Robust Stimulation of Humoral and Cellular Immune Responses following Vaccination with Antigen-Loaded beta-Glucan Particles

beta-Glucan particles (GPs) are purified Saccharomyces cerevisiae cell walls treated so that they are primarily beta1,3-d-glucans and free of mannans and proteins. GPs are phagocytosed by dendritic cells (DCs) via the Dectin-1 receptor, and this interaction stimulates proinflammatory cytokine secretion by DCs. As the hollow, porous GP structure allows for high antigen loading, we hypothesized that antigen-loaded GPs could be exploited as a receptor-targeted vaccine delivery system. Ovalbumin (OVA) was electrostatically complexed inside the hollow GP shells (GP-OVA). Incubation of C57BL/6J mouse bone marrow-derived DCs with GP-OVA resulted in phagocytosis, upregulation of maturation markers, and rapid proteolysis of OVA. Compared with free OVA, GP-OVA was \u3e100-fold more potent at stimulating the proliferation of OVA-reactive transgenic CD8(+) OT-I and CD4(+) OT-II T cells, as measured by in vitro [(3)H]thymidine incorporation using DCs as antigen-presenting cells. Next, immune responses in C57BL/6J mice following subcutaneous immunizations with GP-OVA were compared with those in C57BL/6J mice following subcutaneous immunizations with OVA absorbed onto the adjuvant alum (Alum/OVA). Vaccination with GP-OVA stimulated substantially higher antigen-specific CD4(+) T-cell lymphoproliferative and enzyme-linked immunospot (ELISPOT) responses than that with Alum/OVA. Moreover, the T-cell responses induced by GP-OVA were Th1 biased (determined by gamma interferon [IFN-gamma] ELISPOT assay) and Th17 biased (determined by interleukin-17a [IL-17a] ELISPOT assay). Finally, both the GP-OVA and Alum/OVA formulations induced strong secretions of IgG1 subclass anti-OVA antibodies, although only GP-OVA induced secretion of Th1-associated IgG2c antibodies. Thus, the GP-based vaccine platform combines adjuvanticity and antigen delivery to induce strong humoral and Th1- and Th17-biased CD4(+) T-cell responses

Agent based mobile negotiation for personalized pricing of last minute theatre tickets

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2012 Elsevier B.V.This paper proposes an agent based mobile negotiation framework for personalized pricing of last minutes theatre tickets whose values are dependent on the time remaining to the performance and the locations of potential customers. In particular, case based reasoning and fuzzy cognitive map techniques are adopted in the negotiation framework to identify the best initial offer zone and adopt multi criteria decision in the scoring function to evaluate offers. The proposed framework is tested via a computer simulation in which personalized pricing policy shows higher market performance than other policies therefore the validity of the proposed negotiation framework.The Ministry of Education, Science and Technology (Korea

Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector

YesThe prevalence of big data is starting to spread across the public and private sectors however, an impediment to its widespread adoption orientates around a lack of appropriate big data analytics (BDA) and resulting skills to exploit the full potential of big data availability. In this paper, we propose a novel BDA to contribute towards this void, using a fuzzy cognitive map (FCM) approach that will enhance decision-making thus prioritising IT service procurement in the public sector. This is achieved through the development of decision models that capture the strengths of both data analytics and the established intuitive qualitative approach. By taking advantages of both data analytics and FCM, the proposed approach captures the strength of data-driven decision-making and intuitive model-driven decision modelling. This approach is then validated through a decision-making case regarding IT service procurement in public sector, which is the fundamental step of IT infrastructure supply for publics in a regional government in the Russia federation. The analysis result for the given decision-making problem is then evaluated by decision makers and e-government expertise to confirm the applicability of the proposed BDA. In doing so, demonstrating the value of this approach in contributing towards robust public decision-making regarding IT service procurement.EU FP7 project Policy Compass (Project No. 612133

Idiosyncratic risk and the cross-section of stock returns: the role of mean-reverting idiosyncratic volatility

© The Author(s) 2018. A key prediction of the Capital Asset Pricing Model (CAPM) is that idiosyncratic risk is not priced by investors because in the absence of frictions it can be fully diversified away. In the presence of constraints on diversification, refinements of the CAPM conclude that the part of idiosyncratic risk that is not diversified should be priced. Recent empirical studies yielded mixed evidence with some studies finding positive correlation between idiosyncratic risk and stock returns, while other studies reported none or even negative correlation. We examine whether idiosyncratic risk is priced by the stock market and what are the probable causes for the mixed evidence produced by other studies, using monthly data for the US market covering the period from 1980 until 2013. We find that one-period volatility forecasts are not significantly correlated with stock returns. The mean-reverting unconditional volatility, however, is a robust predictor of returns. Consistent with economic theory, the size of the premium depends on the degree of ‘knowledge’ of the security among market participants. In particular, the premium for Nasdaq-traded stocks is higher than that for NYSE and Amex stocks. We also find stronger correlation between idiosyncratic risk and returns during recessions, which may suggest interaction of risk premium with decreased risk tolerance or other investment considerations like flight to safety or liquidity requirements. We identify the difference between the correlations of the idiosyncratic volatility estimators used by other studies and the true risk metric the mean-reverting volatility as the likely cause for the mixed evidence produced by other studies. Our results are robust with respect to liquidity, momentum, return reversals, unadjusted price, liquidity, credit quality, omitted factors, and hold at daily frequency.Korea National Research Foundation through Global Research Network Progra