EuReCa ONE—27 Nations, ONE Europe, ONE Registry A prospective one month analysis of out-of-hospital cardiac arrest outcomes in 27 countries in Europe

AbstractIntroductionThe aim of the EuReCa ONE study was to determine the incidence, process, and outcome for out of hospital cardiac arrest (OHCA) throughout Europe.MethodsThis was an international, prospective, multi-centre one-month study. Patients who suffered an OHCA during October 2014 who were attended and/or treated by an Emergency Medical Service (EMS) were eligible for inclusion in the study. Data were extracted from national, regional or local registries.ResultsData on 10,682 confirmed OHCAs from 248 regions in 27 countries, covering an estimated population of 174 million. In 7146 (66%) cases, CPR was started by a bystander or by the EMS. The incidence of CPR attempts ranged from 19.0 to 104.0 per 100,000 population per year. 1735 had ROSC on arrival at hospital (25.2%), Overall, 662/6414 (10.3%) in all cases with CPR attempted survived for at least 30 days or to hospital discharge.ConclusionThe results of EuReCa ONE highlight that OHCA is still a major public health problem accounting for a substantial number of deaths in Europe.EuReCa ONE very clearly demonstrates marked differences in the processes for data collection and reported outcomes following OHCA all over Europe. Using these data and analyses, different countries, regions, systems, and concepts can benchmark themselves and may learn from each other to further improve survival following one of our major health care events

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes

Optimal Heating Strategies for a Convection Oven

In this study classical control theory is applied to a heat conduction model with convective boundary conditions. Optimal heating strategies are obtained through solution of an associated algebraic Riccati equation for a finite horizon linear quadratic regulator (LQR). The large dimensional system models, obtained after a Galerkin approximation of the original heat-conduction equations, describe the dynamics of the nodal temperatures driven by a forced convection boundary condition. The models are reduced using optimal Hankel minimum degree (OHMD) reduction. Optimal control histories are obtained for the reduced model and applied to the `full-scale' model. Performance of the regulator for various weighting matrices are compared and evaluated in two case studies, namely the heating of a cylindrically shaped container of mashed potato, and a container of ready-made lasagna. The approach taken here is geometry independent and closed loop meaning that the input is driven by temperature through a feedback mechanism which includes an optimal feedback gain matrix, which is calculated `off-line' through the backwards solution of an associated algebraic Riccati equation. The results indicate a T type heating profile, including a final oscillating behaviour that fine-regulates the temperature to an almost uniform temperature of 100°C

Effect of harvest and delaying controlled atmosphere storage conditions on core breakdown incidence in 'conference' pears

A logistic regression model was built to describe the effect of picking time and the most relevant commercially applied storage factors on the incidence of core breakdown in pears (Pyrus communis L. cv. Conference). The statistical analysis showed that the probability of core breakdown depended on several variables in a more complicated way than assumed before. In general, more mature fruit, stored at lower O-2 and higher CO2 concentrations, at a higher temperature and for longer times are more susceptible to core breakdown. However, delaying the controlled atmosphere (CA) conditions for 21 days decreased the core breakdown incidence efficiently even for late-picked fruit. Together with a proper delay of CA, a sufficiently high O-2 concentration during CA was most important. The model was validated with data of 16 orchards gathered over five harvest seasons in two countries which gives it a wide validity range and a high practical relevance. (C) 2002 Silsoc Research Institute. Published by Elsevier Science Ltd. All rights reserved

Optimal Heating Strategies for a Convection Oven

In this study classical control theory is applied to a heat conduction model with convective boundary conditions. Optimal heating strategies are obtained through solution of an associated algebraic Riccati equation for a finite horizon linear quadratic regulator (LQR). The large dimensional system models, obtained after a Galerkin approximation of the original heat-conduction equations, describe the dynamics of the nodal temperatures driven by a forced convection boundary condition. The models are reduced using optimal Hankel minimum degree (OHMD) reduction. Optimal control histories are obtained for the reduced model and applied to the `full-scale' model. Performance of the regulator for various weighting matrices are compared and evaluated in two case studies, namely the heating of a cylindrically shaped container of mashed potato, and a container of ready-made lasagna. The approach taken here is geometry independent and closed loop meaning that the input is driven by temperature through a feedback mechanism which includes an optimal feedback gain matrix, which is calculated `off-line' through the backwards solution of an associated algebraic Riccati equation. The results indicate a T type heating profile, including a final oscillating behaviour that fine-regulates the temperature to an almost uniform temperature of 100°C

Virtual microstructural leaf tissue generation based on cell growth modeling

A cell growth algorithm for virtual leaf tissue generation is presented based on the biomechanics of plant cells in tissues. The algorithm can account for typical differences in epidermal layers, palisade mesophyll layer and spongy mesophyll layer which have characteristic differences in the shape of cells, arrangement of cells and void fractions present in each layer. The cell is considered as a closed thin walled structure, maintained in tension by turgor pressure. The cell walls are modelled as linear elastic elements which obey Hooke's law. A Voronoi tessellation was used to generate the initial topology of the cells in the spongy mesophyll layer. Then two layers of brick structured cells are added to the top of it to represent the palisade mesophyll and upper epidermis and a single layer is added at bottom of the Voronoi tessellation to represent the lower epidermal layer. Intercellular air spaces are generated by separating the Voronoi cells along the edges starting from where three Voronoi cells are in contact (schizogenous origin) and/or by deleting some of the Voronoi cells (lysigenous origin). Cell expansion then results from turgor pressure acting on the yielding cell wall material. To find the sequence of positions of each vertex and thus the shape of the tissue with time, a system of differential equations for the positions and velocities of each vertex is established and solved using the ordinary differential equation solver in MatLab. Statistical comparison of the cellular characteristics with 2D cross-sectional slices of real leaf tissue of tomato is excellent. The virtual tissues can be used to systematically study effects of leaf structure on water and gas exchange.</p

A variance propagation algorithm for stochastic heat and mass transfer problems in food processes

A variance propagation algorithm for stochastic coupled heat and mass transfer problems subjected to first order autoregressive random process boundary conditions was developed. The algorithm is based on the finite element formulation of Luikov's coupled heat and mass transfer equations and involves the numerical solution of coupled Lyapunov and Sylvester matrix differential equations. It offers a cheap alternative to the Monte Carlo method for the computation of the mean value and variance of the temperature and moisture content field. The algorithm is generally applicable and can easily be inserted in any existing finite element code. Also, it can be extended to other types of random processes. The algorithm was applied to analyse the drying of a soybean kernel. Simulation results show that random fluctuations of the process conditions may cause considerable variability of the temperature and the moisture content within the drying soybean kernel. This is an important feature to take into account for the design of a drying process, and for thermal food processes in genera