Copy number variation burden does not predict severity of neurodevelopmental phenotype in children with a sex chromosome trisomy

Sex chromosome trisomies (SCTs) (XXX, XXY, and XYY karyotypes) are associated with an elevated risk of neurodevelopmental disorders. The range of severity of the phenotype is substantial. We considered whether this variable outcome was related to the presence of copy number variants (CNVs)—stretches of duplicated or deleted DNA. A sample of 125 children with an SCT were compared with 181 children of normal karyotype who had been given the same assessments. First, we compared the groups on measures of overall CNV burden: number of CNVs, total span of CNVs, and likely functional impact (probability of loss‐of‐function intolerance, pLI, summed over CNVs). Differences between groups were small relative to within‐group variance and not statistically significant on overall test. Next, we considered whether a measure of general neurodevelopmental impairment was predicted by pLI summed score, SCT versus comparison group, or the interaction between them. There was a substantial effect of SCT/comparison status but the pLI score was not predictive of outcomes in either group. We conclude that variable presence of CNVs is not a likely explanation for the wide phenotypic variation in children with SCTs. We discuss methodological challenges of testing whether CNVs are implicated in causing neurodevelopmental problems

An orthologue of Bacteroides fragilis NanH is the principal sialidase in Tannerella forsythia

Sialidase activity is a putative virulence factor of the anaerobic periodontal pathogen Tannerella forsythia, but it is uncertain which genes encode this activity. Characterization of a putative sialidase, SiaHI, by others, indicated that this protein alone may not be responsible for all of the sialidase activity. We describe a second sialidase in T. forsythia (TF0035), an orthologue of Bacteroides fragilis NanH, and its expression in Escherichia coli. Sialidase activity of the expressed NanH was confirmed by using 2'-(4-methylumbelliferyl)-alpha-D-N-acetylneuraminic acid as a substrate. Biochemical characterization of the recombinant T. forsythia NanH indicated that it was active over a broad pH range, with optimum activity at pH 5.5. This enzyme has high affinity for 2'-(4-methylumbelliferyl)-alpha-D-N-acetylneuraminic acid (K(m) of 32.9 +/- 10.3 microM) and rapidly releases 4-methylumbelliferone (V(max) of 170.8 +/- 11.8 nmol of 4-methylumbelliferone min(-1) mg of protein(-1)). E. coli lysates containing recombinant T. forsythia NanH cleave sialic acid from a range of substrates, with a preference for alpha2-3 glycosidic linkages. The genes adjacent to nanH encode proteins apparently involved in the metabolism of sialic acid, indicating that the NanH sialidase is likely to be involved in nutrient acquisition

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr

Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations

Deep learning (DL) models are increasingly used to forecast water quality variables for use in decision making. Ingesting recent observations of the forecasted variable has been shown to greatly increase model performance at monitored locations; however, observations are not collected at all locations, and methods are not yet well developed for DL models for optimally ingesting recent observations from other sites to inform focal sites. In this paper, we evaluate two different DL model structures, a long short-term memory neural network (LSTM) and a recurrent graph convolutional neural network (RGCN), both with and without data assimilation for forecasting daily maximum stream temperature 7 days into the future at monitored and unmonitored locations in a 70-segment stream network. All our DL models performed well when forecasting stream temperature as the root mean squared error (RMSE) across all models ranged from 2.03 to 2.11°C for 1-day lead times in the validation period, with substantially better performance at gaged locations (RMSE = 1.45–1.52°C) compared to ungaged locations (RMSE = 3.18–3.27°C). Forecast uncertainty characterization was near-perfect for gaged locations but all DL models were overconfident (i.e., uncertainty bounds too narrow) for ungaged locations. Our results show that the RGCN with data assimilation performed best for ungaged locations and especially at higher temperatures (&gt;18°C) which is important for management decisions in our study location. This indicates that the networked model structure and data assimilation techniques may help borrow information from nearby monitored sites to improve forecasts at unmonitored locations. Results from this study can help guide DL modeling decisions when forecasting other important environmental variables

Scaling Up ART Adherence Clubs in the Public Sector Health System in the Western Cape, South Africa: a Study of the Institutionalisation of a Pilot Innovation

