The use of national datasets to baseline science education reform: exploring value-added approaches

This paper uses data from the National Pupil Database to investigate the differences in ‘performance’ across the range of science courses available following the 2006 Key Stage 4 (KS4) science reforms in England. This is a value-added exploration (from Key Stage 3 [KS3] to KS4) aimed not at the student or the school level, but rather at that of the course. Different methodological approaches to carrying out such an analysis, ranging from simple non-contextualized techniques, to more complex fully contextualized multilevel models, are investigated and their limitations and benefits are evaluated. Important differences between courses are found in terms of the typical ‘value’ they add to the students studying them with particular applied science courses producing higher mean KS4 outcomes for the same KS3 level compared with other courses. The implications of the emergence of such differences, in a context where schools are judged to a great extent on their value-added performance, are discussed. The relative importance of a variety of student characteristics in determining KS4 outcomes are also investigated. Substantive findings are that across all types of course, science prior attainment at KS3, rather than that of mathematics or English, is the most important predictor of KS4 performance in science, and that students of lower socio-economic status consistently make less progress over KS4 than might be expected, despite prior attainment being accounted for in the modelling

Autonomous Demand Response for Primary Frequency Regulation

The research documented within this report examines the use of autonomous demand response to provide primary frequency response in an interconnected power grid. The work builds on previous studies in several key areas: it uses a large realistic model (i.e., the interconnection of the western United States and Canada); it establishes a set of metrics that can be used to assess the effectiveness of autonomous demand response; and it independently adjusts various parameters associated with using autonomous demand response to assess effectiveness and to examine possible threats or vulnerabilities associated with the technology

The role of community-based Hubs in reef restoration: Collaborative monitoring at Moore Reef

The Cairns-Port Douglas region is home to multiple coral rehabilitation and stewardship projects supported by scientists, Traditional Owners, and a range of local stakeholders. The Cairns-Port Douglas Reef Hub has been a platform for collaboration across Traditional Owners, tourism operators, not-for-profits and scientists from the Reef Restoration and Adaptation Program (AIMS and CSIRO) to design and deliver a project at Moore Reef that assesses how new techniques for assisted coral recovery can be applied in rubble habitats. The collaborative project evaluates the viability of newly engineered coral seeding devices developed by AIMS, for deploying coral recruits that were spawned in the National Sea Simulator in December 2022 to sites at Moore Reef close to tourist pontoons. This project provides important data to inform future scaling up of restoration activities and provides a model for active involvement of a range of partners. Through this work, the project builds understanding around key ingredients for best-practice, place-based engagement opportunities for Reef communities and the general public

The potential for modelling peatland habitat condition in Scotland using long-term MODIS data

Funding: All James Hutton Institute authors are supported by the Scottish Government’s Rural and Environment Research and Analysis Directorate under the current Strategic Research Programme (2016-2021). Sally Johnson, Patricia Bruneau and Louise Ross did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors for this project. The peat spatial extent model was created in part within a UK Government – Department for Business, Energy and Industrial Strategy-funded project (TRN860/07/2014, Scoping the use of the methodology set out in Chapters 2 and 3 of the ‘2013 Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands in the UK GHG Inventory: Land Use, Land Use Change and Forestry (LULUCF)), with further updates created within the Strategic Research Programme (2016-2021) funding.Peer reviewedPostprin

Sleep EEG in young people with 22q11.2 deletion syndrome:a cross-sectional study of slow-waves, spindles and correlations with memory and neurodevelopmental symptoms

