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1. The supplementation of a prebiotic improves the microbial community in the gut and the skin of Atlantic salmon (Salmo salar)

Author

Simon Baumgärtner, Jack James, and Amy Ellison

Subjects
Microbiome, Prebiotics, Atlantic salmon, Fish health, Sustainable nutrition, Novel feeding strategies, Aquaculture. Fisheries. Angling, SH1-691
Abstract

Aquaculture growth is hindered by an increasing number of challenges, primarily infectious diseases and inappropriate or unsustainable fish nutrition. Hence it is critical to develop novel prevention strategies to minimise infectious diseases and pharmaceutical interventions. Nutritional challenges and the health of the fish could be improved by managing their microbial communities. Microbiomes can play a crucial role in fish physiology, particularly in digestion, by metabolizing largely indigestible feed components for the host or synthesis essential micronutrients. Beyond their nutritional role, microbiomes are considered the first line of defence against pathogens. In this study, a novel prebiotic mix (Selectovit), composed of 1,3/1,6-beta glucans, mannan-oligosaccharides, nucleic acids, nucleotides, medium chain fatty acids and single chain fatty acids, was tested at different inclusion levels (0.0; 0.5; 1.0; 2.0 g/kg) in the diet of Atlantic salmon (Salmo salar). Using experimental feed trials and 16 S rRNA microbiome profiling, the impact of the prebiotic blend on fish growth and microbial community within both the gastrointestinal tract and the skin was assessed. Overall, the supplement showed no significant impact on growth. However, we clearly demonstrate that the prebiotic can significantly manipulate the microbial community of the distal intestine and the skin. Several potential beneficial bacteria such as Bacillus and Mycoplasma spp. were significantly more abundant in the prebiotic-fed groups compared to the control. In contrast, putative pathogenic bacteria were less abundant in the salmon fed the prebiotic blend. Interestingly, the supplement induced more changes in the skin than in the gut. There is growing evidence in fish for highly complex interactions between the microbial communities of the digestive system and external mucosa, and with the host immune system. Further research in this field could lead to the creation of novel bacterial biomarkers and new non-invasive strategies for fish digestive health monitoring.

Published
2022
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2. Salivary Volatile Organic Compound Analysis: An Optimised Methodology and Longitudinal Assessment Using Direct Injection Mass Spectrometry

Author

Bhamini Vadhwana, Jack James, Melina Pelling, Ilaria Belluomo, Piers R. Boshier, and George B. Hanna

Subjects
volatile organic compounds, saliva, headspace, variation, direct mass spectrometry, selected ion flow tube-mass spectrometry, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

Analysis of salivary volatile organic compounds (VOCs) may offer a novel noninvasive modality for disease detection. This study aims to optimise saliva headspace VOC analysis and assess longitudinal variation of salivary VOCs. Whole saliva from healthy participants was acquired in order to assess four methodological parameters: saliva collection, volume, dilution, and acidification. Saliva VOCs were analysed using untargeted proton transfer reaction time-of-flight mass spectrometry. Using the optimised method, five saliva samples collected over 3 weeks assessed the longitudinal VOC variability and reproducibility with targeted selected ion flow tube-mass spectrometry analysis. The method of saliva collection influenced VOC detection and was a source of contamination. An amount of 500 µL of whole saliva by passive drool yielded optimal VOCs. Longitudinal variation was negligible with target short chain fatty acids and aldehydes. However, certain compounds showed variability suggesting the influence of potential exogenous factors. Overall, there was an acceptable range of inter- and intraindividual VOC variability. Standardisation with morning sampling after a 6 h fast is recommended demonstrating minimal intersubject variability. Future studies should seek to establish salivary VOC levels in healthy and diseased populations.

Published
2023
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3. Protein over-expression in Escherichia coli triggers adaptation analogous to antimicrobial resistance

Author

Jack James, Benjamin Yarnall, Andy Koranteng, Jane Gibson, Tahmina Rahman, and Declan A. Doyle

Subjects
Escherichia coli, Antimicrobial resistance, BL21(DE3), Protein over-expression, Microbiology, QR1-502
Abstract

Abstract Background The E. coli pET system is the most widely used protein over-expression system worldwide. It relies on the assumption that all cells produce target protein and it is generally believed that integral membrane protein (IMP) over-expression is more toxic than their soluble counterparts. Results Using GFP-tagged proteins, high level over-expression of either soluble or IMP targets results in > 99.9% cell loss with survival rate of only 99.9% cell death. These results redefine our understanding of protein over-production and link it to the adaptive survival response seen in the development of antimicrobial resistance.

Published
2021
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4. Is There an Association Between Untreated Hearing Loss and Psychosocial Outcomes?

Author

Dona M. P. Jayakody, Justin Wishart, Inge Stegeman, Robert Eikelboom, Thomas C. Moyle, Jessica M. Yiannos, Jack James Goodman-Simpson, and Osvaldo P. Almeida

Subjects
hearing loss, social loneliness, emotional loneliness, social support, social interaction, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

ObjectiveAge-related hearing loss is one of the leading causes of disability in older adults. This cross-sectional study investigated the association between untreated hearing loss, social (perception of quality and quantity of social network) and emotional loneliness (perception of limited emotional support), social isolation (size of the social network), social support (actual or perceived availability of resources from the social network) and psychological discomfort (depression, anxiety, and stress) in older adults.Study DesignCross-sectional study design.MethodsA total of 202 community derived sample of volunteers, age range 40–89 years, mean age (M) = 65.3 ± 11.0 years were recruited. Of these 115 were females (M = 63.2 ± 12.0 years) and 87 were males (M = 68.2 ± 8.9 years). All participants completed a hearing assessment, social interaction and support questionnaire and a social and emotional loneliness questionnaire.ResultsHearing loss significantly contributed to both moderate [P < 0.001, B (95% CI): 0.01 (0.99–1.02)] and intense levels [P < 0.001, 0.02 (1.00–1.04)] of emotional loneliness. Depression was significantly associated with satisfaction with social support [P < 0.001; −0.17 (−0.23 to −0.11), social interaction [P = 0.01; −0.07 (−0.12 to −0.01)], and moderate [P < 0.001; 0.31 (1.22–1.53)] and intense [P < 0.001; 0.29 (1.20–1.50)] levels of emotional loneliness and intense levels of social loneliness [P = 0.01; 0.12 (1.05–1.21)].ConclusionUntreated hearing loss significantly increases the odds of being emotionally lonely. Depression significantly contributes to social and emotional loneliness, satisfaction with social support and social loneliness. Given the higher prevalence of loneliness and psychological discomfort and their associations with untreated hearing loss, hearing-impaired older adults are at significant risk of developing loneliness and psychological discomfort. Therefore, hearing health professionals should be aware of the psychosocial burden that may accompany hearing loss, in order to provide appropriate advice and support.

Published
2022
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5. Palatability Enhancement Potential of Hermetia illucens Larvae Protein Hydrolysate in Litopenaeus vannamei Diets

Author

David Terrey, Jack James, Ivan Tankovski, Monika Dalim, Michel van Spankeren, Arpita Chakraborty, Eric Schmitt, and Aman Paul

Subjects
insect, protein hydrolysate, free amino acids, short chain peptides, Litopenaeus vannamei, palatability, Organic chemistry, QD241-441
Abstract

Marine feed ingredients derived from cephalopods (e.g., squid) and crustaceans (e.g., krill) are commercially used to improve the palatability of shrimp diets. Increase in global demand for shrimps has resulted in overfishing of these marine organisms and is a matter of concern. Insect protein hydrolysate could be a sustainable alternative for the possible replacement of these marine feed ingredients. During this study, four formulations: diet A (control: not containing any palatability enhancer), diet B (containing squid meal and krill oil), diet C (containing 1% insect protein hydrolysate), and diet D (containing 2% insect protein hydrolysate) were tested for (1) time required by first subject to begin feeding (time to strike) and (2) palatability in Litopenaeus vannamei. Additionally, the chemical composition of all four diet formulations was also analyzed. Results indicate that all diets had similar crude composition. The major essential amino acids in all diets were leucine and lysine, whereas eicosapentaenoic acid was the major omega-3 fatty acid in all diets. There were no significant differences between the mean time to strike for all the tested formulations. Palatability of tested formulations was found in the following order: diet D > diet C > diet B = diet A (p < 0.05), indicating that addition of squid meal and krill oil has no effect on palatability in comparison to control, whereas inclusion of insect protein hydrolysates significantly improves the palatability of formulations. Palatability enhancement potential of insect protein hydrolysate could be attributed to the high free amino acid content and water solubility in comparison to squid meal.

Published
2021
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8. The Social Structure of School Resource Disparities: How Social Capital and Interorganizational Relationships Matter for Educational Equity

Author

Bridwell-Mitchell, E. N., Jack, James, and Childs, Joshua

Abstract

One potentially underestimated aspect of resource inequity in U.S. public schools is access to social capital in external organizational environments. This research examines partnerships among 211 New York City high schools and 918 partner organizations from 2001 to 2005 as sources of external school social capital providing resources that can strengthen organizational capacity to improve educational opportunities and outcomes. The findings, based on an innovative analysis combining content analysis, social network analysis, and multilevel modeling, demonstrate that four partnership characteristics are important in this context: (1) how long partnerships last versus how many there are, (2) partners concentrating resources in a particular area versus across diverse complementary areas, (3) partners being densely connected to other schools and partners rather than being central in the overall school-partner network, and (4) partners conveying instructional resources versus other kinds of resources. Hence, educational research and policy should more broadly conceptualize how schools' external organizational environments matter for educational equity and the role particular kinds of partnerships can play.

Published
2023
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11. Opioids

Author

Collantes, Enrique, additional, Ganty, Praveen, additional, Jack, James, additional, Norman, Jonathan, additional, and Rudiger, Jan, additional

Published
2022
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12. Miscellaneous

Author

Bedran, Hadi, additional, Chakka, Udaya, additional, Fitzmaurice, Bethany, additional, Ganty, Praveen, additional, Jack, James, additional, Keogh, Peter, additional, Pitchiah, Arumugam, additional, Poply, Kavita, additional, Rangaiah, Manamohan, additional, Rudiger, Jan, additional, Stasiowska, Maria, additional, Tameem, Alifia, additional, and Wong, Matthew, additional

Published
2022
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13. Clinical Pharmacology

Author

Bachtold, Sabina, additional, Balasubramanian, Shyam, additional, Guru, Rahul, additional, Howells, Katharine, additional, Jack, James, additional, Kapur, Sandeep, additional, and Rudiger, Jan, additional

Published
2022
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15. Development and characterisation of a dual bi-directional vortex cooling approach to lower the cost of a small liquid bi-propellant rocket engine

Author

Marlow, Jack James, Augousti, Andy, and Baker, Adam

Subjects
621.43, Mechanical, aeronautical and manufacturing engineering
Abstract

Low cost access to space, particularly for small satellites has been identified as one of the major needs of the 2015-2030 UK Space Innovation & Growth Strategy. Chemical propulsion, specifically liquid bi-propellant rocket engines, is the major cost driver for large and small launch vehicles, and has not historically been a strength of the UK. Analysis of the liquid bi-propellant rocket engine highlights that the cooling subsystem has historically been one of the main contributors to overall system costs. The majority of current liquid bi-propellant engines cooling approaches increasing engine complexity, may increase engine mass, reduce performance and require the use of exotic materials to manage high thermal loads. Therefore, the focus of this research is to develop a small low cost liquid rocket engine using a new thermal management approach called Dual Bi-Directional Vortex (DBDV) cooling to enable the use of an inexpensive lightweight metallic alloy for chamber construction, in conjunction with Additive Layer Manufacturing to further reduce costs. DBDV cooling involves producing a coaxial bi-directional vortex flow field using oxidiser injection at the nozzle end of the engine, which then flows towards the fuel injection in a spiral fashion along the chamber wall. This flow field and the resulting pressure gradients confine combustion to the centre vortex or 'hot core' and significantly reduce conduction and convection of heat to the inner chamber sidewall, negating the need for chamber cooling and the attendant disadvantages. The dual vortices also provide intense mixing of propellants which have the potential to increase combustion efficiency and engine performance. Three techniques were used to investigate and develop a small DBDV liquid rocket engine. First CFD studies were used to develop an oxidiser injector design by modelling the complex vortex flows. Second the final design was additive layer manufactured and subjected to cold flow water testing with fast visual data capture to deduce the general characteristics of the dual vortex flow. Finally, experimental hot fire testing compare an uncooled liquid rocket engine, designated the 20N conventional, to an aluminium chamber and ALM stainless steel/bronze vortex liquid rocket engine to evaluate the cooling benefit. Hot fire testing used gaseous oxygen and gaseous propane as the propellants and required significant modifications and upgrades to the existing rocket test facility at Kingston University. Multiple engines were built and instrumented with thermocouples at various chamber sidewall depths and locations to measure the temperature ride during the firing. Mass flow rate, thrust and pressure were also measured to evaluate performance. Engine hot fire testing reported a 77.5% chamber sidewall temperature reduction when using DBDV cooling approach compared to the uncooled engine, which also suffered thermal failure after 7.5 seconds. Average vortex engine chamber inner sidewall temperatures were 125 ̊C verses a predicted combustion flame temperature of 2731 ̊C, which permitted the steady state use of an uncooled aluminium alloy chamber and an additive manufactured stainless steel/bronze oxidiser injector. It was found the tangential oxidiser injector produced a reliable and symmetrical dual vortex flow field which functioned over a wide range of operating parameters. It was also found that increasing the fuel injection mass flow rate for a fixed oxidiser flow rate destabilised the flow field resulting in increased sidewall temperatures. Perspex chambers were also tested, but failed due to transient heating upon ignition leading to unwanted chamber combustion similar to a hybrid rocket engine. In summary, this research demonstrated that the DBDV cooling approach is effective at drastically reducing chamber sidewall temperatures enabling the use of a low-cost material for engine construction whilst maintaining engine performance.

