Milder winters in northern Scandinavia may contribute to larger outbreaks of haemorrhagic fever virus

The spread of zoonotic infectious diseases may increase due to climate factors such as temperature, humidity and precipitation. This is also true for hantaviruses, which are globally spread haemorrhagic fever viruses carried by rodents. Hantaviruses are frequently transmitted to humans all over the world and regarded as emerging viral diseases. Climate variations affect the rodent reservoir populations and rodent population peaks coincide with increased number of human cases of hantavirus infections. In northern Sweden, a form of haemorrhagic fever called nephropathia epidemica (NE), caused by the Puumala hantavirus (PUUV) is endemic and during 2006–2007 an unexpected, sudden and large outbreak of NE occurred in this region. The incidence was 313 cases/100,000 inhabitants in the most endemic areas, and from January through March 2007 the outbreak had a dramatic and sudden start with 474 cases in the endemic region alone. The PUUV rodent reservoir is bank voles and immediately before and during the peak of disease outbreak the affected regions experienced extreme climate conditions with a record-breaking warm winter, registering temperatures 6–9°C above normal. No protective snow cover was present before the outbreak and more bank voles than normal came in contact with humans inside or in close to human dwellings. These extreme climate conditions most probably affected the rodent reservoir and are important factors for the severity of the outbreak

Implementation of AI/Deep Learning Disruption Predictor into a Plasma Control System

This paper reports on advances to the state-of-the-art deep-learning disruption prediction models based on the Fusion Recurrent Neural Network (FRNN) originally introduced a 2019 Nature publication. In particular, the predictor now features not only the disruption score, as an indicator of the probability of an imminent disruption, but also a sensitivity score in real-time to indicate the underlying reasons for the imminent disruption. This adds valuable physics-interpretability for the deep-learning model and can provide helpful guidance for control actuators now that it is fully implemented into a modern Plasma Control System (PCS). The advance is a significant step forward in moving from modern deep-learning disruption prediction to real-time control and brings novel AI-enabled capabilities relevant for application to the future burning plasma ITER system. Our analyses use large amounts of data from JET and DIII-D vetted in the earlier NATURE publication. In addition to when a shot is predicted to disrupt, this paper addresses reasons why by carrying out sensitivity studies. FRNN is accordingly extended to use many more channels of information, including measured DIII-D signals such as (i) the n1rms signal that is correlated with the n =1 modes with finite frequency, including neoclassical tearing mode and sawtooth dynamics, (ii) the bolometer data indicative of plasma impurity content, and (iii) q-min, the minimum value of the safety factor relevant to the key physics of kink modes. The additional channels and interpretability features expand the ability of the deep learning FRNN software to provide information about disruption subcategories as well as more precise and direct guidance for the actuators in a plasma control system

Impact of hyperglycemia on morbidity and mortality, length of hospitalization and rates of re-hospitalization in a general hospital setting in Brazil

<p>Abstract</p> <p>Background</p> <p>Hyperglycemia in hospitalized patients is known to be related to a higher incidence of clinical and surgical complications and poorer outcomes. Adequate glycemic control and earlier diagnosis of type 2 diabetes during hospitalization are cost-effective measures.</p> <p>Methods</p> <p>This prospective cohort study was designed to determine the impact of hyperglycemia on morbidity and mortality in a general hospital setting during a 3-month period by reviewing patients' records. The primary purposes of this trial were to verify that hyperglycemia was diagnosed properly and sufficiently early and that it was managed during the hospital stay; we also aimed to evaluate the relationship between in-hospital hyperglycemia control and outcomes such as complications during the hospital stay, extent of hospitalization, frequency of re-hospitalization, death rates and number of days in the ICU (Intensive Care Unit) after admission. Statistical analyses utilized the Kruskall-Wallis complemented by the "a posteriori" d.m.s. test, Spearman correlation and Chi-squared test, with a level of significance of 5% (p < 0.05).</p> <p>Results</p> <p>We reviewed 779 patient records that fulfilled inclusion criteria. The patients were divided into 5 groups: group (1) diabetic with normal glycemic levels according to American Diabetes Association criteria for in-hospital patients (n = 123); group (2) diabetics with hyperglycemia (n = 76); group (3) non-diabetics with hyperglycemia (n = 225); group (4)diabetics and non-diabetics with persistent hyperglycemia during 3 consecutive days (n = 57) and group (5) those with normal glucose control (n = 298). Compared to patients in groups 1 and 5, patients in groups 2, 3 and 4 had significantly higher mortality rates (17.7% vs. 2.8%) and Intensive Care Unit admissions with complications (23.3% vs. 4.5%). Patients in group 4 had the longest hospitalizations (mean 15.5 days), and group 5 had the lowest re-hospitalization rate (mean of 1.28 hospitalizations). Only 184 (51.4%) hyperglycemic patients had received treatment. An insulin "sliding-scale" alone was the most frequent treatment used, and there was a wide variation in glucose target medical prescriptions. Intra Venous insulin infusion was used in 3.8% of patients in the ICU. Glycohemoglobin(A1C) was measured in 11 patients(2.2%).</p> <p>Conclusions</p> <p>Hospital hyperglycemia was correlated with, among other parameters, morbidity/mortality, length of hospitalization and number of re-hospitalizations. Most patients did not have their glycemic levels measured at the hospital; despite the high number of hyperglycemic patients not diagnosed as diabetics, A1C was not frequently measured. Even when patients are assessed for hyperglycemia, they were not treated properly.</p

