A Relational Event Approach to Modeling Behavioral Dynamics

This chapter provides an introduction to the analysis of relational event data (i.e., actions, interactions, or other events involving multiple actors that occur over time) within the R/statnet platform. We begin by reviewing the basics of relational event modeling, with an emphasis on models with piecewise constant hazards. We then discuss estimation for dyadic and more general relational event models using the relevent package, with an emphasis on hands-on applications of the methods and interpretation of results. Statnet is a collection of packages for the R statistical computing system that supports the representation, manipulation, visualization, modeling, simulation, and analysis of relational data. Statnet packages are contributed by a team of volunteer developers, and are made freely available under the GNU Public License. These packages are written for the R statistical computing environment, and can be used with any computing platform that supports R (including Windows, Linux, and Mac).

Genomic Expansion of Magnetotactic Bacteria Reveals an Early Common Origin of Magnetotaxis with Lineage-specific Evolution

The origin and evolution of magnetoreception, which in diverse prokaryotes and protozoa is known as magnetotaxis and enables these microorganisms to detect Earth’s magnetic field for orientation and navigation, is not well understood in evolutionary biology. The only known prokaryotes capable of sensing the geomagnetic field are magnetotactic bacteria (MTB), motile microorganisms that biomineralize intracellular, membrane-bounded magnetic single-domain crystals of either magnetite (Fe3O4) or greigite (Fe3S4) called magnetosomes. Magnetosomes are responsible for magnetotaxis in MTB. Here we report the first large-scale metagenomic survey of MTB from both northern and southern hemispheres combined with 28 genomes from uncultivated MTB. These genomes expand greatly the coverage of MTB in the Proteobacteria, Nitrospirae, and Omnitrophica phyla, and provide the first genomic evidence of MTB belonging to the Zetaproteobacteria and “Candidatus Lambdaproteobacteria” classes. The gene content and organization of magnetosome gene clusters, which are physically grouped genes that encode proteins for magnetosome biosynthesis and organization, are more conserved within phylogenetically similar groups than between different taxonomic lineages. Moreover, the phylogenies of core magnetosome proteins form monophyletic clades. Together, these results suggest a common ancient origin of iron-based (Fe3O4 and Fe3S4) magnetotaxis in the domain Bacteria that underwent lineage-specific evolution, shedding new light on the origin and evolution of biomineralization and magnetotaxis, and expanding significantly the phylogenomic representation of MTB

Who is the best player ever? A complex network analysis of the history of professional tennis

We consider all matches played by professional tennis players between 1968 and 2010, and, on the basis of this data set, construct a directed and weighted network of contacts. The resulting graph shows complex features, typical of many real networked systems studied in literature. We develop a diffusion algorithm and apply it to the tennis contact network in order to rank professional players. Jimmy Connors is identified as the best player of the history of tennis according to our ranking procedure. We perform a complete analysis by determining the best players on specific playing surfaces as well as the best ones in each of the years covered by the data set. The results of our technique are compared to those of two other well established methods. In general, we observe that our ranking method performs better: it has a higher predictive power and does not require the arbitrary introduction of external criteria for the correct assessment of the quality of players. The present work provides a novel evidence of the utility of tools and methods of network theory in real applications.Comment: 10 pages, 4 figures, 4 table

A Novel Strategy to Screen Bacillus Calmette-Guérin Protein Antigen Recognized by γδ TCR

BACKGROUND: Phosphoantigen was originally identified as the main γδ TCR-recognized antigen that could activate γδ T cells to promote immune protection against mycobacterial infection. However, new evidence shows that the γδ T cells activated by phosphoantigen can only provide partial immune protection against mycobacterial infection. In contrast, whole lysates of Mycobacterium could activate immune protection more potently, implying that other γδ TCR-recognized antigens that elicit protective immune responses. To date, only a few distinct mycobacterial antigens recognized by the γδ TCR have been characterized. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we established a new approach to screen epitopes or protein antigens recognized by the γδ TCR using Bacillus Calmette-Guérin- (BCG-) specific γ TCR transfected cells as probes to pan a 12-mer random-peptide phage-displayed library. Through binding assays and functional analysis, we identified a peptide (BP3) that not only binds to the BCG-specific γδ TCR but also effectively activates γδ T cells isolated from human subjects inoculated with BCG. Importantly, the γδ T cells activated by peptide BP3 had a cytotoxic effect on THP-1 cells infected with BCG. Moreover, the oxidative stress response regulatory protein (OXYS), a BCG protein that matches perfectly with peptide BP3 according to bioinformatics analysis, was confirmed as a ligand for the γδ TCR and was found to activate γδ T cells from human subjects inoculated with BCG. CONCLUSIONS/SIGNIFICANCE: In conclusion, our study provides a novel strategy to identify epitopes or protein antigens for the γδ TCR, and provides a potential means to screen mycobacterial vaccines or candidates for adjuvant

