Plasmacytoid Dendritic Cells Are Productively Infected and Activated through TLR-7 Early after Arenavirus Infection.

The antiviral response is largely mediated by dendritic cells (DCs), including conventional (c) DCs that function as antigen-presenting cells, and plasmacytoid (p) DCs that produce type I interferons, making them an attractive target for viruses. We find that the Old World arenaviruses lymphocytic choriomeningitis virus clone 13 (LCMV Cl13) and Lassa virus bind pDCs to a greater extent than cDCs. Consistently, LCMV Cl13 targets pDCs early after in vivo infection of its natural murine host and establishes a productive and robust replication cycle. pDCs coproduce type I interferons and proinflammatory cytokines, with the former being induced in both infected and uninfected pDCs, demonstrating a dissociation from intrinsic virus replication. TLR7 globally mediates pDC responses, limits pDC viral load, and promotes rapid innate and adaptive immune cell activation. These early events likely help dictate the outcome of infections with arenaviruses and other DC-replicating viruses and shed light on potential therapeutic targets

Mobilizing for change: simulating political movements in armed conflicts

Theories on the establishment and propagation of political movements through mobilization have emerged and evolved over the last half century. Among the major theoretical frameworks that have been advanced are resource mobilization theory, political process theory, and culture theory. However, despite these developments, relatively few methodological approaches have applied bottom-up computational modeling and simulation in explaining movement development in conflicts. With developments made in computational methods, the integration of social theory with modeling and simulation is a natural progression in creating tools that allow analysts, policy makers, and researchers the means to assess the successes or failures of political movements during armed struggles. This article presents an agent-based model and simulation that applies several frequently used theoretical approaches to political mobilization and explores the extent to which group resources and identity shaped conflicts in Central Asia. Given their historical, cultural, political, economic, and geographical circumstances, the authors seek to determine why different movements experienced contrasting political mobilization outcomes. Results show that receiving outside resources could help a relatively weak group, with limited mobilization, overcome opposition that is initially better mobilized, while shared identity and sufficient risk taking are shown to be potentially strong factors in producing successful mobilization. More broadly, the approach advanced enables analysts and researchers to better anticipate future mobilization events and projected paths of conflict by developing and understanding cause and effect relationships within relevant theoretical frameworks

IL-27R signalling mediates early viral containment and impacts innate and adaptive immunity after chronic lymphocytic choriomeningitis virus infection

Chronic viral infections represent a major challenge to host's immune response and a unique network of immunological elements, including cytokines, are required for their containment. By using a model persistent infection with the natural murine pathogen lymphocytic choriomeningitis virus clone 13 (LCMV Cl13) we investigated the role of one such cytokine, interleukin 27 (IL-27), in the control of chronic infection. We found that IL-27R signalling promoted control of LCMV Cl13 as early as day 1 and 5 after infection and that il27p28 transcripts were rapidly elevated in multiple subsets of dendritic cells (DCs) and myeloid cells. In particular, plasmacytoid DCs (pDCs), the most potent type-1-interferon (IFN-I) producing cells, significantly increased il27p28 in a TLR7 dependent fashion. Notably, mice deficient in IL-27 specific receptor (R), WSX-1, exhibited a pleiotropy of innate and adaptive immune alterations after chronic LCMV infection, including compromised NK cell cytotoxicity and antibody responses. While, the majority of these immune alterations appeared cell-extrinsic, cell-intrinsic IL-27R was necessary to maintain early pDC numbers, which, alongside lower IFN-I transcription in CD11b+ DCs and myeloid cells, may explain the compromised IFN-I elevation that we observed early after LCMV Cl13 infection in IL-27R-deficient mice. Together these data highlight the critical role of IL-27 in enabling optimal anti-viral immunity early and late after infection with a systemic persistent virus and suggest that a previously unrecognized positive feedback-loop mediated by IL-27 in pDCs might be involved in this process

Modeling good research practices - overview: a report of the ISPOR-SMDM modeling good research practices task force - 1.

