A Distributed Multilevel Force-directed Algorithm

The wide availability of powerful and inexpensive cloud computing services naturally motivates the study of distributed graph layout algorithms, able to scale to very large graphs. Nowadays, to process Big Data, companies are increasingly relying on PaaS infrastructures rather than buying and maintaining complex and expensive hardware. So far, only a few examples of basic force-directed algorithms that work in a distributed environment have been described. Instead, the design of a distributed multilevel force-directed algorithm is a much more challenging task, not yet addressed. We present the first multilevel force-directed algorithm based on a distributed vertex-centric paradigm, and its implementation on Giraph, a popular platform for distributed graph algorithms. Experiments show the effectiveness and the scalability of the approach. Using an inexpensive cloud computing service of Amazon, we draw graphs with ten million edges in about 60 minutes.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

A retrospective pilot study to determine whether the reproductive tract microbiota differs between women with a history of infertility and fertile women

© 2017 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists Background: We know very little about the microbiota inhabiting the upper female reproductive tract and how it impacts on fertility. Aims: This pilot study aimed to examine the vaginal, cervical and endometrial microbiota for women with a history of infertility compared to women with a history of fertility. Materials and methods: Using a retrospective case–control study design, women were recruited for collection of vaginal, cervical and endometrial samples. The microbiota composition was analysed by 16S ribosomal RNA (rRNA) gene amplification and endometrial expression of selected human genes by quantitative reverse transcription polymerase chain reaction. Results: Sixty-five specimens from the reproductive tract of 31 women were successfully analysed using 16S rRNA gene amplicon sequencing (16 controls and 15 cases). The dominant microbial community members were consistent in the vagina and cervix, and generally consistent with the endometrium although the relative proportions varied. We detected three major microbiota clusters that did not group by tissue location or case–control status. There was a trend that infertile women more often had Ureaplasma in the vagina and Gardnerella in the cervix. Testing for the expression of selected genes in the endometrium did not show evidence of correlation with case–control status, or with microbial community composition, although Tenascin-C expression correlated with a history of miscarriage. Conclusions: There is a need for further exploration of the endometrial microbiota, and how the microbiota members or profile interplays with fertility or assisted reproductive technologies

A Sparse Stress Model

Force-directed layout methods constitute the most common approach to draw general graphs. Among them, stress minimization produces layouts of comparatively high quality but also imposes comparatively high computational demands. We propose a speed-up method based on the aggregation of terms in the objective function. It is akin to aggregate repulsion from far-away nodes during spring embedding but transfers the idea from the layout space into a preprocessing phase. An initial experimental study informs a method to select representatives, and subsequent more extensive experiments indicate that our method yields better approximations of minimum-stress layouts in less time than related methods.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

Gerbes, M5-Brane Anomalies and E_8 Gauge Theory

Abelian gerbes and twisted bundles describe the topology of the NS-NS 3-form gauge field strength H. We review how they have been usefully applied to study and resolve global anomalies in open string theory. Abelian 2-gerbes and twisted nonabelian gerbes describe the topology of the 4-form field strength G of M-theory. We show that twisted nonabelian gerbes are relevant in the study and resolution of global anomalies of multiple coinciding M5-branes. Global anomalies for one M5-brane have been studied by Witten and by Diaconescu, Freed and Moore. The structure and the differential geometry of twisted nonabelian gerbes (i.e. modules for 2-gerbes) is defined and studied. The nonabelian 2-form gauge potential living on multiple coinciding M5-branes arises as curving (curvature) of twisted nonabelian gerbes. The nonabelian group is in general $\tilde\Omega E_8$, the central extension of the E_8 loop group. The twist is in general necessary to cancel global anomalies due to the nontriviality of the 11-dimensional 4-form G field strength and due to the possible torsion present in the cycles the M5-branes wrap. Our description of M5-branes global anomalies leads to the D4-branes one upon compactification of M-theory to Type IIA theory.Comment: 19 page

Effect of combined uphill-downhill sprint training on kinematics and maximum running speed in experienced sprinters

This study examined the effects of sprint running training on sloping surfaces (3°) in experienced sprinters using selected kinematic variables. Twelve experienced sprinters were randomly allocated to two training groups (combined uphill–downhill and horizontal). Pre- and post-training tests were performed to examine the effects of six weeks of training on maximum running speed, step rate, step length, step time, contact time, braking and propulsive phase of contact time, flight time and selected postural characteristics during a step cycle in the final steps of a 35m sprint test. In the combined uphill–downhill training group, maximum running speed was substantially greater (from 9.08 ± 0.90 m s-1 to 9.51 ± 0.62 m s-1; p <0.05) after training by 4.8%; step rate, contact time, step time and concentric phase was not modified. There were no significant changes in maximal speed or sprint kinematics in the horizontal training group. Overall, the posture characteristics did not change with training. The combined uphill–downhill training method was substantially more effective in improving the maximum running speed in experienced sprinters than a traditional horizontal training method

