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European Health Risk Assessment Network on Electromagnetic Fields Exposure |
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D3 – Report on the analysis of risks associated to exposure to EMF: in vitro and in vivo (animals) studies |
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2010 |
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EFHRAN |
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IT'IS @ kuster @ |
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53 |
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Schuderer, J; Oesch, W.; Felber, N.; Spät, D.; Kuster, N. |
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In vitro exposure apparatus for ELF magnetic fields |
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2004 |
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Bioelectromagnetics |
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Bioelectromagnetics |
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25 |
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8 |
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582-591 |
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For in vitro studies on the effect of extremely low frequency (ELF) magnetic field exposures in different laboratories, a programmable, high precision exposure system enabling blinded exposures has been developed and fully characterized. It is based on two shielded 4 coil systems that fit inside a commercial incubator. The volume of uniform B field exposure with 1% field tolerance is 50% larger compared to a Merrit 4 coil system with the same coil volume. The uncertainties for the applied magnetic fields have been specified to be less than 4%. The computer controlled apparatus allows signal waveforms that are composed of several harmonics, blind protocols, monitoring of exposure and environmental conditions and the application of B fields up to 3.6 mT root-mean-square amplitude. Sources of artifacts have been characterized: sham isolation >43 dB, parasitic incident E fields <1 V/m, no recognizable temperature differences in the media for exposure or sham state, and vibrations of the mechanically decoupled dish holder <0.1 m/s2 (= 0.01 g), which is only twice the sham acceleration background level produced by the incubator and fan vibrations. Bioelectromagnetics 25:582–591, 2004. © 2004 Wiley-Liss, Inc. |
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0197-8462 |
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IT'IS @ kuster @ |
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22 |
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Kuster, N. |
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Comments on the Brief Communication “Security considerations in blinded exposure experiments using electromagnetic waves†by Christian Wolf |
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2008 |
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Bioelectromagnetics |
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Bioelectromagnetics |
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29 |
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8 |
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660-661 |
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IT'IS @ kuster @ |
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25 |
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Greenland, S. |
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Multiple-bias modelling for analysis of observational data (with discussion) |
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2005 |
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Journal of the Royal Statistical Society: Series A (Statistics in Society) |
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J Royal Statistical Soc A |
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168 |
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2 |
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267-306 |
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Conventional analytic results do not reflect any source of uncertainty other than random error, and as a result readers must rely on informal judgments regarding the effect of possible biases. When standard errors are small these judgments often fail to capture sources of uncertainty and their interactions adequately. Multiple-bias models provide alternatives that allow one systematically to integrate major sources of uncertainty, and thus to provide better input to research planning and policy analysis. Typically, the bias parameters in the model are not identified by the analysis data and so the results depend completely on priors for those parameters. A Bayesian analysis is then natural, but several alternatives based on sensitivity analysis have appeared in the risk assessment and epidemiologic literature. Under some circumstances these methods approximate a Bayesian analysis and can be modified to do so even better. These points are illustrated with a pooled analysis of case–control studies of residential magnetic field exposure and childhood leukaemia, which highlights the diminishing value of conventional studies conducted after the early 1990s. It is argued that multiple-bias modelling should become part of the core training of anyone who will be entrusted with the analysis of observational data, and should become standard procedure when random error is not the only important source of uncertainty (as in meta-analysis and pooled analysis). |
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0964-1998 |
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WP2 Exposure measurements |
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CBM.UAM @ ccobaleda @ |
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57 |
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Bernstein, B.E.; Meissner, A.; Lander, E.S. |
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The mammalian epigenome |
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2007 |
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Cell |
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128 |
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4 |
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669-681 |
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Animals; Chromatin Assembly and Disassembly/*genetics; CpG Islands/genetics; DNA Methylation; Epigenesis, Genetic/*genetics; Gene Expression Regulation, Developmental/genetics; Genomic Instability/*genetics; Histones/genetics/metabolism; Humans; Mammals/*genetics |
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Chemical modifications to DNA and histone proteins form a complex regulatory network that modulates chromatin structure and genome function. The epigenome refers to the complete description of these potentially heritable changes across the genome. The composition of the epigenome within a given cell is a function of genetic determinants, lineage, and environment. With the sequencing of the human genome completed, investigators now seek a comprehensive view of the epigenetic changes that determine how genetic information is made manifest across an incredibly varied background of developmental stages, tissue types, and disease states. Here we review current research efforts, with an emphasis on large-scale studies, emerging technologies, and challenges ahead. |
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0092-8674 |
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WP5 In vitro |
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PMID: 17320505 |
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UNIBAS @ david.schuermann @ Bernstein2007 |
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70 |
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