Background:: Young people living with 22q11.2 Deletion Syndrome (22q11.2DS) are at increased risk of schizophrenia, intellectual disability, attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). In common with these conditions, 22q11.2DS is also associated with sleep problems. We investigated whether abnormal sleep or sleep-dependent network activity in 22q11.2DS reflects convergent, early signatures of neural circuit disruption also evident in associated neurodevelopmental conditions. Methods:: In a cross-sectional design, we recorded high-density sleep EEG in young people (6–20 years) with 22q11.2DS (n=28) and their unaffected siblings (n=17), quantifying associations between sleep architecture, EEG oscillations (spindles and slow waves) and psychiatric symptoms. We also measured performance on a memory task before and after sleep. Results:: 22q11.2DS was associated with significant alterations in sleep architecture, including a greater proportion of N3 sleep and lower proportions of N1 and REM sleep than in siblings. During sleep, deletion carriers showed broadband increases in EEG power with increased slow-wave and spindle amplitudes, increased spindle frequency and density, and stronger coupling between spindles and slow-waves. Spindle and slow-wave amplitudes correlated positively with overnight memory in controls, but negatively in 22q11.2DS. Mediation analyses indicated that genotype effects on anxiety, ADHD and ASD were partially mediated by sleep EEG measures. Conclusions:: This study provides a detailed description of sleep neurophysiology in 22q11.2DS, highlighting alterations in EEG signatures of sleep which have been previously linked to neurodevelopment, some of which were associated with psychiatric symptoms. Sleep EEG features may therefore reflect delayed or compromised neurodevelopmental processes in 22q11.2DS, which could inform our understanding of the neurobiology of this condition and be biomarkers for neuropsychiatric disorders. Funding:: This research was funded by a Lilly Innovation Fellowship Award (UB), the National Institute of Mental Health (NIMH 5UO1MH101724; MvdB), a Wellcome Trust Institutional Strategic Support Fund (ISSF) award (MvdB), the Waterloo Foundation (918-1234; MvdB), the Baily Thomas Charitable Fund (2315/1; MvdB), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment (IMAGINE) (MR/L011166/1; JH, MvdB and MO), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment 2 (IMAGINE-2) (MR/T033045/1; MvdB, JH and MO); Wellcome Trust Strategic Award ‘Defining Endophenotypes From Integrated Neurosciences’ Wellcome Trust (100202/Z/12/Z MO, JH). NAD was supported by a National Institute for Health Research Academic Clinical Fellowship in Mental Health and MWJ by a Wellcome Trust Senior Research Fellowship in Basic Biomedical Science (202810/Z/16/Z). CE and HAM were supported by Medical Research Council Doctoral Training Grants (C.B.E. 1644194, H.A.M MR/K501347/1). HMM and UB were employed by Eli Lilly & Co during the study; HMM is currently an employee of Boehringer Ingelheim Pharma GmbH & Co KG. The views and opinions expressed are those of the author(s), and not necessarily those of the NHS, the NIHR or the Department of Health funders

Sleep EEG in young people with 22q11.2 deletion syndrome: A cross-sectional study of slow-waves, spindles and correlations with memory and neurodevelopmental symptoms

