Statistical Inference for Valued-Edge Networks: Generalized Exponential Random Graph Models

Across the sciences, the statistical analysis of networks is central to the production of knowledge on relational phenomena. Because of their ability to model the structural generation of networks, exponential random graph models are a ubiquitous means of analysis. However, they are limited by an inability to model networks with valued edges. We solve this problem by introducing a class of generalized exponential random graph models capable of modeling networks whose edges are valued, thus greatly expanding the scope of networks applied researchers can subject to statistical analysis

Many-particle Brownian and Langevin Dynamics Simulations with the Brownmove package

<p>Abstract</p> <p>Background</p> <p>Brownian Dynamics (BD) is a coarse-grained implicit-solvent simulation method that is routinely used to investigate binary protein association dynamics, but due to its efficiency in handling large simulation volumes and particle numbers it is well suited to also describe many-protein scenarios as they often occur in biological cells.</p> <p>Results</p> <p>Here we introduce our "brownmove" simulation package which was designed to handle many-particle problems with varying particle numbers and allows for a very flexible definition of rigid and flexible protein and polymer models. Both a Brownian and a Langevin dynamics (LD) propagation scheme can be used and hydrodynamic interactions are treated efficiently with our recently introduced TEA-HI ansatz [Geyer, Winter, JCP 130 (2009) 114905]. With simulations of constrained polymers and flexible models of spherical proteins we demonstrate that it is crucial to include hydrodynamics when multi-bead models are used in BD or LD simulations. Only then both the translational and the rotational diffusion coefficients and the timescales of the internal dynamics can be reproduced correctly. In the third example project we show how constant density boundary conditions [Geyer et al, JCP 120 (2004) 4573] can be used to set up a non-equilibrium simulation of diffusional transport across an array of fixed obstacles. Finally, we demonstrate how the agglomeration dynamics of multiple particles with attractive patches can be analysed conveniently with the help of a dynamic interaction network.</p> <p>Conclusions</p> <p>Combining BD and LD propagation, fast hydrodynamics, a flexible protein model, and interfaces for "open" simulation settings, our freely available "brownmove" simulation package constitutes a new platform for coarse-grained many-particle simulations of biologically relevant diffusion and transport processes.</p

Transcription Factor SP4 Is a Susceptibility Gene for Bipolar Disorder

The Sp4 transcription factor plays a critical role for both development and function of mouse hippocampus. Reduced expression of the mouse Sp4 gene results in a variety of behavioral abnormalities relevant to human psychiatric disorders. The human SP4 gene is therefore examined for its association with both bipolar disorder and schizophrenia in European Caucasian and Chinese populations respectively. Out of ten SNPs selected from human SP4 genomic locus, four displayed significant association with bipolar disorder in European Caucasian families (rs12668354, p = 0.022; rs12673091, p = 0.0005; rs3735440, p = 0.019; rs11974306, p = 0.018). To replicate the genetic association, the same set of SNPs was examined in a Chinese bipolar case control sample. Four SNPs displayed significant association (rs40245, p = 0.009; rs12673091, p = 0.002; rs1018954, p = 0.001; rs3735440, p = 0.029), and two of them (rs12673091, rs3735440) were shared with positive SNPs from European Caucasian families. Considering the genetic overlap between bipolar disorder and schizophrenia, we extended our studies in Chinese trios families for schizophrenia. The SNP7 (rs12673091, p = 0.012) also displayed a significant association. The SNP7 (rs12673091) was therefore significantly associated in all three samples, and shared the same susceptibility allele (A) across all three samples. On the other hand, we found a gene dosage effect for mouse Sp4 gene in the modulation of sensorimotor gating, a putative endophenotype for both schizophrenia and bipolar disorder. The deficient sensorimotor gating in Sp4 hypomorphic mice was partially reversed by the administration of dopamine D2 antagonist or mood stabilizers. Both human genetic and mouse pharmacogenetic studies support Sp4 gene as a susceptibility gene for bipolar disorder or schizophrenia. The studies on the role of Sp4 gene in hippocampal development may provide novel insights for the contribution of hippocampal abnormalities in these psychiatric disorders

