54 research outputs found
White matter hyperintensity burden predicts cognitive but not motor decline in Parkinson's disease. Results from the ONDRI
Genetic mechanisms of critical illness in COVID-19.
Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 × 10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice
The ALICE experiment at the CERN LHC
ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries. Its overall dimensions are 161626 m3 with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008
Toward Accurate Post-Born–Oppenheimer Molecular Simulations on Quantum Computers: An Adaptive Variational Eigensolver with Nuclear-Electronic Frozen Natural Orbitals
Nuclear
quantum effects such as zero-point energy and
hydrogen
tunneling play a central role in many biological and chemical processes.
The nuclear-electronic orbital (NEO) approach captures these effects
by treating selected nuclei quantum mechanically on the same footing
as electrons. On classical computers, the resources required for an
exact solution of NEO-based models grow exponentially with system
size. By contrast, quantum computers offer a means of solving this
problem with polynomial scaling. However, due to the limitations of
current quantum devices, NEO simulations are confined to the smallest
systems described by minimal basis sets, whereas realistic simulations
beyond the Born–Oppenheimer approximation require more sophisticated
basis sets. For this purpose, we herein extend a hardware-efficient
ADAPT-VQE method to the NEO framework in the frozen natural orbital
(FNO) basis. We demonstrate on H2 and D2 molecules
that the NEO-FNO-ADAPT-VQE method reduces the CNOT count by several
orders of magnitude relative to the NEO unitary coupled cluster method
with singles and doubles while maintaining the desired accuracy. This
extreme reduction in the CNOT gate count is sufficient to permit practical
computations employing the NEO methodan important step toward
accurate simulations involving nonclassical nuclei and non-Born–Oppenheimer
effects on near-term quantum devices. We further show that the method
can capture isotope effects, and we demonstrate that inclusion of
correlation energy systematically improves the prediction of difference
in the zero-point energy (ΔZPE) between isotopes
Differentiating stable buckle fractures from other distal radius fractures: the 1-cm rule
The muscle protein synthetic response to the combined ingestion of protein and carbohydrate is not impaired in healthy older men
Aging Is Accompanied by a Blunted Muscle Protein Synthetic Response to Protein Ingestion
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