UKESM1: description and evaluation of the UK Earth System Model

We document the development of the first version of the United Kingdom Earth System Model UKESM1. The model represents a major advance on its predecessor HadGEM2‐ES, with enhancements to all component models and new feedback mechanisms. These include: a new core physical model with a well‐resolved stratosphere; terrestrial biogeochemistry with coupled carbon and nitrogen cycles and enhanced land management; tropospheric‐stratospheric chemistry allowing the holistic simulation of radiative forcing from ozone, methane and nitrous oxide; two‐moment, five‐species, modal aerosol; and ocean biogeochemistry with two‐way coupling to the carbon cycle and atmospheric aerosols. The complexity of coupling between the ocean, land and atmosphere physical climate and biogeochemical cycles in UKESM1 is unprecedented for an Earth system model. We describe in detail the process by which the coupled model was developed and tuned to achieve acceptable performance in key physical and Earth system quantities, and discuss the challenges involved in mitigating biases in a model with complex connections between its components. Overall the model performs well, with a stable pre‐industrial state, and good agreement with observations in the latter period of its historical simulations. However, global mean surface temperature exhibits stronger‐than‐observed cooling from 1950 to 1970, followed by rapid warming from 1980 to 2014. Metrics from idealised simulations show a high climate sensitivity relative to previous generations of models: equilibrium climate sensitivity (ECS) is 5.4 K, transient climate response (TCR) ranges from 2.68 K to 2.85 K, and transient climate response to cumulative emissions (TCRE) is 2.49 K/TtC to 2.66 K/TtC

Long-term follow-up to ensure quality care of individuals diagnosed with newborn screening conditions: early experience in New England

To fulfill the purpose of newborn screening, comprehensive newborn screening programs must ensure that infants and children with newborn screening conditions are not only diagnosed but also they maintain engagement in appropriate lifespan and family-centered care for best outcomes. To ensure success, monitoring and care-coordination requires a systems-based approach to streamline the significant surveillance activities, which must not overburden the critical core functions of newborn screening nor the health care delivery system. Furthermore, treatment and care can only be improved by translating reliable knowledge into changes in practice, a process that requires evaluations of outcomes that are confirmable at the local level and translatable into a larger, e.g., national data set. We describe a sustainable public health systems approach to long-term follow-up, built on existing comprehensive newborn screening infrastructure and compatible with national endeavors. We also describe early experience with implementation of a centralized public-health tracking model and show that a significant proportion of cases detected through newborn screening do not continue with subspecialty care as they get older

NERC UKESM1.ice-LL model output prepared for CMIP6 ISMIP6

Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets: These data include all datasets published for 'CMIP6.ISMIP6.NERC.UKESM1-ice-LL' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The UKESM1.ice-N96ORCA1 climate model, released in 2019, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), land: JULES-ISMIP6-1.0, landIce: BISICLES-UKESM-ISMIP6-1.0, ocean: NEMO-HadGEM3-GO6.0 (eORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 360 x 330 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA1 tripolar primarily 1 deg; 360 x 330 longitude/latitude). The model was run by the Natural Environment Research Council, STFC-RAL, Harwell, Oxford, OX11 0QX, UK (NERC) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, landIce: 5 km, ocean: 100 km, seaIce: 100 km. Project: These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. - Project website: https://pcmdi.llnl.gov/CMIP6

FXR inhibition may protect from SARS-CoV-2 infection by reducing ACE2.

Preventing SARS-CoV-2 infection by modulating viral host receptors, such as angiotensin-converting enzyme 2 (ACE2)1, could represent a new chemoprophylactic approach for COVID-19 that complements vaccination2,3. However, the mechanisms that control the expression of ACE2 remain unclear. Here we show that the farnesoid X receptor (FXR) is a direct regulator of ACE2 transcription in several tissues affected by COVID-19, including the gastrointestinal and respiratory systems. We then use the over-the-counter compound z-guggulsterone and the off-patent drug ursodeoxycholic acid (UDCA) to reduce FXR signalling and downregulate ACE2 in human lung, cholangiocyte and intestinal organoids and in the corresponding tissues in mice and hamsters. We show that the UDCA-mediated downregulation of ACE2 reduces susceptibility to SARS-CoV-2 infection in vitro, in vivo and in human lungs and livers perfused ex situ. Furthermore, we reveal that UDCA reduces the expression of ACE2 in the nasal epithelium in humans. Finally, we identify a correlation between UDCA treatment and positive clinical outcomes after SARS-CoV-2 infection using retrospective registry data, and confirm these findings in an independent validation cohort of recipients of liver transplants. In conclusion, we show that FXR has a role in controlling ACE2 expression and provide evidence that modulation of this pathway could be beneficial for reducing SARS-CoV-2 infection, paving the way for future clinical trials

