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2. Quantitative Methods for Optimizing Patient Outcomes in Liver Transplantation

Author

Al-Bahou, Raja, Bruner, Julia, Moore, Helen, and Zarrinpar, Ali

Subjects
Quantitative Biology - Other Quantitative Biology, 92B
Abstract

Liver transplantation continues to be the gold standard for treating patients with end-stage liver diseases. However, despite the huge success of liver transplantation in improving patient outcomes, long term graft survival continues to be a major problem. The current clinical practice in the management of liver transplant patients is centered around immunosuppressive multidrug regimens. Current research has been focusing on phenotypic personalized medicine as a novel approach in the optimization of immunosuppression, a regressional math modeling focusing on individual patient dose and response using specific markers like transaminases. A prospective area of study includes the development of a mechanistic computational math modeling for optimizing immunosuppression to improve patient outcomes and increase long-term graft survival by exploring the intricate immune/drug interactions to help us further our understanding and management of medical problems like transplants, autoimmunity, and cancer therapy. Thus, by increasing long-term graft survival, the need for redo transplants will decrease, which will free up organs and potentially help with the organ shortage problem promoting equity and equal opportunity for transplants, as well as decreasing the medical costs associated with additional testing and hospital admissions. Although long-term graft survival remains challenging, computational and quantitative methods have led to significant improvements. In this article, we review recent advances and remaining opportunities. We focus on the following topics: donor organ availability and allocation with a focus on equity, monitoring of patient and graft health, and optimization of immunosuppression dosing., Comment: 2 figures, including a graphical abstract

Published
2023

5. Determining Optimal Combination Regimens for Patients with Multiple Myeloma

Author

Aghaee, Mahya, Ledzewicz, Urszula, Robbins, Michael, Bezman, Natalie, Cho, Hearn Jay, and Moore, Helen

Subjects
Mathematics - Optimization and Control
Abstract

While many novel therapies have been approved in recent years for treating patients with multiple myeloma, there is still no established curative regimen, especially for patients with high risk disease. In this work, we use a mathematical modeling approach to determine combination therapy regimens that maximize healthy lifespan for patients with multiple myeloma. We start with a model of ordinary differential equations for the underlying disease and immune dynamics, which was presented and analyzed previously. We add the effects of three therapies to the model: pomalidomide, dexamethasone, and elotuzumab. We consider multiple approaches to optimizing combinations of these therapies. We find that optimal control combined with approximation outperforms other methods, in that they can quickly produce a combination regimen that is clinically-feasible and near-optimal. Implications of this work can be used to optimize doses and advance the scheduling of drugs.

Published
2022

15. Relationships after stroke : couples' shared and individual perspectives

Author

Moore, Helen

Subjects
616.8, BF Psychology
Abstract

Stroke is a leading cause of disability worldwide, necessitating care from loved ones. Couple outcomes after stroke demonstrate heterogeneity, with impacts of stroke on relationships remaining poorly understood. Most stroke research takes place with survivors and carers individually. Where research is dyadic, joint or individual interviews are often chosen, thus exploring either co-construction or individual constructions of stroke and relationships. This dyadic, qualitative study explored five couples' shared and individual perspectives on stroke and relationships and their impact, a mean of eight years post-stroke. Five joint and ten individual, semi-structured interviews were analysed using Interpretative Phenomenological Analysis. A narrative surrounding evolution of couples' relationships from the past to the present emerged, however narratives regarding the future were absent. Dyads co-constructed narratives of their relational past pre-stroke. Stroke was a life-changing event, leaving couples questioning self, other, and couple identity. Shifts in relational dynamics ensued, with dyads having divergent perspectives on issues such as intimacy. To manage uncertainty and changed dynamics, and to protect their partners, dyads concealed aspects of their post-stroke experience. However, this risked dyads remaining on different pages and navigating a non-negotiated, uncertain future. In conclusion, stroke results in individual and dynamic shifts within relationships, creating uncertainty and divergences in perspective, leaving couples questioning who they are and where they are going. Support from services is essential in helping couples to navigate these challenges.

Published
2020

20. Histologic and Quality Assessment of Genotype-Tissue Expression (GTEx) Research Samples: A Large Postmortem Tissue Collection

Author

Sobin, Leslie, primary, Barcus, Mary, additional, Branton, Philip A., additional, Engel, Kelly B., additional, Keen, Judy, additional, Tabor, David, additional, Ardlie, Kristin G., additional, Greytak, Sarah R., additional, Roche, Nancy, additional, Luke, Brian, additional, Vaught, Jim, additional, Guan, Ping, additional, and Moore, Helen M., additional

Published
2024
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23. Genetic effects on gene expression across human tissues

Author

Aguet, François, Brown, Andrew A, Castel, Stephane E, Davis, Joe R, He, Yuan, Jo, Brian, Mohammadi, Pejman, Park, YoSon, Parsana, Princy, Segrè, Ayellet V, Strober, Benjamin J, Zappala, Zachary, Cummings, Beryl B, Gelfand, Ellen T, Hadley, Kane, Huang, Katherine H, Lek, Monkol, Li, Xiao, Nedzel, Jared L, Nguyen, Duyen Y, Noble, Michael S, Sullivan, Timothy J, Tukiainen, Taru, MacArthur, Daniel G, Getz, Gad, Addington, Anjene, Guan, Ping, Koester, Susan, Little, A Roger, Lockhart, Nicole C, Moore, Helen M, Rao, Abhi, Struewing, Jeffery P, Volpi, Simona, Brigham, Lori E, Hasz, Richard, Hunter, Marcus, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F, Lonsdale, John T, McDonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Bryan, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A, Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A, Gillard, Bryan M, Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T, Jewell, Scott D, Montroy, Robert G, Rohrer, Daniel C, Valley, Dana, Mash, Deborah C, Davis, David A, Sobin, Leslie, Barcus, Mary E, Branton, Philip A, Abell, Nathan S, Balliu, Brunilda, Delaneau, Olivier, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Han, Buhm, He, Amy Z, Hormozdiari, Farhad, Li, Xin, Liu, Boxiang, Kang, Eun Yong, McDowell, Ian C, Ongen, Halit, Palowitch, John J, Peterson, Christine B, Quon, Gerald, Ripke, Stephan, Saha, Ashis, Shabalin, Andrey A, Shimko, Tyler C, Sul, Jae Hoon, Teran, Nicole A, Tsang, Emily K, Zhang, Hailei, Zhou, Yi-Hui, Bustamante, Carlos D, Cox, Nancy J, and Guigó, Roderic

Subjects
Human Genome, Genetics, Biotechnology, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Aetiology, Underpinning research, Generic health relevance, Alleles, Chromosomes, Human, Disease, Female, Gene Expression Profiling, Gene Expression Regulation, Genetic Variation, Genome, Human, Genotype, Humans, Male, Organ Specificity, Quantitative Trait Loci, GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, Lead analysts:, Laboratory, Data Analysis &Coordinating Center (LDACC):, NIH program management:, Biospecimen collection:, Pathology:, eQTL manuscript working group:, General Science & Technology
Abstract

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

Published
2017

24. A thematic analysis of UK healthy planning frameworks and tools designed to support the inclusion of health in urban planning

Author

De La Haye, Amber, Gow, Ruth, Lake, Amelia A., Ball, Caitlin, van Herk, Sebastiaan, Rofin Serra, Marta, Jones, Andy, Chang, Michael, and Moore, Helen J.

Abstract

ABSTRACTWhile there are a number of frameworks and tools available to support the integration of health into urban planning, they have not been systematically evaluated. With health increasingly on the planning agenda, it is crucial to understand the role frameworks play and how they can best be designed/used to support the integration of health in urban planning. We conducted a thematic analysis, drawing on desk research and semi-structured interviews, of seven UK urban planning frameworks and tools designed to integrate health considerations into planning, to identify information on the challenges, considerations, and best practices of framework design and implementation. Through thematic analysis, shared challenges, best practices, and considerations for success were identified in the following themes: framework design and conceptualisation, framework recommendations and content, implementation outcomes and impact, framework evaluations, and general challenges. Main findings included the need to consult all relevant stakeholders, especially communities, developers, and local authorities, to design a useful framework. Simple, clear recommendations aligning with relevant policies around place and health were useful for enabling framework take-up. While anecdotally frameworks were found to facilitate conversations with local communities, data on framework impact was lacking, suggesting better evaluation of framework use would be beneficial in future.