In 2011, a decision was made to scale up a pilot innovation involving ‘adherence clubs’ as a form of differentiated care for HIV positive people in the public sector antiretroviral therapy programme in the Western Cape Province of South Africa. In 2016 we were involved in the qualitative aspect of an evaluation of the adherence club model, the overall objective of which was to assess the health outcomes for patients accessing clubs through epidemiological analysis, and to conduct a health systems analysis to evaluate how the model of care performed at scale. In this paper we adopt a complex adaptive systems lens to analyse planned organisational change through intervention in a state health system. We explore the challenges associated with taking to scale a pilot that began as a relatively simple innovation by a non-governmental organisation

Temporal variability of quasilinear pitch-angle diffusion

Kinetic wave-particle interactions in Earth's outer radiation belt energize and scatter high-energy electrons, playing an important role in the dynamic variation of the extent and intensity of the outer belt. It is possible to model the effects of wave-particle interactions across long length and time scales using quasilinear theory, leading to a Fokker-Planck equation to describe the effects of the waves on the high energy electrons. This powerful theory renders the efficacy of the wave-particle interaction in a diffusion coefficient that varies with energy or momentum and pitch angle. In this article we determine how the Fokker-Planck equation responds to the temporal variation of the quasilinear diffusion coefficient in the case of pitch-angle diffusion due to plasmaspheric hiss. Guided by in-situ observations of how hiss wave activity and local number density change in time, we use stochastic parameterisation to describe the temporal evolution of hiss diffusion coefficients in ensemble numerical experiments. These experiments are informed by observations from three different example locations in near-Earth space, and a comparison of the results indicates that local differences in the distribution of diffusion coefficients can result in material differences to the ensemble solutions. We demonstrate that ensemble solutions of the Fokker-Planck equation depend both upon the timescale of variability (varied between minutes and hours), and the shape of the distribution of diffusion coefficients. The uncertainty in the ensemble results increases for longer timescales of variability, and when the average diffusion coefficient at that location is high. We discuss time and length scales of wave-particle interactions relative to the drift velocity of high-energy electrons and confirm that arithmetic drift-averaging is can be appropriate in some cases. In other cases, further parameterisation is required to reduce uncertainty in the solution. We demonstrate that in some locations, rare but large values of the diffusion coefficient occur during periods of relatively low number density. Ensemble solutions are sensitive to the presence of these rare values, supporting the need for accurate cold plasma density models in radiation belt descriptions

Accelerated waning of the humoral response to COVID-19 vaccines in obesity

Funding: EAVE II is funded by the Medical Research Council (MRC) (MC_PC_19075) with the support of BREATHE—The Health Data Research Hub for Respiratory Health (MC_PC_19004), which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. This research is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20058) and National Core Studies–Immunity. Additional support was provided through Public Health Scotland, the Scottish Government Director-General Health and Social Care and the University of Edinburgh. The SCORPIO study was supported by the MRC (MR/W020564/1, a core award to J.E.T.; MC_UU_0025/12 and MR/T032413/1, awards to N.J.M.) and the Medical Research Foundation (MRF-057-0002-RG-THAV-C0798). Additional support was provided by NHS Blood and Transplant (WPA15-02 to N.J.M.), the Wellcome Trust (Institutional Strategic Support Fund 204845/Z/16/Z to N.J.M.), Addenbrooke’s Charitable Trust (900239 to N.J.M.) and the NIHR Cambridge Biomedical Research Centre and NIHR BioResource. M.A.L is supported by the Biotechnology and Biological Sciences Research Council (BBSRC) (BBS/E/B/000C0427 and BBS/E/B/000C0428) and is a Lister Institute Fellow and an EMBO Young Investigator. I.M.H. is supported by a Cambridge Institute for Medical Research PhD studentship. H.J.S. is supported by a Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and the Royal Society (109407), and a BBSRC institutional program grant (BBS/E/B/000C0433). I.S.F. is supported by the Wellcome Trust (207462/Z/17/Z), the Botnar Fondation, the Bernard Wolfe Health Neuroscience Endowment and an NIHR Senior Investigator Award.Obesity is associated with an increased risk of severe Coronavirus Disease 2019 (COVID-19) infection and mortality. COVID-19 vaccines reduce the risk of serious COVID-19 outcomes; however, their effectiveness in people with obesity is incompletely understood. We studied the relationship among body mass index (BMI), hospitalization and mortality due to COVID-19 among 3.6 million people in Scotland using the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) surveillance platform. We found that vaccinated individuals with severe obesity (BMI > 40 kg/m2) were 76% more likely to experience hospitalization or death from COVID-19 (adjusted rate ratio of 1.76 (95% confidence interval (CI), 1.60–1.94). We also conducted a prospective longitudinal study of a cohort of 28 individuals with severe obesity compared to 41 control individuals with normal BMI (BMI 18.5–24.9 kg/m2). We found that 55% of individuals with severe obesity had unquantifiable titers of neutralizing antibody against authentic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus compared to 12% of individuals with normal BMI (P = 0.0003) 6 months after their second vaccine dose. Furthermore, we observed that, for individuals with severe obesity, at any given anti-spike and anti-receptor-binding domain (RBD) antibody level, neutralizing capacity was lower than that of individuals with a normal BMI. Neutralizing capacity was restored by a third dose of vaccine but again declined more rapidly in people with severe obesity. We demonstrate that waning of COVID-19 vaccine-induced humoral immunity is accelerated in individuals with severe obesity. As obesity is associated with increased hospitalization and mortality from breakthrough infections, our findings have implications for vaccine prioritization policies.Publisher PDFPeer reviewe