The geography of recent genetic ancestry across Europe

The recent genealogical history of human populations is a complex mosaic formed by individual migration, large-scale population movements, and other demographic events. Population genomics datasets can provide a window into this recent history, as rare traces of recent shared genetic ancestry are detectable due to long segments of shared genomic material. We make use of genomic data for 2,257 Europeans (the POPRES dataset) to conduct one of the first surveys of recent genealogical ancestry over the past three thousand years at a continental scale. We detected 1.9 million shared genomic segments, and used the lengths of these to infer the distribution of shared ancestors across time and geography. We find that a pair of modern Europeans living in neighboring populations share around 10-50 genetic common ancestors from the last 1500 years, and upwards of 500 genetic ancestors from the previous 1000 years. These numbers drop off exponentially with geographic distance, but since genetic ancestry is rare, individuals from opposite ends of Europe are still expected to share millions of common genealogical ancestors over the last 1000 years. There is substantial regional variation in the number of shared genetic ancestors: especially high numbers of common ancestors between many eastern populations likely date to the Slavic and/or Hunnic expansions, while much lower levels of common ancestry in the Italian and Iberian peninsulas may indicate weaker demographic effects of Germanic expansions into these areas and/or more stably structured populations. Recent shared ancestry in modern Europeans is ubiquitous, and clearly shows the impact of both small-scale migration and large historical events. Population genomic datasets have considerable power to uncover recent demographic history, and will allow a much fuller picture of the close genealogical kinship of individuals across the world.Comment: Full size figures available from http://www.eve.ucdavis.edu/~plralph/research.html; or html version at http://ralphlab.usc.edu/ibd/ibd-paper/ibd-writeup.xhtm

Methods for adjusting population structure and familial relatedness in association test for collective effect of multiple rare variants on quantitative traits

Because of the low frequency of rare genetic variants in observed data, the statistical power of detecting their associations with target traits is usually low. The collapsing test of collective effect of multiple rare variants is an important and useful strategy to increase the power; in addition, family data may be enriched with causal rare variants and therefore provide extra power. However, when family data are used, both population structure and familial relatedness need to be adjusted for the possible inflation of false positives. Using a unified mixed linear model and family data, we compared six methods to detect the association between multiple rare variants and quantitative traits. Through the analysis of 200 replications of the quantitative trait Q2 from the Genetic Analysis Workshop 17 data set simulated for 697 subjects from 8 extended families, and based on quantile-quantile plots under the null and receiver operating characteristic curves, we compared the false-positive rate and power of these methods. We observed that adjusting for pedigree-based kinship gives the best control for false-positive rate, whereas adjusting for marker-based identity by state slightly outperforms in terms of power. An adjustment based on a principal components analysis slightly improves the false-positive rate and power. Taking into account type-1 error, power, and computational efficiency, we find that adjusting for pedigree-based kinship seems to be a good choice for the collective test of association between multiple rare variants and quantitative traits using family data

Modeling the scaling properties of human mobility

While the fat tailed jump size and the waiting time distributions characterizing individual human trajectories strongly suggest the relevance of the continuous time random walk (CTRW) models of human mobility, no one seriously believes that human traces are truly random. Given the importance of human mobility, from epidemic modeling to traffic prediction and urban planning, we need quantitative models that can account for the statistical characteristics of individual human trajectories. Here we use empirical data on human mobility, captured by mobile phone traces, to show that the predictions of the CTRW models are in systematic conflict with the empirical results. We introduce two principles that govern human trajectories, allowing us to build a statistically self-consistent microscopic model for individual human mobility. The model not only accounts for the empirically observed scaling laws but also allows us to analytically predict most of the pertinent scaling exponents