Pre-columbian origins for North American anthrax

Disease introduction into the New World during colonial expansion is well documented and had a major impact on indigenous populations; however, few diseases have been associated with early human migrations into North America. During the late Pleistocene epoch, Asia and North America were joined by the Beringian Steppe ecosystem which allowed animals and humans to freely cross what would become a water barrier in the Holocene. Anthrax has clearly been shown to be dispersed by human commerce and trade in animal products contaminated with Bacillus anthracis spores. Humans appear to have brought B. anthracis to this area from Asia and then moved it further south as an ice-free corridor opened in central Canada ~13,000 ybp. In this study, we have defined the evolutionary history of Western North American (WNA) anthrax using 2,850 single nucleotide polymorphisms (SNPs) and 285 geographically diverse B. anthracis isolates. Phylogeography of the major WNA B. anthracis clone reveals ancestral populations in northern Canada with progressively derived populations to the south; the most recent ancestor of this clonal lineage is in Eurasia. Our phylogeographic patterns are consistent with B. anthracis arriving with humans via the Bering Land Bridge. This northern-origin hypothesis is highly consistent with our phylogeographic patterns and rates of SNP accumulation observed in current day B. anthracis isolates. Continent-wide dispersal of WNA B. anthracis likely required movement by later European colonizers, but the continent's first inhabitants may have seeded the initial North American populations

Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community’s functional capabilities. Here we describe PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this ‘predictive metagenomic’ approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available

Cervical intraepithelial neoplasia disease progression is associated with increased vaginal microbiome diversity

Persistent infection with oncogenic Human Papillomavirus (HPV) is necessary for cervical carcinogenesis. Although evidence suggests that the vaginal microbiome plays a functional role in the persistence or regression of HPV infections, this has yet to be described in women with cervical intra-epithelial neoplasia (CIN). We hypothesised that increasing microbiome diversity is associated with increasing CIN severity. llumina MiSeq sequencing of 16S rRNA gene amplicons was used to characterise the vaginal microbiota of women with low-grade squamous intra-epithelial lesions (LSIL; n = 52), high-grade (HSIL; n = 92), invasive cervical cancer (ICC; n = 5) and healthy controls (n = 20). Hierarchical clustering analysis revealed an increased prevalence of microbiomes characterised by high-diversity and low levels of Lactobacillus spp. (community state type-CST IV) with increasing disease severity, irrespective of HPV status (Normal = 2/20,10%; LSIL = 11/52,21%; HSIL = 25/92,27%; ICC = 2/5,40%). Increasing disease severity was associated with decreasing relative abundance of Lactobacillus spp. The vaginal microbiome in HSIL was characterised by higher levels of Sneathia sanguinegens (P < 0.01), Anaerococcus tetradius (P < 0.05) and Peptostreptococcus anaerobius (P < 0.05) and lower levels of Lactobacillus jensenii (P < 0.01) compared to LSIL. Our results suggest advancing CIN disease severity is associated with increasing vaginal microbiota diversity and may be involved in regulating viral persistence and disease progression

A unified data representation theory for network visualization, ordering and coarse-graining

Representation of large data sets became a key question of many scientific disciplines in the last decade. Several approaches for network visualization, data ordering and coarse-graining accomplished this goal. However, there was no underlying theoretical framework linking these problems. Here we show an elegant, information theoretic data representation approach as a unified solution of network visualization, data ordering and coarse-graining. The optimal representation is the hardest to distinguish from the original data matrix, measured by the relative entropy. The representation of network nodes as probability distributions provides an efficient visualization method and, in one dimension, an ordering of network nodes and edges. Coarse-grained representations of the input network enable both efficient data compression and hierarchical visualization to achieve high quality representations of larger data sets. Our unified data representation theory will help the analysis of extensive data sets, by revealing the large-scale structure of complex networks in a comprehensible form.Comment: 13 pages, 5 figure

Identifying metabolite markers for preterm birth in cervicovaginal fluid by magnetic resonance spectroscopy

Introduction Preterm birth (PTB) may be preceded by changes in the vaginal microflora and metabolite profiles. Objectives We sought to characterise the metabolite profile of cervicovaginal fluid (CVF) of pregnant women by 1H NMR spectroscopy, and assess their predictive value for PTB. Methods A pair of high-vaginal swabs was obtained from pregnant women with no evidence of clinical infection and grouped as follows: asymptomatic low risk (ALR) women with no previous history of PTB, assessed at 20–22 gestational weeks, g.w., n = 83; asymptomatic high risk (AHR) women with a previous history of PTB, assessed at both 20–22 g.w., n = 71, and 26–28 g.w., n = 58; and women presenting with symptoms of preterm labor (PTL) (SYM), assessed at 24–36 g.w., n = 65. Vaginal secretions were dissolved in phosphate buffered saline and scanned with a 9.4 T NMR spectrometer. Results Six metabolites (lactate, alanine, acetate, glutamine/glutamate, succinate and glucose) were analysed. In all study cohorts vaginal pH correlated with lactate integral (r = -0.62, p\0.0001). Lactate integrals were higher in the term ALR compared to the AHR (20–22 g.w.) women (p = 0.003). Acetate integrals were higher in the preterm versus term women for the AHR (20–22 g.w.) (p = 0.048) and SYM (p = 0.003) groups; and was predictive of PTB\37 g.w. (AUC 0.78; 95 % CI 0.61–0.95), and delivery within 2 weeks of the index assessment (AUC 0.84; 95 % CI 0.64–1) in the SYM women, whilst other metabolites were not. Conclusion High CVF acetate integral of women with symptoms of PTL appears predictive of preterm delivery, as well as delivery within 2 weeks of presentation