Published
2024
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25. Within-day energy balance and symptoms of Relative Energy Deficiency in Sport (RED-S) in recreational female athletes

Author

Moore, Helen and Moore, Helen

Abstract

Relative Energy Deficiency in Sport (RED-S) is a syndrome whereby low energy availability (EA) causes downregulation of physiological processes, resulting in health and performance consequences. Energy availability is normally calculated over 24-hours, however this may conceal energy deficient periods in the day. The present study combined questionnaire, lab, and field-based measures to assess low EA prevalence and to establish whether within-day energy balance (WDEB) was associated with RED-S symptoms in recreationally active (4-6 hours per week moderate-vigorous physical activity), premenopausal women. Seven-day food and training diaries alongside accelerometry and heart rate were used to estimate 24-hour energy availability and hourly WDEB. The largest within-day energy surplus and deficit, the number of hours spent in a surplus and deficit, and the maximum number of consecutive hours in each, were calculated daily and averaged across the 7-days. Body composition, quantitative ultrasound of bone, hematocrit, hemoglobin, total cholesterol, maximum voluntary contraction of the knee during flexion and extension, VO2peak and lactate profile were all assessed. Questionnaires assessed menstrual function, psychological, immunological, and gastrointestinal health, disordered eating, and injury history. Of the 16 participants (mean ±SD; age = 27 ±6 yrs., height = 1.67.0 ±0.05 m, mass = 63.5 ±8.2 kg), 88% did not have adequate energy availability (< 45 kcal∙kg-1FFM∙day-1¬). Low energy availability (< 30 kcal∙kg-1FFM∙day-1¬) was seen in 13% of participants, and 75% had subclinical energy availability (30-45 kcal∙kg-1FFM∙day-1¬), typically associated with weight loss. Correlational analysis between WDEB and RED-S symptoms was done accounting for 24-hour energy availability. Menstrual health was negatively correlated with mean largest energy surplus (p = 0.022). Body fat percentage was positively correlated with total time (p = 0.048), time per day (p = 0.003) and consecutive

Published
2024

30. A Mathematical Model for Tumor–Immune Dynamics in Multiple Myeloma

Author

Gallaher, Jill, Larripa, Kamila, Ledzewicz, Urszula, Renardy, Marissa, Shtylla, Blerta, Tania, Nessy, White, Diana, Wood, Karen, Zhu, Li, Passey, Chaitali, Robbins, Michael, Bezman, Natalie, Shelat, Suresh, Cho, Hearn Jay, Moore, Helen, Lauter, Kristin, Series Editor, Radunskaya, Ami, editor, Segal, Rebecca, editor, and Shtylla, Blerta, editor

Published
2018
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31. A perfectly imperfect engine: Utilizing the digital twin paradigm in pulmonary hypertension.

Author

Walker, Melody, Moore, Helen, Ataya, Ali, Pham, Ann, Corris, Paul A., Laubenbacher, Reinhard, and Bryant, Andrew J.

Subjects
*DIGITAL twins, *PULMONARY arterial hypertension, *CALCIUM antagonists, *INDIVIDUALIZED medicine, *THERAPEUTICS, *PULMONARY hypertension
Abstract

Pulmonary hypertension (PH) is a severe medical condition with a number of treatment options, the majority of which are introduced without consideration of the underlying mechanisms driving it within an individual and thus a lack of tailored approach to treatment. The one exception is a patient presenting with apparent pulmonary arterial hypertension and shown to have vaso‐responsive disease, whose clinical course and prognosis is significantly improved by high dose calcium channel blockers. PH is however characterized by a relative abundance of available data from patient cohorts, ranging from molecular data characterizing gene and protein expression in different tissues to physiological data at the organ level and clinical information. Integrating available data with mechanistic information at the different scales into computational models suggests an approach to a more personalized treatment of the disease using model‐based optimization of interventions for individual patients. That is, constructing digital twins of the disease, customized to a patient, promises to be a key technology for personalized medicine, with the aim of optimizing use of existing treatments and developing novel interventions, such as new drugs. This article presents a perspective on this approach in the context of a review of existing computational models for different aspects of the disease, and it lays out a roadmap for a path to realizing it. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Process evaluation of a primary care‐based type 2 diabetes remission project in the North East of England.

Author

Boocock, Ruth C., Moore, Helen J., Lake, Amelia A., and Haste, Anna

Subjects
*EVALUATION of human services programs, *PATIENT decision making, *RESEARCH methodology, *ATTITUDE (Psychology), *CHANGE, *INTERVIEWING, *TYPE 2 diabetes, *PRIMARY health care, *CONCEPTUAL structures, *INTERPROFESSIONAL relations, *WEIGHT loss, *DESCRIPTIVE statistics, *THEMATIC analysis, *JUDGMENT sampling, *COVID-19 pandemic, *DISEASE remission
Abstract

A type 2 diabetes remission project, Remission in Diabetes (REMI.D), funded by Sport England, was developed by stakeholders based in the North East of England and begun in early 2020. This local delivery pilot sought to tackle health inequalities by working with multiple organisations to demonstrate a way of scaling up an effective type 2 diabetes remission strategy which included both physical activity and dietary components. The intended delivery of the original project was impacted by the COVID‐19 pandemic and changes were made to the project delivery in 2022. The aim of this process evaluation was to learn from the reactive decisions taken by stakeholders which altered the REMI.D project in response to the COVID‐19 pandemic. Twelve stakeholders (from local authorities, secondary care, universities, NHS England commissioning, Diabetes UK, Sport England, Everyone Active and Active Partnerships) involved in the design and delivery of the intervention took part in a semi‐structured interview lasting up to 60 min. Interviews were recorded and transcribed verbatim. Thematic analysis used the pre‐determined 'core content' themes from the Medical Research Council and National Institute for Health Research framework for developing and evaluating complex interventions. Three topics for discussion emerged as follows: (a) lack of effective collaboration, (b) perception of change and (c) scalability of the intervention. Hierarchy within the stakeholder group initially hampered collaboration. Change was reactive as a result of the COVID‐19 pandemic. Project changes reduced project sustainability and scalability but offered valuable learning about the need for explicit project theory for partnership working, co‐production with service users and project flexibility for long‐term health behaviour change. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Language Policies as Virtual Realities: Two Australian Examples.

Author

Moore, Helen

Abstract

This chapter uses the insights of Dorothy Smith and Anna Yeatman, both feminist scholars, to explore the nature of policy formation through two examples from Australia. Smith and Yeatman argue that all description is both biased and interested. The article documents how the values of pluralism and equity were not served well by Australian policy developments in the early 1990s. It also uses case study material to analyze this language policy. Why and how Australian language policy changed so significantly is also discussed. The policies in question are the National Policy on Languages and its replacement by the Australian Language and Literacy Policy. It is argued that the later policy did little but eliminate the previous political commitment to pluralism. (Contains numerous scholarly references and 13 notes.) (KFT)

Published
2000

46. Race, rurality & respectability : English villagers, Eastern European migrants and the intersection of whiteness and class in rural England

Author

Moore, Helen

Subjects
305.8
Abstract

In this research project, which is based on 12 months of residential ethnographic fieldwork, I explore the intersection of whiteness and social class in a rural English village. Drawing on a body of literature known as 'critical whiteness studies' I bring attention to the presence of race in this village location, and argue that although whiteness is largely invisible to the white English village residents, it nonetheless shapes their daily lives in numerous and important ways. I analyse how village residents claim a sense of belonging in the rural Worcestershire village of 'Mayfield' through attachments to place, to history and to people, and how belonging is also secured by unconscious, banal and everyday performances of whiteness, EnglislU1ess and rurality. Here I adopt Pierre Bourdieu's (1984) notion of cultural capital to argue that although the residents of Mayfield are demographically diverse, what unites them is their 'commonsense' understandings of how to fit in with local social networks, 'respectable' ways of living, and the associated decorums of whiteness. I am particularly concerned with how white English village residents define their identity and belonging in opposition to white Eastern European migrant labourers who work on the village's horticultural farms. I argue that in securing their position of hegemonic whiteness, villagers draw upon finely-tuned class distinctions and a racist rhetoric of difference, which positions the migrants as a different 'shade' of white. The migrants have white skins, but without the necessary cultural capital, they are positioned by Mayfield residents as low-status Others who cannot be integrated into village life. While the primary focus of this research is the English villagers of Mayfield, I also incorporate the migrants' perspective. In Mayfield, Eastern European migrants are talked about but not talked-to; observed but not known. Therefore the inclusion of migrant narratives in my thesis is an attempt to address this imbalance.

