Higgs and Dark Matter Hints of an Oasis in the Desert

Recent LHC results suggest a standard model (SM)-like Higgs boson in the vicinity of 125 GeV with no clear indications yet of physics beyond the SM. At the same time, the SM is incomplete, since additional dynamics are required to accommodate cosmological dark matter (DM). In this paper we show that interactions between weak scale DM and the Higgs which are strong enough to yield a thermal relic abundance consistent with observation can easily destabilize the electroweak vacuum or drive the theory into a non-perturbative regime at a low scale. As a consequence, new physics--beyond the DM itself--must enter at a cutoff well below the Planck scale and in some cases as low as O(10 - 1000 TeV), a range relevant to indirect probes of flavor and CP violation. In addition, this cutoff is correlated with the DM mass and scattering cross-section in a parameter space which will be probed experimentally in the near term. Specifically, we consider the SM plus additional spin 0 or 1/2 states with singlet, triplet, or doublet electroweak quantum numbers and quartic or Yukawa couplings to the Higgs boson. We derive explicit expressions for the full two-loop RGEs and one-loop threshold corrections for these theories.Comment: 29 pages, 13 figure

SNAI2/Slug promotes growth and invasion in human gliomas

<p>Abstract</p> <p>Background</p> <p>Numerous factors that contribute to malignant glioma invasion have been identified, but the upstream genes coordinating this process are poorly known.</p> <p>Methods</p> <p>To identify genes controlling glioma invasion, we used genome-wide mRNA expression profiles of primary human glioblastomas to develop an expression-based rank ordering of 30 transcription factors that have previously been implicated in the regulation of invasion and metastasis in cancer.</p> <p>Results</p> <p>Using this approach, we identified the oncogenic transcriptional repressor, <it>SNAI2</it>/Slug, among the upper tenth percentile of invasion-related transcription factors overexpressed in glioblastomas. <it>SNAI2 </it>mRNA expression correlated with histologic grade and invasive phenotype in primary human glioma specimens, and was induced by EGF receptor activation in human glioblastoma cells. Overexpression of <it>SNAI2/</it>Slug increased glioblastoma cell proliferation and invasion <it>in vitro </it>and promoted angiogenesis and glioblastoma growth <it>in vivo</it>. Importantly, knockdown of endogenous <it>SNAI2</it>/Slug in glioblastoma cells decreased invasion and increased survival in a mouse intracranial human glioblastoma transplantation model.</p> <p>Conclusion</p> <p>This genome-scale approach has thus identified <it>SNAI2</it>/Slug as a regulator of growth and invasion in human gliomas.</p

The Rewiring of Ubiquitination Targets in a Pathogenic Yeast Promotes Metabolic Flexibility, Host Colonization and Virulence

Funding: This work was funded by the European Research Council [http://erc.europa.eu/], AJPB (STRIFE Advanced Grant; C-2009-AdG-249793). The work was also supported by: the Wellcome Trust [www.wellcome.ac.uk], AJPB (080088, 097377); the UK Biotechnology and Biological Research Council [www.bbsrc.ac.uk], AJPB (BB/F00513X/1, BB/K017365/1); the CNPq-Brazil [http://cnpq.br], GMA (Science without Borders fellowship 202976/2014-9); and the National Centre for the Replacement, Refinement and Reduction of Animals in Research [www.nc3rs.org.uk], DMM (NC/K000306/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Acknowledgments We thank Dr. Elizabeth Johnson (Mycology Reference Laboratory, Bristol) for providing strains, and the Aberdeen Proteomics facility for the biotyping of S. cerevisiae clinical isolates, and to Euroscarf for providing S. cerevisiae strains and plasmids. We are grateful to our Microscopy Facility in the Institute of Medical Sciences for their expert help with the electron microscopy, and to our friends in the Aberdeen Fungal Group for insightful discussions.Peer reviewedPublisher PD

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

The effects of trastuzumab on the CD4+CD25+FoxP3+ and CD4+IL17A+ T-cell axis in patients with breast cancer

In addition to the direct targeting effects on HER2-positive cells, trastuzumab may have a therapeutic role modulating the activity of the cellular immune system in patients with breast cancer. To investigate this further, the balance of T-regulatory (Treg), Th17, natural killer (NK) and NK T (NKT) cells before, during and after trastuzumab therapy was investigated. Sequential frequencies of circulating Treg cells, Th17 cells, NK and NKT cells were measured in peripheral blood of breast cancer patients and normal controls throughout therapy. Individuals with breast cancer had significantly higher Treg frequencies of peripheral blood compared with healthy controls (9.2 or 8.6 vs 6%; P<0.05), and no significant differences in Treg frequencies were observed between HER2-positive and HER2-negative individuals. The number of Th17 cells was lowest in HER2-positive patients compared with both healthy controls and HER2-negative patients (0.31 vs 0.75% or 0.84%; P=0.01). There appeared to be an inverse relationship between Treg and Th17 frequencies in metastatic breast cancer (MBC) with Treg levels significantly reduced during treatment with trastuzumab (P=0.04), whereas Th17 frequencies were concomitantly increased (P=0.04). This study supports earlier data that Treg cells are present at higher frequencies in breast cancer patients compared with healthy individuals. For the first time, we show that HER2-positive individuals with breast carcinomas have reduced numbers of circulating Th17 cells, which appear, in turn to have an inverse relationship with Treg frequency in MBC. The change in balance of the Treg : Th17 ratio appears to characterise the cancer state, and furthermore, is disrupted by trastuzumab therapy

