Comparison of 20nm silver nanoparticles synthesized with and without a gold core: Structure, dissolution in cell culture media, and biological impact on macrophages

Widespread use of silver nanoparticles raises questions of environmental and biological impact. Many synthesis approaches are used to produce pure silver and silver-shell gold-core particles optimized for specific applications. Since both nanoparticles and silver dissolved from the particles may impact the biological response, it is important to understand the physicochemical characteristics along with the biological impact of nanoparticles produced by different processes. The authors have examined the structure, dissolution, and impact of particle exposure to macrophage cells of two 20 nm silver particles synthesized in different ways, which have different internal structures. The structures were examined by electron microscopy and dissolution measured in Rosewell Park Memorial Institute media with 10% fetal bovine serum. Cytotoxicity and oxidative stress were used to measure biological impact on RAW 264.7 macrophage cells. The particles were polycrystalline, but 20 nm particles grown on gold seed particles had smaller crystallite size with many high-energy grain boundaries and defects, and an apparent higher solubility than 20 nm pure silver particles. Greater oxidative stress and cytotoxicity were observed for 20 nm particles containing the Au core than for 20 nm pure silver particles. A simple dissolution model described the time variation of particle size and dissolved silver for particle loadings larger than 9 μg/ml for the 24-h period characteristic of many in-vitro studies

An implementation of synthetic generation of wind data series

Wind power fluctuation is a major concern of large scale wind power grid integration. To test methods proposed for wind power grid integration, a large amount of wind data with time series are necessary and will be helpful to improve the methods. Meanwhile, due to the short operation history of most wind farms as well as limitations of data collections, the data obtained from wind farms could not satisfy the needs of data analysis. Consequently, synthetic generation of wind data series could be one of the effective solutions for this issue. In this paper, a method is presented for generating wind data series using Markov chain. Due to the high order Markov chain, the possibility matrix designed for a wind farm could cost a lot of memory, which is a problem with current computer technologies. Dynamic list will be introduced in this paper to reduce the memory required. Communication errors are un-avoidable on long way signal transmission between the control centre and wind farms. Missing of data always happens in the historical wind data series. Using these data to generate wind data series may result in some mistakes when searching related elements in the probability matrix. An adaptive method will be applied in this paper to solve the problem. The proposed method will be verified using a set of one-year historical data. The results show that the method could generate wind data series in an effective way. © 2013 IEEE.published_or_final_versio

Altered distribution of mucosal NK cells during HIV infection.

The human gut mucosa is a major site of human immunodeficiency virus (HIV) infection and infection-associated pathogenesis. Increasing evidence shows that natural killer (NK) cells have an important role in control of HIV infection, but the mechanism(s) by which they mediate antiviral activity in the gut is unclear. Here, we show that two distinct subsets of NK cells exist in the gut, one localized to intraepithelial spaces (intraepithelial lymphocytes, IELs) and the other to the lamina propria (LP). The frequency of both subsets of NK cells was reduced in chronic infection, whereas IEL NK cells remained stable in spontaneous controllers with protective killer immunoglobulin-like receptor/human leukocyte antigen genotypes. Both IEL and LP NK cells were significantly expanded in immunological non-responsive patients, who incompletely recovered CD4+ T cells on highly active antiretroviral therapy (HAART). These data suggest that both IEL and LP NK cells may expand in the gut in an effort to compensate for compromised CD4+ T-cell recovery, but that only IEL NK cells may be involved in providing durable control of HIV in the gut

Heterotic analysis using AFLP markers reveals moderate correlations between specific combining ability and genetic distance in maize inbred lines

