Although considerable progress has been made in dissecting the signaling pathways involved in the innate immune response, it is now apparent that this response can no longer be productively thought of in terms of simple linear pathways. InnateDB (www.innatedb.ca) has been developed to facilitate systems-level analyses that will provide better insight into the complex networks of pathways and interactions that govern the innate immune response. InnateDB is a publicly available, manually curated, integrative biology database of the human and mouse molecules, experimentally verified interactions and pathways involved in innate immunity, along with centralized annotation on the broader human and mouse interactomes. To date, more than 3500 innate immunity-relevant interactions have been contextually annotated through the review of 1000 plus publications. Integrated into InnateDB are novel bioinformatics resources, including network visualization software, pathway analysis, orthologous interaction network construction and the ability to overlay user-supplied gene expression data in an intuitively displayed molecular interaction network and pathway context, which will enable biologists without a computational background to explore their data in a more systems-oriented manner.

Tracer diffusivities (limiting mutual diffusion coefficients) of nonassociated aromatic compounds in n-hexane and cyclohexane have been measured at 298.2 K by Taylor's dispersion method. These new data, together with other diffusivities of nonassociated pseudoplanar solutes reported in the literature, are used to determine the separate effects of solute and solvent on tracer diffusion. The data show that for a given pseudoplanar solute diffusing in different solvents at 298.2 K, the tracer diffusivity is dependent not only on the fractional viscosity of the solvent but also on a function of the solvent's molar density, molecular mass, and free volume fraction. For different pseudoplanar aromatic solutes diffusing in a particular solvent at a constant temperature, there is a linear relationship between the reciprocal of the tracer diffusivity and the molecular volume of the solutes. The results are discussed in respect to relevant theories and experimental studies in the literature. An idealized relation, developed on the basis of the Einstein equation by incorporating the newly found solute and solvent dependences, is capable of describing a total of 176 diffusivities of nonassociated pseudoplanar solutes in various solvents at different temperatures to within an average error of ±2.8%. © 2013 AIP Publishing LLC. [http://dx

Limiting mutual diffusion coefficients of carbon tetrachloride in methanol and of benzene, toluene, naphthalene, and biphenyl in cyclohexane as well as in ethanol at different temperatures are reported. These new data, together with literature diffusivities for the same probe solutes and for solute mesitylene in various solvents, are utilized to elucidate the effect of solvent on diffusion. Here, the data are consistent with our recent findings [J. Chem. Phys. 2013, 138, 224503] on the effects of free volume fraction, molar density, molecular mass, and fractional viscosity of solvent on diffusion. The results in this study show that the relation developed previously for solvent dependence of diffusion of disc-shaped solutes is also valid for spherical carbon tetrachloride. It is further found in this investigation that diffusivities are weakly dependent on a solvent's dielectric constant. A relation that includes the dielectric effect of solvent is demonstrated to be capable of describing the solvent dependence of diffusion of the nonpolar solutes of different shapes and sizes in this work to within an average deviation of ±2.7%. Comparisons with other diffusion models reveal that the newly developed relation is more accurate for representing the effect of solvent on diffusion. An expression for Zwanzig's "effective hydrodynamic radius" is also presented.

Influence of solute-solvent coordination on the orientational relaxation of ion assemblies in polar solvents J. Chem. Phys. 136, 014501 (2012) Theoretical study of the aqueous solvation of HgCl2: Monte Carlo simulations using second-order Moller-Plessetderived flexible polarizable interaction potentials J. Chem. Phys. 136, 014502 (2012) A two-dimensional-reference interaction site model theory for solvation structure near solid-liquid interface J. Chem. Phys. 135, 244702 (2011) On the solvation structure of dimethylsulfoxide/water around the phosphatidylcholine head group in solution JCP: BioChem. Phys. 5, 12B611 (2011) Additional information on J. Chem. Phys. Diffusivities of pseudoplanar molecules at trace concentration in methanol have been measured at 298.2 K using Taylor's dispersion method. The data of the polar and nonpolar aromatic solutes are compared, and the effects due to solute-solvent interactions on diffusion, together with the solvation numbers, are determined. In this study, the effects are combined with the recently developed solute hydrogen-bond scales to unravel hydrogen bonding between solute and solvent. It is found that the degrees of association of the solutes with methanol decrease in the sequence hydroquinoneϾaromatic acidsϾphenolsϾaromatic aminesϾaprotic aromatic compounds. Except for o-nitrophenol, which is capable of intramolecular hydrogen bonding, all aromatic acids, phenols, and amines studied behave more as hydrogen-bond donor than acceptor in methanol. The present work also indicates that motions of associated molecules can be understood in terms of the molecular behavior of nonassociated solutes and the hydrogen-bond acidity/basicity of polar solutes.

BackgroundAn important consideration when analyzing both microarray and quantitative PCR expression data is the selection of appropriate genes as endogenous controls or reference genes. This step is especially critical when identifying genes differentially expressed between datasets. Moreover, reference genes suitable in one context (e.g. lung cancer) may not be suitable in another (e.g. breast cancer). Currently, the main approach to identify reference genes involves the mining of expression microarray data for highly expressed and relatively constant transcripts across a sample set. A caveat here is the requirement for transcript normalization prior to analysis, and measurements obtained are relative, not absolute. Alternatively, as sequencing-based technologies provide digital quantitative output, absolute quantification ensues, and reference gene identification becomes more accurate.MethodsSerial analysis of gene expression (SAGE) profiles of non-malignant and malignant lung samples were compared using a permutation test to identify the most stably expressed genes across all samples. Subsequently, the specificity of the reference genes was evaluated across multiple tissue types, their constancy of expression was assessed using quantitative RT-PCR (qPCR), and their impact on differential expression analysis of microarray data was evaluated.ResultsWe show that (i) conventional references genes such as ACTB and GAPDH are highly variable between cancerous and non-cancerous samples, (ii) reference genes identified for lung cancer do not perform well for other cancer types (breast and brain), (iii) reference genes identified through SAGE show low variability using qPCR in a different cohort of samples, and (iv) normalization of a lung cancer gene expression microarray dataset with or without our reference genes, yields different results for differential gene expression and subsequent analyses. Specifically, key established pathways in lung cancer exhibit higher statistical significance using a dataset normalized with our reference genes relative to normalization without using our reference genes.ConclusionsOur analyses found NDUFA1, RPL19, RAB5C, and RPS18 to occupy the top ranking positions among 15 suitable reference genes optimal for normalization of lung tissue expression data. Significantly, the approach used in this study can be applied to data generated using new generation sequencing platforms for the identification of reference genes optimal within diverse contexts.