Vascular endothelial growth factor prevents G93A-SOD1-induced motor neuron degeneration

Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disorder characterized by selective loss of motor neurons (MNs). Twenty percent of familial ALS cases are associated with mutations in Cu 2+ /Zn 2+ superoxide dismutase (SOD1). To specifically understand the cellular mechanisms underlying mutant SOD1 toxicity, we have established an in vitro model of ALS using rat primary MN cultures transfected with an adenoviral vector encoding a mutant SOD1, G93A-SOD1. Transfected cells undergo axonal degeneration and alterations in biochemical responses characteristic of cell death such as activation of caspase-3. Vascular endothelial growth factor (VEGF) is an angiogenic and neuroprotective growth factor that can increase axonal outgrowth, block neuronal apoptosis, and promote neurogenesis. Decreased VEGF gene expression in mice results in a phenotype similar to that seen in patients with ALS, thus linking loss of VEGF to the pathogenesis of MN degeneration. Decreased neurotrophic signals prior to and during disease progression may increase MN susceptibility to mutant SOD1-induced toxicity. In this study, we demonstrate a decrease in VEGF and VEGFR2 levels in the spinal cord of G93A-SOD1 ALS mice. Furthermore, in isolated MN cultures, VEGF alleviates the effects of G93A-SOD1 toxicity and neuroprotection involves phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) signaling. Overall, these studies validate the usefulness of VEGF as a potential therapeutic factor for the treatment of ALS and give valuable insight into the responsible signaling pathways and mechanisms involved. © 2009 Wiley Periodicals, Inc. Develop Neurobiol, 2009Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64297/1/20747_ftp.pd

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Hunt for new phenomena using large jet multiplicities and missing transverse momentum with ATLAS in 4.7 fb−1 of s√=7TeV proton-proton collisions

Results are presented of a search for new particles decaying to large numbers of jets in association with missing transverse momentum, using 4.7 fb−1 of pp collision data at s√=7TeV collected by the ATLAS experiment at the Large Hadron Collider in 2011. The event selection requires missing transverse momentum, no isolated electrons or muons, and from ≥6 to ≥9 jets. No evidence is found for physics beyond the Standard Model. The results are interpreted in the context of a MSUGRA/CMSSM supersymmetric model, where, for large universal scalar mass m 0, gluino masses smaller than 840 GeV are excluded at the 95% confidence level, extending previously published limits. Within a simplified model containing only a gluino octet and a neutralino, gluino masses smaller than 870 GeV are similarly excluded for neutralino masses below 100 GeV

Measurement of the cross-section of high transverse momentum vector bosons reconstructed as single jets and studies of jet substructure in pp collisions at √s = 7 TeV with the ATLAS detector

This paper presents a measurement of the cross-section for high transverse momentum W and Z bosons produced in pp collisions and decaying to all-hadronic final states. The data used in the analysis were recorded by the ATLAS detector at the CERN Large Hadron Collider at a centre-of-mass energy of √s = 7 TeV;{\rm Te}{\rm V}$and correspond to an integrated luminosity of$4.6\;{\rm f}{{{\rm b}}^{-1}}$. The measurement is performed by reconstructing the boosted W or Z bosons in single jets. The reconstructed jet mass is used to identify the W and Z bosons, and a jet substructure method based on energy cluster information in the jet centre-of-mass frame is used to suppress the large multi-jet background. The cross-section for events with a hadronically decaying W or Z boson, with transverse momentum${{p}_{{\rm T}}}\gt 320\;{\rm Ge}{\rm V}$and pseudorapidity$|\eta |\lt 1.9$, is measured to be${{\sigma }_{W+Z}}=8.5\pm 1.7$ pb and is compared to next-to-leading-order calculations. The selected events are further used to study jet grooming techniques