Subsurface Reflectors Detected by SHARAD Reveal Stratigraphy and Buried Channels over Central Elysium Planitia, Mars

The Central Elysium Planitia (CEP) is one of the youngest geological units on Mars and displays evidence of volcanic and fluvial activities on the surface. The origin of the CEP material has long been debated with a range of hypotheses from purely fluvial to solely volcanic origins. This study presents a comprehensive investigation of SHARAD (SHAllow RADar) data to reveal subsurface radar reflectors over the CEP region. Distribution of the detected radar reflectors show possible connections between the CEP and outflow channels, such as Athabasca Valles and Marte Vallis. Analysis of the radar reflectors in the CEP region show six subsurface layers implying multiple depositional and erosional episodes. Two of the layers are found to correspond to two exposed layers of one terraced crater. By measuring the depth accurately of these exposed layers in the derived HiRISE (High Resolution Imaging Scientific Experiment) and CTX (Context Camera) DTMs (Digital Terrain Models) and inverting the dielectric constant combining the layers in radargrams, an interpretation that the filling material contains water ice is favoured

Metamaterials with conformational nonlinearity

Within a decade of fruitful development, metamaterials became a prominent area of research, bridging theoretical and applied electrodynamics, electrical engineering and material science. Being man-made structures, metamaterials offer a particularly useful playground to develop interdisciplinary concepts. Here we demonstrate a novel principle in metamaterial assembly which integrates electromagnetic, mechanical, and thermal responses within their elements. Through these mechanisms, the conformation of the meta-molecules changes, providing a dual mechanism for nonlinearity and offering nonlinear chirality. Our proposal opens a wide road towards further developments of nonlinear metamaterials and photonic structures, adding extra flexibility to their design and control

Expression of Foxp3 in colorectal cancer but not in Treg cells correlates with disease progression in patients with colorectal cancer

Background: Regulatory T cells (Treg) expressing the transcription factor forkhead-box protein P3 (Foxp3) have been identified to counteract anti-tumor immune responses during tumor progression. Besides, Foxp3 presentation by cancer cells itself may also allow them to evade from effector T-cell responses, resulting in a survival benefit of the tumor. For colorectal cancer (CRC) the clinical relevance of Foxp3 has not been evaluated in detail. Therefore the aim of this study was to study its impact in colorectal cancer (CRC). Methods and Findings: Gene and protein analysis of tumor tissues from patients with CRC was performed to quantify the expression of Foxp3 in tumor infiltrating Treg and colon cancer cells. The results were correlated with clinicopathological parameters and patients overall survival. Serial morphological analysis demonstrated Foxp3 to be expressed in cancer cells. High Foxp3 expression of the cancer cells was associated with poor prognosis compared to patients with low Foxp3 expression. In contrast, low and high Foxp3 level in tumor infiltrating Treg cells demonstrated no significant differences in overall patient survival. Conclusions: Our findings strongly suggest that Foxp3 expression mediated by cancer cells rather than by Treg cells contribute to disease progression

A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems

In this paper we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware-experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results

MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

Heavy Squarks at the LHC

The LHC, with its seven-fold increase in energy over the Tevatron, is capable of probing regions of SUSY parameter space exhibiting qualitatively new collider phenomenology. Here we investigate one such region in which first generation squarks are very heavy compared to the other superpartners. We find that the production of these squarks, which is dominantly associative, only becomes rate-limited at mSquark > 4(5) TeV for L~10(100) fb-1. However, discovery of this scenario is complicated because heavy squarks decay primarily into a jet and boosted gluino, yielding a dijet-like topology with missing energy (MET) pointing along the direction of the second hardest jet. The result is that many signal events are removed by standard jet/MET anti-alignment cuts designed to guard against jet mismeasurement errors. We suggest replacing these anti-alignment cuts with a measurement of jet substructure that can significantly extend the reach of this channel while still removing much of the background. We study a selection of benchmark points in detail, demonstrating that mSquark= 4(5) TeV first generation squarks can be discovered at the LHC with L~10(100)fb-1

