46 research outputs found
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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
Recommended from our members
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
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 brightness temperature of
the intergalactic medium (IGM). From this limited data, at we infer
"" upper limits on the IGM brightness temperature to be
"pseudo" mK at "pseudo" Mpc (data-limited)
and "pseudo" mK at "pseudo" 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.Comment: 22 pages, 12 figures (including sub-figures). Published in PhRvD.
Abstract may be slightly abridged compared to the actual manuscript due to
length limitations on arXi
Whole-genome sequencing reveals host factors underlying critical COVID-19
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease
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
Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases
The production of peroxide and superoxide is an inevitable consequence of
aerobic metabolism, and while these particular "reactive oxygen species" (ROSs)
can exhibit a number of biological effects, they are not of themselves
excessively reactive and thus they are not especially damaging at physiological
concentrations. However, their reactions with poorly liganded iron species can
lead to the catalytic production of the very reactive and dangerous hydroxyl
radical, which is exceptionally damaging, and a major cause of chronic
inflammation. We review the considerable and wide-ranging evidence for the
involvement of this combination of (su)peroxide and poorly liganded iron in a
large number of physiological and indeed pathological processes and
inflammatory disorders, especially those involving the progressive degradation
of cellular and organismal performance. These diseases share a great many
similarities and thus might be considered to have a common cause (i.e.
iron-catalysed free radical and especially hydroxyl radical generation). The
studies reviewed include those focused on a series of cardiovascular, metabolic
and neurological diseases, where iron can be found at the sites of plaques and
lesions, as well as studies showing the significance of iron to aging and
longevity. The effective chelation of iron by natural or synthetic ligands is
thus of major physiological (and potentially therapeutic) importance. As
systems properties, we need to recognise that physiological observables have
multiple molecular causes, and studying them in isolation leads to inconsistent
patterns of apparent causality when it is the simultaneous combination of
multiple factors that is responsible. This explains, for instance, the
decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference
Whole-genome sequencing reveals host factors underlying critical COVID-19
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease