ASU Scholarship Showcase

Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network “mobile” can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.

We develop a completely data-driven approach to reconstructing coupled neuronal networks that contain a small subset of chaotic neurons. Such chaotic elements can be the result of parameter shift in their individual dynamical systems and may lead to abnormal functions of the network. To accurately identify the chaotic neurons may thus be necessary and important, for example, applying appropriate controls to bring the network to a normal state. However, due to couplings among the nodes, the measured time series, even from non-chaotic neurons, would appear random, rendering inapplicable traditional nonlinear time-series analysis, such as the delay-coordinate embedding method, which yields information about the global dynamics of the entire network. Our method is based on compressive sensing. In particular, we demonstrate that identifying chaotic elements can be formulated as a general problem of reconstructing the nodal dynamical systems, network connections and all coupling functions, as well as their weights. The working and efficiency of the method are illustrated by using networks of non-identical FitzHugh–Nagumo neurons with randomly-distributed coupling weights.

Bacterial lipopolysaccharides (LPS) are structural components of the outer membranes of Gram-negative bacteria and also are potent inducers of inflammation in mammals. Higher vertebrates are extremely sensitive to LPS, but lower vertebrates, like fish, are resistant to their systemic toxic effects. However, the effects of LPS on the fish intestinal mucosa remain unknown. Edwardsiella ictaluri is a primitive member of the Enterobacteriaceae family that causes enteric septicemia in channel catfish (Ictalurus punctatus). E. ictaluri infects and colonizes deep lymphoid tissues upon oral or immersion infection. Both gut and olfactory organs are the primary sites of invasion. At the systemic level, E. ictaluri pathogenesis is relatively well characterized, but our knowledge about E. ictaluri intestinal interaction is limited. Recently, we observed that E. ictaluri oligo-polysaccharide (O-PS) LPS mutants have differential effects on the intestinal epithelia of orally inoculated catfish. Here we evaluate the effects of E. ictaluri O-PS LPS mutants by using a novel catfish intestinal loop model and compare it to the rabbit ileal loop model inoculated with Salmonella enterica serovar Typhimurium LPS. We found evident differences in rabbit ileal loop and catfish ileal loop responses to E. ictaluri and S. Typhimurium LPS. We determined that catfish respond to E. ictaluri LPS but not to S. Typhimurium LPS. We also determined that E. ictaluri inhibits cytokine production and induces disruption of the intestinal fish epithelia in an O-PS-dependent fashion. The E. ictaluri wild type and ΔwibT LPS mutant caused intestinal tissue damage and inhibited proinflammatory cytokine synthesis, in contrast to E. ictaluri Δgne and Δugd LPS mutants. We concluded that the E. ictaluri O-PS subunits play a major role during pathogenesis, since they influence the recognition of the LPS by the intestinal mucosal immune system of the catfish. The LPS structure of E. ictaluri mutants is needed to understand the mechanism of interaction.

Contemporary vaccine development relies less on empirical methods of vaccine construction, and now employs a powerful array of precise engineering strategies to construct immunogenic live vaccines. In this review, we will survey various engineering techniques used to create attenuated vaccines, with an emphasis on recent advances and insights. We will further explore the adaptation of attenuated strains to create multivalent vaccine platforms for immunization against multiple unrelated pathogens. These carrier vaccines are engineered to deliver sufficient levels of protective antigens to appropriate lymphoid inductive sites to elicit both carrier-specific and foreign antigen-specific immunity. Although many of these technologies were originally developed for use in Salmonella vaccines, application of the essential logic of these approaches will be extended to development of other enteric vaccines where possible. A central theme driving our discussion will stress that the ultimate success of an engineered vaccine rests on achieving the proper balance between attenuation and immunogenicity. Achieving this balance will avoid over-activation of inflammatory responses, which results in unacceptable reactogenicity, but will retain sufficient metabolic fitness to enable the live vaccine to reach deep tissue inductive sites and trigger protective immunity. The breadth of examples presented herein will clearly demonstrate that genetic engineering offers the potential for rapidly propelling vaccine development forward into novel applications and therapies which will significantly expand the role of vaccines in public health.

Current research on criminal case processing typically examines a single decision-making point, so drawing reliable conclusions about the impact that factors such as defendants’ race or ethnicity exert across successive stages of the justice system is difficult. Using data from the New York County District Attorney's Office that tracks 185,275 diverse criminal cases, this study assesses racial and ethnic disparity for multiple discretionary points of prosecution and sentencing. Findings from multivariate logistic regression analyses demonstrate that the effects of race and ethnicity vary by discretionary point and offense category. Black and Latino defendants were more likely than White defendants to be detained, to receive a custodial plea offer, and to be incarcerated—and they received especially punitive outcomes for person offenses—but were more likely to benefit from case dismissals. The findings for Asian defendants were less consistent but suggest they were the least likely to be detained, to receive custodial offers, and to be incarcerated. These findings are discussed in the context of contemporary theoretical perspectives on racial bias and cumulative disadvantage in the justice system.

