A measure of individual role in collective dynamics

Identifying key players in collective dynamics remains a challenge in several research fields, from the efficient dissemination of ideas to drug target discovery in biomedical problems. The difficulty lies at several levels: how to single out the role of individual elements in such intermingled systems, or which is the best way to quantify their importance. Centrality measures describe a node's importance by its position in a network. The key issue obviated is that the contribution of a node to the collective behavior is not uniquely determined by the structure of the system but it is a result of the interplay between dynamics and network structure. We show that dynamical influence measures explicitly how strongly a node's dynamical state affects collective behavior. For critical spreading, dynamical influence targets nodes according to their spreading capabilities. For diffusive processes it quantifies how efficiently real systems may be controlled by manipulating a single node.Comment: accepted for publication in Scientific Report

The USNO-B Catalog

USNO-B is an all-sky catalog that presents positions, proper motions, magnitudes in various optical passbands, and star/galaxy estimators for 1,042,618,261 objects derived from 3,643,201,733 separate observations. The data were obtained from scans of 7,435 Schmidt plates taken for the various sky surveys during the last 50 years. USNO-B1.0 is believed to provide all-sky coverage, completeness down to V = 21, 0.2 arcsecond astrometric accuracy at J2000, 0.3 magnitude photometric accuracy in up to five colors, and 85% accuracy for distinguishing stars from non-stellar objects. A brief discussion of various issues is given here, but the actual data are available from http://www.nofs.navy.mil and other sites.Comment: Accepted by Astronomical Journa

Accounting for Redundancy when Integrating Gene Interaction Databases

During the last years gene interaction networks are increasingly being used for the assessment and interpretation of biological measurements. Knowledge of the interaction partners of an unknown protein allows scientists to understand the complex relationships between genetic products, helps to reveal unknown biological functions and pathways, and get a more detailed picture of an organism's complexity. Being able to measure all protein interactions under all relevant conditions is virtually impossible. Hence, computational methods integrating different datasets for predicting gene interactions are needed. However, when integrating different sources one has to account for the fact that some parts of the information may be redundant, which may lead to an overestimation of the true likelihood of an interaction. Our method integrates information derived from three different databases (Bioverse, HiMAP and STRING) for predicting human gene interactions. A Bayesian approach was implemented in order to integrate the different data sources on a common quantitative scale. An important assumption of the Bayesian integration is independence of the input data (features). Our study shows that the conditional dependency cannot be ignored when combining gene interaction databases that rely on partially overlapping input data. In addition, we show how the correlation structure between the databases can be detected and we propose a linear model to correct for this bias. Benchmarking the results against two independent reference data sets shows that the integrated model outperforms the individual datasets. Our method provides an intuitive strategy for weighting the different features while accounting for their conditional dependencies

Effect of Homocysteine-Lowering Treatment With Folic Acid and B Vitamins on Risk of Type 2 Diabetes in Women: A Randomized, Controlled Trial

OBJECTIVE: Homocysteinemia may play an etiologic role in the pathogenesis of type 2 diabetes by promoting oxidative stress, systemic inflammation, and endothelial dysfunction. We investigated whether homocysteine-lowering treatment by B vitamin supplementation prevents the risk of type 2 diabetes. RESEARCH DESIGN AND METHODS: The Women's Antioxidant and Folic Acid Cardiovascular Study (WAFACS), a randomized, double-blind, placebo-controlled trial of 5,442 female health professionals aged ≥40 years with a history of cardiovascular disease (CVD) or three or more CVD risk factors, included 4,252 women free of diabetes at baseline. Participants were randomly assigned to either an active treatment group (daily intake of a combination pill of 2.5 mg folic acid, 50 mg vitamin B6, and 1 mg vitamin B12) or to the placebo group. RESULTS: During a median follow-up of 7.3 years, 504 women had an incident diagnosis of type 2 diabetes. Overall, there was no significant difference between the active treatment group and the placebo group in diabetes risk (relative risk 0.94 [95% CI 0.79–1.11]; P = 0.46), despite significant lowering of homocysteine levels. Also, there was no evidence for effect modifications by baseline intakes of dietary folate, vitamin B6, and vitamin B12. In a sensitivity analysis, the null result remained for women compliant with their study pills (0.92 [0.76–1.10]; P = 0.36). CONCLUSIONS: Lowering homocysteine levels by daily supplementation with folic acid and vitamins B6 and B12 did not reduce the risk of developing type 2 diabetes among women at high risk for CVD

