Poly[di-mu(3)-chloro-mu(2)-trans-1,2-di-4-pyridylethylene-dicopper(I)]: a two-dimensional organic-inorganic hybrid constructed from linear CuCl clusters and bridging ligands

The structure of the title compound, [Cu2Cl2(C12H10N2)](n), contains infinite CuCl staircase-like chains, which lie about inversion centres. The trans-1,2-di-4-pyrid-ylethyl-ene mol-ecules also lie about inversion centres and connect the CuCl chains through Cu-N coordination bonds into a two-dimensional organic-inorganic hybrid network. The planar sheets are stacked along the c axis and associated through weak C-H center dot center dot center dot Cl inter-actions. The results show a reliable structural motif with controllable separation of the CuCl chains by variation of the length of the ligand.

ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide.

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others(1), ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.

Mighty small: Observing and modeling individual microbes becomes big science

Progress in microbiology has always been driven by technological advances, ever since Antonie van Leeuwenhoek discovered bacteria by making an improved compound microscope. However, until very recently we have not been able to identify microbes and record their mostly invisible activities, such as nutrient consumption or toxin production on the level of the single cell, not even in the laboratory. This is now changing with the rapid rise of exciting new technologies for single-cell microbiology (1, 2), which enable microbiologists to do what plant and animal ecologists have been doing for a long time: observe who does what, when, where, and next to whom. Single cells taken from the environment can be identified and even their genomes sequenced. Ex situ, their size, elemental, and biochemical composition, as well as other characteristics can be measured with high-throughput and cells sorted accordingly. Even better, individual microbes can be observed in situ with a range of novel microscopic and spectroscopic methods, enabling localization, identification, or functional characterization of cells in a natural sample, combined with detecting uptake of labeled compounds. Alternatively, they can be placed into fabricated microfluidic environments, where they can be positioned, exposed to stimuli, monitored, and their interactions controlled “in microfluido.” By introducing genetically engineered reporter cells into a fabricated landscape or a microcosm taken from nature, their reproductive success or activity can be followed, or their sensing of their local environment recorded.

Hydrogen bonding and collective proton modes in clusters and periodic layers of squaric acid: A density functional study

Hydrogen bonding in clusters and extended layers of squaric acid molecules has been investigated by density functional computations. Equilibrium geometries, harmonic vibrational frequencies, and energy barriers for proton transfer along hydrogen bonds have been determined using the Car-Parrinello method. The results provide crucial parameters for a first principles modeling of the potential energy surface, and highlight the role of collective modes in the low-energy proton dynamics. The importance of quantum effects in condensed squaric acid systems has been investigated, and shown to be negligible for the lowest-energy collective proton modes. This information provides a quantitative basis for improved atomistic models of the order-disorder and displacive transitions undergone by squaric acid crystals as a function of temperature and pressure. (C) 2001 American Institute of Physics.

Oily fish consumption, dietary docosahexaenoic acid and eicosapentaenoic acid intakes, and associations with neovascular age-related macular degeneration

Background: Fish intake, the major source of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), may reduce the risk of age-related macular degeneration (AMD). Objective: We investigated the association of oily fish and dietary DHA and EPA with neovascular AMD (NV-AMD). Design: Participants aged =65 y in the cross-sectional population-based EUREYE study underwent fundus photography and were interviewed by using a food-frequency questionnaire. Fundus images were graded by the International Classification System for Age Related Maculopathy. Questionnaire data were converted to nutrient intakes with the use of food-composition tables. Survey logistic regression was used to calculate odds ratios (ORs) and 95% CIs of energy-adjusted quartiles of EPA or DHA with NV-AMD, taking into account potential confounders. Results: Dietary intake data and fundus images were available for 105 cases with NV-AMD and for 2170 controls without any features of early or late AMD. Eating oily fish at least once per week compared with less than once per week was associated with a halving of the odds of NV-AMD (OR = 0.47; 95% CI: 0.33, 0.68; P = 0.002). Compared with the lowest quartile, there was a significant trend for decreased odds with increasing quartiles of either DHA or EPA. ORs in the highest quartiles were 0.32 (95% CI: 0.12, 0.87; P = 0.03) for DHA and 0.29 (95% CI: 0.11, 0.73; P = 0.02) for EPA. Conclusions: Eating oily fish at least once per week compared with less than once per week was associated with a halving of the OR for NV-AMD. © 2008 American Society for Nutrition.

Facile in situ synthesis of nanofluids based on ionic liquids and copper oxide clusters and nanoparticles

Two stable nanofluids comprising of mixed valent copper(_I,_II) oxide clusters (<1 nm) suspended in 1-butyl-3-methylimidazolium acetate, [C(₄)mim][OAc], and copper(_II) oxide nanoparticles (<50 nm) suspended in trioctyl(dodecyl) phosphonium acetate, [P-₈₈₈₁₂][OAc], were synthesised in a facile one-pot reaction from solutions of copper(_II) acetate hydrate in the corresponding ionic liquids. Formation of the nanostructures was studied using ¹³C NMR spectroscopy and differential scanning calorimetry (DSC). From a solution of Cu(OAc)₂ in 1-ethyl-3-methylimidazolium acetate, [C₂mim][OAc], crystals were obtained that revealed the structure of [C₂mim][Cu₃(OAc)₅(OH)₂(H₂O)]center dot H₂O, indicating the formation of copper hydroxo-clusters in the course of the reaction. Synthesised nanostructures were studied using transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS). Physical properties of the prepared IL-nanofluids were examined using IR and UV-VIS spectroscopy, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and densitometry. 

Is Use of Optional Attributes and Associations in Conceptual Modeling Always Problematic? Theory and Empirical Tests

Prior research has argued that use of optional properties in conceptual models results in loss of information about the semantics of the domains represented by the models. Empirical research undertaken to date supports this argument. Nevertheless, no systematic analysis has been done of whether use of optional properties is always problematic. Furthermore, prior empirical research might have deliberately or unwittingly employed models where use of optionality always causes problems. Accordingly, we examine analytically whether use of optional properties is always problematic. We employ our analytical results to inform the design of an experiment where we systematically examined the impact of optionality on users’ ability to understand domains represented by different types of conceptual models. We found evidence that use of optionality undermines users’ ability to understand the domain represented by a model but that this effect weakens when use of mandatory properties to replace optional properties leads to more-complex models.