1,786 research outputs found
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 Tregâ:âTh17 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 âalien agenciesâ 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
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
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