Published
2017

16. Development of smart, compact fusion diagnostics using field-programmable gate arrays

Author

Lovell, Jack James

Subjects
530
Abstract

Fusion research requires high quality diagnostics to understand the complex physical processes involved. Traditional analogue systems are complex, large and expensive, and expansion of diagnostic capabilities is often impossible without building a completely new system at considerable expense. Field-programmable gate array (FPGA) technology can provide a solution to this problem. By implementing complex functionality and digital signal processing on an FPGA chip, diagnostic hardware can be greatly simplified and compacted. In this thesis we describe the enhancements of two diagnostics for the MAST-Upgrade tokamak using FPGA technology. Firstly, the design of the back end electronics for the new divertor bolometer is described. Results of tests of the new electronics at a number of sites, including lab-based testing and tokamak installations, are also presented. We demonstrate the correct functionality of the electronics and illustrate a number of important effects which must be taken into account when interpreting bolometer data on MAST-U. Secondly, we describe the new control and acquisition electronics developed for the MAST-U divertor Langmuir probe diagnostic. Much of the analogue control circuitry of the previous system has been upgraded to a digital implementation on an FPGA, which results in a significantly more compact and cost effective design. Given that MAST-Upgrade will feature around 850 Langmuir probes, these improvements are extremely important to keep the diagnostic manageable. Again, results are presented from the testing of the system at several sites, which both demonstrate the correct functionality of the new system and provide information on the diagnostic behaviour which needs to be accounted for when interpreting the probe data during MAST-U experiments.

Published
2017

17. Maternal temperature in emergency caesarean section (MATES): an observational multicentre study

Author

Hughes, Natasha, de las Casas, Ruth, Long, Charlotte, Skeoch, Chris, Duckham, Emily, Shippam, William, Barnes, Lucy, Madders, Rachel, Campbell, Natasha, Ali, Yousef, Pararajasingam, Suji, Stead, Richard, Katayani, Katayani, Jackson, James, Nolan, Louise, Kochar, Arun, Ranns, Christopher, Leong, Maria, Jack, James, Benoliel, Sophie, Annamalai, Partha, Picton, Graham, Lunberg-Adams, Matt, Lebbe, Asfir, Lau, Julie, Reddy, Anu, Sen, Soumen, Kanji, Rafiq, Riccaboni, Anna, Mackenzie, Matthew, Macallan, Jennifer, Mason, Rupert, Martins, Nicole, Hawksley, Sarah, Wimble, Katie, Ghafoor, Tahir, Hallewell, Christopher, Thomas, Janine, Misquita, Lucia, Walters, Michelle, Krishnan, Priya, McHale, Sean, Ashpole, Keri, George, Richard, Graham, George, Hudsmith, Jonny, Way, Mark, Armstrong, Sarah, Burwell, David, Iossifidis, Francoise, Uncles, David, Fludder, Vanessa, Bate, Tom, Thorburn, P.T., Monteiro, R., Chakladar, A., Cochrane, A., Roberts, J., and Mark Harper, C.

Published
2021
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19. High energy resummation and electroweak corrections in dijet production at hadronic colliders

Author

Medley, Jack James, Smillie, Jennifer, and Zwicky, Roman

Subjects
539.7, Coloured final states, quantum chromodynamics, Large Hadron Collider, LHC, dilepton pair, dijets, large dijet invariant mass, large dijet rapidity spans, Future Circular Collider, FCC
Abstract

Coloured final states are ubiquitous at hadron colliders such as the Large Hadron Collider (LHC). Therefore understanding high energy perturbative quantum chromodynamics (QCD) at these experiments is essential not only as a test of the Standard Model, but also because these processes form the dominant background to many searches for new physics. One such `standard candle' is the production of a dilepton pair in association with dijets. Here we present a new description of this final state (through the production of a Z⁰ boson and γ*). This calculation adds to the fixed-order accuracy the dominant logarithms in the limit of large partonic centre-of-mass energy to all orders in the strong coupling αs. This is achieved within the framework of High Energy Jets. This calculation is made possible by extending the high energy treatment to take into account the multiple t-channel exchanges arising from Z⁰ and gamma* -emissions off several quark lines. The correct description of the interference effects from the various t-channel exchanges requires an extension of the subtraction terms in the all-order calculation. We describe this construction and compare the resulting predictions to a number of recent analyses of LHC data. The description of a wide range of observables is good, and, as expected, stands out from other approaches in particular in the regions of large dijet invariant mass and large dijet rapidity spans. In addition we also present the application of the High Energy Jets framework to two new experimental scenarios. Firstly, we show a comparison of High Energy Jets matched to the ARIADNE parton shower to an ATLAS study of gap activity in dijet events. We see that our description agrees well with the data throughout and in many distributions gives the best theoretical description. This shows the extra logarithmic corrections are essential to describe data already in LHC Run I. Secondly, we present a study of Z⁰/γ* plus dijets at 100 TeV. We compare the behaviour of the high energy logarithmic enhancements to the QCD perturbative series at 7 TeV and 100 Tev and see that at any high energy hadronic Future Circular Collider (FCC) the effects described by our resummation become significantly more important.

Published
2016

20. An Analysis of Pennsylvania's Cyber Charter Schools. Issue Brief

Author

Research for Action, Jack, James, Sludden, John, and Schott, Adam

Abstract

Pennsylvania's first cyber charter school opened in 1998, enrolling 44 full-time students. From this modest beginning, Pennsylvania's cyber charter sector has grown to 16 schools enrolling 35,000 students from all but one school district in the Commonwealth. Pennsylvania has one of the nation's most extensive cyber charter sectors, and six additional proposed schools are before the Department of Education (PDE) for review. The recent growth in the sector coincides with increasing attention from state policymakers. As of this writing, there are at least 12 legislative proposals pending in the Pennsylvania General Assembly addressing cyber authorization, funding, or oversight. To help situate cyber charter schools within a state context, Research for Action (RFA) examined the state's recently-issued School Performance Profile (SPP) scores for the 11 cyber charters for which complete data are available. RFA then compared these scores to all public schools statewide, including traditional public schools and brick-and-mortar charters. RFA's analysis is based on publicly-available data from PDE's School Performance Profile. Also, given the relationship between student mobility and academic achievement, RFA examined enrollment into and out of five cyber charters for which data were available during the 2010-11 and 2011-12 school years. RFA reviewed the demographics of the student populations in cyber charter schools as compared to traditional public schools and brick-and-mortar charters. Main findings for these anlyses are reported here in tabulated form. A glossary of terms is included. Appendix A, "Cyber Charter Enrollment Trends for the 2011 and 2012 School Years", is presented in table 6.

Published
2013

21. From Policy to Practice: Tracing the Development and Implementation of Placement and Diagnostic Assessments across States, Systems, and Community Colleges. Lessons from Florida and Virginia Community Colleges -- Phase 2 Report

Author

Research for Action, Duffy, Mark, Tandberg, David A., Harrill, Sandra, Jack, James, Park, Elizabeth, and Shaw, Kathleen M.

Abstract

National initiatives to raise K-12 standards and align them to postsecondary entrance requirements have prompted states and/or state postsecondary systems to enact policies to improve alignment among postsecondary readiness standards, postsecondary placement and diagnostic exams, and developmental education curricula. This report examines how six community colleges--three each in the states of Florida and Virginia--responded to the state-wide reform of college placement and diagnostic testing. It is a companion piece to "From Policy to Practice: Tracing the Development and Implementation of Placement and Diagnostic Assessments across States, Systems and Community Colleges - Analysis of Policy Reform in Five States" (ED553141) that provided an analysis of how five states commissioned vendors to develop new placement tests that include a diagnostic component. Analysis in this report provides a comprehensive picture of state policy reform by tracing implementation through multiple levels--beginning most broadly at the state level and progressing through increasingly granular levels of implementation. Appendix A provides case studies and Appendix B presents "Local and Community College Characteristics."

Published
2013

22. School Closings in Philadelphia

Author

Jack, James and Sludden, John

Abstract

In 2012, the School District of Philadelphia closed six schools. In 2013, it closed 24. The closure of 30 schools has occurred amid a financial crisis, headlined by the district's $1.35 billion deficit. School closures are one piece of the district's plan to cut expenditures and close its budget gap. The closures are also intended to make Philadelphia's school system more efficient. Superintendent William Hite summarized the strategy: "This path will lead to greater educational investments throughout our more than 200 schools and improved educational outcomes for students. This path will reverse our enrollment declines as we create safer, more modern learning environments and build sustainable community partnerships and coalitions" (Hangley Jr., 2013). Research on the experiences of other major school districts that have undertaken large-scale school closings suggests a gap between the stated goals of the district's plans and the likely outcomes, particularly regarding academic and financial benefits to district students, staff, and taxpayers (Shaw & Schott, 2013). Despite existing evidence and significant opposition, large-scale closings proceeded in Philadelphia. The intent of this article is to examine why. Herein the author investigates school closings, the policies and factors contributing to these decisions, existing research on this subject, and what these developments may portend for the years ahead in Philadelphia.

Published
2013

23. Computer aided analysis of inflammatory muscle disease using magnetic resonance imaging

Author

Jack, James

Subjects
616.7, Computer aided diagnosis, Computer aided detection, Myositis, Machine learning
Abstract

Inflammatory muscle disease (myositis) is characterised by inflammation and a gradual increase in muscle weakness. Diagnosis typically requires a range of clinical tests, including magnetic resonance imaging of the thigh muscles to assess the disease severity. In the past, this has been measured by manually counting the number of muscles affected. In this work, a computer-aided analysis of inflammatory muscle disease is presented to help doctors diagnose and monitor the disease. Methods to quantify the level of oedema and fat infiltration from magnetic resonance scans are proposed and the disease quantities determined are shown to have positive correlation against expert medical opinion. The methods have been designed and tested on a database of clinically acquired T1 and STIR sequences, and are proven to be robust despite suboptimal image quality. General background information is first introduced, giving an overview of the medical, technical, and theoretical topics necessary to understand the problem domain. Next, a detailed introduction to the physics of magnetic resonance imaging is given. A review of important literature from similar and related domains is presented, with valuable insights that are utilised at a later stage. Scans are carefully pre-processed to bring all slices in to a common frame of reference and the methods to quantify the level of oedema and fat infiltration are defined and shown to have good positive correlation with expert medical opinion. A number of validation tests are performed with re-scanned subjects to indicate the level of repeatability. The disease quantities, together with statistical features from the T1-STIR joint histogram, are used for automatic classification of the disease severity. Automatic classification is shown to be successful on out of sample data for both the oedema and fat infiltration problems.

Published
2015

25. The Mere Exposure Effect in Architecture

Author

“Jack” James, Michael-Paul, Beorkrem, Christopher, Ellinger, Jefferson, De Rycke, Klaas, editor, Gengnagel, Christoph, editor, Baverel, Olivier, editor, Burry, Jane, editor, Mueller, Caitlin, editor, Nguyen, Minh Man, editor, Rahm, Philippe, editor, and Thomsen, Mette Ramsgaard, editor

Published
2018
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26. Cancelled operations: a 7-day cohort study of planned adult inpatient surgery in 245 UK National Health Service hospitals

