Pericarditis and Autoinflammation: A Clinical and Genetic Analysis of Patients With Idiopathic Recurrent Pericarditis and Monogenic Autoinflammatory Diseases at a National Referral Center.

Background: Idiopathic recurrent pericarditis (IRP) is an orphan disease that carries significant morbidity, partly driven by corticosteroid dependence. Innate immune modulators, colchicine and anti-interleukin-1 agents, pioneered in monogenic autoinflammatory diseases, have demonstrated remarkable efficacy in trials, suggesting that autoinflammation may contribute to IRP. This study characterizes the phenotype of patients with IRP and monogenic autoinflammatory diseases, and establishes whether autoinflammatory disease genes are associated with IRP. Methods and Results: We retrospectively analyzed the medical records of patients with IRP (n=136) and monogenic autoinflammatory diseases (n=1910) attending a national center (London, UK) between 2000 and 2021. We examined 4 genes (MEFV, MVK, NLRP3, TNFRSF1A) by next-generation sequencing in 128 patients with IRP and compared the frequency of rare deleterious variants to controls obtained from the Genome Aggregation Database. In this cohort of patients with IRP, corticosteroid dependence was common (39/136, 28.7%) and was associated with chronic pain (adjusted odds ratio 2.8 [95% CI, 1.3-6.5], P=0.012). IRP frequently manifested with systemic inflammation (raised C-reactive protein [121/136, 89.0%] and extrapericardial effusions [68/136, 50.0%]). Pericarditis was observed in all examined monogenic autoinflammatory diseases (0.4%-3.7% of cases). Rare deleterious MEFV variants were more frequent in IRP than in ancestry-matched controls (allele frequency 9/200 versus 2932/129 200, P=0.040). Conclusions: Pericarditis is a feature of interleukin-1 driven monogenic autoinflammatory diseases and IRP is associated with variants in MEFV, a gene involved in interleukin-1β processing. We also found that corticosteroid dependence in IRP is associated with chronic noninflammatory pain. Together these data implicate autoinflammation in IRP and support reducing reliance on corticosteroids in its management

The Complexity of Repairing, Adjusting, and Aggregating of Extensions in Abstract Argumentation

We study the computational complexity of problems that arise in abstract argumentation in the context of dynamic argumentation, minimal change, and aggregation. In particular, we consider the following problems where always an argumentation framework F and a small positive integer k are given. - The Repair problem asks whether a given set of arguments can be modified into an extension by at most k elementary changes (i.e., the extension is of distance k from the given set). - The Adjust problem asks whether a given extension can be modified by at most k elementary changes into an extension that contains a specified argument. - The Center problem asks whether, given two extensions of distance k, whether there is a "center" extension that is a distance at most (k-1) from both given extensions. We study these problems in the framework of parameterized complexity, and take the distance k as the parameter. Our results covers several different semantics, including admissible, complete, preferred, semi-stable and stable semantics

Gravitational wave astronomy

The first decade of the new millenium should see the first direct detections of gravitational waves. This will be a milestone for fundamental physics and it will open the new observational science of gravitational wave astronomy. But gravitational waves already play an important role in the modeling of astrophysical systems. I review here the present state of gravitational radiation theory in relativity and astrophysics, and I then look at the development of detector sensitivity over the next decade, both on the ground (such as LIGO) and in space (LISA). I review the sources of gravitational waves that are likely to play an important role in observations by first- and second-generation interferometers, including the astrophysical information that will come from these observations. The review covers some 10 decades of gravitational wave frequency, from the high-frequency normal modes of neutron stars down to the lowest frequencies observable from space. The discussion of sources includes recent developments regarding binary black holes, spinning neutron stars, and the stochastic background.Comment: 29 pages, 2 figures, as submitted for special millenium issue of Classical and Quantum Gravit

New weapons in the toad toolkit: A review of methods to control and mitigate the biodiversity impacts of invasive cane toads (rhinella marina)