Weak Lensing from Space I: Instrumentation and Survey Strategy

A wide field space-based imaging telescope is necessary to fully exploit the technique of observing dark matter via weak gravitational lensing. This first paper in a three part series outlines the survey strategies and relevant instrumental parameters for such a mission. As a concrete example of hardware design, we consider the proposed Supernova/Acceleration Probe (SNAP). Using SNAP engineering models, we quantify the major contributions to this telescope's Point Spread Function (PSF). These PSF contributions are relevant to any similar wide field space telescope. We further show that the PSF of SNAP or a similar telescope will be smaller than current ground-based PSFs, and more isotropic and stable over time than the PSF of the Hubble Space Telescope. We outline survey strategies for two different regimes - a ``wide'' 300 square degree survey and a ``deep'' 15 square degree survey that will accomplish various weak lensing goals including statistical studies and dark matter mapping.Comment: 25 pages, 8 figures, 1 table, replaced with Published Versio

A Standardised Procedure for Evaluating Creative Systems: Computational Creativity Evaluation Based on What it is to be Creative

Computational creativity is a flourishing research area, with a variety of creative systems being produced and developed. Creativity evaluation has not kept pace with system development with an evident lack of systematic evaluation of the creativity of these systems in the literature. This is partially due to difficulties in defining what it means for a computer to be creative; indeed, there is no consensus on this for human creativity, let alone its computational equivalent. This paper proposes a Standardised Procedure for Evaluating Creative Systems (SPECS). SPECS is a three-step process: stating what it means for a particular computational system to be creative, deriving and performing tests based on these statements. To assist this process, the paper offers a collection of key components of creativity, identified empirically from discussions of human and computational creativity. Using this approach, the SPECS methodology is demonstrated through a comparative case study evaluating computational creativity systems that improvise music

ABT-869, a multitargeted receptor tyrosine kinase inhibitor: inhibition of FLT3 phosphorylation and signaling in acute myeloid leukemia

In 15% to 30% of patients with acute myeloid leukemia (AML), aberrant proliferation is a consequence of a juxtamembrane mutation in the FLT3 gene (FMS-like tyrosine kinase 3–internal tandem duplication [FLT3-ITD]), causing constitutive kinase activity. ABT-869 (a multitargeted receptor tyrosine kinase inhibitor) inhibited the phosphorylation of FLT3, STAT5, and ERK, as well as Pim-1 expression in MV-4-11 and MOLM-13 cells (IC_(50) approximately 1-10 nM) harboring the FLT3-ITD. ABT-869 inhibited the proliferation of these cells (IC_(50) = 4 and 6 nM, respectively) through the induction of apoptosis (increased sub-G_(0)/G_1 phase, caspase activation, and PARP cleavage), whereas cells harboring wild-type (wt)–FLT3 were less sensitive. In normal human blood spiked with AML cells, ABT-869 inhibited phosphorylation of FLT3 (IC_(50) approximately 100 nM), STAT5, and ERK, and decreased Pim-1 expression. In methylcellulose-based colony-forming assays, ABT-869 had no significant effect up to 1000 nM on normal hematopoietic progenitor cells, whereas in AML patient samples harboring both FLT3-ITD and wt-FLT3, ABT-869 inhibited colony formation (IC_(50) = 100 and 1000 nM, respectively). ABT-869 dose-dependently inhibited MV-4-11 and MOLM-13 flank tumor growth, prevented tumor formation, regressed established MV-4-11 xenografts, and increased survival by 20 weeks in an MV-4-11 engraftment model. In tumors, ABT-869 inhibited FLT3 phosphorylation, induced apoptosis (transferase-mediated dUTP nick-end labeling [TUNEL]) and decreased proliferation (Ki67). ABT-869 is under clinical development for AML

Multi-agent systems in epidemiology: a first step for computational biology in the study of vector-borne disease transmission

