Crystal structure of the β2 adrenergic receptor-Gs protein complex

G protein-coupled receptors (GPCRs) are responsible for the majority of cellular responses to hormones and neurotransmitters as well as the senses of sight, olfaction and taste. The paradigm of GPCR signalling is the activation of a heterotrimeric GTP binding protein (G protein) by an agonist-occupied receptor. The β(2) adrenergic receptor (β(2)AR) activation of Gs, the stimulatory G protein for adenylyl cyclase, has long been a model system for GPCR signalling. Here we present the crystal structure of the active state ternary complex composed of agonist-occupied monomeric β(2)AR and nucleotide-free Gs heterotrimer. The principal interactions between the β(2)AR and Gs involve the amino- and carboxy-terminal α-helices of Gs, with conformational changes propagating to the nucleotide-binding pocket. The largest conformational changes in the β(2)AR include a 14 ? outward movement at the cytoplasmic end of transmembrane segment 6 (TM6) and an α-helical extension of the cytoplasmic end of TM5. The most surprising observation is a major displacement of the α-helical domain of Gαs relative to the Ras-like GTPase domain. This crystal structure represents the first high-resolution view of transmembrane signalling by a GPCR.     

Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation

Atmospheric aerosols exert an important influence on climate through their effects on stratiform cloud albedo and lifetime and the invigoration of convective storms. Model calculations suggest that almost half of the global cloud condensation nuclei in the atmospheric boundary layer may originate from the nucleation of aerosols from trace condensable vapours, although the sensitivity of the number of cloud condensation nuclei to changes of nucleation rate may be small. Despite extensive research, fundamental questions remain about the nucleation rate of sulphuric acid particles and the mechanisms responsible, including the roles of galactic cosmic rays and other chemical species such as ammonia. Here we present the first results from the CLOUD experiment at CERN. We find that atmospherically relevant ammonia mixing ratios of 100 parts per trillion by volume, or less, increase the nucleation rate of sulphuric acid particles more than 100-1,000-fold. Time-resolved molecular measurements reveal that nucleation proceeds by a base-stabilization mechanism involving the stepwise accretion of ammonia molecules. Ions increase the nucleation rate by an additional factor of between two and more than ten at ground-level galactic-cosmic-ray intensities, provided that the nucleation rate lies below the limiting ion-pair production rate. We find that ion-induced binary nucleation of H(2)SO(4)-H(2)O can occur in the mid-troposphere but is negligible in the boundary layer. However, even with the large enhancements in rate due to ammonia and ions, atmospheric concentrations of ammonia and sulphuric acid are insufficient to account for observed boundary-layer nucleation.     

Conjugated action of two species-specific invasion proteins for fetoplacental listeriosis

The ability to cross host barriers is an essential virulence determinant of invasive microbial pathogens. Listeria monocytogenes is a model microorganism that crosses human intestinal and placental barriers, and causes severe maternofetal infections by an unknown mechanism. Several studies have helped to characterize the bacterial invasion proteins InlA and InlB. However, their respective species specificity has complicated investigations on their in vivo role. Here we describe two novel and complementary animal models for human listeriosis: the gerbil, a natural host for L. monocytogenes, and a knock-in mouse line ubiquitously expressing humanized E-cadherin. Using these two models, we uncover the essential and interdependent roles of InlA and InlB in fetoplacental listeriosis, and thereby decipher the molecular mechanism underlying the ability of a microbe to target and cross the placental barrier.     

Adaptive Evolutionary Neural Networks for Forecasting and Trading without a Data‐Snooping Bias

In this paper, we present two neural‐network‐based techniques: an adaptive evolutionary multilayer perceptron (aDEMLP) and an adaptive evolutionary wavelet neural network (aDEWNN). The two models are applied to the task of forecasting and trading the SPDR Dow Jones Industrial Average (DIA), the iShares NYSE Composite Index Fund (NYC) and the SPDR S&P 500 (SPY) exchange‐traded funds (ETFs). We benchmark their performance against two traditional MLP and WNN architectures, a smooth transition autoregressive model (STAR), a moving average convergence/divergence model (MACD) and a random walk model. We show that the proposed architectures present superior forecasting and trading performance compared to the benchmarks and are free from the limitations of the traditional neural networks such as the data‐snooping bias and the time‐consuming and biased processes involved in optimizing their parameters. Copyright © 2015 John Wiley & Sons, Ltd.     

Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms

This paper presents an application of the gene expression programming (GEP) and integrated genetic programming (GP) algorithms to the modelling of ASE 20 Greek index. GEP and GP are robust evolutionary algorithms that evolve computer programs in the form of mathematical expressions, decision trees or logical expressions. The results indicate that GEP and GP produce significant trading performance when applied to ASE 20 and outperform the well‐known existing methods. The trading performance of the derived models is further enhanced by applying a leverage filter. Copyright © 2014 John Wiley & Sons, Ltd.     

Structural basis of Dscam isoform specificity

The Dscam gene gives rise to thousands of diverse cell surface receptors thought to provide homophilic and heterophilic recognition specificity for neuronal wiring and immune responses. Mutually exclusive splicing allows for the generation of sequence variability in three immunoglobulin ecto-domains, D2, D3 and D7. We report X-ray structures of the amino-terminal four immunoglobulin domains (D1-D4) of two distinct Dscam isoforms. The structures reveal a horseshoe configuration, with variable residues of D2 and D3 constituting two independent surface epitopes on either side of the receptor. Both isoforms engage in homo-dimerization coupling variable domain D2 with D2, and D3 with D3. These interactions involve symmetric, antiparallel pairing of identical peptide segments from epitope I that are unique to each isoform. Structure-guided mutagenesis and swapping of peptide segments confirm that epitope I, but not epitope II, confers homophilic binding specificity of full-length Dscam receptors. Phylogenetic analysis shows strong selection of matching peptide sequences only for epitope I. We propose that peptide complementarity of variable residues in epitope I of Dscam is essential for homophilic binding specificity.     

Model Reference Adaptive Control for Networked Distributed Systems with Strong Interconnections and Communication Delays

In recent years, networked distributed control systems (NDCS) have received research attention. Two of the main challenges that such systems face are possible delays in the communication network and the effect of strong interconnections between agents. This paper considers an NDCS that has delays in the communication network, as well as strong interconnections between its agents. The control objective is to make each agent track efficiently a reference model by attenuating the effect of strong interconnections via feedback based on the delayed information. First, the authors assume that each agent knows its own dynamics, as well as the interconnection parameters, but receives information about the states of its neighbors with some communication delay. The authors propose a distributed control scheme and prove that if the interconnections can be weakened and if the communication delays are small enough, then the proposed scheme guarantees that the tracking error of each agent is bounded with a bound that depends on the size of the weakened interconnections and delays, and reduces to zero as these uncertainties reduce to zero. The authors then consider a more realistic situation where the interconnections between agents are unknown despite the cooperation and sharing of state information. For this case the authors propose a distributed adaptive control scheme and prove that the proposed scheme guarantees that the tracking errors are bounded and small in the mean square sense with respect to the size of the weakened interconnections and delays, provided the weakened interconnections and time delays are small enough. The authors then consider the case that each agent knows neither its dynamics nor the interconnection matrices. For this case the authors propose a distributed adaptive control scheme and prove that the proposed scheme guarantees that the tracking errors are bounded and small in the mean square sense provided the weakened interconnections and time delays are small enough. Finally, the authors present an illustrative example to present the applicability and effectiveness of the proposed schemes.     

On the use of power transformations in CAViaR models

Value at risk (VaR) is a risk measure widely used by financial institutions in allocating risk. VaR forecast estimation involves the conditional evaluation of quantiles based on the currently available information. Recent advances in VaR evaluation incorporate a proxy for conditional variance, yielding the conditional autoregressive VaR (CAViaR) models. However, early work in finance literature has shown that the introduction of power transformations has resulted in improvements in volatility forecasting. Having a direct association between volatility and conditional VaR, we adopt power-transformed CAViaR models. We investigate whether the flexible conditional VaR dynamics associated with power-transformed CAViaR models can result in better forecasting results than those assumed by the nontransformed CAViaR models. Estimation in CAViaR models is based on an early-rejection Markov chain Monte Carlo algorithm. We illustrate our forecasting evaluation results using simulated and financial daily return data series. The results demonstrate that there is strong evidence that supports the use of power-transformed CAViaR models when forecasting VaR.     

The product of the γ-secretase processing of ephrinB2 regulates VE-cadherin complexes and angiogenesis

Presenilin-1 (PS1) gene encodes the catalytic component of γ-secretase, which proteolytically processes several type I transmembrane proteins. We here present evidence that the cytosolic peptide efnB2/CTF2 produced by the PS1/γ-secretase cleavage of efnB2 ligand promotes EphB4 receptor-dependent angiogenesis in vitro. EfnB2/CTF2 increases endothelial cell sprouting and tube formation, stimulates the formation of angiogenic complexes that include VE-cadherin, Raf-1 and Rok-α, and increases MLC2 phosphorylation. These functions are mediated by the PDZ-binding domain of efnB2. Acute downregulation of PS1 or inhibition of γ-secretase inhibits the angiogenic functions of EphB4 while absence of PS1 decreases the VE-cadherin angiogenic complexes of mouse brain. Our data reveal a mechanism by which PS1/γ-secretase regulates efnB2/EphB4 mediated angiogenesis.     

Molecular engineering of a backwards-moving myosin motor

All members of the diverse myosin superfamily have a highly conserved globular motor domain that contains the actin- and nucleotide-binding sites and produces force and movement. The light-chain-binding domain connects the motor domain to a variety of functionally specialized tail domains and amplifies small structural changes in the motor domain through rotation of a lever arm. Myosins move on polarized actin filaments either forwards to the barbed (+) or backwards to the pointed (-) end. Here, we describe the engineering of an artificial backwards-moving myosin from three pre-existing molecular building blocks. These blocks are: a forward-moving class I myosin motor domain, a directional inverter formed by a four-helix bundle segment of human guanylate-binding protein-1 and an artificial lever arm formed by two alpha-actinin repeats. Our results prove that reverse-direction movement of myosins can be achieved simply by rotating the direction of the lever arm 180 degrees.