Tailward Propagation of Magnetic Energy Density Variations With Respect to Substorm Onset Times

t During geomagnetic substorms, around 1015 J of energy is extracted from the solar wind and processed by the Earth’s magnetosphere. Prior to the onset of substorm expansion phases, this energy is thought to be largely stored as an increase in the magnetic field in the magnetotail lobes. However, how, when, and where this energy is stored and released within the magnetotail is unclear. Using data from the Cluster spacecraft and substorm onsets from Substorm Onsets and Phases from Indices of the Electrojet (SOPHIE), we examine the variation in the lobe magnetic energy density with respect to substorm onset for 541 isolated onsets. Based on a cross-correlation analysis and a simple model, we deduce the following: On average, the magnetic energy density increases approximately linearly in the hour preceding onset and decreases at a similar rate after onset. The timing and magnitude of these changes varies with downtail distance, with observations from the mid-tail (X ⪅ −9 RE) showing larger changes in the magnetic energy density that occur ∼ 20 min after changes in the near-tail (X ⪆ −9 RE). The decrease in energy density in the near-tail region is observed before the ground onset identified by SOPHIE, implying that the substorm is driven from the magnetotail and propagates into the ionosphere. The implication of these results is that energy in the near-tail region is released first during the substorm expansion phase, with energy conversion propagating away from the Earth with time

Non-cell autonomous influence of the astrocyte system xc− on hypoglycaemic neuronal cell death

Despite longstanding evidence that hypoglycaemic neuronal injury is mediated by glutamate excitotoxicity, the cellular and molecular mechanisms involved remain incompletely defined. Here, we demonstrate that the excitotoxic neuronal death that follows GD (glucose deprivation) is initiated by glutamate extruded from astrocytes via system xc− – an amino acid transporter that imports l-cystine and exports l-glutamate. Specifically, we find that depriving mixed cortical cell cultures of glucose for up to 8 h injures neurons, but not astrocytes. Neuronal death is prevented by ionotropic glutamate receptor antagonism and is partially sensitive to tetanus toxin. Removal of amino acids during the deprivation period prevents – whereas addition of l-cystine restores – GD-induced neuronal death, implicating the cystine/glutamate antiporter, system xc−. Indeed, drugs known to inhibit system xc− ameliorate GD-induced neuronal death. Further, a dramatic reduction in neuronal death is observed in chimaeric cultures consisting of neurons derived from WT (wild-type) mice plated on top of astrocytes derived from sut mice, which harbour a naturally occurring null mutation in the gene (Slc7a11) that encodes the substrate-specific light chain of system xc− (xCT). Finally, enhancement of astrocytic system xc− expression and function via IL-1β (interleukin-1β) exposure potentiates hypoglycaemic neuronal death, the process of which is prevented by removal of l-cystine and/or addition of system xc− inhibitors. Thus, under the conditions of GD, our studies demonstrate that astrocytes, via system xc−, have a direct, non-cell autonomous effect on cortical neuron survival

Multi-model estimates of atmospheric lifetimes of long-lived ozone-depleting substances: present and future

We have diagnosed the lifetimes of long-lived source gases emitted at the surface and removed in the stratosphere using six three-dimensional chemistry-climate models and a two-dimensional model. The models all used the same standard photochemical data. We investigate the effect of different definitions of lifetimes, including running the models with both mixing ratio (MBC) and flux (FBC) boundary conditions. Within the same model, the lifetimes diagnosed by different methods agree very well. Using FBCs versus MBCs leads to a different tracer burden as the implied lifetime contained in the MBC value does not necessarily match a model's own calculated lifetime. In general, there are much larger differences in the lifetimes calculated by different models, the main causes of which are variations in the modeled rates of ascent and horizontal mixing in the tropical midlower stratosphere. The model runs have been used to compute instantaneous and steady state lifetimes. For chlorofluorocarbons (CFCs) their atmospheric distribution was far from steady state in their growth phase through to the 1980s, and the diagnosed instantaneous lifetime is accordingly much longer. Following the cessation of emissions, the resulting decay of CFCs is much closer to steady state. For 2100 conditions the model circulation speeds generally increase, but a thicker ozone layer due to recovery and climate change reduces photolysis rates. These effects compensate so the net impact on modeled lifetimes is small. For future assessments of stratospheric ozone, use of FBCs would allow a consistent balance between rate of CFC removal and model circulation rate

Mitogenomic phylogenetic analyses of the Delphinidae with an emphasis on the Globicephalinae

