Stochastic oscillations of adaptive networks: application to epidemic modelling

Adaptive-network models are typically studied using deterministic differential equations which approximately describe their dynamics. In simulations, however, the discrete nature of the network gives rise to intrinsic noise which can radically alter the system's behaviour. In this article we develop a method to predict the effects of stochasticity in adaptive networks by making use of a pair-based proxy model. The technique is developed in the context of an epidemiological model of a disease spreading over an adaptive network of infectious contact. Our analysis reveals that in this model the structure of the network exhibits stochastic oscillations in response to fluctuations in the disease dynamic.Comment: 11 pages, 4 figure

Growth-induced breaking and unbreaking of ergodicity in fully-connected spin systems

Two canonical models of statistical mechanics, the fully-connected voter and Glauber-Ising models, are modified to incorporate growth via the addition or replication of spins. The resulting behaviour is examined in a regime where the timescale of expansion cannot be separated from that of the internal dynamics. Depending on the model specification, growth radically alters the long-time dynamical behaviour by breaking or unbreaking ergodicity.Comment: 10 pages, 3 figures, 1 tabl

SKU classification: A literature review and conceptual framework

Purpose - Stock keeping unit (SKU) classifications are widely used in the field of production and operations management. Although many theoretical and practical examples of classifications exist, there are no overviews of the current literature, and general guidelines are lacking with respect to method selection for classifying SKUs. The purpose of this paper is to systematically synthesise the earlier work in this area, and to conceptualise and discuss the factors that influence the choice of a specific SKU classification. Design/methodology/approach - The paper structurally reviews existing contributions and synthesises these into a conceptual framework for SKU classification. Findings - How SKUs are classified depends on the classification aim, the context and the method that is chosen. In total, three main production and operations management aims were found: inventory management, forecasting and production strategy. Within the method three decisions are identified to come to a classification: the characteristics, the classification technique and the operationalisation of the classes. Research limitations/implications - Drawing on the literature survey, the authors conclude with a conceptual framework describing the factors that influence SKU classification. Further research could use this framework to develop guidelines for real-life applications. Practical implications Examples from a variety of industries and general directions are provided which managers could use to develop their own SKU classification. Originality/value - The paper aims to advance the literature on SKU classification from the level of individual examples to a conceptual level and provides directions on how to develop a SKU classification

Therapeutic efficacy of AAV-mediated restoration of PKP2 in arrhythmogenic cardiomyopathy

Arrhythmogenic cardiomyopathy is a severe cardiac disorder characterized by lethal arrhythmias and sudden cardiac death, with currently no effective treatment. Plakophilin 2 (PKP2) is the most frequently affected gene. Here we show that adeno-associated virus (AAV)-mediated delivery of PKP2 in PKP2 c.2013delC/WT induced pluripotent stem cell-derived cardiomyocytes restored not only cardiac PKP2 levels but also the levels of other junctional proteins, found to be decreased in response to the mutation. PKP2 restoration improved sodium conduction, indicating rescue of the arrhythmic substrate in PKP2 mutant induced pluripotent stem cell-derived cardiomyocytes. Additionally, it enhanced contractile function and normalized contraction kinetics in PKP2 mutant engineered human myocardium. Recovery of desmosomal integrity and cardiac function was corroborated in vivo, by treating heterozygous Pkp2 c.1755delA knock-in mice. Long-term treatment with AAV9–PKP2 prevented cardiac dysfunction in 12-month-old Pkp2 c.1755delA/WT mice, without affecting wild-type mice. These findings encourage clinical exploration of PKP2 gene therapy for patients with PKP2 haploinsufficiency

A Fluctuation-Driven Mechanism for Slow Decision Processes in Reverberant Networks

The spike activity of cells in some cortical areas has been found to be correlated with reaction times and behavioral responses during two-choice decision tasks. These experimental findings have motivated the study of biologically plausible winner-take-all network models, in which strong recurrent excitation and feedback inhibition allow the network to form a categorical choice upon stimulation. Choice formation corresponds in these models to the transition from the spontaneous state of the network to a state where neurons selective for one of the choices fire at a high rate and inhibit the activity of the other neurons. This transition has been traditionally induced by an increase in the external input that destabilizes the spontaneous state of the network and forces its relaxation to a decision state. Here we explore a different mechanism by which the system can undergo such transitions while keeping the spontaneous state stable, based on an escape induced by finite-size noise from the spontaneous state. This decision mechanism naturally arises for low stimulus strengths and leads to exponentially distributed decision times when the amount of noise in the system is small. Furthermore, we show using numerical simulations that mean decision times follow in this regime an exponential dependence on the amplitude of noise. The escape mechanism provides thus a dynamical basis for the wide range and variability of decision times observed experimentally

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust