166 research outputs found
The prevalence of hyperglycaemia and its relationship with mortality, readmissions and length of stay in an older acute surgical population : a multicentre study
Funding statement This research received no specific grant from any funding agency in the public, commercial or not-for-profit sector.Peer reviewedPostprin
Developing an intervention to facilitate family communication about inherited genetic conditions, and training genetic counsellors in its delivery.
Many families experience difficulty in talking about an inherited genetic condition that affects one or more of them. There have now been a number of studies identifying the issues in detail, however few have developed interventions to assist families. The SPRinG collaborative have used the UK Medical Research Council's guidance on Developing and Evaluating Complex Interventions, to work with families and genetic counsellors (GCs) to co-design a psycho-educational intervention to facilitate family communication and promote better coping and adaptation to living with an inherited genetic condition for parents and their children (<18 years). The intervention is modelled on multi-family discussion groups (MFDGs) used in psychiatric settings. The MFDG was developed and tested over three phases. First focus groups with parents, young people, children and health professionals discussed whether MFDG was acceptable and proposed a suitable design. Using evidence and focus group data, the intervention and a training manual were developed and three GCs were trained in its delivery. Finally, a prototype MFDG was led by a family therapist and co-facilitated by the three GCs. Data analysis showed that families attending the focus groups and intervention thought MFDG highly beneficial, and the pilot sessions had a significant impact on their family' functioning. We also demonstrated that it is possible to train GCs to deliver the MFDG intervention. Further studies are now required to test the feasibility of undertaking a definitive randomised controlled trial to evaluate its effectiveness in improving family outcomes before implementing into genetic counselling practice.The National Institute of Health Research funded the study but any views expressed do not necessarily reflect those of the Authority. Funded by NIHR reference number: RP-DG-1211-10015
A polymorphism near IGF1 is associated with body composition and muscle function in women from the Health, Aging, and Body Composition Study
Previous studies have reported associations of polymorphisms in the IGF1 gene with phenotypes of body composition (BC). The purpose of this study was to identify phenotypes of BC and physical function that were associated with the IGF1 promoter polymorphism (rs35767, âC1245T). Subjects from the Health, Aging, and Body Composition Study, white males and females (n = 925/836) and black males and females (533/705) aged 70â79 years were genotyped for the polymorphism. Phenotypes of muscle size and function, bone mineral density, and BC were analyzed for associations with this polymorphism. To validate and compare these findings, a cohort of young (mean age = 24.6, SD = 5.9) white men and women (n = 173/296) with similar phenotypic measurements were genotyped. An association with BC was identified in elderly females when significant covariates (physical activity, age, smoking status, body mass index) were included. White women with C/C genotype had 3% more trunk fat and 2% more total fat than those with C/T (P < 0.05). Black women with C/C genotype had 3% less total lean mass and 3% less muscle mass than their T/T counterparts (P < 0.05). Associations were identified with muscle strength in white women (P < 0.01) that were in agreement with the C/C genotype having lower muscle function. Thus, in an elderly population but not a young population, a polymorphism in the IGF1 gene may be predictive of differences in body composition, primarily in black females
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Decoding human fetal liver haematopoiesis.
