On the Predictive Information of Futures' Prices: A Wavelet‐Based Assessment

While in speculative markets forward prices could be regarded as natural predictors for future spot rates, empirically, forward prices often fail to indicate ex ante the direction of price movements. In terms of forecasting, the random walk approximation of speculative prices has been established to provide ‘naive’ predictors that are most difficult to outperform by both purely backward‐looking time series models and more structural approaches processing information from forward markets. We empirically assess the implicit predictive content of forward prices by means of wavelet‐based prediction of two foreign exchange (FX) rates and the price of Brent oil quoted either in US dollars or euros. Essentially, wavelet‐based predictors are smoothed auxiliary (padded) time series quotes that are added to the sample information beyond the forecast origin. We compare wavelet predictors obtained from padding with constant prices (i.e. random walk predictors) and forward prices. For the case of FX markets, padding with forward prices is more effective than padding with constant prices, and, moreover, respective wavelet‐based predictors outperform purely backward‐looking time series approaches (ARIMA). For the case of Brent oil quoted in US dollars, wavelet‐based predictors do not signal predictive content of forward prices for future spot prices. Copyright © 2016 John Wiley & Sons, Ltd.     

Mutations in the gene encoding the synaptic scaffolding protein SHANK3 are associated with autism spectrum disorders

SHANK3 (also known as ProSAP2) regulates the structural organization of dendritic spines and is a binding partner of neuroligins; genes encoding neuroligins are mutated in autism and Asperger syndrome. Here, we report that a mutation of a single copy of SHANK3 on chromosome 22q13 can result in language and/or social communication disorders. These mutations concern only a small number of individuals, but they shed light on one gene dosage-sensitive synaptic pathway that is involved in autism spectrum disorders.     

Suppression of crystal nucleation in polydisperse colloids due to increase of the surface free energy

The formation of small crystallites is governed by two competing factors: the free energy gained upon transferring constituent atoms, molecules or colloidal particles from the metastable liquid to the more stable solid, and the free energy needed to create the surface area of the crystallite. Because the ratio of surface area to bulk is large for small particles, small crystallites dissolve spontaneously under conditions where larger crystallites are stable and macroscopic crystal growth occurs only if spontaneously formed crystallites exceed a critical minimum size. On theoretical grounds, the probability of forming such critical crystal nuclei is expected to increase rapidly with supersaturation. However, experiments show that the rate of crystal nucleation in many systems goes through a maximum as the supersaturation is increased. It is commonly assumed that the nucleation rate peaks because, even though the probability of forming critical nuclei increases with increasing concentration, the rate of growth of such nuclei decreases. Here we report simulations of crystal nucleation in suspensions of colloidal spheres with varying size distributions that show that the probability that critical nuclei will form itself goes through a maximum as the supersaturation is increased. We find that this effect, which is strongest for systems with the broadest particle size distribution, results from an increase with supersaturation of the solid-liquid interfacial free energy. The magnitude of this effect suggests that vitrification at high supersaturations should yield colloidal glasses that are truly amorphous, rather than nano-crystalline.     

Continental-scale patterns of canopy tree composition and function across Amazonia

The world's greatest terrestrial stores of biodiversity and carbon are found in the forests of northern South America, where large-scale biogeographic patterns and processes have recently begun to be described. Seven of the nine countries with territory in the Amazon basin and the Guiana shield have carried out large-scale forest inventories, but such massive data sets have been little exploited by tropical plant ecologists. Although forest inventories often lack the species-level identifications favoured by tropical plant ecologists, their consistency of measurement and vast spatial coverage make them ideally suited for numerical analyses at large scales, and a valuable resource to describe the still poorly understood spatial variation of biomass, diversity, community composition and forest functioning across the South American tropics. Here we show, by using the seven forest inventories complemented with trait and inventory data collected elsewhere, two dominant gradients in tree composition and function across the Amazon, one paralleling a major gradient in soil fertility and the other paralleling a gradient in dry season length. The data set also indicates that the dominance of Fabaceae in the Guiana shield is not necessarily the result of root adaptations to poor soils (nodulation or ectomycorrhizal associations) but perhaps also the result of their remarkably high seed mass there as a potential adaptation to low rates of disturbance.     

Structure of the insulin receptor ectodomain reveals a folded-over conformation

The insulin receptor is a phylogenetically ancient tyrosine kinase receptor found in organisms as primitive as cnidarians and insects. In higher organisms it is essential for glucose homeostasis, whereas the closely related insulin-like growth factor receptor (IGF-1R) is involved in normal growth and development. The insulin receptor is expressed in two isoforms, IR-A and IR-B; the former also functions as a high-affinity receptor for IGF-II and is implicated, along with IGF-1R, in malignant transformation. Here we present the crystal structure at 3.8 A resolution of the IR-A ectodomain dimer, complexed with four Fabs from the monoclonal antibodies 83-7 and 83-14 (ref. 4), grown in the presence of a fragment of an insulin mimetic peptide. The structure reveals the domain arrangement in the disulphide-linked ectodomain dimer, showing that the insulin receptor adopts a folded-over conformation that places the ligand-binding regions in juxtaposition. This arrangement is very different from previous models. It shows that the two L1 domains are on opposite sides of the dimer, too far apart to allow insulin to bind both L1 domains simultaneously as previously proposed. Instead, the structure implicates the carboxy-terminal surface of the first fibronectin type III domain as the second binding site involved in high-affinity binding.     

G1-phase progression in pluripotent stem cells

Cellular and Molecular Life Sciences - During early embryonic development both the rapid increase in cell number and the expression of genes that control developmental decisions are tightly...     

Chance and necessity in the evolution of minimal metabolic networks

It is possible to infer aspects of an organism's lifestyle from its gene content. Can the reverse also be done? Here we consider this issue by modelling evolution of the reduced genomes of endosymbiotic bacteria. The diversity of gene content in these bacteria may reflect both variation in selective forces and contingency-dependent loss of alternative pathways. Using an in silico representation of the metabolic network of Escherichia coli, we examine the role of contingency by repeatedly simulating the successive loss of genes while controlling for the environment. The minimal networks that result are variable in both gene content and number. Partially different metabolisms can thus evolve owing to contingency alone. The simulation outcomes do preserve a core metabolism, however, which is over-represented in strict intracellular bacteria. Moreover, differences between minimal networks based on lifestyle are predictable: by simulating their respective environmental conditions, we can model evolution of the gene content in Buchnera aphidicola and Wigglesworthia glossinidia with over 80% accuracy. We conclude that, at least for the particular cases considered here, gene content of an organism can be predicted with knowledge of its distant ancestors and its current lifestyle.