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Proposed Role for COUP-TFII in Regulating Fetal Leydig Cell Steroidogenesis, Perturbation of Which Leads to Masculinization Disorders in Rodents

Reproductive disorders that are common/increasing in prevalence in human males may arise because of deficient androgen production/action during a fetal ‘masculinization programming window’. We identify a potentially important role for Chicken Ovalbumin Upstream Promoter-Transcription Factor II (COUP-TFII) in Leydig cell (LC) steroidogenesis that may partly explain this. In rats, fetal LC size and intratesticular testosterone (ITT) increased ∼3-fold between e15.5-e21.5 which associated with a progressive decrease in the percentage of LC expressing COUP-TFII. Exposure of fetuses to dibutyl phthalate (DBP), which induces masculinization disorders, dose-dependently prevented the age-related decrease in LC COUP-TFII expression and the normal increases in LC size and ITT. We show that nuclear COUP-TFII expression in fetal rat LC relates inversely to LC expression of steroidogenic factor-1 (SF-1)-dependent genes (StAR, Cyp11a1, Cyp17a1) with overlapping binding sites for SF-1 and COUP-TFII in their promoter regions, but does not affect an SF-1 dependent LC gene (3β-HSD) without overlapping sites. We also show that once COUP-TFII expression in LC has switched off, it is re-induced by DBP exposure, coincident with suppression of ITT. Furthermore, other treatments that reduce fetal ITT in rats (dexamethasone, diethylstilbestrol (DES)) also maintain/induce LC nuclear expression of COUP-TFII. In contrast to rats, in mice DBP neither causes persistence of fetal LC COUP-TFII nor reduces ITT, whereas DES-exposure of mice maintains COUP-TFII expression in fetal LC and decreases ITT, as in rats. These findings suggest that lifting of repression by COUP-TFII may be an important mechanism that promotes increased testosterone production by fetal LC to drive masculinization. As we also show an age-related decline in expression of COUP-TFII in human fetal LC, this mechanism may also be functional in humans, and its susceptibility to disruption by environmental chemicals, stress and pregnancy hormones could explain the origin of some human male reproductive disorders

Understanding the potential impact of different drug properties on SARS-CoV-2 transmission and disease burden : a modelling analysis

Q1Q1Background The unprecedented public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods and Findings develop a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care to explore the potential public-health impact of a range of different potential therapeutics, under a range of different scenarios varying: i) healthcare capacity, ii) epidemic trajectories; and iii) drug efficacy in the absence of supportive care. In each case, the outcome of interest was the number of COVID-19 deaths averted in scenarios with the therapeutic compared to scenarios without. We find the impact of drugs like dexamethasone (which are delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in highincome countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions There is a global asymmetry in who is likely to benefit from advances in the treatment of COVID-19 to date, which have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics that can feasibly be delivered to those earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priorityRevista Internacional - Indexad