Policy Trap and Optimal Subsidization Policy under Limited Supply of Vaccines

We adopt a susceptible-infected-susceptible (SIS) model on a Barabási and Albert (BA) network to investigate the effects of different vaccine subsidization policies. The goal is to control the prevalence of the disease given a limited supply and voluntary uptake of vaccines. The results show a uniform subsidization policy is always harmful and increases the prevalence of the disease, because the lower degree individuals’ demand for vaccine crowds out the higher degree individuals’ demand. In the absence of an effective uniform policy, we explore a targeted subsidization policy which relies on a proxy variable instead of individuals’ connectivity. Findings show a poor proxy-based targeted program can still increase the disease prevalence and become a policy trap. The results are robust to general scale-free networks.     

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close “neighborhood” of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.     

Small local variations in B-form DNA lead to a large variety of global geometries which can accommodate most DNA-binding protein motifs

Background  

An important question of biological relevance is the polymorphism of the double-helical DNA structure in its free form, and the changes that it undergoes upon protein-binding. We have analysed a database of free DNA crystal structures to assess the inherent variability of the free DNA structure and have compared it with a database of protein-bound DNA crystal structures to ascertain the protein-induced variations.     

Pro-survival effects of 17β-estradiol on osteocytes are mediated by nitric oxide/cGMP via differential actions of cGMP-dependent protein kinases I and II

Estrogens promote bone health in part by increasing osteocyte survival, an effect that requires activation of the protein kinases Akt and ERK1/2, but the molecular mechanisms involved are only partly understood. Because estrogens increase nitric oxide (NO) synthesis and NO can have anti-apoptotic effects, we examined the role of NO/cGMP signaling in estrogen regulation of osteocyte survival. Etoposide-induced death of MLO-Y4 osteocyte-like cells, assessed by trypan blue staining, caspase-3 cleavage, and TUNEL assays, was completely prevented when cells were pre-treated with 17β-estradiol. This protective effect was mimicked when cells were pre-treated with a membrane-permeable cGMP analog and blocked by pharmacological inhibitors of NO synthase, soluble guanylate cyclase, or cGMP-dependent protein kinases (PKGs), supporting a requirement for NO/cGMP/PKG signaling downstream of 17β-estradiol. siRNA-mediated knockdown and viral reconstitution of individual PKG isoforms demonstrated that the anti-apoptotic effects of estradiol and cGMP were mediated by PKG Iα and PKG II. Akt and ERK1/2 activation by 17β-estradiol required PKG II, and cGMP mimicked the effects of estradiol on Akt and ERK, including induction of ERK nuclear translocation. cGMP induced BAD phosphorylation on several sites, and experiments with phosphorylation-deficient BAD mutants demonstrated that the anti-apoptotic effects of cGMP and 17β-estradiol required BAD phosphorylation on Ser(136) and Ser(155); these sites were targeted by Akt and PKG I, respectively, and regulate BAD interaction with Bcl-2. In conclusion, 17β-estradiol protects osteocytes against apoptosis by activating the NO/cGMP/PKG cascade; PKG II is required for estradiol-induced activation of ERK and Akt, and PKG Iα contributes to pro-survival signaling by directly phosphorylating BAD.     

On combinatorial DNA word design.

We consider the problem of designing DNA codes, namely sets of equi-length words over the alphabet [A, C, G, T] that satisfy certain combinatorial constraints. This problem is motivated by the task of reliably storing and retrieving information in synthetic DNA strands for use in DNA computing or as molecular bar codes in chemical libraries. The primary constraints that we consider, defined with respect to a parameter d, are as follows: for every pair of words w, x in a code, there are at least d mismatches between w and x if w not equal x and also between the reverse of w and the Watson-Crick complement of x. Extending classical results from coding theory, we present several upper and lower bounds on the maximum size of such DNA codes and give methods for constructing such codes. An additional constraint that is relevant to the design of DNA codes is that the free energies and enthalpies of the code words, and thus the melting temperatures, be similar. We describe dynamic programming algorithms that can (a) calculate the total number of words of length n whose free energy value, as approximated by a formula of Breslauer et al. (1986) falls in a given range, and (b) output a random such word. These algorithms are intended for use in heuristic algorithms for constructing DNA codes.     

Constitutive activation of LXR in macrophages regulates metabolic and inflammatory gene expression: identification of ARL7 as a direct target

Ligand activation of liver X receptors (LXRs) has been shown to impact both lipid metabolism and inflammation. One complicating factor in studies utilizing synthetic LXR agonists is the potential for pharmacologic and receptor-independent effects. Here, we describe an LXR gain-of-function system that does not depend on the addition of exogenous ligand. We generated transgenic mice expressing a constitutively active VP16-LXRα protein from the aP2 promoter. These mice exhibit increased LXR signaling selectively in adipose and macrophages. Analysis of gene expression in primary macrophages derived from two independent VP16-LXRα transgenic lines confirmed the ability of LXR to drive expression of genes involved in cholesterol efflux and fatty acid synthesis. Moreover, VP16-LXRα expression also suppressed the induction of inflammatory genes by lipopolysaccharide to a comparable degree as synthetic agonist. We further utilized VP16-LXRα-expressing macrophages to identify and validate new targets for LXRs, including the gene encoding ADP-ribosylation factor-like 7 (ARL7). ARL7 has previously been shown to transport cholesterol to the membrane for ABCA1-associated removal and thus may be integral to the LXR-dependent efflux pathway. We show that the ARL7 promoter contains a functional LXRE and can be transactivated by LXRs in a sequence-specific manner, indicating that ARL7 is a direct target of LXR. These findings provide further support for an important role of LXRs in the coordinated regulation of lipid metabolic and inflammatory gene programs in macrophages.     

