Molecular insights into RBR E3 ligase ubiquitin transfer mechanisms

National Institute of General Medical Sciences R01 GM0880555T32 GM007270, Francis Crick Institute FCI01, Cancer Research UK, Medical Research Council U117565398, Wellcome Trus

Validation of cardiovascular magnetic resonance assessment of pericardial adipose tissue volume

© 2009 Nelson et al; licensee BioMed Central Ltd.Background Pericardial adipose tissue (PAT) has been shown to be an independent predictor of coronary artery disease. To date its assessment has been restricted to the use of surrogate echocardiographic indices such as measurement of epicardial fat thickness over the right ventricular free wall, which have limitations. Cardiovascular magnetic resonance (CMR) offers the potential to non-invasively assess total PAT, however like other imaging modalities, CMR has not yet been validated for this purpose. Thus, we sought to describe a novel technique for assessing total PAT with validation in an ovine model. Methods 11 merino sheep were studied. A standard clinical series of ventricular short axis CMR images (1.5T Siemens Sonata) were obtained during mechanical ventilation breath-holds. Beginning at the mitral annulus, consecutive end-diastolic ventricular images were used to determine the area and volume of epicardial, paracardial and pericardial adipose tissue. In addition adipose thickness was measured at the right ventricular free wall. Following euthanasia, the paracardial adipose tissue was removed from the ventricle and weighed to allow comparison with corresponding CMR measurements. Results There was a strong correlation between CMR-derived paracardial adipose tissue volume and ex vivo paracardial mass (R2 = 0.89, p < 0.001). In contrast, CMR measurements of corresponding RV free wall paracardial adipose thickness did not correlate with ex vivo paracardial mass (R2 = 0.003, p = 0.878). Conclusion In this ovine model, CMR-derived paracardial adipose tissue volume, but not the corresponding and conventional measure of paracardial adipose thickness over the RV free wall, accurately reflected paracardial adipose tissue mass. This study validates for the first time, the use of clinically utilised CMR sequences for the accurate and reproducible assessment of pericardial adiposity. Furthermore this non-invasive modality does not use ionising radiation and therefore is ideally suited for future studies of PAT and its role in cardiovascular risk prediction and disease in clinical practiceAdam J Nelson, Matthew I Worthley, Peter J Psaltis, Angelo Carbone, Benjamin K Dundon, Rae F Duncan, Cynthia Piantadosi, Dennis H Lau, Prashanthan Sanders, Gary A Wittert and Stephen G Worthle

A neurovascular high-frequency optical coherence tomography system enables in situ cerebrovascular volumetric microscopy

Intravascular imaging has emerged as a valuable tool for the treatment of coronary and peripheral artery disease; however, no solution is available for safe and reliable use in the tortuous vascular anatomy of the brain. Endovascular treatment of stroke is delivered under image guidance with insufficient resolution to adequately assess underlying arterial pathology and therapeutic devices. High-resolution imaging, enabling surgeons to visualize cerebral arteries\u27 microstructure and micron-level features of neurovascular devices, would have a profound impact in the research, diagnosis, and treatment of cerebrovascular diseases. Here, we present a neurovascular high-frequency optical coherence tomography (HF-OCT) system, including an imaging console and an endoscopic probe designed to rapidly acquire volumetric microscopy data at a resolution approaching 10 microns in tortuous cerebrovascular anatomies. Using a combination of in vitro, ex vivo, and in vivo models, the feasibility of HF-OCT for cerebrovascular imaging was demonstrated

The effects of COVID-19 on cognitive performance in a community-based cohort: a COVID symptom study biobank prospective cohort study

BACKGROUND: Cognitive impairment has been reported after many types of infection, including SARS-CoV-2. Whether deficits following SARS-CoV-2 improve over time is unclear. Studies to date have focused on hospitalised individuals with up to a year follow-up. The presence, magnitude, persistence and correlations of effects in community-based cases remain relatively unexplored. METHODS: Cognitive performance (working memory, attention, reasoning, motor control) was assessed in a prospective cohort study of participants from the United Kingdom COVID Symptom Study Biobank between July 12, 2021 and August 27, 2021 (Round 1), and between April 28, 2022 and June 21, 2022 (Round 2). Participants, recruited from the COVID Symptom Study smartphone app, comprised individuals with and without SARS-CoV-2 infection and varying symptom duration. Effects of COVID-19 exposures on cognitive accuracy and reaction time scores were estimated using multivariable ordinary least squares linear regression models weighted for inverse probability of participation, adjusting for potential confounders and mediators. The role of ongoing symptoms after COVID-19 infection was examined stratifying for self-perceived recovery. Longitudinal analysis assessed change in cognitive performance between rounds. FINDINGS: 3335 individuals completed Round 1, of whom 1768 also completed Round 2. At Round 1, individuals with previous positive SARS-CoV-2 tests had lower cognitive accuracy (N = 1737, β = −0.14 standard deviations, SDs, 95% confidence intervals, CI: −0.21, −0.07) than negative controls. Deficits were largest for positive individuals with ≥12 weeks of symptoms (N = 495, β = −0.22 SDs, 95% CI: −0.35, −0.09). Effects were comparable to hospital presentation during illness (N = 281, β = −0.31 SDs, 95% CI: −0.44, −0.18), and 10 years age difference (60–70 years vs. 50–60 years, β = −0.21 SDs, 95% CI: −0.30, −0.13) in the whole study population. Stratification by self-reported recovery revealed that deficits were only detectable in SARS-CoV-2 positive individuals who did not feel recovered from COVID-19, whereas individuals who reported full recovery showed no deficits. Longitudinal analysis showed no evidence of cognitive change over time, suggesting that cognitive deficits for affected individuals persisted at almost 2 years since initial infection. INTERPRETATION: Cognitive deficits following SARS-CoV-2 infection were detectable nearly two years post infection, and largest for individuals with longer symptom durations, ongoing symptoms, and/or more severe infection. However, no such deficits were detected in individuals who reported full recovery from COVID-19. Further work is needed to monitor and develop understanding of recovery mechanisms for those with ongoing symptoms. FUNDING: Chronic Disease Research Foundation, Wellcome Trust, National Institute for Health and Care Research, Medical Research Council, British Heart Foundation, Alzheimer's Society, European Union, COVID-19 Driver Relief Fund, French National Research Agency

Abnormal cognition, sleep, EEG and brain metabolism in a novel knock-in Alzheimer mouse, PLB1

Peer reviewedPublisher PD

CAMEMBERT: A Mini-Neptunes GCM Intercomparison, Protocol Version 1.0. A CUISINES Model Intercomparison Project

With an increased focus on the observing and modelling of mini-Neptunes, there comes a need to better understand the tools we use to model their atmospheres. In this paper, we present the protocol for the CAMEMBERT (Comparing Atmospheric Models of Extrasolar Mini-neptunes Building and Envisioning Retrievals and Transits) project, an intercomparison of general circulation models (GCMs) used by the exoplanetary science community to simulate the atmospheres of mini-Neptunes. We focus on two targets well studied both observationally and theoretically with planned JWST Cycle 1 observations: the warm GJ~1214b and the cooler K2-18b. For each target, we consider a temperature-forced case, a clear sky dual-grey radiative transfer case, and a clear sky multi band radiative transfer case, covering a range of complexities and configurations where we know differences exist between GCMs in the literature. This paper presents all the details necessary to participate in the intercomparison, with the intention of presenting the results in future papers. Currently, there are eight GCMs participating (ExoCAM, Exo-FMS, FMS PCM, Generic PCM, MITgcm, RM-GCM, THOR, and the UM), and membership in the project remains open. Those interested in participating are invited to contact the authors.Comment: Accepted to PS

Introduction: approaching space in intellectual history

This article serves as an introduction to the special issue on Conceptions of Space in Intellectual History. It opens with a brief inquiry into the place of ‘space’, both as a topic and as an analytical lens, in the field of intellectual history. The remainder of the introduction suggests a pathway through the special issue. Under three broad headings – ‘territory,’ ‘oceans and empire’, and ‘geopolitics’ – the volume’s articles are presented, brought into dialogue, and situated within a wider trajectory of recent research on conceptions of ‘space’ in intellectual history.Arts and Humanities Research Council; Cambridge Commonwealth, European & International Trust; Levy-Plumb Fund for the Humanities at Christ's College, Cambridge

Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities. The purpose of NINJA is to study the sensitivity of existing gravitational-wave search algorithms using numerically generated waveforms and to foster closer collaboration between the numerical relativity and data analysis communities. We describe the results of the first NINJA analysis which focused on gravitational waveforms from binary black hole coalescence. Ten numerical relativity groups contributed numerical data which were used to generate a set of gravitational-wave signals. These signals were injected into a simulated data set, designed to mimic the response of the Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this data using search and parameter-estimation pipelines. Matched filter algorithms, un-modelled-burst searches and Bayesian parameter-estimation and model-selection algorithms were applied to the data. We report the efficiency of these search methods in detecting the numerical waveforms and measuring their parameters. We describe preliminary comparisons between the different search methods and suggest improvements for future NINJA analyses.Comment: 56 pages, 25 figures; various clarifications; accepted to CQ

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 $10^{-22}$.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