Published
2013

47. 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, 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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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48. Adaptation of informal care relationships following Acquired Brain Injury

Author

Moore, Helen, Gillespie, Alex, and Wilson, J. T. Lindsay

Subjects
362.2, Acquired Brain Injury, intersubjectivity, joint activity, informal care, relationships, adaptation to illness/disability, Disability Living Allowance, Brain Injuries rehabilitation Great Britain, Brain Wounds and injuries Complications Great Britain
Abstract

The number of informal carers in the UK is rising, yet the dynamics of care within informal care relationships remain poorly understood. The present research examined adaptation of informal care relationships affected by Acquired Brain Injury. The research addresses four pairs of questions: (1a) Are there any disagreements and/or misunderstandings between carers and people with Acquired Brain Injury (PwABI) regarding carer identity? (1b) How can the pattern of divergences be explained? (2a) Are there any disagreements and/or misunderstandings between carers and PwABI regarding PwABI identity? (2b) How can the pattern of divergences be explained? (3a) What strategies do carers and PwABI use in collaboration on a joint task? (3b) Is the type of input provided by carers on the joint task comparable to scaffolding as described in the child development literature? (4a) What happens when carers and PwABI collaborate to fill in the Disability Living Allowance (DLA) claim form? (4b) Why do carers see more disability than PwABI when filling in the DLA form? Four mixed-method data sets were used to answer these questions: (1) numerical ratings given by PwABI and carers to map out convergences and divergences (2) videos of discussions between participants and researcher during rating tasks (3) videos of carers and PwABI engaging in a joint task - planning inviting a friend or relative round for a meal and (4) videos of carers and PwABI filling in part of the DLA claim form. All data was collected from the same 28 PwABI/carer dyads who were two or more years post injury. Chapter 4 addresses questions 1a and 1b. Carers’ and PwABIs’ perspective ratings revealed a number of disagreements regarding carer identity. Carers perceived themselves negatively compared to their partners’ view of them. Regarding question 1b, carers feel negatively about themselves due to difficulties in the transition to the role of ‘carer’. They experience a lack of recognition for this caring role as a result of concealing the burden of care. Carers require more long term support from health services to help them achieve recognition for their role, such as facilitating attendance at support groups. Chapter 5 addresses questions 2a and 2b. Carers’ and PwABIs’ perspective ratings revealed only one disagreement and corresponding misunderstanding regarding PwABI identity. Regarding question 2b, alignment was found between the perspectives of carers and PwABI regarding PwABI due to the relational rating method used. It is carer identity which is the source of most divergences of perspective, not PwABI identity as commonly assumed. Using a relational rating method shows promise as a tool to explore perspectives as it treats all viewpoints as equal and avoids pathologising the perspective of PwABI. Chapter 6 addresses questions 3a and 3b. Analysis of strategies shows that completing a joint task is a collaborative process. Carers direct the background of the task but PwABI are in charge of the foreground, making task decisions. However, carers dominate the process and control where and how PwABI contribute. Regarding question 3b, the interaction meets the criteria for scaffolding in the strategies chosen and the flexibility of collaboration. However, removal of supports is often an unrealistic goal, leading to frustration in carers. Examination of processes of collaboration has elucidated the strategies used by carers and PwABI and can enhance theoretical discussion of the applicability of the scaffolding metaphor for a cognitively impaired adult sample. Chapter 7 address questions 4a and 4b. Disagreements were frequent when completing the DLA form. Contestations were almost exclusively in the direction of carers seeing greater disability than PwABI. Regarding question 4b, carers see greater disability due to the communication required to complete the form. Dyads are forced to confront disability, a pattern of interaction they avoid in everyday life. Carers marginalise PwABI point of view and position themselves as ‘expert’ on the PwABI. Differences in frames of reference regarding audience, aim and scope lead carers to maximise the disability and PwABI to minimise this. The impact of completing complex forms on relationships and identity needs to be considered during development of disability benefit assessment methods. A relational approach which studies both halves of informal care partnerships simultaneously allows us to go beyond outcomes of ABI and affords a greater understanding of processes of adaptation.

Published
2012

49. The Biospecimen Preanalytical Variables Program A Multiassay Comparison of Effects of Delay to Fixation and Fixation Duration on Nucleic Acid Quality

Author

Carithers, Latarsha J., Agarwal, Rachana, Guan, Ping, Odeh, Hana, Sachs, Michael C., Engel, Kelly B., Greytak, Sarah R., Barcus, Mary, Soria, Conrado, Lih, Chih-Jian "Jason", Williams, Mickey P., Branton, Philip A., Sobin, Leslie, Fombonne, Benjamin, Bocklage, Therese, Andry, Chris, Duffy, Elizabeth R., Sica, Gabriel, Dhir, Rajiv, Jewell, Scott, Roche, Nancy, and Moore, Helen M.

