Simulated Versus Observed Cluster Eccentricity Evolution

The rate of galaxy cluster eccentricity evolution is useful in understanding large scale structure. Rapid evolution for $z <$ 0.13 has been found in two different observed cluster samples. We present an analysis of projections of 41 clusters produced in hydrodynamic simulations augmented with radiative cooling and 43 clusters from adiabatic simulations. This new, larger set of simulated clusters strengthens the claims of previous eccentricity studies. We find very slow evolution in simulated clusters, significantly different from the reported rates of observational eccentricity evolution. We estimate the rate of change of eccentricity with redshift and compare the rates between simulated and observed clusters. We also use a variable aperture radius to compute the eccentricity, r$_{200}$. This method is much more robust than the fixed aperture radius used in previous studies. Apparently radiative cooling does not change cluster morphology on scales large enough to alter eccentricity. The discrepancy between simulated and observed cluster eccentricity remains. Observational bias or incomplete physics in simulations must be present to produce halos that evolve so differently.Comment: ApJ, in press, minor revision

A Radical Shift for the Future of Environmental Law: the Potential and Risks of the Use of Technology for the Benefit of the Environment

The rate of environmental decline over the past few decades has been alarming, reflecting the relative ineffectiveness of the expanding body of environmental law that has been enacted since the early 1970s. Scholars have analysed the causes for the sub-optimal performance of environmental regulation, and put forward a plethora of explanations. Our scientific understanding of how ecologies interrelate and what critical thresholds exist remains sketchy at best, which hinders the articulation of appropriate regulatory goals. It is also hard to channel the behaviour of citizens for as long as the costs of environmental harm are borne by future generations that are not represented in political and legal processes. Last but not least, disequilibrium exists between those having an interest in pursuing a certain (industrial) activity and the environment, which cannot fend for itself, yet is not easily represented in the law. The search is on for new regulatory approaches that radically improve on the environmental performance of the current regulatory regime. As environmental threats, such as climate change, are becoming ever more acute and serious, and public funds simultaneously increasingly scarce, technology is becoming part of the standard toolbox of environmental regulators. This being so, we can no longer postpone thinking about the implications of the use of technology for environmental law. First and foremost, this is because changes in one mode of regulation will reverberate across the regulatory landscape. Norms that would be challenged by the employment of technologies are in particular those pertaining to access to environmental information, public participation in environmental decision-making and access to justice in environmental cases. These norms not so much regard the effectiveness of environmental regulation, but seek to safeguard its legitimacy. Legitimacy, in this context, implies that both the goals pursued by regulation are proper (or, put more specifically, that regulation responds to major environmental needs) and that regulators pursue those goals in the right way (respecting fundamental rights, proportionality, taking account of principles of environmental law, such as polluter pays, precaution etc.). In general terms, the paper hence revolves around questions concerning (a) the environmental potential of the employment of technology and (b) the compatibility of the use of technology with the existing regulatory landscape. We will look into these issues by focussing on one area where technological innovation may profoundly impact on environmental law: geo-engineering. Geo-engineering is defined as deliberate large-scale manipulation of the planetary environment to counteract anthropogenic climate change. (International) legislation explicitly aimed at regulating the various forms of geo-engineering is still absent. We will analyse how international law should react on the emergence of these innovative technologies. A twofold response seems in order. First, the development and deployment of these technologies needs to be regulated in such a way as to avoid unwanted negative impacts on the environment. Second, legislation may be required to embed geo-engineering within the existing regulation. We will show the various ways in which this can be done. This case, thus, offers an interesting opportunity to explore both the potential and risks that arise when using new technologies to combat environmental degradation

Predator persistence through variability of resource productivity in Tritrophic systems

The trophic structure of species communities depends on the energy transfer between trophic levels. Primary productivity varies strongly through time, challenging the persistence of species at higher trophic levels. Yet resource variability has mostly been studied in systems with only one or two trophic levels. We test the effect of variability in resource productivity in a tritrophic model system including a resource, a size-structured consumer, and a size-specific predator. The model complies with fundamental principles of mass conservation and the body-size dependence of individual-level energetics and predator-prey interactions. Surprisingly, we find that resource variability may promote predator persistence. The positive effect of variability on the predator arises through periods with starvation mortality of juvenile prey, which reduces the intraspecific competition in the prey population. With increasing variability in productivity and starvation mortality in the juvenile prey, the prey availability increases in the size range preferred by the predator. The positive effect of prey mortality on the trophic transfer efficiency depends on the biologically realistic consideration of body size–dependent and food-dependent functions for growth and reproduction in our model. Our findings show that variability may promote the trophic transfer efficiency, indicating that environmental variability may sustain species at higher trophic levels in natural ecosystems

