93 research outputs found
Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015
SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation
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Detection of cosmic structures using the bispectrum phase. II. First results from application to cosmic reionization using the Hydrogen Epoch of Reionization Array
Characterizing the epoch of reionization (EoR) at via the
redshifted 21 cm line of neutral Hydrogen (HI) is critical to modern
astrophysics and cosmology, and thus a key science goal of many current and planned low-frequency radio telescopes. The primary challenge to detecting this signal is the overwhelmingly bright foreground emission at these frequencies, placing stringent requirements on the knowledge of the instruments and inaccuracies in analyses. Results from these experiments have largely been limited not by thermal sensitivity but by systematics, particularly caused by the inability to calibrate the instrument to high accuracy. The interferometric bispectrum phase is immune to antenna-based calibration and errors therein, and presents an independent alternative to detect the EoR HI fluctuations while largely avoiding calibration systematics. Here, we provide a demonstration of this technique on a subset of data from the Hydrogen Epoch of Reionization Array (HERA) to place approximate constraints on the IGM brightness temperature. From this limited data, at we infer "" upper limits on the IGM brightness temperature to be "pseudo" mK at Mpc (data-limited) and
"pseudo" mK at
Mpc (noise-limited). The "pseudo" units denote only an approximate and not an exact correspondence to the actual distance scales and brightness temperatures. By propagating models in parallel to the data analysis, we confirm that the dynamic range required to separate the cosmic HI signal from the foregrounds is similar to that in standard approaches, and the power spectrum of the bispectrum phase is still data-limited (at dynamic range) indicating scope for further improvement in sensitivity as the array build-out continues
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Detection of cosmic structures using the bispectrum phase. II. First results from application to cosmic reionization using the Hydrogen Epoch of Reionization Array
Characterizing the epoch of reionization (EoR) at via the
redshifted 21 cm line of neutral Hydrogen (HI) is critical to modern
astrophysics and cosmology, and thus a key science goal of many current and planned low-frequency radio telescopes. The primary challenge to detecting this signal is the overwhelmingly bright foreground emission at these frequencies, placing stringent requirements on the knowledge of the instruments and inaccuracies in analyses. Results from these experiments have largely been limited not by thermal sensitivity but by systematics, particularly caused by the inability to calibrate the instrument to high accuracy. The interferometric bispectrum phase is immune to antenna-based calibration and errors therein, and presents an independent alternative to detect the EoR HI fluctuations while largely avoiding calibration systematics. Here, we provide a demonstration of this technique on a subset of data from the Hydrogen Epoch of Reionization Array (HERA) to place approximate constraints on the IGM brightness temperature. From this limited data, at we infer "" upper limits on the IGM brightness temperature to be "pseudo" mK at Mpc (data-limited) and
"pseudo" mK at
Mpc (noise-limited). The "pseudo" units denote only an approximate and not an exact correspondence to the actual distance scales and brightness temperatures. By propagating models in parallel to the data analysis, we confirm that the dynamic range required to separate the cosmic HI signal from the foregrounds is similar to that in standard approaches, and the power spectrum of the bispectrum phase is still data-limited (at dynamic range) indicating scope for further improvement in sensitivity as the array build-out continues
Imaging and Modeling Data from the Hydrogen Epoch of Reionization Array
We analyze data from the Hydrogen Epoch of Reionization Array. This is the
third in a series of papers on the closure phase delay-spectrum technique
designed to detect the HI 21cm emission from cosmic reionization. We present
the details of the data and models employed in the power spectral analysis, and
discuss limitations to the process. We compare images and visibility spectra
made with HERA data, to parallel quantities generated from sky models based on
the GLEAM survey, incorporating the HERA telescope model. We find reasonable
agreement between images made from HERA data, with those generated from the
models, down to the confusion level. For the visibility spectra, there is broad
agreement between model and data across the full band of MHz. However,
models with only GLEAM sources do not reproduce a roughly sinusoidal spectral
structure at the tens of percent level seen in the observed visibility spectra
on scales MHz on 29 m baselines. We find that this structure is
likely due to diffuse Galactic emission, predominantly the Galactic plane,
filling the far sidelobes of the antenna primary beam. We show that our current
knowledge of the frequency dependence of the diffuse sky radio emission, and
the primary beam at large zenith angles, is inadequate to provide an accurate
reproduction of the diffuse structure in the models. We discuss implications
due to this missing structure in the models, including calibration, and in the
search for the HI 21cm signal, as well as possible mitigation techniques
Understanding the HERA Phase i receiver system with simulations and its impact on the detectability of the EoR delay power spectrum
The detection of the Epoch of Reionization (EoR) delay power spectrum using a
"foreground avoidance method" highly depends on the instrument chromaticity.
