An integrated network visualization framework towards metabolic engineering applications

Background Over the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential. Results In this work, an open-source software that aims to fill the gap between ME and metabolic network visualization is proposed, in the form of a plugin to the OptFlux ME platform. The framework is based on an abstract layer, where the network is represented as a bipartite graph containing minimal information about the underlying entities and their desired relative placement. The framework provides input/output support for networks specified in standard formats, such as XGMML, SBGN or SBML, providing a connection to genome-scale metabolic models. An user-interface makes it possible to edit, manipulate and query nodes in the network, providing tools to visualize diverse effects, including visual filters and aspect changing (e.g. colors, shapes and sizes). These tools are particularly interesting for ME, since they allow overlaying phenotype simulation results or elementary flux modes over the networks. Conclusions The framework and its source code are freely available, together with documentation and other resources, being illustrated with well documented case studies.This work is partially funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within project ref. COMPETE FCOMP-01-0124-FEDER-015079 and the FCT Strategic Project PEst-OE/EQB/LA0023/2013. The work of PV is funded by PhD grant ref. SFRH/BDE/51442/2011

Comparisons of the factor structure and measurement invariance of the Spence children’s anxiety scale - parent version in children with autism spectrum disorder and typically developing anxious children

The Spence Children’s Anxiety Scale - Parent version (SCAS-P) is often used to assess anxiety in children with autism spectrum disorder (ASD), however, little is known about the validity of the tool in this population. The aim of this study was to determine whether the SCAS-P has the same factorial validity in a sample of young people with ASD (n=285), compared to a sample of typically developing young people with anxiety disorders (n=224). Poor model fit with all of the six hypothesised models precluded invariance testing. Exploratory factor analysis indicated that different anxiety phenomenology characterises the two samples. The findings suggest that cross-group comparisons between ASD and anxious samples based on the SCAS-P scores may not always be appropriat

Serologic Cross-Reactivity of Human IgM and IgG Antibodies to Five Species of Ebola Virus

Five species of Ebola virus (EBOV) have been identified, with nucleotide differences of 30–45% between species. Four of these species have been shown to cause Ebola hemorrhagic fever (EHF) in humans and a fifth species (Reston ebolavirus) is capable of causing a similar disease in non-human primates. While examining potential serologic cross-reactivity between EBOV species is important for diagnostic assays as well as putative vaccines, the nature of cross-reactive antibodies following EBOV infection has not been thoroughly characterized. In order to examine cross-reactivity of human serologic responses to EBOV, we developed antigen preparations for all five EBOV species, and compared serologic responses by IgM capture and IgG enzyme-linked immunosorbent assay (ELISA) in groups of convalescent diagnostic sera from outbreaks in Kikwit, Democratic Republic of Congo (n = 24), Gulu, Uganda (n = 20), Bundibugyo, Uganda (n = 33), and the Philippines (n = 18), which represent outbreaks due to four different EBOV species. For groups of samples from Kikwit, Gulu, and Bundibugyo, some limited IgM cross-reactivity was noted between heterologous sera-antigen pairs, however, IgM responses were largely stronger against autologous antigen. In some instances IgG responses were higher to autologous antigen than heterologous antigen, however, in contrast to IgM responses, we observed strong cross-reactive IgG antibody responses to heterologous antigens among all sets of samples. Finally, we examined autologous IgM and IgG antibody levels, relative to time following EHF onset, and observed early peaking and declining IgM antibody levels (by 80 days) and early development and persistence of IgG antibodies among all samples, implying a consistent pattern of antibody kinetics, regardless of EBOV species. Our findings demonstrate limited cross-reactivity of IgM antibodies to EBOV, however, the stronger tendency for cross-reactive IgG antibody responses can largely circumvent limitations in the utility of heterologous antigen for diagnostic assays and may assist in the development of antibody-mediated vaccines to EBOV

Lessons from Peer Support Among Individuals with Mental Health Difficulties: A Review of the Literature

We conducted a comprehensive narrative review and used a systematic search strategy to identify studies related to peer support among adults with mental health difficulties. The purposes of this review were to describe the principles, effects and benefits of peer support documented in the published literature, to discuss challenging aspects of peer support and to investigate lessons from peer support. Fifty-one studies, including 8 review articles and 19 qualitative studies, met the inclusion criteria for this review. Most of the challenges for peer support were related to “role” and “relationship” issues; that is, how peer support providers relate to people who receive peer support and how peer support providers are treated in the system. The knowledge gained from peer support relationships, such as mutual responsibility and interdependence, might be a clue toward redefining the helper-helper relationship as well as the concepts of help and support

Utilizing individual fish biomass and relative abundance models to map environmental niche associations of adult and juvenile targeted fishes

