Characterising pandemic severity and transmissibility from data collected during first few hundred studies

Early estimation of the probable impact of a pandemic influenza outbreak can assist public health authorities to ensure that response measures are proportionate to the scale of the threat. Recently, frameworks based on transmissibility and severity have been proposed for initial characterization of pandemic impact. Data requirements to inform this assessment may be provided by "First Few Hundred" (FF100) studies, which involve surveillance-possibly in person, or via telephone-of household members of confirmed cases. This process of enhanced case finding enables detection of cases across the full spectrum of clinical severity, including the date of symptom onset. Such surveillance is continued until data for a few hundred cases, or satisfactory characterization of the pandemic strain, has been achieved. We present a method for analysing these data, at the household level, to provide a posterior distribution for the parameters of a model that can be interpreted in terms of severity and transmissibility of a pandemic strain. We account for imperfect case detection, where individuals are only observed with some probability that can increase after a first case is detected. Furthermore, we test this methodology using simulated data generated by an independent model, developed for a different purpose and incorporating more complex disease and social dynamics. Our method recovers transmissibility and severity parameters to a high degree of accuracy and provides a computationally efficient approach to estimating the impact of an outbreak in its early stages.Andrew J. Black, Nicholas Gear, James M. McCaw, Jodie McVernon, Joshua V. Ros

Three Preventative Interventions to Address the Fake News Phenomenon on Social Media

Fake news on social media undermines democracies and civil society. To date the research response has been message centric and reactive. This does not address the problem of fake news contaminating social media populations with disinformation, nor address the fake news producers and disseminators who are predominantly human social media users. Our research proposes three preventative interventions - two that empower social media users and one social media structural change to reduce the spread of fake news. Specifically, we investigate how i) psychological inoculation; ii) digital media literacy and iii) Transaction Cost Economy safeguarding through reputation ranking could elicit greater cognitive elaboration from social media users. Our research provides digital scalable preventative interventions to empower social media users with the aim to reduce the population size exposed to fake news

Testing a model of successful aging in a cohort of masters swimmers

Geard, DE ORCiD: 0000-0002-4292-9278; Rebar, A ORCiD: 0000-0003-3164-993XDue to their high physical functioning, masters athletes are regularly proposed to exemplify successful aging. However, successful aging research on masters athletes has never been undertaken using a multidimensional successful aging model. To determine the best model for future successful aging research on masters athletes, we had masters swimmers (N = 169, M age = 57.4 years, 61% women) self-report subjective successful aging, and physical, psychological, cognitive, and social functioning. Using this data we tested one hypothesized and three alternative successful aging models. The hypothesized model fit the data best (-2LL = 2052.32, AIC = 1717) with physical (β = 0.31, SE = 0.11), psychological (β = 0.25, SE = 0.11), and social (β = 1.20, SE = 0.63) functioning factors significantly loading onto a higher order successful aging latent factor. Successful aging should be conceptualized as a multidimensional phenomenon in future masters athlete research. © 2018 Human Kinetics, Inc

Effects of a 12-Week Cycling Intervention on Successful Aging Measures in Mid-Aged Adults

Purpose: To compare the effect of 12-weeks of cycling training and competition versus recreational cycling on successful aging across physical, psychological, cognitive, and social functioning domains in mid-aged adults. Methods: Recreational cyclists were randomly assigned to an intervention (n = 13, M age = 47.18 years) and comparison (n = 13, M age = 46.91 years) group. Analysis of Covariance was used on self-reported pre-post data to determine changes across time and differences between groups on outcomes. Results: The intervention group scored higher on the role limitation due to physical problems measure of physical functioning (p = .045) and the social activity measure of social functioning (p = .008) with large effect sizes (ηp2 > .14). The remaining physical, psychological, cognitive, and social functioning measures were not significantly different (p > .05) between groups with small to medium effect sizes (ηp2 > .01 to ≤ .06). Conclusion: Cycling training and competition promotes better physical and social functioning than recreational cycling. This finding indicates that an intervention that incorporates the training and competition aspects of sport may promote positive outcomes that are above and beyond those that can be gained from participation in recreational physical activity. Objective measurements on larger samples across a broader range of sports are required to confirm and extend these findings

Continual Conscious Bioluminescent Imaging in Freely Moving Mice

In vivo bioluminescent imaging allows the detection of reporter gene expression in rodents in real time. Here we describe a novel technology whereby we can generate somatotransgenic rodents with the use of a viral vector carrying a luciferase transgene. We are able to achieve long term luciferase expression by a single injection of lentiviral or adeno-associated virus vectors to newborn mice. Further, we describe whole body bioluminescence imaging of conscious mice in a noninvasive manner, thus enforcing the 3R’s (replacement, reduction, and refinement) of biomedical animal research

A GLP1 receptor agonist diabetes drug ameliorates neurodegeneration in a mouse model of infantile neurometabolic disease