<p>Abstract</p> <p>Background</p> <p>Computational biology is often associated with genetic or genomic studies only. However, thanks to the increase of computational resources, computational models are appreciated as useful tools in many other scientific fields. Such modeling systems are particularly relevant for the study of complex systems, like the epidemiology of emerging infectious diseases. So far, mathematical models remain the main tool for the epidemiological and ecological analysis of infectious diseases, with SIR models could be seen as an implicit standard in epidemiology. Unfortunately, these models are based on differential equations and, therefore, can become very rapidly unmanageable due to the too many parameters which need to be taken into consideration. For instance, in the case of zoonotic and vector-borne diseases in wildlife many different potential host species could be involved in the life-cycle of disease transmission, and SIR models might not be the most suitable tool to truly capture the overall disease circulation within that environment. This limitation underlines the necessity to develop a standard spatial model that can cope with the transmission of disease in realistic ecosystems.</p> <p>Results</p> <p>Computational biology may prove to be flexible enough to take into account the natural complexity observed in both natural and man-made ecosystems. In this paper, we propose a new computational model to study the transmission of infectious diseases in a spatially explicit context. We developed a multi-agent system model for vector-borne disease transmission in a realistic spatial environment.</p> <p>Conclusion</p> <p>Here we describe in detail the general behavior of this model that we hope will become a standard reference for the study of vector-borne disease transmission in wildlife. To conclude, we show how this simple model could be easily adapted and modified to be used as a common framework for further research developments in this field.</p

The ADAMTS13-VWF axis is dysregulated in chronic thromboembolic pulmonary hypertension

Chronic thromboembolic pulmonary hypertension (CTEPH) is an important consequence of pulmonary embolism that is associated with abnormalities in haemostasis. We investigated the ADAMTS13-von Willebrand factor (VWF) axis in CTEPH, including its relationship with disease severity, inflammation, ABO groups and ADAMTS13 genetic variants.ADAMTS13 and VWF plasma antigen levels were measured in patients with CTEPH (n=208), chronic thromboembolic disease without pulmonary hypertension (CTED) (n=35), resolved pulmonary embolism (n=28), idiopathic pulmonary arterial hypertension (n=30) and healthy controls (n=68). CTEPH genetic ABO associations and protein quantitative trait loci were investigated. ADAMTS13-VWF axis abnormalities were assessed in CTEPH and healthy control subsets by measuring ADAMTS13 activity, D-dimers and VWF multimeric size.Patients with CTEPH had decreased ADAMTS13 (adjusted β -23.4%, 95% CI -30.9- -15.1%, p<0.001) and increased VWF levels (β +75.5%, 95% CI 44.8-113%, p<0.001) compared to healthy controls. ADAMTS13 levels remained low after reversal of pulmonary hypertension by pulmonary endarterectomy surgery and were equally reduced in CTED. We identified a genetic variant near the ADAMTS13 gene associated with ADAMTS13 protein that accounted for ∼8% of the variation in levels.The ADAMTS13-VWF axis is dysregulated in CTEPH. This is unrelated to pulmonary hypertension, disease severity or markers of systemic inflammation and implicates the ADAMTS13-VWF axis in CTEPH pathobiology

The integrated analysis of metabolic and protein interaction networks reveals novel molecular organizing principles

Background: The study of biological interaction networks is a central theme of systems biology. Here, we investigate the relationships between two distinct types of interaction networks: the metabolic pathway map and the protein-protein interaction network (PIN). It has long been established that successive enzymatic steps are often catalyzed by physically interacting proteins forming permanent or transient multi-enzymes complexes. Inspecting high-throughput PIN data, it was shown recently that, indeed, enzymes involved in successive reactions are generally more likely to interact than other protein pairs. In our study, we expanded this line of research to include comparisons of the underlying respective network topologies as well as to investigate whether the spatial organization of enzyme interactions correlates with metabolic efficiency. Results: Analyzing yeast data, we detected long-range correlations between shortest paths between proteins in both network types suggesting a mutual correspondence of both network architectures. We discovered that the organizing principles of physical interactions between metabolic enzymes differ from the general PIN of all proteins. While physical interactions between proteins are generally dissortative, enzyme interactions were observed to be assortative. Thus, enzymes frequently interact with other enzymes of similar rather than different degree. Enzymes carrying high flux loads are more likely to physically interact than enzymes with lower metabolic throughput. In particular, enzymes associated with catabolic pathways as well as enzymes involved in the biosynthesis of complex molecules were found to exhibit high degrees of physical clustering. Single proteins were identified that connect major components of the cellular metabolism and may thus be essential for the structural integrity of several biosynthetic systems. Conclusion: Our results reveal topological equivalences between the protein interaction network and the metabolic pathway network. Evolved protein interactions may contribute significantly towards increasing the efficiency of metabolic processes by permitting higher metabolic fluxes. Thus, our results shed further light on the unifying principles shaping the evolution of both the functional (metabolic) as well as the physical interaction network