Leptin and Adiponectin: new players in the field of tumor cell and leukocyte migration

Adipose tissue is no longer considered to be solely an energy storage, but exerts important endocrine functions, which are primarily mediated by a network of various soluble factors derived from fat cells, called adipocytokines. In addition to their responsibility to influence energy homeostasis, new studies have identified important pathways linking metabolism with the immune system, and demonstrating a modulatory role of adipocytokines in immune function. Additionally, epidemiological studies underline that obesity represents a significant risk factor for the development of cancer, although the exact mechanism of this relationship remains to be determined. Whereas a possible influence of adipocytokines on the proliferation of tumor cells is already known, new evidence has come to light elucidating a modulatory role of this signaling substances in the regulation of migration of leukocytes and tumor cells. The migration of leukocytes is a key feature to fight cancer cells, whereas the locomotion of tumor cells is a prerequisite for tumor formation and metastasis. We herein review the latest tumor biological findings on the role of the most prominent adipocytokines leptin and adiponectin, which are secreted by fat cells, and which are involved in leukocyte migration, tumor growth, invasion and metastasis. This review thus accentuates the complex, interactive involvement of adipocytokines in the regulation of migration of both leukocytes and tumor cells, and gives an insight in the underlying molecular mechanisms

The TREAT-NMD DMD Global Database: Analysis of more than 7,000 Duchenne Muscular Dystrophy mutations

Analyzing the type and frequency of patient-specific mutations that give rise to Duchenne muscular dystrophy (DMD) is an invaluable tool for diagnostics, basic scientific research, trial planning, and improved clinical care. Locus-specific databases allow for the collection, organization, storage, and analysis of genetic variants of disease. Here, we describe the development and analysis of the TREAT-NMD DMD Global database (http://umd.be/TREAT_DMD/). We analyzed genetic data for 7,149 DMD mutations held within the database. A total of 5,682 large mutations were observed (80% of total mutations), of which 4,894 (86%) were deletions (1 exon or larger) and 784 (14%) were duplications (1 exon or larger). There were 1,445 small mutations (smaller than 1 exon, 20% of all mutations), of which 358 (25%) were small deletions and 132 (9%) small insertions and 199 (14%) affected the splice sites. Point mutations totalled 756 (52% of small mutations) with 726 (50%) nonsense mutations and 30 (2%) missense mutations. Finally, 22 (0.3%) mid-intronic mutations were observed. In addition, mutations were identified within the database that would potentially benefit from novel genetic therapies for DMD including stop codon read-through therapies (10% of total mutations) and exon skipping therapy (80% of deletions and 55% of total mutations)

Error-Prone Splicing Controlled by the Ubiquitin Relative Hub1

Original data of the paper, Error-Prone Splicing Controlled by the Ubiquitin Relative Hub

A cloud and contiki based fire detection system using multi-Hop wireless sensor networks

International Association of Researchers (IARES)4th International Conference on Engineering and MIS, ICEMIS 2018 -- 19 June 2018 through 20 June 2018 -- 138526In this study, a ContikiOS based Library Fire Detection System proposed to provide coverage for a large physical area and to increase throughput by using multi-hop wireless sensor network. Moreover, the system has clouding feature of Google’s Firebase for online data storing and Android application to notify the users in case of emergency. Furthermore, the network can be expanded without adding extra sink nodes to collect data. Benefiting from a multi-hop network, additional source nodes can send temperature values via relay nodes in case of low transmission power with sink node. According to the test results, the system has responded to the changes in temperature and prompted warning/alarm message in approximately 4 seconds using multi-hop network. Additionally, the system can notify the users in case of emergency. © 2018 Association for Computing Machinery

Error-Prone Splicing Controlled by the Ubiquitin Relative Hub1

Accurate pre-mRNA splicing is needed for correct gene expression and relies on faithful splice site recognition. Here, we show that the ubiquitin-like protein Hub1 binds to the DEAD-box helicase Prp5, a key regulator of early spliceosome assembly, and stimulates its ATPase activity thereby enhancing splicing and relaxing fidelity. High Hub1 levels enhance splicing efficiency but also cause missplicing by tolerating suboptimal splice sites and branchpoint sequences. Notably, Prp5 itself is regulated by a Hub1-dependent negative feedback loop. Since Hub1-mediated splicing activation induces cryptic splicing of Prp5, it also represses Prp5 protein levels and thus curbs excessive missplicing. Our findings indicate that Hub1 mediates enhanced, but error-prone splicing, a mechanism that is tightly controlled by a feedback loop of PRP5 cryptic splicing activation

Platform-specific Modeling for RIOT based IoT Systems

ACM SIGSOFT;Association for Computing Machinery (ACM);IEEE Computer Society;IEEE Technical Council on Software Engineering (TCSE);Korean Institute of Information Scientists and Engineers42nd IEEE/ACM International Conference on Software Engineering Workshops, ICSEW 2020 -- 27 June 2020 through 19 July 2020 -- -- 163291The variety of smart devices and their communication models increase the development complexity of embedded software for IoT. Thus, the development of these systems becomes more error-prone, complex, and costly. To tackle this problem, in this study, a model-driven approach is proposed for the development of RIOT-OS based IoT systems. To this end, a meta-model is designed for RIOT-OS. Based on this meta-model, a Domain-specific Modeling Language (DSML) is developed to graphically represent the domain models. To gain more functionality for the language, domain rules are defined as constraints. Also, system codes are generated partially from the instance models. In this way, the development is supported by code synthesis and the number of bugs is reduced. Finally, a smart irrigation system and a smart lighting system are implemented to evaluate the proposed DSML. The results show that about 83.5% of the final code is generated automatically on average. © 2020 ACM.Ege ÜniversitesiThis study is partially funded by the Scientific Research Project No 17-UBE-002 at EGE University, Izmir, Turkey. Some of the ideas in this work were developed during Short Term Scientific Missions (STSM Nos. 41940 and 41967) by two of the authors, within the IC1404 Multi-Paradigm Modelling for Cyber-Physical Systems (MPM4CPS) COST Action