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1. The Response of Planetary Atmospheres to the Impact of Icy Comets I: Tidally-Locked exo-Earths

Author

Sainsbury-Martinez, Felix, Walsh, Catherine, and Cooke, Greg

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Impacts by rocky and icy bodies are thought to have played a key role in shaping the composition of solar system objects, including the Earth's habitability. Hence, it is likely that they play a similar role in exoplanetary systems. We investigate how an icy cometary impact affects the atmospheric chemistry, climate, and composition of an Earth-like, tidally-locked, terrestrial exoplanet, a prime target in the search for a habitable exoplanet beyond our solar system. We couple a cometary impact model which includes thermal ablation and pressure driven breakup with the 3D Earth System Model WACCM6/CESM2, and use this model to investigate the effects of the water and thermal energy delivery associated with an $R=2.5$ km pure water ice cometary impact on an Earth-like atmosphere. We find that water is the primary driver of longer timescale changes to the atmospheric chemistry and composition by acting as a source of opacity, cloud ice, and atmospheric hydrogen/oxygen. The water opacity drives heating at $\sim5\times10^{-4}$ bar, and cooling below, due to a decreased flux reaching the surface. The increase in atmospheric hydrogen and oxygen also drives an increase in the abundance of hydrogen/oxygen rich molecules, with the exception of ozone, whose column density decreases by $\sim10\%$. These atmospheric changes are potentially observable for $\sim$ 1-2 years post-impact, particularly those associated with cloud ice scattering. They also persist, albeit at a much reduced level, to our quasi-steady-state, suggesting that sustained bombardment or multiple large impacts have the potential to shape the composition and habitability of terrestrial exoplanets., Comment: Accepted for Publication in ApJ

Published
2024

2. Flows, Circulations, and Energy Transport in the Outer and Deep Atmospheres of Synchronous and Non-synchronous Hot Jupiters

Author

Sainsbury-Martinez, Felix and Tremblin, Pascal

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Recent studies have shown that vertical enthalpy transport can explain the inflated radii of highly irradiated gaseous exoplanets. They have also shown that rotation can influence this transport, leading to highly irradiated, rapidly rotating, objects that are uninflated. Here we explore the underlying flows, including the impact of (non)synchronous rotation. We use DYNAMICO to run a series of long-timescale, HD209-like, atmospheric models at various surface rotation rates. For models that are tidally-locked, we consider rotation rates between $1/16^\mathrm{th}$ and $40$ times the rotation rate of HD209, whilst for non-synchronous models we consider the range $1/8^\mathrm{th}$ to $4$x. We find that our synchronous models fall into one of three $\Omega$-dependent regimes: at low $\Omega$, we find that the outer atmosphere dynamics are driven by a divergent day-night wind, driving weak vertical transport and the formation of a night-side hot-spot. At intermediate $\Omega$, we find classical hot Jupiter dynamics, whilst at high $\Omega$ we find a strong Coriolis effect that suppresses off-equator dynamics, including the jet-driving standing waves, thus also reducing vertical transport. As for non-synchronicity, when small, we find that it has little effect on dynamics. However as it grows, we find that temporal variations prevents the formation of the persistent structures that drive global dynamics. We find that rotation can significantly impact the atmospheric dynamics of irradiated exoplanets, including vertical advection, which may explain the scatter in the radius-irradiation relation. We have also identified a seemingly robust feature at slow rotation: a night-side hot-spot. As this may have important implications for both the phase curve and atmospheric chemistry, we suggest that this study be followed up with next-generation GCMs that robustly model radiation/chemistry., Comment: Accepted for publication in A&A

Published
2024
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3. Asymmetries in the simulated ozone distribution on TRAPPIST-1e due to orography

Author

Bhongade, Anand, Marsh, Daniel R, Sainsbury-Martinez, Felix, and Cooke, Gregory J

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

TRAPPIST-1e is a tidally locked rocky exoplanet orbiting the habitable zone of an M dwarf star. Upcoming observations are expected to reveal new rocky exoplanets and their atmospheres around M dwarf stars. To interpret these future observations we need to model the atmospheres of such exoplanets. We configured CESM2-WACCM6, a chemistry climate model, for the orbit and stellar irradiance of TRAPPIST-1e assuming an initial Earth-like atmospheric composition. Our aim is to characterize the possible ozone (O$_3$) distribution and explore how this is influenced by the atmospheric circulation shaped by orography, using the Helmholtz wind decomposition and meridional mass streamfunction. The model included Earth-like orography and the substellar point was located over the Pacific Ocean. For such a scenario, our analysis reveals a North-South asymmetry in the simulated O$_3$ distribution. The O$_3$ concentration is highest at pressures $>$ 10 hPa (below $\sim$30 km) near the South Pole. This asymmetry arises from the higher landmass fraction in the Northern Hemisphere, which causes drag in near-surface flows and leads to an asymmetric meridional overturning circulation. Catalytic species were roughly symmetrically distributed and were not found to be primary driver for the O$_3$ asymmetry. The total ozone column (TOC) density was higher for TRAPPIST-1e compared to Earth, with 8000 Dobson Units (DU) near the South Pole and 2000 DU near the North Pole. The results emphasise the sensitivity of O$_3$ to model parameters, illustrating how incorporating Earth-like orography can affect atmospheric dynamics and O$_3$ distribution. This link between surface features and atmospheric dynamics underlines the importance of how changing model parameters used to study exoplanet atmospheres can influence the interpretation of observations., Comment: Accepted for publication in ApJ

Published
2024

4. How Land-Mass Distribution Influences the Atmospheric Dynamics of Tidally Locked Terrestrial Exoplanets

Author

Sainsbury-Martinez, F., Walsh, C., Cooke, G. J., and Marsh, D. R.

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Interpretation of the ongoing efforts to simulate the atmospheres of potentially-habitable terrestrial exoplanets requires that we understand the underlying dynamics and chemistry of such objects to a much greater degree than 1D or even simple 3D models enable. Here, for the tidally-locked habitable-zone planet TRAPPIST-1e, we explore one effect which can shape the dynamics and chemistry of terrestrial planets: the inclusion of an Earth-like land-ocean distribution with orography. To do this we use the Earth-system model WACCM6/CESM2 to run a pair of TRAPPIST-1e models with N$_2$-O$_2$ atmospheres and with the sub-stellar point fixed over either land or ocean. The presence of orography shapes atmospheric transport, and in the case of Earth-like orography, breaks the symmetry between the northern and southern hemispheres which was previously found in slab ocean models. For example, peak zonal jet speeds in the southern hemisphere are $50\rightarrow100\%$ faster than similar jets in the northern hemisphere. This also affects the meridional circulation, transporting equatorial material towards the south-pole. As a result we also find significant changes in the atmospheric chemistry, including the accumulation of potentially lethal quantities of ozone at both the south pole and the surface. Future studies which investigate the effects of land-mass distribution on the dynamics of exoplanetary atmospheres should pay close attention to both the day-side land-fraction as well as the orography of the land. Simply modelling a flat land-mass will not give a complete picture of its dynamical impact., Comment: Accepted for publication in ApJ

Published
2024

5. Lethal surface ozone concentrations are possible on habitable zone exoplanets

Author

Cooke, G. J., Marsh, D. R., Walsh, C., and Sainsbury-Martinez, F.

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Ozone ($\textrm{O}_3$) is important for the survival of life on Earth because it shields the surface from ionising ultraviolet (UV) radiation. However, the existence of $\textrm{O}_3$ in Earth's atmosphere is not always beneficial. Resulting from anthropogenic activity, $\textrm{O}_3$ exists as a biologically harmful pollutant at the surface when it forms in the presence of sunlight and other pollutants. As a strong oxidiser, $\textrm{O}_3$ can be lethal to several different organisms; thus, when assessing the potential habitability of an exoplanet, a key part is determining whether toxic gases could be present at its surface. Using the Whole Atmosphere Community Climate Model version 6 (WACCM6; a three-dimensional chemistry-climate model), twelve atmospheric simulations of the terrestrial exoplanet TRAPPIST-1 e are performed with a variety of $\textrm{O}_2$ concentrations and assuming two different stellar spectra proposed in the literature. Four atmospheric simulations of the exoplanet Proxima Centauri b are also included. Some scenarios for both exoplanets exhibit time-averaged surface $\textrm{O}_3$ mixing ratios exceeding harmful levels of 40 ppbv, with 2200 ppbv the maximum concentration found in the cases simulated. These concentrations are toxic and can be fatal to most life on Earth. In other scenarios $\textrm{O}_3$ remains under harmful limits over a significant fraction of the surface, despite there being present regions which may prove inhospitable. In the case that $\textrm{O}_3$ is detected in a terrestrial exoplanet's atmosphere, determining the surface concentration is an important step when evaluating a planet's habitability., Comment: 24 pages, 8 figures. Accepted in The Planetary Science Journal

Published
2024

6. Neural Methods for Amortized Inference

Author

Zammit-Mangion, Andrew, Sainsbury-Dale, Matthew, and Huser, Raphaël

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Computation
Abstract

Simulation-based methods for statistical inference have evolved dramatically over the past 50 years, keeping pace with technological advancements. The field is undergoing a new revolution as it embraces the representational capacity of neural networks, optimization libraries and graphics processing units for learning complex mappings between data and inferential targets. The resulting tools are amortized, in the sense that, after an initial setup cost, they allow rapid inference through fast feed-forward operations. In this article we review recent progress in the context of point estimation, approximate Bayesian inference, summary-statistic construction, and likelihood approximation. We also cover software, and include a simple illustration to showcase the wide array of tools available for amortized inference and the benefits they offer over Markov chain Monte Carlo methods. The article concludes with an overview of relevant topics and an outlook on future research directions., Comment: 45 pages, 11 figures, 2 tables

Published
2024

8. Rigid frameworks with dilation constraints

Author

Dewar, Sean, Nixon, Anthony, and Sainsbury, Andrew

Subjects
Mathematics - Combinatorics, Mathematics - Metric Geometry
Abstract

We consider the rigidity and global rigidity of bar-joint frameworks in Euclidean $d$-space under additional dilation constraints in specified coordinate directions. In this setting we obtain a complete characterisation of generic rigidity. We then consider generic global rigidity. In particular, we provide an algebraic sufficient condition and a weak necessary condition. We also construct a large family of globally rigid frameworks and conjecture a combinatorial characterisation when most coordinate directions have dilation constraints., Comment: 15 pages, 1 figure

Published
2024

9. The Impact of Cometary 'impacts' on the Chemistry, Climate, and Spectra of Hot Jupiter Atmospheres

Author

Sainsbury-Martinez, Felix and Walsh, Catherine

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Impacts from icy and rocky bodies have helped shape the composition of solar system objects, for example the Earth-Moon system, or the recent impact of comet Shoemaker-Levy 9 with Jupiter. It is likely that such impacts also shape the composition of exoplanetary systems. Here we investigate how cometary impacts might affect the atmospheric composition/chemistry of hot Jupiters, which are prime targets for characterisation. We introduce a parametrised cometary impact model that includes thermal ablation and pressure driven breakup, which we couple with the 1D `radiative-convective' atmospheric model ATMO, including disequilibrium chemistry. We use this model to investigate a wide range of impactor masses and compositions, including those based on observations of Solar System comets, and interstellar ices (with JWST). We find that even a small impactor (R = 2.5 km) can lead to significant short-term changes in the atmospheric chemistry, including a factor $>10$ enhancement in H$_2$O, CO, CO$_2$ abundances, and atmospheric opacity more generally, and the near complete removal of observable hydrocarbons, such as CH$_4$, from the upper atmosphere. These effects scale with the change in atmospheric C/O ratio and metallicity. Potentially observable changes are possible for a body that has undergone significant/continuous bombardment, such that the global atmospheric chemistry has been impacted. Our works reveals that cometary impacts can significantly alter or pollute the atmospheric composition/chemistry of hot Jupiters. These changes have the potential to mute/break the proposed link between atmospheric C/O ratio and planet formation location relative to key snowlines in the natal protoplanetary disc., Comment: Accepted for publication in ApJ

Published
2024

11. Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks

Author

Sainsbury-Dale, Matthew, Zammit-Mangion, Andrew, Richards, Jordan, and Huser, Raphaël

Subjects
Statistics - Methodology, Statistics - Machine Learning
Abstract

Neural Bayes estimators are neural networks that approximate Bayes estimators in a fast and likelihood-free manner. Although they are appealing to use with spatial models, where estimation is often a computational bottleneck, neural Bayes estimators in spatial applications have, to date, been restricted to data collected over a regular grid. These estimators are also currently dependent on a prescribed set of spatial locations, which means that the neural network needs to be re-trained for new data sets; this renders them impractical in many applications and impedes their widespread adoption. In this work, we employ graph neural networks to tackle the important problem of parameter point estimation from data collected over arbitrary spatial locations. In addition to extending neural Bayes estimation to irregular spatial data, our architecture leads to substantial computational benefits, since the estimator can be used with any configuration or number of locations and independent replicates, thus amortising the cost of training for a given spatial model. We also facilitate fast uncertainty quantification by training an accompanying neural Bayes estimator that approximates a set of marginal posterior quantiles. We illustrate our methodology on Gaussian and max-stable processes. Finally, we showcase our methodology on a data set of global sea-surface temperature, where we estimate the parameters of a Gaussian process model in 2161 spatial regions, each containing thousands of irregularly-spaced data points, in just a few minutes with a single graphics processing unit.

Published
2023

14. The optimal second-line therapy for older adults with type 2 diabetes mellitus: protocol for a systematic review and network meta-analysis using individual participant data (IPD)

Author

Wang, Jingya, Nirantharakumar, Krishnarajah, Sainsbury, Christopher, Moore, David J., Sinclair, Alan, Thomas, G. Neil, Hanif, Wasim, Singh, Megha, Tan, Luyuan, Wang, Zhaonan, Simms-Williams, Nikita, Yao, Mi, Gunathilaka, M. Niluka, Singh, Pushpa, Toulis, Konstantinos, Tsapas, Apostolos, Coomar, Dyuti, and Price, Malcolm James

Published
2024
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16. Association of smoking with knee osteoarthritis structural defects and symptoms: an individual participant data meta-analysis

Author

Zubeyir Salis and Amanda Sainsbury

Subjects
Knee osteoarthritis, Smoking, Medicine, Science
Abstract

Abstract Prior meta-analyses have suggested a protective link between smoking and knee osteoarthritis (KOA), but they relied on aggregate data, potentially obscuring the true relationship. To address this limitation, we conducted an Individual Participant Data (IPD) meta-analysis using data from three large cohorts: the Osteoarthritis Initiative (OAI), the Multicenter Osteoarthritis Study (MOST), and the Cohort Hip and Cohort Knee (CHECK) study. Participants from 16 centers in the USA and Netherlands were categorized as current, former, or never smokers. We assessed six outcomes, three related to structural changes over 4–5 years of follow-up, and three related to changes in KOA symptoms over 2–2.5 years, 5 years, and 7–8 years of follow-up. First, the incidence of radiographic KOA was evaluated in 10,072 knees, defined as having a Kellgren-Lawrence grade ≥ 2 (‘radiographic KOA’) at follow-up but not at baseline. Second, the progression of radiographic KOA was evaluated in 5274 knees, defined as an increase in Kellgren–Lawrence grade between baseline and follow-up in knees that had radiographic KOA at baseline. Third, the incidence of symptomatic KOA was evaluated in 12,910 knees, defined as having radiographic KOA in addition to symptoms at follow-up but not at baseline. Fourth, fifth, and sixth, we investigated changes between baseline and all follow-ups in scores for the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) subscales of pain, disability, and stiffness (in 2640 knees). There were no differences between smoking groups in any of these six outcomes. Our study, leveraging data from three large cohorts and the advantages of IPD, finds no evidence that smoking offers any protection against KOA, refuting the notion that smoking may benefit joint health.

