Multiscale Immune Selection and the Transmission-Diversity Feedback in Antigenically Diverse Pathogen Systems

This is the final version of the article. Available from University of Chicago Press via the DOI in this record.Antigenic diversity is commonly used by pathogens to enhance their transmission success. Within-host clonal antigenic variation helps to maintain long infectious periods, whereas high levels of allelic diversity at the population level significantly expand the pool of susceptible individuals. Diversity, however, is not necessarily a static property of a pathogen population but in many cases is generated by the very act of infection and transmission, and it is therefore expected to respond dynamically to changes in transmission and immune selection. We hypothesized that this coupling creates a positive feedback whereby infection and disease transmission promote the generation of diversity, which itself facilitates immune evasion and further infections. To investigate this link in more detail, we considered the human malaria parasite Plasmodium falciparum, one of the most important antigenically diverse pathogens. We developed an individual-based model in which antigenic diversity emerges as a dynamic property from the underlying transmission processes. Our results show that the balance between stochastic extinction and the generation of new antigenic variants is intrinsically linked to within-host and between-host immune selection. This in turn determines the level of diversity that can be maintained in a given population. Furthermore, the transmission-diversity feedback can lead to temporal lags in the response to natural or intervention-induced perturbations in transmission rates. Our results therefore have important implications for monitoring and assessing the effectiveness of disease control efforts

Troubleshooting Strategies in a Complex, Dynamical Domain

In this paper, we present results ftom two empirical studies in which subjects diagnosed faults that occurred in a computerbased, dynamical simulation of an oil-fired marine power plant, called Turbinia. Our results were analyzed in the framework of dual problem space search (DPSS), in which non-routine diagnosis was characterized as a process of generating hypotheses to explain the observed faults, and testing these hypotheses by conducting experiments. In the first study, we found that the less-efficient subjects conducted significantly more experiments, indicating a strong bottom-up bias in their diagnostic sU-ategy. In tiie second study, we examined the effects of imposing external resource bounds on subjects' diagnostic strategies. Results indicated that constraints on diagnosis time led to a reduction in the number of actions performed and components viewed, without appearing to affect diagnostic performance. Constraints on the number of diagnostic tests reduced search in the experiment space, which appeared to negatively affect performance. Taken together, these suggest results that subjects' diagnostic strategies were sensitive to consti-aints in tiie external task environment. We close with a sketch of how DPSS might be augmented to include effects due to external resource bounds

Building a complementary agenda for business process management and digital innovation.

The world is blazing with change and digital innovation is fuelling the fire. Process management can help channel the heat into useful work. Unfortunately, research on digital innovation and process management has been conducted by separate communities operating under orthogonal assumptions. We argue that a synthesis of assumptions is required to bring these streams of research together. We offer suggestions for how these assumptions can be updated to facilitate a convergent conversation between the two research streams. We also suggest ways that methodologies from each stream could benefit the other. Together with the three exemplar empirical studies included in the special issue on business process management and digital innovation, we develop a broader foundation for reinventing research on business process management in a world ablaze with digital innovation

The Convergence of Business Process Management and Digital Innovation

Business process management is a prolific field of research and an area of strong industrial uptake with roots in both management science and information systems engineering. Traditionally, business process management has largely been utilized in an inward-looking way with the aim to improve operations, eliminate waste, and increase efficiency. Recent developments around digital innovation challenge conventional ideas of process reengineering with a strong emphasis on the external market and exploration. In this talk, we will discuss the complementarity of BPM and digital innovation

Sustainable Energy Transition: Intermittency Policy Based on Digital Mirror Actions

The transition to renewable energy requires organizations and governments to formulate and enact new energy policies. This emerging energy era is characterized by higher levels of supply and demand intermittency, which requires information systems to manage the electricity grid. We propose key policy elements for managing intermittency based on information systems to implement digital mirror actions for managing the production, consumption, and transfer of electricity and market mechanisms for maintaining grid equilibrium. This article discusses these and their energy policy implications

Bringing Context Inside Process Research with Digital Trace Data

Context is usually conceptualized as “external” to a theory or model and treated as something to be controlled or eliminated in empirical research. We depart from this tradition and conceptualize context as permeating processual phenomena. This move is possible because digital trace data are now increasingly available, providing rich and fine-grained data about processes mediated or enabled by digital technologies. This paper introduces a novel method for including fine-grained contextual information from digital trace data within the description of process (e.g., who, what, when, where, why). Adding contextual information can result in a very large number of fine-grained categories of events, which are usually considered undesirable. However, we argue that a large number of categories can make process data more informative for theorizing and that including contextual detail enriches the understanding of processes as they unfold. We demonstrate this by analyzing audit trail data of electronic medical records using ThreadNet, an open source software application developed for the qualitative visualization and analysis of process data. The distinctive contribution of our approach is the novel way in which we contextualize events and action in process data. Providing new, usable ways to incorporate context can help researchers ask new questions about the dynamics of processual phenomena

Individual bacteria in structured environments rely on phenotypic resistance to phage

This is the final version. Available on open access from Public Library of Science via the DOI in this recordData Availability: All relevant data are within the paper and its Supporting Information files.Bacteriophages represent an avenue to overcome the current antibiotic resistance crisis, but evolution of genetic resistance to phages remains a concern. In vitro, bacteria evolve genetic resistance, preventing phage adsorption or degrading phage DNA. In natural environments, evolved resistance is lower possibly because the spatial heterogeneity within biofilms, microcolonies, or wall populations favours phenotypic survival to lytic phages. However, it is also possible that the persistence of genetically sensitive bacteria is due to less efficient phage amplification in natural environments, the existence of refuges where bacteria can hide, and a reduced spread of resistant genotypes. Here, we monitor the interactions between individual planktonic bacteria in isolation in ephemeral refuges and bacteriophage by tracking the survival of individual cells. We find that in these transient spatial refuges, phenotypic resistance due to reduced expression of the phage receptor is a key determinant of bacterial survival. This survival strategy is in contrast with the emergence of genetic resistance in the absence of ephemeral refuges in well-mixed environments. Predictions generated via a mathematical modelling framework to track bacterial response to phages reveal that the presence of spatial refuges leads to fundamentally different population dynamics that should be considered in order to predict and manipulate the evolutionary and ecological dynamics of bacteria-phage interactions in naturally structured environments.Medical Research Council (MRC)Engineering and Physical Sciences Research Council (EPSRC)Gordon and Betty and Gordon Moore FoundationEuropean Research Council (ERC)Biotechnology and Biological Sciences Research Council (BBSRC)Natural Environment Research Council (NERC)Marie Skłodowska-Curie ActionsDefence Science and Technology Laboratory (Dstl)Royal Societ

A reference architecture for the collaborative planning modelling process in multi-tier supply chain networks: a Zachman-based approach

A prominent and contemporary challenge for supply chain (SC) managers concerns the coordination of the efforts of the nodes of the SC in order to mitigate unpredictable market behaviour and satisfy variable customer demand. A productive response to this challenge is to share pertinent market-related information, on a timely basis, in order to effectively manage the decision-making associated with the SC production and transportation planning processes. This paper analyses the most well-known reference modelling languages and frameworks in the collaborative SC field and proposes a novel reference architecture, based upon the Zachman Framework (ZF), for supporting collaborative plan- ning (CP) in multi-level, SC networks. The architecture is applied to an automotive supply chain configuration, where, under a collaborative and decentralised approach, improvements in the service levels for each node were observed. The architecture was shown to provide the base discipline for the organisation of the processes required to manage the CP activity.The authors thanks the support from the project 'Operations Design and Management in Global Supply Chains (GLOBOP)' (Ref. DPI2012-38061-C02-01), funded by the Ministry of Science and Education of Spain, for the supply chain environment research contribution.Hernández Hormazábal, JE.; Lyons, AC.; Poler, R.; Mula, J.; Goncalves, R. (2014). A reference architecture for the collaborative planning modelling process in multi-tier supply chain networks: a Zachman-based approach. Production Planning and Control. 25(13-14):1118-1134. https://doi.org/10.1080/09537287.2013.808842S111811342513-14Al-Mutawah, K., Lee, V., & Cheung, Y. (2008). A new multi-agent system framework for tacit knowledge management in manufacturing supply chains. Journal of Intelligent Manufacturing, 20(5), 593-610. doi:10.1007/s10845-008-0142-0Baïna, S., Panetto, H., & Morel, G. (2009). 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Canalization of the evolutionary trajectory of the human influenza virus

Since its emergence in 1968, influenza A (H3N2) has evolved extensively in genotype and antigenic phenotype. Antigenic evolution occurs in the context of a two-dimensional 'antigenic map', while genetic evolution shows a characteristic ladder-like genealogical tree. Here, we use a large-scale individual-based model to show that evolution in a Euclidean antigenic space provides a remarkable correspondence between model behavior and the epidemiological, antigenic, genealogical and geographic patterns observed in influenza virus. We find that evolution away from existing human immunity results in rapid population turnover in the influenza virus and that this population turnover occurs primarily along a single antigenic axis. Thus, selective dynamics induce a canalized evolutionary trajectory, in which the evolutionary fate of the influenza population is surprisingly repeatable and hence, in theory, predictable.Comment: 29 pages, 5 figures, 10 supporting figure

Voltammetric determination of indomenthyl

Cytokines are important mediators coordinating inflammation and wound healing in response to tissue damage and infection. Therefore, immobilization of cytokines on the surface of biomaterials is a promising approach to improve biocompatibility. Soluble cytokines signal through receptors on the cell surface leading to cell differentiation, proliferation, or other effector functions. Random immobilization of cytokines on surfaces will result in a large fraction of inactive protein due to impaired cytokine-receptor interaction. We developed a strategy that combined (i) directed covalent coupling of cytokines, (ii) quantification of coupling efficiency through fluorescence detection, and (iii) a reliable protease cleavage assay to control orientation of coupling. For this purpose, fusion proteins of the SNAP-tag followed by an enterokinase recognition site, yellow fluorescent protein (YFP), and the cytokine of interest being either interleukin-6 (IL-6) or oncostatin M (OSM) were generated. The SNAP-tag is a derivative of O6-alkylguanine-DNA alkyltransferase that couples itself covalently to benzylguanine. Bioactivities of the SNAP-YFP-cytokines were shown to be comparable with the nontagged cytokines. Efficient coupling of SNAP-YFP-cytokines to benzylguanine-modified beads was demonstrated by flow cytometry. The fact that enterokinase treatment released most of the fluorescence from the beads is indicative for directed coupling and only marginal adsorptive binding. Cellular responses to SNAP-YFP-cytokine beads were analyzed in cellular lysates and by confocal microscopy indicating that the directionally immobilized cytokines are fully signaling competent with respect to the activation of ERK and STAT3. The strategy presented here is generally applicable for the directed covalent immobilization of fluorescently labeled proteins including the convenient and reliable control of coupling efficiency and orientation