Author

Moonesinghe, S. Ramani, Wong, Danny J.N., Harris, Steve K., Bedford, James, Boney, Oliver, Chazapis, Maria, Drake, Sharon, Farmer, Laura, Gilhooly, David, Goodwin, James, Lourtie, Jose, Wagstaff, Duncan, Grocott, Mike, Sneyd, Robert, Batchelor, Anna, Brett, Stephen, Plowright, Catherine, Shrestha, Suman, Shawyer, Richard, Ahmed, Shafi, Khondoker, Mizan, Nathanson, Mike, Cripps, Paul, Research & Audit Federation of Trainees (RAFT), Anaesthetic Audit and Research Matrix of Yorkshire (AARMY), Intensive Care & Anaesthesia Research Network of North East Trainees (INCARNNET), Merseyside Anaesthetic Group for Improving Quality (MAGIQ), Midlands East Research by Critical Care and Anaesthetic Trainees (MERCAT), North West Research and Audit Group (NWRAG), Oxford Critical Care Anaesthetic Research Enterprise (OxCCARE), Pan-London Peri-operative Audit & Research Network (PLAN), Scottish East Quality Improvement & Research Academy (SEQuoIA), SESSA Quality Improvement and Research Network (SQUARES), Severn Trainees Anaesthetic Research (STAR), South West Anaesthetic Research Matrix (SWARM), South Yorkshire Hospitals Audit and Research Collaboration (SHARC), Southcoast Peri-operative Audit and Research Collaboration (SPARC), Welsh Anaesthetic Audit Research & Engagement Network (WAAREN), West Midlands Trainee Research Anaesthesia & Intensive Care Network (WMTRAIN), Rawat, Shilpa, Sathe, Sonia, Campbell, Alison, Anandarajah, Janakan, Ball, Nicola, Bandara, Lalindra, Barnes, Dennis, Chapman, Catherine, Connor, Lynda, Cook, Amanda, Ebejer, Amanda, Evans, Samantha, Gallagher, Maire, Goff, Sarah, Halfacree, Irina, Harford, Rachel, Harris, Catherine, Jackson, Rebecca, James, Kathryn, Jones, Claire, Jones, Sharon, Malinovszky, Kathy, Mungai, Serah, Nageswaran, Hari, Perumal, Anand, Pudge, Harriet, Quinn, Leanne, Sheppard, Thomas, Smith, Trudy, Spargo, James, Storton, Sharon, Thomas, Caradog, Thomas, Charlotte, Tyrrell, Samuel, Vale, Owen, Williams, Catrin, Williams, Marie, Williams, Tom, Winfield-Young, Lewys, Worrell, Helen, Moloney, Dermot, Chuni, Chandini, Comara, Jasna, Conway, Brian, Eagle, Zara, Foster, Greg, Platt, Chris, Thorne, Alison, Hee, Wendy Lum, Armstrong, Lisa, Brennan, Albert, Burns, Justine, Busby, Chantal, Couch-Upite, Mechele, Dooks, Emma, Dunlop, Sally, Eijk, Anya, Govindaraju, Ramana, Gregory, Tamsin, Grover, Alka, Hairsine, Brigid, Hennell, Sarah, Hill, Philippa, Hollins, Thomas, Hood, Julian, Horner, Lisa, Hothersall, Helen, Ingham, Rachel, Jackson, Richard, Kitching, Amy, Kurasz, Claire, Munsie, Sarah, Nemeth, Ildiko, Paley, Carole, Premraj, Prabhakaran, Redhead, Sue, Scriven, John, Shaw, Alison, Shenton, Liz, Shiva, Hemantha, Snell, Josie, Sootheran, Lucy, Stewart, Josephine, Swinton, Frank, Totten, Claire, Varghese, Liz, Vest, Sarah, Wetherell, Ben, Hamlyn, Vincent, Tozer, James, Alce, Timothy, Bopanna, Poonam, Draper, Kevin, Emmett, Lucy, Falkner, Phillippa, Fisher, Ellie, Griffiths, Cat, Gunter, Una, Harris, Rebecca, Hashmi, Saima, Jewitt, Helen, Lodhi, Sonal, Organ, Angie, Owen, Elana, Taylor, Frances, Tritean, Maria, Wassall, Richard, Woolley, Jade, MacGregor, Mark, Atkinson, Claire, Croft, Maria, Frost, Victoria, George, Richard, Gray, Catherine, Kuttler, Anja, Lalani, Christina, Peers, Beth, Sharpe, Lisa, Skeoch, Christopher, Tarft, Hayley, Tyson, Emma, Wrigley, Martha, Qadri, Shabir, Abbas, Tahir, Barot, Niraj, Cole, Steve, Ganesh, Ritesh, Groves, Christopher, Iles, Lindsey, Petkova, Hristina, Rau, Clovis, Roberts, Jack, Shakir, Nadeem, Chaurasia, Sunil Kumar, Brown, Julia, Cunningham, Mishell, Daniels, Allison, Gannon, Emily, Haines, Annette, Johnson, Nicola, Ogle, Paul, Perumal, Srinivasan, Zeidan, Lisa, Torrance, Hew, Anwar, Sibtain, Gooneratne, Mevan, Raj, Ashok, Abbott, Tom, Ashton, Laura, Brown, Katherine, Butterfield, Emma, Fenn, Jon, Forsyth-Jones, Tim, Garth, Thomas, Gleeson, Liam, Haines, Ryan, Jacobs, Benjamin, Jyothiraj, Haren, Madhi, Shareef, Marriot, Charlotte, Martin, Rebecca, McMillan, Timothy, Menon, Arun, Mohr, Otto Ernst, Muelmenstaedt, Maria, Naeem, Hanzla, Nagendram, Myura, O'Connor, Cormac, Pang, Ching, Plummer, Kimberley, Rob, Zak, Sellers, Dan, Shaw, Michael, Smith, Christopher, Taylor, Tom, Thorat, Priya, Van Rensberg, Gerhardus, Walker, Sophie, Waqas, Farkhunda, Wicks, Peter, Wirth, Daniel, Armanious, Samuel, Allen, Kellie, Bruni, Salvatore, Burijinti Chenna, Keshava Reddy, Kaliappan, Agilan, Ocampo, Madelaine, Percuin, Adrian, Riches, Joanne, Saclot, Louie, Sevillano, Annaliza, Vertue, Mark, Knowlden, Peter, David, Beena, Gajendragadkar, Pushpaj, Gladstone, George, Hammerbeck, Henry, Iaverdino, Marina, Lilley, Carina, Linton-Willoughby, Ben, Murrell, Daniel, Patro, Shweta, Richie-Mclean, Susanna, Turnbull, Marc, Vatsala, Padmanabhan, McCourt, Killian, Black, Nick, Coary, Ciara, McCarter, Jonathan, Murphy, Alexandra, Pugh, Richard, Littler, Chris, Clements, Stephan, Bairkdar, Linda, Bennett, Gillian, Bird, Tom, Bolger, Annette, Dhar, King, Ene, Raluca, George, David, Haron, Dhania, Hobson, Lucie, Iqbal, Saba, Irvine, Lizzie, Lewis, Sion, McCallum, Roisin, O'Donovan, Benjamin, Patrick, Christopher, Perman, Christopher, Rahman, Nowfal, Roberts, Iolo, Sutcliffe, William, Towers, Tammy, Waite, Alicia, Wright, Stella, Pilsbury, Jane, Allan, Michael, Allen, Cody, Carden, Nikkita, Cotterill, Amanda, Cullis, Kerry, Eden, Daniel, Farmer, Nicola, Galloway, Andrea, Geoghegan, James, Gilani, Ahmed, Hard, Kelly, Hasan, Khalid, Horner, Christopher, Iqbal, Virginia, Lowe, Julie, Mallavalli, Ravindra, McCooty, Shanteela, McKillop, Sian, Mellers, Diane, Mukherjee, Ronan, Nicholas, Michelle, O'Hara, Chloe, Osborne, Fiona, Plunkett, Emma, Sharih, Gauhar, Westwood, John, Whapples, Annabelle, Whitehouse, Diane, Williams, Lucinda, Yasin, Bilal, Cupitt, Jason, Brown, Janette, Stoddard, Emma, Balasubramaniam, Madhu, Athanasopoulos, Paul, Bhatti, Mohammad, Blood, Laura, Buckley, Hugo, Chadwick, Julie, Cocks, Shirley, Fradkin, Deborah, Hetherington, Emily, Hill, Rebecca, Hull, Rob, Loftus, Alison, McKenna, Emma, Mcmanoman, Lucy, Milian, Lauren, Mistry, Raksha, Murthen, Lisa, Parkinson, Dave, Rhead, Kat, Sandbach, Peter, Walker, Ciara, Wheatley, Emma, Spencer, Robert, Alderson, Stephen, Bull, Christopher, Butterworth, Rachel, Cousins, Simon, Goellner, Sarah, Greasley, Mark, Lyle, Fiona, Munro, Michael, Northey, Martin, White, Stuart, Harrison, Alex, Whitney, Paul-Simon, Drake, Jeremy, Babla, Rohan, Bharti, Ash, Cole, Stephen, Crotty, Stephen, Farrow, Amy, Golhar, Anil, Indoe, Peter, Jackson, Rosada, Latif, Mariam, Leong, Melvin, Lewith, Henry, Maton-Howarth, Matthew, Millar, Victoria, Millette, Ben, Oliver, Hannah, Ralhan, Vandita, Rashid, Yasir, Rivero-Bosch, Maria, Rizvi, Sana, Saleh, Rosahn, Venkatesh, Harisg, Wilson, Kate, Nair, Ashok, Basvi, Precious, Bell, Gillian, Edwards, James, Lee, David, Luo, Guanmei, Mewies, Clare, Qureshi, Arif, Sohail, Behzad, Valap, Sachin, Hill, Stephen, Bhuwanee, Deepti, Chan, James, Dereix, John, George, Allen, Ghafoor, Tasmeen, Gold, Emma, Haigh, Daniel, Harding, David, Janardhana, Bhavia, Jayan, Jithu, King, James, Laloë, Pnt, Pearce, Lauren, Pruthi, Amit, Roscoe, Eleanor, Seharawat, Deepak, Stubbington, Mark, Vanjari, Vinayak, Venkataraman, Anantharaman, Yen, Serena, Patil, Vishal, Chan, Charles, Davenport, Garry, Featherstone, Peter, Fourie, Petrus, Hall, Christopher, Mahidik, Preeti, Masoni, Elisa, Ortu, Andrea, Patil, Anita, Pickett, Janet, Sharma, Sandeep, Goodwin, Naomi, Allen, Lucy, Anderson, Nathan, Bateson, Ethan, Bhatia, Sanchita, Churchill, Sara, Cohen, Leon, Colhoun, Patrick, Dunn, Charlotte, Durie, Carys, Elgarf, Sarah, Ferry, Jenny, Guilford, Jeremy, Halligan, Claire, Harrison, Jade, Hayes, Dominic, Holst, Ben, Hughes, Rhys, Hunt, Thomas, Jackson, John, Kohler, George, Kriger, Michael, Kulikouskaya, Svetlana, Kurani, Amit, Maden, Charlotte, Moore, Alex, Mounce, Adam, O'Donnell, Alice, Sparrow, Robert, Sutherland, Jayne, Hanison, James, Bansal, Sujesh, Greenwood, Nick, Alkholany, Mahmoud, Apple, Zoe, Asif, Anam, Bhardwaj, Neeraj, Braid, Karl, Coates, Rebecca, Czukowska, Liliana, Elliott, Lauren, Fang, Li, Greenlee, Hannah, Maria, Jashmin, Mostafa, Tarek, Patil, Amarjeet, Weigert, Andrea, Matson, Alexandra, Adamson, Christine, Barclay, Philip, Barker, Amy, Bautista, Carina, Biswas, Suman, Bull, Rhian, Carungcong, Jaime, Christoper, Fenner, Cifre, Elna, Clancy, Olivia, Friedman, Lauren, Frunza, Gabriella, Habib, Sadia, Keerthikumar, Hindusha, Kirwan, Ursula, Laycock, Helen, Leir, Sarah, Maduekwe, Victor, Martella, Carmela, Meritahti, Minna, Nundlall, Kribashnie, Oblak, Metod, Panesar, Kirat, Peters, Timothy, Pett, Eleanor, Routley, Catriona, Samani, Amee, Santhirapala, Vatsharlan, Sayan, Amrinda, Sisson, Alice, Svensson, Marie-Louise, Thankachen, Mini, Tilley, Bernadette, Topham, Charlotte, Visvendra, Sathya, Warrington, Anna, Wibberley, Helen, Spittle, Nick, Andrews, Mia, Beavis, Sarah, Bernotaitis, Daiva, Chinna, Shalini, Church, Helen, Edwards, Sian, Ford, Nicky, Hazeldine, Sarah, Hudson, James, Macey, Claire, Morgans, Matthew, Toms, Julie, Whileman, Amanda, Woodward, Jan, Wright, Stephanie, Nariani, Jaya, Clark, Sam, Duniec, Larysa, Slorach, Marc, Allan, Ashley, Burrill, Bryony, Fairless, Lynn, Francis, Nicholas, McAdam, Colin, Sheriff, Julie, McLoughlin, Thomas, Arshed, Shayan, Bird, Clare, Campbell, Debbie, Chinery, Elaine, Onya, Enoch, Perry, Ryan, Sabugueiro, Jose Miguel, Shatanda, Lydia, Sheik, Muzaffar, Jo simpson, Wong, Gabriela, Yun-Han, Chen, Wilson, Lawrence, Adshead, Duncan, Castillo, David, Faulkner, Maria, Gibson, Kim, Keogh, Tara, Michlig, Sam, Perritt, Elizabeth, Ridler, Simon, Tizzard, Kate, Troy, Anne, Rafi, Amir, Melsom, Helen, Atkinson, Vikki, Azad, Tariq, Bashliyski, Vladimir, Brown, Ellen, Clark, Sarah, Cowton, Sister Amanda, Deane, Jill, Dent, Jean, Duckett, Karin, Duncan, Louise, Hooper, Nicholas, Johnson, Tom, Kay, Andrea, Kelly, Donna, Kent, Melanie, Knight, Jo, McCarroll, Christina, Newby, Annie, Potts, Kathryn, Roe, James, Rollins, David, Sarwar, Asia, Schofield, Lewis, Skelton, Deborah, Somanath, Sameer, Taysum, Peter, Temple, Julie, Udall, William, Varin, Jane, Venyo, Lucy, Warin, Martin, Wood, Shelly, Dhileepan, Srinivasan, Saibaba, Ravishankar Jakkala, Stewart, Emma, Warwick, Eleanor, Pemberton, Omar Alex, Garmash, Maryna, Griffiths, Rhys, Hale, Suzi, Lahloub, Fatma, Lynch, Ceri, Majeed, Abbas, Patchell, Ifan, Quinton, Jennifer, Sedghi, Babak, Wallis, Stephanie, Mansoor, Sange, Belagodu, Zakaulla, Dastur, Shirin, Fuller, Bridget, Hayes, Imogen, Keshkamat, Ashwini, Monantera, Georgia, Sandhar, Roxana, Sivakumaran, Shamini, Thomas, Megan, Torne, Manish, Turner, Sherma, Wakefield, Phillipa, Rogerson, David, Addleton, Catherine, Aju, Lisha, Appleby, Marie, Barnes, Elizabeth, Boateng, Trish, Carrick, Laura, Coulborn, Elaine, Darbyshire, Rebecca, Downes, Charlotte, Fitzgerald, Jodie, Hall, Linda, Harvey, Laura, Hassan, Amr, Holding, Kathleen, Hufton, Lianne, Humphries, Louise, Humphries, Ryan, Inman, Laurence, Issit, Nicole, Longhurst, Sarah, MacGregor, Melody, Mistry, Trusha, Mohamed, Mona, Otieno, Charlene, Read, David, Scott, Michelle, Singleton, Abbie, Smith, Jill, Sohal, Aariana, Tou, Samson, Unsworth, Vanessa, Wan, Richard, Worth, Christopher, Dobson, Richard, Buckley, Rose, Codling, Rachel, Hunter, Cain, Jackson, Jenny, Lowrie, Caroline, McMillan, Catherine, McNab, Raj, Richardson, Max, Sylvester, James, Watkin, Anna, Chambers, Jonathan, Bown, Rachel, Christie, Colin, Dukes, Stephanie, Horton, Sarah, Rees, Andrew, Williams, Patricia, Williams, Sarah, Pierson, Richard, Agarwal, Nipun, Allcock, Clare, Banga, Irmeet, Baron, Kirsty, Cole, Andrea, Dalay, Santinder, Gidda, Ranjit, Lo, Phillip, Merotra, Susan, Newton, Kathryn, Riddell, Zoe, Sonksen, Julian, Jamadarkhana, Sunil, Alcock, Chanice, Allen, Wei