Published
2024
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17. Evaluation of a Discrimination Training Procedure for Establishing Praise as a Reinforcer

Author

Erin L. Sainsbury, Tina M. Sidener, Catherine Taylor-Santa, Kenneth F. Reeve, and David W. Sidener

Abstract

We evaluated the effects of a discrimination training procedure for establishing praise as a reinforcer for three children with autism spectrum disorder. After establishing two praise words as discriminative stimuli and two nonsense words as S-deltas, we evaluated whether the stimuli then functioned as reinforcers by presenting each stimulus as a consequence for a new response. The results demonstrated that previously neutral praise words functioned as reinforcers and nonsense words did not. As in previous studies on establishing reinforcers, the effects were transitory, and praise words did not continue to function as reinforcers after repeated exposure without discrimination training. Recommendations are provided for future research and maintaining reinforcement effects.

Published
2024
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18. Characterising The Atmospheric Dynamics Of HD209458b-like Hot Jupiters Using AI Driven Image Recognition/Categorisation

Author

Sainsbury-Martinez, F., Tremblin, P., Mancip, M., Donfack, S., Honore, E., and Bourenane, M.

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

In-order to understand the results of recent observations of exoplanets, models have become increasingly complex. Unfortunately this increases both the computational cost and output size of said models. We intend to explore if AI-image-recognition can alleviate this burden. We used DYNAMICO to run a series of HD209458-like models with different orbital-radii. Training data for a number of features of interest was selected from the initial outputs of these models. This was used to train a pair of multi-categorisation convolutional-neural-networks (CNN), which we applied to our outer-atmosphere-equilibrated models. The features detected by our CNNs revealed that our models fall into two regimes: models with a shorter orbital-radii exhibit significant global mixing which shapes the entire atmospheres dynamics. Whereas, models with longer orbital-radii exhibit negligible mixing except at mid-pressures. Here, the initial non-detection of any trained features revealed a surprise: a night-side hot-spot. Analysis suggests that this occurs when rotational influence is sufficiently weak that divergent flows from the day-side to the night-side dominate over rotational-driven transport, such as the equatorial jet. We suggest that image-classification may play an important role in future, computational, atmospheric studies. However special care must be paid to the data feed into the model, from the colourmap, to training the CNN on features with enough breadth and complexity that the CNN can learn to detect them. However, by using preliminary-studies and prior-models, this should be more than achievable for future exascale calculations, allowing for a significant reduction in future workloads and computational resources., Comment: Accepted for publication in ApJ

Published
2023

21. Neural Bayes estimators for censored inference with peaks-over-threshold models

Author

Richards, Jordan, Sainsbury-Dale, Matthew, Zammit-Mangion, Andrew, and Huser, Raphaël

Subjects
Statistics - Methodology, Statistics - Machine Learning
Abstract

Making inference with spatial extremal dependence models can be computationally burdensome since they involve intractable and/or censored likelihoods. Building on recent advances in likelihood-free inference with neural Bayes estimators, that is, neural networks that approximate Bayes estimators, we develop highly efficient estimators for censored peaks-over-threshold models that {use data augmentation techniques} to encode censoring information in the neural network {input}. Our new method provides a paradigm shift that challenges traditional censored likelihood-based inference methods for spatial extremal dependence models. Our simulation studies highlight significant gains in both computational and statistical efficiency, relative to competing likelihood-based approaches, when applying our novel estimators to make inference with popular extremal dependence models, such as max-stable, $r$-Pareto, and random scale mixture process models. We also illustrate that it is possible to train a single neural Bayes estimator for a general censoring level, precluding the need to retrain the network when the censoring level is changed. We illustrate the efficacy of our estimators by making fast inference on hundreds-of-thousands of high-dimensional spatial extremal dependence models to assess extreme particulate matter 2.5 microns or less in diameter (${\rm PM}_{2.5}$) concentration over the whole of Saudi Arabia.

Published
2023

22. Evidence of Radius Inflation in Radiative GCM Models of WASP-76b due to the Advection of Potential Temperature

Author

Sainsbury-Martinez, Felix, Tremblin, Pascal, Schneider, Aaron David, Carone, Ludmila, Baraffe, Isabelle, Chabrier, Gilles, Helling, Christiane, Decin, Leen, and Jørgensen, Uffe Gråe

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Understanding the discrepancy between the radii of observed hot Jupiters and standard 'radiative-convective' models remains a hotly debated topic in the exoplanet community. One mechanism which has been proposed to bridge this gap, and which has recently come under scrutiny, is the vertical advection of potential temperature from the irradiated outer atmosphere deep into the interior, heating the deep, unirradiated, atmosphere, warming the internal adiabat, and resulting in radius inflation. Specifically, a recent study which explored the atmosphere of WASP-76b using a 3D, non-grey, GCM suggested that their models lacked radius inflation, and hence any vertical enthalpy advection. Here we perform additional analysis of these, and related, models, focusing on an explicit analysis of vertical enthalpy transport and the resulting heating of the deep atmosphere compared with 1D models. Our results indicate that, after any evolution linked with initialisation, all the WASP-76b models considered here exhibit significant vertical enthalpy transport, heating the deep atmosphere significantly when compared with standard 1D models. Furthermore, comparison of a long time-scale (and hence near steady-state) model with a Jupiter-like internal-structure model suggests not only strong radius-inflation, but also that the model radius, $1.98 \mathrm{R_{J}}$, may be comparable with observations ($1.83\pm0.06 \mathrm{R_{J}}$). We thus conclude that the vertical advection of potential temperature alone is enough to explain the radius inflation of WASP-76b, and potentially other irradiated gas giants, albeit with the proviso that the exact strength of the vertical advection remains sensitive to model parameters, such as the inclusion of deep atmospheric drag., Comment: Accepted for publication in MNRAS

Published
2023
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23. Investigation of the association of weight loss with radiographic hip osteoarthritis in older community-dwelling female adults.

Author

Salis, Zubeyir, Lui, Li-Yung, Lane, Nancy E, Ensrud, Kristine, and Sainsbury, Amanda

Subjects
aging, female, hip, osteoarthritis, weight loss, Prevention, Osteoporosis, Nutrition, Aging, Obesity, Arthritis, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Musculoskeletal, Medical and Health Sciences, Geriatrics
Abstract

ObjectiveMost guidelines recommending weight loss for hip osteoarthritis are based on research on knee osteoarthritis. Prior studies found no association between weight loss and hip osteoarthritis, but no previous studies have targeted older adults. Therefore, we aimed to determine whether there is any clear benefit of weight loss for radiographic hip osteoarthritis in older adults because weight loss is associated with health risks in older adults.MethodsWe used data from white female participants aged ≥65 years from the Study of Osteoporotic Fractures. Our exposure of interest was weight change from baseline to follow-up at 8 years. Our outcomes were the development of radiographic hip osteoarthritis (RHOA) and the progression of RHOA over 8 years. Generalized estimating equations (clustering of 2 hips per participant) were used to investigate the association between exposure and outcomes adjusted for major covariates.ResultsThere was a total of 11,018 hips from 5509 participants. There was no associated benefit of weight loss for either of our outcomes. The odds ratios (95% confidence intervals) for the development and progression of RHOA were 0.99 (0.92-1.07) and 0.97 (0.86-1.09) for each 5% weight loss, respectively. The results were consistent in sensitivity analyses where participants were limited to those who reported trying to lose weight and who also had a body mass index in the overweight or obese range.ConclusionOur findings suggest no associated benefit of weight loss in older female adults in the structure of the hip joint as assessed by radiography.