FXR inhibition may protect from SARS-CoV-2 infection by reducing ACE2.

Acknowledgements: We thank the European Association for the Study of the Liver (EASL) and the American Association for the Study of Liver Disease (AASLD) for supporting the COVID-Hep and SECURE-Liver registries; S. Marciniak and P. J. Lehner for comments and feedback on the manuscript; I. Goodfellow for providing the viral isolate; M. Wills and S. Clare for all their work ensuring a safe CL-3 working environment; C. Cormie for general lab support; the NIHR Cambridge BRC Cell Phenotyping Hub for their help with flow cytometry and processing of samples; the building staff of the Jeffrey Cheah Biomedical Centre for maintaining the institute open and safe during the period of lockdown; K. Füssel for coordinating the volunteer study and sample collection at the University Medical Centre Hamburg-Eppendorf; J. Hails, K.-I. Nikitopoulou and A. Ford for collecting blood samples; M. Colzani for advising on flow cytometry; A. Wiblin for advising on antibodies; and the Cambridge Biorepository for Translational Medicine for the provision of human tissue used in the study. T.B. was supported by an EASL Juan Rodès PhD fellowship. F.S. was supported by a UKRI Future Leaders fellowship, the Evelyn trust, an NIHR Clinical Lectureship, the Academy of Medical Sciences Starter Grant for Clinical Lecturers, the Addenbrooke’s Charitable Trust and the Rosetrees Trust. In addition, the F.S. laboratory is supported by the Cambridge University Hospitals National Institute for Health Research Biomedical Research Centre and the core support grant from the Wellcome Trust and Medical Research Council (MRC) of the Wellcome–Medical Research Council Cambridge Stem Cell Institute. The L.V. laboratory is funded by the ERC advanced grant New-Chol, the Cambridge University Hospitals National Institute for Health Research Biomedical Research Centre and the core support grant from the Wellcome Trust and MRC of the Wellcome–Medical Research Council Cambridge Stem Cell Institute. M.M., S.F. and G.D. are funded by the NIHR Cambridge Biomedical Research Centre and NIHR AMR Research Capital Funding Scheme (NIHR200640). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. V.L.M. was funded by an MRC Clinical Research Training Fellowship. G.F.M. was funded by a post-doctoral fellowship from the National Institute for Health Research (NIHR) Rare Diseases–Translational Research Collaboration (RD-TRC) and by an MRC Clinical Academic Research Partnership (CARP) award. The UK-PBC Nested Cohort study was funded by an MRC Stratified Medicine award (MR/L001489/1). C.J.R.I. was supported by the Medical Research Council (MC_UU_12014). T.M. is funded by a Wellcome Trust Clinical Research Training Fellowship (102176/B/13/Z). The A.P.D. laboratory was supported by BHF TG/18/4/33770, Wellcome Trust 203814/Z/16/A and Addenbrooke’s Charitable Trust. The COVID-Hep.net registry was supported by the European Association for the Study of the Liver (EASL) and the SECURE-Liver registry was supported by the American Association for the Study of Liver Disease (AASLD). The lung perfusion experiment was supported by the National Institute for Health Research Blood and Transplant Research Unit (NIHR BTRU) in Organ Donation and Transplantation at Newcastle University and the University of Cambridge in partnership with NHS Blood and Transplant (NHSBT). The views expressed are those of the author(s) and not necessarily those of the NIHR, the Department of Health and Social Care or NHSBT. G.B. is funded by the European Reference Network for Hepatological Diseases (ERN RARE LIVER). A.O. acknowledges funding for preclinical research on treatment and prevention of COVID-19 from Unitaid (2020-38-LONGEVITY), the Engineering and Physical Sciences Research Council (EPSRC; EP/R024804/1), the Wellcome Trust (222489/Z/21/Z) and UK Research and Innovation (UKRI; BB/W010801/1). N.J.M. acknowledges funding from the MRC (CSF ref. MR/P008801/1 to N.J.M.), NHSBT (grant ref. WPA15-02 to N.J.M.) and Addenbrooke’s Charitable Trust (grant ref. to 900239 N.J.M.). This research was funded in whole, or in part, by the Wellcome Trust (203151/Z/16/Z, 203151/A/16/Z) and the UKRI Medical Research Council (MC_PC_17230). For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.Preventing SARS-CoV-2 infection by modulating viral host receptors, such as angiotensin-converting enzyme 2 (ACE2)1, could represent a new chemoprophylactic approach for COVID-19 that complements vaccination2,3. However, the mechanisms that control the expression of ACE2 remain unclear. Here we show that the farnesoid X receptor (FXR) is a direct regulator of ACE2 transcription in several tissues affected by COVID-19, including the gastrointestinal and respiratory systems. We then use the over-the-counter compound z-guggulsterone and the off-patent drug ursodeoxycholic acid (UDCA) to reduce FXR signalling and downregulate ACE2 in human lung, cholangiocyte and intestinal organoids and in the corresponding tissues in mice and hamsters. We show that the UDCA-mediated downregulation of ACE2 reduces susceptibility to SARS-CoV-2 infection in vitro, in vivo and in human lungs and livers perfused ex situ. Furthermore, we reveal that UDCA reduces the expression of ACE2 in the nasal epithelium in humans. Finally, we identify a correlation between UDCA treatment and positive clinical outcomes after SARS-CoV-2 infection using retrospective registry data, and confirm these findings in an independent validation cohort of recipients of liver transplants. In conclusion, we show that FXR has a role in controlling ACE2 expression and provide evidence that modulation of this pathway could be beneficial for reducing SARS-CoV-2 infection, paving the way for future clinical trials

Clinical validation of cutoff target ranges in newborn screening of metabolic disorders by tandem mass spectrometry: A worldwide collaborative project

PURPOSE:: To achieve clinical validation of cutoff values for newborn screening by tandem mass spectrometry through a worldwide collaborative effort. METHODS:: Cumulative percentiles of amino acids and acylcarnitines in dried blood spots of approximately 25-30 million normal newborns and 10,742 deidentified true positive cases are compared to assign clinical significance, which is achieved when the median of a disorder range is, and usually markedly outside, either the 99th or the 1st percentile of the normal population. The cutoff target ranges of analytes and ratios are then defined as the interval between selected percentiles of the two populations. When overlaps occur, adjustments are made to maximize sensitivity and specificity taking all available factors into consideration. RESULTS:: As of December 1, 2010, 130 sites in 45 countries have uploaded a total of 25,114 percentile data points, 565,232 analyte results of true positive cases with 64 conditions, and 5,341 cutoff values. The average rate of submission of true positive cases between December 1, 2008, and December 1, 2010, was 5.1 cases/day. This cumulative evidence generated 91 high and 23 low cutoff target ranges. The overall proportion of cutoff values within the respective target range was 42% (2,269/5,341). CONCLUSION:: An unprecedented level of cooperation and collaboration has allowed the objective definition of cutoff target ranges for 114 markers to be applied to newborn screening of rare metabolic disorders. © 2011 Lippincott Williams & Wilkins

Coronal Heating as Determined by the Solar Flare Frequency Distribution Obtained by Aggregating Case Studies

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counter-intuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfv\'en waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold, $\alpha=2$ as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed $>$600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: pre-flare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine that $\alpha = 1.63 \pm 0.03$. This is below the critical threshold, suggesting that Alfv\'en waves are an important driver of coronal heating.Comment: 1,002 authors, 14 pages, 4 figures, 3 tables, published by The Astrophysical Journal on 2023-05-09, volume 948, page 7