Tidal influence on self-potential measurements

DJM was supported by NERC CASE studentship NE/I018417/1. The authors would also like to thank Southern Water for access to the borehole at Saltdean. Atkins Global and Southern Water are thanked for funding installation of the equipment and for additional funding under the NERC studentship. The laboratory components of this work were carried out in the TOTAL Reservoir Physics Laboratory at Imperial College London and their support is gratefully acknowledged. Jackson acknowledges partial support from TOTAL under the TOTAL Chairs programme. The data supporting the conclusions of this work are available through the corresponding author.Peer reviewedPublisher PD

Characterizing the Self‐Potential Response to Concentration Gradients in Heterogeneous Subsurface Environments

DJM was supported by NERC CASE studentship NE/I018417/1. Additional support was provided by NERC to MG under the Science and Solutions for a Changing Planet Doctoral Training Partnership, run by the Grantham Institute for Climate Change at Imperial College London. Two anonymous reviewers are thanked for their comments, which greatly helped to improve the manuscript. The authors would also like to thank Southern Water for access to the borehole at Saltdean. Atkins Global and Southern Water are thanked for some additional funding under the NERC CASE studentship. The laboratory components of this work were carried out with support from TOTAL who we gratefully acknowledged. All data supporting the conclusions of this work are available in the supporting information.Peer reviewedPublisher PD

Flipping the odds of drug development success through human genomics

Drug development depends on accurately identifying molecular targets that both play a causal role in a disease and are amenable to pharmacological action by small molecule drugs or bio-therapeutics, such as monoclonal antibodies. Errors in drug target specification contribute to the extremely high rates of drug development failure. Integrating knowledge of genes that encode druggable targets with those that influence susceptibility to common disease has the potential to radically improve the probability of drug development success

Improving the odds of drug development success through human genomics: modelling study.

Lack of efficacy in the intended disease indication is the major cause of clinical phase drug development failure. Explanations could include the poor external validity of pre-clinical (cell, tissue, and animal) models of human disease and the high false discovery rate (FDR) in preclinical science. FDR is related to the proportion of true relationships available for discovery (γ), and the type 1 (false-positive) and type 2 (false negative) error rates of the experiments designed to uncover them. We estimated the FDR in preclinical science, its effect on drug development success rates, and improvements expected from use of human genomics rather than preclinical studies as the primary source of evidence for drug target identification. Calculations were based on a sample space defined by all human diseases - the 'disease-ome' - represented as columns; and all protein coding genes - 'the protein-coding genome'- represented as rows, producing a matrix of unique gene- (or protein-) disease pairings. We parameterised the space based on 10,000 diseases, 20,000 protein-coding genes, 100 causal genes per disease and 4000 genes encoding druggable targets, examining the effect of varying the parameters and a range of underlying assumptions, on the inferences drawn. We estimated γ, defined mathematical relationships between preclinical FDR and drug development success rates, and estimated improvements in success rates based on human genomics (rather than orthodox preclinical studies). Around one in every 200 protein-disease pairings was estimated to be causal (γ = 0.005) giving an FDR in preclinical research of 92.6%, which likely makes a major contribution to the reported drug development failure rate of 96%. Observed success rate was only slightly greater than expected for a random pick from the sample space. Values for γ back-calculated from reported preclinical and clinical drug development success rates were also close to the a priori estimates. Substituting genome wide (or druggable genome wide) association studies for preclinical studies as the major information source for drug target identification was estimated to reverse the probability of late stage failure because of the more stringent type 1 error rate employed and the ability to interrogate every potential druggable target in the same experiment. Genetic studies conducted at much larger scale, with greater resolution of disease end-points, e.g. by connecting genomics and electronic health record data within healthcare systems has the potential to produce radical improvement in drug development success rate

COVID-19 in Pregnancy in Scotland (COPS):protocol for an observational study using linked Scottish national data

Funding: EAVE II funded by the Medical Research Council (MR/R008345/1) with the support of BREATHE - The Health Data Research Hub for Respiratory Health [MC_PC_19004], which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. Additional support has been provided through the Scottish Government DG Health and Social Care. COPS receive additional funding from Tommy’s charity (1060508; SC039280). SJS is supported by Wellcome Trust (209560/Z/17/Z).Introduction The effects of SARS-CoV-2 in pregnancy are not fully delineated. We will describe the incidence of COVID-19 in pregnancy at population level in Scotland, in a prospective cohort study using linked data. We will determine associations between COVID-19 and adverse pregnancy, neonatal and maternal outcomes and the proportion of confirmed cases of SARS-CoV-2 infection in neonates associated with maternal COVID-19. Methods and analysis Prospective cohort study using national linked data sets. We will include all women in Scotland, UK, who were pregnant on or became pregnant after, 1 March 2020 (the date of the first confirmed case of SARS-CoV-2 infection in Scotland) and all births in Scotland from 1 March 2020 onwards. Individual-level data will be extracted from data sets containing details of all livebirths, stillbirth, terminations of pregnancy and miscarriages and ectopic pregnancies treated in hospital or attending general practice. Records will be linked within the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) platform, which includes primary care records, virology and serology results and details of COVID-19 Community Hubs and Assessment Centre contacts and deaths. We will perform analyses using definitions for confirmed, probable and possible COVID-19 and report serology results (where available). Outcomes will include congenital anomaly, miscarriage, stillbirth, termination of pregnancy, preterm birth, neonatal infection, severe maternal disease and maternal deaths. We will perform descriptive analyses and appropriate modelling, adjusting for demographic and pregnancy characteristics and the presence of comorbidities. The cohort will provide a platform for future studies of the effectiveness and safety of therapeutic interventions and immunisations for COVID-19 and their effects on childhood and developmental outcomes. Ethics and dissemination COVID-19 in Pregnancy in Scotland is a substudy of EAVE II(, which has approval from the National Research Ethics Service Committee. Findings will be reported to Scottish Government, Public Health Scotland and published in peer-reviewed journals.Publisher PDFPeer reviewe