Meteorological Controls on Local and Regional Volcanic Ash Dispersal

Volcanic ash has the capacity to impact human health, livestock, crops and infrastructure, including international air traffic. For recent major eruptions, information on the volcanic ash plume has been combined with relatively coarse-resolution meteorological model output to provide simulations of regional ash dispersal, with reasonable success on the scale of hundreds of kilometres. However, to predict and mitigate these impacts locally, significant improvements in modelling capability are required. Here, we present results from a dynamic meteorological-ash-dispersion model configured with sufficient resolution to represent local topographic and convectively-forced flows. We focus on an archetypal volcanic setting, Soufrière, St Vincent, and use the exceptional historical records of the 1902 and 1979 eruptions to challenge our simulations. We find that the evolution and characteristics of ash deposition on St Vincent and nearby islands can be accurately simulated when the wind shear associated with the trade wind inversion and topographically-forced flows are represented. The wind shear plays a primary role and topographic flows a secondary role on ash distribution on local to regional scales. We propose a new explanation for the downwind ash deposition maxima, commonly observed in volcanic eruptions, as resulting from the detailed forcing of mesoscale meteorology on the ash plume

Diffusion in crowded biological environments: applications of Brownian dynamics

Biochemical reactions in living systems occur in complex, heterogeneous media with total concentrations of macromolecules in the range of 50 - 400 mgml. Molecular species occupy a significant fraction of the immersing medium, up to 40% of volume. Such complex and volume-occupied environments are generally termed 'crowded' and/or 'confined'. In crowded conditions non-specific interactions between macromolecules may hinder diffusion - a major process determining metabolism, transport, and signaling. Also, the crowded media can alter, both qualitatively and quantitatively, the reactions in vivo in comparison with their in vitro counterparts. This review focuses on recent developments in particle-based Brownian dynamics algorithms, their applications to model diffusive transport in crowded systems, and their abilities to reproduce and predict the behavior of macromolecules under in vivo conditions

Human Leg Model Predicts Ankle Muscle-Tendon Morphology, State, Roles and Energetics in Walking

A common feature in biological neuromuscular systems is the redundancy in joint actuation. Understanding how these redundancies are resolved in typical joint movements has been a long-standing problem in biomechanics, neuroscience and prosthetics. Many empirical studies have uncovered neural, mechanical and energetic aspects of how humans resolve these degrees of freedom to actuate leg joints for common tasks like walking. However, a unifying theoretical framework that explains the many independent empirical observations and predicts individual muscle and tendon contributions to joint actuation is yet to be established. Here we develop a computational framework to address how the ankle joint actuation problem is resolved by the neuromuscular system in walking. Our framework is founded upon the proposal that a consideration of both neural control and leg muscle-tendon morphology is critical to obtain predictive, mechanistic insight into individual muscle and tendon contributions to joint actuation. We examine kinetic, kinematic and electromyographic data from healthy walking subjects to find that human leg muscle-tendon morphology and neural activations enable a metabolically optimal realization of biological ankle mechanics in walking. This optimal realization (a) corresponds to independent empirical observations of operation and performance of the soleus and gastrocnemius muscles, (b) gives rise to an efficient load-sharing amongst ankle muscle-tendon units and (c) causes soleus and gastrocnemius muscle fibers to take on distinct mechanical roles of force generation and power production at the end of stance phase in walking. The framework outlined here suggests that the dynamical interplay between leg structure and neural control may be key to the high walking economy of humans, and has implications as a means to obtain insight into empirically inaccessible features of individual muscle and tendons in biomechanical tasks.National Institutes of Health (U.S.) (NIH Pioneer Award DP1 OD003646)Massachusetts Institute of Technology. Media Laboratory (Consortia Account 2736448)Massachusetts Institute of Technology. Media Laboratory (Consortia Account 6895867

Speciation in the Deep Sea: Multi-Locus Analysis of Divergence and Gene Flow between Two Hybridizing Species of Hydrothermal Vent Mussels