The dawn of the dead : (improbable) art after aI-zombie apocalypse

In recent years there has been growing interest in artificial neural networks (ANNs) which are quickly becoming the primary device for machine learning. Used for finding patterns in large data sets, ANNs were also recently employed in many artistic contexts: as tools for artists, semi-independent creators of content, and even as invisible "critics" which / who predict our aesthetic preferences. The aim of this paper is to speculate about the disruptive effect of these ‘alien agencies’ on the (modernist) aesthetic regime of art centred around the notion of autonomy. The author examines how neural networks and connectionist epistemologies may potentially affect the most common ways of producing, circulating, and valorising art. He claims that the possibility of automatizing creativity and art criticism may lead to the emergence of a new aesthetic regime based on forms of dynamic, distributed and probabilistic governance

Performance and Operation of the CMS Electromagnetic Calorimeter

The operation and general performance of the CMS electromagnetic calorimeter using cosmic-ray muons are described. These muons were recorded after the closure of the CMS detector in late 2008. The calorimeter is made of lead tungstate crystals and the overall status of the 75848 channels corresponding to the barrel and endcap detectors is reported. The stability of crucial operational parameters, such as high voltage, temperature and electronic noise, is summarised and the performance of the light monitoring system is presented

Functional and proteomic analysis of a full thickness filaggrin-deficient skin organoid model

Background: Atopic eczema is an itchy inflammatory disorder characterised by skin barrier dysfunction. Loss-of-function mutations in the gene encoding filaggrin (FLG) are a major risk factor, but the mechanisms by which filaggrin haploinsufficiency leads to atopic inflammation remain incompletely understood. Skin as an organ that can be modelled using primary cells in vitro provides the opportunity for selected genetic effects to be investigated in detail. Methods: Primary human keratinocytes and donor-matched primary fibroblasts from healthy individuals were used to create skin organoid models with and without siRNA-mediated knockdown of FLG. Biological replicate sets of organoids were assessed using histological, functional and biochemical measurements. Results: FLG knockdown leads to subtle changes in histology and ultrastructure including a reduction in thickness of the stratum corneum and smaller, less numerous keratohyalin granules. Immature organoids showed some limited evidence of barrier impairment with FLG knockdown, but the mature organoids showed no difference in transepidermal water loss, water content or dye penetration. There was no difference in epidermal ceramide content. Mass spectrometry proteomic analysis detected &gt;8000 proteins per sample. Gene ontology and pathway analyses identified an increase in transcriptional and translational activity but a reduction in proteins contributing to terminal differentiation, including caspase 14, dermokine, AKT1 and TGF-beta-1. Aspects of innate and adaptive immunity were represented in both the up-regulated and down-regulated protein groups, as was the term ‘axon guidance’. Conclusions: This work provides further evidence for keratinocyte-specific mechanisms contributing to immune and neurological, as well as structural, aspects of skin barrier dysfunction. Individuals with filaggrin deficiency may derive benefit from future therapies targeting keratinocyte-immune crosstalk and neurogenic pruritus

Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality

Background. Pre-operative risk assessments used in clinical practice are limited in their ability to identify risk for post-operative mortality. We hypothesize that electrocardiograms contain hidden risk markers that can help prognosticate post-operative mortality. Methods. In a derivation cohort of 45,969 pre-operative patients (age 59+- 19 years, 55 percent women), a deep learning algorithm was developed to leverage waveform signals from pre-operative ECGs to discriminate post-operative mortality. Model performance was assessed in a holdout internal test dataset and in two external hospital cohorts and compared with the Revised Cardiac Risk Index (RCRI) score. Results. In the derivation cohort, there were 1,452 deaths. The algorithm discriminates mortality with an AUC of 0.83 (95% CI 0.79-0.87) surpassing the discrimination of the RCRI score with an AUC of 0.67 (CI 0.61-0.72) in the held out test cohort. Patients determined to be high risk by the deep learning model's risk prediction had an unadjusted odds ratio (OR) of 8.83 (5.57-13.20) for post-operative mortality as compared to an unadjusted OR of 2.08 (CI 0.77-3.50) for post-operative mortality for RCRI greater than 2. The deep learning algorithm performed similarly for patients undergoing cardiac surgery with an AUC of 0.85 (CI 0.77-0.92), non-cardiac surgery with an AUC of 0.83 (0.79-0.88), and catherization or endoscopy suite procedures with an AUC of 0.76 (0.72-0.81). The algorithm similarly discriminated risk for mortality in two separate external validation cohorts from independent healthcare systems with AUCs of 0.79 (0.75-0.83) and 0.75 (0.74-0.76) respectively. Conclusion. The findings demonstrate how a novel deep learning algorithm, applied to pre-operative ECGs, can improve discrimination of post-operative mortality