The relation between flux and fluctuation is fundamental to complex physical systems that support and transport flows. A recently obtained law predicts monotonous enhancement of fluctuation as the average flux is increased, which in principle is valid but only for large systems. For realistic complex systems of small sizes, this law breaks down when both the average flux and fluctuation become large. Here we demonstrate the failure of this law in small systems using real data and model complex networked systems, derive analytically a modified flux-fluctuation law, and validate it through computations of a large number of complex networked systems. Our law is more general in that its predictions agree with numerics and it reduces naturally to the previous law in the limit of large system size, leading to new insights into the flow dynamics in small-size complex systems with significant implications for the statistical and scaling behaviors of small systems, a topic of great recent interest.

There are many proteomic applications that require large collections of purified protein, but parallel production of large numbers of different proteins remains a very challenging task. To help meet the needs of the scientific community, we have developed a human protein production pipeline. Using high-throughput (HT) methods, we transferred the genes of 31 full-length proteins into three expression vectors, and expressed the collection as N-terminal HaloTag fusion proteins in Escherichia coli and two commercial cell-free (CF) systems, wheat germ extract (WGE) and HeLa cell extract (HCE). Expression was assessed by labeling the fusion proteins specifically and covalently with a fluorescent HaloTag ligand and detecting its fluorescence on a LabChip[superscript ®] GX microfluidic capillary gel electrophoresis instrument. This automated, HT assay provided both qualitative and quantitative assessment of recombinant protein. E. coli was only capable of expressing 20% of the test collection in the supernatant fraction with ≥20 μg yields, whereas CF systems had ≥83% success rates. We purified expressed proteins using an automated HaloTag purification method. We purified 20, 33, and 42% of the test collection from E. coli, WGE, and HCE, respectively, with yields ≥1 μg and ≥90% purity. Based on these observations, we have developed a triage strategy for producing full-length human proteins in these three expression systems.

We develop a general framework to analyze the controllability of multiplex networks using multiple-relation networks and multiple-layer networks with interlayer couplings as two classes of prototypical systems. In the former, networks associated with different physical variables share the same set of nodes and in the latter, diffusion processes take place. We find that, for a multiple-relation network, a layer exists that dominantly determines the controllability of the whole network and, for a multiple-layer network, a small fraction of the interconnections can enhance the controllability remarkably. Our theory is generally applicable to other types of multiplex networks as well, leading to significant insights into the control of complex network systems with diverse structures and interacting patterns.

Throughout the long history of virus-host co-evolution, viruses have developed delicate strategies to facilitate their invasion and replication of their genome, while silencing the host immune responses through various mechanisms. The systematic characterization of viral protein-host interactions would yield invaluable information in the understanding of viral invasion/evasion, diagnosis and therapeutic treatment of a viral infection, and mechanisms of host biology. With more than 2,000 viral genomes sequenced, only a small percent of them are well investigated. The access of these viral open reading frames (ORFs) in a flexible cloning format would greatly facilitate both in vitro and in vivo virus-host interaction studies. However, the overall progress of viral ORF cloning has been slow. To facilitate viral studies, we are releasing the initiation of our panviral proteome collection of 2,035 ORF clones from 830 viral genes in the Gateway® recombinational cloning system. Here, we demonstrate several uses of our viral collection including highly efficient production of viral proteins using human cell-free expression system in vitro, global identification of host targets for rubella virus using Nucleic Acid Programmable Protein Arrays (NAPPA) containing 10,000 unique human proteins, and detection of host serological responses using micro-fluidic multiplexed immunoassays. The studies presented here begin to elucidate host-viral protein interactions with our systemic utilization of viral ORFs, high-throughput cloning, and proteomic technologies. These valuable plasmid resources will be available to the research community to enable continued viral functional studies.

Evolutionary dynamical models for cyclic competitions of three species (e.g., rock, paper, and scissors, or RPS) provide a paradigm, at the microscopic level of individual interactions, to address many issues in coexistence and biodiversity. Real ecosystems often involve competitions among more than three species. By extending the RPS game model to five (rock-paper-scissors-lizard-Spock, or RPSLS) mobile species, we uncover a fundamental type of mesoscopic interactions among subgroups of species. In particular, competitions at the microscopic level lead to the emergence of various local groups in different regions of the space, each involving three species. It is the interactions among the groups that fundamentally determine how many species can coexist. In fact, as the mobility is increased from zero, two transitions can occur: one from a five- to a three-species coexistence state and another from the latter to a uniform, single-species state. We develop a mean-field theory to show that, in order to understand the first transition, group interactions at the mesoscopic scale must be taken into account. Our findings suggest, more broadly, the importance of mesoscopic interactions in coexistence of great many species.