Medicine for allowing them the opportunity to publish this Corrigendum; furthermore, they apologize to the readership of the Journal for any inconvenience caused. [International Journal of Molecular Medicine 46: 977­988, 2020; DOI: 10.3892/ijmm.2020.4654].

Carvacrol may alleviate vascular inflammation in diabetic db/db mice.

Type 2 diabetes mellitus (T2DM) is associated with chronic low­grade inflammation. Carvacrol has been confirmed to possess anti­inflammatory properties, but its effect on diabetic vasculature remains unknown. The aim of the present study was to investigate the possible protective effects of carvacrol against vascular endothelial inflammation. The mice were divided into four groups (n=15 per group) as follows: Non­diabetic control mice, db/db mice, db/db mice + carvacrol (low) and db/db mice + carvacrol (high) groups. The effects of carvacrol on the pathomorphism of the thoracoabdominal aorta in db/db mice were evaluated using hematoxylin and eosin and Masson's trichrome staining. The serum levels of insulin signaling molecules, such as phosphorylated insulin receptor, phosphorylated insulin receptor substrate­1, insulin, triglyceride (TG) and inflammatory cytokines [tumor necrosis factor­α, interleukin (IL)­1ß, IL­6 and IL­8] were measured by ELISA. Furthermore, the protein levels of the toll­like receptor (TLR)4/nuclear factor (NF)­κB inflammatory signaling pathway molecules were investigated in the thoracoabdominal aorta of db/db mice and in high glucose­induced endothelial cells. Vascular endothelial cell apoptosis and viability were assessed by using flow cytometry and Cell Counting Kit­8 assays, respectively. The results demonstrated that carvacrol alleviated vascular endothelial cell injury. Carvacrol reduced the expression levels of insulin signaling molecules, insulin, TG and inflammatory cytokines in the serum of db/db mice. Moreover, carvacrol reduced the activation of the TLR4/NF­κB signaling pathway in vivo and in vitro. In vitro, carvacrol inhibited high glucose­induced endothelial cell function by promoting vascular endothelial cell apoptosis and suppressing cell viability. These findings demonstrated that carvacrol could alleviate endothelial dysfunction and vascular inflammation in T2DM.

Reinforcement Learning-Based Control and Networking Co-design for Industrial Internet of Things.

Industrial Internet-of-Things (IIoT), also known as Industry 4.0, is the integration of Internet of Things (IoT) technology into the industrial manufacturing system so that the connectivity, efficiency, and intelligence of factories and plants can be improved. From a cyber physical system (CPS) perspective, multiple systems (e.g., control, networking and computing systems) are synthesized into IIoT systems interactively to achieve the operator's design goals. The interactions among different systems is a non-negligible factor that affects the IIoT design and requirements, such as automation, especially under dynamic industrial operations. In this paper, we leverage reinforcement learning techniques to automatically configure the control and networking systems under a dynamic industrial environment. We design three new policies based on the characteristics of industrial systems so that the reinforcement learning can converge rapidly. We implement and integrate the reinforcement learning-based co-design approach on a realistic wireless cyber-physical simulator to conduct extensive experiments. Our experimental results demonstrate that our approach can effectively and quickly reconfigure the control and networking systems automatically in a dynamic industrial environment.

Effect of Astragalus polysaccharide in treatment of diabetes mellitus: a narrative review.

Diabetes mellitus is a chronic endocrine/metabolism disease characterized by hyperglycemia arising from defects in insulin action, insulin secretion, or both. Diabetes mellitus is often complicated by visceral lesions, which can lead to serious complications and death. A variety of new agents are in development for the treatment of the disease. Astragalus polysaccharides are monomer components extracted from the Traditional Chinese Medicine, Huangqi (Radix Astragali Mongolici), which have been studied widely for treating diabetes mellitus with promising effects in recent years. This paper reviews recent advances in experimental studies on the effects of Astragalus polysaccharides in treating diabetes mellitus. The effects of Astragalus polysaccharides on the etiology and complication of diabetes mellitus including insulin resistance and secretion, diabetic neuropathy, diabetic retinopathy, diabetic cardiomyopathy, diabetic foot, and infection complicated by diabetes mellitus are discussed.

A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective.

The vision of Industry 4.0, otherwise known as the fourth industrial revolution, is the integration of massively deployed smart computing and network technologies in industrial production and manufacturing settings for the purposes of automation, reliability, and control, implicating the development of an Industrial Internet of Things (I-IoT). Specifically, I-IoT is devoted to adopting the Internet of Things (IoT) to enable the interconnection of anything, anywhere, and at anytime in the manufacturing system context to improve the productivity, efficiency, safety and intelligence. As an emerging technology, I-IoT has distinct properties and requirements that distinguish it from consumer IoT, including the unique types of smart devices incorporated, network technologies and quality of service requirements, and strict needs of command and control. To more clearly understand the complexities of I-IoT and its distinct needs, and to present a unified assessment of the technology from a systems perspective, in this paper we comprehensively survey the body of existing research on I-IoT. Particularly, we first present the I-IoT architecture, I-IoT applications (i.e., factory automation (FA) and process automation (PA)) and their characteristics. We then consider existing research efforts from the three key systems aspects of control, networking and computing. Regarding control, we first categorize industrial control systems and then present recent and relevant research efforts. Next, considering networking, we propose a three-dimensional framework to explore the existing research space, and investigate the adoption of some representative networking technologies, including 5G, machine-to-machine (M2M) communication, and software defined networking (SDN). Similarly, concerning computing, we again propose a second three-dimensional framework that explores the problem space of computing in I-IoT, and investigate the cloud, edge, and hybrid cloud and edge computing platforms. Finally, we outline particular challenges and future research needs in control, networking, and computing systems, as well as for the adoption of machine learning, in an I-IoT context.

[Expression and meaning of pro-angiogenic factors in retinopathy of diabetic rats].

OBJECTIVE: To detect the expression of vascular endotheilal growth factor (VEGF), stromal cell-derived factor-1alpha (SDF-1alpha), and its receptor CXCR-4 in the retinopathy of diabetic rats, and to explore the relationship between those factors and diabetic-retinopathy (DR). METHODS: Diabetes was induced in 40 rats with a single intraperitional injection of streptozotocin(STZ). Experimental rats were randomly divided into M1 (diabetic for 1 month), M3 (diabetic for 3 months), and M5 (diabetic for 5 months) groups, and another 10 rats served as a normal control group (NC). Retinal vascular status was observed by transmission electron microscope. After retinal stretched preparation, VEGF, SDF-1alpha and CXCR-4 immunohistochemistry were done. Retinal VEGF, SDF-1alpha, and CXCR-4 mRNA were detected by semi-quantitative RT-PCR. Protein expression was measured by Western blot. RESULTS: Under transmission electron microscope, change in vascular status was found in M1 to M5 groups, but not in the NC group. The changes became increasingly serious with the prolongation of the disease. By immunohistochemistry, we found the expression of VEGF, SDF-1alpha, and CXCR-4 on the retina increased gradually. It increased after injecting STZ for 1 month and increased significantly after 5 months. VEGF, SDF-1alpha, and CXCR-4 mRNA expression increased obviously after injecting STZ for 1 month and increased significantly after 5 months. Western blot showed that protein of VEGF, SDF-1alpha, and CXCR-4 had no change after injecting STZ for 1 month. It began to increase in the M3 group and increased most in the M5 group. CONCLUSION: The expression of VEGF, SDF-1alpha, and CXCR-4 on the retina in retinopathy of diabetic rats increases gradually with the prolongation of the disease. It is an important factor for diabetic retinopathy.