Background:: Young people living with 22q11.2 Deletion Syndrome (22q11.2DS) are at increased risk of schizophrenia, intellectual disability, attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). In common with these conditions, 22q11.2DS is also associated with sleep problems. We investigated whether abnormal sleep or sleep-dependent network activity in 22q11.2DS reflects convergent, early signatures of neural circuit disruption also evident in associated neurodevelopmental conditions. Methods:: In a cross-sectional design, we recorded high-density sleep EEG in young people (6–20 years) with 22q11.2DS (n=28) and their unaffected siblings (n=17), quantifying associations between sleep architecture, EEG oscillations (spindles and slow waves) and psychiatric symptoms. We also measured performance on a memory task before and after sleep. Results:: 22q11.2DS was associated with significant alterations in sleep architecture, including a greater proportion of N3 sleep and lower proportions of N1 and REM sleep than in siblings. During sleep, deletion carriers showed broadband increases in EEG power with increased slow-wave and spindle amplitudes, increased spindle frequency and density, and stronger coupling between spindles and slow-waves. Spindle and slow-wave amplitudes correlated positively with overnight memory in controls, but negatively in 22q11.2DS. Mediation analyses indicated that genotype effects on anxiety, ADHD and ASD were partially mediated by sleep EEG measures. Conclusions:: This study provides a detailed description of sleep neurophysiology in 22q11.2DS, highlighting alterations in EEG signatures of sleep which have been previously linked to neurodevelopment, some of which were associated with psychiatric symptoms. Sleep EEG features may therefore reflect delayed or compromised neurodevelopmental processes in 22q11.2DS, which could inform our understanding of the neurobiology of this condition and be biomarkers for neuropsychiatric disorders. Funding:: This research was funded by a Lilly Innovation Fellowship Award (UB), the National Institute of Mental Health (NIMH 5UO1MH101724; MvdB), a Wellcome Trust Institutional Strategic Support Fund (ISSF) award (MvdB), the Waterloo Foundation (918-1234; MvdB), the Baily Thomas Charitable Fund (2315/1; MvdB), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment (IMAGINE) (MR/L011166/1; JH, MvdB and MO), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment 2 (IMAGINE-2) (MR/T033045/1; MvdB, JH and MO); Wellcome Trust Strategic Award ‘Defining Endophenotypes From Integrated Neurosciences’ Wellcome Trust (100202/Z/12/Z MO, JH). NAD was supported by a National Institute for Health Research Academic Clinical Fellowship in Mental Health and MWJ by a Wellcome Trust Senior Research Fellowship in Basic Biomedical Science (202810/Z/16/Z). CE and HAM were supported by Medical Research Council Doctoral Training Grants (C.B.E. 1644194, H.A.M MR/K501347/1). HMM and UB were employed by Eli Lilly & Co during the study; HMM is currently an employee of Boehringer Ingelheim Pharma GmbH & Co KG. The views and opinions expressed are those of the author(s), and not necessarily those of the NHS, the NIHR or the Department of Health funders

Key questions for modelling COVID-19 exit strategies

Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health

Characterisation of the pro-inflammatory cytokine signature in severe COVID-19

Clinical outcomes from infection with SARS-CoV-2, the cause of the COVID-19 pandemic, are remarkably variable ranging from asymptomatic infection to severe pneumonia and death. One of the key drivers of this variability is differing trajectories in the immune response to SARS-CoV-2 infection. Many studies have noted markedly elevated cytokine levels in severe COVID-19, although results vary by cohort, cytokine studied and sensitivity of assay used. We assessed the immune response in acute COVID-19 by measuring 20 inflammatory markers in 118 unvaccinated patients with acute COVID-19 (median age: 70, IQR: 58-79 years; 48.3% female) recruited during the first year of the pandemic and 44 SARS-CoV-2 naïve healthy controls. Acute COVID-19 was associated with marked elevations in nearly all pro-inflammatory markers, whilst eleven markers (namely IL-1β, IL-2, IL-6, IL-10, IL-18, IL-23, IL-33, TNF-α, IP-10, G-CSF and YKL-40) were associated with disease severity. We observed significant correlations between nearly all markers elevated in those infected with SARS-CoV-2 consistent with widespread immune dysregulation. Principal component analysis highlighted a pro-inflammatory cytokine signature (with strongest contributions from IL-1β, IL-2, IL-6, IL-10, IL-33, G-CSF, TNF-α and IP-10) which was independently associated with severe COVID-19 (aOR: 1.40, 1.11-1.76, p=0.005), invasive mechanical ventilation (aOR: 1.61, 1.19-2.20, p=0.001) and mortality (aOR 1.57, 1.06-2.32, p = 0.02). Our findings demonstrate elevated cytokines and widespread immune dysregulation in severe COVID-19, adding further evidence for the role of a pro-inflammatory cytokine signature in severe and critical COVID-19

RA-MAP, molecular immunological landscapes in early rheumatoid arthritis and healthy vaccine recipients

Rheumatoid arthritis (RA) is a chronic inflammatory disorder with poorly defined aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the peripheral blood immune cell landscape of early, drug naive RA, we performed comprehensive clinical and molecular profiling of 267 RA patients and 52 healthy vaccine recipients for up to 18 months to establish a high quality sample biobank including plasma, serum, peripheral blood cells, urine, genomic DNA, RNA from whole blood, lymphocyte and monocyte subsets. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and autoantibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource offering insights into immune-mediated disease pathogenesis, progression and therapeutic response, ultimately contributing to the development and application of targeted therapies for RA.</p