Published
2023

26. Stratified analyses refine association between TLR7 rare variants and severe COVID-19

Author

Jannik Boos, Caspar I. van der Made, Gayatri Ramakrishnan, Eamon Coughlan, Rosanna Asselta, Britt-Sabina Löscher, Luca V.C. Valenti, Rafael de Cid, Luis Bujanda, Antonio Julià, Erola Pairo-Castineira, J. Kenneth Baillie, Sandra May, Berina Zametica, Julia Heggemann, Agustín Albillos, Jesus M. Banales, Jordi Barretina, Natalia Blay, Paolo Bonfanti, Maria Buti, Javier Fernandez, Sara Marsal, Daniele Prati, Luisa Ronzoni, Nicoletta Sacchi, Joachim L. Schultze, Olaf Riess, Andre Franke, Konrad Rawlik, David Ellinghaus, Alexander Hoischen, Axel Schmidt, Kerstin U. Ludwig, Valeria Rimoldi, Elvezia M. Paraboschi, Alessandra Bandera, Flora Peyvandi, Giacomo Grasselli, Francesco Blasi, Francesco Malvestiti, Serena Pelusi, Cristiana Bianco, Lorenzo Miano, Angela Lombardi, Pietro Invernizzi, Alessio Gerussi, Giuseppe Citerio, Andrea Biondi, Maria Grazia Valsecchi, Marina Elena Cazzaniga, Giuseppe Foti, Ilaria Beretta, Mariella D'Angiò, Laura Rachele Bettini, Xavier Farré, Susana Iraola-Guzmán, Manolis Kogevinas, Gemma Castaño-Vinyals, Koldo Garcia-Etxebarria, Beatriz Nafria, Mauro D'Amato, Adriana Palom, Colin Begg, Sara Clohisey, Charles Hinds, Peter Horby, Julian Knight, Lowell Ling, David Maslove, Danny McAuley, Johnny Millar, Hugh Montgomery, Alistair Nichol, Peter J.M. Openshaw, Alexandre C. Pereira, Chris P. Ponting, Kathy Rowan, Malcolm G. Semple, Manu Shankar-Hari, Charlotte Summers, Timothy Walsh, Latha Aravindan, Ruth Armstrong, Heather Biggs, Ceilia Boz, Adam Brown, Richard Clark, Audrey Coutts, Judy Coyle, Louise Cullum, Sukamal Das, Nicky Day, Lorna Donnelly, Esther Duncan, Angie Fawkes, Paul Fineran, Max Head Fourman, Anita Furlong, James Furniss, Bernadette Gallagher, Tammy Gilchrist, Ailsa Golightly, Fiona Griffiths, Katarzyna Hafezi, Debbie Hamilton, Ross Hendry, Andy Law, Dawn Law, Rachel Law, Sarah Law, Rebecca Lidstone-Scott, Louise Macgillivray, Alan Maclean, Hanning Mal, Sarah McCafferty, Ellie Mcmaster, Jen Meikle, Shona C. Moore, Kirstie Morrice, Lee Murphy, Sheena Murphy, Mybaya Hellen, Wilna Oosthuyzen, Chenqing Zheng, Jiantao Chen, Nick Parkinson, Trevor Paterson, Katherine Schon, Andrew Stenhouse, Mihaela Das, Maaike Swets, Helen Szoor-McElhinney, Filip Taneski, Lance Turtle, Tony Wackett, Mairi Ward, Jane Weaver, Nicola Wrobel, Marie Zechner, Gill Arbane, Aneta Bociek, Sara Campos, Neus Grau, Tim Owen Jones, Rosario Lim, Martina Marotti, Marlies Ostermann, Christopher Whitton, Zoe Alldis, Raine Astin-Chamberlain, Fatima Bibi, Jack Biddle, Sarah Blow, Matthew Bolton, Catherine Borra, Ruth Bowles, Maudrian Burton, Yasmin Choudhury, David Collier, Amber Cox, Amy Easthope, Patrizia Ebano, Stavros Fotiadis, Jana Gurasashvili, Rosslyn Halls, Pippa Hartridge, Delordson Kallon, Jamila Kassam, Ivone Lancoma-Malcolm, Maninderpal Matharu, Peter May, Oliver Mitchelmore, Tabitha Newman, Mital Patel, Jane Pheby, Irene Pinzuti, Zoe Prime, Oleksandra Prysyazhna, Julian Shiel, Melanie Taylor, Carey Tierney, Suzanne Wood, Anne Zak, Olivier Zongo, Stephen Bonner, Keith Hugill, Jessica Jones, Steven Liggett, Evie Headlam, Nageswar Bandla, Minnie Gellamucho, Michelle Davies, Christopher Thompson, Marwa Abdelrazik, Dhanalakshmi Bakthavatsalam, Munzir Elhassan, Arunkumar Ganesan, Anne Haldeos, Jeronimo Moreno-Cuesta, Dharam Purohit, Rachel Vincent, Kugan Xavier, Kumar Rohit, Frater Alasdair, Malik Saleem, Carter David, Jenkins Samuel, Zoe Lamond, Wall Alanna, Jaime Fernandez-Roman, David O. Hamilton, Emily Johnson, Brian Johnston, Maria Lopez Martinez, Suleman Mulla, David Shaw, Alicia A.C. Waite, Victoria Waugh, Ingeborg D. Welters, Karen Williams, Anna Cavazza, Maeve Cockrell, Eleanor Corcoran, Maria Depante, Clare Finney, Ellen Jerome, Mark McPhail, Monalisa Nayak, Harriet Noble, Kevin O'Reilly, Evita Pappa, Rohit Saha, Sian Saha, John Smith, Abigail Knighton, David Antcliffe, Dorota Banach, Stephen Brett, Phoebe Coghlan, Ziortza Fernandez, Anthony Gordon, Roceld Rojo, Sonia Sousa Arias, Maie Templeton, Megan Meredith, Lucy Morris, Lucy Ryan, Amy Clark, Julia Sampson, Cecilia Peters, Martin Dent, Margaret Langley, Saima Ashraf, Shuying Wei, Angela Andrew, Archana Bashyal, Neil Davidson, Paula Hutton, Stuart McKechnie, Jean Wilson, David Baptista, Rebecca Crowe, Rita Fernandes, Rosaleen Herdman-Grant, Anna Joseph, Denise O'Connor, Meryem Allen, Adam Loveridge, India McKenley, Eriko Morino, Andres Naranjo, Richard Simms, Kathryn Sollesta, Andrew Swain, Harish Venkatesh, Jacyntha Khera, Jonathan Fox, Gillian Andrew, Lucy Barclay, Marie Callaghan, Rachael Campbell, Sarah Clark, Dave Hope, Lucy Marshall, Corrienne McCulloch, Kate Briton, Jo Singleton, Sohphie Birch, Lutece Brimfield, Zoe Daly, David Pogson, Steve Rose, Ceri Battle, Elaine Brinkworth, Rachel Harford, Carl Murphy, Luke Newey, Tabitha Rees, Marie Williams, Sophie Arnold, Petra Polgarova, Katerina Stroud, Eoghan Meaney, Megan Jones, Anthony Ng, Shruti Agrawal, Nazima Pathan, Deborah White, Esther Daubney, Kay Elston, Lina Grauslyte, Musarat Hussain, Mandeep Phull, Tatiana Pogreban, Lace Rosaroso, Erika Salciute, George Franke, Joanna Wong, Aparna George, Laura Ortiz-Ruiz de Gordoa, Emily Peasgood, Claire Phillips, Michelle Bates, Jo Dasgin, Jaspret Gill, Annette Nilsson, James Scriven, Carlos Castro Delgado, Deborah Dawson, Lijun Ding, Georgia Durrant, Obiageri Ezeobu, Sarah Farnell-Ward, Abiola Harrison, Rebecca Kanu, Susannah Leaver, Elena Maccacari, Soumendu Manna, Romina Pepermans Saluzzio, Joana Queiroz, Tinashe Samakomva, Christine Sicat, Joana Texeira, Edna Fernandes Da Gloria, Ana Lisboa, John Rawlins, Jisha Mathew, Ashley Kinch, William James Hurt, Nirav Shah, Victoria Clark, Maria Thanasi, Nikki Yun, Kamal Patel, Sara Bennett, Emma Goodwin, Matthew Jackson, Alissa Kent, Clare Tibke, Wiesia Woodyatt, Ahmed Zaki, Azmerelda Abraheem, Peter Bamford, Kathryn Cawley, Charlie Dunmore, Maria Faulkner, Rumanah Girach, Helen Jeffrey, Rhianna Jones, Emily London, Imrun Nagra, Farah Nasir, Hannah Sainsbury, Clare Smedley, Tahera Patel, Matthew Smith, Srikanth Chukkambotla, Aayesha Kazi, Janice Hartley, Joseph Dykes, Muhammad Hijazi, Sarah Keith, Meherunnisa Khan, Janet Ryan-Smith, Philippa Springle, Jacqueline Thomas, Nick Truman, Samuel Saad, Dabheoc Coleman, Christopher Fine, Roseanna Matt, Bethan Gay, Jack Dalziel, Syamlan Ali, Drew Goodchild, Rhiannan Harling, Ravi Bhatterjee, Wendy Goddard, Chloe Davison, Stephen Duberly, Jeanette Hargreaves, Rachel Bolton, Miriam Davey, David Golden, Rebecca Seaman, Shiney Cherian, Sean Cutler, Anne Emma Heron, Anna Roynon-Reed, Tamas Szakmany, Gemma Williams, Owen Richards, Yusuf Cheema, Hollie Brooke, Sarah Buckley, Jose Cebrian Suarez, Ruth Charlesworth, Karen Hansson, John Norris, Alice Poole, Alastair Rose, Rajdeep Sandhu, Brendan Sloan, Elizabeth Smithson, Muthu Thirumaran, Veronica Wagstaff, Alexandra Metcalfe, Mark Brunton, Jess Caterson, Holly Coles, Matthew Frise, Sabi Gurung Rai, Nicola Jacques, Liza Keating, Emma Tilney, Shauna Bartley, Parminder Bhuie, Sian Gibson, Amanda Lyle, Fiona McNeela, Jayachandran Radhakrishnan, Alistair Hughes, Bryan Yates, Jessica Reynolds, Helen Campbell, Maria Thompsom, Steve Dodds, Stacey Duffy, Sandra Greer, Karen Shuker, Ascanio Tridente, Reena Khade, Ashok Sundar, George Tsinaslanidis, Isobel Birkinshaw, Joseph Carter, Kate Howard, Joanne Ingham, Rosie Joy, Harriet Pearson, Samantha Roche, Zoe Scott, Hollie Bancroft, Mary Bellamy, Margaret Carmody, Jacqueline Daglish, Faye Moore, Joanne Rhodes, Mirriam Sangombe, Salma Kadiri, Maria Croft, Ian White, Victoria Frost, Maia Aquino, Rajeev Jha, Vinodh Krishnamurthy, Lai Lim, Li Lim, Edward Combes, Teishel Joefield, Sonja Monnery, Valerie Beech, Sallyanne Trotman, Christine Almaden-Boyle, Pauline Austin, Louise Cabrelli, Stephen Cole, Matt Casey, Susan Chapman, Clare Whyte, Yolanda Baird, Aaron Butler, Indra Chadbourn, Linda Folkes, Heather Fox, Amy Gardner, Raquel Gomez, Gillian Hobden, Luke Hodgson, Kirsten King, Michael Margarson, Tim Martindale, Emma Meadows, Dana Raynard, Yvette Thirlwall, David Helm, Jordi Margalef, Kristine Criste, Rebecca Cusack, Kim Golder, Hannah Golding, Oliver Jones, Samantha Leggett, Michelle Male, Martyna Marani, Kirsty Prager, Toran Williams, Belinda Roberts, Karen Salmon, Peter Anderson, Katie Archer, Karen Austin, Caroline Davis, Alison Durie, Olivia Kelsall, Jessica Thrush, Charlie Vigurs, Laura Wild, Hannah-Louise Wood, Helen Tranter, Alison Harrison, Nicholas Cowley, Michael McAlindon, Andrew Burtenshaw, Stephen Digby, Emma Low, Aled Morgan, Naiara Cother, Tobias Rankin, Sarah Clayton, Alex McCurdy, Cecilia Ahmed, Balvinder Baines, Sarah Clamp, Julie Colley, Risna Haq, Anne Hayes, Jonathan Hulme, Samia Hussain, Sibet Joseph, Rita Kumar, Zahira Maqsood, Manjit Purewal, Leonie Benham, Zena Bradshaw, Joanna Brown, Melanie Caswell, Jason Cupitt, Sarah Melling, Stephen Preston, Nicola Slawson, Emma Stoddard, Scott Warden, Bethan Deacon, Ceri Lynch, Carla Pothecary, Lisa Roche, Gwenllian Sera Howe, Jayaprakash Singh, Keri Turner, Hannah Ellis, Natalie Stroud, Jodie Hunt, Joy Dearden, Emma Dobson, Andy Drummond, Michelle Mulcahy, Sheila Munt, Grainne O'Connor, Jennifer Philbin, Chloe Rishton, Redmond Tully, Sarah Winnard, Susanne Cathcart, Katharine Duffy, Alex Puxty, Kathryn Puxty, Lynne Turner, Jane Ireland, Gary Semple, Kate Long, Simon Whiteley, Elizabeth Wilby, Bethan Ogg, Amanda Cowton, Andrea Kay, Melanie Kent, Kathryn Potts, Ami Wilkinson, Suzanne Campbell, Ellen Brown, Julie Melville, Jay Naisbitt, Rosane Joseph, Maria Lazo, Olivia Walton, Alan Neal, Peter Alexander, Schvearn Allen, Joanne Bradley-Potts, Craig Brantwood, Jasmine Egan, Timothy Felton, Grace Padden, Luke Ward, Stuart Moss, Susannah Glasgow, Lynn Abel, Michael Brett, Brian Digby, Lisa Gemmell, James Hornsby, Patrick MacGoey, Pauline O'Neil, Richard Price, Natalie Rodden, Kevin Rooney, Radha Sundaram, Nicola Thomson, Bridget Hopkins, Laura Thrasyvoulou, Heather Willis, Martyn Clark, Martina Coulding, Edward Jude, Jacqueline McCormick, Oliver Mercer, Darsh Potla, Hafiz Rehman, Heather Savill, Victoria Turner, Charlotte Downes, Kathleen Holding, Katie Riches, Mary Hilton, Mel Hayman, Deepak Subramanian, Priya Daniel, Oluronke Adanini, Nikhil Bhatia, Maines Msiska, Rebecca Collins, Ian Clement, Bijal Patel, A. Gulati, Carole Hays, K. Webster, Anne Hudson, Andrea Webster, Elaine Stephenson, Louise McCormack, Victoria Slater, Rachel Nixon, Helen Hanson, Maggie Fearby, Sinead Kelly, Victoria Bridgett, Philip Robinson, Julie Camsooksai, Charlotte Humphrey, Sarah Jenkins, Henrik Reschreiter, Beverley Wadams, Yasmin Death, Victoria Bastion, Daphene Clarke, Beena David, Harriet Kent, Rachel Lorusso, Gamu Lubimbi, Sophie Murdoch, Melchizedek Penacerrada, Alastair Thomas, Jennifer Valentine, Ana Vochin, Retno Wulandari, Brice Djeugam, Gillian Bell, Katy English, Amro Katary, Louise Wilcox, Michelle Bruce, Karen Connolly, Tracy Duncan, Helen T-Michael, Gabriella Lindergard, Samuel Hey, Claire Fox, Jordan Alfonso, Laura Jayne Durrans, Jacinta Guerin, Bethan Blackledge, Jade Harris, Martin Hruska, Ayaa Eltayeb, Thomas Lamb, Tracey Hodgkiss, Lisa Cooper, Joanne Rothwell, Angela Allan, Felicity Anderson, Callum Kaye, Jade Liew, Jasmine Medhora, Teresa Scott, Erin Trumper, Adriana Botello, Liana Lankester, Nikitas Nikitas, Colin Wells, Bethan Stowe, Kayleigh Spencer, Craig Brandwood, Lara Smith, Katie Birchall, Laurel Kolakaluri, Deborah Baines, Anila Sukumaran, Elena Apetri, Cathrine Basikolo, Laura Catlow, Bethan Charles, Paul Dark, Reece Doonan, Alice Harvey, Daniel Horner, Karen Knowles, Stephanie Lee, Diane Lomas, Chloe Lyons, Tracy Marsden, Danielle McLaughlan, Liam McMorrow, Jessica Pendlebury, Jane Perez, Maria Poulaka, Nicola Proudfoot, Melanie Slaughter, Kathryn Slevin, Vicky Thomas, Danielle Walker, Angiy Michael, Matthew Collis, Tracey Cosier, Gemma Millen, Neil Richardson, Natasha Schumacher, Heather Weston, James Rand, Nicola Baxter, Steven Henderson, Sophie Kennedy-Hay, Christopher McParland, Laura Rooney, Malcolm Sim, Gordan McCreath, Louise Akeroyd, Shereen Bano, Matt Bromley, Lucy Gurr, Tom Lawton, James Morgan, Kirsten Sellick, Deborah Warren, Brian Wilkinson, Janet McGowan, Camilla Ledgard, Amelia Stacey, Kate Pye, Ruth Bellwood, Michael Bentley, Jeremy Bewley, Zoe Garland, Lisa Grimmer, Bethany Gumbrill, Rebekah Johnson, Katie Sweet, Denise Webster, Georgia Efford, Karen Convery, Deirdre Fottrell-Gould, Lisa Hudig, Jocelyn Keshet-Price, Georgina Randell, Katie Stammers, Maria Bokhari, Vanessa Linnett, Rachael Lucas, Wendy McCormick, Jenny Ritzema, Amanda Sanderson, Helen Wild, Anthony Rostron, Alistair Roy, Lindsey Woods, Sarah Cornell, Fiona Wakinshaw, Kimberley Rogerson, Jordan Jarmain, Robert Parker, Amie Reddy, Ian Turner-Bone, Laura Wilding, Peter Harding, Caroline Abernathy, Louise Foster, Andrew Gratrix, Vicky Martinson, Priyai Parkinson, Elizabeth Stones, Llucia Carbral-Ortega, Georgia Bercades, David Brealey, Ingrid Hass, Niall MacCallum, Gladys Martir, Eamon Raith, Anna Reyes, Deborah Smyth, Letizia Zitter, Sarah Benyon, Suzie Marriott, Linda Park, Samantha Keenan, Elizabeth Gordon, Helen Quinn, Kizzy Baines, Lenka Cagova, Adama Fofano, Lucie Garner, Helen Holcombe, Sue Mepham, Alice Michael Mitchell, Lucy Mwaura, Krithivasan Praman, Alain Vuylsteke, Julie Zamikula, Bally Purewal, Vanessa Rivers, Stephanie Bell, Hayley Blakemore, Borislava Borislavova, Beverley Faulkner, Emma Gendall, Elizabeth Goff, Kati Hayes, Matt Thomas, Ruth Worner, Kerry Smith, Deanna Stephens, Louise Mew, Esther Mwaura, Richard Stewart, Felicity Williams, Lynn Wren, Sara-Beth Sutherland, Emily Bevan, Jane Martin, Dawn Trodd, Geoff Watson, Caroline Wrey Brown, Amy Collins, Waqas Khaliq, Estefania Treus Gude, Olugbenga Akinkugbe, Alasdair Bamford, Emily Beech, Holly Belfield, Michael Bell, Charlene Davies, Gareth A.L. Jones, Tara McHugh, Hamza Meghari, Lauran O'Neill, Mark J. Peters, Samiran Ray, Ana Luisa Tomas, Iona Burn, Geraldine Hambrook, Katarina Manso, Ruth Penn, Pradeep Shanmugasundaram, Julie Tebbutt, Danielle Thornton, Jade Cole, Rhys Davies, Donna Duffin, Helen Hill, Ben Player, Emma Thomas, Angharad Williams, Denise Griffin, Nycola Muchenje, Mcdonald Mupudzi, Richard Partridge, Jo-Anna Conyngham, Rachel Thomas, Mary Wright, Maria Alvarez Corral, Reni Jacob, Cathy Jones, Craig Denmade, Sarah Beavis, Katie Dale, Rachel Gascoyne, Joanne Hawes, Kelly Pritchard, Lesley Stevenson, Amanda Whileman, Patricia Doble, Joanne Hutter, Corinne Pawley, Charmaine Shovelton, Marius Vaida, Deborah Butcher, Susie O'Sullivan, Nicola Butterworth-Cowin, Norfaizan Ahmad, Joann Barker, Kris Bauchmuller, Sarah Bird, Kay Cawthron, Kate Harrington, Yvonne Jackson, Faith Kibutu, Becky Lenagh, Shamiso Masuko, Gary H. Mills, Ajay Raithatha, Matthew Wiles, Jayne Willson, Helen Newell, Alison Lye, Lorenza Nwafor, Claire Jarman, Sarah Rowland-Jones, David Foote, Joby Cole, Roger Thompson, James Watson, Lisa Hesseldon, Irene Macharia, Luke Chetam, Jacqui Smith, Amber Ford, Samantha Anderson, Kathryn Birchall, Kay Housley, Sara Walker, Leanne Milner, Helena Hanratty, Helen Trower, Patrick Phillips, Simon Oxspring, Ben Donne, Catherine Jardine, Dewi Williams, Alasdair Hay, Rebecca Flanagan, Gareth Hughes, Scott Latham, Emma McKenna, Jennifer Anderson, Robert Hull, Kat Rhead, Carina Cruz, Natalie Pattison, Rob Charnock, Denise McFarland, Denise Cosgrove, Ashar Ahmed, Anna Morris, Srinivas Jakkula, Asifa Ali, Megan Brady, Sam Dale, Annalisa Dance, Lisa Gledhill, Jill Greig, Kathryn Hanson, Kelly Holdroyd, Marie Home, Diane Kelly, Ross Kitson, Lear Matapure, Deborah Melia, Samantha Mellor, Tonicha Nortcliffe, Jez Pinnell, Matthew Robinson, Lisa Shaw, Ryan Shaw, Lesley Thomis, Alison Wilson, Tracy Wood, Lee-Ann Bayo, Ekta Merwaha, Tahira Ishaq, Sarah Hanley, Meg Hibbert, Dariusz Tetla, Chrsitopher Woodford, Latha Durga, Gareth Kennard-Holden, Debbie Branney, Jordan Frankham, Sally Pitts, Nigel White, Shondipon Laha, Mark Verlander, Alexandra Williams, Abdelhakim Altabaibeh, Ana Alvaro, Kayleigh Gilbert, Louise Ma, Loreta Mostoles, Chetan Parmar, Kathryn Simpson, Champa Jetha, Lauren Booker, Anezka Pratley, Colene Adams, Anita Agasou, Tracie Arden, Amy Bowes, Pauline Boyle, Mandy Beekes, Heather Button, Nigel Capps, Mandy Carnahan, Anne Carter, Danielle Childs, Denise Donaldson, Kelly Hard, Fran Hurford, Yasmin Hussain, Ayesha Javaid, James Jones, Sanal Jose, Michael Leigh, Terry Martin, Helen Millward, Nichola Motherwell, Rachel Rikunenko, Jo Stickley, Julie Summers, Louise Ting, Helen Tivenan, Louise Tonks, Rebecca Wilcox, Maureen Holland, Natalie Keenan, Marc Lyons, Helen Wassall, Chris Marsh, Mervin Mahenthran, Emma Carter, Thomas Kong, Helen Blackman, Ben Creagh-Brown, Sinead Donlon, Natalia Michalak-Glinska, Sheila Mtuwa, Veronika Pristopan, Armorel Salberg, Eleanor Smith, Sarah Stone, Charles Piercy, Jerik Verula, Dorota Burda, Rugia Montaser, Lesley Harden, Irving Mayangao, Cheryl Marriott, Paul Bradley, Celia Harris, Susan Anderson, Eleanor Andrews, Janine Birch, Emma Collins, Kate Hammerton, Ryan O'Leary, Michele Clark, Sarah Purvis, Russell Barber, Claire Hewitt, Annette Hilldrith, Karen Jackson-Lawrence, Sarah Shepardson, Maryanne Wills, Susan Butler, Silvia Tavares, Amy Cunningham, Julia Hindale, Sarwat Arif, Sarah Bean, Karen Burt, Michael Spivey, Carrie Demetriou, Charlotte Eckbad, Sarah Hierons, Lucy Howie, Sarah Mitchard, Lidia Ramos, Alfredo Serrano-Ruiz, Katie White, Fiona Kelly, Daniele Cristiano, Natalie Dormand, Zohreh Farzad, Mahitha Gummadi, Kamal Liyanage, Brijesh Patel, Sara Salmi, Geraldine Sloane, Vicky Thwaites, Mathew Varghese, Anelise C. Zborowski, John Allan, Tim Geary, Gordon Houston, Alistair Meikle, Peter O'Brien, Miranda Forsey, Agilan Kaliappan, Anne Nicholson, Joanne Riches, Mark Vertue, Elizabeth Allan, Kate Darlington, Ffyon Davies, Jack Easton, Sumit Kumar, Richard Lean, Daniel Menzies, Richard Pugh, Xinyi Qiu, Llinos Davies, Hannah Williams, Jeremy Scanlon, Gwyneth Davies, Callum Mackay, Joannne Lewis, Stephanie Rees, Metod Oblak, Monica Popescu, Mini Thankachen, Andrew Higham, Kerry Simpson, Jayne Craig, Rosie Baruah, Sheila Morris, Susie Ferguson, Amy Shepherd, Luke Stephen Prockter Moore, Marcela Paola Vizcaychipi, Laura Gomes de Almeida Martins, Jaime Carungcong, Inthakab Ali Mohamed Ali, Karen Beaumont, Mark Blunt, Zoe Coton, Hollie Curgenven, Mohamed Elsaadany, Kay Fernandes, Sameena Mohamed Ally, Harini Rangarajan, Varun Sarathy, Sivarupan Selvanayagam, Dave Vedage, Matthew White, Mandy Gill, Paul Paul, Valli Ratnam, Sarah Shelton, Inez Wynter, Siobhain Carmody, Valerie Joan Page, Claire Marie Beith, Karen Black, Suzanne Clements, Alan Morrison, Dominic Strachan, Margaret Taylor, Michelle Clarkson, Stuart D'Sylva, Kathryn Norman, Fiona Auld, Joanne Donnachie, Ian Edmond, Lynn Prentice, Nikole Runciman, Dario Salutous, Lesley Symon, Anne Todd, Patricia Turner, Abigail Short, Laura Sweeney, Euan Murdoch, Dhaneesha Senaratne, Michaela Hill, Thogulava Kannan, Wild Laura, Rikki Crawley, Abigail Crew, Mishell Cunningham, Allison Daniels, Laura Harrison, Susan Hope, Ken Inweregbu, Sian Jones, Nicola Lancaster, Jamie Matthews, Alice Nicholson, Gemma Wray, Helen Langton, Rachel Prout, Malcolm Watters, Catherine Novis, Anthony Barron, Ciara Collins, Sundeep Kaul, Heather Passmore, Claire Prendergast, Anna Reed, Paula Rogers, Rajvinder Shokkar, Meriel Woodruff, Hayley Middleton, Oliver Polgar, Claire Nolan, Kanta Mahay, Dawn Collier, Anil Hormis, Victoria Maynard, Cheryl Graham, Rachel Walker, Ellen Knights, Alicia Price, Alice Thomas, Chris Thorpe, Teresa Behan, Caroline Burnett, Jonathan Hatton, Elaine Heeney, Atideb Mitra, Maria Newton, Rachel Pollard, Rachael Stead, Vishal Amin, Elena Anastasescu, Vikram Anumakonda, Komala Karthik, Rizwana Kausar, Karen Reid, Jacqueline Smith, Janet Imeson-Wood, Denise Skinner, Jane Gaylard, Dee Mullan, Julie Newman, Alison Brown, Vikki Crickmore, Gabor Debreceni, Joy Wilkins, Liz Nicol, Rosie Reece-Anthony, Mark Birt, Alison Ghosh, Emma Williams, Louise Allen, Eva Beranova, Nikki Crisp, Joanne Deery, Tracy Hazelton, Alicia Knight, Carly Price, Sorrell Tilbey, Salah Turki, Sharon Turney, Joshua Cooper, Cheryl Finch, Sarah Liderth, Alison Quinn, Natalia Waddington, Tina Coventry, Susan Fowler, Michael MacMahon, Amanda McGregor, Anne Cowley, Judith Highgate, Jane Gregory, Susan O'Connell, Tim Smith, Luigi Barberis, Shameer Gopal, Nichola Harris, Victoria Lake, Stella Metherell, Elizabeth Radford, Amelia Daniel, Joanne Finn, Rajnish Saha, Nikki White, Phil Donnison, Fiona Trim, Beena Eapen, Jenny Birch, Laura Bough, Josie Goodsell, Rebecca Tutton, Patricia Williams, Sarah Williams, Barbara Winter-Goodwin, Ailstair Nichol, Kathy Brickell, Michelle Smyth, Lorna Murphy, Samantha Coetzee, Alistair Gales, Igor Otahal, Meena Raj, Craig Sell, Paula Hilltout, Jayne Evitts, Amanda Tyler, Joanne Waldron, Kate Beesley, Sarah Board, Agnieszka Kubisz-Pudelko, Alison Lewis, Jess Perry, Lucy Pippard, Di Wood, Clare Buckley, Peter Barry, Neil Flint, Patel Rekha, Dawn Hales, Lara Bunni, Claire Jennings, Monica Latif, Rebecca Marshall, Gayathri Subramanian, Peter J. McGuigan, Christopher Wasson, Stephanie Finn, Jackie Green, Erin Collins, Bernadette King, Andy Campbell, Sara Smuts, Joseph Duffield, Oliver Smith, Lewis Mallon, Watkins Claire, Liam Botfield, Joanna Butler, Catherine Dexter, Jo Fletcher, Atul Garg, Aditya Kuravi, Poonam Ranga, Emma Virgilio, Zakaula Belagodu, Bridget Fuller, Anca Gherman, Olumide Olufuwa, Remi Paramsothy, Carmel Stuart, Naomi Oakley, Charlotte Kamundi, David Tyl, Katy Collins, Pedro Silva, June Taylor, Laura King, Charlotte Coates, Maria Crowley, Phillipa Wakefield, Jane Beadle, Laura Johnson, Janet Sargeant, Madeleine Anderson, Ailbhe Brady, Rebekah Chan, Jeff Little, Shane McIvor, Helena Prady, Helen Whittle, Bijoy Mathew, Ben Attwood, Penny Parsons, Geraldine Ward, Pamela Bremmer, West Joe, Baird Tracy, Ruddy Jim, Ellie Davies, Sonia Sathe, Catherine Dennis, Alastair McGregor, Victoria Parris, Sinduya Srikaran, Anisha Sukha, Noreen Clarke, Jonathan Whiteside, Mairi Mascarenhas, Avril Donaldson, Joanna Matheson, Fiona Barrett, Marianne O'Hara, Laura Okeefe, Clare Bradley, Christine Eastgate-Jackson, Helder Filipe, Daniel Martin, Amitaa Maharajh, Sara Mingo Garcia, Glykeria Pakou, Mark De Neef, Kathy Dent, Elizabeth Horsley, Muhmmad Nauman Akhtar, Sandra Pearson, Dorota Potoczna, Sue Spencer, Melanie Clapham, Rosemary Harper, Una Poultney, Polly Rice, Rachel Mutch, Lisa Armstrong, Hayley Bates, Emma Dooks, Fiona Farquhar, Brigid Hairsine, Chantal McParland, Sophie Packham, Rehana Bi, Barney Scholefield, Lydia Ashton, Linsha George, Sophie Twiss, David Wright, Manish Chablani, Amy Kirkby, Kimberley Netherton, Kim Davies, Linda O'Brien, Zohra Omar, Emma Perkins, Tracy Lewis, Isobel Sutherland, Karen Burns, Dr Ben Chandler, Kerry Elliott, Janine Mallinson, Alison Turnbull, Prisca Gondo, Bernard Hadebe, Abdul Kayani, Bridgett Masunda, Taya Anderson, Dan Hawcutt, Laura O'Malley, Laura Rad, Naomi Rogers, Paula Saunderson, Kathryn Sian Allison, Deborah Afolabi, Jennifer Whitbread, Dawn Jones, Rachael Dore, Matthew Halkes, Pauline Mercer, Lorraine Thornton, Joy Dawson, Sweyn Garrioch, Melanie Tolson, Jonathan Aldridge, Ritoo Kapoor, David Loader, Karen Castle, Sally Humphreys, Ruth Tampsett, Katherine Mackintosh, Amanda Ayers, Wendy Harrison, Julie North, Suzanne Allibone, Roman Genetu, Vidya Kasipandian, Amit Patel, Ainhi Mac, Anthony Murphy, Parisa Mahjoob, Roonak Nazari, Lucy Worsley, Andrew Fagan, Thomas Bemand, Ethel Black, Arnold Dela Rosa, Ryan Howle, Shaman Jhanji, Ravishankar Rao Baikady, Kate Colette Tatham, Benjamin Thomas, Dina Bell, Rosalind Boyle, Katie Douglas, Lynn Glass, Emma Lee, Liz Lennon, Austin Rattray, Abigail Taylor, Rachel Anne Hughes, Helen Thomas, Alun Rees, Michaela Duskova, Janet Phipps, Suzanne Brooks, Michelle Edwards, Sheena Quaid, Ekaterina Watson, Adam Brayne, Emma Fisher, Jane Hunt, Peter Jackson, Duncan Kaye, Nicholas Love, Juliet Parkin, Victoria Tuckey, Lynne Van Koutrik, Sasha Carter, Benedict Andrew, Louise Findlay, Katie Adams, Jen Service, Alison Williams, Claire Cheyne, Anne Saunderson, Sam Moultrie, Miranda Odam, Kathryn Hall, Isheunesu Mapfunde, Charlotte Willis, Alex Lyon, Chunda Sri-Chandana, Joslan Scherewode, Lorraine Stephenson, Sarah Marsh, John Hardy, Henry Houlden, Eleanor Moncur, Ambreen Tariq, Arianna Tucci, Maria Hobrok, Ronda Loosley, Heather McGuinness, Helen Tench, Rebecca Wolf-Roberts, Val Irvine, Benjamin Shelley, Claire Gorman, Abhinav Gupta, Elizabeth Timlick, Rebecca Brady, Barry Milligan, Arianna Bellini, Jade Bryant, Anton Mayer, Amy Pickard, Nicholas Roe, Jason Sowter, Alex Howlett, Katy Fidler, Emma Tagliavini, and Kevin Donnelly