BACKGROUND: Previous DNA-based phylogenetic studies of the Delphinidae family suggest it has undergone rapid diversification, as characterised by unresolved and poorly supported taxonomic relationships (polytomies) for some of the species within this group. Using an increased amount of sequence data we test between alternative hypotheses of soft polytomies caused by rapid speciation, slow evolutionary rate and/or insufficient sequence data, and hard polytomies caused by simultaneous speciation within this family. Combining the mitogenome sequences of five new and 12 previously published species within the Delphinidae, we used Bayesian and maximum-likelihood methods to estimate the phylogeny from partitioned and unpartitioned mitogenome sequences. Further ad hoc tests were then conducted to estimate the support for alternative topologies. RESULTS: We found high support for all the relationships within our reconstructed phylogenies, and topologies were consistent between the Bayesian and maximum-likelihood trees inferred from partitioned and unpartitioned data. Resolved relationships included the placement of the killer whale (Orcinus orca) as sister taxon to the rest of the Globicephalinae subfamily, placement of the Risso's dolphin (Grampus griseus) within the Globicephalinae subfamily, removal of the white-beaked dolphin (Lagenorhynchus albirostris) from the Delphininae subfamily and the placement of the rough-toothed dolphin (Steno bredanensis) as sister taxon to the rest of the Delphininae subfamily rather than within the Globicephalinae subfamily. The additional testing of alternative topologies allowed us to reject all other putative relationships, with the exception that we were unable to reject the hypothesis that the relationship between L. albirostris and the Globicephalinae and Delphininae subfamilies was polytomic. CONCLUSION: Despite their rapid diversification, the increased sequence data yielded by mitogenomes enables the resolution of a strongly supported, bifurcating phylogeny, and a chronology of the divergences within the Delphinidae family. This highlights the benefits and potential application of large mitogenome datasets to resolve long-standing phylogenetic uncertainties

A Novel Classification of Lung Cancer into Molecular Subtypes

The remarkably heterogeneous nature of lung cancer has become more apparent over the last decade. In general, advanced lung cancer is an aggressive malignancy with a poor prognosis. The discovery of multiple molecular mechanisms underlying the development, progression, and prognosis of lung cancer, however, has created new opportunities for targeted therapy and improved outcome. In this paper, we define “molecular subtypes” of lung cancer based on specific actionable genetic aberrations. Each subtype is associated with molecular tests that define the subtype and drugs that may potentially treat it. We hope this paper will be a useful guide to clinicians and researchers alike by assisting in therapy decision making and acting as a platform for further study. In this new era of cancer treatment, the ‘one-size-fits-all’ paradigm is being forcibly pushed aside—allowing for more effective, personalized oncologic care to emerge

Multiple Data Analyses and Statistical Approaches for Analyzing Data from Metagenomic Studies and Clinical Trials

Metagenomics, also known as environmental genomics, is the study of the genomic content of a sample of organisms (microbes) obtained from a common habitat. Metagenomics and other “omics” disciplines have captured the attention of researchers for several decades. The effect of microbes in our body is a relevant concern for health studies. There are plenty of studies using metagenomics which examine microorganisms that inhabit niches in the human body, sometimes causing disease, and are often correlated with multiple treatment conditions. No matter from which environment it comes, the analyses are often aimed at determining either the presence or absence of specific species of interest in a given metagenome or comparing the biological diversity and the functional activity of a wider range of microorganisms within their communities. The importance increases for comparison within different environments such as multiple patients with different conditions, multiple drugs, and multiple time points of same treatment or same patient. Thus, no matter how many hypotheses we have, we need a good understanding of genomics, bioinformatics, and statistics to work together to analyze and interpret these datasets in a meaningful way. This chapter provides an overview of different data analyses and statistical approaches (with example scenarios) to analyze metagenomics samples from different medical projects or clinical trials

Cognition and bimanual performance in children with unilateral cerebral palsy: Protocol for a multicentre, cross-sectional study

© 2018 The Author(s). Background: Motor outcomes of children with unilateral cerebral palsy are clearly documented and well understood, yet few studies describe the cognitive functioning in this population, and the associations between the two is poorly understood. Using two hands together in daily life involves complex motor and cognitive processes. Impairment in either domain may contribute to difficulties with bimanual performance. Research is yet to derive whether, and how, cognition affects a child's ability to use their two hands to perform bimanual tasks. Methods/Design: This study will use a prospective, cross-sectional multi-centre observational design. Children (aged 6-12 years) with unilateral cerebral palsy will be recruited from one of five Australian treatment centres. We will examine associations between cognition, bimanual performance and brain neuropathology (lesion type and severity) in a sample of 131 children. The primary outcomes are: Motor - the Assisting Hand Assessment; Cognitive - Executive Function; and Brain - lesion location on structural MRI. Secondary data collected will include: Motor - Box and Blocks, ABILHAND- Kids, Sword Test; Cognitive - standard neuropsychological measures of intelligence. We will use generalized linear modelling and structural equation modelling techniques to investigate relationships between bimanual performance, executive function and brain lesion location. Discussion: This large multi-centre study will examine how cognition affects bimanual performance in children with unilateral cerebral palsy. First, it is anticipated that distinct relationships between bimanual performance and cognition (executive function) will be identified. Second, it is anticipated that interrelationships between bimanual performance and cognition will be associated with common underlying neuropathology. Findings have the potential to improve the specificity of existing upper limb interventions by providing more targeted treatments and influence the development of novel methods to improve both cognitive and motor outcomes in children with unilateral cerebral palsy

Climate simulations for 1880-2003 with GISS modelE

We carry out climate simulations for 1880-2003 with GISS modelE driven by ten measured or estimated climate forcings. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880-2003 forcings, we aim to provide a benchmark against which the effect of improvements in the model, climate forcings, and observations can be tested. Principal model deficiencies include unrealistically weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. The greatest uncertainties in the forcings are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds.Comment: 44 pages; 19 figures; Final text accepted by Climate Dynamic

2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

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