Grouping of endocrine disrupting chemicals for mixture risk assessment – Evidence from a rat study

Exposure to mixtures of endocrine disrupting chemicals may contribute to the rising incidence of hormone-related diseases in humans. Real-life mixtures are complex, comprised of chemicals with mixed modes of action, and essential knowledge is often lacking on how to group such chemicals into cumulative assessment groups, which is an essential prerequisite to conduct a chemical mixture risk assessment. We investigated if mixtures of chemicals with diverse endocrine modes of action can cause mixture effects on hormone sensitive endpoints in developing and adult rat offspring after perinatal exposure. Wistar rats were exposed during pregnancy and lactation simultaneously to either bisphenol A and butylparaben (Emix), diethylhexyl phthalate and procymidone (Amix), or a mixture of all four substances (Totalmix). In male offspring, the anogenital distance was significantly reduced and nipple retention increased in animals exposed to Amix and Totalmix, and the mixture effects were well approximated by the dose addition model. The combination of Amix and Emix responded with more marked changes on these and other endocrine-sensitive endpoints than each binary mixture on its own. Sperm counts were reduced by all exposures. These experimental outcomes suggest that the grouping of chemicals for mixture risk assessment should be based on common health outcomes rather than only similar modes or mechanisms of action. Mechanistic-based approaches such as the concept of Adverse Outcome Pathway (AOP) can provide important guidance if both the information on shared target tissues and the information on shared mode/mechanism of action are taken into account.Danish Environmental Protection Agency, Denmar

Production and reliability oriented SOFC cell and stack design

The paper presents an innovative development methodology for a production and reliability oriented SOFC cell and stack design aiming at improving the stacks robustness, manufacturability, efficiency and cost. Multi-physics models allowed a probabilistic approach to consider statistical variations in production, material and operating parameters for the optimization phase. A methodology for 3D description of spatial distribution of material properties based on a random field models was developed and validated by experiments. Homogenized material models on multiple levels of the SOFC stack were established. The probabilistic models were related to the experimentally obtained properties of base materials to establish a statistical relationship between the material properties and the most relevant load effects. Software algorithms for meta models that allow the detection of relationships between input and output parameters and to perform a sensitivity analysis were developed and implemented. The capabilities of the methodology is illustrated on two practical cases

The Cyprinodon variegatus genome reveals gene expression changes underlying differences in skull morphology among closely related species

Genes in durophage intersection set at 15 dpf. This is a comma separated table of the genes in the 15 dpf durophage intersection set. Given are edgeR results for each pairwise comparison. Columns indicating whether a gene is included in the intersection set at a threshold of 1.5 or 2 fold are provided. (CSV 13 kb

Continuum scale modelling and complementary experimentation of solid oxide cells

Solid oxide cells are an exciting technology for energy conversion. Fuel cells, based on solid oxide technology, convert hydrogen or hydrogen-rich fuels into electrical energy, with potential applications in stationary power generation. Conversely, solid oxide electrolysers convert electricity into chemical energy, thereby offering the potential to store energy from transient resources, such as wind turbines and other renewable technologies. For solid oxide cells to displace conventional energy conversion devices in the marketplace, reliability must be improved, product lifecycles extended, and unit costs reduced. Mathematical models can provide qualitative and quantitative insight into physical phenomena and performance, over a range of length and time scales. The purpose of this paper is to provide the reader with a summary of the state-of-the art of solid oxide cell models. These range from: simple methods based on lumped parameters with little or no kinetics to detailed, time-dependent, three-dimensional solutions for electric field potentials, complex chemical kinetics and fully-comprehensive equations of motion based on effective transport properties. Many mathematical models have, in the past, been based on inaccurate property values obtained from the literature, as well as over-simplistic schemes to compute effective values. It is important to be aware of the underlying experimental methods available to parameterise mathematical models, as well as validate results. In this article, state-of-the-art techniques for measuring kinetic, electric and transport properties are also described. Methods such as electrochemical impedance spectroscopy allow for fundamental physicochemical parameters to be obtained. In addition, effective properties may be obtained using micro-scale computer simulations based on digital reconstruction obtained from X-ray tomography/focussed ion beam scanning electron microscopy, as well as percolation theory. The cornerstone of model validation, namely the polarisation or current-voltage diagram, provides necessary, but insufficient information to substantiate the reliability of detailed model calculations. The results of physical experiments which precisely mimic the details of model conditions are scarce, and it is fair to say there is a gap between the two activities. The purpose of this review is to introduce the reader to the current state-of-the art of solid oxide analysis techniques, in a tutorial fashion, not only numerical and but also experimental, and to emphasise the cross-linkages between techniques