Definitive haematopoiesis in the fetal liver supports self-renewal and differentiation of haematopoietic stem cells and multipotent progenitors (HSC/MPPs) but remains poorly defined in humans. Here, using single-cell transcriptome profiling of approximately 140,000 liver and 74,000 skin, kidney and yolk sac cells, we identify the repertoire of human blood and immune cells during development. We infer differentiation trajectories from HSC/MPPs and evaluate the influence of the tissue microenvironment on blood and immune cell development. We reveal physiological erythropoiesis in fetal skin and the presence of mast cells, natural killer and innate lymphoid cell precursors in the yolk sac. We demonstrate a shift in the haemopoietic composition of fetal liver during gestation away from being predominantly erythroid, accompanied by a parallel change in differentiation potential of HSC/MPPs, which we functionally validate. Our integrated map of fetal liver haematopoiesis provides a blueprint for the study of paediatric blood and immune disorders, and a reference for harnessing the therapeutic potential of HSC/MPPs.We acknowledge funding from the Wellcome Human Cell Atlas Strategic Science Support (WT211276/Z/18/Z); M.H. is funded by Wellcome (WT107931/Z/15/Z), The Lister Institute for Preventive Medicine and NIHR and Newcastle-Biomedical Research Centre; S.A.T. is funded by Wellcome (WT206194), ERC Consolidator and EU MRG-Grammar awards and; S.B. is funded by Wellcome (WT110104/Z/15/Z) and St. Baldrickâs Foundation; E.L. is funded by a Wellcome Sir Henry Dale and Royal Society Fellowships, European Haematology Association, Wellcome and MRC to the Wellcome-MRC Cambridge Stem Cell Institute and BBSRC
Optimizing Sparse RFI Prediction using Deep Learning
Radio Frequency Interference (RFI) is an ever-present limiting factor among
radio telescopes even in the most remote observing locations. When looking to
retain the maximum amount of sensitivity and reduce contamination for Epoch of
Reionization studies, the identification and removal of RFI is especially
important. In addition to improved RFI identification, we must also take into
account computational efficiency of the RFI-Identification algorithm as radio
interferometer arrays such as the Hydrogen Epoch of Reionization Array grow
larger in number of receivers. To address this, we present a Deep Fully
Convolutional Neural Network (DFCN) that is comprehensive in its use of
interferometric data, where both amplitude and phase information are used
jointly for identifying RFI. We train the network using simulated HERA
visibilities containing mock RFI, yielding a known "ground truth" dataset for
evaluating the accuracy of various RFI algorithms. Evaluation of the DFCN model
is performed on observations from the 67 dish build-out, HERA-67, and achieves
a data throughput of 1.6 HERA time-ordered 1024 channeled
visibilities per hour per GPU. We determine that relative to an amplitude only
network including visibility phase adds important adjacent time-frequency
context which increases discrimination between RFI and Non-RFI. The inclusion
of phase when predicting achieves a Recall of 0.81, Precision of 0.58, and
score of 0.75 as applied to our HERA-67 observations.Comment: 11 pages, 7 figure
Mitigating Internal Instrument Coupling for 21 cm Cosmology. II. A Method Demonstration with the Hydrogen Epoch of Reionization Array
We present a study of internal reflection and cross-coupling systematics in Phase I of the Hydrogen Epoch of Reionization Array (HERA). In a companion paper, we outlined the mathematical formalism for such systematics and presented algorithms for modeling and removing them from the data. In this work, we apply these techniques to data from HERA's first observing season as a method demonstration. The data show evidence for systematics that, without removal, would hinder a detection of the 21 cm power spectrum for the targeted Epoch of Reionization (EoR) line-of-sight modes in the range 0.2 h â1 Mpcâ1 < < 0.5 h â1 Mpcâ1. In particular, we find evidence for nonnegligible amounts of spectral structure in the raw autocorrelations that overlaps with the EoR window and is suggestive of complex instrumental effects. Through systematic modeling on a single night of data, we find we can recover these modes in the power spectrum down to the integrated noise floor, achieving a dynamic range in the EoR window of 106 in power (mK2 units) with respect to the bright galactic foreground signal. Future work with deeper integrations will help determine whether these systematics can continue to be mitigated down to EoR levels. For future observing seasons, HERA will have upgraded analog and digital hardware to better control these systematics in the field
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
Bayesian jackknife tests with a small number of subsets: Application to HERA 21cm power spectrum upper limits
We present a Bayesian jackknife test for assessing the probability that a data set contains biased subsets, and, if so, which of the subsets are likely to be biased. The test can be used to assess the presence and likely source of statistical tension between different measurements of the same quantities in an automated manner. Under certain broadly applicable assumptions, the test is analytically tractable. We also provide an open-source code, CHIBORG, that performs both analytic and numerical computations of the test on general Gaussian-distributed data. After exploring the information theoretical aspects of the test and its performance with an array of simulations, we apply it to data from the Hydrogen Epoch of Reionization Array (HERA) to assess whether different sub-seasons of observing can justifiably be combined to produce a deeper 21 cm power spectrum upper limit. We find that, with a handful of exceptions, the HERA data in question are statistically consistent and this decision is justified. We conclude by pointing out the wide applicability of this test, including to CMB experiments and the H0 tension
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