Many fishes undergo ontogenetic habitat shifts to meet their energy and resource needs as they grow. Habitat resource partitioning and patterns of habitat connectivity between conspecific fishes at different life-history stages is a significant knowledge gap. Species distribution models were used to examine patterns in the relative abundance, individual biomass estimates and environmental niche associations of different life stages of three iconic West Australian fishes. Continuous predictive maps describing the spatial distribution of abundance and individual biomass of the study species were created as well predictive hotspot maps that identify possible areas for aggregation of individuals of similar life stages of multiple species (i.e. spawning grounds, fisheries refugia or nursery areas). The models and maps indicate that processes driving the abundance patterns could be different from the body size associated demographic processes throughout an individual's life cycle. Incorporating life-history in the spatially explicit management plans can ensure that critical habitat of the vulnerable stages (e.g. juvenile fish, spawning stock) is included within proposed protected areas and can enhance connectivity between various functional areas (e.g. nursery areas and adult populations) which, in turn, can improve the abundance of targeted species as well as other fish species relying on healthy ecosystem functioning

Computationally-Optimized Bone Mechanical Modeling from High-Resolution Structural Images

Image-based mechanical modeling of the complex micro-structure of human bone has shown promise as a non-invasive method for characterizing bone strength and fracture risk in vivo. In particular, elastic moduli obtained from image-derived micro-finite element (μFE) simulations have been shown to correlate well with results obtained by mechanical testing of cadaveric bone. However, most existing large-scale finite-element simulation programs require significant computing resources, which hamper their use in common laboratory and clinical environments. In this work, we theoretically derive and computationally evaluate the resources needed to perform such simulations (in terms of computer memory and computation time), which are dependent on the number of finite elements in the image-derived bone model. A detailed description of our approach is provided, which is specifically optimized for μFE modeling of the complex three-dimensional architecture of trabecular bone. Our implementation includes domain decomposition for parallel computing, a novel stopping criterion, and a system for speeding up convergence by pre-iterating on coarser grids. The performance of the system is demonstrated on a dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM. Models of distal tibia derived from 3D in-vivo MR images in a patient comprising 200,000 elements required less than 30 seconds to converge (and 40 MB RAM). To illustrate the system's potential for large-scale μFE simulations, axial stiffness was estimated from high-resolution micro-CT images of a voxel array of 90 million elements comprising the human proximal femur in seven hours CPU time. In conclusion, the system described should enable image-based finite-element bone simulations in practical computation times on high-end desktop computers with applications to laboratory studies and clinical imaging

Network capitalism and the role of strategy, contracts and performance expectations for Asia-Pacific innovation partnerships

© Springer Nature Singapore Pte Ltd. 2018. With the growth of emerging economies in Asia-Pacific over the last three decades collaboration with the aim of innovation between firms within and with partners outside the region have developed substantially. Not always have such partnerships fulfilled their anticipated strategic objectives. The literature suggests that the nature of market arrangements and the role of government within that system play a role, but also innate contracting practices and governance of innovation partnerships are related. Yet, our understanding about the specific relationships between these factors and the emerging partnership innovation culture that facilitates joint business activities in an Asia-Pacific context remains vague. In this conceptual chapter we suggest how characteristics of so called network capitalism in conjunction with the nature of contractual agreements between partners, the alignment of their innovation objectives and the ambiguity inherent in their mutual contributions to the partnership can be interpreted as indicators of joint innovation culture. However, while innovation partnerships generally may result to be bureaucratic, market, clan, or adhocracy, we discuss how in an Asia Pacific context, innovation partnerships are limited by the extent of codification and diffusion of information and the social embeddedness of economic transactions

Engineering the Melanocortin-4 Receptor to Control Constitutive and Ligand-Mediated Gs Signaling In Vivo

The molecular and functional diversity of G protein–coupled receptors is essential to many physiological processes. However, this diversity presents a significant challenge to understanding the G protein–mediated signaling events that underlie a specific physiological response. To increase our understanding of these processes, we sought to gain control of the timing and specificity of Gs signaling in vivo. We used naturally occurring human mutations to develop two Gs-coupled engineered receptors that respond solely to a synthetic ligand (RASSLs). Our Gs-coupled RASSLs are based on the melanocortin-4 receptor, a centrally expressed receptor that plays an important role in the regulation of body weight. These RASSLs are not activated by the endogenous hormone α-melanocyte-stimulating hormone but respond potently to a selective synthetic ligand, tetrahydroisoquinoline. The RASSL variants reported here differ in their intrinsic basal activities, allowing the separation of the effects of basal signaling from ligand-mediated activation of the Gs pathway in vivo. These RASSLs can be used to activate Gs signaling in any tissue, but would be particularly useful for analyzing downstream events that mediate body weight regulation in mice. Our study also demonstrates the use of human genetic variation for protein engineering