Subjects
SARS-CoV-2, host genetics, toll-like receptor 7, targeted sequencing, rare variants, variant collapsing analysis, Genetics, QH426-470
Abstract

Summary: Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (

Published
2024
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27. VIVA BRITANNIA! HOW THE ROYAL NAVY CONQUERED HAVANA: After five years of neutrality in the Seven Years' War, in August 1761 Spain signed a secret pact with France that set the country on a collision course with the world's greatest naval power

Author

Sainsbury, Brendan

Subjects
Seven Years' War, 1756-1763 -- Military aspects, Neutrality -- Military aspects, History
Abstract

When King Charles III brought Spain into the Seven Years' War (1756-63) on the side of France, Austria and Sweden, he may have hoped that his nation's belated contribution would [...]

Published
2024

29. Age of Diagnosis for Co-Occurring Autism and Attention Deficit Hyperactivity Disorder during Childhood and Adolescence: A Systematic Review

Author

Willow J. Sainsbury, Kelly Carrasco, Andrew J. O. Whitehouse, Lauren McNeil, and Hannah Waddington

Abstract

Early identification and intervention are recognised as important elements of the clinical pathway for autism spectrum disorder (ASD). Children with ASD and attention deficit hyperactivity disorder (ADHD) may be diagnosed at a different age than children who only have one of these diagnoses. This systematic review aimed to identify the age at which children were diagnosed with both ASD and ADHD. Of the 9552 articles screened, 12 were included in the review. The findings suggest that ASD is typically diagnosed later when ADHD is present, and ADHD is typically diagnosed earlier when ASD is present. Further research is needed to understand the factors impacting a delayed ASD diagnosis and an earlier ADHD diagnosis when the two conditions co-occur.

Published
2023
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30. Youth Voices Creating Healthy Eating and Physically Active Environments in Schools

Author

Shah, Smita, Rizzo Liu, Kym, Lockett, Catriona, and Sainsbury, Emma

Abstract

Objective: The objectives of this study were to (1) measure the acceptability of Students As LifeStyle Activists (SALSA) Youth Voices (SYV) programme, (2) determine the skills gained by peer leaders from their participation in SYV and (3) determine whether peer leaders were able to design and implement an action to promote healthy eating and physical activity in their school. Design: Process evaluation. Setting: Peer leaders (aged 15-16 years) from high schools in Western Sydney, Australia. Method: We conducted a process evaluation to determine the reasons why students participated in SYV, which workshop activities they enjoyed, the skills they gained from participating in SYV and whether the actions were designed and implemented. Peer leaders completed an online survey at the end of the Leadership Day. The peer leaders then presented their actions at an SYV Action Day event and completed a further online survey. Results: Eighty-four peer leaders from seven high schools in Western Sydney participated in SYV. Peer leaders reported their involvement with the SYV programme as positive, with 68% rating it as 'very valuable'. Skills gained by the peer leaders included teamwork (90%), communication (85%), leadership (77%) and confidence (65%). Peer leaders planned and devised actions, which included installing water refill stations, fitting the school gymnasium with new equipment, redesigning girls' sports shorts, and other strategies to engage girls in physical activity. Students from all seven schools presented their actions to receive feedback and expressed confidence that their actions were sustainable. Conclusion: The SYV programme showed that providing peer leaders with ownership of their actions was successful in creating healthy school environments, while building leadership, teamwork, communication skills and confidence in adolescents.

Published
2023
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31. The role of post-tropical cyclones for European extreme weather

Author

Sainsbury, Elliott M., Schiemann, Reinhard, Hodges, Kevin, Baker, Alex, and Shaffrey, Len

Abstract

Post-tropical cyclones (PTCs) can bring extreme winds and heavy precipitation to Europe. This thesis aims to further our understanding of the hazards posed to Europe by PTCs, and the factors (environmental and cyclone-specific) governing their development, variability, and projected changes. It is shown that PTCs are disproportionately responsible for windstorm risk over Europe: Despite comprising less than 1% of the cyclones impacting Northern Europe during the North Atlantic hurricane season, approximately 9% of the cyclones impacting the region during the hurricane season with storm-force (>25 m s -1 ) winds are PTCs. The interannual variability of recurving North Atlantic tropical cyclones (TCs) - defined as TCs which reach the North Atlantic midlatitudes - is shown to be governed by TC activity in the Main Development Region and subtropical North Atlantic, with interannual variability in the seasonal mean steering flow playing a smaller, secondary role. PTCs which are stronger at their TC lifetime maximum intensity, or which reintensify after ET, are shown to be significantly more likely to reach Europe. Europeimpacting PTCs interact more strongly with an upstream trough in a more baroclinic environment and often reintensify upon crossing a midlatitude jet streak. Future projections of PTCs in five CMIP6 models are shown to capture many of the observed features of the TC and PTC climatologies in the North Atlantic, and the disproportionate risk associated with Europe-impacting PTCs. No robust 21st century change in Europe-impacting PTC frequency or intensity is found in these models, because two competing factors - a decrease in North Atlantic TC frequency, and an increase in the fraction of TCs reaching Europe - are of the same magnitude. This thesis provides a framework to understand the European PTC climatology and provides evidence of an uncertain future for European PTC risk.