Self-Potential as a Predictor of Seawater Intrusion in Coastal Groundwater Boreholes

This work was supported by the Natural Environment Research Council in the UK, as part of the Science and Solutions for a Changing Planet Doctor Training Partnership, run by the Grantham Institute for Climate Change at Imperial College London. We thank Southern Water for access to the boreholes at Saltdean and Balsdean. We thank Southern Water and Atkins Global for funding the installation of the equipment. We also thank Dr Amadi Ijioma for providing a prototype of the electrodynamic modelling code in MATLAB, which has since been adapted for use in a coastal chalk aquifer. Three anonymous reviewers are thanked for their comments, which greatly helped to improve the manuscript. The data used in this paper are in the tables, figures and cited information. The authors have no conflicts of interest to declare.Peer reviewedPublisher PDFPublisher PD

Contribution of physical factors to handpump borehole functionality in Africa

Handpumps are the main water supply for rural communities across sub-Saharan Africa. However, studies show that >25 % of handpumps are non-functional at any time. We present results from a systematic field study of handpump borehole functionality. The study was designed to investigate the contribution of physical factors to functionality outcomes, including; hydrogeology, borehole configuration, and handpump components. To achieve this, we deconstructed and examined 145 handpump boreholes in Ethiopia, Uganda and Malawi. Pumping tests showed that 19 % of boreholes were located in aquifers with transmissivity below the minimum required to sustain a handpump. Water levels, measured during the dry season, had a complex relationship with borehole configuration and transmissivity. The handpump cylinder was <10 m below the water table at 38 % of sites, which increases the risk of the handpump running dry during intensive use and/or in areas of low transmissivity. The water column was <20 m at 23 % of sites and screens were <10 m long at 29 % of sites and often sub-optimally positioned in the borehole. Borehole depth had no clear relationship with functionality. Using multinomial regression and four functionality categories (functional; unreliable; low yield; unreliable and low yield) as dependant variables, we found that transmissivity is a significant risk factor for the classification of handpump boreholes as low yield. The configuration of the borehole (e.g. cylinder position, screen/casing configuration and water column) is a statistically significant risk factor for the classification of handpump boreholes as unreliable. Handpump components were in poor overall condition but rising main pipes were a particular problem with 53 % of galvanised pipes corroded and 82 % of uPVC pipes damaged, with implications for handpump performance. Our study highlights the importance of; understanding aquifer properties, investing in borehole siting, construction (including supervision) and commissioning, and improving the quality of components and maintenance of handpumps

Enabling Practice-driven Innovation in the Animal Production Sector

Using the laying hen sector as a case study, the EU-H2020-funded Hennovation project has been testing mechanisms to enable practice-driven innovation through the establishment of innovation networks of farmers and within the laying-hen-processing industry that are facilitated to proactively search for, share and use new ideas to improve hen welfare, efficiency and sustainability. Networks are variably supported by scientists, veterinarians, advisors and others. Nineteen multi-actor networks have been mobilised on local and regional levels across the UK, Sweden, Netherlands, Spain and Czech-Republic.Practice-driven innovation processes were network specific and evolved as the actors within the network came together to share common problems, experiment with possible solutions and learn. Their success was also affected by the institutional context, the structure of the poultry sector, current market forces and wider Agricultural Innovation Systems in each country. This paper explores the circumstances considered necessary by the facilitators to enable practice-driven innovation, providing examples of conditions affecting the innovation process. Further influences included conditions for innovation to happen (e.g. shared opportunity, motivation and knowledge), conditions to work effectively as a network (e.g. trust, collective purpose and contacts) and conditions for successful application in practice (e.g. capacity within the production system and market and legislative ability)

Dimethylarginine dimethylaminohydrolase I enhances tumour growth and angiogenesis

Angiogenesis is a prerequisite for tumour progression and is highly regulated by growth factors and cytokines a number of which also stimulate the production of nitric oxide. Asymmetric dimethylarginine is an endogenous inhibitor of nitric oxide synthesis. Asymmetric dimethylarginine is metabolised by dimethylarginine dimethylaminohydrolase. To study the effect of dimethylarginine dimethylaminohydrolase on tumour growth and vascular development, the rat C6 glioma cell line was manipulated to overexpress the rat gene for dimethylarginine dimethylaminohydrolase I. Enhanced expression of dimethylarginine dimethylaminohydrolase I increased nitric oxide synthesis (as indicated by a two-fold increase in the production of cGMP), expression and secretion of vascular endothelial cell growth factor, and induced angiogenesis in vitro. Tumours derived from these cells grew more rapidly in vivo than cells with normal dimethylarginine dimethylaminohydrolase I expression. Immunohistochemical and magnetic resonance imaging measurements were consistent with increased tumour vascular development. Furthermore, dimethylarginine dimethylaminohydrolase activity was detected in a series of human tumours. This data demonstrates that dimethylarginine dimethylaminohydrolase plays a pivotal role in tumour growth and the development of the tumour vasculature by regulating the concentration of nitric oxide and altering vascular endothelial cell growth factor production