Regulation by anti-inflammatory cytokines (IL-4, IL-10, IL-13, TGFβ)of interleukin-8 production by LPS- and/ or TNFα-activated human polymorphonuclear cells

The capacity to down-regulate the production of IL-8 by LPS-activated human polymorphonuclear cells (PMN) has been demonstrated for IL-4, IL-10, and TGFβ. We compared their relative capacities and further extended this property to IL-13. We report a great heterogeneity among individuals related to the responsiveness of PMN to the IL-4 and IL-13 inhibitory effects while their response to the IL-10 effect was homogenous. The inhibitory activities were observed at the transcriptional level. IL-8 induction by TNFα was, unlike its induction by LPS, resistant to the inhibitory effects of IL-10, IL-4, IL-13 and TGFβ. Furthermore, IL-10 and IL-4 inhibitory activity were less effective when TNFα was acting synergistically with LPS to induce IL-8 production by PMN. LPS-induced cell-associated IL-8, detected in the PMN cultures, could be marginally inhibited by IL-4 and IL-10. Altogether, our data demonstrate that IL-13 is able to inhibit LPS-induced IL-8 production by human PMN, although IL-10 remains the most active anti-inflammatory cytokine. Despite the capacity of IL-4, IL-10, and IL-13 to limit the production of TNFα-induced IL-8 in a whole blood assay, none was able to inhibit this production when studying isolated human polymorphonuclear cells

Electron beam charging of insulators: A self-consistent flight-drift model

International audienceElectron beam irradiation and the self-consistent charge transport in bulk insulating samples are described by means of a new flight-drift model and an iterative computer simulation. Ballistic secondary electron and hole transport is followed by electron and hole drifts, their possible recombination and/or trapping in shallow and deep traps. The trap capture cross sections are the Poole-Frenkel-type temperature and field dependent. As a main result the spatial distributions of currents j(x,t), charges, the field F(x,t) and the potential slope V(x,t) are obtained in a self-consistent procedure as well as the time-dependent secondary electron emission rate sigma(t) and the surface potential V0(t) For bulk insulating samples the time-dependent distributions approach the final stationary state with j(x,t)=const=0 and sigma=1. Especially for low electron beam energies E0=4 keV the incorporation of mainly positive charges can be controlled by the potential VG of a vacuum grid in front of the target surface. For high beam energies E0=10, 20, and 30 keV high negative surface potentials V0=−4, −14, and −24 kV are obtained, respectively. Besides open nonconductive samples also positive ion-covered samples and targets with a conducting and grounded layer (metal or carbon) on the surface have been considered as used in environmental scanning electron microscopy and common SEM in order to prevent charging. Indeed, the potential distributions V(x) are considerably small in magnitude and do not affect the incident electron beam neither by retarding field effects in front of the surface nor within the bulk insulating sample. Thus the spatial scattering and excitation distributions are almost not affected

Prenex Separation Logic with One Selector Field

International audienceWe show that infinite satisfiability can be reduced to finite satisfiabil-ity for all prenex formulas of Separation Logic with k ≥ 1 selector fields (SL k). This fact entails the decidability of the finite and infinite satisfiability problems for the class of prenex formulas of SL 1 , by reduction to the first-order theory of a single unary function symbol and an arbitrary number of unary predicate symbols. We also prove that the complexity of this fragment is not elementary recursive, by reduction from the first-order theory of one unary function symbol. Finally, we prove that the Bernays-Schönfinkel-Ramsey fragment of prenex SL 1 formulas with quantifier prefix in the language ∃ * ∀ * is PSPACE-complete

Electron Beam Charging of Insulators with Surface Layer and Leakage Currents

International audienceThe electron beam induced selfconsistent charge transport in layered insulators is described by means of an electron-hole fight-drift model FDM and an iterative computer simulation. Ballistic secondary electrons and holes, their attenuation and drift, as well as their recombination, trapping, and detrapping are included. Thermal and field-enhanced detrapping are described by the Poole-Frenkel effect. Furthermore, an additional surface layer with a modified electric surface conductivity is included which describes the surface leakage currents and will lead to particular charge incorporation at the interface between the surface layer and the bulk substrate

Towards a Proof Theory of G\"odel Modal Logics

Analytic proof calculi are introduced for box and diamond fragments of basic modal fuzzy logics that combine the Kripke semantics of modal logic K with the many-valued semantics of G\"odel logic. The calculi are used to establish completeness and complexity results for these fragments

Connectionist modal logic: Representing modalities in neural networks

AbstractModal logics are amongst the most successful applied logical systems. Neural networks were proved to be effective learning systems. In this paper, we propose to combine the strengths of modal logics and neural networks by introducing Connectionist Modal Logics (CML). CML belongs to the domain of neural-symbolic integration, which concerns the application of problem-specific symbolic knowledge within the neurocomputing paradigm. In CML, one may represent, reason or learn modal logics using a neural network. This is achieved by a Modalities Algorithm that translates modal logic programs into neural network ensembles. We show that the translation is sound, i.e. the network ensemble computes a fixed-point meaning of the original modal program, acting as a distributed computational model for modal logic. We also show that the fixed-point computation terminates whenever the modal program is well-behaved. Finally, we validate CML as a computational model for integrated knowledge representation and learning by applying it to a well-known testbed for distributed knowledge representation. This paves the way for a range of applications on integrated knowledge representation and learning, from practical reasoning to evolving multi-agent systems