Published
2023
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32. Public involvement in UK health and care research 1995–2020: reflections from a witness seminar

Author

Marisha Emily Palm, David Evans, Sophie Staniszewska, Louca-Mai Brady, Bec Hanley, Kate Sainsbury, Derek Stewart, and Paula Wray

Subjects
Public involvement, Public engagement, Patient and public involvement, Witness seminar, Social movement, NIHR, Medicine, Medicine (General), R5-920
Abstract

Abstract Background Public involvement is important to the relevance and impact of health and care research, as well as supporting the democratisation of research. In 2020, the National Institute for Health Research (NIHR) reorganized and eliminated INVOLVE, an internationally recognised group that had played a central role in public involvement in the UK since 1996. Its remit was subsumed within a new center tasked with public involvement, participant recruitment, and evidence dissemination. A year later, in 2021, interested parties came together to discuss the evolution of INVOLVE and consider how to retain some of the important historical details and learn lessons from its long and important tenure. Methods We hosted a witness seminar in 2022 that was one of four work groups and brought together public involvement leaders that had been part of the conception, development, and evolution of INVOLVE between 1995 and 2020. Witness seminars are a method used to capture the complexity and nuance of historical events or initiatives. They support critical thinking and reflection rather than simple commemoration. We identified those who had played a role in INVOLVE history, ensuring diversity of perspective, and invited them to attend and speak at the seminar. This took place during two sessions where witnesses provided their recollections and participated in a facilitated discussion. Results Across the two online sessions, 29 witnesses attended and contributed thoughts and recollections. Two authors (SS, MP) identified six themes that were described in the witness seminar report and have been discussed, elaborated, and illustrated with witness quotations. These are: the importance of historical perspective; INVOLVE as a social movement; how INVOLVE worked (e.g. its hospitality, kindness, and inclusivity); INVOLVE as a quiet disruptor; public involvement evidence, knowledge, and learning; the infrastructure, processes, and systems developed by INVOLVE; and the demise and loss of INVOLVE as an internationally recognized center of excellence. Discussion The authors of this commentary reflected on the discussions that took place during the witness seminar and the themes that emerged, and share six broad learnings for future practice; (1) it is important to create and nurture public involvement communities of practice; (2) collaborative ways of working support open discussion amongst diverse groups; (3) be aware of the tensions between activism and being part of the establishment; (4) continued efforts should be made to build an evidence base for public involvement practice; (5) there are both benefits and drawbacks to having a centralized organization leading public involvement; and (6) support for public involvement in research requires a fit-for-purpose tendering process that embeds robust public involvement.

Published
2024
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33. The optimal second-line therapy for older adults with type 2 diabetes mellitus: protocol for a systematic review and network meta-analysis using individual participant data (IPD)

Author

Jingya Wang, Krishnarajah Nirantharakumar, Christopher Sainsbury, David J. Moore, Alan Sinclair, G. Neil Thomas, Wasim Hanif, Megha Singh, Luyuan Tan, Zhaonan Wang, Nikita Simms-Williams, Mi Yao, M. Niluka Gunathilaka, Pushpa Singh, Konstantinos Toulis, Apostolos Tsapas, Dyuti Coomar, and Malcolm James Price

Subjects
Randomised controlled trials, Glucose-lowering agents, Glucagon-like peptide-1 agonists, Sodium-glucose cotransporter-2 inhibitors, Dipeptidyl peptidase-4 inhibitors, Biguanide, Medicine
Abstract

Abstract Background Due to increasing life expectancy, almost half of people with type 2 diabetes are aged 65 years or over worldwide. When metformin alone does not control blood sugar, the choice of which second-line therapy to prescribe next is not clear from currently available evidence. The existence of frailty and comorbidities in older adults further increases the complexity of medical decision-making. As only a relatively small proportion of trials report results separately for older adults, the relative efficacy and safety of second-line therapies in older adults with type 2 diabetes mellitus are unknown and require further investigation. This individual participant data (IPD) network meta-analysis evaluates the relative efficacy and safety of second-line therapies on their own or in combination in older adults with type 2 diabetes mellitus. Methods All relevant published and unpublished trials will be identified. Studies published prior to 2015 will be identified from two previous comprehensive aggregate data network meta-analyses. Searches will be conducted in CENTRAL, MEDLINE, and EMBASE from 1st January 2015 onwards, and in clinicaltrials.gov from inception. Randomised controlled trials with at least 100 estimated older adults (≥ 65 years) receiving at least 24 weeks of intervention that assess the effects of glucose-lowering drugs on mortality, glycemia, vascular and other comorbidities outcomes, and quality of life will be eligible. The screening and data extraction process will be conducted independently by two researchers. The quality of studies will be assessed using the Cochrane risk of bias tool 2. Anonymised IPD of all eligible trials will be requested via clinical trial portals or by contacting the principal investigators or sponsors. Received data will be reanalysed where necessary to standardise outcome metrics. Network meta-analyses will be performed to determine the relative effectiveness of therapies. Discussion With the increasing number of older adults with type 2 diabetes worldwide, an IPD network meta-analysis using data from all eligible trials will provide new insights into the optimal choices of second-line antidiabetic drugs to improve patient management and reduce unnecessary adverse events and the subsequent risk of comorbidities in older adults. Systematic review registration PROSPERO CRD42021272686.

Published
2024
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34. Likelihood-Free Parameter Estimation with Neural Bayes Estimators

Author

Sainsbury-Dale, Matthew, Zammit-Mangion, Andrew, and Huser, Raphaël

Subjects
Statistics - Methodology, Statistics - Machine Learning
Abstract

Neural point estimators are neural networks that map data to parameter point estimates. They are fast, likelihood free and, due to their amortised nature, amenable to fast bootstrap-based uncertainty quantification. In this paper, we aim to increase the awareness of statisticians to this relatively new inferential tool, and to facilitate its adoption by providing user-friendly open-source software. We also give attention to the ubiquitous problem of making inference from replicated data, which we address in the neural setting using permutation-invariant neural networks. Through extensive simulation studies we show that these neural point estimators can quickly and optimally (in a Bayes sense) estimate parameters in weakly-identified and highly-parameterised models with relative ease. We demonstrate their applicability through an analysis of extreme sea-surface temperature in the Red Sea where, after training, we obtain parameter estimates and bootstrap-based confidence intervals from hundreds of spatial fields in a fraction of a second., Comment: The American Statistician (2023)

Published
2022
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35. A Feasibility Study on Image Inpainting for Non-cleft Lip Generation from Patients with Cleft Lip

Author

Chen, Shuang, Atapour-Abarghouei, Amir, Kerby, Jane, Ho, Edmond S. L., Sainsbury, David C. G., Butterworth, Sophie, and Shum, Hubert P. H.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

A Cleft lip is a congenital abnormality requiring surgical repair by a specialist. The surgeon must have extensive experience and theoretical knowledge to perform surgery, and Artificial Intelligence (AI) method has been proposed to guide surgeons in improving surgical outcomes. If AI can be used to predict what a repaired cleft lip would look like, surgeons could use it as an adjunct to adjust their surgical technique and improve results. To explore the feasibility of this idea while protecting patient privacy, we propose a deep learning-based image inpainting method that is capable of covering a cleft lip and generating a lip and nose without a cleft. Our experiments are conducted on two real-world cleft lip datasets and are assessed by expert cleft lip surgeons to demonstrate the feasibility of the proposed method., Comment: 4 pages, 2 figures, BHI 2022

Published
2022

36. Eating disorders in weight-related therapy (EDIT): Protocol for a systematic review with individual participant data meta-analysis of eating disorder risk in behavioural weight management

Author

Jebeile, Hiba, Lister, Natalie B, Libesman, Sol, Hunter, Kylie E, McMaster, Caitlin M, Johnson, Brittany J, Baur, Louise A, Paxton, Susan J, Garnett, Sarah P, Ahern, Amy L, Wilfley, Denise E, Maguire, Sarah, Sainsbury, Amanda, Steinbeck, Katharine, Askie, Lisa, Braet, Caroline, Hill, Andrew J, Nicholls, Dasha, Jones, Rebecca A, Dammery, Genevieve, Grunseit, Alicia M, Cooper, Kelly, Kyle, Theodore K, Heeren, Faith A, Quigley, Fiona, Barnes, Rachel D, Bean, Melanie K, Beaulieu, Kristine, Bonham, Maxine, Boutelle, Kerri N, Branco, Braulio Henrique Magnani, Calugi, Simona, Cardel, Michelle I, Carpenter, Kelly, Cheng, Hoi Lun, Grave, Riccardo Dalle, Danielsen, Yngvild S, Demarzo, Marcelo, Dordevic, Aimee, Eichen, Dawn M, Goldschmidt, Andrea B, Hilbert, Anja, Houben, Katrijn, do Prado, Mara Lofrano, Martin, Corby K, McTiernan, Anne, Mensinger, Janell L, Pacanowski, Carly, do Prado, Wagner Luiz, Ramalho, Sofia M, Raynor, Hollie A, Rieger, Elizabeth, Robinson, Eric, Salvo, Vera, Sherwood, Nancy E, Simpson, Sharon A, Skjakodegard, Hanna F, Smith, Evelyn, Partridge, Stephanie, Tanofsky-Kraff, Marian, Taylor, Rachael W, Van Eyck, Annelies, Varady, Krista A, Vidmar, Alaina P, Whitelock, Victoria, Yanovski, Jack, Seidler, Anna L, and Collaboration, on behalf of the Eating Disorders In weight-related Therapy

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Health Sciences, Brain Disorders, Obesity, Clinical Research, Mental Illness, Behavioral and Social Science, Eating Disorders, Nutrition, Mental Health, Clinical Trials and Supportive Activities, Prevention, 3.1 Primary prevention interventions to modify behaviours or promote wellbeing, 6.6 Psychological and behavioural, Mental health, Metabolic and endocrine, Stroke, Oral and gastrointestinal, Adult, Adolescent, Humans, Overweight, Feeding and Eating Disorders, Behavior Therapy, Systematic Reviews as Topic, Meta-Analysis as Topic, Eating Disorders In weight-related Therapy (EDIT) Collaboration, General Science & Technology
Abstract

The Eating Disorders In weight-related Therapy (EDIT) Collaboration brings together data from randomised controlled trials of behavioural weight management interventions to identify individual participant risk factors and intervention strategies that contribute to eating disorder risk. We present a protocol for a systematic review and individual participant data (IPD) meta-analysis which aims to identify participants at risk of developing eating disorders, or related symptoms, during or after weight management interventions conducted in adolescents or adults with overweight or obesity. We systematically searched four databases up to March 2022 and clinical trials registries to May 2022 to identify randomised controlled trials of weight management interventions conducted in adolescents or adults with overweight or obesity that measured eating disorder risk at pre- and post-intervention or follow-up. Authors from eligible trials have been invited to share their deidentified IPD. Two IPD meta-analyses will be conducted. The first IPD meta-analysis aims to examine participant level factors associated with a change in eating disorder scores during and following a weight management intervention. To do this we will examine baseline variables that predict change in eating disorder risk within intervention arms. The second IPD meta-analysis aims to assess whether there are participant level factors that predict whether participation in an intervention is more or less likely than no intervention to lead to a change in eating disorder risk. To do this, we will examine if there are differences in predictors of eating disorder risk between intervention and no-treatment control arms. The primary outcome will be a standardised mean difference in global eating disorder score from baseline to immediately post-intervention and at 6- and 12- months follow-up. Identifying participant level risk factors predicting eating disorder risk will inform screening and monitoring protocols to allow early identification and intervention for those at risk.

Published
2023

38. Food web structure, the hub index and identifying species of ecological significance

Author

E.A. Fulton and K. Sainsbury

Subjects
Ecology, QH540-549.5
Abstract

Ecosystem based fisheries management (EBFM) attempts to take a broader perspective to the management of natural resources. To date it has often focused on the status of specific stocks, species or habitats. Consideration of ecosystem structure has not received as much attention, but lessons from engineering suggest that indicators of structure can highlight whether critical connections in the ecosystem are receiving sufficient management attention. We apply concepts of criticality analysis and the identification of “hub nodes” in networks – which we call hub species – to model ecosystems and long-term diet data. This method highlights both top predators and connected forage species as key ecosystem connectors that need attention under EBFM. The exact identity of these species differs among systems, showing that this method can provide system specificity, which is a key attribute for the acceptance of EBFM tools.

Published
2024
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39. Guidelines to support the design, and selection and appraisal of multimedia teaching aids for microbiology education

Author

R. Van Beek, D. J. C. Spijkerman, N. van derBurgt, B. Hermanns, S. Barendse, P. D. Sainsbury, K. N. Timmis, and J. K. Timmis

Subjects
Biotechnology, TP248.13-248.65
Abstract

Abstract Microbiology education has a serious handicap – the lack of visibility of the players of the subject and their interactions – which engenders a disproportionate reliance upon multimedia teaching aids (MTAs). The International Microbiology Literacy Initiative (IMiLI) is creating educational resources in societally‐relevant microbiology complemented by appropriate MTAs. However, proper guidance supporting microbiology educators in locating and selecting, or commissioning the creation of, adequate MTAs for different target audiences and learning objectives is lacking. The aims of this study were to (i) identify important considerations regarding educational/didactical standards and the design of educational multimedia and (ii) create an evidence‐based guideline for selecting and appraising existing, and informing the creation of new, microbiology MTAs. This investigation is based on an exploratory, mixed‐methods approach. The results of two literature reviews (covering educational and good practice multimedia design) informed the collation of a preliminary appraisal guideline for videos, animations, comics, and video games. A web‐scraping approach was utilised to locate and retrieve existing exemplars of the four multimedia types and create four pertinent multimedia databases (including metadata). The preliminary guideline was piloted (and revised accordingly) by appraising quasi‐random (or purposive) samples of each multimedia type. Educational multimedia experts were interviewed to discuss the findings. Finally, the guideline was updated to reflect the expert comments together with the results of the pilot appraisals. The final guideline has four components: (i) central considerations for selecting and appraising multimedia for specific audiences and educational purposes, (ii) multimedia selection tool, (iii) multimedia appraisal tools, and (iv) extensive background information as appendices linking all sections for further comprehension. Broad utilisation of the guideline has significant potential for simplifying and systematising multimedia selection/creation, leading to superior multimedia‐based learning outcomes, establishing a rapid selection database (pre‐appraised multimedia), reducing disparities in microbiology education and incentivising educational content creators.