International audienceBackground: Reconstructing the history of divergence and gene flow between closely-related organisms has long been a difficult task of evolutionary genetics. Recently, new approaches based on the coalescence theory have been developed to test the existence of gene flow during the process of divergence. The deep sea is a motivating place to apply these new approaches. Differentiation by adaptation can be driven by the heterogeneity of the hydrothermal environment while populations should not have been strongly perturbed by climatic oscillations, the main cause of geographic isolation at the surface. Methodology/Principal Finding: Samples of DNA sequences were obtained for seven nuclear loci and a mitochondrial locus in order to conduct a multi-locus analysis of divergence and gene flow between two closely related and hybridizing species of hydrothermal vent mussels, Bathymodiolus azoricus and B. puteoserpentis. The analysis revealed that (i) the two species have started to diverge approximately 0.760 million years ago, (ii) the B. azoricus population size was 2 to 5 time greater than the B. puteoserpentis and the ancestral population and (iii) gene flow between the two species occurred over the complete species range and was mainly asymmetric, at least for the chromosomal regions studied. Conclusions/Significance: A long history of gene flow has been detected between the two Bathymodiolus species. However, it proved very difficult to conclusively distinguish secondary introgression from ongoing parapatric differentiation. As powerful as coalescence approaches could be, we are left by the fact that natural populations often deviates from standard assumptions of the underlying model. A more direct observation of the history of recombination at one of the seven loci studied suggests an initial period of allopatric differentiation during which recombination was blocked between lineages. Even in the deep sea, geographic isolation may well be a crucial promoter of speciation

Modern Clinical Research on LSD

All modern clinical studies using the classic hallucinogen lysergic acid diethylamide (LSD) in healthy subjects or patients in the last 25 years are reviewed herein. There were five recent studies in healthy participants and one in patients. In a controlled setting, LSD acutely induced bliss, audiovisual synesthesia, altered meaning of perceptions, derealization, depersonalization, and mystical experiences. These subjective effects of LSD were mediated by the 5-HT2A receptor. LSD increased feelings of closeness to others, openness, trust, and suggestibility. LSD impaired the recognition of sad and fearful faces, reduced left amygdala reactivity to fearful faces, and enhanced emotional empathy. LSD increased the emotional response to music and the meaning of music. LSD acutely produced deficits in sensorimotor gating, similar to observations in schizophrenia. LSD had weak autonomic stimulant effects and elevated plasma cortisol, prolactin, and oxytocin levels. Resting-state functional magnetic resonance studies showed that LSD acutely reduced the integrity of functional brain networks and increased connectivity between networks that normally are more dissociated. LSD increased functional thalamocortical connectivity and functional connectivity of the primary visual cortex with other brain areas. The latter effect was correlated with subjective hallucinations. LSD acutely induced global increases in brain entropy that were associated with greater trait openness 14 days later. In patients with anxiety associated with life-threatening disease, anxiety was reduced for 2 months after two doses of LSD. In medical settings, no complications of LSD administration were observed. These data should contribute to further investigations of the therapeutic potential of LSD in psychiatry

Diffusion, Crowding & Protein Stability in a Dynamic Molecular Model of the Bacterial Cytoplasm

A longstanding question in molecular biology is the extent to which the behavior of macromolecules observed in vitro accurately reflects their behavior in vivo. A number of sophisticated experimental techniques now allow the behavior of individual types of macromolecule to be studied directly in vivo; none, however, allow a wide range of molecule types to be observed simultaneously. In order to tackle this issue we have adopted a computational perspective, and, having selected the model prokaryote Escherichia coli as a test system, have assembled an atomically detailed model of its cytoplasmic environment that includes 50 of the most abundant types of macromolecules at experimentally measured concentrations. Brownian dynamics (BD) simulations of the cytoplasm model have been calibrated to reproduce the translational diffusion coefficients of Green Fluorescent Protein (GFP) observed in vivo, and “snapshots” of the simulation trajectories have been used to compute the cytoplasm's effects on the thermodynamics of protein folding, association and aggregation events. The simulation model successfully describes the relative thermodynamic stabilities of proteins measured in E. coli, and shows that effects additional to the commonly cited “crowding” effect must be included in attempts to understand macromolecular behavior in vivo