Models—mathematical frameworks that facilitate estimation of the consequences of health care decisions—have become essential tools for health technology assessment. Evolution of the methods since the first ISPOR modeling task force reported in 2003 has led to a new task force, jointly convened with the Society for Medical Decision Making, and this series of seven papers presents the updated recommendations for best practices in conceptualizing models; implementing state–transition approaches, discrete event simulations, or dynamic transmission models; dealing with uncertainty; and validating and reporting models transparently. This overview introduces the work of the task force, provides all the recommendations, and discusses some quandaries that require further elucidation. The audience for these papers includes those who build models, stakeholders who utilize their results, and, indeed, anyone concerned with the use of models to support decision making

Simulation and real-time optimal scheduling: a framework for integration

Traditional scheduling and simulation models of the same system differ in several fundamental respects. These include the definition of a schedule, the existence of an objective function which orders schedules and indicates the performance of a given schedule according to specific criteria, and the level of fidelity at which the items are represented and processed through he system. This paper presents a conceptual, object-oriented, architecture for combining a traditional, high-level, scheduling system with a detailed, process- level, discrete-event simulation. A multi-echelon planning framework is established in the context of modeling end-to-end military deployments with the focus on detailed seaport operations

A Block-Free Distributed Ledger for P2P Energy Trading:Case with IOTA?

& #x00A9; 2019, Springer Nature Switzerland AG. Across the world, the organisation and operation of the electricity markets is quickly changing, moving towards decentralised, distributed, renewables-based generation with real-time data exchange-based solutions. In order to support this change, blockchain-based distributed ledgers have been proposed for implementation of peer-to-peer energy trading platform. However, blockchain solutions suffer from scalability problems as well as from delays in transaction confirmation. This paper explores the feasibility of using IOTA’s DAG-based block-free distributed ledger for implementation of energy trading platforms. Our agent-based simulation research demonstrates that an IOTA-like DAG-based solution could overcome the constraints that blockchains face in the energy market. However, to be usable for peer-to-peer energy trading, even DAG-based platforms need to consider specificities of energy trading markets (such as structured trading periods and assured confirmation of transactions for every completed period)

Juxtaposition of system dynamics and agent-based simulation for a case study in immunosenescence

Advances in healthcare and in the quality of life significantly increase human life expectancy. With the aging of populations, new un-faced challenges are brought to science. The human body is naturally selected to be well-functioning until the age of reproduction to keep the species alive. However, as the lifespan extends, unseen problems due to the body deterioration emerge. There are several age-related diseases with no appropriate treatment; therefore, the complex aging phenomena needs further understanding. It is known that immunosenescence is highly correlated to the negative effects of aging. In this work we advocate the use of simulation as a tool to assist the understanding of immune aging phenomena. In particular, we are comparing system dynamics modelling and simulation (SDMS) and agent-based modelling and simulation (ABMS) for the case of age-related depletion of naive T cells in the organism. We address the following research questions: Which simulation approach is more suitable for this problem? Can these approaches be employed interchangeably? Is there any benefit of using one approach compared to the other? Results show that both simulation outcomes closely fit the observed data and existing mathematical model; and the likely contribution of each of the naive T cell repertoire maintenance method can therefore be estimated. The differences observed in the outcomes of both approaches are due to the probabilistic character of ABMS contrasted to SDMS. However, they do not interfere in the overall expected dynamics of the populations. In this case, therefore, they can be employed interchangeably, with SDMS being simpler to implement and taking less computational resources

A model based approach for complex dynamic decision-making

Current state-of-the-practice and state-of-the-art of decision-making aids are inadequate for modern organisations that deal with significant uncertainty and business dynamism. This paper highlights the limitations of prevalent decision-making aids and proposes a model-based approach that advances the modelling abstraction and analysis machinery for complex dynamic decision-making. In particular, this paper proposes a meta-model to comprehensively represent organisation, establishes the relevance of model-based simulation technique as analysis means, introduces the advancements over actor technology to address analysis needs, and proposes a method to utilise proposed modelling abstraction, analysis technique, and analysis machinery in an effective and convenient manner. The proposed approach is illustrated using a near real-life case-study from a business process outsourcing organisation

OrgML - a domain specific language for organisational decision-making

Effective decision-making based on precise understanding of an organisation is critical for modern organisations to stay competitive in a dynamic and uncertain business environment. However, the state-of-the-art technologies that are relevant in this context are not adequate to capture and quantitatively analyse complex organisations. This paper discerns the necessary information for an organisational decision-making from management viewpoint, discusses inadequacy of the existing enterprise modelling and specification techniques, proposes a domain specific language to capture the necessary information in machine processable form, and demonstrates how the collected information can be used for a simulation-based evidence-driven organisational decision-making