© 2017 by The University of Chicago Press. All rights reserved. Our best hope of developing innovative methods to combat invasive species is likely to come from the study of high-profile invaders that have attracted intensive research not only into control, but also basic biology. Here we illustrate that point by reviewing current thinking about novel ways to control one of the world’s most well-studied invasions: that of the cane toad in Australia. Recently developed methods for population suppression include more effective traps based on the toad’s acoustic and pheromonal biology. New tools for containing spread include surveillance technologies (e.g., eDNA sampling and automated call detectors), as well as landscape-level barriers that exploit the toad’s vulnerability to desiccation— a strategy that could be significantly enhanced through the introduction of sedentary, rangecore genotypes ahead of the invasion front. New methods to reduce the ecological impacts of toads include conditioned taste aversion in free-ranging predators, gene banking, and targeted gene flow. Lastly, recent advances in gene editing and gene drive technology hold the promise of modifying toad phenotypes in ways that may facilitate control or buffer impact. Synergies between these approaches hold great promise for novel and more effective means to combat the toad invasion and its consequent impacts on biodiversity

Applications of Bayesian Networks as Decision Support Tools for Water Resource Management under Climate Change and Socio-Economic Stressors: A Critical Appraisal

Bayesian networks (BNs) are widely implemented as graphical decision support tools which use probability inferences to generate “what if?” and “which is best?” analyses of potential management options for water resource management, under climate change and socio-economic stressors. This paper presents a systematic quantitative literature review of applications of BNs for decision support in water resource management. The review quantifies to what extent different types of data (quantitative and/or qualitative) are used, to what extent optimization-based and/or scenario-based approaches are adopted for decision support, and to what extent different categories of adaptation measures are evaluated. Most reviewed publications applied scenario-based approaches (68%) to evaluate the performance of management measures, whilst relatively few studies (18%) applied optimization-based approaches to optimize management measures. Institutional and social measures (62%) were mostly applied to the management of water-related concerns, followed by technological and engineered measures (47%), and ecosystem-based measures (37%). There was no significant difference in the use of quantitative and/or qualitative data across different decision support approaches (p = 0.54), or in the evaluation of different categories of management measures (p = 0.25). However, there was significant dependence (p = 0.076) between the types of management measure(s) evaluated, and the decision support approaches used for that evaluation. The potential and limitations of BN applications as decision support systems are discussed along with solutions and recommendations, thereby further facilitating the application of this promising decision support tool for future research priorities and challenges surrounding uncertain and complex water resource systems driven by multiple interactions amongst climatic and non-climatic changes. View Full-Tex

Improving the health and welfare of people who live in slums

Summary In the first paper in this Series we assessed theoretical and empirical evidence and concluded that the health of people living in slums is a function not only of poverty but of intimately shared physical and social environments. In this paper we extend the theory of so-called neighbourhood effects. Slums offer high returns on investment because beneficial effects are shared across many people in densely populated neighbourhoods. Neighbourhood effects also help explain how and why the benefits of interventions vary between slum and non-slum spaces and between slums. We build on this spatial concept of slums to argue that, in all low-income and-middle-income countries, census tracts should henceforth be designated slum or non-slum both to inform local policy and as the basis for research surveys that build on censuses. We argue that slum health should be promoted as a topic of enquiry alongside poverty and health

Processing and Transmission of Information

Contains reports on seven research projects

THE ROLE OF INTERDEPENDENCE IN THE MICRO-FOUNDATIONS OF ORGANIZATION DESIGN: TASK, GOAL, AND KNOWLEDGE INTERDEPENDENCE

Interdependence is a core concept in organization design, yet one that has remained consistently understudied. Current notions of interdependence remain rooted in seminal works, produced at a time when managers’ near-perfect understanding of the task at hand drove the organization design process. In this context, task interdependence was rightly assumed to be exogenously determined by characteristics of the work and the technology. We no longer live in that world, yet our view of interdependence has remained exceedingly task-centric and our treatment of interdependence overly deterministic. As organizations face increasingly unpredictable workstreams and workers co-design the organization alongside managers, our field requires a more comprehensive toolbox that incorporates aspects of agent-based interdependence. In this paper, we synthesize research in organization design, organizational behavior, and other related literatures to examine three types of interdependence that characterize organizations’ workflows: task, goal, and knowledge interdependence. We offer clear definitions for each construct, analyze how each arises endogenously in the design process, explore their interrelations, and pose questions to guide future research