Translating biomonitoring data into risk management and policy implementation options for a European Network on Human Biomonitoring

<p>Abstract</p> <p>Background</p> <p>The "European Environment & Health Action Plan 2004–2010" originates from the concern of the European Commission on the well-being of individuals and the general population. Through this plan, the Commission has set the objectives to improve the information chain for a better understanding of the link between sources of pollution and health effects, to better identify existing knowledge gaps, and improve policy making and communication strategies. Human biomonitoring (HBM) has been included as one of the tools to achieve these objectives. As HBM directly measures the amount of a chemical substance in a person's body, taking into account often poorly understood processes such as bioaccumulation, excretion, metabolism and the integrative uptake variability through different exposure pathways, HBM data are much more relevant for risk assessment than extrapolations from chemical concentrations in soil, air, and water alone. However, HBM primarily is a stepping stone between environmental and health data, and the final aim should be an integrated and holistic systematic risk assessment paradigm where HBM serves as a pivotal point between environment and health, on the one hand leaning on environmental data to provide detailed information on the sources and pathways of pollutants that enter the human body, and on the other hand clarifying new and existing hypotheses on the relationship between environmental pollutants and the prevalence of diseases. With the large amount of data that is being gathered in the different national survey projects, and which is expected to become available in Europe in the near future through the expected European Pilot Project on HBM, a framework to optimize data interpretation from such survey projects may greatly enhance the usefulness of HBM data for risk managers and policy makers.</p> <p>Results</p> <p>This paper outlines an hierarchic approach, based on the stepwise formulation of 4 subsequent steps, that will eventually lead to the formulation of a variety of policy relevant risk reduction options.</p> <p>Conclusion</p> <p>Although the usefulness of this approach still needs to be tested, and potential fine-tuning of the procedure may be necessary, approaching the policy implications of HBM in an objective framework will prove to be essential.</p

Temporal Cliques Admit Sparse Spanners

Let G=(V,E) be an undirected graph on n vertices and lambda:E -> 2^{N} a mapping that assigns to every edge a non-empty set of positive integer labels. These labels can be seen as discrete times when the edge is present. Such a labeled graph {G}=(G,lambda) is said to be temporally connected if a path exists with non-decreasing times from every vertex to every other vertex. In a seminal paper, Kempe, Kleinberg, and Kumar (STOC 2000) asked whether, given such a temporal graph, a sparse subset of edges can always be found whose labels suffice to preserve temporal connectivity - a temporal spanner. Axiotis and Fotakis (ICALP 2016) answered negatively by exhibiting a family of Theta(n^2)-dense temporal graphs which admit no temporal spanner of density o(n^2). The natural question is then whether sparse temporal spanners always exist in some classes of dense graphs. In this paper, we answer this question affirmatively, by showing that if the underlying graph G is a complete graph, then one can always find temporal spanners of density O(n log n). The best known result for complete graphs so far was that spanners of density binom{n}{2}- floor[n/4] = O(n^2) always exist. Our result is the first positive answer as to the existence of o(n^2) sparse spanners in adversarial instances of temporal graphs since the original question by Kempe et al., focusing here on complete graphs. The proofs are constructive and directly adaptable as an algorithm

SECONIC : towards multi-compartmental models for ultrasonic brain stimulation by intramembrane cavitation

Objective. To design a computationally efficient model for ultrasonic neuromodulation (UNMOD) of morphologically realistic multi-compartmental neurons based on intramembrane cavitation.Approach. A Spatially Extended Neuronal Intramembrane Cavitation model that accurately predicts observed fast Charge Oscillations (SECONIC) is designed. A regular spiking cortical Hodgkin-Huxley type nanoscale neuron model of the bilayer sonophore and surrounding proteins is used. The accuracy and computational efficiency of SECONIC is compared with the Neuronal Intramembrane Cavitation Excitation (NICE) and multiScale Optimized model of Neuronal Intramembrane Cavitation (SONIC).Main results. Membrane charge redistribution between different compartments should be taken into account via fourier series analysis in an accurate multi-compartmental UNMOD-model. Approximating charge and voltage traces with the harmonic term and first two overtones results in reasonable goodness-of-fit, except for high ultrasonic pressure (adjusted R-squared >= 0.61). Taking into account the first eight overtones results in a very good fourier series fit (adjusted R-squared >= 0.96) up to 600 kPa. Next, the dependency of effective voltage and rate parameters on charge oscillations is investigated. The two-tone SECONIC-model is one to two orders of magnitude faster than the NICE-model and demonstrates accurate results for ultrasonic pressure up to 100 kPa.Significance. Up to now, the underlying mechanism of UNMOD is not well understood. Here, the extension of the bilayer sonophore model to spatially extended neurons via the design of a multi-compartmental UNMOD-model, will result in more detailed predictions that can be used to validate or falsify this tentative mechanism. Furthermore, a multi-compartmental model for UNMOD is required for neural engineering studies that couple finite difference time domain simulations with neuronal models. Here, we propose the SECONIC-model, extending the SONIC-model by taking into account charge redistribution between compartments

A High-Throughput Candida albicans Two-Hybrid System

We thank Nico Vangoethem for help with preparation of the figures and Ilse Palmans, Tom Adriany, and Selien Schots for technical assistance. Financial support was obtained from the Interuniversity Attraction Poles Programme initiated by the Belgian Science Policy Office (IAP P7/28) and by the KU Leuven Research Council (C14/17/063). C.D. acknowledges support from the French Government’s Investissement d’Avenir program (Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases, ANR-10-LABX-62-IBEID). C.A.M. and C.D. acknowledge support from the Wellcome Trust (088858/Z/09/Z). C.A.M. acknowledges support from the MRC Centre for Medical Mycology (MR/N006364/1) and the University of Aberdeen.Peer reviewedPublisher PD

Comparison between direct electrical and optogenetic subthalamic nucleus stimulation

Subthalamic nucleus deep brain stimulation is a treatment for Parkinson’s disease. In this study, a computational model of a plateau-potential generating subthalamic nucleus neuron (Otsuka-model) and a four-state ChR2(H134R) model (Williams-model) are combined, in order to compare electrical and optogenetic neuromodulation capabilities. The impact of the stimulation modality (optogenetic or electric) on firing rates, strength-duration curves and action potential shape is investigated. First, in contrast to electrical stimulation, mean instantaneous firing rates saturate for optical stimulation at intensities higher than 0.1 W/cm2. Second, rheobase and chronaxie are 175% and 9.6% larger in optogenetic stimulation compared to electrical stimulation, respectively. Third, action potential shape is not significantly impacted by the neurostimulation modality