296 research outputs found

    Prediction of photoperiodic regulators from quantitative gene circuit models

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    Photoperiod sensors allow physiological adaptation to the changing seasons. The external coincidence hypothesis postulates that a light-responsive regulator is modulated by a circadian rhythm. Sufficient data are available to test this quantitatively in plants, though not yet in animals. In Arabidopsis, the clock-regulated genes CONSTANS (CO) and FLAVIN, KELCH, F-BOX (FKF1) and their lightsensitive proteins are thought to form an external coincidence sensor. We use 40 timeseries of molecular data to model the integration of light and timing information by CO, its target gene FLOWERING LOCUS T (FT), and the circadian clock. Among other predictions, the models show that FKF1 activates FT. We demonstrate experimentally that this effect is independent of the known activation of CO by FKF1, thus we locate a major, novel controller of photoperiodism. External coincidence is part of a complex photoperiod sensor: modelling makes this complexity explicit and may thus contribute to crop improvement

    Characterization and Comparison of 2 Distinct Epidemic Community-Associated Methicillin-Resistant Staphylococcus aureus Clones of ST59 Lineage.

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    Sequence type (ST) 59 is an epidemic lineage of community-associated (CA) methicillin-resistant Staphylococcus aureus (MRSA) isolates. Taiwanese CA-MRSA isolates belong to ST59 and can be grouped into 2 distinct clones, a virulent Taiwan clone and a commensal Asian-Pacific clone. The Taiwan clone carries the Panton-Valentine leukocidin (PVL) genes and the staphylococcal chromosomal cassette mec (SCCmec) VT, and is frequently isolated from patients with severe disease. The Asian-Pacific clone is PVL-negative, carries SCCmec IV, and a frequent colonizer of healthy children. Isolates of both clones were characterized by their ability to adhere to respiratory A549 cells, cytotoxicity to human neutrophils, and nasal colonization of a murine and murine sepsis models. Genome variation was determined by polymerase chain reaction of selected virulence factors and by multi-strain whole genome microarray. Additionally, the expression of selected factors was compared between the 2 clones. The Taiwan clone showed a much higher cytotoxicity to the human neutrophils and caused more severe septic infections with a high mortality rate in the murine model. The clones were indistinguishable in their adhesion to A549 cells and persistence of murine nasal colonization. The microarray data revealed that the Taiwan clone had lost the ø3-prophage that integrates into the β-hemolysin gene and includes staphylokinase- and enterotoxin P-encoding genes, but had retained the genes for human immune evasion, scn and chps. Production of the virulence factors did not differ significantly in the 2 clonal groups, although more α-toxin was expressed in Taiwan clone isolates from pneumonia patients. In conclusion, the Taiwan CA-MRSA clone was distinguished by enhanced virulence in both humans and an animal infection model. The evolutionary acquisition of PVL, the higher expression of α-toxin, and possibly the loss of a large portion of the β-hemolysin-converting prophage likely contribute to its higher pathogenic potential than the Asian-Pacific clone

    Performing the repentant lover in the courtroom: An analysis of Oscar Pistorius’ recreation of hegemonic masculinity

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    Michel Foucault (1980) presented social theorists with a consideration of power as existing everywhere. Furthermore, Jonathan Heaney (J Polit Power 6:355–362, 2013) recently asserted that emotions and power should be considered conceptual counterparts. I propose that what Foucault referred in terms of the omnipresence of power refers to its deeply social connection to emotions. One emotion, in particular, romantic love, has captured the sociological imagination not only at the level of personal relationships but also in connection with capitalism, as an ideology spurring consumption and influencing the construction of discourses and places. This chapter presents an analysis of the trial of Oscar Pistorius and the analysis plays on two levels: (a) firstly, through his courtroom interactions with members of the defence, and (b) through my eyes as a viewer, witnessing the trial on television. The televised South African courtroom becomes a space for the portrayal of a power-suffused masculine identity, which is emotionally constituted through emotional control and emotional release

