µTransparent insulating channels as components for miniaturized chemical separation Devices

Currently, miniaturized devices that apply electro osmotic pumping or electrophoretic separations are mostly constructed by etching small insulating channels for supply and separation on glass substrates. In principle, silicon is a superior construction material in terms of inertness and design flexibility. However, because of its semiconducting properties, the use in high voltage applications like the ones mentioned above is quite limited. In this paper, the use of μTransparent Insulating Channel (μTIC) technology is demonstrated as a standard procedure to manufacture miniaturized analytical separation devices. This technique, μchannels having extremely thin, transparent and insulating walls can be fabricated. An overview of the impact of this technology is given, showing the advantages of a fabrication technology that is as flexible as silicon technology for the fabrication of μTAS or “lab on a chip” devices. The following basic technology and control parameters will be highlighted. 1. Up to 100 μm wide rectangular channels 2. Bosses and leak-free connections to external μ fluidics. 3. Web-like structures for inlets/outlets>100 μm. 4. Implementation of conductivity electrodes 5. Good thermal dissipation properties of the thin walls 6. Control of the electro osmotic flow by a radial voltage

Specification of spatial relationships in directed graphs of cell signaling networks

Graph theory provides a useful and powerful tool for the analysis of cellular signaling networks. Intracellular components such as cytoplasmic signaling proteins, transcription factors and genes are connected by links, representing various types of chemical interactions that result in functional consequences. However, these graphs lack important information regarding the spatial distribution of cellular components. The ability of two cellular components to interact depends not only on their mutual chemical affinity but also on co-localization to the same subcellular region. Localization of components is often used as a regulatory mechanism to achieve specific effects in response to different receptor signals. Here we describe an approach for incorporating spatial distribution into graphs, and for the development of mixed graphs where links are specified by mutual chemical affinity as well as colocalization. We suggest that such mixed graphs will provide more accurate descriptions of functional cellular networks and their regulatory capabilities and aid in the development of large-scale predictive models of cellular behavior

New Approaches for ab initio Calculations of Molecules with Strong Electron Correlation

Reliable quantum chemical methods for the description of molecules with dense-lying frontier orbitals are needed in the context of many chemical compounds and reactions. Here, we review developments that led to our newcomputational toolbo x which implements the quantum chemical density matrix renormalization group in a second-generation algorithm. We present an overview of the different components of this toolbox.Comment: 19 pages, 1 tabl

Additive mixture effects of estrogenic chemicals in human cell-based assays can be influenced by inclusion of chemicals with differing effect profiles

Copyright @ 2012 The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and 85 reproduction in any medium, provided the original author and source are credited. The article was made available through the Brunel University Open Access Publishing Fund.A growing body of experimental evidence indicates that the in vitro effects of mixtures of estrogenic chemicals can be well predicted from the estrogenicity of their components by the concentration addition (CA) concept. However, some studies have observed small deviations from CA. Factors affecting the presence or observation of deviations could include: the type of chemical tested; number of mixture components; mixture design; and assay choice. We designed mixture experiments that address these factors, using mixtures with high numbers of components, chemicals from diverse chemical groups, assays with different in vitro endpoints and different mixture designs and ratios. Firstly, the effects of mixtures composed of up to 17 estrogenic chemicals were examined using estrogenicity assays with reporter-gene (ERLUX) and cell proliferation (ESCREEN) endpoints. Two mixture designs were used: 1) a 'balanced' design with components present in proportion to a common effect concentration (e.g. an EC(10)) and 2) a 'non-balanced' design with components in proportion to potential human tissue concentrations. Secondly, the individual and simultaneous ability of 16 potential modulator chemicals (each with minimal estrogenicity) to influence the assay outcome produced by a reference mixture of estrogenic chemicals was examined. Test chemicals included plasticizers, phthalates, metals, PCBs, phytoestrogens, PAHs, heterocyclic amines, antioxidants, UV filters, musks, PBDEs and parabens. In all the scenarios tested, the CA concept provided a good prediction of mixture effects. Modulation studies revealed that chemicals possessing minimal estrogenicity themselves could reduce (negatively modulate) the effect of a mixture of estrogenic chemicals. Whether the type of modulation we observed occurs in practice most likely depends on the chemical concentrations involved, and better information is required on likely human tissue concentrations of estrogens and of potential modulators. Successful prediction of the effects of diverse chemical combinations might be more likely if chemical profiling included consideration of effect modulation.This study is funded by the United Kingdom Food Standards Agency (Contract Number T01045)

Chemical origin of the Venusian clouds Final report

Chemical analysis of cloud components in upper atmosphere of Venu

Chemical-potential route for multicomponent fluids

The chemical potentials of multicomponent fluids are derived in terms of the pair correlation functions for arbitrary number of components, interaction potentials, and dimensionality. The formally exact result is particularized to hard-sphere mixtures with zero or positive nonadditivity. As a simple application, the chemical potentials of three-dimensional additive hard-sphere mixtures are derived from the Percus-Yevick theory and the associated equation of state is obtained. This Percus-Yevick chemical-route equation of state is shown to be more accurate than the virial equation of state. An interpolation between the chemical-potential and compressibility routes exhibits a better performance than the well-known Boubl\'ik-Mansoori-Carnahan-Starling-Leland equation of state.Comment: 9 pages, 1 figure; v2: minor change