Heterotic breeding strategies in maize (Zea mays L.) can be improved if high specific combining abilities in hybrid performance and a DNA marker-based genetic distance in the inbred lines is correlated, and hence heterosis can reliably be predicted. In this study, the genetic diversity across 9 elite maize inbred lines was evaluated using the amplified fragment length polymorphism (AFLP) marker. The genetic distance (GD) between each of all possible inbred pairs and the specific combining ability (SCA) and heterosis in the F1 hybrids were evaluated in a diallel set of crosses (Griffing II). Nineteen AFLP primers produced 1019 reproducible bands of which 691 (67.81%) were polymorphic. This gave an average of 53.6 bands per primer combination. A matrix of Genetic similarity (GS) according to UPGMA clustered the inbred lines into 4 groups with a GD ranging from 0.2442 to 0.4093. The results indicated that GD was moderately correlated with grain yield (0.4096), mid-parent heterosis (MH) (0.3624), better-parent heterosis (BH) (0.3309) and SCA (0.4725). Although the AFLP markers have high polymorphisms and can be used to detect the genetic divergences, place maize inbred lines in different heterotic pools and identify the most positive SCAs and heterosis, they are still limited in fully predicting hybrid performance

Micro-beam Laue alignment of multi-reflection Bragg coherent diffraction imaging measurements

Multi-reflection Bragg coherent diffraction imaging has the potential to allow three-dimensional (3D) resolved measurements of the full lattice strain tensor in specific micro-crystals. Until now such measurements were hampered by the need for laborious, time-intensive alignment procedures. Here a different approach is demonstrated, using micro-beam Laue X-ray diffraction to first determine the lattice orientation of the micro-crystal. This information is then used to rapidly align coherent diffraction measurements of three or more reflections from the crystal. Based on these, 3D strain and stress fields in the crystal are successfully determined. This approach is demonstrated on a focused ion beam milled micro-crystal from which six reflections could be measured. Since information from more than three independent reflections is available, the reliability of the phases retrieved from the coherent diffraction data can be assessed. Our results show that rapid, reliable 3D coherent diffraction measurements of the full lattice strain tensor in specific micro-crystals are now feasible and can be successfully carried out even in heavily distorted samples

Trace doping of multiple elements enables stable battery cycling of LiCoO2 at 4.6 V

LiCoO2 is a dominant cathode material for lithium-ion (Li-ion) batteries due to its high volumetric energy density, which could potentially be further improved by charging to high voltages. However, practical adoption of high-voltage charging is hindered by LiCoO2’s structural instability at the deeply delithiated state and the associated safety concerns. Here, we achieve stable cycling of LiCoO2 at 4.6 V (versus Li/Li+) through trace Ti–Mg–Al co-doping. Using state-of-the-art synchrotron X-ray imaging and spectroscopic techniques, we report the incorporation of Mg and Al into the LiCoO2 lattice, which inhibits the undesired phase transition at voltages above 4.5 V. We also show that, even in trace amounts, Ti segregates significantly at grain boundaries and on the surface, modifying the microstructure of the particles while stabilizing the surface oxygen at high voltages. These dopants contribute through different mechanisms and synergistically promote the cycle stability of LiCoO2 at 4.6 V

Bio-Inspired Aggregation Control of Carbon Nanotubes for Ultra-Strong Composites

High performance nanocomposites require well dispersion and high alignment of the nanometer-sized components, at a high mass or volume fraction as well. However, the road towards such composite structure is severely hindered due to the easy aggregation of these nanometer-sized components. Here we demonstrate a big step to approach the ideal composite structure for carbon nanotube (CNT) where all the CNTs were highly packed, aligned, and unaggregated, with the impregnated polymers acting as interfacial adhesions and mortars to build up the composite structure. The strategy was based on a bio-inspired aggregation control to limit the CNT aggregation to be sub 20--50 nm, a dimension determined by the CNT growth. After being stretched with full structural relaxation in a multi-step way, the CNT/polymer (bismaleimide) composite yielded super-high tensile strengths up to 6.27--6.94 GPa, more than 100% higher than those of carbon fiber/epoxy composites, and toughnesses up to 117--192 MPa. We anticipate that the present study can be generalized for developing multifunctional and smart nanocomposites where all the surfaces of nanometer-sized components can take part in shear transfer of mechanical, thermal, and electrical signals