    Algorithm Engineering in Robust Optimization

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    Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design

    Use of Zebrafish to Probe the Divergent Virulence Potentials and Toxin Requirements of Extraintestinal Pathogenic Escherichia coli

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    Extraintestinal pathogenic E. coli (ExPEC) cause an array of diseases, including sepsis, neonatal meningitis, and urinary tract infections. Many putative virulence factors that might modulate ExPEC pathogenesis have been identified through sequencing efforts, epidemiology, and gene expression profiling, but few of these genes have been assigned clearly defined functional roles during infection. Using zebrafish embryos as surrogate hosts, we have developed a model system with the ability to resolve diverse virulence phenotypes and niche-specific restrictions among closely related ExPEC isolates during either localized or systemic infections. In side-by-side comparisons of prototypic ExPEC isolates, we observed an unexpectedly high degree of phenotypic diversity that is not readily apparent using more traditional animal hosts. In particular, the capacity of different ExPEC isolates to persist and multiply within the zebrafish host and cause disease was shown to be variably dependent upon two secreted toxins, α-hemolysin and cytotoxic necrotizing factor. Both of these toxins appear to function primarily in the neutralization of phagocytes, which are recruited in high numbers to sites of infection where they act as an essential host defense against ExPEC as well as less virulent E. coli strains. These results establish zebrafish as a valuable tool for the elucidation and functional analysis of both ExPEC virulence factors and host defense mechanisms

    Coalition-structured governance improves cooperation to provide public goods

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    While the benefits of common and public goods are shared, they tend to be scarce when contributions are provided voluntarily. Failure to cooperate in the provision or preservation of these goods is fundamental to sustainability challenges, ranging from local fisheries to global climate change. In the real world, such cooperative dilemmas occur in multiple interactions with complex strategic interests and frequently without full information. We argue that voluntary cooperation enabled across overlapping coalitions (akin to polycentricity) not only facilitates a higher generation of non-excludable public goods, but it may also allow evolution toward a more cooperative, stable, and inclusive approach to governance. Contrary to any previous study, we show that these merits of multi-coalition governance are far more general than the singular examples occurring in the literature, and they are robust under diverse conditions of excludability, congestion of the non-excludable public good, and arbitrary shapes of the return-to-contribution function. We first confirm the intuition that a single coalition without enforcement and with players pursuing their self-interest without knowledge of returns to contribution is prone to cooperative failure. Next, we demonstrate that the same pessimistic model but with a multi-coalition structure of governance experiences relatively higher cooperation by enabling recognition of marginal gains of cooperation in the game at stake. In the absence of enforcement, public-goods regimes that evolve through a proliferation of voluntary cooperative forums can maintain and increase cooperation more successfully than singular, inclusive regimes.Supported by US Defense Advanced Research Projects Agency (D17AC00005), National Science Foundation grant GEO-1211972, and Fundacao para a Ciencia e Tecnologia (FCT) through grants PTDC/MAT/STA/3358/2014, PTDC/EEI-SII/5081/2014, and UID/BIA/04050/2013. P.M.H. was supported by the Walbridge Fund at the Princeton Environmental Institute

    Scenario trees and policy selection for multistage stochastic programming using machine learning

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    We propose a hybrid algorithmic strategy for complex stochastic optimization problems, which combines the use of scenario trees from multistage stochastic programming with machine learning techniques for learning a policy in the form of a statistical model, in the context of constrained vector-valued decisions. Such a policy allows one to run out-of-sample simulations over a large number of independent scenarios, and obtain a signal on the quality of the approximation scheme used to solve the multistage stochastic program. We propose to apply this fast simulation technique to choose the best tree from a set of scenario trees. A solution scheme is introduced, where several scenario trees with random branching structure are solved in parallel, and where the tree from which the best policy for the true problem could be learned is ultimately retained. Numerical tests show that excellent trade-offs can be achieved between run times and solution quality
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