Lin, Baker, Pearl, Beadle, Hannah, Bramall, Jon, Chiravasuta, Radu, Chohan, Amina, Christofides, Angela, Cook, Angela, Cotta, Janet, Cruz, Carina, Gilmore, Jemma, Hills, Vicky, King, Kathryn, McClelland, Lucy, Nishimura, Sei, Nyathi, Rumyana, Panagoda, Prasan, Peacock, Louise, Shinn, Emma, Spencer, Sophie, Vianzon, Mayumi, Kapoor, Ritoo, Natarajan, Nagendra, Moore, Joanna, Amoakwa-Adu, Freda, Bahlool, Sinan, Cosier, Tracey, Driscoll, Sarah, Dulea, Claudia, Feneley, Andrew, Fletcher, Marcus, Hammad, Walid, Hazelton, Tracy, Hoyland, Kim, Katyayani, Bennur, Lloyd, Catherine, Moon, Angela, Musselwhite, Janine, Nair, Ganesh, O'Donnell, Joshua, Patankar, Pushkar, Redington, Katy, Sange, Aalia, Snazelle, Mark, Srbljak, Vanja, Stead, Richard, Tariq, Ismail, Thomas, Janine, Turney, Sharon, Chukkambotla, Srikanth, Mathew, Aji, Lie, Jason, Badsha, Zackriah, Bews, Sam, Bhandari, Kumud, Cartmell, Catherine, Cox, Greg, Desai, Hawa, Doran, Mark, Duberley, Stephen, Fitchett, Jill, Forrest, Diane, Freeman, David, Gani, Asif, Gedling, Catherine, Giles, Jessica, Goddard, Wendy, Gregson, Linda, Grimes, Yvonne, Hammond, Bev, Hartley, Janice, Hudson, Gemma, Ibrahim, Ramez, Iqbal, Nasreen, Jewers, Karen, Johnston, Brian, Kakkar, Abhishek, Koczka, Istvan, Lovell, Matt, Mahmoud, Mohamad, Melvin, Cathie, Milner, Matt, Moss, Nicky, Patel, Jeet, Perry, David, Pollard, Mike, Reed, Stephanie, Rennie, Gillian, Riley, Karen, Samuels, Sherrie, Simionescu, Ioana, Sissons, Lorna, Traynor, Stephen, Tucker, Daniel, Vetuz, Glenn, Whalley, Gillian, Marshall, Philippa, Arnold, Tim, Brookes, Jamie, Cowley, Anne, Delascasas, Ruth, Edmunds, Emma, Espitalier-Noel, Dominic, Jeevananthan, Rajeev, Law, Jenni, Mintrim, Kelly, Reid, Jack, Terry, Jackie, Verma, Manish, Zahra, Jean-Paul, Thorning, Geoff, Bailes, John, Dawson, Lindsay, Donovan, Clare, Gan, Jo Han, Jeyarajah, Kaya, Selman, Andrew, Woods, Justin, Csabi, Peter, Choo, Yin Yong, Das, Saheli, Denford, Clare, Desai, Mihir, Dimber, Rahul, Ellisy, Khaled, Griffiths, Ben, Lee, Sindy, Linnett, Vanessa, Daniels, Alex, Perkin, Sadie, Ritzema, Sister Jenny, Storey, Sister Bryony, Wood, Christine, Orme, Robert, Koh, Sock, Banks, Charis, Barker, Oliver, Beames, Susan, Brown, Aislinn, Corbett, Lucy, Dalton, James, Davis, Fiona, Edmunds, Matthew, Gatfield, Will, Gerrans, Edmund, Hickish, Tom, Hignell, Emily, Hiltout, Paula, Johnston, Helen, Miller, Sam, Mullender, Jo, O'Connell, Susan, Rosedale, Kath, Samuel, Katie, Vannahme, Milena, Baigel, Gary, Grayland, Sarah, Hawley, Victoria, McAffrey, Laura, Peggler, Suzannah, Stevens, Joe, Bidd, Heena, El-Boghdadly, Kariem, Zucco, Liana, Adelaja, Yemi, Bhattacharyya, Sanjoy, Bickmore, Elsie, Body, Suzanne, May-Ling Cheung, Jenny, Chowdhury, Priaykam, Cuddihy, Joshua, Ekwere, Ndi, John-Baptiste, Ange Lise, Kelly, Paul, Leslie, Daniel, Mon, Wint, Muzengi, Natasha, Ong, Cheng, Pattni, Nisha, Potter, Thomas, Stanton, Elena, Zaky, Maryam, Partridge, Richard, Bromhead, Helen, Evans, Peter, Griffin, Denise, Kinsella, J. Joseph, Knight, Alexander, Lewis, Rosemary Anna, Lightfoot, Heidi, Martin, Jane, Mupudzi, McDonald, Nahajski, Katherine, Oladele, Segun, Ottaway, Julia, Petley, Stephen, Sheldrake, Ian, Stewart, Alexander Michael, Stokes, Aaron, Trodd, Dawn, Varsani, Nimu, Walshe, Eleanor, Brown, Caroline Wrey, Huntley, Martin, Baldry, Natalie, Bennett, Caroline, Earl, Sophie, Guy, Joyce, Peat, Maggie, Stephenson, Lorraine, Tan, Hao Ern, Wills, Louise, Yare, Michelle, Yeung, Joyce, Antrolikar, Supriya, Atterbury, Katie, Baba, Fayaz, Bancroft, Hollie, Begum, Safia, Bellamy, Mary, Couper, Keith, Evans, Lucy, Flight, Rachel, Frankling, Catriona, Ganesh, Srikant, Gresty, Joanne, Joslyn, Ruth, Kadiri, Salma, Karimi, Aalisha Mariam, Kerr, Amy, Melody, Teresa, Moore, Faye, Morrish, Jennifer, O'Sullivan, Mary, Patel, Vanisha, Reeves, Eleanor, Robley, Richard, Sampson, Julia, Sangombe, Mirriam, Shabangu, Vusumuzi, Sheppard, Lucy, Stafford, Sam, Sutton, Peter, Taylor, Joanne, Turner, James, Velho, Rochelle, Webb, Joanne, Webber, Linda, Werpachowska, Ewa, Wilkinson-Guy, Lisa, Papageorgiou, Constandinos, Bisonoothan, Sohan, Casely, Emma, Casey, Carina, Kam, Elisa, Landers, Geraldine, Pearse, Laura, Raja, Meera, Solomon, Daniel, Stoyanov, Plamen, Talati, Chiraag, Arunachalam, Hari, Ashton, Victoria, Full, Jens, Green, Samira, Gratrix, Andrew, Abernethy, Caroline, Clarke, Abigail, Desai, Pallavbhai, Martinson, Victoria, Parekh, Ravi, Phillips, Mirain, Raina, Anju, Raut, Sarah, Smales, Chris, Smith, Neil, Ugochukwu, Ruth, Willis, Matt, Ignatova, Zhana, Gill, Stuart, Agarwal, Sunita, Barclay, Harry, Campbell, Brian, Collingborn, Maggie, Dagnan, Richard, Davies, David Steven, Dhaliwal, Randeep, Dharmarathna, Ishan, Doriaswami, Yuvraj, Evans, Hywel, Foly, Ahmed, Francis, John, Green, Tim, Hassanin, Ahmed, Havalda, Peter, Huda, Ahmad, Jones, Beryl, Khoju, Ramesh, Lackmann, Maria, Mensah, Kofi, Nwaefulu, Christopher, Schmidt, Ilona, Selvraj, Gopinath, Skarbit, Norbert, Suganthi, Obla, Zeber, Jacek, Nagaratnam, Vidhya, Mukherjee, Smitangshu, Kirby, Sue, Arnold, Glenn, Bendel, Daniel, Boynton, Claire, Carvell, James, Carver, Anthony, Clayton, Matt, Desai, Keyury, Fadhlillah, Fiqry, Georgiou, Christiana, Jayakumar, Vineetha, Jeanes, Lara, Jhugursing, Mhairi, Jose, Jasmine, Karsten, Emma, Kormendy, Flora, Lewis, Stephanie, Lloyd, Dafydd, Mautadin, Francisca, McCahill, Claire, McInerney, Susan, Morland, Laura, Morsman, Elaine, Nayee, Sunny, O'Callaghan, David, Pickford, Emily, Pratap, Bhavesh, Rao, Chandana, Shah, Alka, Smith, Stephen, Smyth, Claire, Souleimanova, Icel, Templeton, Maie, Upadhyaya, Kavita, Uren, Sophie, Voralia, Shree, Wilson, Rebecca, Kushakavsky, Vlad, Ang, Justin, Beeby, Debroah, Bell, Stephanie, Boys, Helen, Brixey, Sue, Chabo, Cathleen, Cubitt, Lynsey, Dawson, Maggie, Finch, Jenny, Lewis, Robert, Purewal, Bally, Pyae, Kaung, Ramsey, Judi, Scoones, Ben, Debreceni, Gabor, Tarin, Obaid, Zondo, Nicola, Bothma, Pieter, Carmichael, Jack, Ferreira, Teresa, Goffin, Kelly, Gurung, Sarada, Kundu, Ashish, MacLennan, Sarah, Murray, Theresa, Verma, Karan, Wilson, Graeme, Winthein, Aleinmar, Jakkampudi, Satyanarayan, Ahmed, Muneeba, Baines, Duncan, Beirnes, Charmaine, Braybrook, Chrissy, Fernandez, Olga, Gracey, Jayshree, Guha, Snehasish, Jain, Arihant, Krishnaiyan, Raghavendran, Moody, Thomas, Novaga, Jo, Tait, Frances, Tate, Jemma, Taylor, Jennifer Claire, Waldron, Molly, White, Sonia, Gupta, Anish, Botfield, Claire, Ahmed, Mohamed, Ashton, Lizzie, Bailey, Andrew Robert, Banugo, Pele, Birch, Sian, Boyle, Henry, Brown, Alice, Chen, Mark, Connolly, Lucy, Dalal, Viral, Edwards, Alexandra, Elnour, Shaima, Faccini, Timothy, Floyd, Theodore, Georgiou, Thomas, Gill, James, Hedley, Russell, Hopkins, Philip, Kumar, Roshmi, Michell, Alice, O'Shaughnessy, Rhiann Marie, O'Sullivan, Laura, Pai, Seema, Parsons, Benjamin, Peltola, Laura, Penhaligan, Beth, Place, Merate, Ramsden, Jonathan, Ratnayake, Gamunu, Shammas, Kathy, Watts, Ali, Williams, Thomas, Woodham, Valantine, Puranik, Sarang, Crooks, Jennifer, Dean, Ania, Honstvet, Chris, Hunter, Katherine, Steynberg, Sarah, Swain, Andrew, Laha, Shondipon, Bonner, Alex, Doyle, Donna, Fallon, Robert, Verlander, Mark, Williams, Alexandra, Yardley, Richard, Whiteley, Simon, Ahmed, Zaid, Child, Ossian Aukland, Black, Sheila, Calderwood, Jamie, Chapman, Andy, Collin, Robert, Dwornik, Kinga, Gallagher, Kate, Gardener, Michelle, Harrop, Gareth, Hart, Peter, Howcroft, Clare, Ilyas, Carl, Kempanna, Umakanth, Krishnamurthy, Gnanshree, Kumara, Paramesh, Loh, LI Lian, Morgan, James, Pipe, Jonathan, Sathiapillai, Anand, Stones, John, Wilby, Elizabeth, Shephard, Buzz, Agarwal, Manju, Bolonenkova, Tatyana, Dunlop, Lisa, Duraisamy, Karthick, Kelly, Jenna, Nurmi, Eveliina, Patel, Mitul, Perry, Jonathan, Prior, Charles, Reece-Anthony, Rosie, Rose, Bernd Oliver, Rowland, Katie, Van Ross, Jennifer, McNamara, Helen, Permall, Natasha, Robertson, Gillian, Siew, Sarah, Smith, Amy, Spearritt, Sue, Verma, Dipali, Williams, Rhys, Zaidi, Suhail, Clayton, Samantha, Goddin, James, Joy, Stuart, Malhotra, Vikram, Mindel, Samuel, Neilson, Zoe, Wijesuria, Shanelle Tharuka, Wilkins, Ryan, Mukherjee, Kirtida, Bradley, Andrew, Coetzee, Samantha, Crook, Alexandra, Emeakaroha, Eunice, Frenkiel, Marek, Hatton, Tom, Kamraj, Kootharajan, Long, Natalie, Manikundalam, Badrinath, Peiris, Muditha, Roche, Matthew, Sandhu, Banher, White, Nichola, Woods, Annette, Yarnold, Adam, Price, Nicolas, Ashe, Marion, Disney, Tom, Dixon, Caroline, Dodds, Emily, El-Sheika, Sarah, Hameed, Yasir, Jones, Rob, Kanal, Karan, Ranaweera, Sanjeewa, Ripoll, Simon, Russell, Nicki, Smith, Sally Anne, Tung, Swee Ang, Emerson, Bruce, Apps, Victoria, Austin, Mandy, Catchpole, Laura, Catley, Christine, Child, Jenny, Cranmer, Karen, Dawson, Lizzie, Farr, Beth, Gerrish, Helen, Gibson, Sian, Gunn, Jacqueline, Holland, Kim, James, Lorri, Jayasekera, Dushyanthi, Lester, Yvonne, Lyle, Amanda, McNeela, Fiona, Oborska, Aneta, Pennington, James, Perkins, Lauren, Robinson-Perrie, Hollie, Shillito, Lauren, Singizi, Bryan, Smolen, Susan, Topliffe, Joanne, Vowles, Ben, Whybro, Natalie, Wijunamai, Amon, Willsher, Lucy, Wootton, Joanne, Varma, Sandeep, Atkinson, Philip, Buckley, Sarah, Darian, Thelma, Dhamaratne, Sachini, Gould, Richard, Graham, Laura, Hirst, Charlotte, Peeling, Andrew, Prentice, Saxon, Rajasekar, Naresh, Rose, Alastair, Smith, Craig, Wilkinson, Kate, Stewart, Richard, Chevis, Chrissie, Ekpa, John, Greig, Nurse Sara, Hinch, Nurse Rebecca, Holder, Carole, Makris, Nikolaos, Moran, Nurse Louise, Padilla Harris, Nurse Cheryl, Scarletta, Nurse Diane, Smith, Jeanette, Sara-Beth Sutherland, Nurse, Turner, Joanne, Valentine, Peter, van Manen, Amelia, Walia, Nurse Sonia, White, Nurse Charlotte, Wilson, Georgina, Wren, Nurse Lynn, Wright, Nurse Francesca, Faulds, Matthew, Agius, Claire-Marie, Ahmed, Raheel, Ahmed, Sameer, Alva, Arjun, Bird, Rachael, Buckley, David, Calder, Verity, Clark, Caroline, Craven, Emily, Cullen, Katherine, Davis, John, Diamond-Fox, Sadie, Doherty, Helen, Dutta, Bhaskar, Fortune, Jonathan, Gatehouse, Alexandra, Gibson, Jane, Hay, David, Hillier, Steve, Hindmarch, Paul, James, Michael, Keshvara, Kiran, Kotur, Karuna, Lawley, Peter, Lochanie, Nimali, Macbeth, Lisa, Madhu, Yamuna, Marcangelo, Sam, McShane, Lesley, Morgan, Amy, Mowat, Stephen, Nelson, Joshua, O'Leary, Denis, Partridge, Jennifer, Pearson, Janaki, Poulton, Tom, Prasad, Sneha, Protheroe, Kay, Qureshi, Adnaan, Rangaswamy, Girish, Richardson, Victoria, Scott, Carmen, Smallshaw, Karen, Soliman, Abdelrahman, Soulsby, Graham, Wahed, Anna, Walker, Iain, Welch, Sarah, Wilson, Jessica, Winkley, Elaine, Womack, Jonathan, Mitchell, Joellene, O'Brien, Peter, Callaghan, Debbie, Clarke, Ruth, Foggo, Graeme, Gilmour, Danielle, Hickey, Stephen, Hii, Stephanie, Livingstone, Susan, McAtear, Megan, Meehan, Sharon, Milne, Gemma, Small, James, Williams, Dewi, Jardine, Catherine, White, Graham, Wright, David, Hunter, Katie, Fleming, Gillian, Marc Hastie, P.A.