Published
2024
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40. Bibliometric and scientometric analysis of PSMA-targeted radiotheranostics: knowledge mapping and global standing

Author

Mohamed Sallam, Mahan Mohammadi, Frank Sainsbury, Nam-Trung Nguyen, Nobuo Kimizuka, Serge Muyldermans, and Martina Benešová-Schäfer

Subjects
bibliometric and scientometrics, prostate cancer, prostate-specific membrane antigen (PSMA), PSMA-targeted radiotheranostics, PSMA pioneers, leading PSMA, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

PurposeBibliometric and scientometric analyses provide a structured approach to large amounts of data, enabling the prediction of research theme trends over time, the detection of shifts in the boundaries of disciplines, and the identification of the most productive countries, institutions and scholars. In the context of prostate-specific membrane antigen (PSMA)-targeted radiotheranostics, no bibliometric or scientometric analysis has been published thus far. Therefore, this study was conducted to identify key contributors to the literature, assess the global scientific production of related research, and possibly predict future development patterns.MethodsScientometrics and bibliometrics were utilized to analyze the current body of knowledge while tracking its evolution to support scientific decision-making comprehensively and systematically. Science mapping techniques were employed to visualize research activities. Two different tools, Tableau and VOSviewer, were utilized, with VOSviewer being deemed the most suitable for the research objectives. The Web of Science (WoS) was used as the principal database for the searches.ResultsThrough the search process over a period of 30 years (January 1993–January 2023), 694 original studies in the English language were subjected to comprehensive analysis. By employing bibliometric and scientometric methods, multiple networks were created that mapped various concepts, such as publication trends, leading countries, cocitations, coauthorship among researchers and scientists, as well as coauthorship among organizations and funding agencies. This study revealed the evolutionary patterns, trends, outliers, and key players in the PSMA field, which enabled a more nuanced understanding of the research landscape.ConclusionThis research contributes to the enrichment of knowledge on PSMA-targeted radiotheranostics through detailed global bibliometric and scientometric analyses. It stresses the necessity for the development of communication platforms, the establishment of supportive infrastructures, and the implementation of proactive solutions to address emerging challenges. This study offers a significant resource for delineating effective strategies and identifying prominent funding bodies essential for continuous advancements in the field of PSMA-based diagnosis and therapy for prostate cancer. It is vital to sustain this momentum to ensure further progress in this pioneering area.

Published
2024
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42. Stratified analyses refine association between TLR7 rare variants and severe COVID-19