Quasi-Normal Modes of Stars and Black Holes

Perturbations of stars and black holes have been one of the main topics of relativistic astrophysics for the last few decades. They are of particular importance today, because of their relevance to gravitational wave astronomy. In this review we present the theory of quasi-normal modes of compact objects from both the mathematical and astrophysical points of view. The discussion includes perturbations of black holes (Schwarzschild, Reissner-Nordstr\"om, Kerr and Kerr-Newman) and relativistic stars (non-rotating and slowly-rotating). The properties of the various families of quasi-normal modes are described, and numerical techniques for calculating quasi-normal modes reviewed. The successes, as well as the limits, of perturbation theory are presented, and its role in the emerging era of numerical relativity and supercomputers is discussed.Comment: 74 pages, 7 figures, Review article for "Living Reviews in Relativity

Host-Pathogen O-Methyltransferase Similarity and Its Specific Presence in Highly Virulent Strains of Francisella tularensis Suggests Molecular Mimicry

Whole genome comparative studies of many bacterial pathogens have shown an overall high similarity of gene content (>95%) between phylogenetically distinct subspecies. In highly clonal species that share the bulk of their genomes subtle changes in gene content and small-scale polymorphisms, especially those that may alter gene expression and protein-protein interactions, are more likely to have a significant effect on the pathogen's biology. In order to better understand molecular attributes that may mediate the adaptation of virulence in infectious bacteria, a comparative study was done to further analyze the evolution of a gene encoding an o-methyltransferase that was previously identified as a candidate virulence factor due to its conservation specifically in highly pathogenic Francisella tularensis subsp. tularensis strains. The o-methyltransferase gene is located in the genomic neighborhood of a known pathogenicity island and predicted site of rearrangement. Distinct o-methyltransferase subtypes are present in different Francisella tularensis subspecies. Related protein families were identified in several host species as well as species of pathogenic bacteria that are otherwise very distant phylogenetically from Francisella, including species of Mycobacterium. A conserved sequence motif profile is present in the mammalian host and pathogen protein sequences, and sites of non-synonymous variation conserved in Francisella subspecies specific o-methyltransferases map proximally to the predicted active site of the orthologous human protein structure. Altogether, evidence suggests a role of the F. t. subsp. tularensis protein in a mechanism of molecular mimicry, similar perhaps to Legionella and Coxiella. These findings therefore provide insights into the evolution of niche-restriction and virulence in Francisella, and have broader implications regarding the molecular mechanisms that mediate host-pathogen relationships

Factors contributing to delay in parasite clearance in uncomplicated falciparum malaria in children

Background: Drug resistance in Plasmodium falciparum is common in many endemic and other settings but there is no clear recommendation on when to change therapy when there is delay in parasite clearance after initiation of therapy in African children. Methods: The factors contributing to delay in parasite clearance, defined as a clearance time > 2 d, in falciparum malaria were characterized in 2,752 prospectively studied children treated with anti-malarial drugs between 1996 and 2008. Results: 1,237 of 2,752 children (45%) had delay in parasite clearance. Overall 211 children (17%) with delay in clearance subsequently failed therapy and they constituted 72% of those who had drug failure, i.e., 211 of 291 children. The following were independent risk factors for delay in parasite clearance at enrolment: age less than or equal to 2 years (Adjusted odds ratio [AOR] = 2.13, 95% confidence interval [CI]1.44-3.15, P < 0.0001), presence of fever (AOR = 1.33, 95% CI = 1.04-1.69, P = 0.019), parasitaemia >50,000/ul (AOR = 2.21, 95% CI = 1.77-2.75, P < 0.0001), and enrolment before year 2000 (AOR= 1.55, 95% CI = 1.22-1.96, P < 0.0001). Following treatment, a body temperature ≥ 38°C and parasitaemia > 20000/μl a day after treatment began, were independent risk factors for delay in clearance. Non-artemisinin monotherapies were associated with delay in clearance and treatment failures, and in those treated with chloroquine or amodiaquine, with pfmdr 1/pfcrt mutants. Delay in clearance significantly increased gametocyte carriage (P < 0.0001). Conclusion: Delay in parasite clearance is multifactorial, is related to drug resistance and treatment failure in uncomplicated malaria and has implications for malaria control efforts in sub-Saharan Africa