-A., Hunter, Catherine, Lockhart, Jennifer, Reid, Kirsten, Robb, Hilary, Harten, Johann, Crooks, Barbara A., Ratnasabapathy, Urmila, Staber, Manfred, Pettigrew, Tom, Varveris, Daphne, Brett, Michael, Appleton, Richard, Briskoe, Michael, Brown, Graeme, Brown, Stewart, Christie, Fiona, Coady, Guy, Cowan, Richard, Drysdale, Alice, D'Sylva, Stewart, Edgar, Paul, Finnie, Graeme, Gardner, John, Gupta, Shub, Hall, Colin, Hamilton, Jane, Hunter, Laura, Ikram, Umairali, Imrie, Gregor, Kerr, Euan, Kinsella, Michael, Kommer, Maya, Lafferty, Brian, Lochrin, Christopher, Lovejoy, Tom, Loy, Maria, MacLean, Aillison, MacPherson, David, Marshall, Cara, Mawhinney, Ruth, McAteer, Claire, McCaul, Prof James, McCusker, Michael, McDowall, Katherine, McGovern, Christopher, Mckie, Stewart, Morrison, Melanie, Mulla, Suleman, Neale, Elizabeth, Niciu, Cristina, Ong, Su Ying, O'Sullivan, Finbar, Parcell, Sophie, Ramsay, Sarah, Robson, Rebecca, Roy, Nithin, Samuel, Jasmine, Scotland, Gemma, Sharma, Natasha, Slade, Kate, Soosay, Alvin, Soulsby, Charlotte, Steuart, Lois, Stevenson, Sara, Sweeney, Laura, Tan, Kerwei, Taylor, Calum, Th'ng, Francesca, Thompson, Caroline, Wardlow, James, Watson, Martin, Williams, Robin, Woodier, James, Young, Simon, Robinson, David, Howes, Jacqueline, Berwick, Scott, Boyle, Andrew, Brown, Neil, Celnik, Anna, Coleman, Alistair, Elwkhiee, Mohamed, Fernandes, Mario, Hanlon, Katie, MacLean, Sarah, Morgan, Rhian, Edgar, Jonathan, Chapman, Roddy, Razouk, Khaled, Atrah, Ali, Bhat, Sunny, Bramma, Yvonne, Campbell, Euan, Campbell, Rachel, Cormack, Anna, Dalchow, Stephan, Dodd, Ammy, Ferguson, Laura, Ferraioli, Donna, Hynd, Moyra, Janeczko, Adam, Jeffrey, Sally, Kinsey, Tony, Kummur, Yuvaraj, McIntosh, Karen, McKenna, John, Mclaughlin, Maria, Millington, Ryhs, Murphy, Emma, Parker, Kris, Reevell, Tom, Robertson, Fiona, Shankey-Smith, Will, Slorach, Colum, Szelei, Tamas, Warnock, Geoff, Watson, Stuart, Alston, Peter, Geddes, Murray, McLellan, Stuart, Allen, Eireann, Birnie, Karen, Brown, Kirsteen, Critchley, Julia, Cullen, Margaret, Eros, Alex, Forbes, Callum, French, Helen, Hall, David, Hetherington, Jonathan, Kellner, Maximiliane, Kelly, Keith, Khaled, Hiba, Mantle, Damien, McLenachan, John, Midgley, Susan, Nimmo, Susan, Ordys, Bart, Phelan, Hannah, Roddam, Philip, Shaw, Louise, Smith, Carolyn, Steel, Elizabeth, Stuart, Robert, Sturrock, John, Waite, Alasdair, Waterson, Fraser, Watson, Hannah, Wood, Elizabeth, Schraag, Stefan, Boyd, Elizabeth, Jain, Surabhi, Matthews, Elaine, Rappai, Geejo, Barr, Catriona, Stewart, Michael, Christie, Sharon, Smith, Tim, Arrow, Kate, Austin, Pauline, Chapman, Susie, Little, Jonathan, Malein, William, Sadler, Amy, Younger, Rhona, Reavley, Caroline, Allan, Katy, Ashok, Vignesh, Boroojeny, Ayda Borjian, Cutts, John-Paul, Faulds, Fiona, Fernie, Mark, Gadre, Amit, Gately, Tom, Haddon, Richard, Induruwage, Lalani, King, Siobhan, Liddle, Sian, Mallett, Paul, Mehotra, Saurabh, Ali, Inthekab Mohammed, Morris, Rachel, Nunn, David, Ferraro, Rocio Ochoa, Padhi, Pulak, Prusack, Ewa, Quak, Edmund, Singleton, Georgina, So, Kin, Stolady, Daniel, Welch, Drew, Whitear, Michael, Wilkinson, Kathy, Wu, James, Yusaf, Alex, Kakodkar, Prashant, Ghoneim, Hoda Abou, Balliston, Sara, Dudgeon, Lucy, Idris, Muna Elsheikh, Karattuparambil, Juneenath, Nanda, Lohita, Raithatha, Bhavesh, Saad, Mahmood, Spimpolo, Jenny, Titinchi, Linda, Wilson, Julie, Winstone, Ulrika, Martindale, Sarah, Cameron, Ewen, Fenner, Lynn, Hartford-Beynon, Jake, Mooney, Iain, Mundy, Charlotte, Rhidian, Rhys, Scutt, Sophie, Todd, Anna, Graham, Fiona, Ashton, Amy, Cooper, Theresa, Davidson, Katherine, Eapen, Suresh, Crowther, Hannah, Hindmoor, Claire, McSkeane, Anna, Mostafa, Mahamed, Mudimadagu, Gururaj, Rice, Polly, Wilson, Antoinette, Henry, Garry, Hollister, Nigel, Hunt, Jane, Isaac, Amanda, Morris, David, Paredes-Guerra, Antonio, Pass, Katherine, Paul, Martin, Rait, Kiran, Rousseau, Guy, Shacklock, Emma, Skinner, Amanda, Stancombe, Lucia, Thomson, Laura, Nutt, Christopher, Wright, Geoffrey, Holland, Johnny, O'Neill, Orla, Sengottaiyans, Arun, Mitra, Atideb, Garg, Sanjeev, Adams, Jonathan, Aiyedun, Temitope, Ali, Hani, Biuk, Sahar, Bond, Bryany, Cheeseman, Michelle, Clayton, Mark, Cottam, Lisa-Jayne, Dent, Kathy, Evans, Elizabeth, Evans, Sandra, Goodhand, Hannah, Green, Karen, Hatton, Jonathan, Hill, Joanne, Hutchinson, Dorothy, Jacob, Shibu, Joseph, Renjith, MacNally, Laura, Mann, Jason, McTaggart, Virginia, Newton, Maria, Pearson, Sandra, Rayet, Jaspreet, Saunders, Rebecca, Saxena, Sandeep, Venkatesh, Hemamangala, Whotton, Nikita, Ezihe-Ejiofor, Ada, Barot, Hemangini, Bridger, Hayley, Elhallous, Shady, Ghafoor, Rizana, Manhas, Vitul, Patil, Tanmay, Sadavarte, Nitin, Tharmalingam, Bhamini, Pritchard, David, Bage, Jean, Higgin, Sarah, Krishnaier, Asokan, Neilly, Esther, Rayappu, Sean, Siaw, Chye, Songaile, Ilma, Standen, Peter, Suresh, Narayanan, Weston, William, Williams, Lynne, Yuchen, Jiang, Alagar, Ravi, Taylor, Adrian, Matata, Claire, McCrossan, Roopa, Robertson, Andrew, Shekar, Priya, Stoker, Wendy, Turnbull, Elizabeth, Watkinson, Clare, Worthy, Stephen, Yates, Bryan, Ignatov, Dancho, Davies, Matthew, Abdu, Ayman, Banni, Donata, Bowyer, Helen, Brooks, David, Buhmann, Ulf, Christenssen, Victoria, Collins, James, D'Sa, Aaron, Forde, Steven, Groves, Alice, Hosahalli, Jyothi, Hunt, Lauren, Koshy, George, Lee, Robyn, Martin, Susan, McKnight, Angus, Murphy, Piers, Nash, Henry, Nkanang, Bassey, Oracki, Pamela, Pauley, Tara, Pope, Alan, Samanta, Romit, Sgardelis, Panagiotis, Stocks, Tom, Vaitheeswaran, Sivaprakash, Verma, Priya, Vrazhalska, Madlena Ivanova, Weisz, Mike, Moppett, Iain, Arunachalam, Subha, Begum, Zorba, Bhangu, Sonia, Bown, Gemma, Chana, Avninder, Chhaniyara, Puja, Constable, Natalie, Delme, Luff, Fenner, Helen, Griffith, Oliver, Hackett, Stephen, Hewson, David, Inkpin, Kristofor, Jones, Richard, Kirkdale, Richard, Lyons, Ian, Mandal, Arnab, Mehrotra, Prerna, Murphy, Martin, Pearce-Smith, Alison, Priestley, Martin, Pyke, Shirley, Rasoli, Sonia, Sharma, Suneal, Squires, Gemma, Tsim, Peter, Veitch, Jonathan, Bond-Smith, Giles, Kay, Olivia, Siviter, Richard, Allen, John, Baxter, Linden, Beer, Sally, Bernardo, Mariana, Coles, Holly, Cudlip, Jo, Devries, Talitha, Duggleby, Phil, Espinosa, Alexis, Fitzgibbon, Karina, Galente, Joao, Georgiou, Domonique, Ghosh, Soumi, Hingley, Nicholas, Kingan, Ryan, Levett, Chris, Martinez, Jose, Mattin, Alex, Moore, Anna, Morrish, Samuel, Nash, Amy, Patel, Tejuswi, Roe, Cieron, Thwaites, Victoria, Wali, Anuj, Watterson, Dafydd, Charlotte Yates, Anna Wilson, Gimenez, Marc, Boltres, Anita, McClean, Rebecca, Papadopoullos, Sam, Teh, Elena, Webb, Stephen, Brammar, Andrew, Humphreys, Joanne, Alibhai, Moiz, Alston, Daisy, Cohen, Jolyon, Coleman, Laura, Davies, Simon, Dervin, Dionne, Dooley, Rebecca, Drummond, Andrew, Findlay, Douglas, Fleming, Naomi, Hammoud, Yazzim, Hussain, Sanniah, Irwin, Katy, Javed, Asad, Kent, Linda, Lock, Lorraine, McSorland, Denise, Meadows, Alison, Mulligan, Paula, Nichols, Wendy, O'Callaghan, Maria, Ogor, Jonathan, Poole, Joanna, Ryder, Geoffrey, Shakoor, Akmal, Teo, Wei, Minto, Gary, Adshead, Stephen, Anderson, Helen, Carpenter, Adam, Clelland, Stuart, Datar, Priya, Elloway, Esme, Holl, Matt, Hulbert, Aidan, Humphreys, James, Hyams, Ben, McAleer, Sam, Newmarch, Mary, Notman, Holly, Patrick, Abigail, Perham, Anna, Pitman, Catherine, Reed, Fiona, Sampson, Paul, Smith, Hannah, Spinney, Sam, Toms, Nina, Warrener, Tim, Girgis, Michael, Barcraft-Barnes, Helena, Camsooksai, Julie, Colvin, Carolyn, Davies, Jack, Hamilton, Alex, Linton, Fiona, Nussbaum, Greg, Patch, Sarah, Simpson, Diane, Tbaily, Lee, Bain, James, A'Court, Alicja, Barr, Emma, Blethyn, Kate, Craig, Thomas, Cutler, Hugh, Davies, Jenny, Fry, Rebecca, Hawes, Elizabeth, Jenkins, Nicholas, Knight, Martin, Restall, David, Stubbs, Matthew, Sutherland, Angus, Swarbrick, Claire, Wilson, Robin, Winwright, Paul, Hamilton, Kevin, Adams, Anne, Allen, Orlanda, Boampomaa, Marilyn, Boniface, Anna-Marie, Coe, Robert, Daniel, Amelia, Finn, Joanne, Gill, Issac, Griffiths, Huw, Hackney, Joanna, Han, Ruth, Hare, Edward, Rintoul, Edward, Shpuza, Ervin, Smith, Ruth, Staines, Nikki, Suppiah, Puvan, White, Tracey, Pearson, Darcy, Cracknell, Ben, Farrell, Nadine, Hermanowski, Jane, Hodgson, Ruth, Hoskins, Toby, Jones, Rhiannon, Keable, Sam, Rosbergen, Melissa, Giles, Julian, Dawes, Thomas, Green, Ben Eden, Pottinger, Gail, Weller, Debbie, John, John, Burgess, Lisa, Denton, Jean, Done, Alaine, Edwards, Jayne, Garrett, Theresa, Gilla, Rajesh, Griffith-Norris, Samantha, Jones, Teresa, Linklater-Jones, Barbara, Nicholas, Claire, Owen, Sara, Perkins, Charlotte, Rowlands, Tessa, Steen, Julie, Turner, Sarah, Wales, Johanna, Woolley, Carol-Ann, Hormis, Anil, Collier, Dawn, Dixon, Kathryn, Gardner, Michael, Murray, Vicky, Soar, Harry, Walker, Rachel, Yaruk, Shifa, Yarwood, Daniel, Dill-Russell, Patrick, ruthy Arumugam, Bird, Georgina, Bleasby, Nichola, Chater-Lea, Peter, Craig, Emma, Davies, George, Foxton, Julie, Gilfillan, Helen, Jerram, Keelan, Kudsk-Iversen, Søren, Lee, Rebecca, Livesy, John, Mohabir, Amanda, Morris, Katherine, Raffles, Mike, Smith, Annika, Wang, Huiqi, Craig, James, Barratt, Nina, Bates, Andy, Bokor, Norbert, Cranshaw, Julius, Dominguez, Sergio, Fraine, Annette, Green, Richard, Molloy, Katie, Penny, Christina, Pitts, Sally, Purandare, Laura, Rabbi, Taslima, Serrano, Monica, Stoycheva, Tina, Vamplew, Luke, Williams, Steve, Berry, Julian, Adams, Benita, Bean, Sarah, Burt, Karen, Devooght-Johnson, Nicki, Hammonds, Fiona, Nicholls, Tom, Rowe, Michelle, Summers, Jessica, Ward, Olivia, Wroath, Belinda, Young, Gabbie, Matthews, Cathryn, Crosbie, Gearoid, Dunn, Alex, Eddy, Sara, Garcia, Lynda, Garwood, James, Green, Adam, Gupwell, Karin, Jones, Nicola, Marriott, Suzie, Masood, Mohammad, Mazzola, Francesca, McEvoy, Evanna, Ng, Yang, Park, Linda, Pauling, Stephanie, Potter, Alison, Renton, Caroline, Samways, Adam, Sibley, Pauline, Stead, Jenny, Thorpe, Kevin, Turner, Elizabeth, Walter, Michelle, Windsor, Kevin, Jha, Rajeev, Hooker, Nicolas, Kidel, Carlos, Abayalingam, Mayavan, Boulding, Richard, Coakley, Philip, Elahi, Noor, Helder, Filipe, Hilton, James, Joshi, Kunal, Kaur, Rupinder, Male, Victoria, Naji, Saqib, Pinto, Manuel, Rajendran, Yohinee, Save, Manjeet, Smith, Megan, Spence, Emily, Tang, Sophie, Urwin, Thomas, Wittenberg, Marc, Yan, Ruoling, Williams, Colin, Ardeshna, Arjun, Bamford, Peter, Hagyard, Sarah, Johnson, Patrick, McMonagle, Martina, Morris, Hayleigh, Murphy, Thomas, Papadopoulos, Stavros, Simpson, Emma, Smith-Williams, Jonathan, Vyapury, Vin, Juneja, Rohit, Black, Ethel, Eeles, Alex, Elliot, Justine, Jhanji, Shaman, Knoetze, Reynard, McCanny, Jamie, Oswald, Lauren, Roderick, Ellie, Gunning, Paul, Siddaiah, Narendra, Balachandar, Krishna, Bhimarasetty, Chandra, Bird, Laura, Blunt, Conny, Da Silva, Egidio, Darbyshire, Mark, Echaveznaguicni, Irene, Girgis, Youssef, Goodman, Martin, Gowda, Dinkar, Gowni, Rajashekar, Hayes, Melony, Jackson, Natalie, James, Anitha, Jayapal, Rekha, Jones, Claudette, Leung, Enid, Minhas, Simran, Mubarak, Mona, Muniyappa, Sudeshkumar, Nassa, Zehrin, Neal, Tom, Nyangoni, Kudakwashe, Panchakshariah, Suresh, Philpott, Bethany, Pinner, Craig, Pygall, Daniel, Rangaiah, Manamohan, Rao, Anil, Rea, William, Shellard, Richard, Shinner, Guy, Sutherland, Tony, Tharakan, Liza, Thomas, Sue, Travasso, Betty, Venkatesh, Pyda, Wortley, Dionne, Dickinson, Matthew, Benoliel, Sophie, Doyle, Nanci, Marriott, Cheryl, Martin, Sarah, Montague, Laura, Penhaligon, Kate, Saha, Rita, Santhirapala, Ramai, Suntharanathan, Lushani, Wakeford, Nichola, Webb, Carly, Winterbottom, Toby, Jordan, Lesley, Aldridge, Matt, Bolton-Hill, Clare, Cook, Prof Tim, Kangesan, Inthu, Kettley, Laura, Mew, Edward, Penketh, James, Quinn, Eleonore, Scholes, Sam, Uppugonduri, Sreekanth Rayalu, Allen, Lara, Lyndsay Bibb, Jill Brown, Busby, Charlotte, Katherine Cheshire, Davis, Matron Beryl, Denyer, Rebecca, Julie Edwards, Gardiner, Laura, Haque, Shamim, Icke, Julia, Jones, Katherine, Donna McIntosh, Mandy Oakley, Prasad, Linda, Victoria Roberts, Smallwood, Andrew, Tammy Smith, Stelfox, Lucy, Angela Stevens, Angela Willberry, Pratt, Oliver, Chincholkar, Mahindra, Darwin, Leanne, Dearden, Joy, Flowerdew, Adele, Harrison, Louise, Hartley, Robert, Ingham, Andrea, Jones, Ben, Lee, Stephanie, Longdon, Elizabeth, Marsden, Tracy, Meats, Kirsty, Michael, Angiy, Norwood-Green, Drew, O'Loughlin, Victoria, Owen, Holly, Patel, Manju, Perez, Jane, Whiston, Jessica, Wood, Andrea, Williams, Simon, Billingham, Chloe, Clarke, Caroline, Holmwood, Xantha, Knighton, Melba, Sands, Becky, Stevens, Paul, Strong-Sheldrake, Sophia, Taylor, Matthew, Rambhatla, Mrutyunjaya Rao, Brodier, Elizabeth, Choudhry, Ozerah, Choudhry, Usman, Fitzmaurice, Bethany, Hulme, Jonathan, Kannan, Santhana, Mak, Kay