Two distinct modes of guidance signalling during collective migration of border cells

Although directed migration is a feature of both individual cells and cell groups, guided migration has been studied most extensively for single cells in simple environments. Collective guidance of cell groups remains poorly understood, despite its relevance for development and metastasis. Neural crest cells and neuronal precursors migrate as loosely organized streams of individual cells, whereas cells of the fish lateral line, Drosophila tracheal tubes and border-cell clusters migrate as more coherent groups. Here we use Drosophila border cells to examine how collective guidance is performed. We report that border cells migrate in two phases using distinct mechanisms. Genetic analysis combined with live imaging shows that polarized cell behaviour is critical for the initial phase of migration, whereas dynamic collective behaviour dominates later. PDGF- and VEGF-related receptor and epidermal growth factor receptor act in both phases, but use different effector pathways in each. The myoblast city (Mbc, also known as DOCK180) and engulfment and cell motility (ELMO, also known as Ced-12) pathway is required for the early phase, in which guidance depends on subcellular localization of signalling within a leading cell. During the later phase, mitogen-activated protein kinase and phospholipase Cgamma are used redundantly, and we find that the cluster makes use of the difference in signal levels between cells to guide migration. Thus, information processing at the multicellular level is used to guide collective behaviour of a cell group.     

Studies on thermally grown oxide as an interface between plasma-sprayed coatings and a nickel-based superalloy substrate

A thermally grown oxide layer formed by hot corrosion was investigated as an interface between plasma-sprayed coatings and a nickel-based superalloy substrate. The hot corrosion mechanism of NiCr-Cr₂O₃ and Al₂O₃-40wt% TiO₂ (A40T) plasma coated Inconel 617 was evaluated. The experiments were carried out at 1000℃ using a combination of Na₂SO₄, NaCl, and ₂O₅ salts to simulate the conditions of a gas turbine in a marine environment. The hot corrosion results revealed the spallation and dissolution of oxides upon prolonged exposure. Optical images and scanning electron micrographs of the exposed samples revealed the formation of oxide scale and provided details of its morphology in NiCr-Cr₂O₃ coated samples. Microstructure characterization of A40T coatings demonstrated a thermally grown oxide (TGO) layer at 1000℃. Increasing the thickness of the TGO layer decreased the corrosion resistance. The elemental analysis and image mapping revealed the migration of active elements from the substrate and coatings toward the corrosive environment.     

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.     

Engineered two-dimensional Ising interactions in a trapped-ion quantum simulator with hundreds of spins

The presence of long-range quantum spin correlations underlies a variety of physical phenomena in condensed-matter systems, potentially including high-temperature superconductivity. However, many properties of exotic, strongly correlated spin systems, such as spin liquids, have proved difficult to study, in part because calculations involving N-body entanglement become intractable for as few as N?≈?30 particles. Feynman predicted that a quantum simulator--a special-purpose 'analogue' processor built using quantum bits (qubits)--would be inherently suited to solving such problems. In the context of quantum magnetism, a number of experiments have demonstrated the feasibility of this approach, but simulations allowing controlled, tunable interactions between spins localized on two- or three-dimensional lattices of more than a few tens of qubits have yet to be demonstrated, in part because of the technical challenge of realizing large-scale qubit arrays. Here we demonstrate a variable-range Ising-type spin-spin interaction, J(i,j), on a naturally occurring, two-dimensional triangular crystal lattice of hundreds of spin-half particles (beryllium ions stored in a Penning trap). This is a computationally relevant scale more than an order of magnitude larger than previous experiments. We show that a spin-dependent optical dipole force can produce an antiferromagnetic interaction J(i,j) proportional variant d(-a)(i,j), where 0?≤?a?≤?3 and d(i,j) is the distance between spin pairs. These power laws correspond physically to infinite-range (a = 0), Coulomb-like (a = 1), monopole-dipole (a = 2) and dipole-dipole (a = 3) couplings. Experimentally, we demonstrate excellent agreement with a theory for 0.05???a???1.4. This demonstration, coupled with the high spin count, excellent quantum control and low technical complexity of the Penning trap, brings within reach the simulation of otherwise computationally intractable problems in quantum magnetism.     

On the Benefits of Equicorrelation for Portfolio Allocation

The importance of modelling correlation has long been recognised in the field of portfolio management, with large‐dimensional multivariate problems increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating a number of models used to generate forecasts of the correlation matrix for large‐dimensional problems. We find evidence in favour of assuming equicorrelation across various portfolio sizes, particularly during times of crisis. During periods of market calm, however, the suitability of the constant conditional correlation model cannot be discounted, especially for large portfolios. A portfolio allocation problem is used to compare forecasting methods. The global minimum variance portfolio and Model Confidence Set are used to compare methods, while portfolio weight stability and relative economic value are also considered. Copyright © 2015 John Wiley & Sons, Ltd.     

Bayesian Analysis of Asymmetric Stochastic Conditional Duration Model

This paper proposes Markov chain Monte Carlo methods to estimate the parameters and log durations of the correlated or asymmetric stochastic conditional duration models. Following the literature, instead of fitting the models directly, the observation equation of the models is first subjected to a logarithmic transformation. A correlation is then introduced between the transformed innovation and the latent process in an attempt to improve the statistical fits of the models. In order to perform one‐step‐ahead in‐sample and out‐of‐sample duration forecasts, an auxiliary particle filter is used to approximate the filter distributions of the latent states. Simulation studies and application to the IBM transaction dataset illustrate that our proposed estimation methods work well in terms of parameter and log duration estimation. Copyright © 2014 John Wiley & Sons, Ltd.     

Novel putative receptor tyrosine kinase encoded by the melanoma-inducing Tu locus in Xiphophorus

Malignant melanoma in Xiphophorus fish hybrids is caused by the activity of a dominant oncogene Tu. By combining genetic and molecular approaches, we have isolated the melanoma oncogene. We show that its level of expression correlates with the degree of malignancy of the tumour. The corresponding proto-oncogene is developmentally regulated. The Tu gene codes for a novel receptor tyrosine kinase which is closely related to the receptor for epidermal growth factor.