The cytokine macrophage migration inhibitory factor (MIF) plays a critical role in inflammatory diseases and atherogenesis. We identify the chemokine receptors CXCR2 and CXCR4 as functional receptors for MIF. MIF triggered G(alphai)- and integrin-dependent arrest and chemotaxis of monocytes and T cells, rapid integrin activation and calcium influx through CXCR2 or CXCR4. MIF competed with cognate ligands for CXCR4 and CXCR2 binding, and directly bound to CXCR2. CXCR2 and CD74 formed a receptor complex, and monocyte arrest elicited by MIF in inflamed or atherosclerotic arteries involved both CXCR2 and CD74. In vivo, Mif deficiency impaired monocyte adhesion to the arterial wall in atherosclerosis-prone mice, and MIF-induced leukocyte recruitment required Il8rb (which encodes Cxcr2). Blockade of Mif but not of canonical ligands of Cxcr2 or Cxcr4 in mice with advanced atherosclerosis led to plaque regression and reduced monocyte and T-cell content in plaques. By activating both CXCR2 and CXCR4, MIF displays chemokine-like functions and acts as a major regulator of inflammatory cell recruitment and atherogenesis. Targeting MIF in individuals with manifest atherosclerosis can potentially be used to treat this condition.

We study the general properties of stochastic two-species models for predator-prey competition and coexistence with Lotka-Volterra type interactions defined on a d-dimensional lattice. Introducing spatial degrees of freedom and allowing for stochastic fluctuations generically invalidates the classical, deterministic mean-field picture. Already within mean-field theory, however, spatial constraints, modeling locally limited resources, lead to the emergence of a continuous active-toabsorbing state phase transition. Field-theoretic arguments, supported by Monte Carlo simulation results, indicate that this transition, which represents an extinction threshold for the predator population, is governed by the directed percolation universality class. In the active state, where predators and prey coexist, the classical center singularities with associated population cycles are replaced by either nodes or foci. In the vicinity of the stable nodes, the system is characterized by essentially stationary localized clusters of predators in a sea of prey. Near the stable foci, however, the stochastic lattice Lotka-Volterra system displays complex, correlated spatio-temporal patterns of competing activity fronts. Correspondingly, the population densities in our numerical simulations turn out to oscillate irregularly in time, with amplitudes that tend to zero in the thermodynamic limit. Yet in finite systems these oscillatory fluctuations are quite persistent, and their features are determined by the intrinsic interaction rates rather than the initial conditions. We emphasize the robustness of this scenario with respect to various model perturbations.

Including spatial structure and stochastic noise invalidates the classical Lotka-Volterra picture of stable regular population cycles emerging in models for predator-prey interactions. Growth-limiting terms for the prey induce a continuous extinction threshold for the predator population whose critical properties are in the directed percolation universality class. Here, we discuss the robustness of this scenario by considering an ecologically inspired stochastic lattice predator-prey model variant where the predation process includes next-nearest-neighbor interactions. We find that the corresponding stochastic model reproduces the above scenario in dimensions 1 < d ≤ 4, in contrast with mean-field theory which predicts a first-order phase transition. However, the mean-field features are recovered upon allowing for nearest-neighbor particle exchange processes, provided these are sufficiently fast. [5,6] and mathematical biology [7] as, for instance, it can also be formulated as a host-pathogen model [8]. Yet it has often been severely criticized as being biologically unrealistic and mathematically unstable [4,7,9]. Recent investigations of zero-dimensional [10] and spatial stochastic models [8,11,12,13,14,15] have shown that this criticism definitely pertains to the original deterministic rate equations; however, it turns out that the stochastic, or lattice, two-species predator-prey model variants display quite robust properties, rather insensitive on the details of the underlying microscopic processes (for a recent overview, see Ref. [16]). In particular, the lattice predator-prey models (LPPM), display the following features: (i) The population densities typically display erratic (rather than regular periodic) oscillations, with amplitudes that vanish in the thermodynamic limit [13], caused by persistent and recurrent predator-prey activity waves that form complex spatio-temporal structures [17]; (ii) when the prey population growth is limited (finite carrying capacity, local site restrictions), there exists an extinction threshold for the predator population [14,15]; this constitutes a nonequilibrium active-to-absorbing-state phase transition with the critical exponents of directed percolation (DP) [18,19]. Also, for host-pathogen models with * Electronic address: mauro.mobilia@physik.lmu.de two types of pathogens, the invasion of the system by one pathogen (the other becoming extinct) through oscillatory behavior, was reported using mean-field and pairapproximation treatments [8].As noted by various authors [13,14,15,17], a more realistic description of the predator-prey interaction should include the possibility for the agents to move. In fact, in real ecosystems prey tend to evade the predators, while the predators aim to pursue the prey. One approach to account for the motion of the agents is to consider diffusion (nearest-neighbor hopping) of predators and/or prey, which however does not really affect the global properties of the LPPM [14]. Another approach, to be considered here, is to assume a nearest...

We consider the dynamics of the voter model and of the monomer-monomer catalytic process in the presence of many "competing" inhomogeneities and show, through exact calculations and numerical simulations, that their presence results in a nontrivial fluctuating steady state whose properties are studied and turn out to specifically depend on the dimensionality of the system, the strength of the inhomogeneities and their separating distances. In fact, in arbitrary dimensions, we obtain an exact (yet formal) expression of the order parameters (magnetization and concentration of adsorbed particles) in the presence of an arbitrary number n of inhomogeneities ("zealots" in the voter language) and formal similarities with suitable electrostatic systems are pointed out. In the nontrivial cases n = 1, 2, we explicitly compute the static and long-time properties of the order parameters and therefore capture the generic features of the systems. When n > 2, the problems are studied through numerical simulations. In one spatial dimension, we also compute the expressions of the stationary order parameters in the completely disordered case, where n is arbitrary large. Particular attention is paid to the spatial dependence of the stationary order parameters and formal connections with electrostatics.