A Regularized Graph Layout Framework for Dynamic Network Visualization

Many real-world networks, including social and information networks, are dynamic structures that evolve over time. Such dynamic networks are typically visualized using a sequence of static graph layouts. In addition to providing a visual representation of the network structure at each time step, the sequence should preserve the mental map between layouts of consecutive time steps to allow a human to interpret the temporal evolution of the network. In this paper, we propose a framework for dynamic network visualization in the on-line setting where only present and past graph snapshots are available to create the present layout. The proposed framework creates regularized graph layouts by augmenting the cost function of a static graph layout algorithm with a grouping penalty, which discourages nodes from deviating too far from other nodes belonging to the same group, and a temporal penalty, which discourages large node movements between consecutive time steps. The penalties increase the stability of the layout sequence, thus preserving the mental map. We introduce two dynamic layout algorithms within the proposed framework, namely dynamic multidimensional scaling (DMDS) and dynamic graph Laplacian layout (DGLL). We apply these algorithms on several data sets to illustrate the importance of both grouping and temporal regularization for producing interpretable visualizations of dynamic networks.Comment: To appear in Data Mining and Knowledge Discovery, supporting material (animations and MATLAB toolbox) available at http://tbayes.eecs.umich.edu/xukevin/visualization_dmkd_201

A novel ultra-high strength maraging steel with balanced ductility and creep resistance achieved by nanoscale β-NiAl and Laves phase precipitates

A novel ultra-high strength precipitation hardened martensitic steel with balanced ductility and creep resistance has been developed. It utilises a unique combination of nanometre scale intermetallic precipitates of Laves phases and β-NiAl to achieve such properties. The mechanical properties of this steel were assessed by tensile and creep testing. With different heat treatments, this steel showed a remarkable combination of mechanical properties: yield strength of >1800 MPa, ultimate tensile strength of ~ 2000 MPa, tensile ductility up to ~8% at room temperature and creep rupture life > 2,000 hours under 700 MPa stress at 500 °C. The microstructures at different length scales were characterised using scanning / transmission electron microscopy and atom probe tomography. The austenisation and ageing temperatures were found be the key factors determining the microstructural development and resulting mechanical properties. Large primary Laves phase precipitates formed at lower austenisation temperatures resulted in reduced creep strength; whilst the small difference (20 °C) in ageing temperatures had significant impact on the spatial distribution characteristics of β-NiAl precipitates. Lower ageing temperature produced much smaller but more uniformly distributed β-NiAl precipitates which contributed to the higher observed yield strength. It is clear from this study that whilst this novel alloy system showed great potentials, careful design of heat treatment is still required to achieve balanced mechanical properties to meet the service requirements in aerospace propulsion systems

A Macrophage Response to Mycobacterium leprae Phenolic Glycolipid Initiates Nerve Damage in Leprosy

$\textit{Mycobacterium leprae}$ causes leprosy and is unique among mycobacterial diseases in producing peripheral neuropathy. This debilitating morbidity is attributed to axon demyelination resulting from direct interaction of the $\textit{M. leprae}$-specific phenolic glycolipid 1 (PGL-1) with myelinating glia and their subsequent infection. Here, we use transparent zebrafish larvae to visualize the earliest events of $\textit{M. leprae}$-induced nerve damage. We find that demyelination and axonal damage are not directly initiated by $\textit{M. leprae}$ but by infected macrophages that patrol axons; demyelination occurs in areas of intimate contact. PGL-1 confers this neurotoxic response on macrophages: macrophages infected with $\textit{M. marinum}$-expressing PGL-1 also damage axons. PGL-1 induces nitric oxide synthase in infected macrophages, and the resultant increase in reactive nitrogen species damages axons by injuring their mitochondria and inducing demyelination. Our findings implicate the response of innate macrophages to $\textit{M. leprae}$ PGL-1 in initiating nerve damage in leprosy.This work was supported by an A.P. Giannini Foundation Postdoctoral Fellowship, an NIH training grant (T32 AI1007411), and an NIH NRSA Postdoctoral Fellowship (AI104240) to C.A.M.; an NSF Predoctoral Fellowship and NIH training grant T32 AI55396 to C.J.C.; a UCLA Clinical Translational Science Institute grant (UL1TR001881 to K.K.S.); K08AR066545 to P.O.S.; U19AI111224 and R01AI049313 to D.B.M.; an NIH grant (R01AR064582) to A.S.; the NIH Director’s Pioneer Award, an NIH MERIT award (R37AI054503), and a Wellcome Trust Principal Research Fellowship to L.R