Anne, Namih, Miriam, Rajdev, Bharati, Rambhatla, Swetha, Reilley, Stuart, Rice, Rebecca, Sethia, Nalini, Smith, Katy, Wakhle, Rahul, Walmsley, Chris, Wrench, Ian, Agyemang, Michael, Bell, Elizabeth, Bird, Sarah, Briscoe, James, Cruickshanks, Andy, Drinkwater, Jake, Eggleston, Sam, Elms, Henry, Hammon, Laura, Harris, Meredith, Harrison, Christopher, Hirst, Claire, Housley, Kay, Kapoor, Krish, Kibutu, Faith, Kilner, Beverly, King, Emily, Kirk, Emily, Marshall, Esme, Mazzone, Paolo, Middle, Janet, Milner, Leanne, Mitchell, Adam, Morris, Becky, Mudd, Alexandra, Needham, Matthew, Nicholas, James, Penson, Rob, Perfitt, Joel, Pinkerton, Mark, Recto, Mayeth, Rehnstrom, Maria, Riley, Catherine, Ryan, Lorna, Smith, Jennie, Strong, Samantha, Thornley, Helen, Tookey, Bethany, West, Daniel, Whitaker, John, Willcock, Sarah, Willoughby, Shay, Wright, Jane, Jones, Paul, Abbott, Riquella, Bacon, Lisa, Godden, Christopher, Howe, David, Loughlin, Angela, Moore, Helen, Passey, Samuel, Rodgers, Rebekah, Foley, Paul, Hagan, Samantha, Marcus, Simon, Gardner, Irene, Haslam, Zena, Morrison, Moira, Obeysekera, Chai, Porter, Kim, Terrett, Helen, Henning, Jeremy, Baillie, Kirsty, Buchanan, Ella, Cain, Martyn, Colling, Kerry, Duarte, Raquel, Gibb, Chris, Hynd, Ryan, Irvine, Victoria, Lyons, Rob, Middleton, Karoline, Razaque, Usman, Sheikh, Faisal, Tabiner, Tariq, Frey, Christian, Brown, Carly, Clifford, Gayle, McKee, Madeleine, Stidolph, Beverley, White, Emert, Campbell, Bridget, Mason, Sophie, Parsons, Penny, Santana-Vaz, Natasha, Stagg, Camilla, Shah, Nirav, Barnes, Veronica, Bedoes, Penny, Clarke, Jonathan, Crichton, Robert, Das, Madhurima, Davies, Paul, Farrah, Helen, Hegarty, Aoife, Howlett, Luisa, Kleine-Brueggeney, Maren, Ma, Samson, Marsh, Veronica, McAndrew, Katherine, Mellinghoff, Johannes, Oscier, Christopher, Ryan, Christine, Smee, Elizabeth, Thurairasa, Dushanthi, Goel, Vandana, Adeney, Christopher, Behl, Sanjay, Chadwick, Karen, Coleman, Thomas, Davies, Claire, Dealing, Sharon, Elwood, Jamie, Fadden, Emma, Gillies, Stella, Kennedy, Tom, Miller, Thomas, Morton, Simon, Reilly, Rebecca, Smyth, Sue, Syratt, Thomas, Welfare, Emma, Thomas, Elizabeth, Awolesi, Jennifer, Bennett, Hannah, Bradshaw, Elizabeth, Crabtree, David, Duraman, Lauren, Hughes, Kerry, Kirk, Sarah, Leonard, Dee, Stoeter, Rachel, Parrington, Simon, Andorka, Matyas, Ang, Kingsin, Bailey, Linda, Brooks, Stephanie, Chiu, Oon, Collins, Sally, Jack, James, Knight, Harry, Lynn-Smith, Anastasia, Mackenzie, Matt, Maher, Sarah, Nimako, Louise, Sangaralingham, Siva, Sanusi, Seliat, Weller, Samantha, Willard, Elizabeth, Kulkarni, Anand, Carroll, Peter, Clark, Martyn, Coulding, Martina, Denman, Elizabeth, El Habishi, Mohyman, Haywood, Patrick, McConniffe, Jane, McCormick, Jacqueline, Melachuri, Krishnakar, Philip, Evelyn, Ridgway, Stephanie, Savill, Heather, Sharif, Kamal, Vere, Joanne, Harris, Stephen, Coombs, Alex, Darch, Flora, Doble, Patricia, Foot, Jayne, Gillett, Chris, Judd, Thomas, Moss, Alison, Pawley, Corinne, Tait, Moira, Whitcher, Alison, Wood, Natalie, Montgomery, Jane, De Selincourt, Gabrielle, Fitzell, Pauline, Flower, Katie, Horan, Kathleen, Hulance, Bianca, Mercer, Pauline, Shaw, Sarah, Webber, Robin, Kakkar, Manish, Joachim, Suganthi, Aggarwal, Seetal, Ali, Amr, Ang, Boon, Bhardwa, Vishnu, Deamer, Wendy, Filby, Lorna, Fletcher, Jo, Fombon, Felix, Gawley, Shannon, Gosavi, Chandrakant, Hindle, Julia, Lawrence, Tara, Maher, Robert, Moore, Samantha, Netherton, Kimberley, Orasanu, Teodora, Poimenidi, Evangelia, Potter, Louise, Ranasinghe, Niyesa, Ribeiro, Lester, Ruth, Thoy, Butler, Susie, Sutton, Tim, Thomas, Issy, Veluvolu, Divya, Walker, Thomas, Wariyapola, Charindri, Zaheer, Lail, Luoma, Valpuri, Ferguson, Catriona, Stewart, Adrienne, Bapat, Smita, Bose, Gahan, Bugo, John, Campbell, Marta, Cervi, Elizabeth, Ciechanowicz, Sarah, Coathup, Rachel, El-Wahab, Niveen, Frith, Claire, Gill, Preea, Gray, Martin, Luoma, Astri, Mehta, Sachin, Murali, Mayur, Mussad, Asya, Parker, Laura, Patch, Josh, Perella, Paolo, Robson, Emily, Setty, Thunga, Vieira, Filipe, Wall, Josh, Witby, Jon, Zghaibe, Wael, Zhang, Sheldon, Merron, Stephen, Abano, Nenette, Barnett, Loretta, Barry, Adrian, Birks, Pamela, Brade, Judith, Butler, Adrian, Carpio, Racquel, Colclough, Viv, Eaton, Katrina, Edwards, Carol, Emery, Lisa, Finney, Kay, Gallagher, Susan, Ghatge, Satyajeet, Grocott, Jeanette, Hall, Amanda, Hardwick, Alison, Harrison, Anne, Hendy, Susan, Hiden, Joanne, James, Alex, Jeganath, Vijay, Kumar, Rahul, Lord, Stephen, Lovatt, Rachel, Lyjko, Susan, Maguire, Holly, Marsden, Mia, Mehta, Venu, Mishra, Rajeev, Mittal, Rohit, Moores, Andrew, Nalwaya, Pramod, Omeara, Matthew, Orosz, Sandor, Patel, Nehal, Pattison, Nicola, Ponce, Ida, Puttapa, Ashok, Rajamanickam, Tamilselvan, Rao, Nagaraj, Remegoso, Alda, Rhodes, Rochelle, Rooney, Angela, Sadler, Emma, Singh, Permendra, Soon, Wai, Tomlins, Simon, Umbarje, Kanchan, Vallabhaneni, Murali, Varquez, Resti, Wain, Jill, White, Sorana, Willetts, Elizabeth, Williams, Benedict, Wood, Andrew, Washington, Stephen, Anipindi, Sujata, Aston, Jennifer, Bradley-Potts, Joanne, Butler, Ian, Cunningham, Jennifer, Duncan, Alastair, Garrard, Hywel, Haslam, Daniel, Kirk, Danielle, McCormick, Richard, McEvoy, Michael, Mistry, Sara, Ormandy, Danielle, Sharp, Tracy, Song, Andrew, Williamson, Georgina, Young, Francis, Tasker, Laura, Bailey, Elizabeth, Baker, Roisin, Bamford, Amy, Bergin, Colin, Blackburn, Julia, Bodo, Kinga, Carrera, Ronald, Cooper, Lauren, Despy, Liesl, Ellis, Karen, Foster, Morgan, Garner, Sharon, Harkett, Lyndon, Harkett, Samantha, Ip, Peter, Lay, Frances, Liu, Hon Sum, Mee, Laura, Nazir, Samir, Osbourne-Wylde, Jacob, Patel, Krupali, Pope, Martin, Reeves, Emma, Sahni, Melanie, Small, Charlotte, Spooner, Brendon, Spruce, Elaine, Whitehouse, Arlo, Wharton, Nicholas, Alexander, Rachel, Ashford, Amy, Aspinall, Rebecca, Bateman, Richard, Bell, Matthew, Bennett-Britton, Jennifer, Bewley, Jeremy, Blanshard, Hannah, Bourdeaux, Christopher, Brook, Peter, Cain, Helen, Cameron, Claire, Cassells, Naomi, Chauhan, Nilesh, Clarke, Adrian, Cockroft, Melanie, Cohen, Alan, Collins, Joanna, Cominos, Timothy, Craven, Rachael, Davies, Ian, Dolling, Sarah, Dowse, Claire, Driver, Kate, Duffen, Adam, Dunn, Sarah-Jane, Earnshaw, Charlotte, Forrest, Frances, Freshwater-Turner, Dan, Gardner, Issie, Gibbins, Matthew, Gibbison, Ben, Gleeson, Suzanne, Gould, Timothy, Govier, Matthew, Gupta, Benjamin, Hadfield, John, Harvey, Nicola, Henderson, Sophia, Herbert, Lara, Hillier, James, Hood, Elizabeth, Howes, Ben, Howes, Helen, Hughes, Sian, Jackson, Kathryn, Jacobs, Toby, Jenkins, Emma, Jenkins, Ian, Johnstone, Alistair, Jones, Lydia, Jones, Rebecca, Joshi, Natasha, Kamalanathan, Kajan, Kellie, Neil, Kidd, Lawrence, Kinsella, Mike (Stephen), Knight, Thomas, Leslie, Rebecca, Linter, Stephen, Lovell, Tim, Martin, Matthew, McHugh, Ursula, McIndoe, Andrew, McKendry, Rachel, Middleditch, Alexander, Miles, Edward, Milne, Lesley, Molyneux, Mat, Muchatuta, Neil, Murphy, Ruth, O'Higgins, Fran, Oglesby, Kieran, Pachucki, Marcin, Paoloni, Claudia, Patel, Nishita, Patton, Catherine (Katie), Paulich, Skylar, Pearson, Annabel, Pickering, Anthony, Platt, Martin, Pope, Charlie, Pryn, Steve, Ranjan, Amit, Rasburn, Neil, Ray, Andrew, Rivers, Jonathan, Rooney, Kieron, Ryder, Ian, Sanders, Sarah, Sasi-Kumar, Kavita, Scott, Liam, Scrutton, Mark, Searles, Chloe, Self, James, Shah, Sanjoy, Sheils, Mark, Shipway, Toby, Short, Heather, Simmonds, Lauren, Smith, Daniela, Soodan, Anjali, Steeds, Charlotte, Sweet, Katie, Syme, Phoebe, Thomas, Matthew J., Tomkins, Sally, Underwood, Susan, Wagstaff, Adrian, Watson, Paul, Webster, Denise, Welham, Katie, Whaley, Anne, Williams, Helen, Wilson, Hannah, Winton, Anoushka, Woodward, Thomas, Worthington, Jeanie, Younie, Stuart, Bradbury, Carol, Auldin, Mohammad, Bosworth, Kate, Choksey, Falguni, Dudkowsky, Bernice, Elton, John, Evans, Gail, Grove, Charlotte, Ingram, Clare, Kelly, Andrew, Lax, Peter, Lynes, Elena, Madden, George, Mistry, Vinesh, Molitor, Timothy, Morgan, Catherine, Morris, Natalie, Pallister, Emily, Patel, Pooja, Ragothaman, Vijay, Ramm, Katie, Robinson, Ben, Sharma, Meghna, Shuttleworth, Daniel, Vaidyanath, Chandrashekhar, Warren, Jen, Wong, Rachel, Lau, Gary, Conway, Hannah, Majeed, Adeel, Parmar, Jaina, Rana, Meenal, Yusuff, Hakeem, Rimmer, Corinne, Abdelrhamen, Wael, Allison, Kathryn, Burns, Karen, Cahill, Nichola, Clark, Jon, Donaldson, Hannah, Heseltine, Nick, Mackenzie, Nicola, McArthur, Carol, Moreland, Neil, Shohelly, Sharmin, Thatcher, Hilary, Tran, Steven, Walker, Catriona, Al-Rawi, Samar, Wakatsuki, Mai, Aarvold, Alice, Addy, Melissa, Ashfield, Georgina, Beauchamp, Nigel, Belcher, Alex, Bennett, Tom, Burgess, Victoria, Burton, Andy, Campbell, Matthew, Cruikshank, Ross, Cumpstey, Andy, Davies, Rhys, Ford, Chris, Ford, Renee, Hawkins, Lesley, Hendra, Tim, Huttley, Thomas, Jolly, Erica, Kalcheva, Nevena, Kennedy, Charlie, Lees, Jessica, Lowe, Richard, Martindale, Tim, McCormick, Sarah, McPhee, Hannah, Millinchamp, Fran, Muddanyake, Rahul, Osorio, Eduardo, Patel, Kiran, Pestell, Samuel, Phillips, Steve, Plumb, Jamie, Pratt, Thomas, Quartermain, Bert, Reeves, Rebecca, Robin, Sophie, Scully, Thecla, Sehgal, Anamika, Seifalan, Said, Shuttleworth, Suzanne, Siddique, Omar, Sleap, Esme, Smith, Victoria, Snooks, Richard, Solanki, Virginia, Timmons, Christina, Trimble, Alice, Tunney, Doug, Walker, Kat, Wee, Naomi, Wigley, James, Wilkins, Huw, Wong, Hanna, Wood, Laura, Yogya, Dinithi, Young, Ruth, Shanbhag, Sumant, Ameer, Farrukh, Finnity, Jonathan, Haddock, James, Hunt, Alex, Kuravi, Aditya, Lenehen, Fionnuala, McOwat, Lindsay, Naqvi, Asad, Richardson, Lisa, Siddons, Victoria, Charters, Seema, Jumani, Deepa, Bradley, Peter, Bubb, Laura, Chan, Rebekah, Connell, Lynne, Crone, Rachel, Davis, Hannah, Defeyter, Pascal, Evans, Alison, Howard, Ramdas, Prady, Helena, Rogers, Natalie, Roughley, Lindsay, Whittle, Helen, Zeinali, Daniel, Cherian, Vinanti, Latif, Muhammad Usman, Bajwa, Maqsood, Guy, Jonny, Guz, Krzysztos, Iftikhar, Nauman, Iwanicka, Beata, Khan, Mujeeb, Love, Anna-Marie, Montgomery, Celia, Mulvany, Stephen, O'Kane, Emma, O'Kane, Sinead, Siddiqui, Mansoor, Small, Cathal, Subhani, Shaik, Dana, Emily, Kennedy, Richard, Amey, Isobel, Ashton, Hilary, Baird, Yolanda, Bushell, Caroline, Chadbourn, Indra, Cohen, Merle, Finlay, Emma, Gilbert, Jeanette, Helm, David, Lewis, Carla, Macallan, Jenny, Margalef, Jordi, Martins, Nic, Metiu, Gabi, Moore, Sally, Rose, Hannah, Standley, Tom, Page, Valerie, Bakonyi, Tomas, Ben-Nathan, Simon, Claridge, Melanie, Evans, Jackie, Gardiner, Harriet, Kantsedikas, Ilya, Lachana, Ann, Makker, Ratna, Markwell, Karen, Merrill, Colin, Mukerjee, Prasun, O'Donohoe, Lynn, Oglesby, Fiona, Osbourne, Laura, Parker, Beena, Passaro, Emelia, Russell, Katherine, Shah, Sneh, Sundayi, Saul, Walker, Elaine, Zhao, Xiao, Hosdurga, Guru, Cotterill, Donna, Crowther, Nicola, Dymond, Harvey, Ratcliffe-Law, Thomas, Saunders, Glenn, Saunders, Thomas, Gopal, Vijayakumar, Ahmed, Sajjad, Ali, Abdalla, Crawford, Sarah, De'Ath, Clare, Humphreys, Sally, Swanevelder, Carin, Yap, Yeng, Silk, Jane, Adeniba, Rashidat, Armstrong, Richard, Egole, Osi, Fan, Karen, Gilbert, Kayleigh, Gould, Laura, Hickman, John, Long, Fei, Pahary, Sheik, Reichman, Michelle, Simpson, Kathryn, Singaravelu, Suresh, Ahmed, Dabeeruddeen, Brailsford, Fiona, Bridge, Laura, Collis, Lauren, Jacob, Reni, Jones, Cathy, Kirrage, Amanda, Lowe, Jessica, Mullen, Joanne, Prenter, Andrew, Sarao, Sarbpreet, Sharpley, David, Wankhade, Kavita, Persad, Cindy, Burtenshaw, Andrew, Blyth, Kate, Corcoran, Felicity, Davis, Caroline, Dolan, Rachel, Hussain, Nageena, Pearson, Emma, Pierson, Anna, Poyntz, Victoria, Thrush, Jessica, Wollaston, Alex, Wollaston, Julie, Clements, Paul, Biswas, Arindam, Clayton, Sarah, Clayton, Thomas, Cochrane, Naomi, Duell, Kirsty, Evans, James, Gaskell, Mark, Heaton, Dianne, Heaton, Linzi, Hill, Claire, Killen, Ruth, Latham, Sandra, McIntosh, Gemma, Moore, Chris, Parkinson, Val, Pemberton, Nicola, Robinson, Matthew, Sawyer, Alastair, Sykes, Isabelle, Taylor, Tracey, Tierney, Caroline, van de Snepscheut-Jones, Katja, Wade, Emily, Wahid, Mohammed, Wang, Henry, Williams, Claire, Wu, Dominic, Yadagiri, Manjula, Zabauski, Dmitry, Troth, Laura, Andrews, Eleanor, Bains, Ranjit, Beard, Laura, Birch, Janine, Britton, Rachael, Salmon, Mike, Vassell, Elizabeth, Kubisz-Pudelko, Agnieszka, Allen, Jamie, Allison, Joanna, Baird, Andrew, Gregory, Rob, Luckhurst, Hannah, Mairs, Rebecca, Marshall, Ben, Pippard, Lucy, Pitt-Kerby, Tressy, Savva, Andrew, Walkden, Graham, Weegenaar, Celly, Chandler, Ben, Kanakaraj, Muthuraj, Chamberlain, Andy, Dyer, Simon, Elliott, Kerry, Forshaw, Greg, Furness, Rosie, Gibson, Andy, Howe, Laura, Kent, Sarah, Rodgers, Alicia, Straughan, Ben, Temlett, Emma, Whitwell, John, Wong, D.J.N., Harris, S.K., and Moonesinghe, S.R.

