Inferring microRNA and transcription factor regulatory networks in heterogeneous data

Background: Transcription factors (TFs) and microRNAs (miRNAs) are primary metazoan gene regulators. Regulatory mechanisms of the two main regulators are of great interest to biologists and may provide insights into the causes of diseases. However, the interplay between miRNAs and TFs in a regulatory network still remains unearthed. Currently, it is very difficult to study the regulatory mechanisms that involve both miRNAs and TFs in a biological lab. Even at data level, a network involving miRNAs, TFs and genes will be too complicated to achieve. Previous research has been mostly directed at inferring either miRNA or TF regulatory networks from data. However, networks involving a single type of regulator may not fully reveal the complex gene regulatory mechanisms, for instance, the way in which a TF indirectly regulates a gene via a miRNA. Results: We propose a framework to learn from heterogeneous data the three-component regulatory networks, with the presence of miRNAs, TFs, and mRNAs. This method firstly utilises Bayesian network structure learning to construct a regulatory network from multiple sources of data: gene expression profiles of miRNAs, TFs and mRNAs, target information based on sequence data, and sample categories. Then, in order to produce more meaningful results for further biological experimentation and research, the method searches the learnt network to identify the interplay between miRNAs and TFs and applies a network motif finding algorithm to further infer the network. We apply the proposed framework to the data sets of epithelial-to-mesenchymal transition (EMT). The results elucidate the complex gene regulatory mechanism for EMT which involves both TFs and miRNAs. Several discovered interactions and molecular functions have been confirmed by literature. In addition, many other discovered interactions and bio-markers are of high statistical significance and thus can be good candidates for validation by experiments. Moreover, the results generated by our method are compact, involving a small number of interactions which have been proved highly relevant to EMT. Conclusions: We have designed a framework to infer gene regulatory networks involving both TFs and miRNAs from multiple sources of data, including gene expression data, target information, and sample categories. Results on the EMT data sets have shown that the proposed approach is able to produce compact and meaningful gene regulatory networks that are highly relevant to the biological conditions of the data sets. This framework has the potential for application to other heterogeneous datasets to reveal the complex gene regulatory relationships.Thuc D Le, Lin Liu, Bing Liu, Anna Tsykin, Gregory J Goodall, Kenji Satou and Jiuyong L

Characterizing Recast Nafion® Film Electrode Interface Diffusion and Kinetics in a Non-Aqueous System.

Color poster with text, images, charts, photographs, and graphs.Electrochemistry involves manual redox, in which electrons flowing through an electrode’s current force the reduction or oxidation of a molecule at the electrode’s surface. A potentiostat is the instrument which provides the current, where the parameters can be controlled. Nafion is a cation-exchange polymer which allows the flow of charged molecules through its permeable layer. Nafion has been studied to hydrate in aqueous systems and alter the diffusion behavior of molecules in an electrochemical system. This investigation will contribute to the understudied electrochemical behavior of non-aqueous systems applicable to redox flow battery systems.University of Wisconsin--Eau Claire Office of Research and Sponsored Program

Awareness of Health Issues in the Pomeranian Region as a Precondition for Developing a Health Region

Health is the most desirable value in modern society and a crucial aspect of a region to be considered a place to live and rest. The concept of a health region is seen as a tool to increase the attractiveness of a place. The Pomeranian region is considered to have the potential to develop itself as a health region. The goal of this paper is to analyse if the awareness of health issues is already present within the region. Empirical research shows that most themes discussed in the literature as preconditions for developing a health region exist, while simultaneously, there are still several obstacles to achieve this goal

Trauma Center-Based Surveillance of Nontraffic Pedestrian Injury among California Children

Introduction: Every year in the United States, thousands of young children are injured by passenger vehicles in driveways or parking areas. Little is known about risk factors, and incidence rates are difficult to estimate because ascertainment using police collision reports or media sources is incomplete. This study used surveillance at trauma centers to identify incidents and parent interviews to obtain detailed information on incidents, vehicles, and children.Methods: Eight California trauma centers conducted surveillance of nontraffic pedestrian collision injury to children aged 14 years or younger from January 2005 to July 2007. Three of these centers conducted follow-up interviews with family members.Results: Ninety-four injured children were identified. Nine children (10%) suffered fatal injury. Seventy children (74%) were 4 years old or younger. Family members of 21 victims from this study (23%) completed an interview. Of these 21 interviewed victims, 17 (81%) were male and 13 (62%) were 1 or 2years old. In 13 cases (62%), the child was backed over, and the driver was the mother or father in 11 cases (52%). Fifteen cases (71%) involved a sport utility vehicle, pickup truck, or van. Most collisions occurred in a residential driveway.Conclusion: Trauma center surveillance can be used for case ascertainment and for collecting information on circumstances of nontraffic pedestrian injuries. Adoption of a specific external cause-of injury code would allow passive surveillance of these injuries. Research is needed to understand the contributions of family, vehicular, and environmental characteristics and injury risk to inform prevention efforts. [West J Emerg Med. 2012;13(2):139–145.