Bioengineered Nisin A Derivatives with Enhanced Activity against Both Gram Positive and Gram Negative Pathogens

peer-reviewedNisin is a bacteriocin widely utilized in more than 50 countries as a safe and natural antibacterial food preservative. It is the most extensively studied bacteriocin, having undergone decades of bioengineering with a view to improving function and physicochemical properties. The discovery of novel nisin variants with enhanced activity against clinical and foodborne pathogens has recently been described. We screened a randomized bank of nisin A producers and identified a variant with a serine to glycine change at position 29 (S29G), with enhanced efficacy against S. aureus SA113. Using a site-saturation mutagenesis approach we generated three more derivatives (S29A, S29D and S29E) with enhanced activity against a range of Gram positive drug resistant clinical, veterinary and food pathogens. In addition, a number of the nisin S29 derivatives displayed superior antimicrobial activity to nisin A when assessed against a range of Gram negative food-associated pathogens, including E. coli, Salmonella enterica serovar Typhimurium and Cronobacter sakazakii. This is the first report of derivatives of nisin, or indeed any lantibiotic, with enhanced antimicrobial activity against both Gram positive and Gram negative bacteria.This work was supported by the Irish Government under the National Development Plan, through Science Foundation Ireland Investigator awards (10/IN.1/B3027) and (06/IN.1/B98) (http://www.sfi.ie)

A model to estimate effects of SNPs on host susceptibility and infectivity for an endemic infectious disease

International audienceAbstractBackgroundInfectious diseases in farm animals affect animal health, decrease animal welfare and can affect human health. Selection and breeding of host individuals with desirable traits regarding infectious diseases can help to fight disease transmission, which is affected by two types of (genetic) traits: host susceptibility and host infectivity. Quantitative genetic studies on infectious diseases generally connect an individual’s disease status to its own genotype, and therefore capture genetic effects on susceptibility only. However, they usually ignore variation in exposure to infectious herd mates, which may limit the accuracy of estimates of genetic effects on susceptibility. Moreover, genetic effects on infectivity will exist as well. Thus, to design optimal breeding strategies, it is essential that genetic effects on infectivity are quantified. Given the potential importance of genetic effects on infectivity, we set out to develop a model to estimate the effect of single nucleotide polymorphisms (SNPs) on both host susceptibility and host infectivity. To evaluate the quality of the resulting SNP effect estimates, we simulated an endemic disease in 10 groups of 100 individuals, and recorded time-series data on individual disease status. We quantified bias and precision of the estimates for different sizes of SNP effects, and identified the optimum recording interval when the number of records is limited.ResultsWe present a generalized linear mixed model to estimate the effect of SNPs on both host susceptibility and host infectivity. SNP effects were on average slightly underestimated, i.e. estimates were conservative. Estimates were less precise for infectivity than for susceptibility. Given our sample size, the power to estimate SNP effects for susceptibility was 100% for differences between genotypes of a factor 1.56 or more, and was higher than 60% for infectivity for differences between genotypes of a factor 4 or more. When disease status was recorded 11 times on each animal, the optimal recording interval was 25 to 50% of the average infectious period.ConclusionsOur model was able to estimate genetic effects on susceptibility and infectivity. In future genome-wide association studies, it may serve as a starting point to identify genes that affect disease transmission and disease prevalence

Genetic parameters and genomic breeding values for digital dermatitis in Holstein Friesian dairy cattle: host susceptibility, infectivity and the basic reproduction ratio