Published
2018
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28. Spectrophotometric analysis of stochastic hybrid black silicon nanostructures for crystalline silicon photovoltaic cells

Author

Tyson, Jack James. and Tyson, Jack James.

Abstract

Black silicon nanotextures offer exceptionally low levels of reflectance and are of interest to the field of solar photovoltaics. The nanowires that form this texture create a graded refractive index, allowing light to be absorbed with high efficiency. Explored here is the application of these nanotextures on top of conventional microscale pyramids, combining the advantages forwarded by the latter, predominantly being a second chance for absorption, and the former, being light steering. These structures are known as hybrid black silicon. Variations on the wet chemical etch parameters are explored and related to topological features, which can, in–turn, be related to front surface reflectance. The hybrid black silicon textures created are shown to exhibit reflectance as low as 0.7%. An advanced hemispherical reflectometry system is reported, designed for measuring the optical characteristics of a variety of samples resolved against wavelength, angle of incidence, and polarisation. Variable angle reflectance data enables a new perspective on the interaction between electromagnetic waves and nanostructures, which do not interact with light in the same way as their microscale counterparts. The versatility of this data is demonstrated for photovoltaics when combined with geographic spectral irradiance data. Solar cell optical performance, when structured with the textures measured in the reflectometer, is successfully predicted should that cell be placed in Southampton, UK. This mathematical formulation is capable, alongside the appropriate angle–resolved reflectance data, of approximating the optical performance of a given sample when situated almost anywhere in the world. Supporting the reflectance data gathered through this work is a black silicon nanowire model, pseudorandomised using custom–made algorithms against a set of desired surface features. The model uniquely generates complex surface topologies that meet the requirements of electromagnetic wave optics simul

Published
2023

29. Garnet growth and mineral geochronology constrains the diachronous Neoproterozoic convergent evolution of the southern Dom Feliciano Belt, Uruguay

Author

Jack James Percival, Jiří Konopásek, Pedro Oyhantçabal, Jiří Sláma, and Robert Anczkiewicz

Subjects
Geochemistry and Petrology, Geology
Abstract

The Dom Feliciano Belt of southern Brazil and Uruguay represents part of a larger Neoproterozoic orogenic system formed during the amalgamation of Western Gondwana. The hinterland and foreland domains in parts of the belt preserve deformation structures and metamorphic assemblages that developed during early crustal thickening from c. 650 Ma. However, the metamorphic history of the southern foreland, in Uruguay, and its relationship with the hinterland, is not so well understood. We show that metamorphism in the southern hinterland is characterized by near-isothermal decompression from ~10 kbar (~770°C) down to ~6 kbar, reflecting exhumation from depths of ~40 km during convergent thrusting and crustal thickening. This metamorphic event and associated magmatism is constrained by garnet Lu–Hf and zircon U–Pb dating to c. 655–640 Ma, supporting age and P–T constraints from previous studies. In contrast, prograde metamorphism in the foreland supracrustal rocks reached maximum lower-amphibolite facies conditions (~6–7 kbar and ~550–570°C) and is constrained by garnet Lu–Hf dating to 582 ± 23 Ma. An exposed sheet of imbricated foreland basement rocks reached partial melting at upper-amphibolite facies conditions, and metamorphism is similarly constrained to c. 585–570 Ma by monazite U–Pb dating. The data indicate that metamorphism in the foreland occurred during a sinistral transpressional event c. 55–85 Ma after the start of crustal thickening recorded in the hinterland, whereby strain partitioning during sinistral transpression led to imbrication in the foreland and oblique thrusting of the basement over more distal supracrustal rocks. This event is coeval with transpressional deformation in the Kaoko and Gariep belts, indicating a distinct two-stage tectonic history driven by the three-way convergence between the Congo, Kalahari, and South American cratons.

Published
2023

31. U.S. Adolescent Alcohol Use and Best Practices to Provide Education and Resources to Mitigate Long-Term Complications: A Scoping Review Protocol

Author

Jack, James

Subjects
U.S. Adolescent Alcohol Use, Medicine and Health Sciences, Community Health and Preventive Medicine, Public Health
Abstract

To identify best practices in education and intervention to reduce the use of alcohol amongst adolescents in the United States to reduce the potential of long term health consequences.