Subjects
Transcription (Genetics), Formaldehyde, RNA, Nucleic acids, DNA, Genetic research, Ovarian tumors, Polymerase chain reaction, Cancer, Nucleotides, Tumors, Health, University of Pittsburgh, The University of New Mexico, Emory University
Abstract

* Context.--Despite widespread use of formalin-fixed, paraffin-embedded (FFPE) tissue in clinical and research settings, potential effects of variable tissue processing remain largely unknown. Objective.--To elucidate molecular effects associated with clinically relevant preanalytical variability, the National Cancer Institute initiated the Biospecimen Preanalytical Variables (BPV) program. Design.--The BPV program, a well-controlled series of systematic, blind and randomized studies, investigated whether a delay to fixation (DTF) or time in fixative (TIF) affects the quantity and quality of DNA and RNA isolated from FFPE colon, kidney, and ovarian tumors in comparison to case-matched snap-frozen controls. Results.--DNA and RNA yields were comparable among FFPE biospecimens subjected to different DTF and TIF time points. DNA and RNA quality metrics revealed assay--and time point-specific effects of DTF and TIF. A quantitative reverse transcription-polymerase chain reaction (qRTPCR) assay was superior when assessing RNA quality, consistently detecting differences between FFPE and snap-frozen biospecimens and among DTF and TIF time points. RNA Integrity Number and [DV.sub.200] (representing the percentage of RNA fragments longer than 200 nucleotides) displayed more limited sensitivity. Differences in DNA quality (Q-ratio) between FFPE and snap-frozen biospecimens and among DTF and TIF time points were detected with a qPCR-based assay. Conclusions.--DNA and RNA quality may be adversely affected in some tumor types by a 12-hour DTF or a TIF of 72 hours. Results presented here as well as those of additional BPV molecular analyses underway will aid in the identification of acceptable delays and optimal fixation times, and quality assays that are suitable predictors of an FFPE biospecimen's fit-for-purpose. (Arch Pathol Lab Med. 2019;143:1106-1118; doi: 10.5858/arpa.2018-0172-OA), Formalin fixation and paraffin embedding, first developed for histologic diagnosis more than a century ago, is used for tissue preservation by medical institutions around the world. Despite analytical challenges, molecular [...]

Published
2019
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50. Mathematical Modeling of Tumor Cell Proliferation Kinetics and Label Retention in a Mouse Model of Lung Cancer

Author

Zheng, Yanyan, Moore, Helen, Piryatinska, Alexandra, Solis, Trinidad, and Sweet-Cordero, E Alejandro

Subjects
Lung, Bioengineering, Cancer, Lung Cancer, Animals, Bromodeoxyuridine, Cell Cycle, Cell Line, Tumor, Cell Proliferation, Fluorescent Dyes, Humans, Immunohistochemistry, Kinetics, Lung Neoplasms, Mice, Mice, Knockout, Models, Biological, Neoplasms, Experimental, Organic Chemicals, Proto-Oncogene Proteins p21(ras), Time Factors, Transplantation, Heterologous, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Slowly cycling tumor cells that may be present in human tumors may evade cytotoxic therapies, which tend to be more efficient at destroying cells with faster growth rates. However, the proportion and growth rate of slowly cycling tumor cells is often unknown in preclinical model systems used for drug discovery. Here, we report a quantitative approach to quantitate slowly cycling malignant cells in solid tumors, using a well-established mouse model of Kras-induced lung cancer (Kras(G12D/+)). 5-Bromo-2-deoxyuridine (BrdUrd) was administered to tumor-bearing mice, and samples were collected at defined times during pulse and chase phases. Mathematical and statistical modeling of the label-retention data during the chase phase supported the existence of a slowly cycling label-retaining population in this tumor model and permitted the estimation of its proportion and proliferation rate within a tumor. The doubling time of the slowly cycling population was estimated at approximately 5.7 weeks, and this population represented approximately 31% of the total tumor cells in this model system. The mathematical modeling techniques implemented here may be useful in other tumor models where direct observation of cell-cycle kinetics is difficult and may help evaluate tumor cell subpopulations with distinct cell-cycling rates.

Published
2013

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