571 research outputs found
Clinical Trials and Medical Care: Defining the Therapeutic Misconception
A key component of informed consent to participate in medical research includes understanding that research is not the same as treatment
A quantum Monte Carlo study of the one-dimensional ionic Hubbard model
Quantum Monte Carlo methods are used to study a quantum phase transition in a
1D Hubbard model with a staggered ionic potential (D). Using recently
formulated methods, the electronic polarization and localization are determined
directly from the correlated ground state wavefunction and compared to results
of previous work using exact diagonalization and Hartree-Fock. We find that the
model undergoes a thermodynamic transition from a band insulator (BI) to a
broken-symmetry bond ordered (BO) phase as the ratio of U/D is increased. Since
it is known that at D = 0 the usual Hubbard model is a Mott insulator (MI) with
no long-range order, we have searched for a second transition to this state by
(i) increasing U at fixed ionic potential (D) and (ii) decreasing D at fixed U.
We find no transition from the BO to MI state, and we propose that the MI state
in 1D is unstable to bond ordering under the addition of any finite ionic
potential. In real 1D systems the symmetric MI phase is never stable and the
transition is from a symmetric BI phase to a dimerized BO phase, with a
metallic point at the transition
Rare Copy Number Variants in \u3cem\u3eNRXN1\u3c/em\u3e and \u3cem\u3eCNTN6\u3c/em\u3e Increase Risk for Tourette Syndrome
Tourette syndrome (TS) is a model neuropsychiatric disorder thought to arise from abnormal development and/or maintenance of cortico-striato-thalamo-cortical circuits. TS is highly heritable, but its underlying genetic causes are still elusive, and no genome-wide significant loci have been discovered to date. We analyzed a European ancestry sample of 2,434 TS cases and 4,093 ancestry-matched controls for rare (\u3c 1% frequency) copy-number variants (CNVs) using SNP microarray data. We observed an enrichment of global CNV burden that was prominent for large (\u3e 1 Mb), singleton events (OR = 2.28, 95% CI [1.39–3.79], p = 1.2 × 10−3) and known, pathogenic CNVs (OR = 3.03 [1.85–5.07], p = 1.5 × 10−5). We also identified two individual, genome-wide significant loci, each conferring a substantial increase in TS risk (NRXN1 deletions, OR = 20.3, 95% CI [2.6–156.2]; CNTN6 duplications, OR = 10.1, 95% CI [2.3–45.4]). Approximately 1% of TS cases carry one of these CNVs, indicating that rare structural variation contributes significantly to the genetic architecture of TS
Targeted genomic capture and massively parallel sequencing to identify genes for hereditary hearing loss in middle eastern families
Climate-controlled submarine landslides on the Antarctic continental margin
Antarctica’s continental margins pose an unknown submarine landslidegenerated tsunami risk to Southern Hemisphere populations and infrastructure. Understanding the factors driving slope failure is essential to assessing future geohazards. Here, we present a multidisciplinary study of a major submarine landslide complex along the eastern Ross Sea continental slope (Antarctica) that identifies preconditioning factors and failure mechanisms. Weak layers, identified beneath three submarine landslides, consist of distinct packages of interbedded Miocene- to Pliocene-age diatom oozes and glaciomarine diamicts. The observed lithological differences, which arise from glacial to interglacial variations in biological productivity, ice proximity, and ocean circulation, caused changes in sediment deposition that inherently preconditioned slope failure. These recurrent Antarctic submarine landslides were likely triggered by seismicity associated with glacioisostatic readjustment, leading to failure within the preconditioned weak layers. Ongoing climate warming and ice retreat may increase regional glacioisostatic seismicity, triggering Antarctic submarine landslides
Improving the sensitivity to gravitational-wave sources by modifying the input-output optics of advanced interferometers
We study frequency dependent (FD) input-output schemes for signal-recycling
interferometers, the baseline design of Advanced LIGO and the current
configuration of GEO 600. Complementary to a recent proposal by Harms et al. to
use FD input squeezing and ordinary homodyne detection, we explore a scheme
which uses ordinary squeezed vacuum, but FD readout. Both schemes, which are
sub-optimal among all possible input-output schemes, provide a global noise
suppression by the power squeeze factor, while being realizable by using
detuned Fabry-Perot cavities as input/output filters. At high frequencies, the
two schemes are shown to be equivalent, while at low frequencies our scheme
gives better performance than that of Harms et al., and is nearly fully
optimal. We then study the sensitivity improvement achievable by these schemes
in Advanced LIGO era (with 30-m filter cavities and current estimates of
filter-mirror losses and thermal noise), for neutron star binary inspirals, and
for narrowband GW sources such as low-mass X-ray binaries and known radio
pulsars. Optical losses are shown to be a major obstacle for the actual
implementation of these techniques in Advanced LIGO. On time scales of
third-generation interferometers, like EURO/LIGO-III (~2012), with
kilometer-scale filter cavities, a signal-recycling interferometer with the FD
readout scheme explored in this paper can have performances comparable to
existing proposals. [abridged]Comment: Figs. 9 and 12 corrected; Appendix added for narrowband data analysi
Upper limits on the strength of periodic gravitational waves from PSR J1939+2134
The first science run of the LIGO and GEO gravitational wave detectors
presented the opportunity to test methods of searching for gravitational waves
from known pulsars. Here we present new direct upper limits on the strength of
waves from the pulsar PSR J1939+2134 using two independent analysis methods,
one in the frequency domain using frequentist statistics and one in the time
domain using Bayesian inference. Both methods show that the strain amplitude at
Earth from this pulsar is less than a few times .Comment: 7 pages, 1 figure, to appear in the Proceedings of the 5th Edoardo
Amaldi Conference on Gravitational Waves, Tirrenia, Pisa, Italy, 6-11 July
200
Searching for a Stochastic Background of Gravitational Waves with LIGO
The Laser Interferometer Gravitational-wave Observatory (LIGO) has performed
the fourth science run, S4, with significantly improved interferometer
sensitivities with respect to previous runs. Using data acquired during this
science run, we place a limit on the amplitude of a stochastic background of
gravitational waves. For a frequency independent spectrum, the new limit is
. This is currently the most sensitive
result in the frequency range 51-150 Hz, with a factor of 13 improvement over
the previous LIGO result. We discuss complementarity of the new result with
other constraints on a stochastic background of gravitational waves, and we
investigate implications of the new result for different models of this
background.Comment: 37 pages, 16 figure
Deep learning models for predicting RNA degradation via dual crowdsourcing
Medicines based on messenger RNA (mRNA) hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limited by their thermostability, which is fundamentally limited by the intrinsic instability of RNA molecules to a chemical degradation reaction called in-line hydrolysis. Predicting the degradation of an RNA molecule is a key task in designing more stable RNA-based therapeutics. Here, we describe a crowdsourced machine learning competition (‘Stanford OpenVaccine’) on Kaggle, involving single-nucleotide resolution measurements on 6,043 diverse 102–130-nucleotide RNA constructs that were themselves solicited through crowdsourcing on the RNA design platform Eterna. The entire experiment was completed in less than 6 months, and 41% of nucleotide-level predictions from the winning model were within experimental error of the ground truth measurement. Furthermore, these models generalized to blindly predicting orthogonal degradation data on much longer mRNA molecules (504–1,588 nucleotides) with improved accuracy compared with previously published models. These results indicate that such models can represent in-line hydrolysis with excellent accuracy, supporting their use for designing stabilized messenger RNAs. The integration of two crowdsourcing platforms, one for dataset creation and another for machine learning, may be fruitful for other urgent problems that demand scientific discovery on rapid timescales
Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis
BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London
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