The Shape and Scale of Galactic Rotation from Cepheid Kinematics

A catalog of Cepheid variables is used to probe the kinematics of the Galactic disk. Radial velocities are measured for eight distant Cepheids toward l = 300; these new Cepheids provide a particularly good constraint on the distance to the Galactic center, R_0. We model the disk with both an axisymmetric rotation curve and one with a weak elliptical component, and find evidence for an ellipticity of 0.043 +/- 0.016 near the Sun. Using these models, we derive R_0 = 7.66 +/- 0.32 kpc and v_circ = 237 +/- 12 km/s. The distance to the Galactic center agrees well with recent determinations from the distribution of RR Lyrae variables, and disfavors most models with large ellipticities at the solar orbit.Comment: 36 pages, LaTeX, 10 figure

The power spectra of CMB and density fluctuations seeded by local cosmic strings

We compute the power spectra in the cosmic microwave background and cold dark matter (CDM) fluctuations seeded by strings, using the largest string simulations performed so far to evaluate the two-point functions of their stress energy tensor. We find that local strings differ from global defects in that the scalar components of the stress-energy tensor dominate over vector and tensor components. This result has far reaching consequences. We find that cosmic strings exhibit a single Doppler peak of acceptable height at high $\ell$. They also seem to have a less severe bias problem than global defects, although the CDM power spectrum in the ``standard'' cosmology (flat geometry, zero cosmological constant, 5% baryonic component) is the wrong shape to fit large scale structure data

Aeroservoelastic Wind-Tunnel Test of the SUGAR Truss Braced Wing Wind-Tunnel Model

The Subsonic Ultra Green Aircraft Research (SUGAR) Truss-Braced Wing (TBW) aeroservoelastic (ASE) wind-tunnel test was conducted in the NASA Langley Transonic Dynamics Tunnel (TDT) and was completed in April, 2014. The primary goals of the test were to identify the open-loop flutter boundary and then demonstrate flutter suppression. A secondary goal was to demonstrate gust load alleviation (GLA). Open-loop flutter and limit cycle oscillation onset boundaries were identified for a range of Mach numbers and various angles of attack. Two sets of control laws were designed for the model and both sets of control laws were successful in suppressing flutter. Control laws optimized for GLA were not designed; however, the flutter suppression control laws were assessed using the TDT Airstream Oscillation System. This paper describes the experimental apparatus, procedures, and results of the TBW wind-tunnel test. Acquired system ID data used to generate ASE models is also discussed.2 study

Scaling and Small Scale Structure in Cosmic String Networks

We examine the scaling properties of an evolving network of strings in Minkowski spacetime and study the evolution of length scales in terms of a 3-scale model proposed by Austin, Copeland and Kibble (ACK). We find good qualitative and some quantitative agreement between the model and our simulations. We also investigate small-scale structure by altering the minimum allowed size for loop production E_c. Certain quantities depend significantly on this parameter: for example the scaling density can vary by a factor of two or more with increasing E_c. Small-scale structure as defined by ACK disappears if no restrictions are placed on loop production, and the fractal dimension of the string changes smoothly from 2 to 1 as the resolution scale is decreased. Loops are nearly all produced at the lattice cut-off. We suggest that the lattice cut-off should be interpreted as corresponding to the string width, and that in a real network loops are actually produced with this size. This leads to a radically different string scenario, with particle production rather than gravitational radiation being the dominant mode of energy dissipation. At the very least, a better understanding of the discretisation effects in all simulations of cosmic strings is called for.Comment: 22pp Plain LaTeX, 12 EPS figure

3D Multicolor Super-Resolution Imaging Offers Improved Accuracy in Neuron Tracing

The connectivity among neurons holds the key to understanding brain function. Mapping neural connectivity in brain circuits requires imaging techniques with high spatial resolution to facilitate neuron tracing and high molecular specificity to mark different cellular and molecular populations. Here, we tested a three-dimensional (3D), multicolor super-resolution imaging method, stochastic optical reconstruction microscopy (STORM), for tracing neural connectivity using cultured hippocampal neurons obtained from wild-type neonatal rat embryos as a model system. Using a membrane specific labeling approach that improves labeling density compared to cytoplasmic labeling, we imaged neural processes at 44 nm 2D and 116 nm 3D resolution as determined by considering both the localization precision of the fluorescent probes and the Nyquist criterion based on label density. Comparison with confocal images showed that, with the currently achieved resolution, we could distinguish and trace substantially more neuronal processes in the super-resolution images. The accuracy of tracing was further improved by using multicolor super-resolution imaging. The resolution obtained here was largely limited by the label density and not by the localization precision of the fluorescent probes. Therefore, higher image resolution, and thus higher tracing accuracy, can in principle be achieved by further improving the label density

Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large-scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose-response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large-scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker-specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.Peer reviewe

Genome-wide association study of eosinophilic granulomatosis with polyangiitis reveals genomic loci stratified by ANCA status

Eosinophilic granulomatosis with polyangiitis (EGPA) is a rare inflammatory disease of unknown cause. 30% of patients have anti-neutrophil cytoplasmic antibodies (ANCA) specific for myeloperoxidase (MPO). Here, we describe a genome-wide association study in 676 EGPA cases and 6809 controls, that identifies 4 EGPA-associated loci through conventional case-control analysis, and 4 additional associations through a conditional false discovery rate approach. Many variants are also associated with asthma and six are associated with eosinophil count in the general population. Through Mendelian randomisation, we show that a primary tendency to eosinophilia contributes to EGPA susceptibility. Stratification by ANCA reveals that EGPA comprises two genetically and clinically distinct syndromes. MPO+\u2009ANCA EGPA is an eosinophilic autoimmune disease sharing certain clinical features and an HLA-DQ association with MPO+\u2009ANCA-associated vasculitis, while ANCA-negative EGPA may instead have a mucosal/barrier dysfunction origin. Four candidate genes are targets of therapies in development, supporting their exploration in EGPA

Analysis of Combinatorial Regulation: Scaling of Partnerships between Regulators with the Number of Governed Targets

Through combinatorial regulation, regulators partner with each other to control common targets and this allows a small number of regulators to govern many targets. One interesting question is that given this combinatorial regulation, how does the number of regulators scale with the number of targets? Here, we address this question by building and analyzing co-regulation (co-transcription and co-phosphorylation) networks that describe partnerships between regulators controlling common genes. We carry out analyses across five diverse species: Escherichia coli to human. These reveal many properties of partnership networks, such as the absence of a classical power-law degree distribution despite the existence of nodes with many partners. We also find that the number of co-regulatory partnerships follows an exponential saturation curve in relation to the number of targets. (For E. coli and Bacillus subtilis, only the beginning linear part of this curve is evident due to arrangement of genes into operons.) To gain intuition into the saturation process, we relate the biological regulation to more commonplace social contexts where a small number of individuals can form an intricate web of connections on the internet. Indeed, we find that the size of partnership networks saturates even as the complexity of their output increases. We also present a variety of models to account for the saturation phenomenon. In particular, we develop a simple analytical model to show how new partnerships are acquired with an increasing number of target genes; with certain assumptions, it reproduces the observed saturation. Then, we build a more general simulation of network growth and find agreement with a wide range of real networks. Finally, we perform various down-sampling calculations on the observed data to illustrate the robustness of our conclusions

Pore confinement effects and stabilization of carbon nitride oligomers in macroporous silica for photocatalytic hydrogen production

An ordered macroporous host (mac-SiO2) has been used to prevent aggregation of layered photocatalysts based on carbon nitride. Using typical carbon nitride synthesis conditions, cyanamide was condensed at 550 °C in the presence and absence of mac-SiO2. Condensation in the absence of mac-SiO2 results in materials with structural characteristics consistent with the carbon nitride, melon, accompanied by ca. 2 wt% carbonization. For mac-SiO2 supported materials, condensation occurs with greater carbonization (ca. 6 wt%). On addition of 3 wt% Pt cocatalyst photocatalytic hydrogen production under visible light is found to be up to 10 times greater for the supported composites. Time-resolved photoluminescence spectroscopy shows that excited state relaxation is more rapid for the mac-SiO2 supported materials suggesting faster electron-hole recombination and that supported carbon nitride does not exhibit improved charge separation. CO2 temperature programmed desorption indicates that enhanced photoactivity of supported carbon nitride is attributable to an increased surface area compared to bulk carbon nitride and an increase in the concentration of weakly basic catalytic sites, consistent with carbon nitride oligomers