Concordance of sibling's recall of measures of childhood socioeconomic position

<p>Abstract</p> <p>Background</p> <p>Studies of socioeconomic determinants of health often rely on recalled information on childhood socioeconomic position, despite limited evidence of the validity of this information. This study examined concordance between siblings of recalled measures of childhood socioeconomic position.</p> <p>Methods</p> <p>This cross-sectional study examined reports by 1280 adult sibling pairs in the National Survey of Midlife Development in the United States of seven measures of childhood socioeconomic position: father's occupation (in 9 categories), father having a professional occupation, father being a supervisor at work, father's education level, mother's education level, receipt of welfare payments, and subjective appraisal of being better or worse off financially than others.</p> <p>Results</p> <p>Concordance was high for father's professional occupation (0.97; 95% confidence interval (CI) 0.96, 0.98), father's occupation in 9 categories (0.76; 95% CI 0.73, 0.80), and receipt of welfare payments (0.95; 95% CI 0.93, 0.97). Concordance was lower for father's and mother's education level, and lowest for subjective appraisal of socioeconomic position (0.60; 95% CI 0.57, 0.64). Concordance of parental education was lower for sibling pairs with high school educations or less.</p> <p>Conclusion</p> <p>Concordance of recalled measures of childhood socioeconomic position by siblings is generally but not uniformly high.</p

Perspectives on the Trypanosoma cruzi-host cell receptor interaction

Chagas disease is caused by the parasite Trypanosoma cruzi. The critical initial event is the interaction of the trypomastigote form of the parasite with host receptors. This review highlights recent observations concerning these interactions. Some of the key receptors considered are those for thromboxane, bradykinin, and for the nerve growth factor TrKA. Other important receptors such as galectin-3, thrombospondin, and laminin are also discussed. Investigation into the molecular biology and cell biology of host receptors for T. cruzi may provide novel therapeutic targets

Hypoxia, Snail and incomplete epithelial–mesenchymal transition in breast cancer

BACKGROUND: Hypoxia is an element of the tumour microenvironment that impacts upon numerous cellular factors linked to clinical aggressiveness in cancer. One such factor, Snail, a master regulator of the epithelial-mesenchymal transition (EMT), has been implicated in key tumour biological processes such as invasion and metastasis. In this study we set out to investigate regulation of EMT in hypoxia, and the importance of Snail in cell migration and clinical outcome in breast cancer. METHODS: Four breast cancer cell lines were exposed to 0.1% oxygen and expression of EMT markers was monitored. The migratory ability was analysed following Snail overexpression and silencing. Snail expression was assessed in 500 tumour samples from premenopausal breast cancer patients, randomised to either 2 years of tamoxifen or no adjuvant treatment. RESULTS: Exposure to 0.1% oxygen resulted in elevated levels of Snail protein, along with changes in vimentin and E-cadherin expression, and in addition increased migration of MDA-MB-468 cells. Overexpression of Snail increased the motility of MCF-7, T-47D and MDA-MB-231 cells, whereas silencing of the protein resulted in decreased migratory propensity of MCF-7, MDA-MB-468 and MDA-MB-231 cells. Moreover, nuclear Snail expression was associated with tumours of higher grade and proliferation rate, but not with disease recurrence. Interestingly, Snail negativity was associated with impaired tamoxifen response (P = 0.048). CONCLUSIONS: Our results demonstrate that hypoxia induces Snail expression but generally not a migratory phenotype, suggesting that hypoxic cells are only partially pushed towards EMT. Furthermore, our study supports the link between Snail and clinically relevant features and treatment response

Mapping Migratory Bird Prevalence Using Remote Sensing Data Fusion

This is the publisher’s final pdf. The published article is copyrighted by the Public Library of Science and can be found at: http://www.plosone.org/home.action.Background: Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. \ud \ud Methodology and Principal Findings: A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. \ud \ud Conclusion and Significance: Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level