Infantile neuroaxonal dystrophy (INAD) is a rare paediatric neurodegenerative condition caused by mutations in the PLA2G6 gene, which is also the causative gene for PARK14-linked young adult-onset dystonia parkinsonism. INAD patients usually die within their first decade of life, and there are currently no effective treatments available. GLP1 receptor (GLP-1R) agonists are licensed for treating type 2 diabetes mellitus but have also demonstrated neuroprotective properties in a clinical trial for Parkinson's disease. Therefore, we evaluated the therapeutic efficacy of a new recently licensed GLP-1R agonist diabetes drug in a mouse model of INAD. Systemically administered high-dose semaglutide delivered weekly to juvenile INAD mice improved locomotor function and extended the lifespan. An investigation into the mechanisms underlying these therapeutic effects revealed that semaglutide significantly increased levels of key neuroprotective molecules while decreasing those involved in pro-neurodegenerative pathways. The expression of mediators in both the apoptotic and necroptotic pathways were also significantly reduced in semaglutide treated mice. A reduction of neuronal loss and neuroinflammation was observed. Finally, there was no obvious inflammatory response in wild-type mice associated with the repeated high doses of semaglutide used in this study

Mechanism of Radiation-Induced Bystander Effects: A Unifying Model

The radiation-induced bystander effect represents a paradigm shift in our understanding of the radiobiological effects of ionizing radiation, in that extranuclear and extracellular events may also contribute to the final biological consequences of exposure to low doses of radiation. Although radiation-induced bystander effects have been well documented in a variety of biological systems, the mechanism is not known. It is likely that multiple pathways are involved in the bystander phenomenon, and different cell types respond differently to bystander signalling. Using cDNA microarrays, a number of cellular signalling genes, including cyclooxygenase-2 (COX-2), have been shown to be causally linked to the bystander phenomenon. The observation that inhibition of the phosphorylation of extracellular signal-related kinase (ERK) suppressed the bystander response further confirmed the important role of the mitogen-activated protein kinase (MAPK) signalling cascade in the bystander process. Furthermore, cells deficient in mitochondrial DNA showed a significantly reduced response to bystander signalling, suggesting a functional role of mitochondria in the signalling process. Inhibitors of nitric oxide (NO) synthase (NOS) and mitochondrial calcium uptake provided evidence that NO and calcium signalling are part of the signalling cascade. The bystander observations imply that the relevant target for various radiobiological endpoints is larger than an individual cell. A better understanding of the cellular and molecular mechanisms of the bystander phenomenon, together with evidence of their occurrence in-vivo, will allow us to formulate a more accurate model for assessing the health effects of low doses of ionizing radiation

The State of the Art in Multilayer Network Visualization

Modelling relationships between entities in real-world systems with a simple graph is a standard approach. However, reality is better embraced as several interdependent subsystems (or layers). Recently the concept of a multilayer network model has emerged from the field of complex systems. This model can be applied to a wide range of real-world datasets. Examples of multilayer networks can be found in the domains of life sciences, sociology, digital humanities and more. Within the domain of graph visualization there are many systems which visualize datasets having many characteristics of multilayer graphs. This report provides a state of the art and a structured analysis of contemporary multilayer network visualization, not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those developing systems across application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer graph visualization, as well as tools, tasks, and analytic techniques from within application domains. This report also identifies the outstanding challenges for multilayer graph visualization and suggests future research directions for addressing them

Proceedings of a Sickle Cell Disease Ontology workshop - Towards the first comprehensive ontology for Sickle Cell Disease

Sickle cell disease (SCD) is a debilitating single gene disorder caused by a single point mutation that results in physical deformation (i.e. sickling) of erythrocytes at reduced oxygen tensions. Up to 75% of SCD in newborns world-wide occurs in sub-Saharan Africa, where neonatal and childhood mortality from sickle cell related complications is high. While SCD research across the globe is tackling the disease on multiple fronts, advances have yet to significantly impact on the health and quality of life of SCD patients, due to lack of coordination of these disparate efforts. Ensuring data across studies is directly comparable through standardization is a necessary step towards realizing this goal. Such a standardization requires the development and implementation of a disease-specific ontology for SCD that is applicable globally. Ontology development is best achieved by bringing together experts in the domain to contribute their knowledge. The SCD community and H3ABioNet members joined forces at a recent SCD Ontology workshop to develop an ontology covering aspects of SCD under the classes: phenotype, diagnostics, therapeutics, quality of life, disease modifiers and disease stage. The aim of the workshop was for participants to contribute their expertise to development of the structure and contents of the SCD ontology. Here we describe the proceedings of the Sickle Cell Disease Ontology Workshop held in Cape Town South Africa in February 2016 and its outcomes. The objective of the workshop was to bring together experts in SCD from around the world to contribute their expertise to the development of various aspects of the SCD ontology

Integrating BDI agents with Agent-based simulation platforms

Agent-Based Models (ABMs) is increasingly being used for exploring and supporting decision making about social science scenarios involving modelling of human agents. However existing agent-based simulation platforms (e.g., SWARM, Repast) provide limited support for the simulation of more complex cognitive agents required by such scenarios. We present a framework that allows Belief-Desire Intention (BDI) cognitive agents to be embedded in an ABM system. Architecturally, this means that the "brains" of an agent can be modelled in the BDI system in the usual way, while the "body" exists in the ABM system. The architecture is exible in that the ABM can still have non-BDI agents in the simulation, and the BDI-side can have agents that do not have a physical counterpart (such as an organisation). The framework addresses a key integration challenge of coupling event-based BDI systems, with time-stepped ABM systems. Our framework is modular and supports integration off-the-shelf BDI systems with off-the-shelf ABM systems. The framework is Open Source, and all integrations and applications are available for use by the modelling community