International audienceBackground : For infectious diseases, the probability that an animal gets infected depends on its own susceptibility, and on the number of infectious herd mates and their infectivity. Together with the duration of the infectious period, susceptibility and infectivity determine the basic reproduction ratio of the disease ( R0 ). R0 is the average number of secondary cases caused by a typical infectious individual in an otherwise uninfected population. An infectious disease dies out when R0 is lower than 1. Thus, breeding strategies that aim at reducing disease prevalence should focus on reducing R0 , preferably to a value lower than 1. In animal breeding, however, R0 has received little attention. Here, we estimate the additive genetic variance in host susceptibility, host infectivity, and R0 for the endemic claw disease digital dermatitis (DD) in Holstein Friesian dairy cattle, and estimate genomic breeding values (GEBV ) for these traits. We recorded DD disease status of both hind claws of 1513 cows from 12 Dutch dairy farms, every 2 weeks, 11 times. The genotype data consisted of 75,904 single nucleotide polymorphisms (SNPs) for 1401 of the cows. We modelled the probability that a cow got infected between recordings, and compared four generalized linear mixed models. All models included a genetic effect for susceptibility; Models 2 and 4 also included a genetic effect for infectivity, while Models 1 and 2 included a farm*period interaction. We corrected for variation in exposure to infectious herd mates via an offset.Results : GEBV for R0 from the model that included genetic effects for susceptibility only had an accuracy of ~ 0.39 based on cross-validation between farms, which is very high given the limited amount of data and the complexity of the trait. Models with a genetic effect for infectivity showed a larger bias, but also a slightly higher accuracy of GEBV. Additive genetic standard deviation for R0 was large, i.e. ~ 1.17, while the mean R0 was 2.36.Conclusions : GEBV for R0 showed substantial variation. The mean R0 was only about one genetic standard deviation greater than 1. These results suggest that lowering DD prevalence by selective breeding is promising

Pacing therapy for atrioventricular dromotropathy: A combined computational-experimental-clinical study

AIMS: Investigate haemodynamic effects, and their mechanisms, of restoring atrioventricular (AV)-coupling using pacemaker therapy in normal and failing hearts in a combined computational-experimental-clinical study. METHODS AND RESULTS: Computer simulations were performed in the CircAdapt model of the normal and failing human heart and circulation. Experiments were performed in a porcine model of AV dromotropathy. In a proof-of-principle clinical study, left ventricular (LV) pressure and volume were measured in 22 heart failure (HF) patients (LV ejection fraction \u3c35%) with prolonged PR interval (\u3e230 ms) and narrow or non-left bundle branch block QRS complex. Computer simulations and animal studies in normal hearts showed that restoring of AV-coupling with unchanged ventricular activation sequence significantly increased LV filling, mean arterial pressure, and cardiac output by 10-15%. In computer simulations of failing hearts and in HF patients, reducing PR interval by biventricular (BiV) pacing (patients: from 300 ± 61 to 137 ± 30 ms) resulted in significant increases in LV stroke volume and stroke work (patients: 34 ± 40% and 26 ± 31%, respectively). However, worsening of ventricular dyssynchrony by using right ventricular (RV) pacing abrogated the benefit of restoring AV-coupling. In model simulations, animals and patients, the increase of LV filling and associated improvement of LV pump function coincided with both larger mitral inflow (E- and A-wave area) and reduction of diastolic mitral regurgitation. CONCLUSION: Restoration of AV-coupling by BiV pacing in normal and failing hearts with prolonged AV conduction leads to considerable haemodynamic improvement. These results indicate that BiV or physiological pacing, but not RV pacing, may improve cardiac function in patients with HF and prolonged PR interval

Intestinal microbiome landscaping : insight in community assemblage and implications for microbial modulation strategies

High individuality, large complexity and limited understanding of the mechanisms underlying human intestinal microbiome function remain the major challenges for designing beneficial modulation strategies. Exemplified by the analysis of intestinal bacteria in a thousand Western adults, we discuss key concepts of the human intestinal microbiome landscape, i.e. the compositional and functional 'core', the presence of community types and the existence of alternative stable states. Genomic investigation of core taxa revealed functional redundancy, which is expected to stabilize the ecosystem, as well as taxa with specialized functions that have the potential to shape the microbiome landscape. The contrast between Prevotella-and Bacteroides-dominated systems has been well described. However, less known is the effect of not so abundant bacteria, for example, Dialister spp. that have been proposed to exhibit distinct bistable dynamics. Studies employing time-series analysis have highlighted the dynamical variation in the microbiome landscape with and without the effect of defined perturbations, such as the use of antibiotics or dietary changes. We incorporate ecosystem-level observations of the human intestinal microbiota and its keystone species to suggest avenues for designing microbiome modulation strategies to improve host health.Peer reviewe

Review of approaches to establish reference levels to interpret indicators

Agricultural and Food Policy, Environmental Economics and Policy, Farm Management, Land Economics/Use,