Author

Rimoldi, Valeria, Paraboschi, Elvezia M., Bandera, Alessandra, Peyvandi, Flora, Grasselli, Giacomo, Blasi, Francesco, Malvestiti, Francesco, Pelusi, Serena, Bianco, Cristiana, Miano, Lorenzo, Lombardi, Angela, Invernizzi, Pietro, Gerussi, Alessio, Citerio, Giuseppe, Biondi, Andrea, Valsecchi, Maria Grazia, Cazzaniga, Marina Elena, Foti, Giuseppe, Beretta, Ilaria, D'Angiò, Mariella, Bettini, Laura Rachele, Farré, Xavier, Iraola-Guzmán, Susana, Kogevinas, Manolis, Castaño-Vinyals, Gemma, Garcia-Etxebarria, Koldo, Nafria, Beatriz, D'Amato, Mauro, Palom, Adriana, Begg, Colin, Clohisey, Sara, Hinds, Charles, Horby, Peter, Knight, Julian, Ling, Lowell, Maslove, David, McAuley, Danny, Millar, Johnny, Montgomery, Hugh, Nichol, Alistair, Openshaw, Peter J.M., Pereira, Alexandre C., Ponting, Chris P., Rowan, Kathy, Semple, Malcolm G., Shankar-Hari, Manu, Summers, Charlotte, Walsh, Timothy, Baillie, J. Kenneth, Aravindan, Latha, Armstrong, Ruth, Biggs, Heather, Boz, Ceilia, Brown, Adam, Clark, Richard, Coutts, Audrey, Coyle, Judy, Cullum, Louise, Das, Sukamal, Day, Nicky, Donnelly, Lorna, Duncan, Esther, Fawkes, Angie, Fineran, Paul, Fourman, Max Head, Furlong, Anita, Furniss, James, Gallagher, Bernadette, Gilchrist, Tammy, Golightly, Ailsa, Griffiths, Fiona, Hafezi, Katarzyna, Hamilton, Debbie, Hendry, Ross, Law, Andy, Law, Dawn, Law, Rachel, Law, Sarah, Lidstone-Scott, Rebecca, Macgillivray, Louise, Maclean, Alan, Mal, Hanning, McCafferty, Sarah, Mcmaster, Ellie, Meikle, Jen, Moore, Shona C., Morrice, Kirstie, Murphy, Lee, Murphy, Sheena, Hellen, Mybaya, Oosthuyzen, Wilna, Zheng, Chenqing, Chen, Jiantao, Parkinson, Nick, Paterson, Trevor, Schon, Katherine, Stenhouse, Andrew, Das, Mihaela, Swets, Maaike, Szoor-McElhinney, Helen, Taneski, Filip, Turtle, Lance, Wackett, Tony, Ward, Mairi, Weaver, Jane, Wrobel, Nicola, Zechner, Marie, Arbane, Gill, Bociek, Aneta, Campos, Sara, Grau, Neus, Jones, Tim Owen, Lim, Rosario, Marotti, Martina, Ostermann, Marlies, Whitton, Christopher, Alldis, Zoe, Astin-Chamberlain, Raine, Bibi, Fatima, Biddle, Jack, Blow, Sarah, Bolton, Matthew, Borra, Catherine, Bowles, Ruth, Burton, Maudrian, Choudhury, Yasmin, Collier, David, Cox, Amber, Easthope, Amy, Ebano, Patrizia, Fotiadis, Stavros, Gurasashvili, Jana, Halls, Rosslyn, Hartridge, Pippa, Kallon, Delordson, Kassam, Jamila, Lancoma-Malcolm, Ivone, Matharu, Maninderpal, May, Peter, Mitchelmore, Oliver, Newman, Tabitha, Patel, Mital, Pheby, Jane, Pinzuti, Irene, Prime, Zoe, Prysyazhna, Oleksandra, Shiel, Julian, Taylor, Melanie, Tierney, Carey, Wood, Suzanne, Zak, Anne, Zongo, Olivier, Bonner, Stephen, Hugill, Keith, Jones, Jessica, Liggett, Steven, Headlam, Evie, Bandla, Nageswar, Gellamucho, Minnie, Davies, Michelle, Thompson, Christopher, Abdelrazik, Marwa, Bakthavatsalam, Dhanalakshmi, Elhassan, Munzir, Ganesan, Arunkumar, Haldeos, Anne, Moreno-Cuesta, Jeronimo, Purohit, Dharam, Vincent, Rachel, Xavier, Kugan, Rohit, Kumar, Alasdair, Frater, Saleem, Malik, David, Carter, Samuel, Jenkins, Lamond, Zoe, Alanna, Wall, Fernandez-Roman, Jaime, Hamilton, David O., Johnson, Emily, Johnston, Brian, Martinez, Maria Lopez, Mulla, Suleman, Shaw, David, Waite, Alicia A.C., Waugh, Victoria, Welters, Ingeborg D., Williams, Karen, Cavazza, Anna, Cockrell, Maeve, Corcoran, Eleanor, Depante, Maria, Finney, Clare, Jerome, Ellen, McPhail, Mark, Nayak, Monalisa, Noble, Harriet, O'Reilly, Kevin, Pappa, Evita, Saha, Rohit, Saha, Sian, Smith, John, Knighton, Abigail, Antcliffe, David, Banach, Dorota, Brett, Stephen, Coghlan, Phoebe, Fernandez, Ziortza, Gordon, Anthony, Rojo, Roceld, Arias, Sonia Sousa, Templeton, Maie, Meredith, Megan, Morris, Lucy, Ryan, Lucy, Clark, Amy, Sampson, Julia, Peters, Cecilia, Dent, Martin, Langley, Margaret, Ashraf, Saima, Wei, Shuying, Andrew, Angela, Bashyal, Archana, Davidson, Neil, Hutton, Paula, McKechnie, Stuart, Wilson, Jean, Baptista, David, Crowe, Rebecca, Fernandes, Rita, Herdman-Grant, Rosaleen, Joseph, Anna, O'Connor, Denise, Allen, Meryem, Loveridge, Adam, McKenley, India, Morino, Eriko, Naranjo, Andres, Simms, Richard, Sollesta, Kathryn, Swain, Andrew, Venkatesh, Harish, Khera, Jacyntha, Fox, Jonathan, Andrew, Gillian, Barclay, Lucy, Callaghan, Marie, Campbell, Rachael, Clark, Sarah, Hope, Dave, Marshall, Lucy, McCulloch, Corrienne, Briton, Kate, Singleton, Jo, Birch, Sohphie, Brimfield, Lutece, Daly, Zoe, Pogson, David, Rose, Steve, Battle, Ceri, Brinkworth, Elaine, Harford, Rachel, Murphy, Carl, Newey, Luke, Rees, Tabitha, Williams, Marie, Arnold, Sophie, Polgarova, Petra, Stroud, Katerina, Meaney, Eoghan, Jones, Megan, Ng, Anthony, Agrawal, Shruti, Pathan, Nazima, White, Deborah, Daubney, Esther, Elston, Kay, Grauslyte, Lina, Hussain, Musarat, Phull, Mandeep, Pogreban, Tatiana, Rosaroso, Lace, Salciute, Erika, Franke, George, Wong, Joanna, George, Aparna, Ortiz-Ruiz de Gordoa, Laura, Peasgood, Emily, Phillips, Claire, Bates, Michelle, Dasgin, Jo, Gill, Jaspret, Nilsson, Annette, Scriven, James, Delgado, Carlos Castro, Dawson, Deborah, Ding, Lijun, Durrant, Georgia, Ezeobu, Obiageri, Farnell-Ward, Sarah, Harrison, Abiola, Kanu, Rebecca, Leaver, Susannah, Maccacari, Elena, Manna, Soumendu, Saluzzio, Romina Pepermans, Queiroz, Joana, Samakomva, Tinashe, Sicat, Christine, Texeira, Joana, Da Gloria, Edna Fernandes, Lisboa, Ana, Rawlins, John, Mathew, Jisha, Kinch, Ashley, Hurt, William James, Shah, Nirav, Clark, Victoria, Thanasi, Maria, Yun, Nikki, Patel, Kamal, Bennett, Sara, Goodwin, Emma, Jackson, Matthew, Kent, Alissa, Tibke, Clare, Woodyatt, Wiesia, Zaki, Ahmed, Abraheem, Azmerelda, Bamford, Peter, Cawley, Kathryn, Dunmore, Charlie, Faulkner, Maria, Girach, Rumanah, Jeffrey, Helen, Jones, Rhianna, London, Emily, Nagra, Imrun, Nasir, Farah, Sainsbury, Hannah, Smedley, Clare, Patel, Tahera, Smith, Matthew, Chukkambotla, Srikanth, Kazi, Aayesha, Hartley, Janice, Dykes, Joseph, Hijazi, Muhammad, Keith, Sarah, Khan, Meherunnisa, Ryan-Smith, Janet, Springle, Philippa, Thomas, Jacqueline, Truman, Nick, Saad, Samuel, Coleman, Dabheoc, Fine, Christopher, Matt, Roseanna, Gay, Bethan, Dalziel, Jack, Ali, Syamlan, Goodchild, Drew, Harling, Rhiannan, Bhatterjee, Ravi, Goddard, Wendy, Davison, Chloe, Duberly, Stephen, Hargreaves, Jeanette, Bolton, Rachel, Davey, Miriam, Golden, David, Seaman, Rebecca, Cherian, Shiney, Cutler, Sean, Heron, Anne Emma, Roynon-Reed, Anna, Szakmany, Tamas, Williams, Gemma, Richards, Owen, Cheema, Yusuf, Brooke, Hollie, Buckley, Sarah, Suarez, Jose Cebrian, Charlesworth, Ruth, Hansson, Karen, Norris, John, Poole, Alice, Rose, Alastair, Sandhu, Rajdeep, Sloan, Brendan, Smithson, Elizabeth, Thirumaran, Muthu, Wagstaff, Veronica, Metcalfe, Alexandra, Brunton, Mark, Caterson, Jess, Coles, Holly, Frise, Matthew, Rai, Sabi Gurung, Jacques, Nicola, Keating, Liza, Tilney, Emma, Bartley, Shauna, Bhuie, Parminder, Gibson, Sian, Lyle, Amanda, McNeela, Fiona, Radhakrishnan, Jayachandran, Hughes, Alistair, Yates, Bryan, Reynolds, Jessica, Campbell, Helen, Thompsom, Maria, Dodds, Steve, Duffy, Stacey, Greer, Sandra, Shuker, Karen, Tridente, Ascanio, Khade, Reena, Sundar, Ashok, Tsinaslanidis, George, Birkinshaw, Isobel, Carter, Joseph, Howard, Kate, Ingham, Joanne, Joy, Rosie, Pearson, Harriet, Roche, Samantha, Scott, Zoe, Bancroft, Hollie, Bellamy, Mary, Carmody, Margaret, Daglish, Jacqueline, Moore, Faye, Rhodes, Joanne, Sangombe, Mirriam, Kadiri, Salma, Croft, Maria, White, Ian, Frost, Victoria, Aquino, Maia, Jha, Rajeev, Krishnamurthy, Vinodh, Lim, Lai, Lim, Li, Combes, Edward, Joefield, Teishel, Monnery, Sonja, Beech, Valerie, Trotman, Sallyanne, Almaden-Boyle, Christine, Austin, Pauline, Cabrelli, Louise, Cole, Stephen, Casey, Matt, Chapman, Susan, Whyte, Clare, Baird, Yolanda, Butler, Aaron, Chadbourn, Indra, Folkes, Linda, Fox, Heather, Gardner, Amy, Gomez, Raquel, Hobden, Gillian, Hodgson, Luke, King, Kirsten, Margarson, Michael, Martindale, Tim, Meadows, Emma, Raynard, Dana, Thirlwall, Yvette, Helm, David, Margalef, Jordi, Criste, Kristine, Cusack, Rebecca, Golder, Kim, Golding, Hannah, Jones, Oliver, Leggett, Samantha, Male, Michelle, Marani, Martyna, Prager, Kirsty, Williams, Toran, Roberts, Belinda, Salmon, Karen, Anderson, Peter, Archer, Katie, Austin, Karen, Davis, Caroline, Durie, Alison, Kelsall, Olivia, Thrush, Jessica, Vigurs, Charlie, Wild, Laura, Wood, Hannah-Louise, Tranter, Helen, Harrison, Alison, Cowley, Nicholas, McAlindon, Michael, Burtenshaw, Andrew, Digby, Stephen, Low, Emma, Morgan, Aled, Cother, Naiara, Rankin, Tobias, Clayton, Sarah, McCurdy, Alex, Ahmed, Cecilia, Baines, Balvinder, Clamp, Sarah, Colley, Julie, Haq, Risna, Hayes, Anne, Hulme, Jonathan, Hussain, Samia, Joseph, Sibet, Kumar, Rita, Maqsood, Zahira, Purewal, Manjit, Benham, Leonie, Bradshaw, Zena, Brown, Joanna, Caswell, Melanie, Cupitt, Jason, Melling, Sarah, Preston, Stephen, Slawson, Nicola, Stoddard, Emma, Warden, Scott, Deacon, Bethan, Lynch, Ceri, Pothecary, Carla, Roche, Lisa, Howe, Gwenllian Sera, Singh, Jayaprakash, Turner, Keri, Ellis, Hannah, Stroud, Natalie, Hunt, Jodie, Dearden, Joy, Dobson, Emma, Drummond, Andy, Mulcahy, Michelle, Munt, Sheila, O'Connor, Grainne, Philbin, Jennifer, Rishton, Chloe, Tully, Redmond, Winnard, Sarah, Cathcart, Susanne, Duffy, Katharine, Puxty, Alex, Puxty, Kathryn, Turner, Lynne, Ireland, Jane, Semple, Gary, Long, Kate, Whiteley, Simon, Wilby, Elizabeth, Ogg, Bethan, Cowton, Amanda, Kay, Andrea, Kent, Melanie, Potts, Kathryn, Wilkinson, Ami, Campbell, Suzanne, Brown, Ellen, Melville, Julie, Naisbitt, Jay, Joseph, Rosane, Lazo, Maria, Walton, Olivia, Neal, Alan, Alexander, Peter, Allen, Schvearn, Bradley-Potts, Joanne, Brantwood, Craig, Egan, Jasmine, Felton, Timothy, Padden, Grace, Ward, Luke, Moss, Stuart, Glasgow, Susannah, Abel, Lynn, Brett, Michael, Digby, Brian, Gemmell, Lisa, Hornsby, James, MacGoey, Patrick, O'Neil, Pauline, Price, Richard, Rodden, Natalie, Rooney, Kevin, Sundaram, Radha, Thomson, Nicola, Hopkins, Bridget, Thrasyvoulou, Laura, Willis, Heather, Clark, Martyn, Coulding, Martina, Jude, Edward, McCormick, Jacqueline, Mercer, Oliver, Potla, Darsh, Rehman, Hafiz, Savill, Heather, Turner, Victoria, Downes, Charlotte, Holding, Kathleen, Riches, Katie, Hilton, Mary, Hayman, Mel, Subramanian, Deepak, Daniel, Priya, Adanini, Oluronke, Bhatia, Nikhil, Msiska, Maines, Collins, Rebecca, Clement, Ian, Patel, Bijal, Gulati, A., Hays, Carole, Webster, K., Hudson, Anne, Webster, Andrea, Stephenson, Elaine, McCormack, Louise, Slater, Victoria, Nixon, Rachel, Hanson, Helen, Fearby, Maggie, Kelly, Sinead, Bridgett, Victoria, Robinson, Philip, Camsooksai, Julie, Humphrey, Charlotte, Jenkins, Sarah, Reschreiter, Henrik, Wadams, Beverley, Death, Yasmin, Bastion, Victoria, Clarke, Daphene, David, Beena, Kent, Harriet, Lorusso, Rachel, Lubimbi, Gamu, Murdoch, Sophie, Penacerrada, Melchizedek, Thomas, Alastair, Valentine, Jennifer, Vochin, Ana, Wulandari, Retno, Djeugam, Brice, Bell, Gillian, English, Katy, Katary, Amro, Wilcox, Louise, Bruce, Michelle, Connolly, Karen, Duncan, Tracy, T-Michael, Helen, Lindergard, Gabriella, Hey, Samuel, Fox, Claire, Alfonso, Jordan, Durrans, Laura Jayne, Guerin, Jacinta, Blackledge, Bethan, Harris, Jade, Hruska, Martin, Eltayeb, Ayaa, Lamb, Thomas, Hodgkiss, Tracey, Cooper, Lisa, Rothwell, Joanne, Allan, Angela, Anderson, Felicity, Kaye, Callum, Liew, Jade, Medhora, Jasmine, Scott, Teresa, Trumper, Erin, Botello, Adriana, Lankester, Liana, Nikitas, Nikitas, Wells, Colin, Stowe, Bethan, Spencer, Kayleigh, Brandwood, Craig, Smith, Lara, Birchall, Katie, Kolakaluri, Laurel, Baines, Deborah, Sukumaran, Anila, Apetri, Elena, Basikolo, Cathrine, Catlow, Laura, Charles, Bethan, Dark, Paul, Doonan, Reece, Harvey, Alice, Horner, Daniel, Knowles, Karen, Lee, Stephanie, Lomas, Diane, Lyons, Chloe, Marsden, Tracy, McLaughlan, Danielle, McMorrow, Liam, Pendlebury, Jessica, Perez, Jane, Poulaka, Maria, Proudfoot, Nicola, Slaughter, Melanie, Slevin, Kathryn, Thomas, Vicky, Walker, Danielle, Michael, Angiy, Collis, Matthew, Cosier, Tracey, Millen, Gemma, Richardson, Neil, Schumacher, Natasha, Weston, Heather, Rand, James, Baxter, Nicola, Henderson, Steven, Kennedy-Hay, Sophie, McParland, Christopher, Rooney, Laura, Sim, Malcolm, McCreath, Gordan, Akeroyd, Louise, Bano, Shereen, Bromley, Matt, Gurr, Lucy, Lawton, Tom, Morgan, James, Sellick, Kirsten, Warren, Deborah, Wilkinson, Brian, McGowan, Janet, Ledgard, Camilla, Stacey, Amelia, Pye, Kate, Bellwood, Ruth, Bentley, Michael, Bewley, Jeremy, Garland, Zoe, Grimmer, Lisa, Gumbrill, Bethany, Johnson, Rebekah, Sweet, Katie, Webster, Denise, Efford, Georgia, Convery, Karen, Fottrell-Gould, Deirdre, Hudig, Lisa, Keshet-Price, Jocelyn, Randell, Georgina, Stammers, Katie, Bokhari, Maria, Linnett, Vanessa, Lucas, Rachael, McCormick, Wendy, Ritzema, Jenny, Sanderson, Amanda, Wild, Helen, Rostron, Anthony, Roy, Alistair, Woods, Lindsey, Cornell, Sarah, Wakinshaw, Fiona, Rogerson, Kimberley, Jarmain, Jordan, Parker, Robert, Reddy, Amie, Turner-Bone, Ian, Wilding, Laura, Harding, Peter, Abernathy, Caroline, Foster, Louise, Gratrix, Andrew, Martinson, Vicky, Parkinson, Priyai, Stones, Elizabeth, Carbral-Ortega, Llucia, Bercades, Georgia, Brealey, David, Hass, Ingrid, MacCallum, Niall, Martir, Gladys, Raith, Eamon, Reyes, Anna, Smyth, Deborah, Zitter, Letizia, Benyon, Sarah, Marriott, Suzie, Park, Linda, Keenan, Samantha, Gordon, Elizabeth, Quinn, Helen, Baines, Kizzy, Cagova, Lenka, Fofano, Adama, Garner, Lucie, Holcombe, Helen, Mepham, Sue, Mitchell, Alice Michael, Mwaura, Lucy, Praman, Krithivasan, Vuylsteke, Alain, Zamikula, Julie, Purewal, Bally, Rivers, Vanessa, Bell, Stephanie, Blakemore, Hayley, Borislavova, Borislava, Faulkner, Beverley, Gendall, Emma, Goff, Elizabeth, Hayes, Kati, Thomas, Matt, Worner, Ruth, Smith, Kerry, Stephens, Deanna, Mew, Louise, Mwaura, Esther, Stewart, Richard, Williams, Felicity, Wren, Lynn, Sutherland, Sara-Beth, Bevan, Emily, Martin, Jane, Trodd, Dawn, Watson, Geoff, Brown, Caroline Wrey, Collins, Amy, Khaliq, Waqas, Gude, Estefania Treus, Akinkugbe, Olugbenga, Bamford, Alasdair, Beech, Emily, Belfield, Holly, Bell, Michael, Davies, Charlene, Jones, Gareth A.L., McHugh, Tara, Meghari, Hamza, O'Neill, Lauran, Peters, Mark J., Ray, Samiran, Tomas, Ana Luisa, Burn, Iona, Hambrook, Geraldine, Manso, Katarina, Penn, Ruth, Shanmugasundaram, Pradeep, Tebbutt, Julie, Thornton, Danielle, Cole, Jade, Davies, Rhys, Duffin, Donna, Hill, Helen, Player, Ben, Thomas, Emma, Williams, Angharad, Griffin, Denise, Muchenje, Nycola, Mupudzi, Mcdonald, Partridge, Richard, Conyngham, Jo-Anna, Thomas, Rachel, Wright, Mary, Corral, Maria Alvarez, Jacob, Reni, Jones, Cathy, Denmade, Craig, Beavis, Sarah, Dale, Katie, Gascoyne, Rachel, Hawes, Joanne, Pritchard, Kelly, Stevenson, Lesley, Whileman, Amanda, Doble, Patricia, Hutter, Joanne, Pawley, Corinne, Shovelton, Charmaine, Vaida, Marius, Butcher, Deborah, O'Sullivan, Susie, Butterworth-Cowin, Nicola, Ahmad, Norfaizan, Barker, Joann, Bauchmuller, Kris, Bird, Sarah, Cawthron, Kay, Harrington, Kate, Jackson, Yvonne, Kibutu, Faith, Lenagh, Becky, Masuko, Shamiso, Mills, Gary H., Raithatha, Ajay, Wiles, Matthew, Willson, Jayne, Newell, Helen, Lye, Alison, Nwafor, Lorenza, Jarman, Claire, Rowland-Jones, Sarah, Foote, David, Cole, Joby, Thompson, Roger, Watson, James, Hesseldon, Lisa, Macharia, Irene, Chetam, Luke, Smith, Jacqui, Ford, Amber, Anderson, Samantha, Birchall, Kathryn, Housley, Kay, Walker, Sara, Milner, Leanne, Hanratty, Helena, Trower, Helen, Phillips, Patrick, Oxspring, Simon, Donne, Ben, Jardine, Catherine, Williams, Dewi, Hay, Alasdair, Flanagan, Rebecca, Hughes, Gareth, Latham, Scott, McKenna, Emma, Anderson, Jennifer, Hull, Robert, Rhead, Kat, Cruz, Carina, Pattison, Natalie, Charnock, Rob, McFarland, Denise, Cosgrove, Denise, Ahmed, Ashar, Morris, Anna, Jakkula, Srinivas, Ali, Asifa, Brady, Megan, Dale, Sam, Dance, Annalisa, Gledhill, Lisa, Greig, Jill, Hanson, Kathryn, Holdroyd, Kelly, Home, Marie, Kelly, Diane, Kitson, Ross, Matapure, Lear, Melia, Deborah, Mellor, Samantha, Nortcliffe, Tonicha, Pinnell, Jez, Robinson, Matthew, Shaw, Lisa, Shaw, Ryan, Thomis, Lesley, Wilson, Alison, Wood, Tracy, Bayo, Lee-Ann, Merwaha, Ekta, Ishaq, Tahira, Hanley, Sarah, Hibbert, Meg, Tetla, Dariusz, Woodford, Chrsitopher, Durga, Latha, Kennard-Holden, Gareth, Branney, Debbie, Frankham, Jordan, Pitts, Sally, White, Nigel, Laha, Shondipon, Verlander, Mark, Williams, Alexandra, Altabaibeh, Abdelhakim, Alvaro, Ana, Gilbert, Kayleigh, Ma, Louise, Mostoles, Loreta, Parmar, Chetan, Simpson, Kathryn, Jetha, Champa, Booker, Lauren, Pratley, Anezka, Adams, Colene, Agasou, Anita, Arden, Tracie, Bowes, Amy, Boyle, Pauline, Beekes, Mandy, Button, Heather, Capps, Nigel, Carnahan, Mandy, Carter, Anne, Childs, Danielle, Donaldson, Denise, Hard, Kelly, Hurford, Fran, Hussain, Yasmin, Javaid, Ayesha, Jones, James, Jose, Sanal, Leigh, Michael, Martin, Terry, Millward, Helen, Motherwell, Nichola, Rikunenko, Rachel, Stickley, Jo, Summers, Julie, Ting, Louise, Tivenan, Helen, Tonks, Louise, Wilcox, Rebecca, Holland, Maureen, Keenan, Natalie, Lyons, Marc, Wassall, Helen, Marsh, Chris, Mahenthran, Mervin, Carter, Emma, Kong, Thomas, Blackman, Helen, Creagh-Brown, Ben, Donlon, Sinead, Michalak-Glinska, Natalia, Mtuwa, Sheila, Pristopan, Veronika, Salberg, Armorel, Smith, Eleanor, Stone, Sarah, Piercy, Charles, Verula, Jerik, Burda, Dorota, Montaser, Rugia, Harden, Lesley, Mayangao, Irving, Marriott, Cheryl, Bradley, Paul, Harris, Celia, Anderson, Susan, Andrews, Eleanor, Birch, Janine, Collins, Emma, Hammerton, Kate, O'Leary, Ryan, Clark, Michele, Purvis, Sarah, Barber, Russell, Hewitt, Claire, Hilldrith, Annette, Jackson-Lawrence, Karen, Shepardson, Sarah, Wills, Maryanne, Butler, Susan, Tavares, Silvia, Cunningham, Amy, Hindale, Julia, Arif, Sarwat, Bean, Sarah, Burt, Karen, Spivey, Michael, Demetriou, Carrie, Eckbad, Charlotte, Hierons, Sarah, Howie, Lucy, Mitchard, Sarah, Ramos, Lidia, Serrano-Ruiz, Alfredo, White, Katie, Kelly, Fiona, Cristiano, Daniele, Dormand, Natalie, Farzad, Zohreh, Gummadi, Mahitha, Liyanage, Kamal, Patel, Brijesh, Salmi, Sara, Sloane, Geraldine, Thwaites, Vicky, Varghese, Mathew, Zborowski, Anelise C., Allan, John, Geary, Tim, Houston, Gordon, Meikle, Alistair, O'Brien, Peter, Forsey, Miranda, Kaliappan, Agilan, Nicholson, Anne, Riches, Joanne, Vertue, Mark, Allan, Elizabeth, Darlington, Kate, Davies, Ffyon, Easton, Jack, Kumar, Sumit, Lean, Richard, Menzies, Daniel, Pugh, Richard, Qiu, Xinyi, Davies, Llinos, Williams, Hannah, Scanlon, Jeremy, Davies, Gwyneth, Mackay, Callum, Lewis, Joannne, Rees, Stephanie, Oblak, Metod, Popescu, Monica, Thankachen, Mini, Higham, Andrew, Simpson, Kerry, Craig, Jayne, Baruah, Rosie, Morris, Sheila, Ferguson, Susie, Shepherd, Amy, Prockter Moore, Luke Stephen, Vizcaychipi, Marcela Paola, Gomes de Almeida Martins, Laura, Carungcong, Jaime, Mohamed Ali, Inthakab Ali, Beaumont, Karen, Blunt, Mark, Coton, Zoe, Curgenven, Hollie, Elsaadany, Mohamed, Fernandes, Kay, Ally, Sameena Mohamed, Rangarajan, Harini, Sarathy, Varun, Selvanayagam, Sivarupan, Vedage, Dave, White, Matthew, Gill, Mandy, Paul, Paul, Ratnam, Valli, Shelton, Sarah, Wynter, Inez, Carmody, Siobhain, Page, Valerie Joan, Beith, Claire Marie, Black, Karen, Clements, Suzanne, Morrison, Alan, Strachan, Dominic, Taylor, Margaret, Clarkson, Michelle, D'Sylva, Stuart, Norman, Kathryn, Auld, Fiona, Donnachie, Joanne, Edmond, Ian, Prentice, Lynn, Runciman, Nikole, Salutous, Dario, Symon, Lesley, Todd, Anne, Turner, Patricia, Short, Abigail, Sweeney, Laura, Murdoch, Euan, Senaratne, Dhaneesha, Hill, Michaela, Kannan, Thogulava, Laura, Wild, Crawley, Rikki, Crew, Abigail, Cunningham, Mishell, Daniels, Allison, Harrison, Laura, Hope, Susan, Inweregbu, Ken, Jones, Sian, Lancaster, Nicola, Matthews, Jamie, Nicholson, Alice, Wray, Gemma, Langton, Helen, Prout, Rachel, Watters, Malcolm, Novis, Catherine, Barron, Anthony, Collins, Ciara, Kaul, Sundeep, Passmore, Heather, Prendergast, Claire, Reed, Anna, Rogers, Paula, Shokkar, Rajvinder, Woodruff, Meriel, Middleton, Hayley, Polgar, Oliver, Nolan, Claire, Mahay, Kanta, Collier, Dawn, Hormis, Anil, Maynard, Victoria, Graham, Cheryl, Walker, Rachel, Knights, Ellen, Price, Alicia, Thomas, Alice, Thorpe, Chris, Behan, Teresa, Burnett, Caroline, Hatton, Jonathan, Heeney, Elaine, Mitra, Atideb, Newton, Maria, Pollard, Rachel, Stead, Rachael, Amin, Vishal, Anastasescu, Elena, Anumakonda, Vikram, Karthik, Komala, Kausar, Rizwana, Reid, Karen, Smith, Jacqueline, Imeson-Wood, Janet, Skinner, Denise, Gaylard, Jane, Mullan, Dee, Newman, Julie, Brown, Alison, Crickmore, Vikki, Debreceni, Gabor, Wilkins, Joy, Nicol, Liz, Reece-Anthony, Rosie, Birt, Mark, Ghosh, Alison, Williams, Emma, Allen, Louise, Beranova, Eva, Crisp, Nikki, Deery, Joanne, Hazelton, Tracy, Knight, Alicia, Price, Carly, Tilbey, Sorrell, Turki, Salah, Turney, Sharon, Cooper, Joshua, Finch, Cheryl, Liderth, Sarah, Quinn, Alison, Waddington, Natalia, Coventry, Tina, Fowler, Susan, MacMahon, Michael, McGregor, Amanda, Cowley, Anne, Highgate, Judith, Gregory, Jane, O'Connell, Susan, Smith, Tim, Barberis, Luigi, Gopal, Shameer, Harris, Nichola, Lake, Victoria, Metherell, Stella, Radford, Elizabeth, Daniel, Amelia, Finn, Joanne, Saha, Rajnish, White, Nikki, Donnison, Phil, Trim, Fiona, Eapen, Beena, Birch, Jenny, Bough, Laura, Goodsell, Josie, Tutton, Rebecca, Williams, Patricia, Williams, Sarah, Winter-Goodwin, Barbara, Nichol, Ailstair, Brickell, Kathy, Smyth, Michelle, Murphy, Lorna, Coetzee, Samantha, Gales, Alistair, Otahal, Igor, Raj, Meena, Sell, Craig, Hilltout, Paula, Evitts, Jayne, Tyler, Amanda, Waldron, Joanne, Beesley, Kate, Board, Sarah, Kubisz-Pudelko, Agnieszka, Lewis, Alison, Perry, Jess, Pippard, Lucy, Wood, Di, Buckley, Clare, Barry, Peter, Flint, Neil, Rekha, Patel, Hales, Dawn, Bunni, Lara, Jennings, Claire, Latif, Monica, Marshall, Rebecca, Subramanian, Gayathri, McGuigan, Peter J., Wasson, Christopher, Finn, Stephanie, Green, Jackie, Collins, Erin, King, Bernadette, Campbell, Andy, Smuts, Sara, Duffield, Joseph, Smith, Oliver, Mallon, Lewis, Claire, Watkins, Botfield, Liam, Butler, Joanna, Dexter, Catherine, Fletcher, Jo, Garg, Atul, Kuravi, Aditya, Ranga, Poonam, Virgilio, Emma, Belagodu, Zakaula, Fuller, Bridget, Gherman, Anca, Olufuwa, Olumide, Paramsothy, Remi, Stuart, Carmel, Oakley, Naomi, Kamundi, Charlotte, Tyl, David, Collins, Katy, Silva, Pedro, Taylor, June, King, Laura, Coates, Charlotte, Crowley, Maria, Wakefield, Phillipa, Beadle, Jane, Johnson, Laura, Sargeant, Janet, Anderson, Madeleine, Brady, Ailbhe, Chan, Rebekah, Little, Jeff, McIvor, Shane, Prady, Helena, Whittle, Helen, Mathew, Bijoy, Attwood, Ben, Parsons, Penny, Ward, Geraldine, Bremmer, Pamela, Joe, West, Tracy, Baird, Jim, Ruddy, Davies, Ellie, Sathe, Sonia, Dennis, Catherine, McGregor, Alastair, Parris, Victoria, Srikaran, Sinduya, Sukha, Anisha, Clarke, Noreen, Whiteside, Jonathan, Mascarenhas, Mairi, Donaldson, Avril, Matheson, Joanna, Barrett, Fiona, O'Hara, Marianne, Okeefe, Laura, Bradley, Clare, Eastgate-Jackson, Christine, Filipe, Helder, Martin, Daniel, Maharajh, Amitaa, Garcia, Sara Mingo, Pakou, Glykeria, De Neef, Mark, Dent, Kathy, Horsley, Elizabeth, Akhtar, Muhmmad Nauman, Pearson, Sandra, Potoczna, Dorota, Spencer, Sue, Clapham, Melanie, Harper, Rosemary, Poultney, Una, Rice, Polly, Mutch, Rachel, Armstrong, Lisa, Bates, Hayley, Dooks, Emma, Farquhar, Fiona, Hairsine, Brigid, McParland, Chantal, Packham, Sophie, Bi, Rehana, Scholefield, Barney, Ashton, Lydia, George, Linsha, Twiss, Sophie, Wright, David, Chablani, Manish, Kirkby, Amy, Netherton, Kimberley, Davies, Kim, O'Brien, Linda, Omar, Zohra, Perkins, Emma, Lewis, Tracy, Sutherland, Isobel, Burns, Karen, Ben Chandler, Dr, Elliott, Kerry, Mallinson, Janine, Turnbull, Alison, Gondo, Prisca, Hadebe, Bernard, Kayani, Abdul, Masunda, Bridgett, Anderson, Taya, Hawcutt, Dan, O'Malley, Laura, Rad, Laura, Rogers, Naomi, Saunderson, Paula, Allison, Kathryn Sian, Afolabi, Deborah, Whitbread, Jennifer, Jones, Dawn, Dore, Rachael, Halkes, Matthew, Mercer, Pauline, Thornton, Lorraine, Dawson, Joy, Garrioch, Sweyn, Tolson, Melanie, Aldridge, Jonathan, Kapoor, Ritoo, Loader, David, Castle, Karen, Humphreys, Sally, Tampsett, Ruth, Mackintosh, Katherine, Ayers, Amanda, Harrison, Wendy, North, Julie, Allibone, Suzanne, Genetu, Roman, Kasipandian, Vidya, Patel, Amit, Mac, Ainhi, Murphy, Anthony, Mahjoob, Parisa, Nazari, Roonak, Worsley, Lucy, Fagan, Andrew, Bemand, Thomas, Black, Ethel, Dela Rosa, Arnold, Howle, Ryan, Jhanji, Shaman, Baikady, Ravishankar Rao, Tatham, Kate Colette, Thomas, Benjamin, Bell, Dina, Boyle, Rosalind, Douglas, Katie, Glass, Lynn, Lee, Emma, Lennon, Liz, Rattray, Austin, Taylor, Abigail, Hughes, Rachel Anne, Thomas, Helen, Rees, Alun, Duskova, Michaela, Phipps, Janet, Brooks, Suzanne, Edwards, Michelle, Quaid, Sheena, Watson, Ekaterina, Brayne, Adam, Fisher, Emma, Hunt, Jane, Jackson, Peter, Kaye, Duncan, Love, Nicholas, Parkin, Juliet, Tuckey, Victoria, Van Koutrik, Lynne, Carter, Sasha, Andrew, Benedict, Findlay, Louise, Adams, Katie, Service, Jen, Williams, Alison, Cheyne, Claire, Saunderson, Anne, Moultrie, Sam, Odam, Miranda, Hall, Kathryn, Mapfunde, Isheunesu, Willis, Charlotte, Lyon, Alex, Sri-Chandana, Chunda, Scherewode, Joslan, Stephenson, Lorraine, Marsh, Sarah, Hardy, John, Houlden, Henry, Moncur, Eleanor, Tariq, Ambreen, Tucci, Arianna, Hobrok, Maria, Loosley, Ronda, McGuinness, Heather, Tench, Helen, Wolf-Roberts, Rebecca, Irvine, Val, Shelley, Benjamin, Gorman, Claire, Gupta, Abhinav, Timlick, Elizabeth, Brady, Rebecca, Milligan, Barry, Bellini, Arianna, Bryant, Jade, Mayer, Anton, Pickard, Amy, Roe, Nicholas, Sowter, Jason, Howlett, Alex, Fidler, Katy, Tagliavini, Emma, Donnelly, Kevin, Boos, Jannik, van der Made, Caspar I., Ramakrishnan, Gayatri, Coughlan, Eamon, Asselta, Rosanna, Löscher, Britt-Sabina, Valenti, Luca V.C., de Cid, Rafael, Bujanda, Luis, Julià, Antonio, Pairo-Castineira, Erola, May, Sandra, Zametica, Berina, Heggemann, Julia, Albillos, Agustín, Banales, Jesus M., Barretina, Jordi, Blay, Natalia, Bonfanti, Paolo, Buti, Maria, Fernandez, Javier, Marsal, Sara, Prati, Daniele, Ronzoni, Luisa, Sacchi, Nicoletta, Schultze, Joachim L., Riess, Olaf, Franke, Andre, Rawlik, Konrad, Ellinghaus, David, Hoischen, Alexander, Schmidt, Axel, and Ludwig, Kerstin U.