Risk Assessment of H2N2 Influenza Viruses from the Avian Reservoir

H2N2 influenza A viruses were the cause of the 1957-1958 pandemic. Historical evidence demonstrates they arose from avian virus ancestors, and while the H2N2 subtype has disappeared from humans, it persists in wild and domestic birds. Reemergence of H2N2 in humans is a significant threat due to the absence of humoral immunity in individuals under the age of 50. Thus, examination of these viruses, particularly those from the avian reservoir, must be addressed through surveillance, characterization, and antiviral testing. The data presented here are a risk assessment of 22 avian H2N2 viruses isolated from wild and domestic birds over 6 decades. Our data show that they have a low rate of genetic and antigenic evolution and remained similar to isolates circulating near the time of the pandemic. Most isolates replicated in mice and human bronchial epithelial cells, but replication in swine tissues was low or absent. Multiple isolates replicated in ferrets, and 3 viruses were transmitted to direct-contact cage mates. Markers of mammalian adaptation in hemagglutinin (HA) and PB2 proteins were absent from all isolates, and they retained a preference for avian-like α2,3-linked sialic acid receptors. Most isolates remained antigenically similar to pandemic A/Singapore/1/57 (H2N2) virus, suggesting they could be controlled by the pandemic vaccine candidate. All viruses were susceptible to neuraminidase inhibitors and adamantanes. Nonetheless, the sustained pathogenicity of avian H2N2 viruses in multiple mammalian models elevates their risk potential for human infections and stresses the need for continual surveillance as a component of prepandemic planning.     

GDSCalc: A Web-Based Application for Evaluating Discrete Graph Dynamical Systems

Discrete dynamical systems are used to model various realistic systems in network science, from social unrest in human populations to regulation in biological networks. A common approach is to model the agents of a system as vertices of a graph, and the pairwise interactions between agents as edges. Agents are in one of a finite set of states at each discrete time step and are assigned functions that describe how their states change based on neighborhood relations. Full characterization of state transitions of one system can give insights into fundamental behaviors of other dynamical systems. In this paper, we describe a discrete graph dynamical systems (GDSs) application called GDSCalc for computing and characterizing system dynamics. It is an open access system that is used through a web interface. We provide an overview of GDS theory. This theory is the basis of the web application; i.e., an understanding of GDS provides an understanding of the software features, while abstracting away implementation details. We present a set of illustrative examples to demonstrate its use in education and research. Finally, we compare GDSCalc with other discrete dynamical system software tools. Our perspective is that no single software tool will perform all computations that may be required by all users; tools typically have particular features that are more suitable for some tasks. We situate GDSCalc within this space of software tools.     

Oxidatively truncated phospholipids are required agents of tumor necrosis factor α (TNFα)-induced apoptosis

TNFα generates reactive oxygen species (ROS) at the cell surface that induce cell death, but how ROS communicate to mitochondria and their specific apoptotic action(s) are both undefined. ROS oxidize phospholipids to hydroperoxides that are friable and fragment adjacent to the (hydro)peroxide function, forming truncated phospholipids, such as azelaoyl phosphatidylcholine (Az-PC). Az-PC is relatively soluble, and exogenous Az-PC rapidly enters cells to damage mitochondrial integrity and initiate intrinsic apoptosis. We determined whether this toxic phospholipid is formed within cells during TNFα stimulation in sufficient quantities to induce apoptosis and if they are essential in TNFα-induced cytotoxicity. We found that TNFα induced ROS formation and phospholipid peroxidation in Jurkat cells, and either chemical interference with NADPH oxidase activity or siRNA suppression of the NADPH oxidase-4 subunit blocked ROS accumulation and phospholipid peroxidation. Mass spectrometry showed that phospholipid peroxides and then Az-PC increased after TNFα exposure, whereas ROS inhibition abolished Az-PC accumulation and TNFα-induced cell death. Glutathione peroxidase-4 (GPx4), which specifically metabolizes lipid hydroperoxides, fell in TNFα-stimulated cells prior to death. Ectopic GPx4 overcame this, reduced peroxidized phospholipid accumulation, blocked Az-PC accumulation, and prevented death. Conversely, GPx4 siRNA knockdown enhanced phospholipid peroxidation, increasing TNFα-stimulated Az-PC formation and apoptosis. Truncated phospholipids were essential elements of TNFα-induced apoptosis because overexpression of PAFAH2 (a phospholipase A(2) that selectively hydrolyzes truncated phospholipids) blocked TNFα-induced Az-PC accumulation without affecting phospholipid peroxidation. PAFAH2 also abolished apoptosis. Thus, phospholipid oxidation and truncation to apoptotic phospholipids comprise an essential element connecting TNFα receptor signaling to mitochondrial damage and apoptotic death.