Published
2023
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32. sj-docx-1-soe-10.1177_00380407231176541 – Supplemental material for The Social Structure of School Resource Disparities: How Social Capital and Interorganizational Relationships Matter for Educational Equity

Author

Bridwell-Mitchell, E. N., Jack, James, and Childs, Joshua

Subjects
Sociology, Education, FOS: Sociology
Abstract

Supplemental material, sj-docx-1-soe-10.1177_00380407231176541 for The Social Structure of School Resource Disparities: How Social Capital and Interorganizational Relationships Matter for Educational Equity by E. N. Bridwell-Mitchell, James Jack and Joshua Childs in Sociology of Education

Published
2023
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35. Regional anesthesia and enhanced recovery:We need more data

Author

El-Boghdadly, Kariem, Jack, James M., Heaney, Aine, Black, Nick D., Englesakis, Marina, Kehlet, Henrik, Chan, Vincent, El-Boghdadly, Kariem, Jack, James M., Heaney, Aine, Black, Nick D., Englesakis, Marina, Kehlet, Henrik, and Chan, Vincent

Published
2022

36. Role of regional anesthesia and analgesia in enhanced recovery after colorectal surgery:A systematic review of randomized controlled trials

Author

El-Boghdadly, Kariem, Jack, James M., Heaney, Aine, Black, Nick D., Englesakis, Marina F., Kehlet, Henrik, Chan, Vincent W.S., El-Boghdadly, Kariem, Jack, James M., Heaney, Aine, Black, Nick D., Englesakis, Marina F., Kehlet, Henrik, and Chan, Vincent W.S.

Abstract

Background: Effective analgesia is an important element of enhanced recovery after surgery (ERAS), but the clinical impact of regional anesthesia and analgesia for colorectal surgery remains unclear. Objective: We aimed to determine the impact of regional anesthesia following colorectal surgery in the setting of ERAS. Evidence review: We performed a systematic review of nine databases up to June 2020, seeking randomized controlled trials comparing regional anesthesia versus control in an ERAS pathway for colorectal surgery. We analyzed the studies with successful ERAS implementation, defined as ERAS protocols with a hospital length of stay of ≤5 days. Data were qualitatively synthesized. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. Findings: Of the 29 studies reporting ERAS pathways, only 13 comprising 1170 patients were included, with modest methodological quality and poor reporting of adherence to ERAS pathways. Epidural analgesia had limited evidence of outcome benefits in open surgery, while spinal analgesia with intrathecal opioids may potentially be associated with improved outcomes with no impact on length of stay in laparoscopic surgery, though dosing must be further investigated. There was limited evidence for fascial plane blocks or other regional anesthetic techniques. Conclusions: Although there was variable methodological quality and reporting of ERAS, we found little evidence demonstrating the clinical benefits of regional anesthetic techniques in the setting of successful ERAS implementation, and future studies must report adherence to ERAS in order for their interventions to be generalizable to modern clinical practice. PROSPERO registration number: CRD42020161200.

Published
2022

37. Is There an Association Between Untreated Hearing Loss and Psychosocial Outcomes?

Author

MS KNO, Brain, Jayakody, Dona M P, Wishart, Justin, Stegeman, Inge, Eikelboom, Robert, Moyle, Thomas C, Yiannos, Jessica M, Goodman-Simpson, Jack James, Almeida, Osvaldo P, MS KNO, Brain, Jayakody, Dona M P, Wishart, Justin, Stegeman, Inge, Eikelboom, Robert, Moyle, Thomas C, Yiannos, Jessica M, Goodman-Simpson, Jack James, and Almeida, Osvaldo P

Published
2022

41. Neoproterozoic orogenesis in south-eastern South America - An examination of pre-orogenic rifting, sedimentation, and mountain building processes recorded in the Dom Feliciano Belt

Author

Percival, Jack James and Konopásek, Jiří

Subjects
VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Tektonikk: 463, VDP::Mathematics and natural science: 400::Geosciences: 450::Tectonics: 463
Abstract

The Dom Feliciano Belt records the convergence between multiple South American and African cratonic bodies during the Neoproterozoic, and forms part of the larger South Atlantic Neoproterozoic Orogenic System (SANOS). Studying the evolution of the Dom Feliciano Belt allows the development of tectonic models spanning the time from pre-orogenic rifting to orogenesis, and the information recorded in any one part of the belt can have implications for the entire system. The nature of orogenesis in the SANOS has been strongly debated in recent years, with the contention hinging on the timing of convergence and the presence or absence of long-lived subduction prior to collision. This work focuses on the Kaoko–Dom Feliciano–Gariep belts, which comprise the southern part of the SANOS. Supracrustal metasedimentary rocks in the foreland position of the Dom Feliciano Belt (the Schist Belt) record the entire duration of orogenesis from pre-orogenic rifting to metamorphism and thrusting related to early convergence and crustal thickening. However, there are currently little to no constraints on the timing or conditions of these major tectonic events. The aim of this work is to understand the tectonic context and evolution of the Kaoko–Dom Feliciano–Gariep orogenic system by using a combination of methods including structural geology, geochronology, and phase equilibrium modelling. This work is divided into three papers, focussing on the Dom Feliciano Belt foreland in Santa Catarina, Brazil (Papers I & II), and in Uruguay (Paper III). The results from Paper I show that the protolith of the Schist Belt can be correlated along the majority of the Dom Feliciano Belt, as well as across the Atlantic Ocean in the Kaoko Belt, indicating close proximity between the South American (Luis Alves–Nico Pérez) and African (Congo and Kalahari) cratons at the onset of sedimentation and rifting. The results from Papers II & III show that early metamorphism in the foreland and hinterland, driven by crustal thickening and subsequent exhumation, was coeval, occurring between ca. 660–640 Ma. We interpret this as the earliest record of orogenesis in the system. The results from Paper III show that a second major transpressive event from ca. 580 Ma resulted in further metamorphism and deformation in the southern Dom Feliciano Belt foreland, coeval with transpression in the eastern part of the system in the Kaoko and Gariep Belts. The results of this study indicate an intracontinental rift or back-arc rift setting for the Kaoko–Dom Feliciano–Gariep system prior to orogenesis.

Published
2022

42. Tectono-Metamorphic Evolution of the Northern Dom Feliciano Belt Foreland, Santa Catarina, Brazil: Implications for Models of Subduction-Driven Orogenesis

Author

Jack James Percival, Jiří Konopásek, Robert Anczkiewicz, Morgan Ganerød, Jiří Sláma, Roberto Sacks Campos, and Maria de Fátima Bitencourt

Subjects
Geophysics, Geochemistry and Petrology
Abstract

The Dom Feliciano Belt in southern Brazil and Uruguay represents the western half of a Neoproterozoic orogenic belt located in the southern portion of the South Atlantic Neoproterozoic Orogenic System. Current interpretations are divided as to the nature of orogenesis in this belt, in part owing to lacking geochronological constraints. Metamorphosed and deformed supracrustal sequences of the Brusque Complex in the northern Dom Feliciano Belt, representing part of the orogenic foreland, record the onset and duration of crustal thickening. Structural analysis and pressure–temperature estimates indicate that the complex reached peak regional metamorphic conditions of 540–570°C and 5.5–6.7 kbar during thrusting and burial, consistent with orogenic metamorphism and early crustal thickening. Garnet–whole rock Lu–Hf and Sm–Nd isochron ages date this event to between circa 660–650 Ma. Ar–Ar dating of mica suggests thrust-controlled exhumation and partial cooling by circa 635 Ma, and that localised deformation occurred into the late Ediacaran. Our results show that the orogenic foreland reached metamorphic conditions typical for crustal thickening 20–30 million years prior to the onset of massive magmatic activity in the hinterland. Such a delay is typical of hot, internal parts of orogens, which supports interpretations that hinterland magmatism in the northern Dom Feliciano Belt represents post-collisional magmatism and not arc magmatism above a subduction zone. Instead, we suggest that orogenesis in the northern Dom Feliciano Belt was initiated by rift-basin inversion driven by far-field forces transmitted through the crust in an intracontinental rift or back-arc rift setting.

Published
2022

44. Protein over-expression in Escherichia coli triggers adaptation analogous to antimicrobial resistance

Author

Andy Koranteng, Tahmina Rahman, Jack James, Benjamin Yarnall, Jane Gibson, and Declan A. Doyle

Subjects
Programmed cell death, lcsh:QR1-502, Bioengineering, medicine.disease_cause, Antimicrobial resistance, Applied Microbiology and Biotechnology, lcsh:Microbiology, 03 medical and health sciences, Antibiotic resistance, Drug Resistance, Bacterial, medicine, Escherichia coli, Integral membrane protein, 030304 developmental biology, 0303 health sciences, Microbial Viability, 030306 microbiology, Chemistry, Research, Escherichia coli Proteins, Computational Biology, Membrane Proteins, Gene Expression Regulation, Bacterial, Adaptation, Physiological, Cell loss, Anti-Bacterial Agents, Protein over-expression, Biochemistry, Mutation, Over expression, BL21(DE3), Target protein, Adaptation, Biotechnology
Abstract

Background The E. coli pET system is the most widely used protein over-expression system worldwide. It relies on the assumption that all cells produce target protein and it is generally believed that integral membrane protein (IMP) over-expression is more toxic than their soluble counterparts. Results Using GFP-tagged proteins, high level over-expression of either soluble or IMP targets results in > 99.9% cell loss with survival rate of only Conclusions We demonstrate that it is the act of high-level over-expression of exogenous proteins in E. coli that sets in motion a chain of events leading to > 99.9% cell death. These results redefine our understanding of protein over-production and link it to the adaptive survival response seen in the development of antimicrobial resistance.

Published
2021

45. Palatability Enhancement Potential of

Author

David, Terrey, Jack, James, Ivan, Tankovski, Monika, Dalim, Michel, van Spankeren, Arpita, Chakraborty, Eric, Schmitt, and Aman, Paul

Subjects
Conservation of Natural Resources, Protein Hydrolysates, Diptera, Communication, Decapodiformes, Aquaculture, Animal Feed, free amino acids, Arthropod Proteins, Diet, Food Preferences, Penaeidae, Solubility, palatability, Larva, Animals, Humans, Insect Proteins, insect, short chain peptides, Amino Acids, Essential, Dietary Proteins, Litopenaeus vannamei, Euphausiacea, protein hydrolysate
Abstract

Marine feed ingredients derived from cephalopods (e.g., squid) and crustaceans (e.g., krill) are commercially used to improve the palatability of shrimp diets. Increase in global demand for shrimps has resulted in overfishing of these marine organisms and is a matter of concern. Insect protein hydrolysate could be a sustainable alternative for the possible replacement of these marine feed ingredients. During this study, four formulations: diet A (control: not containing any palatability enhancer), diet B (containing squid meal and krill oil), diet C (containing 1% insect protein hydrolysate), and diet D (containing 2% insect protein hydrolysate) were tested for (1) time required by first subject to begin feeding (time to strike) and (2) palatability in Litopenaeus vannamei. Additionally, the chemical composition of all four diet formulations was also analyzed. Results indicate that all diets had similar crude composition. The major essential amino acids in all diets were leucine and lysine, whereas eicosapentaenoic acid was the major omega-3 fatty acid in all diets. There were no significant differences between the mean time to strike for all the tested formulations. Palatability of tested formulations was found in the following order: diet D > diet C > diet B = diet A (p < 0.05), indicating that addition of squid meal and krill oil has no effect on palatability in comparison to control, whereas inclusion of insect protein hydrolysates significantly improves the palatability of formulations. Palatability enhancement potential of insect protein hydrolysate could be attributed to the high free amino acid content and water solubility in comparison to squid meal.

Published
2020

47. Maternal temperature in emergency caesarean section (MATES): an observational multicentre study

Author

Thorburn, P.T., primary, Monteiro, R., additional, Chakladar, A., additional, Cochrane, A., additional, Roberts, J., additional, Mark Harper, C., additional, Hughes, Natasha, additional, de las Casas, Ruth, additional, Long, Charlotte, additional, Skeoch, Chris, additional, Duckham, Emily, additional, Shippam, William, additional, Barnes, Lucy, additional, Madders, Rachel, additional, Campbell, Natasha, additional, Ali, Yousef, additional, Pararajasingam, Suji, additional, Stead, Richard, additional, Katayani, Katayani, additional, Jackson, James, additional, Nolan, Louise, additional, Kochar, Arun, additional, Ranns, Christopher, additional, Leong, Maria, additional, Jack, James, additional, Benoliel, Sophie, additional, Annamalai, Partha, additional, Picton, Graham, additional, Lunberg-Adams, Matt, additional, Lebbe, Asfir, additional, Lau, Julie, additional, Reddy, Anu, additional, Sen, Soumen, additional, Kanji, Rafiq, additional, Riccaboni, Anna, additional, Mackenzie, Matthew, additional, Macallan, Jennifer, additional, Mason, Rupert, additional, Martins, Nicole, additional, Hawksley, Sarah, additional, Wimble, Katie, additional, Ghafoor, Tahir, additional, Hallewell, Christopher, additional, Thomas, Janine, additional, Misquita, Lucia, additional, Walters, Michelle, additional, Krishnan, Priya, additional, McHale, Sean, additional, Ashpole, Keri, additional, George, Richard, additional, Graham, George, additional, Hudsmith, Jonny, additional, Way, Mark, additional, Armstrong, Sarah, additional, Burwell, David, additional, Iossifidis, Francoise, additional, Uncles, David, additional, Fludder, Vanessa, additional, and Bate, Tom, additional

Published
2021
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48. A new mathematical interpretation of disordered nanoscale material systems for computational modelling

Author

Jack James Tyson, Tasmiat Rahman, and Stuart A. Boden

Subjects
Work (thermodynamics), Field (physics), Computer science, Nanowire, General Physics and Astronomy, 01 natural sciences, Ray, Finite element method, 010305 fluids & plasmas, Set (abstract data type), Hardware and Architecture, 0103 physical sciences, Statistical physics, 010306 general physics, Nanoscopic scale, Microscale chemistry
Abstract

As the era of microscale technologies becomes increasingly overcome by that of the nanoscale, an ever-increasing emphasis on the accurate modelling of such scaled systems is apparent. This work explores the combination of the finite element method with a new set of statistical algorithms to model the optical properties of disordered nanoscale morphologies. A silicon surface textured with a random distribution of nanowires is created to simulate, as an example study, how it responds to incident light. By averaging over many iterations of the model in which the structural parameters are varied around average values, a good match to experiment is achieved, showcasing an error as low as 1.34% in magnitude against measured data. This research introduces a fresh computational approach to simulating heterogeneous material structures widely applicable for modelling across the field of nanotechnology.

Published
2020

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