Published
2024
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44. Association of long-term use of non-steroidal anti-inflammatory drugs with knee osteoarthritis: a prospective multi-cohort study over 4-to-5 years

Author

Zubeyir Salis and Amanda Sainsbury

Subjects
Knee osteoarthritis, Non-steroidal anti-inflammatory drug, NSAID, Medicine, Science
Abstract

Abstract This study examines the long-term impact of non-steroidal anti-inflammatory drugs (NSAIDs) on the progression of symptoms and structural deterioration of the joint in knee osteoarthritis. The study analyzes data from 4197 participants (8394 knees) across the Osteoarthritis Initiative (OAI), Multicenter Osteoarthritis Study (MOST), and Cohort Hip and Cohort Knee (CHECK) over 4-to-5 years. Adjustments were made for major covariates. We focussed on binary outcomes to assess the presence or absence of significant changes. We found that, relative to non-users, individuals using NSAIDs long-term were significantly more likely to experience aggravated symptoms exceeding the minimally clinically important difference, specifically, pain (OR: 2.04, 95% CI: 1.66–2.49), disability (OR: 2.21, 95% CI: 1.74–2.80), and stiffness (OR: 1.58, 95% CI: 1.29–1.93). Long-term users also faced a higher probability than non-users of having total knee replacement (OR: 3.13, 95% CI: 2.08–4.70), although no significant difference between long-term users and non-users was observed for structural deterioration in the knee joint (OR: 1.25, 95% CI: 0.94–1.65). While acknowledging the limitations of this study due to its observational design and the potential for bidirectional causality, these findings suggest that long-term NSAID use could accelerate the progression to total knee replacement by markedly exacerbating symptoms.

Published
2024
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45. Taking care of knowledge, taking care of salmon: towards Indigenous data sovereignty in an era of climate change and cumulative effects

Author

S.E. Cannon, J.W. Moore, M.S. Adams, T. Degai, E. Griggs, J. Griggs, T. Marsden, A.J. Reid, N. Sainsbury, K.M. Stirling, Axdii A. Yee S. Barnes, R. Benson, D. Burrows, Gala'game R. Chamberlin, B. Charley, D. Dick, A.T. Duncan, Kung Kayangas M. Liddle, M. Paul, N. Paul Prince, C. Scotnicki, K. Speck, J. Squakin, C. Van Der Minne, J. Walkus, K. West, and Kii'iljuus B. Wilson

Subjects
Indigenous data sovereignty, Pacific salmon, research practices, British Columbia, cumulative effects, collaborative research, Education, Science
Abstract

In this paper, we argue that Indigenous data sovereignty (IDS) is vital for addressing threats to ecosystems, as well as for Indigenous Peoples re-establishing and maintaining sovereignty over their territories. Indigenous knowledge-holders face pressure from non-Indigenous scientists to collaborate to address environmental problems, while the open data movement is pressuring them to make their data public. We examine the role of IDS in the context of cumulative effects and climate change that threaten salmon-bearing ecosystems in British Columbia, guided by content from an online workshop in June 2022 and attended exclusively by a Tier-1 audience (First Nations knowledge-holders and/or technical staff working for Nations). Attention to data is required for fruitful collaborations between Indigenous communities and non-Indigenous researchers to address the impacts of climate change and the cumulative effects affecting salmon-bearing watersheds in BC. In addition, we provide steps that Indigenous governments can take to assert sovereignty over data, recommendations that external researchers can use to ensure they respect IDS, and questions that external researchers and Indigenous partners can discuss to guide decision-making about data management. Finally, we reflect on what we learned during the process of co-creating materials.

Published
2024
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46. Basis-Function Models in Spatial Statistics

Author

Cressie, Noel, Sainsbury-Dale, Matthew, and Zammit-Mangion, Andrew

Subjects
Statistics - Methodology
Abstract

Spatial statistics is concerned with the analysis of data that have spatial locations associated with them, and those locations are used to model statistical dependence between the data. The spatial data are treated as a single realisation from a probability model that encodes the dependence through both fixed effects and random effects, where randomness is manifest in the underlying spatial process and in the noisy, incomplete, measurement process. The focus of this review article is on the use of basis functions to provide an extremely flexible and computationally efficient way to model spatial processes that are possibly highly non-stationary. Several examples of basis-function models are provided to illustrate how they are used in Gaussian, non-Gaussian, multivariate, and spatio-temporal settings, with applications in geophysics. Our aim is to emphasise the versatility of these spatial statistical models and to demonstrate that they are now centre-stage in a number of application domains. The review concludes with a discussion and illustration of software currently available to fit spatial-basis-function models and implement spatial-statistical prediction., Comment: 30 pages, 6 figures

Published
2022

47. DNA-origami-directed virus capsid polymorphism

Author

Seitz, Iris, Saarinen, Sharon, Kumpula, Esa-Pekka, McNeale, Donna, Anaya-Plaza, Eduardo, Lampinen, Vili, Hytönen, Vesa P., Sainsbury, Frank, Cornelissen, Jeroen J. L. M., Linko, Veikko, Huiskonen, Juha T., and Kostiainen, Mauri A.

Published
2023
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49. Modelling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data using FRK

Author

Sainsbury-Dale, Matthew, Zammit-Mangion, Andrew, and Cressie, Noel

Subjects
Statistics - Computation, Statistics - Applications, Statistics - Methodology
Abstract

Non-Gaussian spatial and spatio-temporal data are becoming increasingly prevalent, and their analysis is needed in a variety of disciplines. FRK is an R package for spatial/spatio-temporal modelling and prediction with very large data sets that, to date, has only supported linear process models and Gaussian data models. In this paper, we describe a major upgrade to FRK that allows for non-Gaussian data to be analysed in a generalised linear mixed model framework. These vastly more general spatial and spatio-temporal models are fitted using the Laplace approximation via the software TMB. The existing functionality of FRK is retained with this advance into non-Gaussian models; in particular, it allows for automatic basis-function construction, it can handle both point-referenced and areal data simultaneously, and it can predict process values at any spatial support from these data. This new version of FRK also allows for the use of a large number of basis functions when modelling the spatial process, and is thus often able to achieve more accurate predictions than previous versions of the package in a Gaussian setting. We demonstrate innovative features in this new version of FRK, highlight its ease of use, and compare it to alternative packages using both simulated and real data sets., Comment: 38 pages, 15 figures

Published
2021

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