Top Quarks as a Window to String Resonances

We study the discovery potential of string resonances decaying to $t\bar{t}$ final state at the LHC. We point out that top quark pair production is a promising and an advantageous channel for studying such resonances, due to their low Standard Model background and unique kinematics. We study the invariant mass distribution and angular dependence of the top pair production cross section via exchanges of string resonances. The mass ratios of these resonances and the unusual angular distribution may help identify their fundamental properties and distinguish them from other new physics. We find that string resonances for a string scale below 4 TeV can be detected via the $t\bar{t}$ channel, either from reconstructing the $t\bar{t}$ semi-leptonic decay or recent techniques in identifying highly boosted tops.Comment: 22 pages, 6 figure

Climate warming leads to divergent succession of grassland microbial communities

Accurate climate projections require an understanding of the effects of warming on ecological communities and the underlying mechanisms that drive them . However, little is known about the effects of climate warming on the succession of microbial communities . Here we examined the temporal succession of soil microbes in a long-term climate change experiment at a tall-grass prairie ecosystem. Experimental warming was found to significantly alter the community structure of bacteria and fungi. By determining the time-decay relationships and the paired differences of microbial communities under warming and ambient conditions, experimental warming was shown to lead to increasingly divergent succession of the soil microbial communities, with possibly higher impacts on fungi than bacteria. Variation partition- and null model-based analyses indicate that stochastic processes played larger roles than deterministic ones in explaining microbial community taxonomic and phylogenetic compositions. However, in warmed soils, the relative importance of stochastic processes decreased over time, indicating a potential deterministic environmental filtering elicited by warming. Although successional trajectories of microbial communities are difficult to predict under future climate change scenarios, their composition and structure are projected to be less variable due to warming-driven selection. 1–3 4,

Resistance of Foxp3+ Regulatory T Cells to Nur77-Induced Apoptosis Promotes Allograft Survival

The NR4A nuclear receptor family member Nur77 (NR4A1) promotes thymocyte apoptosis during negative selection of autoreactive thymocytes, but may also function in mature extrathymic T cells. We studied the effects of over-expression of Nur77 on the apoptosis of murine peripheral T cells, including thymic-derived Foxp3+ regulatory (Treg) cells. Overexpression of Nur77 in the T cell lineage decreased numbers of peripheral CD4 and CD8 T cells by ∼80% compared to wild-type (WT) mice. However, the proportions of Treg cells were markedly increased in the thymus (61% of CD4+Foxp3+ singly positive thymocytes vs. 8% in WT) and secondary lymphoid organs (40–50% of CD4+Foxp3+ T cells vs. 7–8% in WT) of Nur77 transgenic (Nur77Tg) mice, and immunoprecipitation studies showed Nur77 was associated with a recently identified HDAC7/Foxp3 transcriptional complex. Upon activation through the T cell receptor in vitro or in vivo, Nur77Tg T cells showed only marginally decreased proliferation but significantly increased apoptosis. Fully allogeneic cardiac grafts transplanted to Nur77Tg mice survived long-term with well-preserved structure, and recipient splenocytes showed markedly enhanced apoptosis and greatly reduced anti-donor recall responses. Allografts in Nur77Tg recipients had significantly increased expression of multiple Treg-associated genes, including Foxp3, Foxp1, Tip60 and HDAC9. Allograft rejection was restored by CD25 monoclonal antibody therapy, indicating that allograft acceptance was dependent upon Treg function in Nur77Tg recipients. These data show that compared to conventional CD4 and CD8 T cells, Foxp3+ Tregs are relatively resistant to Nur77-mediated apoptosis, and that tipping the balance between the numbers of Tregs and responder T cells in the early period post-transplantation can determine the fate of the allograft. Hence, induced expression of Nur77 might be a novel means to achieve long-term allograft survival