The systematic effects induced by the radio-telescope spread the foreground
signal in the delay domain, which contaminates the EoR window theoretically
observable. Applied to the Hydrogen Epoch of Reionization Array (HERA), this
paper combines detailed electromagnetic and electrical simulations in order to
model the chromatic effects of the instrument, and quantify its frequency and
time responses. In particular, the effects of the analogue receiver,
transmission cables, and mutual coupling are included. These simulations are
able to accurately predict the intensity of the reflections occurring in the
150-m cable which links the antenna to the back-end. They also show that
electromagnetic waves can propagate from one dish to another one through large
sections of the array due to mutual coupling. The simulated system time
response is attenuated by a factor after a characteristic delay which
depends on the size of the array and on the antenna position. Ultimately, the
system response is attenuated by a factor after 1400 ns because of the
reflections in the cable, which corresponds to characterizable
-modes above 0.7 at 150 MHz. Thus, this new
study shows that the detection of the EoR signal with HERA Phase I will be more
challenging than expected. On the other hand, it improves our understanding of
the telescope, which is essential to mitigate the instrument chromaticity
Automated Detection of Antenna Malfunctions in Large-N Interferometers: A case study With the Hydrogen Epoch of Reionization Array
We present a framework for identifying and flagging malfunctioning antennas in large radio
interferometers. We outline two distinct categories of metrics designed to detect outliers along known failure
modes of large arrays: cross-correlation metrics, based on all antenna pairs, and auto-correlation metrics, based
solely on individual antennas. We define and motivate the statistical framework for all metrics used, and present
tailored visualizations that aid us in clearly identifying new and existing systematics. We implement these
techniques using data from 105 antennas in the Hydrogen Epoch of Reionization Array (HERA) as a case study.
Finally, we provide a detailed algorithm for implementing these metrics as flagging tools on real data sets
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Foreground modelling via Gaussian process regression: An application to HERA data
The key challenge in the observation of the redshifted 21-cm signal from
cosmic reionization is its separation from the much brighter foreground
emission. Such separation relies on the different spectral properties of the
two components, although, in real life, the foreground intrinsic spectrum is
often corrupted by the instrumental response, inducing systematic effects that
can further jeopardize the measurement of the 21-cm signal. In this paper, we
use Gaussian Process Regression to model both foreground emission and
instrumental systematics in hours of data from the Hydrogen Epoch of
Reionization Array. We find that a simple co-variance model with three
components matches the data well, giving a residual power spectrum with white
noise properties. These consist of an "intrinsic" and instrumentally corrupted
component with a coherence-scale of 20 MHz and 2.4 MHz respectively (dominating
the line of sight power spectrum over scales h
cMpc) and a baseline dependent periodic signal with a period of
MHz (dominating over h cMpc) which should
be distinguishable from the 21-cm EoR signal whose typical coherence-scales is
MHz
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Foreground modelling via Gaussian process regression: An application to HERA data
The key challenge in the observation of the redshifted 21-cm signal from
cosmic reionization is its separation from the much brighter foreground
emission. Such separation relies on the different spectral properties of the
two components, although, in real life, the foreground intrinsic spectrum is
often corrupted by the instrumental response, inducing systematic effects that
can further jeopardize the measurement of the 21-cm signal. In this paper, we
use Gaussian Process Regression to model both foreground emission and
instrumental systematics in hours of data from the Hydrogen Epoch of
Reionization Array. We find that a simple co-variance model with three
components matches the data well, giving a residual power spectrum with white
noise properties. These consist of an "intrinsic" and instrumentally corrupted
component with a coherence-scale of 20 MHz and 2.4 MHz respectively (dominating
the line of sight power spectrum over scales h
cMpc) and a baseline dependent periodic signal with a period of
MHz (dominating over h cMpc) which should
be distinguishable from the 21-cm EoR signal whose typical coherence-scales is
MHz
Ibudilast, a Pharmacologic Phosphodiesterase Inhibitor, Prevents Human Immunodeficiency Virus-1 Tat-Mediated Activation of Microglial Cells
Human Immunodeficiency Virus-1 (HIV-1)-associated neurocognitive disorders (HAND) occur, in part, due to the inflammatory response to viral proteins, such as the HIV-1 transactivator of transcription (Tat), in the central nervous system (CNS). Given the need for novel adjunctive therapies for HAND, we hypothesized that ibudilast would inhibit Tat-induced excess production of pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNFα) in microglial cells. Ibudilast is a non-selective cyclic AMP phosphodiesterase inhibitor that has recently shown promise as a treatment for neuropathic pain via its ability to attenuate glial cell activation. Accordingly, here we demonstrate that pre-treatment of both human and mouse microglial cells with increasing doses of ibudilast inhibited Tat-induced synthesis of TNFα by microglial cells in a manner dependent on serine/threonine protein phosphatase activity. Ibudilast had no effect on Tat-induced p38 MAP kinase activation, and blockade of adenosine A2A receptor activation did not reverse ibudilast's inhibition of Tat-induced TNFα production. Interestingly, ibudilast reduced Tat-mediated transcription of TNFα, via modulation of nuclear factor-kappa B (NF-κB) signaling, as shown by transcriptional activity of NF-κB and analysis of inhibitor of kappa B alpha (IκBα) stability. Together, our findings shed light on the mechanism of ibudilast's inhibition of Tat-induced TNFα production in microglial cells and may implicate ibudilast as a potential novel adjunctive therapy for the management of HAND
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