Searching for sterile neutrinos in ice

Oscillation interpretation of the results from the LSND, MiniBooNE and some other experiments requires existence of sterile neutrino with mass $\sim 1$ eV and mixing with the active neutrinos $|U_{\mu 0}|^2 \sim (0.02 - 0.04)$. It has been realized some time ago that existence of such a neutrino affects significantly the fluxes of atmospheric neutrinos in the TeV range which can be tested by the IceCube Neutrino Observatory. In view of the first IceCube data release we have revisited the oscillations of high energy atmospheric neutrinos in the presence of one sterile neutrino. Properties of the oscillation probabilities are studied in details for various mixing schemes both analytically and numerically. The energy spectra and angular distributions of the $\nu_\mu-$events have been computed for the simplest $\nu_s-$mass, and $\nu_s - \nu_\mu$ mixing schemes and confronted with the IceCube data. An illustrative statistical analysis of the present data shows that in the $\nu_s-$mass mixing case the sterile neutrinos with parameters required by LSND/MiniBooNE can be excluded at about $3\sigma$ level. The $\nu_s- \nu_\mu$ mixing scheme, however, can not be ruled out with currently available IceCube data.Comment: 41 pages, 16 figures. Accepted for publication in JHEP. Minor changes from the previous versio

Exploring neurotransmitters and their receptors for breast cancer prevention and treatment

While psychological factors have long been linked to breast cancer pathogenesis and outcomes, accumulating evidence is revealing how the nervous system contributes to breast cancer development, progression, and treatment resistance. Central to the psychological-neurological nexus are interactions between neurotransmitters and their receptors expressed on breast cancer cells and other types of cells in the tumor microenvironment, which activate various intracellular signaling pathways. Importantly, the manipulation of these interactions is emerging as a potential avenue for breast cancer prevention and treatment. However, an important caveat is that the same neurotransmitter can exert multiple and sometimes opposing effects. In addition, certain neurotransmitters can be produced and secreted by non-neuronal cells including breast cancer cells that similarly activate intracellular signaling upon binding to their receptors. In this review we dissect the evidence for the emerging paradigm linking neurotransmitters and their receptors with breast cancer. Foremost, we explore the intricacies of such neurotransmitter-receptor interactions, including those that impinge on other cellular components of the tumor microenvironment, such as endothelial cells and immune cells. Moreover, we discuss findings where clinical agents used to treat neurological and/or psychological disorders have exhibited preventive/therapeutic effects against breast cancer in either associative or pre-clinical studies. Further, we elaborate on the current progress to identify druggable components of the psychological-neurological nexus that can be exploited for the prevention and treatment of breast cancer as well as other tumor types. We also provide our perspectives regarding future challenges in this field where multidisciplinary cooperation is a paramount requirement

The relationship between EEG band power, cognitive processing and intelligence in school-age children

To investigate the differences in event-related potential parameters related to children’s intelligence and cognitive ability, 24 individuals from an experimental class of intellectually gifted children and 23 intellectually average children as the control group from a regular class were selected in the present study and the main neural mechanism pertaining tohigh intelligence was investigated. The electroencephalogram (EEG) was recorded and the relationship between different percentages of Delta, Theta, Alpha1, Alpha2, Beta1 and Beta2 and intelligence and cognitive ability were analyzed. The results suggested that Delta power activity in brighter individuals was more than that in normal individuals, and Alpha2 and Beta1 power activity in higher intelligence individuals were less than that in normalindividuals. In high ability group, Alpha1 was significantly correlated with visual search ability, and Theta band correlated with simple abstract matching significantly. While in the normal group, Delta band related significantly with short term memory abilities. Spectral EEG parameters could be regarded as neural bases for fast reaction and a good tool todiscriminate high intelligent children from the average.&nbsp